climate model experiments: Topics by Science.gov

Sample records for climate model experiments

Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.
Development of probabilistic regional climate scenario in East Asia

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Ishizaki, N. N.

2015-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in East Asia (CORDEX-EA and Japan), the probability distribution of 2m air temperature was estimated by using developed regression model. The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. Probabilistic climate information in present (1969-1998) and future (2069-2098) climate was developed using CMIP3 SRES A1b scenarios 21 models and the observation data (CRU_TS3.22 & University of Delaware in CORDEX-EA, NIAES AMeDAS mesh data in Japan). The prototype of probabilistic information in CORDEX-EA and Japan represent the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Appropriate combination of statistical methods and optimization of climate ensemble experiments using multi-General Circulation Models (GCMs) and multi-regional climate models (RCMs) ensemble downscaling experiments are investigated.
Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

Watanabe, S.; Kim, H.; Utsumi, N.

2017-12-01

This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.
Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less
Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

DOE PAGES

Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.; ...

2015-06-01

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less
The PMIP4 contribution to CMIP6 - Part 1: Overview and over-arching analysis plan

NASA Astrophysics Data System (ADS)

Kageyama, Masa; Braconnot, Pascale; Harrison, Sandy P.; Haywood, Alan M.; Jungclaus, Johann H.; Otto-Bliesner, Bette L.; Peterschmitt, Jean-Yves; Abe-Ouchi, Ayako; Albani, Samuel; Bartlein, Patrick J.; Brierley, Chris; Crucifix, Michel; Dolan, Aisling; Fernandez-Donado, Laura; Fischer, Hubertus; Hopcroft, Peter O.; Ivanovic, Ruza F.; Lambert, Fabrice; Lunt, Daniel J.; Mahowald, Natalie M.; Peltier, W. Richard; Phipps, Steven J.; Roche, Didier M.; Schmidt, Gavin A.; Tarasov, Lev; Valdes, Paul J.; Zhang, Qiong; Zhou, Tianjun

2018-03-01

This paper is the first of a series of four GMD papers on the PMIP4-CMIP6 experiments. Part 2 (Otto-Bliesner et al., 2017) gives details about the two PMIP4-CMIP6 interglacial experiments, Part 3 (Jungclaus et al., 2017) about the last millennium experiment, and Part 4 (Kageyama et al., 2017) about the Last Glacial Maximum experiment. The mid-Pliocene Warm Period experiment is part of the Pliocene Model Intercomparison Project (PlioMIP) - Phase 2, detailed in Haywood et al. (2016).The goal of the Paleoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to different climate forcings for documented climatic states very different from the present and historical climates. Through comparison with observations of the environmental impact of these climate changes, or with climate reconstructions based on physical, chemical, or biological records, PMIP also addresses the issue of how well state-of-the-art numerical models simulate climate change. Climate models are usually developed using the present and historical climates as references, but climate projections show that future climates will lie well outside these conditions. Palaeoclimates very different from these reference states therefore provide stringent tests for state-of-the-art models and a way to assess whether their sensitivity to forcings is compatible with palaeoclimatic evidence. Simulations of five different periods have been designed to address the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6): the millennium prior to the industrial epoch (CMIP6 name: past1000); the mid-Holocene, 6000 years ago (midHolocene); the Last Glacial Maximum, 21 000 years ago (lgm); the Last Interglacial, 127 000 years ago (lig127k); and the mid-Pliocene Warm Period, 3.2 million years ago (midPliocene-eoi400). These climatic periods are well documented by palaeoclimatic and palaeoenvironmental records, with climate and environmental changes relevant for the study and projection of future climate changes. This paper describes the motivation for the choice of these periods and the design of the numerical experiments and database requests, with a focus on their novel features compared to the experiments performed in previous phases of PMIP and CMIP. It also outlines the analysis plan that takes advantage of the comparisons of the results across periods and across CMIP6 in collaboration with other MIPs.
Meeting the Next Generation Science Standards Through "Rediscovered" Climate Model Experiments

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2013-12-01

Since the Educational Global Climate Model (EdGCM) Project made its debut in January 2005, over 150 institutions have employed EdGCM software for a variety of uses ranging from short lab exercises to semester-long and year-long thesis projects. The vast majority of these EdGCM adoptees have been at the undergraduate and graduate levels, with few users at the K-12 level. The K-12 instructors who have worked with EdGCM in professional development settings have commented that, although EdGCM can be used to illustrate a number of the Disciplinary Core Ideas and connects to many of the Common Core State Standards across subjects and grade levels, significant hurdles preclude easy integration of EdGCM into their curricula. Time constraints, a scarcity of curriculum materials, and classroom technology are often mentioned as obstacles in providing experiences to younger grade levels in realistic climate modeling research. Given that the NGSS incorporates student performance expectations relating to Earth System Science, and to climate science and the human dimension in particular, we feel that a streamlined version of EdGCM -- one that eliminates the need to run the climate model on limited computing resources, and provides a more guided climate modeling experience -- would be highly beneficial for the K-12 community. This new tool currently under development, called EzGCM, functions through a browser interface, and presents "rediscovery experiments" that allow students to do their own exploration of model output from published climate experiments, or from sensitivity experiments designed to illustrate how climate models as well as the climate system work. The experiments include background information and sample questions, with more extensive notes for instructors so that the instructors can design their own reflection questions or follow-on activities relating to physical or human impacts, as they choose. An added benefit of the EzGCM tool is that, like EdGCM, it helps illustrate the process of doing research on a complex topic, in a way that builds upon earlier experiences in inquiry-based learning. By having students work through a multi-stage process that requires them to plan several steps ahead, through data processing, analysis and interpretation, they learn how to do research in addition to improving their understanding of climate change.
Lake Representations in Global Climate Models: An End-User Perspective

NASA Astrophysics Data System (ADS)

Rood, R. B.; Briley, L.; Steiner, A.; Wells, K.

2017-12-01

The weather and climate in the Great Lakes region of the United States and Canada are strongly influenced by the lakes. Within global climate models, lakes are incorporated in many ways. If one is interested in quantitative climate information for the Great Lakes, then it is a first principle requirement that end-users of climate model simulation data, whether scientists or practitioners, need to know if and how lakes are incorporated into models. We pose the basic question, how are lakes represented in CMIP models? Despite significant efforts by the climate community to document and publish basic information about climate models, it is unclear how to answer the question about lake representations? With significant knowledge of the practice of the field, then a reasonable starting point is to use the ES-DOC Comparator (https://compare.es-doc.org/ ). Once at this interface to model information, the end-user is faced with the need for more knowledge about the practice and culture of the discipline. For example, lakes are often categorized as a type of land, a counterintuitive concept. In some models, though, lakes are specified in ocean models. There is little evidence and little confidence that the information obtained through this process is complete or accurate. In fact, it is verifiably not accurate. This experience, then, motivates identifying and finding either human experts or technical documentation for each model. The conclusion from this exercise is that it can take months or longer to provide a defensible answer to if and how lakes are represented in climate models. Our experience with lake finding is that this is not a unique experience. This talk documents our experience and explores barriers we have identified and strategies for reducing those barriers.
CMIP5 Scientific Gaps and Recommendations for CMIP6

DOE PAGES

Stouffer, R. J.; Eyring, V.; Meehl, G. A.; ...

2017-01-23

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less
CMIP5 Scientific Gaps and Recommendations for CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stouffer, R. J.; Eyring, V.; Meehl, G. A.

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less
Low fidelity of CORDEX and their driving experiments indicates future climatic uncertainty over Himalayan watersheds of Indus basin

NASA Astrophysics Data System (ADS)

Hasson, Shabeh ul; Böhner, Jürgen; Chishtie, Farrukh

2018-03-01

Assessment of future water availability from the Himalayan watersheds of Indus Basin (Jhelum, Kabul and upper Indus basin—UIB) is a growing concern for safeguarding the sustainable socioeconomic wellbeing downstream. This requires, before all, robust climate change information from the present-day state-of-the-art climate models. However, the robustness of climate change projections highly depends upon the fidelity of climate modeling experiments. Hence, this study assesses the fidelity of seven dynamically refined (0.44° ) experiments, performed under the framework of the coordinated regional climate downscaling experiment for South Asia (CX-SA), and additionally, their six coarse-resolution driving datasets participating in the coupled model intercomparison project phase 5 (CMIP5). We assess fidelity in terms of reproducibility of the observed climatology of temperature and precipitation, and the seasonality of the latter for the historical period (1971-2005). Based on the model fidelity results, we further assess the robustness or uncertainty of the far future climate (2061-2095), as projected under the extreme-end warming scenario of the representative concentration pathway (RCP) 8.5. Our results show that the CX-SA and their driving CMIP5 experiments consistently feature low fidelity in terms of the chosen skill metrics, suggesting substantial cold (6-10 ° C) and wet (up to 80%) biases and underestimation of observed precipitation seasonality. Surprisingly, the CX-SA are unable to outperform their driving datasets. Further, the biases of CX-SA and of their driving CMIP5 datasets are higher in magnitude than their projected changes under RCP8.5—and hence under less extreme RCPs—by the end of 21st century, indicating uncertain future climates for the Indus Basin watersheds. Higher inter-dataset disagreements of both CMIP5 and CX-SA for their simulated historical precipitation and for its projected changes reinforce uncertain future wet/dry conditions whereas the CMIP5 projected warming is less robust owing to higher historical period uncertainty. Interestingly, a better agreement among those CX-SA experiments that have been obtained through downscaling different CMIP5 experiments with the same regional climate model (RCM) indicates the RCMs' ability of modulating the influence of lateral boundary conditions over a large domain. These findings, instead of suggesting the usual skill-based identification of 'reasonable' global or regional low fidelity experiments, rather emphasize on a paradigm shift towards improving their fidelity by exploiting the potential of meso-to-local scale climate models—preferably of those that can solely resolve global-to-local scale climatic processes—in terms of microphysics, resolution and explicitly resolved convections. Additionally, an extensive monitoring of the nival regime within the Himalayan watersheds will reduce the observational uncertainty, allowing for a more robust fidelity assessment of the climate modeling experiments.
Pliocene Model Intercomparison Project (PlioMIP): Experimental Design and Boundary Conditions (Experiment 2)

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Dowsett, H. J.; Robinson, M. M.; Stoll, D. K.; Dolan, A. M.; Lunt, D. J.; Otto-Bliesner, B.; Chandler, M. A.

2011-01-01

The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere only climate models. The second (Experiment 2) utilizes fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.
Pliocene Model Intercomparison Project (PlioMIP): experimental design and boundary conditions (Experiment 2)

USGS Publications Warehouse

Haywood, A.M.; Dowsett, H.J.; Robinson, M.M.; Stoll, D.K.; Dolan, A.M.; Lunt, D.J.; Otto-Bliesner, B.; Chandler, M.A.

2011-01-01

The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere-only climate models. The second (Experiment 2) utilises fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.
How does the sensitivity of climate affect stratospheric solar radiation management?

NASA Astrophysics Data System (ADS)

Ricke, K.; Rowlands, D. J.; Ingram, W.; Keith, D.; Morgan, M. G.

2011-12-01

If implementation of proposals to engineer the climate through solar radiation management (SRM) ever occurs, it is likely to be contingent upon climate sensitivity. Despite this, no modeling studies have examined how the effectiveness of SRM forcings differs between the typical Atmosphere-Ocean General Circulation Models (AOGCMs) with climate sensitivities close to the Coupled Model Intercomparison Project (CMIP) mean and ones with high climate sensitivities. Here, we use a perturbed physics ensemble modeling experiment to examine variations in the response of climate to SRM under different climate sensitivities. When SRM is used as a substitute for mitigation its ability to maintain the current climate state gets worse with increased climate sensitivity and with increased concentrations of greenhouse gases. However, our results also demonstrate that the potential of SRM to slow climate change, even at the regional level, grows with climate sensitivity. On average, SRM reduces regional rates of temperature change by more than 90 percent and rates of precipitation change by more than 50 percent in these higher sensitivity model configurations. To investigate how SRM might behave in models with high climate sensitivity that are also consistent with recent observed climate change we perform a "perturbed physics" ensemble (PPE) modelling experiment with the climateprediction.net (cpdn) version of the HadCM3L AOGCM. Like other perturbed physics climate modelling experiments, we simulate past and future climate scenarios using a wide range of model parameter combinations that both reproduce past climate within a specified level of accuracy and simulate future climates with a wide range of climate sensitivities. We chose 43 members ("model versions") from a subset of the 1,550 from the British Broadcasting Corporation (BBC) climateprediction.net project that have data that allow restarts. We use our results to explore how much assessments of SRM that use best-estimate models, and so near-median climate sensitivity, may be ignoring important contingencies associated with implementing SRM in reality. A primary motivation for studying SRM via the injection of aerosols in the stratosphere is to evaluate its potential effectiveness as "insurance" in the case of higher-than-expected climate response to global warming. We find that this is precisely when SRM appears to be least effective in returning regional climates to their baseline states and reducing regional rates of precipitation change. On the other hand, given the very high regional temperature anomalies associated with rising greenhouse gas concentrations in high sensitivity models, it is also where SRM is most effective in reducing rates of change relative to a no SRM alternative.
Hurricanes and Climate: the U.S. CLIVAR Working Group on Hurricanes

NASA Technical Reports Server (NTRS)

Walsh, Kevin; Camargo, Suzana J.; Vecchi, Gabriel A.; Daloz, Anne Sophie; Elsner, James; Emanuel, Kerry; Horn, Michael; Lim, Young-Kwon; Roberts, Malcolm; Patricola, Christina;

2015-01-01

While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. The idealized experiments of the Hurricane Working Group of U.S. CLIVAR, combined with results from other model simulations, have suggested relationships between tropical cyclone formation rates and climate variables such as mid-tropospheric vertical velocity. Systematic differences are shown between experiments in which only sea surface temperature is increases versus experiments where only atmospheric carbon dioxide is increased, with the carbon dioxide experiments more likely to demonstrate a decrease in numbers. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.

The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

NASA Astrophysics Data System (ADS)

Dessens, Olivier

2016-04-01

Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of analysing GCMs with the step-experiments. Acknowledgments: This work is supported by the FP7 HELIX project (www.helixclimate.eu) References: Anandarajah, G., Pye, S., Usher, W., Kesicki, F., & Mcglade, C. (2011). TIAM-UCL Global model documentation. https://www.ucl.ac.uk/energy-models/models/tiam-ucl/tiam-ucl-manual Good, P., Gregory, J. M., Lowe, J. A., & Andrews, T. (2013). Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections. Climate Dynamics, 40(3-4), 1041-1053.
A Comparison of Climate Feedback Strength between CO2 Doubling and LGM Experiments

NASA Astrophysics Data System (ADS)

Yoshimori, M.; Yokohata, T.; Abe-Ouchi, A.

2008-12-01

Studies of past climate potentially provide a constraint on the uncertainty of climate sensitivity, but previous studies warn against a simple scaling to the future. The climate sensitivity is determined by various feedback processes and they may vary with climate states and forcings. In this study, we investigate similarities and differences of feedbacks for a CO2 doubling, a last glacial maximum (LGM), and LGM greenhouse gas (GHG) forcing experiments, using an atmospheric general circulation model coupled to a slab ocean model. After computing the radiative forcing, the individual feedback strengths: water vapor, lapse rate, albedo, and cloud feedbacks, are evaluated explicitly. For this particular model, the difference in the climate sensitivity among experiments is attributed to the shortwave cloud feedback in which there is a tendency that it becomes weaker or even negative in the cooling experiments. No significant difference is found in the water vapor feedback between warming and cooling experiments by GHGs despite the nonlinear dependence of the Clausius-Clapeyron relation on temperature. The weaker water vapor feedback in the LGM experiment due to a relatively weaker tropical forcing is compensated by the stronger lapse rate feedback due to a relatively stronger extratropical forcing. A hypothesis is proposed which explains the asymmetric cloud response between warming and cooling experiments associated with a displacement of the region of mixed- phase clouds. The difference in the total feedback strength between experiments is, however, relatively small compared to the current intermodel spread, and does not necessarily preclude the use of LGM climate as a future constraint.
ISMIP6: Ice Sheet Model Intercomparison Project for CMIP6

NASA Technical Reports Server (NTRS)

Nowicki, S.

2015-01-01

ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6) targets the Cryosphere in a Changing Climate and the Future Sea Level Grand Challenges of the WCRP (World Climate Research Program). Primary goal is to provide future sea level contribution from the Greenland and Antarctic ice sheets, along with associated uncertainty. Secondary goal is to investigate feedback due to dynamic ice sheet models. Experiment design uses and augment the existing CMIP6 (Coupled Model Intercomparison Project Phase 6) DECK (Diagnosis, Evaluation, and Characterization of Klima) experiments. Additonal MIP (Model Intercomparison Project)- specific experiments will be designed for ISM (Ice Sheet Model). Effort builds on the Ice2sea, SeaRISE (Sea-level Response to Ice Sheet Evolution) and COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) efforts.
Learning and Risk Exposure in a Changing Climate

NASA Astrophysics Data System (ADS)

Moore, F.

2015-12-01

Climate change is a gradual process most apparent over long time-scales and large spatial scales, but it is experienced by those affected as changes in local weather. Climate change will gradually push the weather people experience outside the bounds of historic norms, resulting in unprecedented and extreme weather events. However, people do have the ability to learn about and respond to a changing climate. Therefore, connecting the weather people experience with their perceptions of climate change requires understanding how people infer the current state of the climate given their observations of weather. This learning process constitutes a first-order constraint on the rate of adaptation and is an important determinant of the dynamic adjustment costs associated with climate change. In this paper I explore two learning models that describe how local weather observations are translated into perceptions of climate change: an efficient Bayesian learning model and a simpler rolling-mean heuristic. Both have a period during which the learner's beliefs about the state of the climate are different from its true state, meaning the learner is exposed to a different range of extreme weather outcomes then they are prepared for. Using the example of surface temperature trends, I quantify this additional exposure to extreme heat events under both learning models and both RCP 8.5 and 2.6. Risk exposure increases for both learning models, but by substantially more for the rolling-mean learner. Moreover, there is an interaction between the learning model and the rate of climate change: the inefficient rolling-mean learner benefits much more from the slower rates of change under RCP 2.6 then the Bayesian. Finally, I present results from an experiment that suggests people are able to learn about a trending climate in a manner consistent with the Bayesian model.
DOE Office of Scientific and Technical Information (OSTI.GOV)

LaRow, Timothy

The SSTs used in our study come from the Community Climate System Model version 4 (CCSM4) (Gent et al 2011) and from the Canadian Centre for Climate Modeling and Analysis (CanESM2) (Chylek et al20ll) climate models from the fifth Coupled Model Intercomparison Project (CMIP5) (Taylor et al2012). We've examined the tropical cyclones using both the historical simulation that employs volcanic and aerosol forcing as well as the representative concentration pathway 4.5 (RCP4.5). In addition, we've compared the present day North Atlantic tropical cyclone metrics from a previous study (LaRow, 2013) to these climate change experiments. The experimental setup is shownmore » in Table 1. We considered the CMIP5 experiment number '3.2 historical' (Taylor et al,201l), which provides simulations of the recent past (1850-2005). The second set of CMIP5 SSTs is the RCp4.5 experiment where the radiative forcing stabilizes at 45W m-2 after 2100 (experiment number 4.1 in Taylor etal2}ll).« less

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE PAGES

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...

2017-01-01

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

NASA Technical Reports Server (NTRS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.;

2017-01-01

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions 'How does the Earth system respond to forcing?' and 'What are the origins and consequences of systematic model biases?' and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity. A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming? CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. 1. How well do clouds and other relevant variables simulated by models agree with observations? 2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models? 3. Which models have the most credible representations of processes relevant to the simulation of clouds? 4. How do clouds and their changes interact with other elements of the climate system?

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less
Mesoscale weather and climate modeling with the global non-hydrostatic Goddard Earth Observing System Model (GEOS-5) at cloud-permitting resolutions

NASA Astrophysics Data System (ADS)

Putman, W. M.; Suarez, M.

2009-12-01

The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.
Reflecting on the challenges of building a rich interconnected metadata database to describe the experiments of phase six of the coupled climate model intercomparison project (CMIP6) for the Earth System Documentation Project (ES-DOC) and anticipating the opportunities that tooling and services based on rich metadata can provide.

NASA Astrophysics Data System (ADS)

Pascoe, C. L.

2017-12-01

The Coupled Model Intercomparison Project (CMIP) has coordinated climate model experiments involving multiple international modelling teams since 1995. This has led to a better understanding of past, present, and future climate. The 2017 sixth phase of the CMIP process (CMIP6) consists of a suite of common experiments, and 21 separate CMIP-Endorsed Model Intercomparison Projects (MIPs) making a total of 244 separate experiments. Precise descriptions of the suite of CMIP6 experiments have been captured in a Common Information Model (CIM) database by the Earth System Documentation Project (ES-DOC). The database contains descriptions of forcings, model configuration requirements, ensemble information and citation links, as well as text descriptions and information about the rationale for each experiment. The database was built from statements about the experiments found in the academic literature, the MIP submissions to the World Climate Research Programme (WCRP), WCRP summary tables and correspondence with the principle investigators for each MIP. The database was collated using spreadsheets which are archived in the ES-DOC Github repository and then rendered on the ES-DOC website. A diagramatic view of the workflow of building the database of experiment metadata for CMIP6 is shown in the attached figure.The CIM provides the formalism to collect detailed information from diverse sources in a standard way across all the CMIP6 MIPs. The ES-DOC documentation acts as a unified reference for CMIP6 information to be used both by data producers and consumers. This is especially important given the federated nature of the CMIP6 project. Because the CIM allows forcing constraints and other experiment attributes to be referred to by more than one experiment, we can streamline the process of collecting information from modelling groups about how they set up their models for each experiment. End users of the climate model archive will be able to ask questions enabled by the interconnectedness of the metadata such as "Which MIPs make use of experiment A?" and "Which experiments use forcing constraint B?".
The influence of initial and surface boundary conditions on a model-generated January climatology

NASA Technical Reports Server (NTRS)

Wu, K. F.; Spar, J.

1981-01-01

The influence on a model-generated January climate of various surface boundary conditions, as well as initial conditions, was studied by using the GISS coarse-mesh climate model. Four experiments - two with water planets, one with flat continents, and one with mountains - were used to investigate the effects of initial conditions, and the thermal and dynamical effects of the surface on the model generated-climate. However, climatological mean zonal-symmetric sea surface temperature is used in all four runs over the model oceans. Moreover, zero ground wetness and uniform ground albedo except for snow are used in the last experiments.
The Model Intercomparison Project on the Climatic Response to Volcanic Forcing (VolMIP): Experimental Design and Forcing Input Data for CMIP6

NASA Technical Reports Server (NTRS)

Zanchettin, Davide; Khodri, Myriam; Timmreck, Claudia; Toohey, Matthew; Schmidt, Anja; Gerber, Edwin P.; Hegerl, Gabriele; Robock, Alan; Pausata, Francesco; Ball, William T.;

2016-01-01

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used.

Using Web 2.0 Techniques To Bring Global Climate Modeling To More Users

NASA Astrophysics Data System (ADS)

Chandler, M. A.; Sohl, L. E.; Tortorici, S.

2012-12-01

The Educational Global Climate Model has been used for many years in undergraduate courses and professional development settings to teach the fundamentals of global climate modeling and climate change simulation to students and teachers. While course participants have reported a high level of satisfaction in these courses and overwhelmingly claim that EdGCM projects are worth the effort, there is often a high level of frustration during the initial learning stages. Many of the problems stem from issues related to installation of the software suite and to the length of time it can take to run initial experiments. Two or more days of continuous run time may be required before enough data has been gathered to begin analyses. Asking users to download existing simulation data has not been a solution because the GCM data sets are several gigabytes in size, requiring substantial bandwidth and stable dedicated internet connections. As a means of getting around these problems we have been developing a Web 2.0 utility called EzGCM (Easy G-G-M) which emphasizes that participants learn the steps involved in climate modeling research: constructing a hypothesis, designing an experiment, running a computer model and assessing when an experiment has finished (reached equilibrium), using scientific visualization to support analysis, and finally communicating the results through social networking methods. We use classic climate experiments that can be "rediscovered" through exercises with EzGCM and are attempting to make this Web 2.0 tool an entry point into climate modeling for teachers with little time to cover the subject, users with limited computer skills, and for those who want an introduction to the process before tackling more complex projects with EdGCM.
Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.
An economic evaluation of solar radiation management.

PubMed

Aaheim, Asbjørn; Romstad, Bård; Wei, Taoyuan; Kristjánsson, Jón Egill; Muri, Helene; Niemeier, Ulrike; Schmidt, Hauke

2015-11-01

Economic evaluations of solar radiation management (SRM) usually assume that the temperature will be stabilized, with no economic impacts of climate change, but with possible side-effects. We know from experiments with climate models, however, that unlike emission control the spatial and temporal distributions of temperature, precipitation and wind conditions will change. Hence, SRM may have economic consequences under a stabilization of global mean temperature even if side-effects other than those related to the climatic responses are disregarded. This paper addresses the economic impacts of implementing two SRM technologies; stratospheric sulfur injection and marine cloud brightening. By the use of a computable general equilibrium model, we estimate the economic impacts of climatic responses based on the results from two earth system models, MPI-ESM and NorESM. We find that under a moderately increasing greenhouse-gas concentration path, RCP4.5, the economic benefits of implementing climate engineering are small, and may become negative. Global GDP increases in three of the four experiments and all experiments include regions where the benefits from climate engineering are negative. Copyright © 2015 Elsevier B.V. All rights reserved.
Integrating physiological threshold experiments with climate modeling to project mangrove species' range expansion.

PubMed

Cavanaugh, Kyle C; Parker, John D; Cook-Patton, Susan C; Feller, Ilka C; Williams, A Park; Kellner, James R

2015-05-01

Predictions of climate-related shifts in species ranges have largely been based on correlative models. Due to limitations of these models, there is a need for more integration of experimental approaches when studying impacts of climate change on species distributions. Here, we used controlled experiments to identify physiological thresholds that control poleward range limits of three species of mangroves found in North America. We found that all three species exhibited a threshold response to extreme cold, but freeze tolerance thresholds varied among species. From these experiments, we developed a climate metric, freeze degree days (FDD), which incorporates both the intensity and the frequency of freezes. When included in distribution models, FDD accurately predicted mangrove presence/absence. Using 28 years of satellite imagery, we linked FDD to observed changes in mangrove abundance in Florida, further exemplifying the importance of extreme cold. We then used downscaled climate projections of FDD to project that these range limits will move northward by 2.2-3.2 km yr(-1) over the next 50 years. © 2014 John Wiley & Sons Ltd.
The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Hélène; Douville, Hervé; Good, Peter; Kay, Jennifer E.; Klein, Stephen A.; Marchand, Roger; Medeiros, Brian; Pier Siebesma, A.; Skinner, Christopher B.; Stevens, Bjorn; Tselioudis, George; Tsushima, Yoko; Watanabe, Masahiro

2017-01-01

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions How does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions.
1. How well do clouds and other relevant variables simulated by models agree with observations?
2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?
3. Which models have the most credible representations of processes relevant to the simulation of clouds?
4. How do clouds and their changes interact with other elements of the climate system?
Development of Site Specific Climate Scenarios for River and Sediment discharge Using Macrophysical Climate Models: An Example from Puerto Rico

EPA Science Inventory

Climate change and land use change are the primary drivers of changes in ecosystem services globally. Global climate models suggest that in the future Puerto Rico and other small islands in the Caribbean will experience changes in rainfall seasonality. It is anticipated that wa...
Comparison of Grid Nudging and Spectral Nudging Techniques for Dynamical Climate Downscaling within the WRF Model

NASA Astrophysics Data System (ADS)

Fan, X.; Chen, L.; Ma, Z.

2010-12-01

Climate downscaling has been an active research and application area in the past several decades focusing on regional climate studies. Dynamical downscaling, in addition to statistical methods, has been widely used in downscaling as the advanced modern numerical weather and regional climate models emerge. The utilization of numerical models enables that a full set of climate variables are generated in the process of downscaling, which are dynamically consistent due to the constraints of physical laws. While we are generating high resolution regional climate, the large scale climate patterns should be retained. To serve this purpose, nudging techniques, including grid analysis nudging and spectral nudging, have been used in different models. There are studies demonstrating the benefit and advantages of each nudging technique; however, the results are sensitive to many factors such as nudging coefficients and the amount of information to nudge to, and thus the conclusions are controversy. While in a companion work of developing approaches for quantitative assessment of the downscaled climate, in this study, the two nudging techniques are under extensive experiments in the Weather Research and Forecasting (WRF) model. Using the same model provides fair comparability. Applying the quantitative assessments provides objectiveness of comparison. Three types of downscaling experiments were performed for one month of choice. The first type is serving as a base whereas the large scale information is communicated through lateral boundary conditions only; the second is using the grid analysis nudging; and the third is using spectral nudging. Emphases are given to the experiments of different nudging coefficients and nudging to different variables in the grid analysis nudging; while in spectral nudging, we focus on testing the nudging coefficients, different wave numbers on different model levels to nudge.
On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study

NASA Astrophysics Data System (ADS)

Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.

2018-02-01

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.
Global warming and climate change in Amazonia: Climate-vegetation feedback and impacts on water resources

NASA Astrophysics Data System (ADS)

Marengo, José; Nobre, Carlos A.; Betts, Richard A.; Cox, Peter M.; Sampaio, Gilvan; Salazar, Luis

This chapter constitutes an updated review of long-term climate variability and change in the Amazon region, based on observational data spanning more than 50 years of records and on climate-change modeling studies. We start with the early experiments on Amazon deforestation in the late 1970s, and the evolution of these experiments to the latest studies on greenhouse gases emission scenarios and land use changes until the end of the twenty-first century. The "Amazon dieback" simulated by the HadCM3 model occurs after a "tipping point" of CO2 concentration and warming. Experiments on Amazon deforestation and change of climate suggest that once a critical deforestation threshold (or tipping point) of 40-50% forest loss is reached in eastern Amazonia, climate would change in a way which is dangerous for the remaining forest. This may favor a collapse of the tropical forest, with a substitution of the forest by savanna-type vegetation. The concept of "dangerous climate change," as a climate change, which induces positive feedback, which accelerate the change, is strongly linked to the occurrence of tipping points, and it can be explained as the presence of feedback between climate change and the carbon cycle, particularly involving a weakening of the current terrestrial carbon sink and a possible reversal from a sink (as in present climate) to a source by the year 2050. We must, therefore, currently consider the drying simulated by the Hadley Centre model(s) as having a finite probability under global warming, with a potentially enormous impact, but with some degree of uncertainty.
Next Generation Climate Change Experiments Needed to Advance Knowledge and for Assessment of CMIP6

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katzenberger, John; Arnott, James; Wright, Alyson

2014-10-30

The Aspen Global Change Institute hosted a technical science workshop entitled, “Next generation climate change experiments needed to advance knowledge and for assessment of CMIP6,” on August 4-9, 2013 in Aspen, CO. Jerry Meehl (NCAR), Richard Moss (PNNL), and Karl Taylor (LLNL) served as co-chairs for the workshop which included the participation of 32 scientists representing most of the major climate modeling centers for a total of 160 participant days. In August 2013, AGCI gathered a high level meeting of representatives from major climate modeling centers around the world to assess achievements and lessons learned from the most recent generationmore » of coordinated modeling experiments known as the Coupled Model Intercomparison Project – 5 (CMIP5) as well as to scope out the science questions and coordination structure desired for the next anticipated phase of modeling experiments called CMIP6. The workshop allowed for reflection on the coordination of the CMIP5 process as well as intercomparison of model results, such as were assessed in the most recent IPCC 5th Assessment Report, Working Group 1. For example, this slide from Masahiro Watanabe examines performance on a range of models capturing Atlantic Meridional Overturning Circulation (AMOC).« less
Integrating physiological threshold experiments with climate modeling to project mangrove range limits

NASA Astrophysics Data System (ADS)

Cavanaugh, K. C.; Kellner, J.; Cook-Patton, S.; Williams, P.; Feller, I. C.; Parker, J.

2014-12-01

Due to limitations of purely correlative species distribution models, there is a need for more integration of experimental approaches when studying impacts of climate change on species distributions. Here we used controlled experiments to identify physiological thresholds that control poleward range limits of three species of mangroves found in North America. We found that all three species exhibited a threshold response to extreme cold, but freeze tolerance thresholds varied among species. From these experiments we developed a climate metric, freeze degree days (FDD), which incorporates both the intensity and frequency of freezes. When included in distribution models, FDD was a better predictor of mangrove presence/absence than other temperature-based metrics. Using 27 years of satellite imagery, we linked FDD to past changes in mangrove abundance in Florida, further supporting the relevance of FDD. We then used downscaled climate projections of FDD to project poleward migration of these range limits over the next 50 years.
Quantifying the importance of model-to-model variability in integrated assessments of 21st century climate

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Calvin, K. V.

2016-12-01

The C4MIP and CMIP5 model intercomparison projects (MIPs) highlighted uncertainties in climate projections, driven to a large extent by interactions between the terrestrial carbon cycle and climate feedbacks. In addition, the importance of feedbacks between human (energy and economic) systems and natural (carbon and climate) systems is poorly understood, and not considered in the previous MIP protocols. The experiments conducted under the previous Integrated Earth System Model (iESM) project, which coupled a earth system model with an integrated assessment model (GCAM), found that the inclusion of climate feedbacks on the terrestrial system in an RCP4.5 scenario increased ecosystem productivity, resulting in declines in cropland extent and increases in bioenergy production and forest cover. As a follow-up to these studies and to further understand climate-carbon cycle interactions and feedbacks, we examined the robustness of these results by running a suite of GCAM-only experiments using changes in ecosystem productivity derived from both the CMIP5 archive and the Agricultural Model Intercomparison Project. In our results, the effects of climate on yield in an RCP8.5 scenario tended to be more positive than those of AgMIP, but more negative than those of the other CMIP models. We discuss these results and the implications of model-to-model variability for integrated coupling studies of the future earth system.
Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

Building Systems from Scratch: an Exploratory Study of Students Learning About Climate Change

NASA Astrophysics Data System (ADS)

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual programming environment, Scratch, to design games to teach others about climate change. The experience was carefully constructed so that girls of widely differing levels of experience were able to engage in a cycle of game design. This qualitative study aimed to explore the representational choices the girls made as they took up aspects of climate change systems and modeled them in their games. Evidence points to the ways in which designing games about climate science fostered emergent systems thinking and engagement in modeling practices as learners chose what to represent in their games, grappled with the realism of their respective representations, and modeled interactions among systems components. Given the girls' levels of programming skill, parts of systems were more tractable to create than others. The educational purpose of the games was important to the girls' overall design experience, since it influenced their choice of topic, and challenged their emergent understanding of climate change as a systems problem.
Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.

NASA Astrophysics Data System (ADS)

Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.

2017-12-01

Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.
Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2010-12-01

EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.
The Community Earth System Model-Polar Climate Working Group and the status of CESM2.

NASA Astrophysics Data System (ADS)

Bailey, D. A.; Holland, M. M.; DuVivier, A. K.

2017-12-01

The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.
Could geoengineering research help answer one of the biggest questions in climate science?

NASA Astrophysics Data System (ADS)

Wood, Robert; Ackerman, Thomas; Rasch, Philip; Wanser, Kelly

2017-07-01

Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol-cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experiments whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. The control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol-cloud interactions needed to better constrain aerosol forcing in global climate models.
National Centers for Environmental Prediction

Science.gov Websites

Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Model Configuration Collaborators Documentation and Code FAQ Operational Change Log Parallel Experiment
The Pliocene Model Intercomparison Project - Phase 2

NASA Astrophysics Data System (ADS)

Haywood, Alan; Dowsett, Harry; Dolan, Aisling; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark; Hunter, Stephen; Lunt, Daniel; Pound, Matthew; Salzmann, Ulrich

2016-04-01

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate, and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilised for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilise state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land/ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
The Role of Air-sea Coupling in the Response of Climate Extremes to Aerosols

NASA Astrophysics Data System (ADS)

Mahajan, S.

2017-12-01

Air-sea interactions dominate the climate of surrounding regions and thus also modulate the climate response to local and remote aerosol forcings. To clearly isolate the role of air-sea coupling in the climate response to aerosols, we conduct experiments with a full complexity atmosphere model that is coupled to a series of ocean models progressively increasing in complexity. The ocean models range from a data ocean model with prescribed SSTs, to a slab ocean model that only allows thermodynamic interactions, to a full dynamic ocean model. In a preliminary study, we have conducted single forcing experiments with black carbon aerosols in an atmosphere GCM coupled to a data ocean model and a slab ocean model. We find that while black carbon aerosols can intensify mean and extreme summer monsoonal precipitation over the Indian sub-continent, air-sea coupling can dramatically modulate this response. Black carbon aerosols in the vicinity of the Arabian Sea result in an increase of sea surface temperatures there in the slab ocean model, which intensify the low-level Somali Jet. The associated increase in moisture transport into Western India enhances the mean as well as extreme precipitation. In prescribed SST experiments, where SSTs are not allowed to respond BC aerosols, the response is muted. We will present results from a hierarchy of GCM simulations that investigate the role of air-sea coupling in the climate response to aerosols in more detail.
An imperative need for global change research in tropical forests.

PubMed

Zhou, Xuhui; Fu, Yuling; Zhou, Lingyan; Li, Bo; Luo, Yiqi

2013-09-01

Tropical forests play a crucial role in regulating regional and global climate dynamics, and model projections suggest that rapid climate change may result in forest dieback or savannization. However, these predictions are largely based on results from leaf-level studies. How tropical forests respond and feedback to climate change is largely unknown at the ecosystem level. Several complementary approaches have been used to evaluate the effects of climate change on tropical forests, but the results are conflicting, largely due to confounding effects of multiple factors. Although altered precipitation and nitrogen deposition experiments have been conducted in tropical forests, large-scale warming and elevated carbon dioxide (CO2) manipulations are completely lacking, leaving many hypotheses and model predictions untested. Ecosystem-scale experiments to manipulate temperature and CO2 concentration individually or in combination are thus urgently needed to examine their main and interactive effects on tropical forests. Such experiments will provide indispensable data and help gain essential knowledge on biogeochemical, hydrological and biophysical responses and feedbacks of tropical forests to climate change. These datasets can also inform regional and global models for predicting future states of tropical forests and climate systems. The success of such large-scale experiments in natural tropical forests will require an international framework to coordinate collaboration so as to meet the challenges in cost, technological infrastructure and scientific endeavor.
A replicated climate change field experiment reveals rapid evolutionary response in an ecologically important soil invertebrate.

PubMed

Bataillon, Thomas; Galtier, Nicolas; Bernard, Aurelien; Cryer, Nicolai; Faivre, Nicolas; Santoni, Sylvain; Severac, Dany; Mikkelsen, Teis N; Larsen, Klaus S; Beier, Claus; Sørensen, Jesper G; Holmstrup, Martin; Ehlers, Bodil K

2016-07-01

Whether species can respond evolutionarily to current climate change is crucial for the persistence of many species. Yet, very few studies have examined genetic responses to climate change in manipulated experiments carried out in natural field conditions. We examined the evolutionary response to climate change in a common annelid worm using a controlled replicated experiment where climatic conditions were manipulated in a natural setting. Analyzing the transcribed genome of 15 local populations, we found that about 12% of the genetic polymorphisms exhibit differences in allele frequencies associated to changes in soil temperature and soil moisture. This shows an evolutionary response to realistic climate change happening over short-time scale, and calls for incorporating evolution into models predicting future response of species to climate change. It also shows that designed climate change experiments coupled with genome sequencing offer great potential to test for the occurrence (or lack) of an evolutionary response. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
The Process of Change Experimented by Teachers and Students when Voluntarily Trying Environmental Behaviors

ERIC Educational Resources Information Center

Pruneau, Diane; Doyon, Andre; Langis, Joanne; Vasseur, Liette; Martin, Gilles; Ouellet, Eileen; Boudreau, Gaston

2006-01-01

During a training program on climate change education, teachers were invited to experiment with environmental behaviors in their personal lives. They then created their own climate change education model, with which they experimented in their classroom. Through teachers' and students' work, individual interviews, and questionnaires, researchers…
Millennial Climatic Fluctuations Are Key to the Structure of Last Glacial Ecosystems

PubMed Central

Huntley, Brian; Allen, Judy R. M.; Collingham, Yvonne C.; Hickler, Thomas; Lister, Adrian M.; Singarayer, Joy; Stuart, Anthony J.; Sykes, Martin T.; Valdes, Paul J.

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in “normal” and “hosing” experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The “hosing” experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the “normal” experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems. PMID:23613985
Millennial climatic fluctuations are key to the structure of last glacial ecosystems.

PubMed

Huntley, Brian; Allen, Judy R M; Collingham, Yvonne C; Hickler, Thomas; Lister, Adrian M; Singarayer, Joy; Stuart, Anthony J; Sykes, Martin T; Valdes, Paul J

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in "normal" and "hosing" experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The "hosing" experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the "normal" experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems.
The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.
Reconstructing the climate states of the Late Pleistocene with the MIROC climate model

NASA Astrophysics Data System (ADS)

Chan, Wing-Le; Abe-Ouchi, Ayako; O'ishi, Ryouta; Takahashi, Kunio

2014-05-01

The Late Pleistocene was a period which lasted from the Eemian interglacial period to the start of the warm Holocene and was characterized mostly by widespread glacial ice. It was also a period which saw modern humans spread throughout the world and other species of the same genus, like the Neanderthals, become extinct. Various hypotheses have been put forward to explain the extinction of Neanderthals, about 30,000 years ago. Among these is one which involves changes in past climate and the inability of Neanderthals to adapt to such changes. The last traces of Neanderthals coincide with the end of Marine Isotope Stage 3 (MIS3) which was marked by large fluctuations in temperature and so-called Heinrich events, as suggested by geochemical records from ice cores. It is thought that melting sea ice or icebergs originating from the Laurentide ice sheet led to a large discharge of freshwater into the North Atlantic Ocean during the Heinrich events and severely weakened the Atlantic meridional overturning circulation, with important environmental ramifications across parts of Europe such as sharp decreases in temperature and reduction in forest cover. In order to assess the effects of past climate change on past hominin migration and on the extinction of certain species, it is first important to have a good understanding of the past climate itself. In this study, we have used three variants of MIROC (The Model for Interdisciplinary Research on Climate), a global climate model, for a time slice experiment within the Late Pleistocene: two mid-resolution models (an atmosphere model and a coupled atmosphere-ocean model) and a high-resolution atmosphere model. To obtain a fuller picture, we also look at a cool stadial state as obtained from a 'freshwater hosing' coupled-model experiment, designed to mimic the effects of freshwater discharge in the North Atlantic. We next use the sea surface temperature response from this experiment to drive the atmosphere models. We discuss the general features of the model-simulated climates and how model resolution can affect these results. We also compare our results with some available proxy data to elucidate where model simulations show good agreement.
Investigation of models for large-scale meteorological prediction experiments

NASA Technical Reports Server (NTRS)

Spar, J.

1981-01-01

An attempt is made to compute the contributions of various surface boundary conditions to the monthly mean states generated by the 7 layer, 8 x 10 GISS climate model (Hansen et al., 1980), and also to examine the influence of initial conditions on the model climate simulations. Obvious climatic controls as the shape and rotation of the Earth, the solar radiation, and the dry composition of the atmosphere are fixed, and only the surface boundary conditions are altered in the various climate simulations.
Sensitivity of the atmospheric water cycle to corrections of the sea surface temperature bias over southern Africa in a regional climate model

NASA Astrophysics Data System (ADS)

Weber, Torsten; Haensler, Andreas; Jacob, Daniela

2017-12-01

Regional climate models (RCMs) have been used to dynamically downscale global climate projections at high spatial and temporal resolution in order to analyse the atmospheric water cycle. In southern Africa, precipitation pattern were strongly affected by the moisture transport from the southeast Atlantic and southwest Indian Ocean and, consequently, by their sea surface temperatures (SSTs). However, global ocean models often have deficiencies in resolving regional to local scale ocean currents, e.g. in ocean areas offshore the South African continent. By downscaling global climate projections using RCMs, the biased SSTs from the global forcing data were introduced to the RCMs and affected the results of regional climate projections. In this work, the impact of the SST bias correction on precipitation, evaporation and moisture transport were analysed over southern Africa. For this analysis, several experiments were conducted with the regional climate model REMO using corrected and uncorrected SSTs. In these experiments, a global MPI-ESM-LR historical simulation was downscaled with the regional climate model REMO to a high spatial resolution of 50 × 50 km2 and of 25 × 25 km2 for southern Africa using a double-nesting method. The results showed a distinct impact of the corrected SST on the moisture transport, the meridional vertical circulation and on the precipitation pattern in southern Africa. Furthermore, it was found that the experiment with the corrected SST led to a reduction of the wet bias over southern Africa and to a better agreement with observations as without SST bias corrections.
The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

NASA Technical Reports Server (NTRS)

Rind, David H.; Lean, Judith L.; Jonas, Jeffrey

2014-01-01

Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.
A new Geoengineering Model Intercomparison Project (GeoMIP) experiment designed for climate and chemistry models

DOE PAGES

Tilmes, S.; Mills, Mike; Niemeier, Ulrike; ...

2015-01-15

A new Geoengineering Model Intercomparison Project (GeoMIP) experiment "G4 specified stratospheric aerosols" (short name: G4SSA) is proposed to investigate the impact of stratospheric aerosol geoengineering on atmosphere, chemistry, dynamics, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulfur dioxide (SO₂) into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments between 2020 and 2100. This stratospheric aerosol distribution, with a total burden of about 2 Tg S has been derived using the ECHAM5-HAM microphysical model, based on a continuous annualmore » tropical emission of 8 Tg SO₂ yr⁻¹. A ramp-up of geoengineering in 2020 and a ramp-down in 2070 over a period of 2 years are included in the distribution, while a background aerosol burden should be used for the last 3 decades of the experiment. The performance of this experiment using climate and chemistry models in a multi-model comparison framework will allow us to better understand the impact of geoengineering and its abrupt termination after 50 years in a changing environment. The zonal and monthly mean stratospheric aerosol input data set is available at https://www2.acd.ucar.edu/gcm/geomip-g4-specified-stratospheric-aerosol-data-set.« less
Hydrological changes in the tropics: an Holocene perspective

NASA Astrophysics Data System (ADS)

Braconnot, Pascale

2015-04-01

Past climates offer a large set of natural experiences that can be used to better understand the relative role of different climate feedbacks arising from changes in the Earth's global energetics, Earth's hydrological cycle or from the coupling between climate and biogeochemical cycles. In addition, the numerous climate reconstructions from different and independent ice, marine and terrestrial climate archives allow to test how climate models reproduce past changes and to assess their credibility when used for future climate projections. The presentation will review some of the mechanisms affecting the long term trend in the location of the intertropical convergence zone and the Afro-Asian monsoon. Using simulations of the PMIP project, as well as sensitivity experiments with the IPSL model, I'll discuss the role of monsoon changes in the global Earth's energetics and the different feedbacks from ocean and land-surface. The presentation will contrast the conditions in the Early, the mid and late Holocene and show how robust features of monsoon changes can be used to better assess future changes in regions where model results are uncertain, such as West Africa.

Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

NASA Astrophysics Data System (ADS)

Screen, James A.; Deser, Clara; Smith, Doug M.; Zhang, Xiangdong; Blackport, Russell; Kushner, Paul J.; Oudar, Thomas; McCusker, Kelly E.; Sun, Lantao

2018-03-01

The decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.
Assessment of the performance of CORDEX-South Asia experiments for monsoonal precipitation over the Himalayan region during present climate: part I

NASA Astrophysics Data System (ADS)

Ghimire, S.; Choudhary, A.; Dimri, A. P.

2018-04-01

Analysis of regional climate simulations to evaluate the ability of 11 Coordinated Regional Climate Downscaling Experiment in South Asia experiments (CORDEX-South Asia) along with their ensemble to produce precipitation from June to September (JJAS) over the Himalayan region have been carried out. These suite of 11 combinations come from 6 regional climate models (RCMs) driven with 10 initial and boundary conditions from different global climate models and are collectively referred here as 11 CORDEX South Asia experiments. All the RCMs use a similar domain and are having similar spatial resolution of 0.44° ( 50 km). The set of experiments are considered to study precipitation sensitivity associated with the Indian summer monsoon (ISM) over the study region. This effort is made as ISM plays a vital role in summertime precipitation over the Himalayan region which acts as driver for the sustenance of habitat, population, crop, glacier, hydrology etc. In addition, so far the summer monsoon precipitation climatology over the Himalayan region has not been studied with the help of CORDEX data. Thus this study is initiated to evaluate the ability of the experiments and their ensemble in reproducing the characteristics of summer monsoon precipitation over Himalayan region, for the present climate (1970-2005). The precipitation climatology, annual precipitation cycles and interannual variabilities from each simulation have been assessed against the gridded observational dataset: Asian Precipitation-Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources for the given time period. Further, after the selection of the better performing experiment the frequency distribution of precipitation was also studied. In this study, an approach has also been made to study the degree of agreement among individual experiments as a way to quantify the uncertainty among them. The experiments though show a wide variation among themselves and individually over time and space in simulating precipitation distribution over the study region, but noticeably along the foothills of the Himalayas all the simulations show dry precipitation bias against the corresponding observation. In addition, as we move towards higher elevation regions these experiments in general show wet bias. The experiment driven by EC-EARTH global climate model and downscaled using Rossby Center regional Atmospheric model version 4 developed by Swedish Meteorological and Hydrological Institute (SMHI-RCA4) simulate precipitation closely in correspondence with the observation. The ensemble outperforms the result of individual experiments. Correspondingly, different kinds of statistical analysis like spatial and temporal correlation, Taylor diagram, frequency distribution and scatter plot have been performed to compare the model output with observation and to explain the associated resemblance, robustness and dynamics statistically. Through the bias and ensemble spread analysis, an estimation of the uncertainty of the model fields and the degree of agreement among them has also been carried out in this study. Overview of the study suggests that these experiments facilitate precipitation evolution and structure over the Himalayan region with certain degree of uncertainty.
Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.
Assessment of gridded observations used for climate model validation in the Mediterranean region: the HyMeX and MED-CORDEX framework

NASA Astrophysics Data System (ADS)

Flaounas, Emmanouil; Drobinski, Philippe; Borga, Marco; Calvet, Jean-Christophe; Delrieu, Guy; Morin, Efrat; Tartari, Gianni; Toffolon, Roberta

2012-06-01

This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA&D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA&D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA&D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA&D dataset in the context of regional climate research in the Euro-Mediterranean region.
Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

NASA Astrophysics Data System (ADS)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).
Transient climate simulations of the deglaciation 21-9 thousand years before present (version 1) - PMIP4 Core experiment design and boundary conditions

NASA Astrophysics Data System (ADS)

Ivanovic, Ruza F.; Gregoire, Lauren J.; Kageyama, Masa; Roche, Didier M.; Valdes, Paul J.; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev

2016-07-01

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.
Evaluation of the multi-model CORDEX-Africa hindcast using RCMES

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Lean, P.; Mattmann, C. A.; Goodale, C. E.; Hart, A.; Zimdars, P.; Hewitson, B.; Jones, C.

2011-12-01

Recent global climate change studies have concluded with a high confidence level that the observed increasing trend in the global-mean surface air temperatures since mid-20th century is triggered by the emission of anthropogenic greenhouse gases (GHGs). The increase in the global-mean temperature due to anthropogenic emissions is nearly monotonic and may alter the climatological norms resulting in a new climate normal. In the presence of anthropogenic climate change, assessing regional impacts of the altered climate state and developing the plans for mitigating any adverse impacts are an important concern. Assessing future climate state and its impact remains a difficult task largely because of the uncertainties in future emissions and model errors. Uncertainties in climate projections propagates into impact assessment models and result in uncertainties in the impact assessments. In order to facilitate the evaluation of model data, a fundamental step for assessing model errors, the JPL Regional Climate Model Evaluation System (RCMES: Lean et al. 2010; Hart et al. 2011) has been developed through a joint effort of the investigators from UCLA and JPL. RCMES is also a regional climate component of a larger worldwide ExArch project. We will present the evaluation of the surface temperatures and precipitation from multiple RCMs participating in the African component of the Coordinated Regional Climate Downscaling Experiment (CORDEX) that has organized a suite of regional climate projection experiments in which multiple RCMs and GCMs are incorporated. As a part of the project, CORDEX organized a 20-year regional climate hindcast study in order to quantify and understand the uncertainties originating from model errors. Investigators from JPL, UCLA, and the CORDEX-Africa team collaborate to analyze the RCM hindcast data using RCMES. The analysis is focused on measuring the closeness between individual regional climate model outputs as well as their ensembles and observed data. The model evaluation is quantified in terms of widely used metrics. Details on the conceptual outline and architecture of RCMES is presented in two companion papers "The Regional climate model Evaluation System (RCMES) based on contemporary satellite and other observations for assessing regional climate model fidelity" and "A Reusable Framework for Regional Climate Model Evaluation" in GC07 and IN30, respectively.
World Ocean Circulation Experiment

NASA Technical Reports Server (NTRS)

Clarke, R. Allyn

1992-01-01

The oceans are an equal partner with the atmosphere in the global climate system. The World Ocean Circulation Experiment is presently being implemented to improve ocean models that are useful for climate prediction both by encouraging more model development but more importantly by providing quality data sets that can be used to force or to validate such models. WOCE is the first oceanographic experiment that plans to generate and to use multiparameter global ocean data sets. In order for WOCE to succeed, oceanographers must establish and learn to use more effective methods of assembling, quality controlling, manipulating and distributing oceanographic data.
Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the time this contribution is being written, the proposed testbed represents the first implementation of a distributed large-scale, multi-model experiment in the ESGF/CMIP context, joining together server-side approaches for scientific data analysis, HPDA frameworks, end-to-end workflow management, and cloud computing.
Pliocene Model Intercomparison (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

NASA Technical Reports Server (NTRS)

Haywood, A. M.; Dowsett, H. J.; Dolan, A. M.; Rowley, D.; Abe-Ouchi, A.; Otto-Bliesner, B.; Chandler, M. A.; Hunter, S. J.; Lunt, D. J.; Pound, M.;

2015-01-01

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP operates under the umbrella of the Palaeoclimate Modelling Intercomparison Project (PMIP), which examines multiple intervals in Earth history, the consistency of model predictions in simulating these intervals and their ability to reproduce climate signals preserved in geological climate archives. This paper provides a thorough model intercomparison project description, and documents the experimental design in a detailed way. Specifically, this paper describes the experimental design and boundary conditions that will be utilized for the experiments in Phase 2 of PlioMIP.

Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5

NASA Astrophysics Data System (ADS)

Giorgetta, Marco A.; Jungclaus, Johann; Reick, Christian H.; Legutke, Stephanie; Bader, Jürgen; Böttinger, Michael; Brovkin, Victor; Crueger, Traute; Esch, Monika; Fieg, Kerstin; Glushak, Ksenia; Gayler, Veronika; Haak, Helmuth; Hollweg, Heinz-Dieter; Ilyina, Tatiana; Kinne, Stefan; Kornblueh, Luis; Matei, Daniela; Mauritsen, Thorsten; Mikolajewicz, Uwe; Mueller, Wolfgang; Notz, Dirk; Pithan, Felix; Raddatz, Thomas; Rast, Sebastian; Redler, Rene; Roeckner, Erich; Schmidt, Hauke; Schnur, Reiner; Segschneider, Joachim; Six, Katharina D.; Stockhause, Martina; Timmreck, Claudia; Wegner, Jörg; Widmann, Heinrich; Wieners, Karl-H.; Claussen, Martin; Marotzke, Jochem; Stevens, Bjorn

2013-07-01

The new Max-Planck-Institute Earth System Model (MPI-ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO2-only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080-2100 ranges from 1.5°C under the RCP2.6 scenario to 4.4°C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K-1 if the CO2 concentration is constant, or as small as 1.6% K-1, if the CO2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario.
A new framework for climate sensitivity and prediction: a modelling perspective

NASA Astrophysics Data System (ADS)

Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

2016-03-01

The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new perspective.
NASA Downscaling Project: Final Report

NASA Technical Reports Server (NTRS)

Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa

2017-01-01

A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA - 2 reanalyses were used to drive the NU - WRF regional climate model and a GEOS - 5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000 - 2010. The results of these experiments were compared to observational datasets to evaluate the output.
NASA Downscaling Project

NASA Technical Reports Server (NTRS)

Ferraro, Robert; Waliser, Duane; Peters-Lidard, Christa

2017-01-01

A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA-2 reanalyses were used to drive the NU-WRF regional climate model and a GEOS-5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000-2010. The results of these experiments were compared to observational datasets to evaluate the output.
Quantifying the effect of varying GHG's concentration in Regional Climate Models

NASA Astrophysics Data System (ADS)

López-Romero, Jose Maria; Jerez, Sonia; Palacios-Peña, Laura; José Gómez-Navarro, Juan; Jiménez-Guerrero, Pedro; Montavez, Juan Pedro

2017-04-01

Regional Climate Models (RCMs) are driven at the boundaries by Global Circulation Models (GCM), and in the particular case of Climate Change projections, such simulations are forced by varying greenhouse gases (GHGs) concentrations. In hindcast simulations driven by reanalysis products, the climate change signal is usually introduced in the assimilation process as well. An interesting question arising in this context is whether GHGs concentrations have to be varied within the RCMs model itself, or rather they should be kept constant. Some groups keep the GHGs concentrations constant under the assumption that information about climate change signal is given throughout the boundaries; sometimes certain radiation parameterization schemes do not permit such changes. Other approaches vary these concentrations arguing that this preserves the physical coherence respect to the driving conditions for the RCM. This work aims to shed light on this topic. For this task, various regional climate simulations with the WRF model for the 1954-2004 period have been carried out for using a Euro-CORDEX compliant domain. A series of simulations with constant and variable GHGs have been performed using both, a GCM (ECHAM6-OM) and a reanalysis product (ERA-20C) data. Results indicate that there exist noticeable differences when introducing varying GHGs concentrations within the RCM domain. The differences in 2-m temperature series between the experiments with varying or constant GHGs concentration strongly depend on the atmospheric conditions, appearing a strong interannual variability. This suggests that short-term experiments are not recommended if the aim is to assess the role of varying GHGs. In addition, and consistently in both GCM and reanalysis-driven experiments, the magnitude of temperature trends, as well as the spatial pattern represented by varying GHGs experiment, are closer to the driving dataset than in experiments keeping constant the GHGs concentration. These results point towards the need for the inclusion of varying GHGs concentration within the RCM itself when dynamically downscaling global datasets, both in GCM and hindcast simulations.
Climate impacts on agricultural biomass production in the CORDEX.be project context

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van Schaeybroeck, Bert; Termonia, Piet; Willems, Patrick; Van Lipzig, Nicole; Marbaix, Philippe; van Ypersele, Jean-Pascal; Fettweis, Xavier; De Ridder, Koen; Stavrakou, Trissevgeni; Luyten, Patrick; Pottiaux, Eric

2016-04-01

The most important coordinated international effort to translate the IPCC-AR5 outcomes to regional climate modelling is the so-called "COordinated Regional climate Downscaling EXperiment" (CORDEX, http://wcrp-cordex.ipsl.jussieu.fr/). CORDEX.be is a national initiative that aims at combining the Belgian climate and impact modelling research into a single network. The climate network structure is naturally imposed by the top-down data flow, from the four participating upper-air Regional Climate Modelling groups towards seven Local Impact Models (LIMs). In addition to the production of regional climate projections following the CORDEX guidelines, very high-resolution results are provided at convection-permitting resolutions of about 4 km across Belgium. These results are coupled to seven local-impact models with severity indices as output. A multi-model approach is taken that allows uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. The down-scaled scenarios at 4 km resolution allow for impact assessment in different Belgian agro-ecological zones. Climate impacts on arable agriculture are quantified using REGCROP which is a regional dynamic agri-meteorological model geared towards modelling climate impact on biomass production of arable crops (Gobin, 2010, 2012). Results from previous work show that heat stress and water shortages lead to reduced crop growth, whereas increased CO2-concentrations and a prolonged growing season have a positive effect on crop yields. The interaction between these effects depend on the crop type and the field conditions. Root crops such as potato will experience increased drought stress particularly when the probability rises that sensitive crop stages coincide with dry spells. This may be aggravated when wet springs cause water logging in the field and delay planting dates. Despite lower summer precipitation projections for future climate in Belgium, winter cereal yield reductions due to drought stress will be smaller due to earlier maturity. Preliminary results will be presented using the new scenario runs for Belgium.
Timeslice experiments for understanding regional climate projections: applications to the tropical hydrological cycle and European winter circulation

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Douville, Hervé; Skinner, Christopher B.

2017-11-01

A set of atmosphere-only timeslice experiments are described, designed to examine the processes that cause regional climate change and inter-model uncertainty in coupled climate model responses to CO_2 forcing. The timeslice experiments are able to reproduce the pattern of regional climate change in the coupled models, and are applied here to two cases where inter-model uncertainty in future projections is large: the tropical hydrological cycle, and European winter circulation. In tropical forest regions, the plant physiological effect is the largest cause of hydrological cycle change in the two models that represent this process. This suggests that the CMIP5 ensemble mean may be underestimating the magnitude of water cycle change in these regions, due to the inclusion of models without the plant effect. SST pattern change is the dominant cause of precipitation and circulation change over the tropical oceans, and also appears to contribute to inter-model uncertainty in precipitation change over tropical land regions. Over Europe and the North Atlantic, uniform SST increases drive a poleward shift of the storm-track. However this does not consistently translate into an overall polewards storm-track shift, due to large circulation responses to SST pattern change, which varies across the models. Coupled model SST biases influence regional rainfall projections in regions such as the Maritime Continent, and so projections in these regions should be treated with caution.
National Centers for Environmental Prediction

Science.gov Websites

Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Configuration Collaborators Documentation and Code FAQ Operational Change Log Parallel Experiment Change Log
National Centers for Environmental Prediction

Science.gov Websites

Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Collaborators Documentation and Code FAQ Operational Change Log Parallel Experiment Change Log Contacts
High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

NASA Astrophysics Data System (ADS)

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; Senior, Catherine A.; Bellucci, Alessio; Bao, Qing; Chang, Ping; Corti, Susanna; Fučkar, Neven S.; Guemas, Virginie; von Hardenberg, Jost; Hazeleger, Wilco; Kodama, Chihiro; Koenigk, Torben; Leung, L. Ruby; Lu, Jian; Luo, Jing-Jia; Mao, Jiafu; Mizielinski, Matthew S.; Mizuta, Ryo; Nobre, Paulo; Satoh, Masaki; Scoccimarro, Enrico; Semmler, Tido; Small, Justin; von Storch, Jin-Song

2016-11-01

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, "what are the origins and consequences of systematic model biases?", but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

2016 International Land Model Benchmarking (ILAMB) Workshop Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.
Air-Quality and Climate Coupling in High Resolution for Urban Heat Island Study

NASA Astrophysics Data System (ADS)

Halenka, T.; Huszar, P.; Belda, M.

2012-04-01

Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale and climate change effects on air-quality the regional climate model RegCM and chemistry/aerosol model CAMx was coupled. Climate change impacts on air-quality have been studied in high resolution of 10km with interactive two-way coupling of the effects of air-quality on climate. The experiments with the couple were performed for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. New experiments in high resolution are prepared andsimulated for Urban Heat Island studies within the OP Central Europe Project UHI. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for the experiments. Sensitivity tests switching on/off urban areas emissions are analysed as well. The results for year 2005 are presented and discussed, interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.
The impacts of land use, radiative forcing, and biological changes on regional climate in Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.; Pielke, R. A., Sr.

2013-12-01

Because regional responses of surface hydrological and biogeochemical changes are particularly complex, it is necessary to develop assessment tools for regional scale adaptation to climate. We developed a dynamical downscaling method using the regional climate model (NIED-RAMS) over Japan. The NIED-RAMS model includes a plant model that considers biological processes, the General Energy and Mass Transfer Model (GEMTM) which adds spatial resolution to accurately assess critical interactions within the regional climate system for vulnerability assessments to climate change. We digitalized a potential vegetation map that formerly existed only on paper into Geographic Information System data. It quantified information on the reduction of green spaces and the expansion of urban and agricultural areas in Japan. We conducted regional climate sensitivity experiments of land use and land cover (LULC) change, radiative forcing, and biological effects by using the NIED-RAMS with horizontal grid spacing of 20 km. We investigated regional climate responses in Japan for three experimental scenarios: 1. land use and land cover is changed from current to potential vegetation; 2. radiative forcing is changed from 1 x CO2 to 2 x CO2; and 3. biological CO2 partial pressures in plants are doubled. The experiments show good accuracy in reproducing the surface air temperature and precipitation. The experiments indicate the distinct change of hydrological cycles in various aspects due to anthropogenic LULC change, radiative forcing, and biological effects. The relative impacts of those changes are discussed and compared. Acknowledgments This study was conducted as part of the research subject "Vulnerability and Adaptation to Climate Change in Water Hazard Assessed Using Regional Climate Scenarios in the Tokyo Region' (National Research Institute for Earth Science and Disaster Prevention; PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA), and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.
Climate Modeling and Causal Identification for Sea Ice Predictability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less
Characteristics of Quasi-Biennial Oscillation simulation in the Meteorological Research Institute earth system model

NASA Astrophysics Data System (ADS)

Yoshida, K.; Naoe, H.

2016-12-01

Whether climate models drive Quasi-Biennial Oscillation (QBO) appropriately is important to assess QBO impact on climate change such as global warming and solar related variation. However, there were few models generating QBO in the Coupled Model Intercomparison Project Phase 5 (CMIP5). This study focuses on dynamical structure of the QBO and its sensitivity to background wind pattern and model configuration. We present preliminary results of experiments designed by "Towards Improving the QBO in Global Climate Models (QBOi)", which is derived from the Stratosphere-troposphere processes and their role in climate (SPARC), in the Meteorological Research Institute earth system model, MRI-ESM2. The simulations were performed in present-day climate condition, repeated annual cycle condition with various CO2 level and sea surface temperatures, and QBO hindcast. In the present climate simulation, zonal wind in the equatorial stratosphere generally exhibits realistic behavior of the QBO. Equatorial zonal wind variability associated with QBO is overestimated in upper stratosphere and underestimated in lower stratosphere. In the MRI-ESM2, the QBO behavior is mainly driven by gravity wave drag parametrization (GWDP) introduced in Hines (1997). Comparing to reanalyses, shortage of resolved wave forcing is found especially in equatorial lower stratosphere. These discrepancies can be attributed to difference in wave forcing, background wind pattern and model configuration. We intend to show results of additional sensitivity experiments to examine how model configuration and background wind pattern affect resolved wave source, wave propagation characteristics, and QBO behavior.
A user-targeted synthesis of the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutierrez, Jose; Kotlarski, Sven; Hertig, Elke; Wibig, Joanna; Rössler, Ole; Huth, Radan

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. We consider different aspects: (1) marginal aspects such as mean, variance and extremes; (2) temporal aspects such as spell length characteristics; (3) spatial aspects such as the de-correlation length of precipitation extremes; and multi-variate aspects such as the interplay of temperature and precipitation or scale-interactions. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur. Experiment 1 (perfect predictors): what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Experiment 2 (Global climate model predictors): how is the overall representation of regional climate, including errors inherited from global climate models? Experiment 3 (pseudo reality): do methods fail in representing regional climate change? Here, we present a user-targeted synthesis of the results of the first VALUE experiment. In this experiment, downscaling methods are driven with ERA-Interim reanalysis data to eliminate global climate model errors, over the period 1979-2008. As reference data we use, depending on the question addressed, (1) observations from 86 meteorological stations distributed across Europe; (2) gridded observations at the corresponding 86 locations or (3) gridded spatially extended observations for selected European regions. With more than 40 contributing methods, this study is the most comprehensive downscaling inter-comparison project so far. The results clearly indicate that for several aspects, the downscaling skill varies considerably between different methods. For specific purposes, some methods can therefore clearly be excluded.
State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

PubMed

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun'ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-02-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO 2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.
State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling

PubMed Central

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun’ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-01-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets. PMID:28246631
SEEPLUS: A SIMPLE ONLINE CLIMATE MODEL

NASA Astrophysics Data System (ADS)

Tsutsui, Junichi

A web application for a simple climate model - SEEPLUS (a Simple climate model to Examine Emission Pathways Leading to Updated Scenarios) - has been developed. SEEPLUS consists of carbon-cycle and climate-change modules, through which it provides the information infrastructure required to perform climate-change experiments, even on a millennial-timescale. The main objective of this application is to share the latest scientific knowledge acquired from climate modeling studies among the different stakeholders involved in climate-change issues. Both the carbon-cycle and climate-change modules employ impulse response functions (IRFs) for their key processes, thereby enabling the model to integrate the outcome from an ensemble of complex climate models. The current IRF parameters and forcing manipulation are basically consistent with, or within an uncertainty range of, the understanding of certain key aspects such as the equivalent climate sensitivity and ocean CO2 uptake data documented in representative literature. The carbon-cycle module enables inverse calculation to determine the emission pathway required in order to attain a given concentration pathway, thereby providing a flexible way to compare the module with more advanced modeling studies. The module also enables analytical evaluation of its equilibrium states, thereby facilitating the long-term planning of global warming mitigation.
The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: scientific objectives and experimental design

NASA Astrophysics Data System (ADS)

Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark A.; Hunter, Stephen J.; Lunt, Daniel J.; Pound, Matthew; Salzmann, Ulrich

2016-03-01

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

NASA Technical Reports Server (NTRS)

Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark A.; Hunter, Stephen J.; Lunt, Daniel J.; Pound, Matthew;

2016-01-01

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

Weather extremes in very large, high-resolution ensembles: the weatherathome experiment

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rosier, S.; Massey, N.; Rye, C.; Bowery, A.; Miller, J.; Otto, F.; Jones, R.; Wilson, S.; Mote, P.; Stone, D. A.; Yamazaki, Y. H.; Carrington, D.

2011-12-01

Resolution and ensemble size are often seen as alternatives in climate modelling. Models with sufficient resolution to simulate many classes of extreme weather cannot normally be run often enough to assess the statistics of rare events, still less how these statistics may be changing. As a result, assessments of the impact of external forcing on regional climate extremes must be based either on statistical downscaling from relatively coarse-resolution models, or statistical extrapolation from 10-year to 100-year events. Under the weatherathome experiment, part of the climateprediction.net initiative, we have compiled the Met Office Regional Climate Model HadRM3P to run on personal computer volunteered by the general public at 25 and 50km resolution, embedded within the HadAM3P global atmosphere model. With a global network of about 50,000 volunteers, this allows us to run time-slice ensembles of essentially unlimited size, exploring the statistics of extreme weather under a range of scenarios for surface forcing and atmospheric composition, allowing for uncertainty in both boundary conditions and model parameters. Current experiments, developed with the support of Microsoft Research, focus on three regions, the Western USA, Europe and Southern Africa. We initially simulate the period 1959-2010 to establish which variables are realistically simulated by the model and on what scales. Our next experiments are focussing on the Event Attribution problem, exploring how the probability of various types of extreme weather would have been different over the recent past in a world unaffected by human influence, following the design of Pall et al (2011), but extended to a longer period and higher spatial resolution. We will present the first results of the unique, global, participatory experiment and discuss the implications for the attribution of recent weather events to anthropogenic influence on climate.
Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitchell, Daniel; AchutaRao, Krishna; Allen, Myles

The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the presentmore » day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.« less
Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design

DOE PAGES

Mitchell, Daniel; AchutaRao, Krishna; Allen, Myles; ...

2017-02-08

The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the presentmore » day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.« less
Simple Climate Model Evaluation Using Impulse Response Tests

NASA Astrophysics Data System (ADS)

Schwarber, A.; Hartin, C.; Smith, S. J.

2017-12-01

Simple climate models (SCMs) are central tools used to incorporate climate responses into human-Earth system modeling. SCMs are computationally inexpensive, making them an ideal tool for a variety of analyses, including consideration of uncertainty. Despite their wide use, many SCMs lack rigorous testing of their fundamental responses to perturbations. Here, following recommendations of a recent National Academy of Sciences report, we compare several SCMs (Hector-deoclim, MAGICC 5.3, MAGICC 6.0, and the IPCC AR5 impulse response function) to diagnose model behavior and understand the fundamental system responses within each model. We conduct stylized perturbations (emissions and forcing/concentration) of three different chemical species: CO2, CH4, and BC. We find that all 4 models respond similarly in terms of overall shape, however, there are important differences in the timing and magnitude of the responses. For example, the response to a BC pulse differs over the first 20 years after the pulse among the models, a finding that is due to differences in model structure. Such perturbation experiments are difficult to conduct in complex models due to internal model noise, making a direct comparison with simple models challenging. We can, however, compare the simplified model response from a 4xCO2 step experiment to the same stylized experiment carried out by CMIP5 models, thereby testing the ability of SCMs to emulate complex model results. This work allows an assessment of how well current understanding of Earth system responses are incorporated into multi-model frameworks by way of simple climate models.
Experimental and observational studies find contrasting responses of soil nutrients to climate change.

PubMed

Yuan, Z Y; Jiao, F; Shi, X R; Sardans, Jordi; Maestre, Fernando T; Delgado-Baquerizo, Manuel; Reich, Peter B; Peñuelas, Josep

2017-06-01

Manipulative experiments and observations along environmental gradients, the two most common approaches to evaluate the impacts of climate change on nutrient cycling, are generally assumed to produce similar results, but this assumption has rarely been tested. We did so by conducting a meta-analysis and found that soil nutrients responded differentially to drivers of climate change depending on the approach considered. Soil carbon, nitrogen, and phosphorus concentrations generally decreased with water addition in manipulative experiments but increased with annual precipitation along environmental gradients. Different patterns were also observed between warming experiments and temperature gradients. Our findings provide evidence of inconsistent results and suggest that manipulative experiments may be better predictors of the causal impacts of short-term (months to years) climate change on soil nutrients but environmental gradients may provide better information for long-term correlations (centuries to millennia) between these nutrients and climatic features. Ecosystem models should consequently incorporate both experimental and observational data to properly assess the impacts of climate change on nutrient cycling.
Motivational climate, staff and members' behaviors, and members' psychological well-being at a national fitness franchise.

PubMed

Brown, Theresa C; Fry, Mary D

2014-06-01

The purpose of this study was to examine the association between members' perceptions of staffs behaviors, motivational climate, their own behaviors, commitment to future exercise, and life satisfaction in a group-fitness setting. The theory-driven hypothesized mediating role of perceptions of the climate was also tested. Members (N = 5,541) of a national group-fitness studio franchise completed a survey regarding their class experiences. The survey included questions that measured participants' perceptions of the motivational climate (caring, task-involving, ego-involving), perceptions of staff's behaviors, their own behaviors, commitment to exercise, and life satisfaction. Structural equation modeling was used to assess both the association between variables and the theoretically driven predictive relationships. The participants perceived the environment as highly caring and task-involving and low ego-involving. They reported high exercise commitment and moderately high life satisfaction and perceived that the staffs and their own behaviors reflected caring, task-involving characteristics. Structural equation modeling demonstrated that those who perceived a higher caring, task-involving climate and lower ego-involving climate were more likely to report more task-involving, caring behaviors among the staff and themselves as well as greater commitment to exercise. In addition, a theory-driven mediational model suggested that staff behaviors may be an antecedent to members' exercise experiences by impacting their perceptions of the climate. The results of this study give direction to specific behaviors in which staff of group-fitness programs might engage to positively influence members' exercise experiences.
Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

NASA Astrophysics Data System (ADS)

Tsarouchi, Gina; Buytaert, Wouter

2018-02-01

Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000-2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000-2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030-2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.
Exploration of relative skill of individual CORDEX South Asia domain experiments (GCM/RCM combinations) for spatiotemporal simulation of temperature and precipitation over the Karakoram sub-region

NASA Astrophysics Data System (ADS)

Forsythe, N. D.; Fowler, H.; Pritchard, D.

2016-12-01

High mountain Asia (HMA) constitutes one the key "water towers of the world", giving rise to river basins whose resources support hundreds of millions of people. This area will experience rapid demographic growth and socio-economic development for the next few decades compounding pressure on resource managements systems from inevitable climate change. In order to develop climate services to support water resources planning and facilitate adaptive capacity building, it is essential to critically characterise the skill and biases of the evaluation (reanalysis-driven) and control (historical period) components of presently available regional climate model (RCM) experiments. For mountain regions in particular, the ability of RCMs to reasonably reproduce the influence of complex topography, through lapse rates and orographic forcing, on sub-regional climate - notably temperature and precipitation - must be assessed in detail. HMA falls within the South Asia domain of the Coordinated Regional Downscaling Experiment (CORDEX) initiative. Multiple international modelling centres have contributed RCM experiments for the CORDEX South Asia domain. This substantial multi-model ensemble provides a valuable opportunity to explore the spread in model skill at simulation of key characteristics of the present HMA climate. This study focuses geographically on the northwest Upper Indus basin (NW UIB) which covers the bulk of the Karakoram range. Within this subdomain we use climatologies derived from local observations and meteorological reanalyses (ERA-Interim, NASA MERRA-2, HAR)as benchmarks for inter-comparison of individual CORDEX South Asia ensemble members skill in reproducing seasonality and spatial gradients (orographic precipitation profile, temperature lapse rates). Validation of individual CORDEX South Asia ensemble members to this level of detail is indispensable because discontinuities - e.g. differences in latent heat regimes (fusion versus vaporisation) - abound in mountain environments. These discontinuities may undermine widely used statistical approaches (e.g. change factors) used for downscaling and bias correction of future climate projections to locally observed conditions.
Model confirmation in climate economics

PubMed Central

Millner, Antony; McDermott, Thomas K. J.

2016-01-01

Benefit–cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth—one of its most important economic components—had questionable predictive power over the 20th century. PMID:27432964

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

NASA Technical Reports Server (NTRS)

Wen, G.; Cahalan, R.; Rind, D.; Jonas, J.; Pilewskie, P.; Harder, J.

2012-01-01

We report a series of experiments to explore clima responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.
Ontological and Epistemological Issues Regarding Climate Models and Computer Experiments

NASA Astrophysics Data System (ADS)

Vezer, M. A.

2010-12-01

Recent philosophical discussions (Parker 2009; Frigg and Reiss 2009; Winsberg, 2009; Morgon 2002, 2003, 2005; Gula 2002) about the ontology of computer simulation experiments and the epistemology of inferences drawn from them are of particular relevance to climate science as computer modeling and analysis are instrumental in understanding climatic systems. How do computer simulation experiments compare with traditional experiments? Is there an ontological difference between these two methods of inquiry? Are there epistemological considerations that result in one type of inference being more reliable than the other? What are the implications of these questions with respect to climate studies that rely on computer simulation analysis? In this paper, I examine these philosophical questions within the context of climate science, instantiating concerns in the philosophical literature with examples found in analysis of global climate change. I concentrate on Wendy Parker’s (2009) account of computer simulation studies, which offers a treatment of these and other questions relevant to investigations of climate change involving such modelling. Two theses at the center of Parker’s account will be the focus of this paper. The first is that computer simulation experiments ought to be regarded as straightforward material experiments; which is to say, there is no significant ontological difference between computer and traditional experimentation. Parker’s second thesis is that some of the emphasis on the epistemological importance of materiality has been misplaced. I examine both of these claims. First, I inquire as to whether viewing computer and traditional experiments as ontologically similar in the way she does implies that there is no proper distinction between abstract experiments (such as ‘thought experiments’ as well as computer experiments) and traditional ‘concrete’ ones. Second, I examine the notion of materiality (i.e., the material commonality between object and target systems) and some arguments for the claim that materiality entails some inferential advantage to traditional experimentation. I maintain that Parker’s account of the ontology of computer simulations has some interesting though potentially problematic implications regarding conventional distinctions between abstract and concrete methods of inquiry. With respect to her account of materiality, I outline and defend an alternative account, posited by Mary Morgan (2002, 2003, 2005), which holds that ontological similarity between target and object systems confers some epistemological advantage to traditional forms of experimental inquiry.
The PMIP4 contribution to CMIP6 - Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations

NASA Astrophysics Data System (ADS)

Otto-Bliesner, Bette L.; Braconnot, Pascale; Harrison, Sandy P.; Lunt, Daniel J.; Abe-Ouchi, Ayako; Albani, Samuel; Bartlein, Patrick J.; Capron, Emilie; Carlson, Anders E.; Dutton, Andrea; Fischer, Hubertus; Goelzer, Heiko; Govin, Aline; Haywood, Alan; Joos, Fortunat; LeGrande, Allegra N.; Lipscomb, William H.; Lohmann, Gerrit; Mahowald, Natalie; Nehrbass-Ahles, Christoph; Pausata, Francesco S. R.; Peterschmitt, Jean-Yves; Phipps, Steven J.; Renssen, Hans; Zhang, Qiong

2017-11-01

Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land-sea contrast and high-latitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last Interglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.
Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

NASA Technical Reports Server (NTRS)

Thiele, O. (Editor); Schiffer, R. A. (Editor)

1985-01-01

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.
Characterizing sources of uncertainty from global climate models and downscaling techniques

USGS Publications Warehouse

Wootten, Adrienne; Terando, Adam; Reich, Brian J.; Boyles, Ryan; Semazzi, Fred

2017-01-01

In recent years climate model experiments have been increasingly oriented towards providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here we present a method, based on a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. We apply the method to the Southeast U.S. using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios are typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast U.S. for precipitation and ~30% for extreme heat days (> 35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a sub-sample of all models are available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. We conclude with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.
Efficient design based on perturbed parameter ensembles to identify plausible and diverse variants of a model for climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.; Sexton, D.; Murphy, J.

2017-12-01

We present exploratory work towards developing an efficient strategy to select variants of a state-of-the-art but expensive climate model suitable for climate projection studies. The strategy combines information from a set of idealized perturbed parameter ensemble (PPE) and CMIP5 multi-model ensemble (MME) experiments, and uses two criteria as basis to select model variants for a PPE suitable for future projections: a) acceptable model performance at two different timescales, and b) maintaining diversity in model response to climate change. We demonstrate that there is a strong relationship between model errors at weather and climate timescales for a variety of key variables. This relationship is used to filter out parts of parameter space that do not give credible simulations of historical climate, while minimizing the impact on ranges in forcings and feedbacks that drive model responses to climate change. We use statistical emulation to explore the parameter space thoroughly, and demonstrate that about 90% can be filtered out without affecting diversity in global-scale climate change responses. This leads to identification of plausible parts of parameter space from which model variants can be selected for projection studies.
EdGCM: Research Tools for Training the Climate Change Generation

NASA Astrophysics Data System (ADS)

Chandler, M. A.; Sohl, L. E.; Zhou, J.; Sieber, R.

2011-12-01

Climate scientists employ complex computer simulations of the Earth's physical systems to prepare climate change forecasts, study the physical mechanisms of climate, and to test scientific hypotheses and computer parameterizations. The Intergovernmental Panel on Climate Change 4th Assessment Report (2007) demonstrates unequivocally that policy makers rely heavily on such Global Climate Models (GCMs) to assess the impacts of potential economic and emissions scenarios. However, true climate modeling capabilities are not disseminated to the majority of world governments or U.S. researchers - let alone to the educators who will be training the students who are about to be presented with a world full of climate change stakeholders. The goal is not entirely quixotic; in fact, by the mid-1990's prominent climate scientists were predicting with certainty that schools and politicians would "soon" be running GCMs on laptops [Randall, 1996]. For a variety of reasons this goal was never achieved (nor even really attempted). However, around the same time NASA and the National Science Foundation supported a small pilot project at Columbia University to show the potential of putting sophisticated computer climate models - not just "demos" or "toy models" - into the hands of non-specialists. The Educational Global Climate Modeling Project (EdGCM) gave users access to a real global climate model and provided them with the opportunity to experience the details of climate model setup, model operation, post-processing and scientific visualization. EdGCM was designed for use in both research and education - it is a full-blown research GCM, but the ultimate goal is to develop a capability to embed these crucial technologies across disciplines, networks, platforms, and even across academia and industry. With this capability in place we can begin training the skilled workforce that is necessary to deal with the multitude of climate impacts that will occur over the coming decades. To further increase the educational potential of climate models, the EdGCM project has also created "EZgcm". Through a joint venture of NASA, Columbia University and McGill University EZgcm moves the focus toward a greater use of Web 1.0 and Web 2.0-based technologies. It shifts the educational objectives towards a greater emphasis on teaching students how science is conducted and what role science plays in assessing climate change. That is, students learn about the steps of the scientific process as conveyed by climate modeling research: constructing a hypothesis, designing an experiment, running a computer model, using scientific visualization to support analysis, communicating the results of that analysis, and role playing the scientific peer review process. This is in stark contrast to what they learn from the political debate over climate change, which they often confuse with a scientific debate.
International Land Model Benchmarking (ILAMB) Workshop Report, Technical Report DOE/SC-0186

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffman, Forrest M.; Koven, Charles D.; Kappel-Aleks, Gretchen

2016-11-01

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.
The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

NASA Technical Reports Server (NTRS)

Phillips, T. J.; Semtner, A. J., Jr.

1984-01-01

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.
Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

NASA Technical Reports Server (NTRS)

Moore, Berrien, III; Sahagian, Dork

1997-01-01

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.
Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

NASA Astrophysics Data System (ADS)

Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

2012-12-01

Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the results of the earlier decisions, as simulated by C-ROADS. Preliminary evaluations show that both exercises have the potential to provide powerful learning experiences. University students who played World Climate in a climate change course cited it as one of the course activities "promoting the most learning." Students' responses on anonymous surveys and open-ended questions revealed that the experience affected them at visceral, as well as intellectual levels. All of the students recommended that the exercise be continued in future years and many felt that it was the most important learning experience of the semester. Similarly, understanding of climate change and the dynamics of the climate improved for the majority of Future Climate participants, and 90% of participants stated that they were more likely to take action to address climate change on a personal level because of their experience.
Modelling the Climate - Greenland Ice Sheet Interaction in the Coupled Ice-sheet/Climate Model EC-EARTH - PISM

NASA Astrophysics Data System (ADS)

Yang, S.; Madsen, M. S.; Rodehacke, C. B.; Svendsen, S. H.; Adalgeirsdottir, G.

2014-12-01

Recent observations show that the Greenland ice sheet (GrIS) has been losing mass with an increasing speed during the past decades. Predicting the GrIS changes and their climate consequences relies on the understanding of the interaction of the GrIS with the climate system on both global and local scales, and requires climate model systems with an explicit and physically consistent ice sheet module. A fully coupled global climate model with a dynamical ice sheet model for the GrIS has recently been developed. The model system, EC-EARTH - PISM, consists of the EC-EARTH, an atmosphere, ocean and sea ice model system, and the Parallel Ice Sheet Model (PISM). The coupling of PISM includes a modified surface physical parameterization in EC-EARTH adapted to the land ice surface over glaciated regions in Greenland. The PISM ice sheet model is forced with the surface mass balance (SMB) directly computed inside the EC-EARTH atmospheric module and accounting for the precipitation, the surface evaporation, and the melting of snow and ice over land ice. PISM returns the simulated basal melt, ice discharge and ice cover (extent and thickness) as boundary conditions to EC-EARTH. This coupled system is mass and energy conserving without being constrained by any anomaly correction or flux adjustment, and hence is suitable for investigation of ice sheet - climate feedbacks. Three multi-century experiments for warm climate scenarios under (1) the RCP85 climate forcing, (2) an abrupt 4xCO2 and (3) an idealized 1% per year CO2 increase are performed using the coupled model system. The experiments are compared with their counterparts of the standard CMIP5 simulations (without the interactive ice sheet) to evaluate the performance of the coupled system and to quantify the GrIS feedbacks. In particular, the evolution of the Greenland ice sheet under the warm climate and its impacts on the climate system are investigated. Freshwater fluxes from the Greenland ice sheet melt to the Arctic and North Atlantic basin and their influence on the ocean stratification and ocean circulation are analysed. The changes in the surface climate and the atmospheric circulation associated with the impact of the Greenland ice sheet changes are quantified. The interaction between the Greenland ice sheet and Arctic sea ice is also examined.
Improved Analysis of Earth System Models and Observations using Simple Climate Models

NASA Astrophysics Data System (ADS)

Nadiga, B. T.; Urban, N. M.

2016-12-01

Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using both ESM experiments and actual observations are presented. One such result points to the importance of direct sequestration of heat below 700 m, a process that is not allowed for in the simple models that have been traditionally used to deduce climate sensitivity.
Evolution of carbon sinks in a changing climate.

PubMed

Fung, Inez Y; Doney, Scott C; Lindsay, Keith; John, Jasmin

2005-08-09

Climate change is expected to influence the capacities of the land and oceans to act as repositories for anthropogenic CO2 and hence provide a feedback to climate change. A series of experiments with the National Center for Atmospheric Research-Climate System Model 1 coupled carbon-climate model shows that carbon sink strengths vary with the rate of fossil fuel emissions, so that carbon storage capacities of the land and oceans decrease and climate warming accelerates with faster CO2 emissions. Furthermore, there is a positive feedback between the carbon and climate systems, so that climate warming acts to increase the airborne fraction of anthropogenic CO2 and amplify the climate change itself. Globally, the amplification is small at the end of the 21st century in this model because of its low transient climate response and the near-cancellation between large regional changes in the hydrologic and ecosystem responses. Analysis of our results in the context of comparable models suggests that destabilization of the tropical land sink is qualitatively robust, although its degree is uncertain.
Evolution of carbon sinks in a changing climate

PubMed Central

Fung, Inez Y.; Doney, Scott C.; Lindsay, Keith; John, Jasmin

2005-01-01

Climate change is expected to influence the capacities of the land and oceans to act as repositories for anthropogenic CO2 and hence provide a feedback to climate change. A series of experiments with the National Center for Atmospheric Research–Climate System Model 1 coupled carbon–climate model shows that carbon sink strengths vary with the rate of fossil fuel emissions, so that carbon storage capacities of the land and oceans decrease and climate warming accelerates with faster CO2 emissions. Furthermore, there is a positive feedback between the carbon and climate systems, so that climate warming acts to increase the airborne fraction of anthropogenic CO2 and amplify the climate change itself. Globally, the amplification is small at the end of the 21st century in this model because of its low transient climate response and the near-cancellation between large regional changes in the hydrologic and ecosystem responses. Analysis of our results in the context of comparable models suggests that destabilization of the tropical land sink is qualitatively robust, although its degree is uncertain. PMID:16061800
High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

DOE PAGES

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; ...

2016-11-22

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relativelymore » few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. Lastly, HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.« less
Keno-21: Fundamental Issues in the Design of Geophysical Simulation Experiments and Resource Allocation in Climate Modelling

NASA Astrophysics Data System (ADS)

Smith, L. A.

2001-05-01

Many sources of uncertainty come into play when modelling geophysical systems by simulation. These include uncertainty in the initial condition, uncertainty in model parameter values (and the parameterisations themselves) and error in the model class from which the model(s) was selected. In recent decades, climate simulations have focused resources on reducing the last of these by including more and more details into the model. One can question when this ``kitchen sink'' approach should be complimented with realistic estimates of the impact from other uncertainties noted above. Indeed while the impact of model error can never be fully quantified, as all simulation experiments are interpreted a the rosy scenario which assumes a priori that nothing crucial is missing, the impact of other uncertainties can be quantified at only the cost of computational power; as illustrated, for example, in ensemble climate modelling experiments like Casino-21. This talk illustrates the interplay uncertainties in the context of a trivial nonlinear system and an ensemble of models. The simple systems considered in this small scale experiment, Keno-21, are meant to illustrate issues of experimental design; they are not intended to provide true climate simulations. The use of simulation models with huge numbers of parameters given limited data is usually justified by an appeal to the Laws of Physics: the number of free degrees-of-freedom are many fewer than the number of variables; both variables, parameterisations, and parameter values are constrained by ``the physics" and the resulting simulation yields a realistic reproduction of the entire planet's climate system to within reasonable bounds. But what bounds? exactly? In a single model run under transient forcing scenario, there are good statistical grounds for considering only large space and time averages; most of these reasons vanish if an ensemble of runs are made. Ensemble runs can quantify the (in)ability of a model to provide insight on regional changes: if a model cannot capture regional variations in the data on which the model was constructed (that is, in-sample) claims that out-of-sample predictions of those same regional averages should be used in policy making are vacuous. While motivated by climate modelling and illustrated on a trivial nonlinear system, these issues have implications across the range of geophysical modelling. These include implications for appropriate resource allocation, on the making of science policy, and on the public understanding of science and the role of uncertainty in decision making.
The Earth System Model

NASA Technical Reports Server (NTRS)

Schoeberl, Mark; Rood, Richard B.; Hildebrand, Peter; Raymond, Carol

2003-01-01

The Earth System Model is the natural evolution of current climate models and will be the ultimate embodiment of our geophysical understanding of the planet. These models are constructed from components - atmosphere, ocean, ice, land, chemistry, solid earth, etc. models and merged together through a coupling program which is responsible for the exchange of data from the components. Climate models and future earth system models will have standardized modules, and these standards are now being developed by the ESMF project funded by NASA. The Earth System Model will have a variety of uses beyond climate prediction. The model can be used to build climate data records making it the core of an assimilation system, and it can be used in OSSE experiments to evaluate. The computing and storage requirements for the ESM appear to be daunting. However, the Japanese ES theoretical computing capability is already within 20% of the minimum requirements needed for some 2010 climate model applications. Thus it seems very possible that a focused effort to build an Earth System Model will achieve succcss.
Potential evapotranspiration and continental drying

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2016-01-01

By various measures (drought area and intensity, climatic aridity index, and climatic water deficits), some observational analyses have suggested that much of the Earth’s land has been drying during recent decades, but such drying seems inconsistent with observations of dryland greening and decreasing pan evaporation. ‘Offline’ analyses of climate-model outputs from anthropogenic climate change (ACC) experiments portend continuation of putative drying through the twenty-first century, despite an expected increase in global land precipitation. A ubiquitous increase in estimates of potential evapotranspiration (PET), driven by atmospheric warming, underlies the drying trends, but may be a methodological artefact. Here we show that the PET estimator commonly used (the Penman–Monteith PET for either an open-water surface or a reference crop) severely overpredicts the changes in non-water-stressed evapotranspiration computed in the climate models themselves in ACC experiments. This overprediction is partially due to neglect of stomatal conductance reductions commonly induced by increasing atmospheric CO2 concentrations in climate models. Our findings imply that historical and future tendencies towards continental drying, as characterized by offline-computed runoff, as well as other PET-dependent metrics, may be considerably weaker and less extensive than previously thought.
A new dynamical downscaling approach with GCM bias corrections and spectral nudging

NASA Astrophysics Data System (ADS)

Xu, Zhongfeng; Yang, Zong-Liang

2015-04-01

To improve confidence in regional projections of future climate, a new dynamical downscaling (NDD) approach with both general circulation model (GCM) bias corrections and spectral nudging is developed and assessed over North America. GCM biases are corrected by adjusting GCM climatological means and variances based on reanalysis data before the GCM output is used to drive a regional climate model (RCM). Spectral nudging is also applied to constrain RCM-based biases. Three sets of RCM experiments are integrated over a 31 year period. In the first set of experiments, the model configurations are identical except that the initial and lateral boundary conditions are derived from either the original GCM output, the bias-corrected GCM output, or the reanalysis data. The second set of experiments is the same as the first set except spectral nudging is applied. The third set of experiments includes two sensitivity runs with both GCM bias corrections and nudging where the nudging strength is progressively reduced. All RCM simulations are assessed against North American Regional Reanalysis. The results show that NDD significantly improves the downscaled mean climate and climate variability relative to other GCM-driven RCM downscaling approach in terms of climatological mean air temperature, geopotential height, wind vectors, and surface air temperature variability. In the NDD approach, spectral nudging introduces the effects of GCM bias corrections throughout the RCM domain rather than just limiting them to the initial and lateral boundary conditions, thereby minimizing climate drifts resulting from both the GCM and RCM biases.

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.
Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set

NASA Astrophysics Data System (ADS)

Day, J. J.; Tietsche, S.; Collins, M.; Goessling, H. F.; Guemas, V.; Guillory, A.; Hurlin, W. J.; Ishii, M.; Keeley, S. P. E.; Matei, D.; Msadek, R.; Sigmond, M.; Tatebe, H.; Hawkins, E.

2015-10-01

Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation.
The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

NASA Astrophysics Data System (ADS)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing the thermal contrast between the mountain slopes and the surrounding lowlands which drives these wind systems. This analysis is extended to investigate the impacts that the SAF has on the large-scale mountain-plain circulation that develops east of the Rockies over the Great Plains. To help isolate the SAF, a more idealized regional climate experiment which isolates the SAF is performed. It was found that SAF may influence thermally driven atmospheric dynamics up-to 200km east of the Mountains where the SAF originates, suggesting broader regional impacts of the SAF which may not be well resolved by coarser resolution global climate models. The implications of these changes on pollution transport and moist convection are also explored using these simulations.
Improving Climate Projections Using "Intelligent" Ensembles

NASA Technical Reports Server (NTRS)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.
Uncertain soil moisture feedbacks in model projections of Sahel precipitation

NASA Astrophysics Data System (ADS)

Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra

2017-06-01

Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.Plain Language SummaryClimate model projections of Sahel rainfall remain notoriously uncertain; understanding the physical processes responsible for this uncertainty is thus crucial. Our study focuses on analyzing the feedbacks of soil moisture changes on model projections of the West African Monsoon under global warming. Soil moisture-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term soil moisture changes on projected precipitation changes have not been investigated specifically. To isolate these feedbacks, we use targeted simulations from five climate models, with and without soil moisture change. Importantly, we find that climate models exhibit soil moisture-precipitation feedbacks of different sign in this region: in some models soil moisture changes amplify precipitation changes (positive feedback), in others they dampen them (negative feedback). The impact of those feedbacks is in some cases of comparable amplitude to the projected precipitation changes themselves. In other words, we show, over a subset of climate models, how land-atmosphere interactions may be a cause of uncertainty in model projections of precipitation; we emphasize the need to evaluate these processes carefully in current and next-generation climate model simulations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC51G..05B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC51G..05B">Climatic effects of large-scale deforestation in Earth System Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brovkin, V.; Boysen, L.; Pongratz, J. 2017-12-01 Processes in terrestrial ecosystems, to a large extent, are controlled by climate and CO2 concentration. In turn, geographical distribution of vegetation cover strongly affects heat, moisture, and momentum fluxes between land surface and atmosphere (biogeophysical effects). Anthropogenic land use and land cover changes (LULCC) are now included into Earth System Models (ESMs) in the form of historical and hypothetical future scenarios as a forcing in the Coupled Model Intercomparison project, phase 6 (CMIP6). A propagation of climatic effects from land to the ocean in ESMs allows to investigate a global climate response to LULCC in addition to analysis of local effects over deforested land. One complication in the analysis of global climatic effects of historical and future LULCC scenarios is their relatively small amplitude. To increase the signal-to-noise ratio, the Land Use Model Intercomparison Project (LUMIP) suggested an idealized deforestation simulation following a prototype of 1%-CO2 increase experiment commonly used in CMIPs. The idealized experiment allows to investigate - in a harmonized way across models - a response of land surface biophysics and climate to a large-scale deforestation of 20 million km2 distributed over the most forested parts of globe. The forest is removed linearly over a period of 50 years, with an additional 30 years with no specified change in forest cover. Boundary conditions such as CO2 concentration and other forcings are kept at the pre-industrial level. We will present results of idealized deforestation experiments and other sensitivity runs with the CMIP6-version of MPI-ESM, which will be part of the later multi-model comparison. A special focus will be put on less well investigated aspects of LULCC that the idealized setup is particularly well suited for studying, such as non-linearities of the model response to the deforestation forcing and detectability of the signal over time. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120014238','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120014238">Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Sellers, Piers; Rienecker Michele; Randall, David; Frolking, Steve 2012-01-01 Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/39613','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/39613">Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale</a> <a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> William S. Currie; Mark E. Harmon; Ingrid C. Burke; Stephen C. Hart; William J. Parton; Whendee L. Silver 2009-01-01 We analyzed results from 10-year long field incubations of foliar and fine root litter from the Long-term lntersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5453695','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5453695">Experimental and observational studies find contrasting responses of soil nutrients to climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Yuan, ZY; Jiao, F; Shi, XR; Sardans, Jordi; Maestre, Fernando T; Delgado-Baquerizo, Manuel; Reich, Peter B; Peñuelas, Josep 2017-01-01 Manipulative experiments and observations along environmental gradients, the two most common approaches to evaluate the impacts of climate change on nutrient cycling, are generally assumed to produce similar results, but this assumption has rarely been tested. We did so by conducting a meta-analysis and found that soil nutrients responded differentially to drivers of climate change depending on the approach considered. Soil carbon, nitrogen, and phosphorus concentrations generally decreased with water addition in manipulative experiments but increased with annual precipitation along environmental gradients. Different patterns were also observed between warming experiments and temperature gradients. Our findings provide evidence of inconsistent results and suggest that manipulative experiments may be better predictors of the causal impacts of short-term (months to years) climate change on soil nutrients but environmental gradients may provide better information for long-term correlations (centuries to millennia) between these nutrients and climatic features. Ecosystem models should consequently incorporate both experimental and observational data to properly assess the impacts of climate change on nutrient cycling. DOI: http://dx.doi.org/10.7554/eLife.23255.001 PMID:28570219 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070034992&hterms=climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070034992&hterms=climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bchange">AO/NAO Response to Climate Change. 1; Respective Influences of Stratospheric and Tropospheric Climate Changes</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rind, D.; Perlwitz, J.; Lonergan, P. 2005-01-01 We utilize the GISS Global Climate Middle Atmosphere Model and 8 different climate change experiments, many of them focused on stratospheric climate forcings, to assess the relative influence of tropospheric and stratospheric climate change on the extratropical circulation indices (Arctic Oscillation, AO; North Atlantic Oscillation, NAO). The experiments are run in two different ways: with variable sea surface temperatures (SSTs) to allow for a full tropospheric climate response, and with specified SSTs to minimize the tropospheric change. The results show that tropospheric warming (cooling) experiments and stratospheric cooling (warming) experiments produce more positive (negative) AO/NAO indices. For the typical magnitudes of tropospheric and stratospheric climate changes, the tropospheric response dominates; results are strongest when the tropospheric and stratospheric influences are producing similar phase changes. Both regions produce their effect primarily by altering wave propagation and angular momentum transports, but planetary wave energy changes accompanying tropospheric climate change are also important. Stratospheric forcing has a larger impact on the NAO than on the AO, and the angular momentum transport changes associated with it peak in the upper troposphere, affecting all wavenumbers. Tropospheric climate changes influence both the A0 and NAO with effects that extend throughout the troposphere. For both forcings there is often vertical consistency in the sign of the momentum transport changes, obscuring the difference between direct and indirect mechanisms for influencing the surface circulation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ems..confE.546H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ems..confE.546H">Assessing the capability of high resolution climatic model experiments to simulate Mediterranean cyclonic tracks</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hatzaki, M.; Flocas, H. A.; Giannakopoulos, C.; Kostopoulou, E.; Kouroutzoglou, I.; Keay, K.; Simmonds, I. 2010-09-01 In this study, a comparison of a reanalysis driven simulation to a GCM driven simulation of a regional climate model is performed in order to assess the model's ability to capture the climatic characteristics of cyclonic tracks in the Mediterranean in the present climate. The ultimate scope of the study will be to perform a future climate projection related to cyclonic tracks in order to better understand and assess climate change in the Mediterranean. The climatology of the cyclonic tracks includes inter-monthly variations, classification of tracks according to their origin domain, dynamic and kinematic characteristics, as well as trend analysis. For this purpose, the ENEA model is employed based on PROTHEUS system composed of the RegCM atmospheric regional model and the MITgcm ocean model, coupled through the OASIS3 flux coupler. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. Two experiments are employed; a) the ERA402 with lateral Boundary conditions from ERA40 for the 43-year period 1958-2000, and b) the EH5OM_20C3M where the lateral boundary conditions for the atmosphere (1951-2000) are taken from the ECHAM5-MPIOM 20c3m global simulation (run3) included in the IPCC-AR4. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. This approach is considered to be crucial, since open lows are also incorporated into the storm life-cycle, preventing possible inappropriate time series breaks, if a temporary weakening to an open-low state occurs. The model experiments verify that considerable inter-monthly variations of track density occur in the Mediterranean region, consistent with previous studies. The classification of the tracks according to their origin domain show that the vast majority originate within the examined area itself. The study of the kinematic and dynamic parameters of tracks according to their origin demonstrate that deeper cyclones follow the SW track. ACKNOWLEDGMENTS: M. Hatzaki would like to thank the Greek State Scholarships Foundation for financial support through the program of postdoctoral research. The support of EU-FP6 project CIRCE Integrated Project-Climate Change and Impact Research: the Mediterranean Environment (http://www.circeproject.eu) for climate model data provision is also greatly acknowledged. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B53J..08L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B53J..08L">Insights from Modeling the Integrated Climate, Biogeochemical Cycles, Human Activities and Their Interactions in the ACME Earth System Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Leung, L. R.; Thornton, P. E.; Riley, W. J.; Calvin, K. V. 2017-12-01 Towards the goal of understanding the contributions from natural and managed systems to current and future greenhouse gas fluxes and carbon-climate and carbon-CO2 feedbacks, efforts have been underway to improve representations of the terrestrial, river, and human components of the ACME earth system model. Broadly, our efforts include implementation and comparison of approaches to represent the nutrient cycles and nutrient limitations on ecosystem production, extending the river transport model to represent sediment and riverine biogeochemistry, and coupling of human systems such as irrigation, reservoir operations, and energy and land use with the ACME land and river components. Numerical experiments have been designed to understand how terrestrial carbon, nitrogen, and phosphorus cycles regulate climate system feedbacks and the sensitivity of the feedbacks to different model treatments, examine key processes governing sediment and biogeochemistry in the rivers and their role in the carbon cycle, and exploring the impacts of human systems in perturbing the hydrological and carbon cycles and their interactions. This presentation will briefly introduce the ACME modeling approaches and discuss preliminary results and insights from numerical experiments that lay the foundation for improving understanding of the integrated climate-biogeochemistry-human system. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMED52A..01G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMED52A..01G">Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Goldenson, N. L. 2014-12-01 Exploration in an open-ended computer game is an engaging way to explore climate and climate change. Everyone can explore physical models with real-time visualization in the educational simulator Universe Sandbox ² (universesandbox.com/2), which includes basic climate simulations on planets. I have implemented a time-dependent, one-dimensional meridional heat transport energy balance model to run and be adjustable in real time in the midst of a larger simulated system. Universe Sandbox ² is based on the original game - at its core a gravity simulator - with other new physically-based content for stellar evolution, and handling collisions between bodies. Existing users are mostly science enthusiasts in informal settings. We believe that this is the first climate simulation to be implemented in a professionally developed computer game with modern 3D graphical output in real time. The type of simple climate model we've adopted helps us depict the seasonal cycle and the more drastic changes that come from changing the orbit or other external forcings. Users can alter the climate as the simulation is running by altering the star(s) in the simulation, dragging to change orbits and obliquity, adjusting the climate simulation parameters directly or changing other properties like CO2 concentration that affect the model parameters in representative ways. Ongoing visuals of the expansion and contraction of sea ice and snow-cover respond to the temperature calculations, and make it accessible to explore a variety of scenarios and intuitive to understand the output. Variables like temperature can also be graphed in real time. We balance computational constraints with the ability to capture the physical phenomena we wish to visualize, giving everyone access to a simple open-ended meridional energy balance climate simulation to explore and experiment with. The software lends itself to labs at a variety of levels about climate concepts including seasons, the Greenhouse effect, reservoirs and flows, albedo feedback, Snowball Earth, climate sensitivity, and model experiment design. Climate calculations are extended to Mars with some modifications to the Earth climate component, and could be used in lessons about the Mars atmosphere, and exploring scenarios of Mars climate history. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1233786-sensitivity-vadose-zone-water-fluxes-climate-shifts-arid-settings','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1233786-sensitivity-vadose-zone-water-fluxes-climate-shifts-arid-settings">Sensitivity of Vadose Zone Water Fluxes to Climate Shifts in Arid Settings</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Pfletschinger, H.; Prömmel, K.; Schüth, C. 2014-01-01 Vadose zone water fluxes in arid settings are investigated regarding their sensitivity to hydraulic soil parameters and meteorological data. The study is based on the inverse modeling of highly defined soil column experiments and subsequent scenario modeling comparing different climate projections for a defined arid region. In arid regions, groundwater resources are prone to depletion due to excessive water use and little recharge potential. Especially in sand dune areas, groundwater recharge is highly dependent on vadose zone properties and corresponding water fluxes. Nevertheless, vadose zone water fluxes under arid conditions are hard to determine owing to, among other reasons, deepmore » vadose zones with generally low fluxes and only sporadic high infiltration events. In this study, we present an inverse model of infiltration experiments accounting for variable saturated nonisothermal water fluxes to estimate effective hydraulic and thermal parameters of dune sands. A subsequent scenario modeling links the results of the inverse model with projections of a global climate model until 2100. The scenario modeling clearly showed the high dependency of groundwater recharge on precipitation amounts and intensities, whereas temperature increases are only of minor importance for deep infiltration. However, simulated precipitation rates are still affected by high uncertainties in the response to the hydrological input data of the climate model. Thus, higher certainty in the prediction of precipitation pattern is a major future goal for climate modeling to constrain future groundwater management strategies in arid regions.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/90175','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/90175">Detection of greenhouse-gas-induced climatic change. Progress report, July 1, 1994--July 31, 1995</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Jones, P.D.; Wigley, T.M.L. 1995-07-21 The objective of this research is to assembly and analyze instrumental climate data and to develop and apply climate models as a basis for detecting greenhouse-gas-induced climatic change, and validation of General Circulation Models. In addition to changes due to variations in anthropogenic forcing, including greenhouse gas and aerosol concentration changes, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the anthropogenic effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics.more » To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas and aerosol concentration changes and other factors. Analyses will be guided by a variety of models, from simple energy balance climate models to coupled atmosphere ocean General Circulation Models. These analyses are oriented towards obtaining early evidence of anthropogenic climatic change that would lead either to confirmation, rejection or modification of model projections, and towards the statistical validation of General Circulation Model control runs and perturbation experiments.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22.3295S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22.3295S">On the appropriate definition of soil profile configuration and initial conditions for land surface-hydrology models in cold regions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sapriza-Azuri, Gonzalo; Gamazo, Pablo; Razavi, Saman; Wheater, Howard S. 2018-06-01 Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire - Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/964360-carbon-land-model-intercomparison-project-lamp-model-data-comparison-system-evaluation-coupled-biosphere-atmosphere-models','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/964360-carbon-land-model-intercomparison-project-lamp-model-data-comparison-system-evaluation-coupled-biosphere-atmosphere-models">The Carbon-Land Model Intercomparison Project (C-LAMP): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E 2009-01-01 The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the Community Land Model version 3 (CLM3) in the Community Climate System Model version 3 (CCSM3): The CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons against Ameriflus site measurements, MODIS satellite observations, NOAA flask records, TRANSCOM inversions, and Free Air CO{sub 2} Enrichment (FACE) site measurements, and other datasets have been performed and are described in Randerson et al. (2009). The C-LAMP diagnostics package was used to validate improvements to CASA and CN for use in the next generation model, CLM4. It is hoped that this effort will serve as a prototype for an international carbon-cycle model benchmarking activity for models being used for the Inter-governmental Panel on Climate Change (IPCC) Fifth Assessment Report. More information about C-LAMP, the experimental protocol, performance metrics, output standards, and model-data comparisons from the CLM3-CASA and CLM3-CN models are available at http://www.climatemodeling.org/c-lamp.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC13A0942W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC13A0942W">Predicting the Impacts of Climate Change on Central American Agriculture</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Winter, J. M.; Ruane, A. C.; Rosenzweig, C. 2011-12-01 Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950032597&hterms=Global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DGlobal%2Bwarming','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950032597&hterms=Global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DGlobal%2Bwarming">Possible implications of global climate change on global lightning distributions and frequencies</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Price, Colin; Rind, David 1994-01-01 The Goddard Institute for Space Studies (GISS) general circulation model (GCM) is used to study the possible implications of past and future climate change on global lightning frequencies. Two climate change experiments were conducted: one for a 2 x CO2 climate (representing a 4.2 degs C global warming) and one for a 2% decrease in the solar constant (representing a 5.9 degs C global cooling). The results suggest at 30% increase in global lightning activity for the warmer climate and a 24% decrease in global lightning activity for the colder climate. This implies an approximate 5-6% change in global lightning frequencies for every 1 degs C global warming/cooling. Both intracloud and cloud-to-ground frequencies are modeled, with cloud-to-ground lightning frequencies showing larger sensitivity to climate change than intracloud frequencies. The magnitude of the modeled lightning changes depends on season, location, and even time of day. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active">7</li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active">8</li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160012261&hterms=leadership&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dleadership','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160012261&hterms=leadership&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dleadership">The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB V1.0) Contribution to CMIP6</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Kovats, R. Sari; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160012261'); toggleEditAbsImage('author_20160012261_show'); toggleEditAbsImage('author_20160012261_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160012261_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160012261_hide"> 2016-01-01 This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decisionmakers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs (observational datasets) and indicated user needs for the gridding and processing of model output. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.3493R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.3493R">The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB v1.0) contribution to CMIP6</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Sari Kovats, R.; Lotze, Heike K.; Mearns, Linda O.; Navarra, Antonio; Ojima, Dennis S.; Riahi, Keywan; Rosenzweig, Cynthia; Themessl, Matthias; Vincent, Katharine 2016-09-01 This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMEP24A..05M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMEP24A..05M">Morphological Inheritance in Sandy Coastline Morphologies Subject to Long-Term Changes in Wave Climate: Surprising Insights from a Coastline Evolution Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Murray, A. B.; Thomas, C.; Hurst, M. D.; Barkwith, A.; Ashton, A. D.; Ellis, M. A. 2014-12-01 Recent numerical modelling demonstrates that when sandy coastlines are affected predominantly by waves approaching from "high" angles (> ~45° between the coastline and wave crests at the offshore limit of shore-parallel contours), large-scale (kms to 100 kms) morphodynamic instabilities and finite-amplitude interactions can lead to the emergence of striking coastline features, including sand waves, capes and spits. The type of feature that emerges depends on the wave climate, defined as the angular distribution of wave influences on alongshore sediment transport. Under a constant wave climate, coastline morphology reaches a dynamical steady state; the cross-shore/alongshore aspect ratio and the general appearance of the features remains constant. In previous modelling involving wave-climate change, as well as comparisons between observed coastline morphologies and wave climates, it has been implicitly assumed that the morphology adjusts in a quasi-equilibrium fashion, so that at any time the coastline shape reflects the current forcing. However, here we present new model results showing pronounced path dependence in coastline morphodynamics. In experiments with a period of constant wave climate followed by a period of transition to a new wave climate and then a run-on phase, the features that exist during the run-on phase can be qualitatively and quantitatively different from those that would develop initially under the final wave climate. Although the features inherited from the past wave-climate history may in some case be true alternate stable states, in other cases the inherited features gradually decay toward the morphology that would be expected given the final wave climate. A suite of such experiments allows us to characterize how the e-folding timescale of this decay depends on 1) the initial wave climate, 2) the path through wave-climate space, and 3) the rate of transition. When the initial features are flying spits with cross-shore amplitudes of 6 - 8 km, e-folding times can be on the order of millennia or longer. These results could provide a new perspective when interpreting current and past coastline features. In addition, the complex paleo-coastline structure that develops in the coastal hinterlands in these experiments could be relevant to the structures observed in some coastal environments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18023636','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18023636">The predictive validity of safety climate.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Johnson, Stephen E 2007-01-01 Safety professionals have increasingly turned their attention to social science for insight into the causation of industrial accidents. One social construct, safety climate, has been examined by several researchers [Cooper, M. D., & Phillips, R. A. (2004). Exploratory analysis of the safety climate and safety behavior relationship. Journal of Safety Research, 35(5), 497-512; Gillen, M., Baltz, D., Gassel, M., Kirsch, L., & Vacarro, D. (2002). Perceived safety climate, job Demands, and coworker support among union and nonunion injured construction workers. Journal of Safety Research, 33(1), 33-51; Neal, A., & Griffin, M. A. (2002). Safety climate and safety behaviour. Australian Journal of Management, 27, 66-76; Zohar, D. (2000). A group-level model of safety climate: Testing the effect of group climate on microaccidents in manufacturing jobs. Journal of Applied Psychology, 85(4), 587-596; Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628] who have documented its importance as a factor explaining the variation of safety-related outcomes (e.g., behavior, accidents). Researchers have developed instruments for measuring safety climate and have established some degree of psychometric reliability and validity. The problem, however, is that predictive validity has not been firmly established, which reduces the credibility of safety climate as a meaningful social construct. The research described in this article addresses this problem and provides additional support for safety climate as a viable construct and as a predictive indicator of safety-related outcomes. This study used 292 employees at three locations of a heavy manufacturing organization to complete the 16 item Zohar Safety Climate Questionnaire (ZSCQ) [Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628]. In addition, safety behavior and accident experience data were collected for 5 months following the survey and were statistically analyzed (structural equation modeling, confirmatory factor analysis, exploratory factor analysis, etc.) to identify correlations, associations, internal consistency, and factorial structures. Results revealed that the ZSCQ: (a) was psychometrically reliable and valid, (b) served as an effective predictor of safety-related outcomes (behavior and accident experience), and (c) could be trimmed to an 11 item survey with little loss of explanatory power. Practitioners and researchers can use the ZSCQ with reasonable certainty of the questionnaire's reliability and validity. This provides a solid foundation for the development of meaningful organizational interventions and/or continued research into social factors affecting industrial accident experience. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GMD....11.1009B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GMD....11.1009B">Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Butchart, Neal; Anstey, James A.; Hamilton, Kevin; Osprey, Scott; McLandress, Charles; Bushell, Andrew C.; Kawatani, Yoshio; Kim, Young-Ha; Lott, Francois; Scinocca, John; Stockdale, Timothy N.; Andrews, Martin; Bellprat, Omar; Braesicke, Peter; Cagnazzo, Chiara; Chen, Chih-Chieh; Chun, Hye-Yeong; Dobrynin, Mikhail; Garcia, Rolando R.; Garcia-Serrano, Javier; Gray, Lesley J.; Holt, Laura; Kerzenmacher, Tobias; Naoe, Hiroaki; Pohlmann, Holger; Richter, Jadwiga H.; Scaife, Adam A.; Schenzinger, Verena; Serva, Federico; Versick, Stefan; Watanabe, Shingo; Yoshida, Kohei; Yukimoto, Seiji 2018-03-01 The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913780K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913780K">The WASCAL high-resolution climate projection ensemble for West Africa</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kunstmann, Harald; Heinzeller, Dominikus; Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Hamann, Ilse; Salack, Seyni 2017-04-01 With climate change being one of the most severe challenges to rural Africa in the 21st century, West Africa is facing an urgent need to develop effective adaptation and mitigation measures to protect its constantly growing population. We perform ensemble-based regional climate simulations at a high resolution of 12km for West Africa to allow a scientifically sound derivation of climate change adaptation measures. Based on the RCP4.5 scenario, our ensemble consist of three simulation experiments with the Weather Research & Forecasting Tool (WRF) and one additional experiment with the Consortium for Small-scale Modelling Model COSMO in Climate Mode (COSMO-CLM). We discuss the model performance over the validation period 1980-2010, including a novel, station-based precipitation database for West Africa obtained within the WASCAL (West African Science Service Centre for Climate Change and Adapted Land Use) program. Particular attention is paid to the representation of the dynamics of the West African Summer Monsoon and to the added value of our high-resolution models over existing data sets. We further present results on the climate change signal obtained for the two future periods 2020-2050 and 2070-2100 and compare them to current state-of-the-art projections from the CORDEX-Africa project. While the temperature change signal is similar to that obtained within CORDEX-Africa, our simulations predict a wetter future for the Coast of Guinea and the southern Soudano area and a slight drying in the northernmost part of the Sahel. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.pnas.org/content/106/suppl.2/19685.abstract','USGSPUBS'); return false;" href="http://www.pnas.org/content/106/suppl.2/19685.abstract">Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T. 2009-01-01 Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034289','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034289">Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Jackson, S.T.; Betancourt, J.L.; Booth, R.K.; Gray, S.T. 2009-01-01 Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2780932','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2780932">Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T. 2009-01-01 Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. PMID:19805104 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140007298','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140007298">Climate Scenarios for the NASA / USAID SERVIR Project: Challenges for Multiple Planning Horizons</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Robertson, Franklin R.; Roberts, J. B.; Lyon, B.; Funk, C.; Bosilovich, M. G. 2014-01-01 SERVIR, an acronym meaning "to serve" in Spanish, is a joint venture between NASA and the U.S. Agency for International Development (USAID) which provides satellite-based Earth observation data, modeling, and science applications to help developing nations in Central America, East Africa and the Himalayas improve environmental decision making. Anticipating climate variability / climate change impacts has now become an important component of the SERVIR efforts to build capacity in these regions. Uncertainty in hydrometeorological components of climate variations and exposure to extreme events across scales from weather to climate are of particular concern. We report here on work to construct scenarios or outlooks that are being developed as input drivers for decision support systems (DSSs) in a variety of settings. These DSSs are being developed jointly by a broad array NASA Applied Science Team (AST) Investigations and user communities in the three SERVIR Hub Regions, Central America, East Africa and the Himalayas. Issues span hydrologic / water resources modeling, agricultural productivity, and forest carbon reserves. The scenarios needed for these efforts encompass seasonal forecasts, interannual outlooks, and likely decadal / multi-decadal trends. Providing these scenarios across the different AST efforts enables some level of integration in considering regional responses to climate events. We will discuss a number of challenges in developing this continuum of scenarios including the identification and "mining" of predictability, addressing multiple continental regions, issues of downscaling global model integrations to regional / local applications (i.e. hydrologic and crop modeling). We compare / contrast the role of the U.S. National Multi- Model Experiment initiative in seasonal forecasts and the CMIP-5 climate model experiments in supporting these efforts. Examples of these scenarios, their use, and an assessment of their utility as well as limitations will be presented. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70031075','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70031075">Modeled impact of anthropogenic land cover change on climate</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J. 2007-01-01 Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1871823','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1871823">Combined climate and carbon-cycle effects of large-scale deforestation</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Bala, G.; Caldeira, K.; Wickett, M.; Phillips, T. J.; Lobell, D. B.; Delire, C.; Mirin, A. 2007-01-01 The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO2 to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate. PMID:17420463 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17420463','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17420463">Combined climate and carbon-cycle effects of large-scale deforestation.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bala, G; Caldeira, K; Wickett, M; Phillips, T J; Lobell, D B; Delire, C; Mirin, A 2007-04-17 The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO(2) to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These simulations were performed by using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has a net cooling influence on Earth's climate, because the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. Although these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/907848','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/907848">Combined Climate and Carbon-Cycle Effects of Large-Scale Deforestation</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Bala, G; Caldeira, K; Wickett, M 2006-10-17 The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow global warming. Deforestation releases CO{sub 2} to the atmosphere, which exerts a warming influence on Earth's climate. However, biophysical effects of deforestation, which include changes in land surface albedo, evapotranspiration, and cloud cover also affect climate. Here we present results from several large-scale deforestation experiments performed with a three-dimensional coupled global carbon-cycle and climate model. These are the first such simulations performed using a fully three-dimensional model representing physical and biogeochemical interactions among land, atmosphere, and ocean. We find that global-scale deforestation has amore » net cooling influence on Earth's climate, since the warming carbon-cycle effects of deforestation are overwhelmed by the net cooling associated with changes in albedo and evapotranspiration. Latitude-specific deforestation experiments indicate that afforestation projects in the tropics would be clearly beneficial in mitigating global-scale warming, but would be counterproductive if implemented at high latitudes and would offer only marginal benefits in temperate regions. While these results question the efficacy of mid- and high-latitude afforestation projects for climate mitigation, forests remain environmentally valuable resources for many reasons unrelated to climate.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1228343-geoengineering-model-intercomparison-project-phase-geomip6-simulation-design-preliminary-results','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1228343-geoengineering-model-intercomparison-project-phase-geomip6-simulation-design-preliminary-results">The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): Simulation design and preliminary results</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Kravitz, Benjamin S.; Robock, Alan; Tilmes, S.; ... 2015-10-27 We present a suite of new climate model experiment designs for the Geoengineering Model Intercomparison Project (GeoMIP). This set of experiments, named GeoMIP6 (to be consistent with the Coupled Model Intercomparison Project Phase 6), builds on the previous GeoMIP project simulations, and has been expanded to address several further important topics, including key uncertainties in extreme events, the use of geoengineering as part of a portfolio of responses to climate change, and the relatively new idea of cirrus cloud thinning to allow more long wave radiation to escape to space. We discuss experiment designs, as well as the rationale formore » those designs, showing preliminary results from individual models when available. We also introduce a new feature, called the GeoMIP Testbed, which provides a platform for simulations that will be performed with a few models and subsequently assessed to determine whether the proposed experiment designs will be adopted as core (Tier 1) GeoMIP experiments. In conclusion, this is meant to encourage various stakeholders to propose new targeted experiments that address their key open science questions, with the goal of making GeoMIP more relevant to a broader set of communities.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.U54A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.U54A..01S">Modeling the Climatic Consequences of Geoengineering</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Somerville, R. C. 2005-12-01 The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert opinion is that this evidence is now sufficient to establish the human cause of much recent climate change. Nevertheless, no model can provide detailed and fully trustworthy answers to every possible question of interest. As an example, how will the climatology of Atlantic hurricanes change as the greenhouse effect becomes stronger? Can models reliably forecast changes in the length of the hurricane season or changes in the geographical regions affected by hurricanes? The answer is no, or at least, not yet. Additionally, climate models are not based entirely on first principles, such as Newtonian physics. Instead, they have been developed primarily to simulate the present climate and relatively small departures from it. To achieve this goal, a certain amount of empiricism has been built into the models. The result has sometimes been to increase the apparent realism of models at the cost of limiting their generality. Thus, the available climate models may well be less capable of simulating a geoengineering experiment that might lead to a radically different climate. New model development may be required for this new application. The challenge is to distinguish between what models can and cannot do well. It would be irresponsible and unethical, either to undertake geoengineering projects without modeling their consequences, or to place blind faith in the models. To decide how best to model a proposed geoengineering technique requires a deep understanding of the strengths and weaknesses of climate models. The history of modeling successes and failures is a valuable guide to the wise interpretation of model results. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC51G..07D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC51G..07D">Past exposure to climate extremes can inform future projections and guide management: coral reefs as a model system</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Donner, S. D. 2016-12-01 Coral reefs are thought to be more sensitive to climate change than any other marine ecosystem. Episodes of mass coral bleaching, due to anomalously warm water temperatures, have led to coral mortality, declines in coral cover and shifts in the population of other reef-dwelling organisms. The onset of mass bleaching is typically predicted using accumulated heat stress, specifically when the SST exceeds a local climatological maximum by 1-2 °C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs depends on the past thermal experience of the coral reef and the composition of the coral community. This presentation describes the results of a long-term field and modelling research program evaluating the influence of climate experience on the susceptibility of coral reef ecosystems to future climate extremes. Modeling work identified Kiribati's equatorial Gilbert Islands, where the El Niño / Southern Oscillation drives year-to-year shifts in current strength, current direction and consequently ocean temperatures, as an ideal natural laboratory for studying ocean climate extremes. The field program then tracked changes in the coral communities over multiple heat stress events (e.g. 2004-5, 2009-10 El Niño) at a matrix of sites exposed to different levels of historical climate variability and human disturbance. Among the results is evidence that coral bleaching patterns are best predicted by the coefficient of variation of past SST, light exposure, and the presence of particular resilient coral taxa, rather than the standard heat stress metrics. The lessons of this research can be applicable other systems where past experience influences the response to climate extremes </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC41B0965S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC41B0965S">Evaluation of CMIP5 models in the context of food security assessments in Sahel and Eastern Africa</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Shukla, S.; Funk, C. C.; Dettinger, M. D.; Robertson, F. R. 2012-12-01 Global climate change will adversely impact agricultural production in many African countries, mainly in the Sahel region and Eastern Africa that are already considered food insecure regions. The impacts of climate change will be particularly severe in these food insecure countries due to their high dependence on domestic agriculture production, rapid population growth, and lack of technological advances. Early planning and the targeted use of resources will therefore be critical to informing and motivating climate change adaptation actions that can save lives and mitigate economic losses. We seek to use Climate Model Intercomparison Project Phase-5 (CMIP5) global climate model projections to assess and attribute food and water security conditions in the above mentioned regions over next two decades or so. As a first order of business, however, we need to understand how the different models represent the tropical ocean response to anthropogenic warming. We pursue this question through an evaluation of the performance of eight different coupled ocean-atmosphere models under the conditions of the 'historical' experiment. The historical experiment forces the simulations with observed 1850-2005 greenhouse gas, aerosol and land cover. While all the models show substantial warming of the tropical oceans, the pattern and atmospheric response to that warming varies substantially. This analysis suggests that the Community Climate System Model (CCSM4) provides the most realistic 1850-2005 changes over the Indo-Pacific. We then present initial downscaling results, based on large scale forcing from the CCSM4, combined with statistical downscaling based on a combination of monthly simulations from Community Atmopsheric Model 4 (CAM4) and observed gridded time series of African rainfall and air temperatures. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC11D1033T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC11D1033T">Advancing coupled human-earth system models: The integrated Earth System Model Project</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X. 2012-12-01 As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems. While these initial experiments have relied on offline coupling methodologies, current and future experiments are utilizing a single model code developed to integrate GCAM into CESM as a component of the land model. This unique capability facilitates many new applications to scientific questions arising from human and biogeophysical systems interaction. Future developments will further integrate the energy system decisions and greenhouse gas emissions as simulated in GCAM with the appropriate climate and land system components of CESM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900056837&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dseasonal%2Bforecast','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900056837&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dseasonal%2Bforecast">Simulated forecast error and climate drift resulting from the omission of the upper stratosphere in numerical models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Boville, Byron A.; Baumhefner, David P. 1990-01-01 Using an NCAR community climate model, Version I, the forecast error growth and the climate drift resulting from the omission of the upper stratosphere are investigated. In the experiment, the control simulation is a seasonal integration of a medium horizontal general circulation model with 30 levels extending from the surface to the upper mesosphere, while the main experiment uses an identical model, except that only the bottom 15 levels (below 10 mb) are retained. It is shown that both random and systematic errors develop rapidly in the lower stratosphere with some local propagation into the troposphere in the 10-30-day time range. The random growth rate in the troposphere in the case of the altered upper boundary was found to be slightly faster than that for the initial-condition uncertainty alone. However, this is not likely to make a significant impact in operational forecast models, because the initial-condition uncertainty is very large. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active">8</li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active">9</li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=305425','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=305425">Rising temperatures reduce global wheat production</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a> Crop models are essential to assess the threat of climate change for food production but have not been systematically tested against temperature experiments, despite demonstrated uncertainty in temperature response. Herein, we compare 30 different wheat crop models against field experiments in which... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1390443-could-geoengineering-research-help-answer-one-biggest-questions-climate-science-geoengineering-research','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1390443-could-geoengineering-research-help-answer-one-biggest-questions-climate-science-geoengineering-research">Could geoengineering research help answer one of the biggest questions in climate science?: GEOENGINEERING RESEARCH</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Wood, Robert; Ackerman, Thomas; Rasch, Philip J.; ... 2017-06-22 Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol–cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experimentsmore » whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. Here, the control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol–cloud interactions needed to better constrain aerosol forcing in global climate models.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1390443','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1390443">Could geoengineering research help answer one of the biggest questions in climate science?: GEOENGINEERING RESEARCH</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Wood, Robert; Ackerman, Thomas; Rasch, Philip J. Anthropogenic aerosol impacts on clouds constitute the largest source of uncertainty in quantifying the radiative forcing of climate, and hinders our ability to determine Earth's climate sensitivity to greenhouse gas increases. Representation of aerosol–cloud interactions in global models is particularly challenging because these interactions occur on typically unresolved scales. Observational studies show influences of aerosol on clouds, but correlations between aerosol and clouds are insufficient to constrain aerosol forcing because of the difficulty in separating aerosol and meteorological impacts. In this commentary, we argue that this current impasse may be overcome with the development of approaches to conduct control experimentsmore » whereby aerosol particle perturbations can be introduced into patches of marine low clouds in a systematic manner. Such cloud perturbation experiments constitute a fresh approach to climate science and would provide unprecedented data to untangle the effects of aerosol particles on cloud microphysics and the resulting reflection of solar radiation by clouds. Here, the control experiments would provide a critical test of high-resolution models that are used to develop an improved representation aerosol–cloud interactions needed to better constrain aerosol forcing in global climate models.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6707H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6707H">The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) project: a summary</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hawkins, Ed; Day, Jonny; Tietsche, Steffen 2016-04-01 Recent years have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. We describe a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual TimEscales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we provide a summary and update of the project's results which include: (1) quantifying the predictability of Arctic climate, especially sea ice; (2) the state-dependence of this predictability, finding that extreme years are potentially more predictable than neutral years; (3) analysing a spring 'predictability barrier' to skillful forecasts; (4) initial sea ice thickness information provides much of the skill for summer forecasts; (5) quantifying the sources of error growth and uncertainty in Arctic predictions. The dataset is now publicly available. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20180000964&hterms=Experimental+design&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DExperimental%2Bdesign','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20180000964&hterms=Experimental+design&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DExperimental%2Bdesign">The PMIP4 Contribution to CMIP6-Part 4: Scientific Objectives and Experimental Design of the PMIP4-CMIP6 Last Glacial Maximum Experiments and PMIP4 Sensitivity Experiments</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kageyama, Masa; Albani, Samuel; Braconnot, Pascale; Harrison, Sandy P.; Hopcroft, Peter O.; Ivanovic, Ruza F.; Lambert, Fabrice; Marti, Olivier; Peltier, W. Richard; Peterschmitt, Jean-Yves; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20180000964'); toggleEditAbsImage('author_20180000964_show'); toggleEditAbsImage('author_20180000964_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20180000964_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20180000964_hide"> 2017-01-01 The Last Glacial Maximum (LGM, 21,000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.4035K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.4035K">The PMIP4 contribution to CMIP6 - Part 4: Scientific objectives and experimental design of the PMIP4-CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kageyama, Masa; Albani, Samuel; Braconnot, Pascale; Harrison, Sandy P.; Hopcroft, Peter O.; Ivanovic, Ruza F.; Lambert, Fabrice; Marti, Olivier; Peltier, W. Richard; Peterschmitt, Jean-Yves; Roche, Didier M.; Tarasov, Lev; Zhang, Xu; Brady, Esther C.; Haywood, Alan M.; LeGrande, Allegra N.; Lunt, Daniel J.; Mahowald, Natalie M.; Mikolajewicz, Uwe; Nisancioglu, Kerim H.; Otto-Bliesner, Bette L.; Renssen, Hans; Tomas, Robert A.; Zhang, Qiong; Abe-Ouchi, Ayako; Bartlein, Patrick J.; Cao, Jian; Li, Qiang; Lohmann, Gerrit; Ohgaito, Rumi; Shi, Xiaoxu; Volodin, Evgeny; Yoshida, Kohei; Zhang, Xiao; Zheng, Weipeng 2017-11-01 The Last Glacial Maximum (LGM, 21 000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412600A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412600A">FUPSOL: Modelling the Future and Past Solar Influence on Earth Climate</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Anet, J. G.; Rozanov, E.; Peter, T. 2012-04-01 Global warming is becoming one of the main threats to mankind. There is growing evidence that anthropogenic greenhouse gases have become the dominant factor since about 1970. At the same time natural factors of climate change such as solar and volcanic forcings cannot be neglected on longer time scales. Despite growing scientific efforts over the last decades in both, observations and simulations, the uncertainty of the solar contribution to the past climate change remained unacceptably high (IPCC, 2007), the reasons being on one hand missing observations of solar irradiance prior to the satellite era, and on the other hand a majority of models so far not including all processes relevant for solar-climate interactions. This project aims at elucidating the processes governing the effects of solar activity variations on Earth's climate. We use the state-of-the-art coupled atmosphere-ocean-chemistry-climate model (AOCCM) SOCOL (Schraner et al, 2008) developed in Switzerland by coupling the community Earth System Model (ESM) COSMOS distributed by MPI for Meteorology (Hamburg, Germany) with a comprehensive atmospheric chemistry module. The model solves an extensive set of equations describing the dynamics of the atmosphere and ocean, radiative transfer, transport of species, their chemical transformations, cloud formation and the hydrological cycle. The intention is to show how past solar variations affected climate and how the decrease in solar forcing expected for the next decades will affect climate on global and regional scales. We will simulate the global climate system behavior during Dalton minimum (1790 and 1830) and first half of 21st century with a series of multiyear ensemble experiments and perform these experiments using all known anthropogenic and natural climate forcing taken in different combinations to understand the effects of solar irradiance in different spectral regions and particle precipitation variability. Further on, we will quantify the solar influence on global climate in the future by evaluating the simulations and using information from past analogs such as the Dalton minimum. In the end, the project aims at reducing the uncertainty of the solar contribution to past and future climate change, which so far remained high despite many years of analyses of observational records and theoretical investigations with climate models of different complexity. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...48.1841V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...48.1841V">Decadal climate prediction with a refined anomaly initialisation approach</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K. 2017-03-01 In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/55486','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/55486">Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment</a> <a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Natalie A. Griffiths; Paul J. Hanson; Daniel M. Ricciuto; Colleen M. Iversen; Anna M. Jensen; Avni Malhotra; Karis J. McFarlane; Richard J. Norby; Khachik Sargsyan; Stephen D. Sebestyen; Xiaoying Shi; Anthony P. Walker; Eric J. Ward; Jeffrey M. Warren; David J. Weston 2017-01-01 We are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.4019G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.4019G">nonlinMIP contribution to CMIP6: model intercomparison project for non-linear mechanisms: physical basis, experimental design and analysis principles (v1.0)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Good, Peter; Andrews, Timothy; Chadwick, Robin; Dufresne, Jean-Louis; Gregory, Jonathan M.; Lowe, Jason A.; Schaller, Nathalie; Shiogama, Hideo 2016-11-01 nonlinMIP provides experiments that account for state-dependent regional and global climate responses. The experiments have two main applications: (1) to focus understanding of responses to CO2 forcing on states relevant to specific policy or scientific questions (e.g. change under low-forcing scenarios, the benefits of mitigation, or from past cold climates to the present day), or (2) to understand the state dependence (non-linearity) of climate change - i.e. why doubling the forcing may not double the response. State dependence (non-linearity) of responses can be large at regional scales, with important implications for understanding mechanisms and for general circulation model (GCM) emulation techniques (e.g. energy balance models and pattern-scaling methods). However, these processes are hard to explore using traditional experiments, which explains why they have had so little attention in previous studies. Some single model studies have established novel analysis principles and some physical mechanisms. There is now a need to explore robustness and uncertainty in such mechanisms across a range of models (point 2 above), and, more broadly, to focus work on understanding the response to CO2 on climate states relevant to specific policy/science questions (point 1). nonlinMIP addresses this using a simple, small set of CO2-forced experiments that are able to separate linear and non-linear mechanisms cleanly, with a good signal-to-noise ratio - while being demonstrably traceable to realistic transient scenarios. The design builds on the CMIP5 (Coupled Model Intercomparison Project Phase 5) and CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) protocols, and is centred around a suite of instantaneous atmospheric CO2 change experiments, with a ramp-up-ramp-down experiment to test traceability to gradual forcing scenarios. In all cases the models are intended to be used with CO2 concentrations rather than CO2 emissions as the input. The understanding gained will help interpret the spread in policy-relevant scenario projections. Here we outline the basic physical principles behind nonlinMIP, and the method of establishing traceability from abruptCO2 to gradual forcing experiments, before detailing the experimental design, and finally some analysis principles. The test of traceability from abruptCO2 to transient experiments is recommended as a standard analysis within the CMIP5 and CMIP6 DECK protocols. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015WRR....51.1959V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015WRR....51.1959V">Seasonal hydrologic responses to climate change in the Pacific Northwest</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Vano, Julie A.; Nijssen, Bart; Lettenmaier, Dennis P. 2015-04-01 Increased temperatures and changes in precipitation will result in fundamental changes in the seasonal distribution of streamflow in the Pacific Northwest and will have serious implications for water resources management. To better understand local impacts of regional climate change, we conducted model experiments to determine hydrologic sensitivities of annual, seasonal, and monthly runoff to imposed annual and seasonal changes in precipitation and temperature. We used the Variable Infiltration Capacity (VIC) land-surface hydrology model applied at 1/16° latitude-longitude spatial resolution over the Pacific Northwest (PNW), a scale sufficient to support analyses at the hydrologic unit code eight (HUC-8) basin level. These experiments resolve the spatial character of the sensitivity of future water supply to precipitation and temperature changes by identifying the seasons and locations where climate change will have the biggest impact on runoff. The PNW exhibited a diversity of responses, where transitional (intermediate elevation) watersheds experience the greatest seasonal shifts in runoff in response to cool season warming. We also developed a methodology that uses these hydrologic sensitivities as basin-specific transfer functions to estimate future changes in long-term mean monthly hydrographs directly from climate model output of precipitation and temperature. When principles of linearity and superposition apply, these transfer functions can provide feasible first-order estimates of the likely nature of future seasonal streamflow change without performing downscaling and detailed model simulations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25238981','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25238981">Enhanced science-stakeholder communication to improve ecosystem model performances for climate change impact assessments.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Jönsson, Anna Maria; Anderbrant, Olle; Holmér, Jennie; Johansson, Jacob; Schurgers, Guy; Svensson, Glenn P; Smith, Henrik G 2015-04-01 In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science-stakeholder collaboration, and in a two-way dialog link empirical experience and impact modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science-stakeholder communication. By this, we hope to stimulate a discussion among the science-stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AtmRe.206...87O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AtmRe.206...87O">Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent 2018-07-01 In this study, we investigate changes in seasonal temperature and precipitation climatology of CORDEX Middle East and North Africa (MENA) region for three periods of 2010-2040, 2040-2070 and 2070-2100 with respect to the control period of 1970-2000 by using regional climate model simulations. Projections of future climate conditions are modeled by forcing Regional Climate Model, RegCM4.4 of the International Centre for Theoretical Physics (ICTP) with two different CMIP5 global climate models. HadGEM2-ES global climate model of the Met Office Hadley Centre and MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were used to generate 50 km resolution data for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 13. We test the seasonal time-scale performance of RegCM4.4 in simulating the observed climatology over domain of the MENA by using the output of two different global climate models. The projection results show relatively high increase of average temperatures from 3 °C up to 9 °C over the domain for far future (2070-2100). A strong decrease in precipitation is projected in almost all parts of the domain according to the output of the regional model forced by scenario outputs of two global models. Therefore, warmer and drier than present climate conditions are projected to occur more intensely over the CORDEX-MENA domain. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A24D..02Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A24D..02Y">Decadal climate prediction in the large ensemble limit</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yeager, S. G.; Rosenbloom, N. A.; Strand, G.; Lindsay, K. T.; Danabasoglu, G.; Karspeck, A. R.; Bates, S. C.; Meehl, G. A. 2017-12-01 In order to quantify the benefits of initialization for climate prediction on decadal timescales, two parallel sets of historical simulations are required: one "initialized" ensemble that incorporates observations of past climate states and one "uninitialized" ensemble whose internal climate variations evolve freely and without synchronicity. In the large ensemble limit, ensemble averaging isolates potentially predictable forced and internal variance components in the "initialized" set, but only the forced variance remains after averaging the "uninitialized" set. The ensemble size needed to achieve this variance decomposition, and to robustly distinguish initialized from uninitialized decadal predictions, remains poorly constrained. We examine a large ensemble (LE) of initialized decadal prediction (DP) experiments carried out using the Community Earth System Model (CESM). This 40-member CESM-DP-LE set of experiments represents the "initialized" complement to the CESM large ensemble of 20th century runs (CESM-LE) documented in Kay et al. (2015). Both simulation sets share the same model configuration, historical radiative forcings, and large ensemble sizes. The twin experiments afford an unprecedented opportunity to explore the sensitivity of DP skill assessment, and in particular the skill enhancement associated with initialization, to ensemble size. This talk will highlight the benefits of a large ensemble size for initialized predictions of seasonal climate over land in the Atlantic sector as well as predictions of shifts in the likelihood of climate extremes that have large societal impact. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29374176','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29374176">Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Morioka, Yushi; Doi, Takeshi; Behera, Swadhin K 2018-01-26 Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3684808','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3684808">Sea Surface Temperature of the mid-Piacenzian Ocean: A Data-Model Comparison</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Dowsett, Harry J.; Foley, Kevin M.; Stoll, Danielle K.; Chandler, Mark A.; Sohl, Linda E.; Bentsen, Mats; Otto-Bliesner, Bette L.; Bragg, Fran J.; Chan, Wing-Le; Contoux, Camille; Dolan, Aisling M.; Haywood, Alan M.; Jonas, Jeff A.; Jost, Anne; Kamae, Youichi; Lohmann, Gerrit; Lunt, Daniel J.; Nisancioglu, Kerim H.; Abe-Ouchi, Ayako; Ramstein, Gilles; Riesselman, Christina R.; Robinson, Marci M.; Rosenbloom, Nan A.; Salzmann, Ulrich; Stepanek, Christian; Strother, Stephanie L.; Ueda, Hiroaki; Yan, Qing; Zhang, Zhongshi 2013-01-01 The mid-Piacenzian climate represents the most geologically recent interval of long-term average warmth relative to the last million years, and shares similarities with the climate projected for the end of the 21st century. As such, it represents a natural experiment from which we can gain insight into potential climate change impacts, enabling more informed policy decisions for mitigation and adaptation. Here, we present the first systematic comparison of Pliocene sea surface temperature (SST) between an ensemble of eight climate model simulations produced as part of PlioMIP (Pliocene Model Intercomparison Project) with the PRISM (Pliocene Research, Interpretation and Synoptic Mapping) Project mean annual SST field. Our results highlight key regional and dynamic situations where there is discord between the palaeoenvironmental reconstruction and the climate model simulations. These differences have led to improved strategies for both experimental design and temporal refinement of the palaeoenvironmental reconstruction. PMID:23774736 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018OcMod.122...57G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018OcMod.122...57G">A commentary on the Atlantic meridional overturning circulation stability in climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gent, Peter R. 2018-02-01 The stability of the Atlantic meridional overturning circulation (AMOC) in ocean models depends quite strongly on the model formulation, especially the vertical mixing, and whether it is coupled to an atmosphere model. A hysteresis loop in AMOC strength with respect to freshwater forcing has been found in several intermediate complexity climate models and in one fully coupled climate model that has very coarse resolution. Over 40% of modern climate models are in a bistable AMOC state according to the very frequently used simple stability criterion which is based solely on the sign of the AMOC freshwater transport across 33° S. In a recent freshwater hosing experiment in a climate model with an eddy-permitting ocean component, the change in the gyre freshwater transport across 33° S is larger than the AMOC freshwater transport change. This casts very strong doubt on the usefulness of this simple AMOC stability criterion. If a climate model uses large surface flux adjustments, then these adjustments can interfere with the atmosphere-ocean feedbacks, and strongly change the AMOC stability properties. AMOC can be shut off for many hundreds of years in modern fully coupled climate models if the hosing or carbon dioxide forcing is strong enough. However, in one climate model the AMOC recovers after between 1000 and 1400 years. Recent 1% increasing carbon dioxide runs and RCP8.5 future scenario runs have shown that the AMOC reduction is smaller using an eddy-resolving ocean component than in the comparable standard 1° ocean climate models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.3231G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.3231G">OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Griffies, Stephen M.; Danabasoglu, Gokhan; Durack, Paul J.; Adcroft, Alistair J.; Balaji, V.; Böning, Claus W.; Chassignet, Eric P.; Curchitser, Enrique; Deshayes, Julie; Drange, Helge; Fox-Kemper, Baylor; Gleckler, Peter J.; Gregory, Jonathan M.; Haak, Helmuth; Hallberg, Robert W.; Heimbach, Patrick; Hewitt, Helene T.; Holland, David M.; Ilyina, Tatiana; Jungclaus, Johann H.; Komuro, Yoshiki; Krasting, John P.; Large, William G.; Marsland, Simon J.; Masina, Simona; McDougall, Trevor J.; Nurser, A. J. George; Orr, James C.; Pirani, Anna; Qiao, Fangli; Stouffer, Ronald J.; Taylor, Karl E.; Treguier, Anne Marie; Tsujino, Hiroyuki; Uotila, Petteri; Valdivieso, Maria; Wang, Qiang; Winton, Michael; Yeager, Stephen G. 2016-09-01 The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs.OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.2859W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.2859W">Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Williams, C.; Kniveton, D.; Layberry, R. 2009-04-01 It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes remote SST anomalies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1112005M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112005M">Quantifying the role of ocean initial conditions in decadal prediction</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Matei, D.; Pohlmann, H.; Müller, W.; Haak, H.; Jungclaus, J.; Marotzke, J. 2009-04-01 The forecast skill of decadal climate predictions is investigated using two different initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. The results show promising skill up to decadal time scales particularly over the North Atlantic (see also Pohlmann et al. 2009). However, mismatches between the ocean climates of GECCO and the MPI-OM model may lead to inconsistencies in the representation of water masses. Therefore, we pursue an alternative approach to the representation of the observed North Atlantic climate for the period 1948-2007. Using the same MPI-OM ocean model as in the coupled system, we perform an ensemble of four NCEP integrations. The ensemble mean temperature and salinity anomalies are then nudged into the coupled model, followed by hindcast/forecast experiments. The model gives dynamically consistent three-dimensional temperature and salinity fields, thereby avoiding the problems of model drift that were encountered when the assimilation experiment was only driven by reconstructed SSTs (Keenlyside et al. 2008, Pohlmann et al. 2009). Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes, such as North Atlantic and Tropical Pacific climate, MOC variability, Subpolar Gyre variability. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active">9</li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active">10</li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26501958','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26501958">Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien 2015-10-01 Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4621050','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4621050">Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien 2015-01-01 Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. PMID:26501958 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25902494','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25902494">Amplified Arctic warming by phytoplankton under greenhouse warming.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Park, Jong-Yeon; Kug, Jong-Seong; Bader, Jürgen; Rolph, Rebecca; Kwon, Minho 2015-05-12 Phytoplankton have attracted increasing attention in climate science due to their impacts on climate systems. A new generation of climate models can now provide estimates of future climate change, considering the biological feedbacks through the development of the coupled physical-ecosystem model. Here we present the geophysical impact of phytoplankton, which is often overlooked in future climate projections. A suite of future warming experiments using a fully coupled ocean-atmosphere model that interacts with a marine ecosystem model reveals that the future phytoplankton change influenced by greenhouse warming can amplify Arctic surface warming considerably. The warming-induced sea ice melting and the corresponding increase in shortwave radiation penetrating into the ocean both result in a longer phytoplankton growing season in the Arctic. In turn, the increase in Arctic phytoplankton warms the ocean surface layer through direct biological heating, triggering additional positive feedbacks in the Arctic, and consequently intensifying the Arctic warming further. Our results establish the presence of marine phytoplankton as an important potential driver of the future Arctic climate changes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4434777','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4434777">Amplified Arctic warming by phytoplankton under greenhouse warming</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Park, Jong-Yeon; Kug, Jong-Seong; Bader, Jürgen; Rolph, Rebecca; Kwon, Minho 2015-01-01 Phytoplankton have attracted increasing attention in climate science due to their impacts on climate systems. A new generation of climate models can now provide estimates of future climate change, considering the biological feedbacks through the development of the coupled physical–ecosystem model. Here we present the geophysical impact of phytoplankton, which is often overlooked in future climate projections. A suite of future warming experiments using a fully coupled ocean−atmosphere model that interacts with a marine ecosystem model reveals that the future phytoplankton change influenced by greenhouse warming can amplify Arctic surface warming considerably. The warming-induced sea ice melting and the corresponding increase in shortwave radiation penetrating into the ocean both result in a longer phytoplankton growing season in the Arctic. In turn, the increase in Arctic phytoplankton warms the ocean surface layer through direct biological heating, triggering additional positive feedbacks in the Arctic, and consequently intensifying the Arctic warming further. Our results establish the presence of marine phytoplankton as an important potential driver of the future Arctic climate changes. PMID:25902494 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.tmp..221D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.tmp..221D">Simulation of climate characteristics and extremes of the Volta Basin using CCLM and RCA regional climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Darko, Deborah; Adjei, Kwaku A.; Appiah-Adjei, Emmanuel K.; Odai, Samuel N.; Obuobie, Emmanuel; Asmah, Ruby 2018-06-01 The extent to which statistical bias-adjusted outputs of two regional climate models alter the projected change signals for the mean (and extreme) rainfall and temperature over the Volta Basin is evaluated. The outputs from two regional climate models in the Coordinated Regional Climate Downscaling Experiment for Africa (CORDEX-Africa) are bias adjusted using the quantile mapping technique. Annual maxima rainfall and temperature with their 10- and 20-year return values for the present (1981-2010) and future (2051-2080) climates are estimated using extreme value analyses. Moderate extremes are evaluated using extreme indices (viz. percentile-based, duration-based, and intensity-based). Bias adjustment of the original (bias-unadjusted) models improves the reproduction of mean rainfall and temperature for the present climate. However, the bias-adjusted models poorly reproduce the 10- and 20-year return values for rainfall and maximum temperature whereas the extreme indices are reproduced satisfactorily for the present climate. Consequently, projected changes in rainfall and temperature extremes were weak. The bias adjustment results in the reduction of the change signals for the mean rainfall while the mean temperature signals are rather magnified. The projected changes for the original mean climate and extremes are not conserved after bias adjustment with the exception of duration-based extreme indices. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C41B0670T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C41B0670T">Estimating the impact of internal climate variability on ice sheet model simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tsai, C. Y.; Forest, C. E.; Pollard, D. 2016-12-01 Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1510121P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1510121P">PIMMS tools for capturing metadata about simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pascoe, Charlotte; Devine, Gerard; Tourte, Gregory; Pascoe, Stephen; Lawrence, Bryan; Barjat, Hannah 2013-04-01 PIMMS (Portable Infrastructure for the Metafor Metadata System) provides a method for consistent and comprehensive documentation of modelling activities that enables the sharing of simulation data and model configuration information. The aim of PIMMS is to package the metadata infrastructure developed by Metafor for CMIP5 so that it can be used by climate modelling groups in UK Universities. PIMMS tools capture information about simulations from the design of experiments to the implementation of experiments via simulations that run models. PIMMS uses the Metafor methodology which consists of a Common Information Model (CIM), Controlled Vocabularies (CV) and software tools. PIMMS software tools provide for the creation and consumption of CIM content via a web services infrastructure and portal developed by the ES-DOC community. PIMMS metadata integrates with the ESGF data infrastructure via the mapping of vocabularies onto ESGF facets. There are three paradigms of PIMMS metadata collection: Model Intercomparision Projects (MIPs) where a standard set of questions is asked of all models which perform standard sets of experiments. Disciplinary level metadata collection where a standard set of questions is asked of all models but experiments are specified by users. Bespoke metadata creation where the users define questions about both models and experiments. Examples will be shown of how PIMMS has been configured to suit each of these three paradigms. In each case PIMMS allows users to provide additional metadata beyond that which is asked for in an initial deployment. The primary target for PIMMS is the UK climate modelling community where it is common practice to reuse model configurations from other researchers. This culture of collaboration exists in part because climate models are very complex with many variables that can be modified. Therefore it has become common practice to begin a series of experiments by using another climate model configuration as a starting point. Usually this other configuration is provided by a researcher in the same research group or by a previous collaborator with whom there is an existing scientific relationship. Some efforts have been made at the university department level to create documentation but there is a wide diversity in the scope and purpose of this information. The consistent and comprehensive documentation enabled by PIMMS will enable the wider sharing of climate model data and configuration information. The PIMMS methodology assumes an initial effort to document standard model configurations. Once these descriptions have been created users need only describe the specific way in which their model configuration is different from the standard. Thus the documentation burden on the user is specific to the experiment they are performing and fits easily into the workflow of doing their science. PIMMS metadata is independent of data and as such is ideally suited for documenting model development. PIMMS provides a framework for sharing information about failed model configurations for which data are not kept, the negative results that don't appear in scientific literature. PIMMS is a UK project funded by JISC, The University of Reading, The University of Bristol and STFC. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810013172','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810013172">Do initial conditions matter? A comparison of model climatologies generated from different initial states</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Spar, J.; Cohen, C.; Wu, P. 1981-01-01 A coarse mesh (8 by 10) 7 layer global climate model was used to compute 15 months of meteorological history in two perpetual January experiments on a water planet (without continents) with a zonally symmetric climatological January sea surface temperature field. In the first of the two water planet experiments the initial atmospheric state was a set of zonal mean values of specific humidity, temperature, and wind at each latitude. In the second experiment the model was initialized with globally uniform mean values of specific humidity and temperature on each sigma level surface, constant surface pressure (1010 mb), and zero wind everywhere. A comparison was made of the mean January climatic states generated by the two water planet experiments. The first two months of each 15 January run were discarded, and 13 month averages were computed from months 3 through 15. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830013405','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830013405">Radiation budget measurement/model interface</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Vonderhaar, T. H.; Ciesielski, P.; Randel, D.; Stevens, D. 1983-01-01 This final report includes research results from the period February, 1981 through November, 1982. Two new results combine to form the final portion of this work. They are the work by Hanna (1982) and Stevens to successfully test and demonstrate a low-order spectral climate model and the work by Ciesielski et al. (1983) to combine and test the new radiation budget results from NIMBUS-7 with earlier satellite measurements. Together, the two related activities set the stage for future research on radiation budget measurement/model interfacing. Such combination of results will lead to new applications of satellite data to climate problems. The objectives of this research under the present contract are therefore satisfied. Additional research reported herein includes the compilation and documentation of the radiation budget data set a Colorado State University and the definition of climate-related experiments suggested after lengthy analysis of the satellite radiation budget experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A51I0173L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A51I0173L">Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lee, H. 2016-12-01 Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910031763&hterms=climate+facts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bfacts','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910031763&hterms=climate+facts&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bfacts">On the limitations of General Circulation Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Stone, Peter H.; Risbey, James S. 1990-01-01 General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A52B..08B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A52B..08B">Tinkering With AGCMs To Investigate Atmospheric Behavior</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bitz, C. M. 2014-12-01 My experience teaching a course in global climate modeling has proven that students (and instructors) with wide-ranging backgrounds in earth-science learn effectively about the complexity of climate by tinker with model components. As an example, I will present a series of experiments in an AGCM with highly simplified geometries for ocean and land to test the response of the atmosphere to variations in basic parameters. The figure below shows an example of how the zonal wind changes with surface roughness and orography. The pinnacle of experiments explored in my course was the outcome of a homework assignment where students reduced the cloud droplet radius by 40% over ocean, and the results surprised students and instructor alike. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3948235','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3948235">Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Prudhomme, Christel; Giuntoli, Ignazio; Robinson, Emma L.; Clark, Douglas B.; Arnell, Nigel W.; Dankers, Rutger; Fekete, Balázs M.; Franssen, Wietse; Gerten, Dieter; Gosling, Simon N.; Hagemann, Stefan; Hannah, David M.; Kim, Hyungjun; Masaki, Yoshimitsu; Satoh, Yusuke; Stacke, Tobias; Wada, Yoshihide; Wisser, Dominik 2014-01-01 Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by bias-corrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty. PMID:24344266 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24344266','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24344266">Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Prudhomme, Christel; Giuntoli, Ignazio; Robinson, Emma L; Clark, Douglas B; Arnell, Nigel W; Dankers, Rutger; Fekete, Balázs M; Franssen, Wietse; Gerten, Dieter; Gosling, Simon N; Hagemann, Stefan; Hannah, David M; Kim, Hyungjun; Masaki, Yoshimitsu; Satoh, Yusuke; Stacke, Tobias; Wada, Yoshihide; Wisser, Dominik 2014-03-04 Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by bias-corrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GMD....11.1133K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GMD....11.1133K">The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Keller, David P.; Lenton, Andrew; Scott, Vivian; Vaughan, Naomi E.; Bauer, Nico; Ji, Duoying; Jones, Chris D.; Kravitz, Ben; Muri, Helene; Zickfeld, Kirsten 2018-03-01 The recent IPCC reports state that continued anthropogenic greenhouse gas emissions are changing the climate, threatening <q>severe, pervasive and irreversible</q> impacts. Slow progress in emissions reduction to mitigate climate change is resulting in increased attention to what is called geoengineering, climate engineering, or climate intervention - deliberate interventions to counter climate change that seek to either modify the Earth's radiation budget or remove greenhouse gases such as CO2 from the atmosphere. When focused on CO2, the latter of these categories is called carbon dioxide removal (CDR). Future emission scenarios that stay well below 2 °C, and all emission scenarios that do not exceed 1.5 °C warming by the year 2100, require some form of CDR. At present, there is little consensus on the climate impacts and atmospheric CO2 reduction efficacy of the different types of proposed CDR. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDRMIP) was initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDRMIP experiments, which are formally part of the 6th Coupled Model Intercomparison Project (CMIP6). These experiments are designed to address questions concerning CDR-induced climate <q>reversibility</q>, the response of the Earth system to direct atmospheric CO2 removal (direct air capture and storage), and the CDR potential and impacts of afforestation and reforestation, as well as ocean alkalinization.> </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1455276-carbon-dioxide-removal-model-intercomparison-project-cdrmip-rationale-experimental-protocol-cmip6','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1455276-carbon-dioxide-removal-model-intercomparison-project-cdrmip-rationale-experimental-protocol-cmip6">The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Keller, David P.; Lenton, Andrew; Scott, Vivian The recent IPCC reports state that continued anthropogenic greenhouse gas emissions are changing the climate, threatening severe, pervasive and irreversible impacts. Slow progress in emissions reduction to mitigate climate change is resulting in increased attention to what is called geoengineering, climate engineering, or climate intervention – deliberate interventions to counter climate change that seek to either modify the Earth's radiation budget or remove greenhouse gases such as CO 2 from the atmosphere. When focused on CO 2, the latter of these categories is called carbon dioxide removal (CDR). Future emission scenarios that stay well below 2 °C, and all emissionmore » scenarios that do not exceed 1.5 °C warming by the year 2100, require some form of CDR. At present, there is little consensus on the climate impacts and atmospheric CO 2 reduction efficacy of the different types of proposed CDR. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDRMIP) was initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDRMIP experiments, which are formally part of the 6th Coupled Model Intercomparison Project (CMIP6). These experiments are designed to address questions concerning CDR-induced climate reversibility, the response of the Earth system to direct atmospheric CO 2 removal (direct air capture and storage), and the CDR potential and impacts of afforestation and reforestation, as well as ocean alkalinization.>« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.8697S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.8697S">The IS-ENES climate4impact portal: bridging the CMIP5 and CORDEX data to impact users</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Som de Cerff, Wim; Plieger, Maarten; Page, Christian; Tatarinova, Natalia; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Sjökvist, Elin; Vega Saldarriaga, Manuel; Santiago Cofiño Gonzalez, Antonio 2015-04-01 The aim of climate4impact (climate4impact.eu) is to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. The portal is based on 17 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. It has been developed within the IS-ENES European project and is currently operated and further developed in the IS ENES2 project. As the climate impact community is very broad, the focus is mainly on the scientific impact community. Climate4impact is connected to the Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and regional climate model data (RCM) data from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services using OpenID, and offers a user interface for searching, visualizing and downloading global climate model data and more. A challenging task is to describe the available model data and how it can be used. The portal informs users about possible caveats when using climate model data. All impact use cases are described in the documentation section, using highlighted keywords pointing to detailed information in the glossary. Climate4impact currently has two main objectives. The first one is to work on a web interface which automatically generates a graphical user interface on WPS endpoints. The WPS calculates climate indices and subset data using OpenClimateGIS/icclim on data stored in ESGF data nodes. Data is then transmitted from ESGF nodes over secured OpenDAP and becomes available in a new, per user, secured OpenDAP server. The results can then be visualized again using ADAGUC WMS. Dedicated wizards for processing of climate indices will be developed in close collaboration with users. The second one is to expose climate4impact services, so as to offer standardized services which can be used by other portals (like the future Copernicus platform, developed in the EU FP7 CLIPC project). This has the advantage to add interoperability between several portals, as well as to enable the design of specific portals aimed at different impact communities, either thematic or national. In the presentation the following subjects will be detailed: - Lessons learned developing climate4impact.eu - Download: Directly from ESGF nodes and other THREDDS catalogs - Connection with the downscaling portal of the university of Cantabria - Experiences on the question and answer site via Askbot - Visualization: Visualize data from ESGF data nodes using ADAGUC Web Map Services. - Processing: Transform data, subset, export into other formats, and perform climate indices calculations using Web Processing Services implemented by PyWPS, based on NCAR NCPP OpenClimateGIS and IS-ENES2 icclim. - Security: Login using OpenID for access to the ESGF data nodes. The ESGF works in conjunction with several external websites and systems. The climate4impact portal uses X509 based short lived credentials, generated on behalf of the user with a MyProxy service. Single Sign-on (SSO) is used to make these websites and systems work together. - Discovery: Facetted search based on e.g. variable name, model and institute using the ESGF search services. A catalog browser allows for browsing through CMIP5 and any other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.2973L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.2973L">The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lawrence, David M.; Hurtt, George C.; Arneth, Almut; Brovkin, Victor; Calvin, Kate V.; Jones, Andrew D.; Jones, Chris D.; Lawrence, Peter J.; de Noblet-Ducoudré, Nathalie; Pongratz, Julia; Seneviratne, Sonia I.; Shevliakova, Elena 2016-09-01 Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-management strategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1377473','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1377473">The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Lawrence, David M.; Hurtt, George C.; Arneth, Almut Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1377473-land-use-model-intercomparison-project-lumip-contribution-cmip6-rationale-experimental-design','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1377473-land-use-model-intercomparison-project-lumip-contribution-cmip6-rationale-experimental-design">The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Lawrence, David M.; Hurtt, George C.; Arneth, Almut; ... 2016-09-02 Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the following questions. (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy, and are there regional land-managementmore » st rategies with the promise to help mitigate climate change? In addressing these questions, LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. There will be particular focus on the separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land use, the unique impacts of land-cover change vs. land-management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent to which impacts of enhanced CO 2 concentrations on plant photosynthesis are modulated by past and future land use.LUMIP involves three major sets of science activities: (1) development of an updated and expanded historical and future land-use data set, (2) an experimental protocol for specific LUMIP experiments for CMIP6, and (3) definition of metrics and diagnostic protocols that quantify model performance, and related sensitivities, with respect to LULCC. In this paper, we describe LUMIP activity (2), i.e., the LUMIP simulations that will formally be part of CMIP6. These experiments are explicitly designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes a two-phase experimental design. Phase one features idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate, as well as to quantify model sensitivity to potential land-cover and land-use change. Phase two experiments focus on quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. This paper documents these simulations in detail, explains their rationale, outlines plans for analysis, and describes a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). It is essential that modeling groups participating in LUMIP adhere to the experimental design as closely as possible and clearly report how the model experiments were executed.« less </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active">10</li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active">11</li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JAMES..10...78D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JAMES..10...78D">A Caveat Note on Tuning in the Development of Coupled Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dommenget, Dietmar; Rezny, Michael 2018-01-01 State-of-the-art coupled general circulation models (CGCMs) have substantial errors in their simulations of climate. In particular, these errors can lead to large uncertainties in the simulated climate response (both globally and regionally) to a doubling of CO2. Currently, tuning of the parameterization schemes in CGCMs is a significant part of the developed. It is not clear whether such tuning actually improves models. The tuning process is (in general) neither documented, nor reproducible. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In this study, ensembles of perturbed physics experiments are performed with the Globally Resolved Energy Balance (GREB) model to test the impact of tuning. The work illustrates that tuning has, in average, limited skill given the complexity of the system, the limited computing resources, and the limited observations to optimize parameters. While tuning may improve model performance (such as reproducing observed past climate), it will not get closer to the "true" physics nor will it significantly improve future climate change projections. Tuning will introduce artificial compensating error interactions between submodels that will hamper further model development. In turn, flux corrections do perform well in most, but not all aspects. A main advantage of flux correction is that it is much cheaper, simpler, more transparent, and it does not introduce artificial error interactions between submodels. These GREB model experiments should be considered as a pilot study to motivate further CGCM studies that address the issues of model tuning. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.5600K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.5600K">Impacts of boundary condition changes on regional climate projections over West Africa</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kim, Jee Hee; Kim, Yeonjoo; Wang, Guiling 2017-06-01 Future projections using regional climate models (RCMs) are driven with boundary conditions (BCs) typically derived from global climate models. Understanding the impact of the various BCs on regional climate projections is critical for characterizing their robustness and uncertainties. In this study, the International Center for Theoretical Physics Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of different aspects of boundary conditions, including lateral BCs and sea surface temperature (SST), on projected future changes of regional climate in West Africa, and BCs from the coupled European Community-Hamburg Atmospheric Model 5/Max Planck Institute Ocean Model are used as an example. Historical, future, and several sensitivity experiments are conducted with various combinations of BCs and CO2 concentration, and differences among the experiments are compared to identify the most important drivers for RCMs. When driven by changes in all factors, the RegCM4-produced future climate changes include significantly drier conditions in Sahel and wetter conditions along the Guinean coast. Changes in CO2 concentration within the RCM domain alone or changes in wind vectors at the domain boundaries alone have minor impact on projected future climate changes. Changes in the atmospheric humidity alone at the domain boundaries lead to a wetter Sahel due to the northward migration of rain belts during summer. This impact, although significant, is offset and dominated by changes of other BC factors (primarily temperature) that cause a drying signal. Future changes of atmospheric temperature at the domain boundaries combined with SST changes over oceans are sufficient to cause a future climate that closely resembles the projection that accounts for all factors combined. Therefore, climate variability and changes simulated by RCMs depend primarily on the variability and change of temperature aspects of the RCM BCs. Moreover, it is found that the response of the RCM climate to different climate change factors is roughly linear in that the projected changes driven by combined factors are close to the sum of projected changes due to each individual factor alone at least for long-term averages. Findings from this study are important for understanding the source(s) of uncertainties in regional climate projections and for designing innovative approaches to climate downscaling and impact assessment. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN21D0071T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN21D0071T">AIRS Obs4MIPs V2 data set</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tian, B. 2017-12-01 The Coupled Model Intercomparison Project (CMIP) has become a central element of national and international assessments of climate change. The CMIP Phase 6 (CMIP6) model experiments will be the foundation for the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), scheduled for publication around 2021. To increase the fidelity of the IPCC AR6, the CMIP6 model experiments need rigorous evaluation. The "Observations for Model Intercomparison Projects" (Obs4MIPs) collects, organizes and publishes various well-established satellite data sets for CMIP model evaluation. The Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU), the NASA's temperature and humidity sounding system on the Aqua satellite, has provided over a decade-long high-quality tropospheric temperature and moisture sounding data. Under the current support of the NASA Data for Operation and Assessment (NDOA) program, we are generating and publishing the AIRS Obs4MIPs V2 data set including the monthly mean tropospheric air temperature, specific humidity, and relative humidity profiles from September 2002 to September 2016. This will provide the latest AIRS data in Obs4MIPs and assist the climate modeling community to better use the AIRS data for CMIP (including CMIP3, CMIP5, and CMIP6) model evaluation. In this presentation, we will discuss the AIRS Obs4MIPs V2 data set and their possible use for CMIP6 climate model evaluation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711175B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711175B">Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier 2015-04-01 At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29867150','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29867150">Role of subsurface ocean in decadal climate predictability over the South Atlantic.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Morioka, Yushi; Doi, Takeshi; Storto, Andrea; Masina, Simona; Behera, Swadhin K 2018-06-04 Decadal climate predictability in the South Atlantic is explored by performing reforecast experiments using a coupled general circulation model with two initialization schemes; one is assimilated with observed sea surface temperature (SST) only, and the other is additionally assimilated with observed subsurface ocean temperature and salinity. The South Atlantic is known to undergo decadal variability exhibiting a meridional dipole of SST anomalies through variations in the subtropical high and ocean heat transport. Decadal reforecast experiments in which only the model SST is initialized with the observation do not predict well the observed decadal SST variability in the South Atlantic, while the other experiments in which the model SST and subsurface ocean are initialized with the observation skillfully predict the observed decadal SST variability, particularly in the Southeast Atlantic. In-depth analysis of upper-ocean heat content reveals that a significant improvement of zonal heat transport in the Southeast Atlantic leads to skillful prediction of decadal SST variability there. These results demonstrate potential roles of subsurface ocean assimilation in the skillful prediction of decadal climate variability over the South Atlantic. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.5198Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.5198Z">Assessing the contribution of different factors in RegCM4.3 regional climate model projections using the Factor Separation method over the Med-CORDEX domain</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zsolt Torma, Csaba; Giorgi, Filippo 2014-05-01 A set of regional climate model (RCM) simulations applying dynamical downscaling of global climate model (GCM) simulations over the Mediterranean domain specified by the international initiative Coordinated Regional Downscaling Experiment (CORDEX) were completed with the Regional Climate Model RegCM, version RegCM4.3. Two GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the RegCM: HadGEM2-ES (HadGEM) and MPI-ESM-MR (MPI). The simulations consist of an ensemble including multiple physics configurations and different "Reference Concentration Pathways" (RCP4.5 and RCP8.5). In total 15 simulations were carried out with 7 model physics configurations with varying convection and land surface schemes. The horizontal grid spacing of the RCM simulations is 50 km and the simulated period in all cases is 1970-2100 (1970-2099 in case of HadGEM driven simulations). This ensemble includes a combination of experiments in which different model components are changed individually and in combination, and thus lends itself optimally to the application of the Factor Separation (FS) method. This study applies the FS method to investigate the contributions of different factors, along with their synergy, on a set of regional climate model (RCM) projections for the Mediterranean region. The FS method is applied to 6 projections for the period 1970-2100 performed with the regional model RegCM4.3 over the Med-CORDEX domain. Two different sets of factors are intercompared, namely the driving global climate model (HadGEM and MPI) boundary conditions against two model physics settings (convection scheme and irrigation). We find that both the GCM driving conditions and the model physics provide important contributions, depending on the variable analyzed (surface air temperature and precipitation), season (winter vs. summer) and time horizon into the future, while the synergy term mostly tends to counterbalance the contributions of the individual factors. We demonstrate the usefulness of the FS method to assess different sources of uncertainty in RCM-based regional climate projections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140012059','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140012059">Characteristics of Tropical Cyclones in High-Resolution Models of the Present Climate</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, Jeffery A.; Kim, Daeyhun; Kumar, Arun; LaRow, Timothy E.; Lim, Young-Kwon; Murakami, Hiroyuki; Roberts, Malcolm J.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140012059'); toggleEditAbsImage('author_20140012059_show'); toggleEditAbsImage('author_20140012059_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140012059_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140012059_hide"> 2014-01-01 The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) in two types of experiments, using a climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150000770','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000770">Characteristics of Tropical Cyclones in High-resolution Models in the Present Climate</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, Jeffrey A.; Kim, Daehyun; Kumar, Arun; LaRow, Timothy E.; Lim, Young-Kwon; Murakami, Hiroyuki; Reed, Kevin; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20150000770'); toggleEditAbsImage('author_20150000770_show'); toggleEditAbsImage('author_20150000770_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20150000770_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20150000770_hide"> 2014-01-01 The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010HESSD...7.2915F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010HESSD...7.2915F">Physical and chemical consequences of artificially deepened thermocline in a small humic lake - a paired whole-lake climate change experiment</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Forsius, M.; Saloranta, T.; Arvola, L.; Salo, S.; Verta, M.; Ala-Opas, P.; Rask, M.; Vuorenmaa, J. 2010-05-01 Climate change with higher air temperatures and changes in cloud cover, radiation and wind speed alters the heat balance and stratification patterns of lakes. A paired whole-lake thermocline manipulation experiment of a small (0.047 km2) shallow dystrophic lake (Halsjärvi) was carried out in southern Finland. A thermodynamic model (MyLake) was used for both predicting the impacts of climate change scenarios and for determining the manipulation target of the experiment. The model simulations assuming several climate change scenarios indicated large increases in the whole-lake monthly mean temperature (+1.4-4.4 °C in April-October for the A2 scenario), and shortening of the length of the ice covered period by 56-89 days. The thermocline manipulation resulted in large changes in the thermodynamic properties of the lake, and those were rather well consistent with the simulated future increases in the heat content during the summer-autumn season. The manipulation also resulted in changes in the oxygen stratification, and the expansion of the oxic water layer increased the spatial extent of the sediment surface oxic-anoxic interfaces. The experiment also affected several other chemical constituents; concentrations of TotN, NH4 and organic carbon showed a statistically significant decrease, likely due to both unusual hydrological conditions during the experiment period and increased decomposition and sedimentation. Changes in mercury processes and in the aquatic food web were also introduced. In comparison with the results of a similar whole-lake manipulation experiment in a deep, oligotrophic, clear-watered lake in Norway, it is evident that shallow dystrophic lakes, common in the boreal region, are more sensitive to physical perturbations. This means that projected climate change may strongly modify their physical and chemical conditions in the future. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMED31E..02P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMED31E..02P">Teaching Climate Change to Future Teachers Using 'Real' Data: Challenges and Opportunities (Invited)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Petcovic, H. L.; Barone, S.; Fulford, J. 2013-12-01 A climate-literate public is essential to resolving pressing problems related to global change. Future elementary teachers are a critical audience in climate and climate change education, as they will introduce children in early grades (USA grades K-8, children ages 5-14) to fundamentals of the climate system, natural and anthropogenic drivers of climate change, and impacts of global change on human and natural systems. Here we describe challenges we have encountered in teaching topics of the carbon cycle, greenhouse gases, past climate, recent anthropogenic change, and carbon footprints to future elementary teachers. We also describe how we have met (to varying degrees of success) these challenges in an introductory earth science course that is specifically designed for this audience. Two prominent challenges we have encountered are: the complex nature of the scientific content of climate change, and robust misconceptions held by our students about these topics. To address the first challenge, we attempt to adjust the scientific content to a level appropriate for future K-8 teachers, without sacrificing too much accuracy or critical detail. To address the second challenge, we explicitly discuss alternate conceptions of each topic. The use of authentic data sets can also address both of these challenges. Yet incorporating 'real' climate and paleoclimate data into the classroom poses still an additional challenge of instructional design. We use a variety of teaching approaches in our laboratory-based course including student-designed experiments, computer simulations, physical models, and authentic data sets. We have found that students strongly prefer the physical models and experiments, because these are 'hands-on' and perceived as easily adaptable to the K-8 classroom. Students often express dislike for activities that use authentic data sets (for example, an activity using graphs of CO2 and methane concentrations in Vostok ice cores), in particular because they have difficulty interpreting graphs. To respond to this concern, we couple physical models/experiments with data sets in a guided inquiry teaching format in order to satisfy those students who prefer 'hands-on' learning yet tie the models to the real world. Pre/post testing of students shows that this method is effective in most topics, yet future teachers still struggle with identifying natural versus anthropogenic drivers of climate change. We continue to address these challenges in future course modifications. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JAMES..10..207L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JAMES..10..207L">Adjoint-Based Climate Model Tuning: Application to the Planet Simulator</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef 2018-01-01 The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813139K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813139K">From Past to future: the Paleoclimate Modelling Intercomparison Project's contribution to CMIP6</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kageyama, Masa; Braconnot, Pascale; Harrison, Sandy; Haywood, Alan; Jungclaus, Johann; Otto-Bliesner, Bette; Abe-Ouchi, Ayako 2016-04-01 Since the 1990s, PMIP has developed with the following objectives: 1/to evaluate the ability of climate models used for climate prediction in simulating well-documented past climates outside the range of present and recent climate variability; 2/to understand the mechanisms of these climate changes, in particular the role of the different climate feedbacks. To achieve these goals, PMIP has actively fostered paleo-data syntheses, multi-model analyses, including analyses of relationships between model results from past and future simulations, and model-data comparisons. For CMIP6, PMIP will focus on five past periods: - the Last Millennium (850 CE - present), to analyse natural climate variability on multidecadal or longer time-scales - the mid-Holocene, 6000 years ago, to compare model runs with paleodata for a period of warmer climate in the Northern Hemisphere, with an enhanced hydrological cycle - the Last Glacial Maximum, 21000 years ago, to evaluate the ability of climate models to represent a cold climate extreme and examine whether paleoinformation about this period can help and constrain climate sensitivity - the Last InterGlacial (~127,000 year ago), which provides a benchmark for a period of high sea-level stand - the mid-Pliocene warm period (~3.2 million years ago), which allows for the evaluation of the model's long-term response to a CO2 level analogous to the modern one. This poster will present the rationale of these "PMIP4-CMIP6" experiments. Participants are invited to come and discuss about the experimental set-up and the model output to be distributed via CMIP6. For more information and discussion of the PMIP4-CMIP6 experimental design, please visit: https://wiki.lsce.ipsl.fr/pmip3/doku.php/pmip3:cmip6:design:index </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1439208','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1439208">What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Di Vittorio, Alan V.; Kyle, Page; Collins, William D. Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1439208-what-effects-agro-ecological-zones-land-use-region-boundaries-land-resource-projection-using-global-change-assessment-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1439208-what-effects-agro-ecological-zones-land-use-region-boundaries-land-resource-projection-using-global-change-assessment-model">What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Di Vittorio, Alan V.; Kyle, Page; Collins, William D. 2016-09-03 Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMPP51A1928S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMPP51A1928S">Simulations of Western North American Hydroclimate during the Little Ice Age and Medieval Climate Anomaly</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Simon, S. M.; Mann, M. E.; Steinman, B. A.; Feng, S.; Zhang, Y.; Miller, S. K. 2013-12-01 Despite the immense impact that large, modern North American droughts, such as those of the 1930s and 1950s, have had on economic, social, aquacultural, and agricultural systems, they are smaller in duration and magnitude than the multidecadal megadroughts that affected North America, in particular the western United States, during the Medieval Climate Anomaly (MCA, ~ 900-1300 AD) and the Little Age (LIA, ~1450-1850 AD). Although various proxy records have been used to reconstruct the timing of these MCA and LIA megadroughts in the western United States, there still exists great uncertainty in the magnitude and spatial coherence of such droughts in the Pacific Northwest region, especially on decadal to centennial timescales. This uncertainty motivates the following study to establish a causal link between the climate forcing that induced these megadroughts and the spatiotemporal response of regional North American hydroclimates to this forcing. This study seeks to establish a better understanding of the influence of tropical Pacific and North Atlantic SSTs on North American drought during the MCA and LIA. We force NCAR's Community Atmospheric Model version 5.1.1 (CAM 5) with prescribed proxy-reconstructed tropical Pacific and North Atlantic SST anomalies from the MCA and LIA, in order to investigate the influence that these SST anomalies had on the spatiotemporal patterns of drought in North America. To isolate the effects of individual ocean basin SSTs on the North American climate system, the model experiments use a variety of SST permutations in the tropical Pacific and North Atlantic basin as external forcing. In order to quantify the spatiotemporal response of the North American climate system to these SST forcing permutations, temperature and precipitation data derived from the MCA and LIA model experiments are compared to lake sediment isotope and tree ring-based hydroclimate reconstructions from the Pacific Northwest. The spatiotemporal temperature and precipitation patterns from the model experiments indicate that in the Pacific Northwest, the MCA and LIA were anomalously wet and dry periods, respectively, a finding that is largely supported by the lake sediment records. This pattern contrasts with the dry MCA/wet LIA pattern diagnosed in model experiments for the U.S Southwest and indicated by tree ring-based proxy data. Thus, the CAM 5 model experiments confirm the wet/dry dipole pattern suggested by proxy data for the western U.S. during the MCA and LIA and highlights the role that the natural variability of tropical Pacific and North Atlantic SSTs played in driving this spatiotemporal climate pattern and its related teleconnections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1412913A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1412913A">Scientific workflow and support for high resolution global climate modeling at the Oak Ridge Leadership Computing Facility</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Anantharaj, V.; Mayer, B.; Wang, F.; Hack, J.; McKenna, D.; Hartman-Baker, R. 2012-04-01 The Oak Ridge Leadership Computing Facility (OLCF) facilitates the execution of computational experiments that require tens of millions of CPU hours (typically using thousands of processors simultaneously) while generating hundreds of terabytes of data. A set of ultra high resolution climate experiments in progress, using the Community Earth System Model (CESM), will produce over 35,000 files, ranging in sizes from 21 MB to 110 GB each. The execution of the experiments will require nearly 70 Million CPU hours on the Jaguar and Titan supercomputers at OLCF. The total volume of the output from these climate modeling experiments will be in excess of 300 TB. This model output must then be archived, analyzed, distributed to the project partners in a timely manner, and also made available more broadly. Meeting this challenge would require efficient movement of the data, staging the simulation output to a large and fast file system that provides high volume access to other computational systems used to analyze the data and synthesize results. This file system also needs to be accessible via high speed networks to an archival system that can provide long term reliable storage. Ideally this archival system is itself directly available to other systems that can be used to host services making the data and analysis available to the participants in the distributed research project and to the broader climate community. The various resources available at the OLCF now support this workflow. The available systems include the new Jaguar Cray XK6 2.63 petaflops (estimated) supercomputer, the 10 PB Spider center-wide parallel file system, the Lens/EVEREST analysis and visualization system, the HPSS archival storage system, the Earth System Grid (ESG), and the ORNL Climate Data Server (CDS). The ESG features federated services, search & discovery, extensive data handling capabilities, deep storage access, and Live Access Server (LAS) integration. The scientific workflow enabled on these systems, and developed as part of the Ultra-High Resolution Climate Modeling Project, allows users of OLCF resources to efficiently share simulated data, often multi-terabyte in volume, as well as the results from the modeling experiments and various synthesized products derived from these simulations. The final objective in the exercise is to ensure that the simulation results and the enhanced understanding will serve the needs of a diverse group of stakeholders across the world, including our research partners in U.S. Department of Energy laboratories & universities, domain scientists, students (K-12 as well as higher education), resource managers, decision makers, and the general public. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA.....5651K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA.....5651K">Climate Change and Runoff Statistics: a Process Study for the Rhine Basin using a coupled Climate-Runoff Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kleinn, J.; Frei, C.; Gurtz, J.; Vidale, P. L.; Schär, C. 2003-04-01 The consequences of extreme runoff and extreme water levels are within the most important weather induced natural hazards. The question about the impact of a global climate change on the runoff regime, especially on the frequency of floods, is of utmost importance. In winter-time, two possible climate effects could influence the runoff statistis of large Central European rivers: the shift from snowfall to rain as a consequence of higher temperatures and the increase of heavy precipitation events due to an intensification of the hydrological cycle. The combined effect on the runoff statistics is examined in this study for the river Rhine. To this end, sensitivity experiments with a model chain including a regional climate model and a distributed runoff model are presented. The experiments are based on an idealized surrogate climate change scenario which stipulates a uniform increase in temperature by 2 Kelvin and an increase in atmospheric specific humidity by 15% (resulting from unchanged relative humidity) in the forcing fields for the regional climate model. The regional climate model CHRM is based on the mesoscale weather prediction model HRM of the German Weather Service (DWD) and has been adapted for climate simulations. The model is being used in a nested mode with horizontal resolutions of 56 km and 14 km. The boundary conditions are taken from the original ECMWF reanalysis and from a modified version representing the surrogate scenario. The distributed runoff model (WaSiM) is used at a horizontal resolution of 1 km for the whole Rhine basin down to Cologne. The coupling of the models is provided by a downscaling of the climate model fields (precipitaion, temperature, radiation, humidity, and wind) to the resolution of the distributed runoff model. The simulations cover the period of September 1987 to January 1994 with a special emphasis on the five winter seasons 1989/90 until 1993/94, each from November until January. A detailed validation of the control simulation shows a good correspondence of the precipitation fields from the regional climate model with measured fields regarding the distribution of precipitation at the scale of the Rhine basin. Systematic errors are visible at the scale of single subcatchements, in the altitudinal distribution and in the frequency distribution of precipitation. These errors only marginally affect the runoff simulations, which show good correspondence with runoff observations. The presentation includes results from the scenario simulations for the whole basin as well as for Alpine and lowland subcatchements. The change in the runoff statistics is being analyzed with respect to the changes in snowfall and to the fequency distribution of precipitation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5734685','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5734685">Which climate change path are we following? Bad news from Scots pine</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> D’Andrea, Ettore; Rezaie, Negar; Cammarano, Mario; Matteucci, Giorgio 2017-01-01 Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated. PMID:29252985 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29252985','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29252985">Which climate change path are we following? Bad news from Scots pine.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bombi, Pierluigi; D'Andrea, Ettore; Rezaie, Negar; Cammarano, Mario; Matteucci, Giorgio 2017-01-01 Current expectations on future climate derive from coordinated experiments, which compile many climate models for sampling the entire uncertainty related to emission scenarios, initial conditions, and modelling process. Quantifying this uncertainty is important for taking decisions that are robust under a wide range of possible future conditions. Nevertheless, if uncertainty is too large, it can prevent from planning specific and effective measures. For this reason, reducing the spectrum of the possible scenarios to a small number of one or a few models that actually represent the climate pathway influencing natural ecosystems would substantially increase our planning capacity. Here we adopt a multidisciplinary approach based on the comparison of observed and expected spatial patterns of response to climate change in order to identify which specific models, among those included in the CMIP5, catch the real climate variation driving the response of natural ecosystems. We used dendrochronological analyses for determining the geographic pattern of recent growth trends for three European species of trees. At the same time, we modelled the climatic niche for the same species and forecasted the suitability variation expected across Europe under each different GCM. Finally, we estimated how well each GCM explains the real response of ecosystems, by comparing the expected variation with the observed growth trends. Doing this, we identified four climatic models that are coherent with the observed trends. These models are close to the highest range limit of the climatic variations expected by the ensemble of the CMIP5 models, suggesting that current predictions of climate change impacts on ecosystems could be underestimated. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160002946','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160002946">Big Data Challenges in Climate Science: Improving the Next-Generation Cyberinfrastructure</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schnase, John L.; Lee, Tsengdar J.; Mattmann, Chris A.; Lynnes, Christopher S.; Cinquini, Luca; Ramirez, Paul M.; Hart, Andre F.; Williams, Dean N.; Waliser, Duane; Rinsland, Pamela; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160002946'); toggleEditAbsImage('author_20160002946_show'); toggleEditAbsImage('author_20160002946_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160002946_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160002946_hide"> 2016-01-01 The knowledge we gain from research in climate science depends on the generation, dissemination, and analysis of high-quality data. This work comprises technical practice as well as social practice, both of which are distinguished by their massive scale and global reach. As a result, the amount of data involved in climate research is growing at an unprecedented rate. Climate model intercomparison (CMIP) experiments, the integration of observational data and climate reanalysis data with climate model outputs, as seen in the Obs4MIPs, Ana4MIPs, and CREATE-IP activities, and the collaborative work of the Intergovernmental Panel on Climate Change (IPCC) provide examples of the types of activities that increasingly require an improved cyberinfrastructure for dealing with large amounts of critical scientific data. This paper provides an overview of some of climate science's big data problems and the technical solutions being developed to advance data publication, climate analytics as a service, and interoperability within the Earth System Grid Federation (ESGF), the primary cyberinfrastructure currently supporting global climate research activities. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active">11</li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active">12</li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28207766','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28207766">Climate Change Across Seasons Experiment (CCASE): A new method for simulating future climate in seasonally snow-covered ecosystems.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Templer, Pamela H; Reinmann, Andrew B; Sanders-DeMott, Rebecca; Sorensen, Patrick O; Juice, Stephanie M; Bowles, Francis; Sofen, Laura E; Harrison, Jamie L; Halm, Ian; Rustad, Lindsey; Martin, Mary E; Grant, Nicholas 2017-01-01 Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5313155','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5313155">Climate Change Across Seasons Experiment (CCASE): A new method for simulating future climate in seasonally snow-covered ecosystems</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Templer, Pamela H.; Reinmann, Andrew B.; Sanders-DeMott, Rebecca; Sorensen, Patrick O.; Juice, Stephanie M.; Bowles, Francis; Sofen, Laura E.; Harrison, Jamie L.; Halm, Ian; Rustad, Lindsey; Martin, Mary E.; Grant, Nicholas 2017-01-01 Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise. PMID:28207766 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21H3130P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21H3130P">The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pincus, R.; Stevens, B. B.; Forster, P.; Collins, W.; Ramaswamy, V. 2014-12-01 The Radiative Forcing Model Intercomparison Project (RFMIP): Assessment and characterization of forcing to enable feedback studies An enormous amount of attention has been paid to the diversity of responses in the CMIP and other multi-model ensembles. This diversity is normally interpreted as a distribution in climate sensitivity driven by some distribution of feedback mechanisms. Identification of these feedbacks relies on precise identification of the forcing to which each model is subject, including distinguishing true error from model diversity. The Radiative Forcing Model Intercomparison Project (RFMIP) aims to disentangle the role of forcing from model sensitivity as determinants of varying climate model response by carefully characterizing the radiative forcing to which such models are subject and by coordinating experiments in which it is specified. RFMIP consists of four activities: 1) An assessment of accuracy in flux and forcing calculations for greenhouse gases under past, present, and future climates, using off-line radiative transfer calculations in specified atmospheres with climate model parameterizations and reference models 2) Characterization and assessment of model-specific historical forcing by anthropogenic aerosols, based on coordinated diagnostic output from climate models and off-line radiative transfer calculations with reference models 3) Characterization of model-specific effective radiative forcing, including contributions of model climatology and rapid adjustments, using coordinated climate model integrations and off-line radiative transfer calculations with a single fast model 4) Assessment of climate model response to precisely-characterized radiative forcing over the historical record, including efforts to infer true historical forcing from patterns of response, by direct specification of non-greenhouse-gas forcing in a series of coordinated climate model integrations This talk discusses the rationale for RFMIP, provides an overview of the four activities, and presents preliminary motivating results. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26680131','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26680131">Mesocosms Reveal Ecological Surprises from Climate Change.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Fordham, Damien A 2015-12-01 Understanding, predicting, and mitigating the impacts of climate change on biodiversity poses one of the most crucial challenges this century. Currently, we know more about how future climates are likely to shift across the globe than about how species will respond to these changes. Two recent studies show how mesocosm experiments can hasten understanding of the ecological consequences of climate change on species' extinction risk, community structure, and ecosystem functions. Using a large-scale terrestrial warming experiment, Bestion et al. provide the first direct evidence that future global warming can increase extinction risk for temperate ectotherms. Using aquatic mesocosms, Yvon-Durocher et al. show that human-induced climate change could, in some cases, actually enhance the diversity of local communities, increasing productivity. Blending these theoretical and empirical results with computational models will improve forecasts of biodiversity loss and altered ecosystem processes due to climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC43C0746W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC43C0746W">Isolating the Effects of the Warming Trend from the General Climate Change in Water Resources: California Case</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, J.; Yin, H.; Chung, F. 2008-12-01 While the population growth, the future land use change, and the desire for better environmental preservation and protection are adding up pressure on water resources management in California, California is facing an extra challenge of addressing potential climate change impacts on water supple and demand in California. The concerns on water facilities planning and flood control caused by climate change include modified precipitation patterns, changes in snow levels and runoff patterns due to increased air temperatures. Although long-term climate projections are largely uncertain, there appears to be a strong consistency in predicting the warming trend of future surface temperature, and the resulting shift in the seasonal patterns of runoff. However, projected changes in precipitation (wetting or drying), which control annual runoff, are far less certain. This paper attempts to separate the effects of warming trend from the effects of precipitation trend on water planning especially in California where reservoir operations are more sensitive to seasonal patterns of runoff than to the total annual runoff. The water resources systems planning model, CALSIM2, is used to evaluate climate change impact on water resource management in California. Rather than directly ingesting estimated streamflows from climate model projections into CALSIM2, a three step perturbation ratio method is proposed to introduce climate change impact into the planning model. Firstly, monthly perturbation ratio of projected monthly inflow to simulated historical monthly inflow is applied to observed historical monthly inflow to generate climate change inflows to major dams and reservoirs. To isolate the effects of warming trend on water resources, a further annual inflow adjustment is applied to the inflows generated in step one to preserve the volume of the observed annual inflow. To re-introduce the effects of precipitation trend on water resources, an additional inflow trend adjustment is applied to the adjusted climate change inflow. Therefore, three CALSIM2 experiments will be implemented: (1) base run with the observed historic inflow (1921 to 2003); (2) sensitivity run with the adjusted climate change inflow through annual inflow adjustment; (3) sensitivity run with the adjusted climate change inflow through annual inflow adjustment and inflow trend adjustment. To account for the variability of various climate models in projecting future climates, the uncertainty in future emission scenarios, and the difference in different projection periods, estimated inflows from 6 climate models for 2 emission scenarios (A2 and B1) and two projection periods (2030-2059 and 2070-2099) are included in the CALSIM model experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.2853J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.2853J">C4MIP - The Coupled Climate-Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre; Bopp, Laurent; Brovkin, Victor; Dunne, John; Graven, Heather; Hoffman, Forrest; Ilyina, Tatiana; John, Jasmin G.; Jung, Martin; Kawamiya, Michio; Koven, Charlie; Pongratz, Julia; Raddatz, Thomas; Randerson, James T.; Zaehle, Sönke 2016-08-01 Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMIN13A1098M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMIN13A1098M">Modeling and Analysis Compute Environments, Utilizing Virtualization Technology in the Climate and Earth Systems Science domain</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Michaelis, A.; Nemani, R. R.; Wang, W.; Votava, P.; Hashimoto, H. 2010-12-01 Given the increasing complexity of climate modeling and analysis tools, it is often difficult and expensive to build or recreate an exact replica of the software compute environment used in past experiments. With the recent development of new technologies for hardware virtualization, an opportunity exists to create full modeling, analysis and compute environments that are “archiveable”, transferable and may be easily shared amongst a scientific community or presented to a bureaucratic body if the need arises. By encapsulating and entire modeling and analysis environment in a virtual machine image, others may quickly gain access to the fully built system used in past experiments, potentially easing the task and reducing the costs of reproducing and verify past results produced by other researchers. Moreover, these virtual machine images may be used as a pedagogical tool for others that are interested in performing an academic exercise but don't yet possess the broad expertise required. We built two virtual machine images, one with the Community Earth System Model (CESM) and one with Weather Research Forecast Model (WRF), then ran several small experiments to assess the feasibility, performance overheads costs, reusability, and transferability. We present a list of the pros and cons as well as lessoned learned from utilizing virtualization technology in the climate and earth systems modeling domain. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160000444&hterms=wheat&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dwheat','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160000444&hterms=wheat&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dwheat">Benchmark Data Set for Wheat Growth Models: Field Experiments and AgMIP Multi-Model Simulations.</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Asseng, S.; Ewert, F.; Martre, P.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.J.; Rotter, R. P. 2015-01-01 The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170005725','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170005725">2016 International Land Model Benchmarking (ILAMB) Workshop Report</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen; Lawrence, David M.; Riley, William J.; Randerson, James T.; Ahlstrom, Anders; Abramowitz, Gabriel; Baldocchi, Dennis D.; Best, Martin J.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170005725'); toggleEditAbsImage('author_20170005725_show'); toggleEditAbsImage('author_20170005725_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170005725_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170005725_hide"> 2016-01-01 As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT........10Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT........10Y">Statistical and dynamical assessment of land-ocean-atmosphere interactions across North Africa</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yu, Yan North Africa is highly vulnerable to hydrologic variability and extremes, including impacts of climate change. The current understanding of oceanic versus terrestrial drivers of North African droughts and pluvials is largely model-based, with vast disagreement among models in terms of the simulated oceanic impacts and vegetation feedbacks. Regarding oceanic impacts, the relative importance of the tropical Pacific, tropical Indian, and tropical Atlantic Oceans in regulating the North African rainfall variability, as well as the underlying mechanism, remains debated among different modeling studies. Classic theory of land-atmosphere interactions across the Sahel ecotone, largely based on climate modeling experiments, has promoted positive vegetation-rainfall feedbacks associated with a dominant surface albedo mechanism. However, neither the proposed positive vegetation-rainfall feedback with its underlying albedo mechanism, nor its relative importance compared with oceanic drivers, has been convincingly demonstrated up to now using observational data. Here, the multivariate Generalized Equilibrium Feedback Assessment (GEFA) is applied in order to identify the observed oceanic and terrestrial drivers of North African climate and quantify their impacts. The reliability of the statistical GEFA method is first evaluated against dynamical experiments within the Community Earth System Model (CESM). In order to reduce the sampling error caused by short data records, the traditional GEFA approach is refined through stepwise GEFA, in which unimportant forcings are dropped through stepwise selection. In order to evaluate GEFA's reliability in capturing oceanic impacts, the atmospheric response to a sea-surface temperature (SST) forcing across the tropical Pacific, tropical Indian, and tropical Atlantic Ocean is estimated independently through ensembles of dynamical experiments and compared with GEFA-based assessments. Furthermore, GEFA's performance in capturing terrestrial impacts is evaluated through ensembles of fully coupled CESM dynamical experiments, with modified leaf area index (LAI) and soil moisture across the Sahel or West African Monsoon (WAM) region. The atmospheric responses to oceanic and terrestrial forcings are generally consistent between the dynamical experiments and statistical GEFA, confirming GEFA's capability of isolating the individual impacts of oceanic and terrestrial forcings on North African climate. Furthermore, with the incorporation of stepwise selection, GEFA can now provide reliable estimates of the oceanic and terrestrial impacts on the North African climate with the typical length of observational datasets, thereby enhancing the method's applicability. After the successful validation of GEFA, the key observed oceanic and terrestrial drivers of North African climate are identified through the application of GEFA to gridded observations, remote sensing products, and reanalyses. According to GEFA, oceanic drivers dominate over terrestrial drivers in terms of their observed impacts on North African climate in most seasons. Terrestrial impacts are comparable to, or more important than, oceanic impacts on rainfall during the post-monsoon across the Sahel and WAM region, and after the short rain across the Horn of Africa (HOA). The key ocean basins that regulate North African rainfall are typically located in the tropics. While the observed impacts of SST variability across the tropical Pacific and tropical Atlantic Oceans on the Sahel rainfall are largely consistent with previous model-based findings, minimal impacts from tropical Indian Ocean variability on Sahel rainfall are identified in observations, in contrast to previous modeling studies. The current observational analysis verifies model-hypothesized positive vegetation-rainfall feedback across the Sahel and HOA, which is confined to the post-monsoon and post-short rains season, respectively. However, the observed positive vegetation feedback to rainfall in the semi-arid Sahel and HOA is largely due to moisture recycling, rather than the classic albedo mechanism. Future projections of Sahel rainfall remain highly uncertain in terms of both sign and magnitude within phases three and five of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The GEFA-based observational analyses will provide a benchmark for evaluating climate models, which will facilitate effective process-based model weighting for more reliable projections of regional climate, as well as model development. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.3879A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.3879A">The North American Regional Climate Change Assessment Program (NARCCAP): Status and results</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Arritt, R. 2009-04-01 NARCCAP is an international program that is generating projections of climate change for the U.S., Canada, and northern Mexico at decision-relevant regional scales. NARCCAP uses multiple limited-area regional climate models (RCMs) nested within multiple atmosphere-ocean general circulation models (AOGCMs). The use of multiple regional and global models allows us to investigate the uncertainty in model responses to future emissions (here, the A2 SRES scenario). The project also includes global time-slice experiments at the same discretization (50 km) using the GFDL atmospheric model (AM2.1) and the NCAR atmospheric model (CAM3). Phase I of the experiment uses the regional models nested within reanalysis in order to establish uncertainty attributable to the RCMs themselves. Phase II of the project then nests the RCMs within results from the current and future runs of the AOGCMs to explore the cascade of uncertainty from the global to the regional models. Phase I has been completed and the results to be shown include findings that spectral nudging is beneficial in some regions but not in others. Phase II is nearing completion and some preliminary results will be shown. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMNH21A1587D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMNH21A1587D">Wind extremes in the North Sea basin under climate change: an ensemble study of 12 CMIP5 GCMs</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> de Winter, R.; Ruessink, G.; Sterl, A. 2012-12-01 Coastal safety may be influenced by climate change, as changes in extreme surge levels and wave extremes may increase the vulnerability of dunes and other coastal defenses. In the North Sea, an area already prone to severe flooding, these high surge levels and waves are generated by severe wind speeds during storm events. As a result of the geometry of the North Sea, not only the maximum wind speed is relevant, but also wind direction. Analyzing changes in a changing climate implies that several uncertainties need to be taken into account. First, there is the uncertainty in climate experiments, which represents the possible development of the emission of greenhouse gases. Second, there is uncertainty between the climate models that are used to analyze the effect of different climate experiments. The third uncertainty is the natural variability of the climate. When this system variability is large, small trends will be difficult to detect. The natural variability results in statistical uncertainty, especially for events with high return values. We addressed the first two types of uncertainties for extreme wind conditions in the North Sea using 12 CMIP5 GCMs. To evaluate the differences between the climate experiments, two climate experiments (rcp4.5 and rcp8.5) from 2050-2100 are compared with historical runs, running from 1950-2000. Rcp4.5 is considered to be a middle climate experiment and rcp8.5 represents high-end climate scenarios. The projections of the 12 GCMs for a given scenario illustrate model uncertainty. We focus on the North Sea basin, because changes in wind conditions could have a large impact on safety of the densely populated North Sea coast, an area that has already a high exposure to flooding. Our results show that, consistent with ERA-Interim results, the annual maximum wind speed in the historical run demonstrates large interannual variability. For the North Sea, the annual maximum wind speed is not projected to change in either rcp4.5 or rcp8.5. In fact, the differences in the 12 GCMs are larger than the difference between the three experiments. Furthermore, our results show that, the variation in direction of annual maximum wind speed is large and this precludes a firm statement on climate-change induced changes in these directions. Nonetheless, most models indicate a decrease in annual maximum wind speed from south-eastern directions and an increase from south-western and western directions. This might be caused by a poleward shift of the storm track. The amount of wind from north-west and north-north-west, wind directions that are responsible for the development of extreme storm surges in the southern part of the North Sea, are not projected to change. However, North Sea coasts that have the longest fetch for western direction, e.g. the German Bight, may encounter more often high storm surge levels and extreme waves when the annual maximum wind will indeed be more often from western direction. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020047055','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020047055">Modeling Feedbacks Between Water and Vegetation in the Climate System</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Miller, James R.; Russell, Gary L.; Hansen, James E. (Technical Monitor) 2001-01-01 Not only is water essential for life on earth, but life itself affects the global hydrologic cycle and consequently the climate of the planet. Whether the global feedbacks between life and the hydrologic cycle tend to stabilize the climate system about some equilibrium level is difficult to assess. We use a global climate model to examine how the presence of vegetation can affect the hydrologic cycle in a particular region. A control for the present climate is compared with a model experiment in which the Sahara Desert is replaced by vegetation in the form of trees and shrubs common to the Sahel region. A second model experiment is designed to identify the separate roles of two different effects of vegetation, namely the modified albedo and the presence of roots that can extract moisture from deeper soil layers. The results show that the presence of vegetation leads to increases in precipitation and soil moisture in western Sahara. In eastern Sahara, the changes are less clear. The increase in soil moisture is greater when the desert albedo is replaced by the vegetation albedo than when both the vegetation albedo and roots are added. The effect of roots is to withdraw water from deeper layers during the dry season. One implication of this study is that the insertion of vegetation into the Sahara modifies the hydrologic cycle so that the vegetation is more likely to persist than initially. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMED31D..02C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMED31D..02C">The NASA Global Climate Change Education Project: An Integrated Effort to Improve the Teaching and Learning about Climate Change (Invited)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chambers, L. H.; Pippin, M. R.; Welch, S.; Spruill, K.; Matthews, M. J.; Person, C. 2010-12-01 The NASA Global Climate Change Education (GCCE) Project, initiated in 2008, seeks to: - improve the teaching and learning about global climate change in elementary and secondary schools, on college campuses, and through lifelong learning; - increase the number of people, particularly high school and undergraduate students, using NASA Earth observation data, Earth system models, and/or simulations to investigate and analyze global climate change issues; - increase the number of undergraduate students prepared for employment and/or to enter graduate school in technical fields relevant to global climate change. Through an annual solicitation, proposals are requested for projects that address these goals using a variety of approaches. These include using NASA Earth system data, interactive models and/or simulations; providing research experiences for undergraduate or community college students, or for pre- or in-service teachers; or creating long-term teacher professional development experiences. To date, 57 projects have been funded to pursue these goals (22 in 2008, 18 in 2009, and 17 in 2010), each for a 2-3 year period. The vast majority of awards address either teacher professional development, or use of data, models, or simulations; only 7 awards have been made for research experiences. NASA, with assistance from the Virginia Space Grant Consortium, is working to develop these awardees into a synergistic community that works together to maximize its impact. This paper will present examples of collaborations that are evolving within this developing community. It will also introduce the opportunities available in fiscal year 2011, when a change in emphasis is expected for the project as it moves within the NASA Office of Education Minority University Research and Education Program (MUREP). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1941459','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1941459">Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Knight, Christopher G.; Knight, Sylvia H. E.; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J.; Kettleborough, Jamie A.; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A.; Allen, Myles R. 2007-01-01 In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally. PMID:17640921 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.B23G..07W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.B23G..07W">Diagnosing and Assessing Uncertainties of the Carbon Cycle in Terrestrial Ecosystem Models from a Multi-Model Ensemble Experiment</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, W.; Dungan, J. L.; Hashimoto, H.; Michaelis, A.; Milesi, C.; Ichii, K.; Nemani, R. R. 2009-12-01 We are conducting an ensemble modeling exercise using the Terrestrial Observation and Prediction System (TOPS) to characterize structural uncertainty in carbon fluxes and stocks estimates from different ecosystem models. The experiment uses public-domain versions of Biome-BGC, LPJ, TOPS-BGC, and CASA, driven by a consistent set of climate fields for North America at 8km resolution and daily/monthly time steps over the period of 1982-2006. A set of diagnostics is developed to characterize the behavior of the models in the climate (temperature-precipitation) space, and to evaluate the simulated carbon cycle in an integrated way. The key findings of this study include that: (relative) optimal primary production is generally found in climate regions where the relationship between annual temperature (T, oC) and precipitation (P, mm) is defined by P = 50*T+500; the ratios between NPP and GPP are close to 50% on average, yet can vary between models and in different climate regions; the allocation of carbon to leaf growth represents a positive feedback to the primary production, and different approaches to constrain this process have significant impacts on the simulated carbon cycle; substantial differences in biomass stocks may be induced by small differences in the tissue turnover rate and the plant mortality; the mean residence time of soil carbon pools is strongly influenced by schemes of temperature regulations; non-respiratory disturbances (e.g., fires) are the main driver for NEP, yet its magnitudes vary between models. Overall, these findings indicate that although the structures of the models are similar, the uncertainties among them can be large, highlighting the problem inherent in relying on only one modeling approach to map surface carbon fluxes or to assess vegetation-climate interactions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC41F0648R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC41F0648R">Maximum warming occurs about one decade after carbon dioxide emission</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ricke, K.; Caldeira, K. 2014-12-01 There has been a long tradition of estimating the amount of climate change that would result from various carbon dioxide emission or concentration scenarios but there has been relatively little quantitative analysis of how long it takes to feel the consequences of an individual carbon dioxide emission. Using conjoined results of recent carbon-cycle and physical-climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6 to 30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. To characterize the carbon cycle uncertainty associated with the global temperature response to a carbon dioxide emission today, we use fits to the time series of carbon dioxide concentrations from a CO2-impulse response function model intercomparison project's 15 ensemble members (1). To characterize both the uncertainty in climate sensitivity and in the thermal inertia of the climate system, we use fits to the time series of global temperature change from the Coupled Model Intercomparison Project phase 5 (CMIP5; 2) abrupt4xco2 experiment's 20 ensemble's members separating the effects of each uncertainty factors using one of two simple physical models for each CMIP5 climate model. This yields 6,000 possible combinations of these three factors using a standard convolution integral approach. Our results indicate that benefits of avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While the relevant time lags imposed by the climate system are substantially shorter than a human lifetime, they are substantially longer than the typical political election cycle, making the delay and its associated uncertainties both economically and politically significant. References: 1. Joos F et al. (2013) Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmos Chem Phys 13:2793-2825. 2. Taylor KE, Stouffer RJ, Meehl GA (2011) An Overview of CMIP5 and the Experiment Design. Bull Am Meteorol Soc 93:485-498. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814513C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814513C">Regional modelling of nitrate leaching from Swiss organic and conventional cropping systems under climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Calitri, Francesca; Necpalova, Magdalena; Lee, Juhwan; Zaccone, Claudio; Spiess, Ernst; Herrera, Juan; Six, Johan 2016-04-01 Organic cropping systems have been promoted as a sustainable alternative to minimize the environmental impacts of conventional practices. Relatively little is known about the potential to reduce NO3-N leaching through the large-scale adoption of organic practices. Moreover, the potential to mitigate NO3-N leaching and thus the N pollution under future climate change through organic farming remain unknown and highly uncertain. Here, we compared regional NO3-N leaching from organic and conventional cropping systems in Switzerland using a terrestrial biogeochemical process-based model DayCent. The objectives of this study are 1) to calibrate and evaluate the model for NO3-N leaching measured under various management practices from three experiments at two sites in Switzerland; 2) to estimate regional NO3-N leaching patterns and their spatial uncertainty in conventional and organic cropping systems (with and without cover crops) for future climate change scenario A1B; 3) to explore the sensitivity of NO3-N leaching to changes in soil and climate variables; and 4) to assess the nitrogen use efficiency for conventional and organic cropping systems with and without cover crops under climate change. The data for model calibration/evaluation were derived from field experiments conducted in Liebefeld (canton Bern) and Eschikon (canton Zürich). These experiments evaluated effects of various cover crops and N fertilizer inputs on NO3-N leaching. The preliminary results suggest that the model was able to explain 50 to 83% of the inter-annual variability in the measured soil drainage (RMSE from 12.32 to 16.89 cm y-1). The annual NO3-N leaching was also simulated satisfactory (RMSE = 3.94 to 6.38 g N m-2 y-1), although the model had difficulty to reproduce the inter-annual variability in the NO3-N leaching losses correctly (R2 = 0.11 to 0.35). Future climate datasets (2010-2099) from the 10 regional climate models (RCM) were used in the simulations. Regional NO3-N leaching predictions for conventional cropping system with a three years rotation (silage maize, potatoes and winter wheat) in Zurich and Bern cantons varied from 6.30 to 16.89 g N m-2 y-1 over a 30-years period. Further simulations and analyses will follow to provide insights into understanding of driving variables and patterns of N losses by leaching in response to changes from conventional to organic cropping systems, and climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23495633','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23495633">Potential changes in forest composition could reduce impacts of climate change on boreal wildfires.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Terrier, Aurélie; Girardin, Martin P; Périé, Catherine; Legendre, Pierre; Bergeron, Yves 2013-01-01 There is general consensus that wildfires in boreal forests will increase throughout this century in response to more severe and frequent drought conditions induced by climate change. However, prediction models generally assume that the vegetation component will remain static over the next few decades. As deciduous species are less flammable than conifer species, it is reasonable to believe that a potential expansion of deciduous species in boreal forests, either occurring naturally or through landscape management, could offset some of the impacts of climate change on the occurrence of boreal wildfires. The objective of this study was to determine the potential of this offsetting effect through a simulation experiment conducted in eastern boreal North America. Predictions of future fire activity were made using multivariate adaptive regression splines (MARS) with fire behavior indices and ecological niche models as predictor variables so as to take into account the effects of changing climate and tree distribution on fire activity. A regional climate model (RCM) was used for predictions of future fire risk conditions. The experiment was conducted under two tree dispersal scenarios: the status quo scenario, in which the distribution of forest types does not differ from the present one, and the unlimited dispersal scenario, which allows forest types to expand their range to fully occupy their climatic niche. Our results show that future warming will create climate conditions that are more prone to fire occurrence. However, unlimited dispersal of southern restricted deciduous species could reduce the impact of climate change on future fire occurrence. Hence, the use of deciduous species could be a good option for an efficient strategic fire mitigation strategy aimed at reducing fire Propagation in coniferous landscapes and increasing public safety in remote populated areas of eastern boreal Canada under climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AdAtS..25..641Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AdAtS..25..641Y">Coupled model simulations of climate changes in the 20th century and beyond</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yu, Yongqiang; Zhi, Hai; Wang, Bin; Wan, Hui; Li, Chao; Liu, Hailong; Li, Wei; Zheng, Weipeng; Zhou, Tianjun 2008-07-01 Several scenario experiments of the IPCC 4th Assessment Report (AR4) are performed by version g1.0 of a Flexible coupled Ocean-Atmosphere-Land System Model (FGOALS) developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), including the “Climate of the 20th century experiment”, “CO2 1% increase per year to doubling experiment” and two separate IPCC greenhouse gases emission scenarios A1B and B1 experiments. To distinguish between the different impacts of natural variations and human activities on the climate change, three-member ensemble runs are performed for each scenario experiment. The coupled model simulations show: (1) from 1900 to 2000, the global mean temperature increases about 0.5°C and the major increase occurs during the later half of the 20th century, which is in consistent with the observations that highlights the coupled model’s ability to reproduce the climate changes since the industrial revolution; (2) the global mean surface air temperature increases about 1.6°C in the CO2 doubling experiment and 1.5°C and 2.4°C in the A1B and B1 scenarios, respectively. The global warming is indicated by not only the changes of the surface temperature and precipitation but also the temperature increase in the deep ocean. The thermal expansion of the sea water would induce the rise of the global mean sea level. Both the control run and the 20th century climate change run are carried out again with version g1.1 of FGOALS, in which the cold biases in the high latitudes were removed. They are then compared with those from version g1.0 of FGOALS in order to distinguish the effect of the model biases on the simulation of global warming. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active">12</li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active">13</li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A23K0380W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A23K0380W">Modeled Response of Greenland Climate to the Presence of Biomass Burning-Based Absorbing Aerosols in the Atmosphere and Snow</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ward, J. L.; Flanner, M.; Bergin, M. H.; Courville, Z.; Dibb, J. E.; Polashenski, C.; Soja, A. J.; Strellis, B. M.; Thomas, J. L. 2016-12-01 Combustion of biomass material results in the emission of microscopic particles, some of which absorb incoming solar radiation. Including black carbon (BC), these absorbing species can affect regional climate through changes in the local column energy budgets, cloud direct and indirect effects, and atmospheric dynamical processes. The cryosphere, which consists of both snow and ice, is unusually susceptible to changes in radiation due to its characteristically high albedo. As the largest element of the cryosphere in the Northern Hemisphere, the Greenland Ice Sheet (GrIS) covers most of Greenland's terrestrial surface and, if subjected to the increased presence of light-absorbing impurities, could experience enhanced melt. A particularly enhanced melt episode of the GrIS occurred during July 2012; at the same time, large-scale biomass burning events were observed in Eurasia and North America. Observations showed that, at the same time, single-scattering albedo (SSA) was lower than average while aerosol optical depth (AOD) was high for the Greenland region. In this study, we apply idealized climate simulations to analyze how various aspects of Greenland's climate are affected by the enhanced presence of particulate matter in the atmospheric and on the surface of the GrIS. We employ the Community Earth System Model (CESM) with prescribed sea surface temperatures and active land and atmospheric components. Using four sets of modeling experiments, we perturb 1) only AOD, 2) only SSA, 3) mass mixing ratios of BC and dust in snow, and 4) both AOD and in-snow impurity concentrations. The chosen values for each of these modeling experiments are based on field measurements taken in 2011 (AOD, SSA) and the summers of 2012-2014 (mass mixing ratios of BC and dust). Comparing the results of these experiments provides information on how the overall climate of Greenland could be affected by large biomass burning events. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GeoRL..42.2951M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GeoRL..42.2951M">Tropical rainforest response to marine sky brightening climate engineering</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Muri, Helene; Niemeier, Ulrike; Kristjánsson, Jón Egill 2015-04-01 Tropical forests represent a major atmospheric carbon dioxide sink. Here the gross primary productivity (GPP) response of tropical rainforests to climate engineering via marine sky brightening under a future scenario is investigated in three Earth system models. The model response is diverse, and in two of the three models, the tropical GPP shows a decrease from the marine sky brightening climate engineering. Partial correlation analysis indicates precipitation to be important in one of those models, while precipitation and temperature are limiting factors in the other. One model experiences a reversal of its Amazon dieback under marine sky brightening. There, the strongest partial correlation of GPP is to temperature and incoming solar radiation at the surface. Carbon fertilization provides a higher future tropical rainforest GPP overall, both with and without climate engineering. Salt damage to plants and soils could be an important aspect of marine sky brightening. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1919112F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1919112F">Large scale and cloud-based multi-model analytics experiments on climate change data in the Earth System Grid Federation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fiore, Sandro; Płóciennik, Marcin; Doutriaux, Charles; Blanquer, Ignacio; Barbera, Roberto; Donvito, Giacinto; Williams, Dean N.; Anantharaj, Valentine; Salomoni, Davide D.; Aloisio, Giovanni 2017-04-01 In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated, such as the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the talk discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC). The general "environment" of the case study relates to: (i) multi-model data analysis inter-comparison challenges; (ii) addressed on CMIP5 data; and (iii) which are made available through the IS-ENES/ESGF infrastructure. The added value of the solution proposed in the INDIGO-DataCloud project are summarized in the following: (i) it implements a different paradigm (from client- to server-side); (ii) it intrinsically reduces data movement; (iii) it makes lightweight the end-user setup; (iv) it fosters re-usability (of data, final/intermediate products, workflows, sessions, etc.) since everything is managed on the server-side; (v) it complements, extends and interoperates with the ESGF stack; (vi) it provides a "tool" for scientists to run multi-model experiments, and finally; and (vii) it can drastically reduce the time-to-solution for these experiments from weeks to hours. At the time the contribution is being written, the proposed testbed represents the first concrete implementation of a distributed multi-model experiment in the ESGF/CMIP context joining server-side and parallel processing, end-to-end workflow management and cloud computing. As opposed to the current scenario based on search & discovery, data download, and client-based data analysis, the INDIGO-DataCloud architectural solution described in this contribution addresses the scientific computing & analytics requirements by providing a paradigm shift based on server-side and high performance big data frameworks jointly with two-level workflow management systems realized at the PaaS level via a cloud infrastructure. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830011121','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830011121">The radiative impact of cumulus cloudiness in a general circulation model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Moeng, C. H.; Randall, D. A. 1982-01-01 The effect of cumulus cloudiness on the radiational heating and, on other aspects of the climate were simulated by the GLAS Climate Model. An experiment in which the cumulus cloudiness is neglected completely for purposes of the solar and terrestrial radiation parameterizations was performed. The results are compared with those of a control run, in which 100% cumulus cloud cover is assumed. The net solar radiation input into the Earth atmosphere system is more realistic in the experiment, and the model's underprediction of the global mean outgoing thermal radiation at the top of the atmosphere is reduced. The results suggest that there is a positive feedback between cumulus convection and the radiation field. The upper troposphere is warmer in the experiment, the surface air temperature increases over land, and the thermal lows over the continents intensity. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A21G0191A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A21G0191A">Projection of Summer Climate on Tokyo Metropolitan Area using Pseudo Global Warming Method</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Adachi, S. A.; Kimura, F.; Kusaka, H.; Hara, M. 2010-12-01 Recent surface air temperature observations in most of urban areas show the remarkable increasing trend affected by the global warming and the heat island effects. There are many populous areas in Japan. In such areas, the effects of land-use change and urbanization on the local climate are not negligible (Fujibe, 2010). The heat stress for citizen there is concerned to swell moreover in the future. Therefore, spatially detailed climate projection is required for making adaptation and mitigation plans. This study focuses on the Tokyo metropolitan area (TMA) in summer and aims to estimate the local climate change over the TMA in 2070s using a regional climate model. The Regional Atmospheric Modeling System (RAMS) was used for downscaling. A single layer urban canopy model (Kusaka et al., 2001) is built into RAMS as a parameterization expressing the features of urban surface. We performed two experiments for estimating present and future climate. In the present climate simulation, the initial and boundary conditions for RAMS are provided from the JRA-25/JCDAS. On the other hand, the Pseudo Global Warming (PGW) method (Sato et al., 2007) is applied to estimate the future climate, instead of the conventional dynamical downscaling method. The PGW method is expected to reduce the model biases in the future projection estimated by Atmosphere-Ocean General Circulation Models (AOGCM). The boundary conditions used in the PGW method is given by the PGW data, which are obtained by adding the climate monthly difference between 1990s and 2070s estimated by AOGCMs to the 6-hourly reanalysis data. In addition, the uncertainty in the regional climate projection depending on the AOGCM projections is estimated from additional downscaling experiments using the different PGW data obtained from five AOGCMs. Acknowledgment: This work was supported by the Global Environment Research Fund (S-5-3) of the Ministry of the Environment, Japan. References: 1. Fujibe, F., Int. J. Climatol., doi:10.1002/joc.2142 (2010). 2. Kusaka, H., H. Kondo, Y. Kikegawa, and F. Kimura, Bound.-Layer Meteor., 101, 329-358 (2001). 3. Sato, T., F. Kimura, and A. Kitoh, J. Hydrology, 144-154 (2007). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.4205D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.4205D">Linking the M&Rfi Weather Generator with Agrometeorological Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dubrovsky, Martin; Trnka, Miroslav 2015-04-01 Realistic meteorological inputs (representing the present and/or future climates) for the agrometeorological model simulations are often produced by stochastic weather generators (WGs). This contribution presents some methodological issues and results obtained in our recent experiments. We also address selected questions raised in the synopsis of this session. The input meteorological time series for our experiments are produced by the parametric single site weather generator (WG) Marfi, which is calibrated from the available observational data (or interpolated from surrounding stations). To produce meteorological series representing the future climate, the WG parameters are modified by climate change scenarios, which are prepared by the pattern scaling method: the standardised scenarios derived from Global or Regional Climate Models are multiplied by the change in global mean temperature (ΔTG) determined by the simple climate model MAGICC. The presentation will address following questions: (i) The dependence of the quality of the synthetic weather series and impact results on the WG settings. An emphasis will be put on an effect of conditioning the daily WG on monthly WG (presently being one of our hot topics), which aims at improvement of the reproduction of the low-frequency weather variability. Comparison of results obtained with various WG settings is made in terms of climatic and agroclimatic indices (including extreme temperature and precipitation characteristics and drought indices). (ii) Our methodology accounts for the uncertainties coming from various sources. We will show how the climate change impact results are affected by 1. uncertainty in climate modelling, 2. uncertainty in ΔTG, and 3. uncertainty related to the complexity of the climate change scenario (focusing on an effect of inclusion of changes in variability into the climate change scenarios). Acknowledgements: This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248. The weather generator is being developed within the frame of WG4VALUE project (LD12029), which is supported by Ministry of Education, Youth and Sports and linked to the COST action ES1102 VALUE. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008825','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008825">High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Putnam, WilliamM. 2011-01-01 In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..1212960M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..1212960M">Initializing decadal climate predictions over the North Atlantic region</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Matei, Daniela Mihaela; Pohlmann, Holger; Jungclaus, Johann; Müller, Wolfgang; Haak, Helmuth; Marotzke, Jochem 2010-05-01 Decadal climate prediction aims to predict the internally-generated decadal climate variability in addition to externally-forced climate change signal. In order to achieve this it is necessary to start the predictions from the current climate state. In this study we investigate the forecast skill of the North Atlantic decadal climate predictions using two different ocean initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer, 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. Hindcast experiments are then performed over the period 1952-2001. An alternative approach is one in which the subsurface ocean temperature and salinity are diagnosed from an ensemble of ocean model runs forced by the NCEP-NCAR atmospheric reanalyzes for the period 1948-2007, then nudge into the coupled model to produce initial conditions for the hindcast experiments. An anomaly coupling scheme is used in both approaches to avoid the hindcast drift and the associated initial shock. Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes. We asses the skill of the initialized decadal hindcast experiments against the prediction skill of the non-initialized hindcasts simulation. We obtain an overview of the regions with the highest predictability from the regional distribution of the anomaly correlation coefficients and RMSE for the SAT. For the first year the hindcast skill is increased over almost all ocean regions in the NCEP-forced approach. This increase in the hindcast skill for the 1 year lead time is somewhat reduced in the GECCO approach. At lead time 5yr and 10yr, the skill enhancement is still found over the North Atlantic and North Pacific regions. We also consider the potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) and Nordic Seas Overflow by comparing the predicted values to the respective assimilation experiments. Hindcasts of Atlantic MOC and Denmark Strait Overflow show higher predictability than the comparison experiments without initialization and damped persistence predictions up to about 5-6 years. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...48.2339T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...48.2339T">Impact of spectral nudging on regional climate simulation over CORDEX East Asia using WRF</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tang, Jianping; Wang, Shuyu; Niu, Xiaorui; Hui, Pinhong; Zong, Peishu; Wang, Xueyuan 2017-04-01 In this study, the impact of the spectral nudging method on regional climate simulation over the Coordinated Regional Climate Downscaling Experiment East Asia (CORDEX-EA) region is investigated using the Weather Research and Forecasting model (WRF). Driven by the ERA-Interim reanalysis, five continuous simulations covering 1989-2007 are conducted by the WRF model, in which four runs adopt the interior spectral nudging with different wavenumbers, nudging variables and nudging coefficients. Model validation shows that WRF has the ability to simulate spatial distributions and temporal variations of the surface climate (air temperature and precipitation) over CORDEX-EA domain. Comparably the spectral nudging technique is effective in improving the model's skill in the following aspects: (1), the simulated biases and root mean square errors of annual mean temperature and precipitation are obviously reduced. The SN3-UVT (spectral nudging with wavenumber 3 in both zonal and meridional directions applied to U, V and T) and SN6 (spectral nudging with wavenumber 6 in both zonal and meridional directions applied to U and V) experiments give the best simulations for temperature and precipitation respectively. The inter-annual and seasonal variances produced by the SN experiments are also closer to the ERA-Interim observation. (2), the application of spectral nudging in WRF is helpful for simulating the extreme temperature and precipitation, and the SN3-UVT simulation shows a clear advantage over the other simulations in depicting both the spatial distributions and inter-annual variances of temperature and precipitation extremes. With the spectral nudging, WRF is able to preserve the variability in the large scale climate information, and therefore adjust the temperature and precipitation variabilities toward the observation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1198147-climate-simulations-projections-super-parameterized-climate-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1198147-climate-simulations-projections-super-parameterized-climate-model">Climate simulations and projections with a super-parameterized climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Stan, Cristiana; Xu, Li 2014-07-01 The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49.2685P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49.2685P">Initialization shock in decadal hindcasts due to errors in wind stress over the tropical Pacific</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pohlmann, Holger; Kröger, Jürgen; Greatbatch, Richard J.; Müller, Wolfgang A. 2017-10-01 Low prediction skill in the tropical Pacific is a common problem in decadal prediction systems, especially for lead years 2-5 which, in many systems, is lower than in uninitialized experiments. On the other hand, the tropical Pacific is of almost worldwide climate relevance through its teleconnections with other tropical and extratropical regions and also of importance for global mean temperature. Understanding the causes of the reduced prediction skill is thus of major interest for decadal climate predictions. We look into the problem of reduced prediction skill by analyzing the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcasts for the fifth phase of the Climate Model Intercomparison Project and performing a sensitivity experiment in which hindcasts are initialized from a model run forced only by surface wind stress. In both systems, sea surface temperature variability in the tropical Pacific is successfully initialized, but most skill is lost at lead years 2-5. Utilizing the sensitivity experiment enables us to pin down the reason for the reduced prediction skill in MPI-ESM to errors in wind stress used for the initialization. A spurious trend in the wind stress forcing displaces the equatorial thermocline in MPI-ESM unrealistically. When the climate model is then switched into its forecast mode, the recovery process triggers artificial El Niño and La Niña events at the surface. Our results demonstrate the importance of realistic wind stress products for the initialization of decadal predictions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B13H..07H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B13H..07H">Long-term Ecosystem Experiments, Data Assimilation, and Meta-Analysis</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hungate, B. A.; Van Groenigen, K. J.; Osenberg, C. W.; van Gestel, N. 2015-12-01 Land ecosystems affect climate and the atmosphere, and climate and atmospheric change affects ecosystems. Syntheses of ecosystem experiments investigating their responses to environmental change holds promise for understanding how to model these interactions, and thereby gain insight into Earth's future biosphere, atmosphere, and climate. Long-term experiments examining ecosystem responses are thought to be especially important in this effort, for their potential to reveal cumulative and progressive effects, subtle effects initially undetectable experimentally, but manifest more clearly over time, often with stronger implications for modeled responses than the more dramatic, short-term experimental responses. Here, we present new analyses of long-term experiments manipulating temperature, CO2 concentration, and precipitation, testing the general hypothesis that there are common temporal patterns of responses that reveal general biogeochemical characterizing ecosystem responses to these environmental changes. For example, we show that increased carbon input with elevated CO2 stimulates emissions of nitrous oxide and methane, important greenhouse gases, and that effects show no signs of diminishing over the duration of experiments that have documented responses. At the same time, we show that the temporal resolution for this response is limited, pointing to a potential limitation in the ability of experiments to address clearly long-term hypotheses. We also show that warming tends to have limited cumulative effects on total soil carbon stocks in long-term experiments, and explore the mechanisms underlying this response. Finally, we discuss the implications of these findings for models used to simulate long-term ecosystem responses to these environmental forcings, as well as the implications of these findings for the next generation of terrestrial ecosystem experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=Change+AND+climate&pg=7&id=EJ1096082','ERIC'); return false;" href="https://eric.ed.gov/?q=Change+AND+climate&pg=7&id=EJ1096082">Exploring Students' Epistemological Knowledge of Models and Modelling in Science: Results from a Teaching/Learning Experience on Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a> Tasquier, Giulia; Levrini, Olivia; Dillon, Justin 2016-01-01 The scientific community has been debating climate change for over two decades. In the light of certain arguments put forward by the aforesaid community, the EU has recommended a set of innovative reforms to science teaching such as incorporating environmental issues into the scientific curriculum, thereby helping to make schools a place of civic… </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6931B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6931B">Creating "Intelligent" Ensemble Averages Using a Process-Based Framework</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Baker, Noel; Taylor, Patrick 2014-05-01 The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is used to add value to individual model projections and construct a consensus projection. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, individual models reproduce certain climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. The intention is to produce improved ("intelligent") unequal-weight ensemble averages. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables—e.g., outgoing longwave radiation and surface temperature. Several climate process metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument in combination with surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing the equal-weighted ensemble average and an ensemble weighted using the process-based metric. Additionally, this study investigates the dependence of the metric weighting scheme on the climate state using a combination of model simulations including a non-forced preindustrial control experiment, historical simulations, and several radiative forcing Representative Concentration Pathway (RCP) scenarios. Ultimately, the goal of the framework is to advise better methods for ensemble averaging models and create better climate predictions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP41C2277P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP41C2277P">Reconstructing Common Era Climate Fields Using Data Assimilation, Proxies, and a Linear Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Perkins, W. A.; Hakim, G. J. 2016-12-01 In this work, we examine the skill of a new approach to performing climate field reconstructions (CFRs) using a form of online paleoclimate data assimilation (PDA). Many previous studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs), and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational costs by employing an empirical forecast model (known as a linear inverse model; LIM), which has been shown to have comparable skill to CGCMs. CFRs of annually averaged 2m air temperature anomalies are compared between the Last Millennium Reanalysis framework (no forecasting or "offline"), a persistence forecast, and four LIM forecasting experiments over the instrumental period (1850 - 2000). We test LIM calibrations for observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial and global mean temperature (GMT). The detrended GMT skill metrics show the most dramatic increases in skill with coefficient of efficiency (CE) improvements over the no-forecasting benchmark averaging 57%. LIM experiments display a common pattern of spatial field increases in CE skill over northern hemisphere land areas and in the high-latitude North Atlantic - Barents Sea corridor (Figure 1). However, the non-GCM-calibrated LIMs introduce other deficiencies into the spatial skill of these reconstructions, likely due to aspects of the LIM calibration process. Overall, the CMIP5 LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the usage of the LIM forecasts, and not simple persistence of temperature anomalies over time. These results show that the use of LIM forecasting can help add further dynamical constraint to CFRs. As we move forward, this will be an important factor in fully utilizing dynamically consistent information from the proxy record while reconstructing the past millennium. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050177236','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050177236">GLACE: The Global Land-Atmosphere Coupling Experiment Part 2: Analysis</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Guo, Zhichang; Dirmeyer, Paul A.; Koster, Randal D.; Bonan, Gordon; Chan, Edmond; Cox, Peter; Gordon, C. T.; Kanae, Shinjiro; Kowalczyk, Eva; Lawrence, David 2005-01-01 The twelve weather and climate models participating in the Global Land-Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land-atmosphere coupling and some intriguing commonalities. In this paper, we address the causes of variations in coupling strength - both the geographic variations within a given model and the model-to-model differences. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage - an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation-precipitation connection, however, also play a key role. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26369503','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26369503">Solar forcing synchronizes decadal North Atlantic climate variability.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Thiéblemont, Rémi; Matthes, Katja; Omrani, Nour-Eddine; Kodera, Kunihiko; Hansen, Felicitas 2015-09-15 Quasi-decadal variability in solar irradiance has been suggested to exert a substantial effect on Earth's regional climate. In the North Atlantic sector, the 11-year solar signal has been proposed to project onto a pattern resembling the North Atlantic Oscillation (NAO), with a lag of a few years due to ocean-atmosphere interactions. The solar/NAO relationship is, however, highly misrepresented in climate model simulations with realistic observed forcings. In addition, its detection is particularly complicated since NAO quasi-decadal fluctuations can be intrinsically generated by the coupled ocean-atmosphere system. Here we compare two multi-decadal ocean-atmosphere chemistry-climate simulations with and without solar forcing variability. While the experiment including solar variability simulates a 1-2-year lagged solar/NAO relationship, comparison of both experiments suggests that the 11-year solar cycle synchronizes quasi-decadal NAO variability intrinsic to the model. The synchronization is consistent with the downward propagation of the solar signal from the stratosphere to the surface. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24880596','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24880596">Modelling the influence of climate change on the chemical concentrations in the Baltic Sea region with the POPCYCLING-Baltic model.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Kong, Deguo; MacLeod, Matthew; Cousins, Ian T 2014-09-01 The effect of projected future changes in temperature, wind speed, precipitation and particulate organic carbon on concentrations of persistent organic chemicals in the Baltic Sea regional environment is evaluated using the POPCYCLING-Baltic multimedia chemical fate model. Steady-state concentrations of hypothetical perfectly persistent chemicals with property combinations that encompass the entire plausible range for non-ionizing organic substances are modelled under two alternative climate change scenarios (IPCC A2 and B2) and compared to a baseline climate scenario. The contributions of individual climate parameters are deduced in model experiments in which only one of the four parameters is changed from the baseline scenario. Of the four selected climate parameters, temperature is the most influential, and wind speed is least. Chemical concentrations in the Baltic region are projected to change by factors of up to 3.0 compared to the baseline climate scenario. For chemicals with property combinations similar to legacy persistent organic pollutants listed by the Stockholm Convention, modelled concentration ratios between two climate change scenarios and the baseline scenario range from factors of 0.5 to 2.0. This study is a first step toward quantitatively assessing climate change-induced changes in the environmental concentrations of persistent organic chemicals in the Baltic Sea region. Copyright © 2014 Elsevier Ltd. All rights reserved. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1237126-characteristics-tropical-cyclones-high-resolution-models-present-climate','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1237126-characteristics-tropical-cyclones-high-resolution-models-present-climate">Characteristics of tropical cyclones in high-resolution models in the present climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; ... 2014-12-05 The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TCmore » frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMED23E..06R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMED23E..06R">Interactive, process-oriented climate modeling with CLIMLAB</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rose, B. E. J. 2016-12-01 Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active">13</li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active">14</li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/47121','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/47121">Climate change and associated fire potential for the south-eastern United States in the 21st century</a> <a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Anthony P. Bedel; Thomas L. Mote; Scott L. Goodrick 2013-01-01 Climate models indicate that the climate of the south-eastern US will experience increasing temperatures and associated evapotranspiration in the 21st century. The current study found that conditions in the south-eastern US will likely become drier overall, given a warmer environment during future winter and spring seasons. This study examined the potential effects of... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GPC...112...64P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GPC...112...64P">Are there interactive effects of physiological and radiative forcing produced by increased CO2 concentration on changes of land hydrological cycle?</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Peng, Jing; Dan, Li; Dong, Wenjie 2014-01-01 Three coupled climate-carbon cycle models including CESM (Community Earth System Model), CanEsm (the Canadian Centre for Climate Modelling and Analysis Earth System Model) and BCC (Beijing Climate Center Climate System Model) were used to estimate whether changes in land hydrological cycle responded to the interactive effects of CO2-physiological forcing and CO2-radiative forcing. No signs could be indicated that the interactive effects of CO2-physiological forcing and CO2-radiative forcing on the hydrological variables (e.g. precipitation, evapotranspiration and runoff) were detected at global and regional scales. For each model, increases in precipitation, evapotranspiration and runoff (e.g. 0.37, 0.18 and 0.25 mm/year2) were simulated in response to CO2-radiative forcing (experiment M3). Decreases in precipitation and evapotranspiration (about - 0.02 and - 0.09 mm/year2) were captured if the CO2 physiological effect was only accounted for (experiment M2). In this experiment, a reverse sign in runoff (the increase of 0.08 mm/year2) in contrast to M3 is presented. All models simulated the same signs across Eastern Asia in response to the CO2 physiological forcing and radiative forcing: increases in precipitation and evapotranspiration only considering greenhouse effect; reductions in precipitation and evapotranspiration in response to CO2-physiological effect; and enhanced trends in runoff from all experiments. However, there was still a large uncertainty on the magnitude of the effect of transpiration on runoff (decreased transpiration accounting for 8% to 250% of the increased runoff) from the three models. Two models (CanEsm and BCC) attributed most of the increase in runoff to the decrease in transpiration if the CO2-physiological effect was only accounted for, whereas CESM exhibited that the decrease in transpiration could not totally explain the increase in runoff. The attribution of the CO2-physiological forcing to changes in stomatal conductance versus changes in vegetation structure (e.g. increased Leaf Area Index) is an issue to discuss, and among the three models, no agreement appeared. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900041193&hterms=climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900041193&hterms=climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D20%26Ntt%3Dclimate%2Bchange">Climate change and the middle atmosphere. I - The doubled CO2 climate</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rind, D.; Prather, M. J.; Suozzo, R.; Balachandran, N. K. 1990-01-01 The effect of doubling the atmospheric content of CO2 on the middle-atmosphere climate is investigated using the GISS global climate model. In the standard experiment, the CO2 concentration is doubled both in the stratosphere and troposphere, and the SSTs are increased to match those of the doubled CO2 run of the GISS model. Results show that the doubling of CO2 leads to higher temperatures in the troposphere, and lower temperatures in the stratosphere, with a net result being a decrease of static stability for the atmosphere as a whole. The middle atmosphere dynamical differences found were on the order of 10-20 percent of the model values for the current climate. These differences, along with the calculated temperature differences of up to about 10 C, may have a significant impact on the chemistry of the future atmosphere, including that of stratospheric ozone, the polar ozone 'hole', and basic atmospheric composition. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..1413531W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..1413531W">Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F. 2012-04-01 Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MAP...129..395C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MAP...129..395C">Recent land cover changes and sensitivity of the model simulations to various land cover datasets for China</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chen, Liang; Ma, Zhuguo; Mahmood, Rezaul; Zhao, Tianbao; Li, Zhenhua; Li, Yanping 2017-08-01 Reliable land cover data are important for improving numerical simulation by regional climate model, because the land surface properties directly affect climate simulation by partitioning of energy, water and momentum fluxes and by determining temperature and moisture at the interface between the land surface and atmosphere. China has experienced significant land cover change in recent decades and accurate representation of these changes is, hence, essential. In this study, we used a climate model to examine the changes experienced in the regional climate because of the different land cover data in recent decades. Three sets of experiments are performed using the same settings, except for the land use/cover (LC) data for the years 1990, 2000, 2009, and the model default LC data. Three warm season periods are selected, which represented a wet (1998), normal (2000) and a dry year (2011) for China in each set of experiment. The results show that all three sets of land cover experiments simulate a warm bias relative to the control with default LC data for near-surface temperature in summertime in most parts of China. It is especially noticeable in the southwest China and south of the Yangtze River, where significant changes of LC occurred. Deforestation in southwest China and to the south of Yangtze River in the experiment cases may have contributed to the negative precipitation bias relative to the control cases. Large LC changes in northwestern Tibetan Plateau for 2000 and 2009 datasets are also associated with changes in surface temperature, precipitation, and heat fluxes. Wind anomalies and energy budget changes are consistent with the precipitation and temperature changes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPP24B..03I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPP24B..03I">Setting up a model intercomparison project for the last deglaciation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ivanovic, R. F.; Gregoire, L. J.; Valdes, P. J.; Roche, D. M.; Kageyama, M. 2014-12-01 The last deglaciation (~ 21-9 ka) presents a series of opportunities to study the underlying mechanisms of abrupt climate changes and long-term trends in the Earth System. Most of the forcings are relatively well constrained and geological archives record responses over a range of timescales. Despite this, large uncertainties remain over the feedback loops that culminated in the collapse of the great Northern Hemisphere ice sheets, and a consensus has yet to be reached on the chains of events that led to rapid surface warming and cooling during this period.Climate models are powerful tools for quantitatively assessing these outstanding issues through their ability to temporally resolve cause and effect, as well as break down the contributions from different forcings. This is well demonstrated by pioneering work; for example by Liu et al. (2009), Roche et al. (2011), Gregoire et al. (2012) and Menviel et al. (2011). However, such work is not without challenges; model-geological data mismatches remain unsolved and it is difficult to compare results from different models with unique experiment designs. Therefore, we have established a multidisciplinary Paleoclimate Model Intercomparison Project working group to coordinate transient climate model simulations and geological archive compilations of the last deglaciation. Here, we present the plans and progress of the working group in its first phase of activity; the investigation of Heinrich Stadial 1 and the lead into the Bolling warming event. We describe the set-up of the core deglacial experiment, explain our approach for dealing with uncertain climate forcings and outline our solutions to challenges posed by this research. By defining a common experiment design, we have built a framework to include models of different speeds, complexities and resolution, maximising the reward of this varied approach. One of the next challenges is to compile transient proxy records and develop a methodology for dealing with uncertainty and error in model-geological data comparisons. Through this global and interdisciplinary initiative, we combine multi-proxy records with a suite of different modelling techniques to test hypotheses for abrupt climate changes and reconstruct the chain of events that deglaciated the Earth 21-9 ka. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4031I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4031I">Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ivanovic, Ruza; Gregoire, Lauren; Kageyama, Masa; Roche, Didier; Valdes, Paul; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev 2016-04-01 The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 thousand years. Here, we present the design of a coordinated Core simulation over the period 21-9 thousand years before present (ka) with time varying orbital forcing, greenhouse gases, ice sheets, and other geographical changes. A choice of two ice sheet reconstructions is given. Additional focussed simulations will also be coordinated on an ad-hoc basis by the working group, for example to investigate the effect of ice sheet and iceberg meltwater, and the uncertainty in other forcings. Some of these focussed simulations will concentrate on shorter durations around specific events to allow the more computationally expensive models to take part. Ivanovic, R. F., Gregoire, L. J., Kageyama, M., Roche, D. M., Valdes, P. J., Burke, A., Drummond, R., Peltier, W. R., and Tarasov, L.: Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions, Geosci. Model Dev. Discuss., 8, 9045-9102, doi:10.5194/gmdd-8-9045-2015, 2015. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160004999&hterms=philosophy&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dphilosophy','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160004999&hterms=philosophy&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dphilosophy">A Practical Philosophy of Complex Climate Modelling</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Schmidt, Gavin A.; Sherwood, Steven 2014-01-01 We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917825F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917825F">Spatiotemporal assessment of historical skill and projected future changes in CORDEX South Asia ensemble simulation of precipitation and temperature for the Upper Indus Basin</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Forsythe, Nathan; Fowler, Hayley; Pritchard, David 2017-04-01 High mountain Asia (HMA), including the Hindu Kush-Karakoram, Himalayas and Tibetan Plateau, constitutes one the key "water towers of the world", giving rise to river basins whose resources support hundreds of millions of people. This area is currently experiencing substantial demographic growth and socio-economic development. This evolution will likely continue for the next few decades and compound pressure on resource managements systems from inevitable climate change. In order to develop climate services to support water resources planning and facilitate adaptive capacity building, it is essential to critically characterise the skill and biases of the evaluation (reanalysis-driven) and control (historical period) components of presently available regional climate model (RCM) experiments. For mountain regions in particular, the ability of RCMs to reasonably reproduce the influence of complex topography, through lapse rates and orographic forcing, on sub-regional climate - notably temperature and precipitation - must be assessed in detail. This is vital because the spatiotemporal distribution of precipitation and temperature in mountains determine the seasonality of streamflow from the headwater reaches and of major river basins. Once the biases of individual GCM/RCM experiments have been identified methodologies can be developed for modulating (correcting) the projected patterns of change identified by comparing simulated climate sub-regional climate under specific emissions scenarios (e.g. RCP8.5) to historical representations by the same model (time-slice approach). Such methods could for example include calculating temperature change factors as a function elevation difference from present 0°C (freezing) isotherm rather than simply using the overlying RCM grid cell if for instance the RCM showed exacerbated temperature increase at snow line (i.e. albedo feedback in elevation dependent warming) but also showed a pronounced bias in the historical (vertical) position of the isotherm. HMA falls within the South Asia domain of the Coordinated Regional Downscaling Experiment (CORDEX) initiative to which multiple international modelling centres have contributed RCM experiments. This work evaluates the present publically available CORDEX South Asia experiments including integrations of CCAM, RegCM4, REMO2009 and RCA4. These have been driven by a range of GCMS including ACCESS1.0, CNRM-CM5, GFDL, LMDZ, MPI-ESM, and NorESM. This substantial multi-model ensemble provides a valuable opportunity to explore the spread in model skill at simulation of key characteristics of the present HMA climate. This study focuses geographically within the CORDEX South Asia domain on an orthogonal subdomain from 72E to 77E and 32.5N to 37.5N which covers the bulk of the Karakoram range and key headwaters tributaries of the Indus river basin upon which Pakistan is preponderantly dependent for agricultural water supply and hydro-electric power generation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.7168M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.7168M">Interbasin effects of the Indian Ocean on Pacific decadal climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Chikamoto, Yoshimitsu; Ishii, Masayoshi 2016-07-01 We demonstrate the significant impact of the Indian Ocean on the Pacific climate on decadal timescales by comparing two sets of data assimilation experiments (pacemaker experiments) conducted over recent decades. For the Indian Ocean of an atmosphere-ocean coupled global climate model, we assimilate ocean temperature and salinity anomalies defined as deviations from climatology or as anomalies with the area-averaged changes for the Indian Ocean subtracted. When decadal sea surface temperature (SST) trends are observed to be strong over the Indian Ocean, the equatorial thermocline uniformly deepens, and the model simulates the eastward tendencies of surface wind aloft. Surface winds strongly converge around the maritime continent, and the associated strengthening of the Walker circulation suppresses an increasing trend in the equatorial Pacific SST through ocean thermocline shoaling, similar to common changes associated with seasonal Indian Ocean warming. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6855V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6855V">The foundation for climate services in Belgium: CORDEX.be</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Van Schaeybroeck, Bert; Termonia, Piet; De Ridder, Koen; Fettweis, Xavier; Gobin, Anne; Luyten, Patrick; Marbaix, Philippe; Pottiaux, Eric; Stavrakou, Trissevgeni; Van Lipzig, Nicole; van Ypersele, Jean-Pascal; Willems, Patrick 2017-04-01 According to the Global Framework for Climate Services (GFCS) there are four pillars required to build climate services. As the first step towards the realization of a climate center in Belgium, the national project CORDEX.be focused on one pillar: research modelling and projection. By bringing together the Belgian climate and impact modeling research of nine groups a data-driven capacity development and community building in Belgium based on interactions with users. The project is based on the international CORDEX ("COordinated Regional Climate Downscaling Experiment") project where ".be" indicates it will go beyond for Belgium. Our national effort links to the regional climate initiatives through the contribution of multiple high-resolution climate simulations over Europe following the EURO-CORDEX guidelines. Additionally the same climate simulations were repeated at convection-permitting resolutions over Belgium (3 to 5 km). These were used to drive different local impact models to investigate the impact of climate change on urban effects, storm surges and waves, crop production and changes in emissions from vegetation. Akin to international frameworks such as CMIP and CORDEX a multi-model approach is adopted allowing for uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. However, due to the lack of a large set of high resolution model runs, a combination of all available climate information is supplemented with the statistical downscaling approach. The organization of the project, together with its main results will be outlined. The proposed coordination framework could serve as a demonstration case for regions or countries where the climate-research capacity is present but a structure is required to assemble it coherently. Based on interactions and feedback with stakeholders different applications are planned, demonstrating the use of the climate data. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006ESASP.614E..98L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006ESASP.614E..98L">An Assessment of IPCC 20th Century Climate Simulations Using the 15-year Sea Level Record from Altimetry</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Leuliette, E.; Nerem, S.; Jakub, T. 2006-07-01 Recen tly, multiple ensemble climate simulations h ave been produced for th e forthco ming Fourth A ssessment Report of the Intergovernmental Panel on Climate Change (IPCC). N early two dozen coupled ocean- atmo sphere models have contr ibuted output for a variety of climate scen arios. One scenar io, the climate of the 20th century exper imen t (20C3 M), produces model output that can be comp ared to th e long record of sea level provided by altimetry . Generally , the output from the 20C3M runs is used to initialize simulations of future climate scenar ios. Hence, v alidation of the 20 C3 M experiment resu lts is crucial to the goals of th e IPCC. We present compar isons of global mean sea level (G MSL) , global mean steric sea level change, and regional patterns of sea lev el chang e from these models to r esults from altimetry, tide gauge measurements, and reconstructions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCC...7.....B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCC...7.....B">COP21 climate negotiators' responses to climate model forecasts</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bosetti, Valentina; Weber, Elke; Berger, Loïc; Budescu, David V.; Liu, Ning; Tavoni, Massimo 2017-02-01 Policymakers involved in climate change negotiations are key users of climate science. It is therefore vital to understand how to communicate scientific information most effectively to this group. We tested how a unique sample of policymakers and negotiators at the Paris COP21 conference update their beliefs on year 2100 global mean temperature increases in response to a statistical summary of climate models' forecasts. We randomized the way information was provided across participants using three different formats similar to those used in Intergovernmental Panel on Climate Change reports. In spite of having received all available relevant scientific information, policymakers adopted such information very conservatively, assigning it less weight than their own prior beliefs. However, providing individual model estimates in addition to the statistical range was more effective in mitigating such inertia. The experiment was repeated with a population of European MBA students who, despite starting from similar priors, reported conditional probabilities closer to the provided models' forecasts than policymakers. There was also no effect of presentation format in the MBA sample. These results highlight the importance of testing visualization tools directly on the population of interest. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A53N..04K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A53N..04K">Transient Atmospheric Circulation Changes in a Grand ensemble of Idealized CO2 Increase Experiments</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Karpechko, A.; Manzini, E.; Kornblueh, L. 2017-12-01 The yearly evolution with increasing forcing of the large-scale atmospheric circulation is examined in a 68-member ensemble of 1pctCO2 scenario experiments performed with the MPI-ESM model. Each member of the experiment ensemble is integrated for 155 years, from initial conditions taken from a 2000-yr long pre-industrial control climate experiment. The 1pctCO2 scenario experiments are conducted following the protocol of including as external forcing only a CO2 concentration increase at 1%/year, till quadrupling of CO2 concentrations. MPI-ESM is the Max-Planck-Institute Earth System Model (including coupling between the atmosphere, ocean and seaice). By averaging over the 68 members (ensemble mean), atmospheric variability is greatly reduced. Thus, it is possible to investigate the sensitivity to the climate state of the atmospheric response to CO2 doubling. Indicators of global change show the expected monotonic evolution with increasing CO2 and a weak dependence of the thermodynamical response to CO2 doubling on the climate state. The surface climate response of the atmospheric circulation, diagnosed for instance by the pressure at sea level, and the eddy-driven jet response show instead a marked dependence to the climate state, for the Northern winter season. We find that as the CO2 concentration increases above doubling, Northern winter trends in some indicators of atmospheric circulation changes decrease or even reverse, posing the question on what are the causes of this nonlinear behavior. The investigation of the role of stationary waves, the meridional overturning circulation, the decrease in Arctic sea ice and the stratospheric vortex points to the latter as a plausible cause of such nonlinear response. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1258S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1258S">Variability in Terrestrial Water Storage and its effect on polar motion</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Śliwińska, Justyna; Nastula, Jolanta 2017-04-01 Explaining the hydrological part of observed polar motion excitation has been a major challenge over a dozen years. The terrestrial water storage (TWS) excitation of polar motion - hydrological angular momentum (HAM), has been investigated widely using global hydrological models mainly at seasonal timescales. Unfortunately, the results from the models do not fully explain the role of hydrological signal in polar motion excitation. The determination of TWS from the Earth's gravity field observations represents an indirect approach for estimating land hydrology. Throughout the past decade, the Gravity Recovery and Climate Experiment (GRACE) has given an unprecedented view on global variations in Terrestrial Water Storage. Our investigations are focused on the influence of Terrestrial Water Storage (TWS) variations obtained from Gravity Recovery and Climate Experiment (GRACE) mission on polar motion excitation functions at decadal and inter-annual timescales. The global and regional trend, seasonal cycle as well as some extremes in TWS variations are considered here. Here TWS are obtained from the monthly mass grids land GRACE Tellus data: GRACE CSR RL05, GRACE GFZ RL05 and GRACE JPL RL05. As a comparative dataset, we also use TWS estimates determined from the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5). GRACE data and state-of-the-art CMIP5 climate models allow us to show the variability of hydrological part of polar motion under climate changes. Our studies include two steps: first, the determination and comparisons of regional patterns of TWS obtained from GRACE data and climate models, and second, comparison of the regional and global hydrological excitation functions of polar motion with a hydrological signal in the geodetic excitation functions of polar motion. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.H33I..08B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.H33I..08B">What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M. 2009-12-01 “…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility planning is conducted. In the near term we feel strongly that water utilities and climate scientists should work together to leverage the upcoming Coupled Model Intercomparison Project, Phase 5 (CMIP5; a coordinated set climate model experiments that will be used to support the upcoming IPCC Fifth Assessment) to better benefit water utilities. In the longer term, even with model and downscaling improvements, it is very likely that substantial uncertainty about future climate change at the desired spatial and temporal scales will remain. Nonetheless, there is no doubt the climate is changing, and the challenge is to work with what we have, or what we can reasonably expect to have in the coming years to make the best decisions we can. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC23A1039K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC23A1039K">Effects of Projected Future Climate Change on Groundwater Recharge and Storage for Two Coastal Aquifers in Guanacaste Province, Costa Rica</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kolb, C. 2017-12-01 Climate change is expected to pose a significant threat to water resources in the future. Guanacaste Province, located in northwestern Costa Rica, has a unique climate that is influenced by the Pacific Ocean and Caribbean Sea, as well as the Central Cordillera mountain range. Although the region experiences a marked rainy season between May and November, the hot, dry summers often stress water resources. Climate change projections suggest increased temperatures and reduced precipitation for the region, which will further stress water supplies. This study focuses on the effects of climate change on groundwater resources for two coastal aquifers, Potrero and Brasilito. The UZF model package coupled with the finite difference groundwater flow model MODFLOW were used to evaluate the effect of climate change on groundwater recharge and storage. A potential evapotranspiration model was used to estimate groundwater infiltration rates used in the MODFLOW model. Climate change projections for temperature, precipitation, and sea level rise were used to develop climate scenarios, which were compared to historical data. Preliminary results indicate that climate change could reduce future recharge, especially during the dry season. Additionally, the coastal aquifers are at increased risk of reduced storage and increased salinization due to the reductions in groundwater recharge and sea level rise. Climate change could also affect groundwater quality in the region, disrupting the ecosystem and impairing a primary source of drinking water. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://crocdoc.ifas.ufl.edu/projects/climateenvelopemodeling/','USGSPUBS'); return false;" href="http://crocdoc.ifas.ufl.edu/projects/climateenvelopemodeling/">Use and interpretation of climate envelope models: a practical guide</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Watling, James I.; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S. 2013-01-01 This guidebook is intended to provide a practical overview of climate envelope modeling for conservation professionals and natural resource managers. The material is intended for people with little background or experience in climate envelope modeling who want to better understand and interpret models developed by others and the results generated by such models, or want to do some modeling themselves. This is not an exhaustive review of climate envelope modeling, but rather a brief introduction to some key concepts in the discipline. Readers interested in a more in-depth treatment of much of the material presented here are referred to an excellent book, Mapping Species Distributions: Spatial Inference and Prediction by Janet Franklin. Also, a recent review (Araújo & Peterson 2012) provides an excellent, though more technical, discussion of many of the issues dealt with here. Here we treat selected topics from a practical perspective, using minimal jargon to explain and illustrate some of the many issues that one has to be aware of when using climate envelope models. When we do introduce specialized terminology in the guidebook, we bold the term when it is first used; a glossary of these terms is included at the back of the guidebook. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1130690-impact-abrupt-suspension-solar-radiation-management-termination-effect-experiment-g2-geoengineering-model-intercomparison-project-geomip','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1130690-impact-abrupt-suspension-solar-radiation-management-termination-effect-experiment-g2-geoengineering-model-intercomparison-project-geomip">The Impact of Abrupt Suspension of Solar Radiation Management (Termination Effect) in Experiment G2 of the Geoengineering Model Intercomparison Project (GeoMIP)</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Jones, Andrew; Haywood, J.; Alterskjaer, Kari 2013-09-11 We have examined changes in climate which result from the sudden termination of geoengineering after 50 years of offsetting a 1% per annum increase in CO2 concentra- tions as simulated by 11 different climate models in experiment G2 of the Geoengineering Model Intercomparison Project. The models agree on a rapid rate of global-mean warming following termination, accompanied by increases in global-mean precipitation rate and in plant net primary productivity, and decreases in sea-ice cover. While there is a considerable degree of consensus for the geographical distribution of warming, there is much less of an agreement regarding the patterns of changemore » in the other quantities.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814608M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814608M">Present and Future Surface Mass Budget of Small Arctic Ice Caps in a High Resolution Regional Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mottram, Ruth; Langen, Peter; Koldtoft, Iben; Midefelt, Linnea; Hesselbjerg Christensen, Jens 2016-04-01 Globally, small ice caps and glaciers make a substantial contribution to sea level rise; this is also true in the Arctic. Around Greenland small ice caps are surprisingly important to the total mass balance from the island as their marginal coastal position means they receive a large amount of precipitation and also experience high surface melt rates. Since small ice caps and glaciers have had a disproportionate number of long-term monitoring and observational schemes in the Arctic, likely due to their relative accessibility, they can also be a valuable source of data. However, in climate models the surface mass balance contributions are often not distinguished from the main ice sheet and the presence of high relief topography is difficult to capture in coarse resolution climate models. At the same time, the diminutive size of marginal ice masses in comparison to the ice sheet makes modelling their ice dynamics difficult. Using observational data from the Devon Ice Cap in Arctic Canada and the Renland Ice Cap in Eastern Greenland, we assess the success of a very high resolution (~5km) regional climate model, HIRHAM5 in capturing the surface mass balance (SMB) of these small ice caps. The model is forced with ERA-Interim and we compare observed mean SMB and the interannual variability to assess model performance. The steep gradient in topography around Renland is challenging for climate models and additional statistical corrections are required to fit the calculated surface mass balance to the high relief topography. Results from a modelling experiment at Renland Ice Cap shows that this technique produces a better fit between modelled and observed surface topography. We apply this statistical relationship to modelled SMB on the Devon Ice Cap and use the long time series of observations from this glacier to evaluate the model and the smoothed SMB. Measured SMB values from a number of other small ice caps including Mittivakkat and A.P. Olsen ice cap are also compared with model output. Finally we use climate simulations forced with two different RCP scenarios to examine the likely future evolution of SMB over these small ice masses. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active">14</li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active">15</li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011WRR....4712516G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011WRR....4712516G">Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain 2011-12-01 Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1408078-rethinking-default-construction-multimodel-climate-ensembles','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1408078-rethinking-default-construction-multimodel-climate-ensembles">Rethinking the Default Construction of Multimodel Climate Ensembles</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Rauser, Florian; Gleckler, Peter; Marotzke, Jochem 2015-07-21 Here, we discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process.more » If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. Finally, with an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020054204&hterms=Global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DGlobal%2Bwarming','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020054204&hterms=Global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DGlobal%2Bwarming">Enhanced Climatic Warming Over the Tibetan Plateau Due to Doubling CO2: A Model Study</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Chen, Baode; Chao, Winston C.; Liu, Xiaodong; Lau, William K. M. (Technical Monitor) 2001-01-01 A number of studies have presented the evidences that surface climate change associated with global warming at high elevation sites shows more pronounced warming than at low elevations, i.e. an elevation dependency of climatic warming pointed out that snow-albedo feedback may be responsible for the excessive warming in the Swiss Alps. From an ensemble of climate change experiments of increasing greenhouse gases and aerosols using an air-sea coupled climate model, Eyre and Raw (1999) found a marked elevation dependency of the simulated surface screen temperature increase over the Rocky Mountains. Using almost all available instrumental records, Liu and Chen (2000) showed that the main portion of the Tibetan Plateau (TP) has experienced significant ground temperature warming since the middlebrows, especially in winter, and that there is a tendency for the warming trend to increase with elevation in the TP as well as its surrounding areas. In this paper, we will investigate the mechanism of elevation dependency of climatic warming in the TP by using a high-resolution regional climate model. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JGRD..11812444K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JGRD..11812444K">Altitude dependency of future snow cover changes over Central Japan evaluated by a regional climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kawase, Hiroaki; Hara, Masayuki; Yoshikane, Takao; Ishizaki, Noriko N.; Uno, Fumichika; Hatsushika, Hiroaki; Kimura, Fujio 2013-11-01 Sea of Japan side of Central Japan is one of the heaviest snowfall areas in the world. We investigate near-future snow cover changes on the Sea of Japan side using a regional climate model. We perform the pseudo global warming (PGW) downscaling based on the five global climate models (GCMs). The changes in snow cover strongly depend on the elevation; decrease in the ratios of snow cover is larger in the lower elevations. The decrease ratios of the maximum accumulated snowfall in the short term, such as 1 day, are smaller than those in the long term, such as 1 week. We conduct the PGW experiments focusing on specific periods when a 2 K warming at 850 hPa is projected by the individual GCMs (PGW-2K85). The PGW-2K85 experiments show different changes in precipitation, resulting in snow cover changes in spite of similar warming conditions. Simplified sensitivity experiments that assume homogenous warming of the atmosphere (2 K) and the sea surface show that the altitude dependency of snow cover changes is similar to that in the PGW-2K85 experiments, while the uncertainty of changes in the sea surface temperature influences the snow cover changes both in the lower and higher elevations. The decrease in snowfall is, however, underestimated in the simplified sensitivity experiments as compared with the PGW experiments. Most GCMs project an increase in dry static stability and some GCMs project an anticyclonic anomaly over Central Japan, indicating the inhibition of precipitation, including snowfall, in the PGW experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27788346','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27788346">Spatial Selection and Local Adaptation Jointly Shape Life-History Evolution during Range Expansion.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Van Petegem, Katrien H P; Boeye, Jeroen; Stoks, Robby; Bonte, Dries 2016-11-01 In the context of climate change and species invasions, range shifts increasingly gain attention because the rates at which they occur in the Anthropocene induce rapid changes in biological assemblages. During range shifts, species experience multiple selection pressures. For poleward expansions in particular, it is difficult to interpret observed evolutionary dynamics because of the joint action of evolutionary processes related to spatial selection and to adaptation toward local climatic conditions. To disentangle the effects of these two processes, we integrated stochastic modeling and data from a common garden experiment, using the spider mite Tetranychus urticae as a model species. By linking the empirical data with those derived form a highly parameterized individual-based model, we infer that both spatial selection and local adaptation contributed to the observed latitudinal life-history divergence. Spatial selection best described variation in dispersal behavior, while variation in development was best explained by adaptation to the local climate. Divergence in life-history traits in species shifting poleward could consequently be jointly determined by contemporary evolutionary dynamics resulting from adaptation to the environmental gradient and from spatial selection. The integration of modeling with common garden experiments provides a powerful tool to study the contribution of these evolutionary processes on life-history evolution during range expansion. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/33221','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/33221">Simulated response of conterminous United States ecosystems to climate change at different levels of fire suppression, CO2 emission rate, and growth response to CO2</a> <a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> James M. Lenihan; Dominique Bachelet; Ronald P. Neilson; Raymond Drapek 2008-01-01 A modeling experiment was designed to investigate the impact of fire management, CO2 emission rate, and the growth response to CO2 on the response of ecosystems in the conterminous United States to climate scenarios produced by three different general circulation models (GCMs) as simulated by the MCl Dynamic General... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNH23E2887V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNH23E2887V">Attribution of extreme rainfall from Hurricane Harvey, August 2017</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> van der Wiel, K.; van Oldenborgh, G. J.; Sebastian, A.; Singh, R.; Arrighi, J.; Otto, F. E. L.; Haustein, K.; Li, S.; Vecchi, G.; Cullen, H. M. 2017-12-01 During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation over Houston and the surrounding area, particularly on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. Using observational datasets and high-resolution global climate model experiments we investigate the return period of this event and to what extent anthropogenic climate change influenced the likelihood and intensity of this type of events. The event definition for the attribution is set by the main impact, flooding in the city of Houston. Most rivers crested on August 28 or 29, driven by intensive rainfall on August 26-28. We therefore use the annual maximum of three-day average precipitation as the event definition. Station data (GHCN-D) and a gridded precipitation product (CPC unified analysis) are used to find the return period of the event and changes in the observed record. To attribute changes to anthropogenic climate change we use time-slice experiments from two high-resolution global climate models (EC-Earth 2.3 and GFDL HiFLOR, both integrated at approximately 25 km). A regional model (HadRM3P) was rejected because of unrealistic modelled extremes. Finally we put the attribution results in context, given local vulnerability and exposure. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.1841W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.1841W">Rainfall variability over southern Africa: an overview of current research using satellite and climate model data</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Williams, C.; Kniveton, D.; Layberry, R. 2009-04-01 It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9.2255D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9.2255D">The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Day, Jonathan J.; Tietsche, Steffen; Collins, Mat; Goessling, Helge F.; Guemas, Virginie; Guillory, Anabelle; Hurlin, William J.; Ishii, Masayoshi; Keeley, Sarah P. E.; Matei, Daniela; Msadek, Rym; Sigmond, Michael; Tatebe, Hiroaki; Hawkins, Ed 2016-06-01 Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño-Southern Oscillation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015NatCC...5...56T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015NatCC...5...56T">Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tang, Jinyun; Riley, William J. 2015-01-01 The large uncertainty in soil carbon-climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity (Q10; ref. ) and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. We show that because mineral surfaces interact with substrates, enzymes and microbes, both Q10 and microbial carbon use efficiency are hysteretic (so that neither can be represented by a single static function) and the conventional labile and recalcitrant substrate characterization with static temperature sensitivity is flawed. In a 4-K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker soil carbon-climate feedbacks than did the static Q10 and static carbon use efficiency model when forced with yearly, daily and hourly variable temperatures. These results imply that current Earth system models probably overestimate the response of soil carbon stocks to global warming. Future ecosystem models should therefore consider the dynamic interactions between sorptive mineral surfaces, substrates and microbial processes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19830026140','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830026140">The continuous similarity model of bulk soil-water evaporation</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Clapp, R. B. 1983-01-01 The continuous similarity model of evaporation is described. In it, evaporation is conceptualized as a two stage process. For an initially moist soil, evaporation is first climate limited, but later it becomes soil limited. During the latter stage, the evaporation rate is termed evaporability, and mathematically it is inversely proportional to the evaporation deficit. A functional approximation of the moisture distribution within the soil column is also included in the model. The model was tested using data from four experiments conducted near Phoenix, Arizona; and there was excellent agreement between the simulated and observed evaporation. The model also predicted the time of transition to the soil limited stage reasonably well. For one of the experiments, a third stage of evaporation, when vapor diffusion predominates, was observed. The occurrence of this stage was related to the decrease in moisture at the surface of the soil. The continuous similarity model does not account for vapor flow. The results show that climate, through the potential evaporation rate, has a strong influence on the time of transition to the soil limited stage. After this transition, however, bulk evaporation is independent of climate until the effects of vapor flow within the soil predominate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100033502','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100033502">ARM/GCSS/SPARC TWP-ICE CRM Intercomparison Study</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Fridlind, Ann; Ackerman, Andrew; Petch, Jon; Field, Paul; Hill, Adrian; McFarquhar, Greg; Xie, Shaocheng; Zhang, Minghua 2010-01-01 Specifications are provided for running a cloud-resolving model (CRM) and submitting results in a standardized format for inclusion in a n intercomparison study and archiving for public access. The simulated case study is based on measurements obtained during the 2006 Tropical Warm Pool - International Cloud Experiment (TWP-ICE) led by the U. S. department of Energy Atmospheric Radiation Measurement (ARM) program. The modeling intercomparison study is based on objectives developed in concert with the Stratospheric Processes And their Role in Climate (SPARC) program and the GEWEX cloud system study (GCSS) program. The Global Energy and Water Cycle Experiment (GEWEX) is a core project of the World Climate Research PRogramme (WCRP). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014NatCo...5E5752B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014NatCo...5E5752B">Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M. 2014-12-01 The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4268699','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4268699">Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M. 2014-01-01 The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25482065','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25482065">Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Boulton, Chris A; Allison, Lesley C; Lenton, Timothy M 2014-12-08 The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27465689','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27465689">High sensitivity of Indian summer monsoon to Middle East dust absorptive properties.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Jin, Qinjian; Yang, Zong-Liang; Wei, Jiangfeng 2016-07-28 The absorptive properties of dust aerosols largely determine the magnitude of their radiative impacts on the climate system. Currently, climate models use globally constant values of dust imaginary refractive index (IRI), a parameter describing the dust absorption efficiency of solar radiation, although it is highly variable. Here we show with model experiments that the dust-induced Indian summer monsoon (ISM) rainfall differences (with dust minus without dust) change from -9% to 23% of long-term climatology as the dust IRI is changed from zero to the highest values used in the current literature. A comparison of the model results with surface observations, satellite retrievals, and reanalysis data sets indicates that the dust IRI values used in most current climate models are too low, tending to significantly underestimate dust radiative impacts on the ISM system. This study highlights the necessity for developing a parameterization of dust IRI for climate studies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED31B0281R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED31B0281R">Murals as Models: Supporting NGSS three-dimensional teaching in climate change educator professional learning</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rogers, M. J. B.; Petrone, C.; Merrick, B. A.; Drewes, A. 2017-12-01 The current shift in K-12 science education is towards a teaching and learning approach in which students actively do and experience science in a deep, meaningful way while being fully active in their learning. For students and teachers who have not experienced this approach, this shift is difficult without scaffolding. Professional learning for educators must allow teachers to experience this approach and reflect on their experience. We share an example from our 2017 K-12 Climate Change Academy in which educators created and modified murals of Earth's climate system while investigating ecosystem interactions, the carbon cycle, energy flow, and human impacts. The Academy constituted an online component followed by three consecutive in person days. The mural activity served as a framework. The first mural modeling occurred online. A1: Take a photo of an outdoor landscape. Annotate it with elements of Earth's atmosphere, biosphere, geosphere, hydrosphere and indicate energy flow, carbon cycling, and the processes driving these. Activities 2-6 were employed throughout the in person days. A2: Small groups create 2D, mural sized models of Earth's climate system. A3: Groups use carbon themed cards to document naturally occurring and human-influenced aspects of the carbon cycle on their models. A4-5: Teams add climate change impacts and possible mitigation/adaptation responses to murals. A6: Ongoing throughout, team members modify models as needed based on learning. Throughout the Academy, participants were able to experience the activities as students. As Academy facilitators, we modeled how educators could use these models in their classrooms. We used A1 submissions as a formative assessment tool and also as a guide for forming groups for the first in person mural. A2 was used as a small group icebreaker, serving as a bridge between the online and in person sessions both for community building and for providing peer support in knowledge building. A3-A5 allowed for reflection upon and meaning making from other activities. At set stopping points, participants changed roles to discuss the 3D NGSS elements they experienced and think about how each activity could be used in their classroom. We will share best practices from these activities, how they can be adapted for other uses, and Academy participants' reflections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1233519-collaborative-project-understanding-climate-model-biases-tropical-atlantic-impact-simulations-extreme-climate-events','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1233519-collaborative-project-understanding-climate-model-biases-tropical-atlantic-impact-simulations-extreme-climate-events">Collaborative Project: Understanding Climate Model Biases in Tropical Atlantic and Their Impact on Simulations of Extreme Climate Events</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Chang, Ping Recent studies have revealed that among all the tropical oceans, the tropical Atlantic has experienced the most pronounced warming trend over the 20th century. Many extreme climate events affecting the U.S., such as hurricanes, severe precipitation and drought events, are influenced by conditions in the Gulf of Mexico and the Atlantic Ocean. It is therefore imperative to have accurate simulations of the climatic mean and variability in the Atlantic region to be able to make credible projections of future climate change affecting the U.S. and other countries adjoining the Atlantic Ocean. Unfortunately, almost all global climate models exhibit large biasesmore » in their simulations of tropical Atlantic climate. The atmospheric convection simulation errors in the Amazon region and the associated errors in the trade wind simulations are hypothesized to be a leading cause of the tropical Atlantic biases in climate models. As global climate models have resolutions that are too coarse to resolve some of the atmospheric and oceanic processes responsible for the model biases, we propose to use a high-resolution coupled regional climate model (CRCM) framework to address the tropical bias issue. We propose to combine the expertise in tropical coupled atmosphere-ocean modeling at Texas A&M University (TAMU) and the coupled land-atmosphere modeling expertise at Pacific Northwest National Laboratory (PNNL) to develop a comprehensive CRCM for the Atlantic sector within a general and flexible modeling framework. The atmospheric component of the CRCM will be the NCAR WRF model and the oceanic component will be the Rutgers/UCLA ROMS. For the land component, we will use CLM modified at PNNL to include more detailed representations of vegetation and soil hydrology processes. The combined TAMU-PNNL CRCM model will be used to simulate the Atlantic climate, and the associated land-atmosphere-ocean interactions at a horizontal resolution of 9 km or finer. A particular focus of the model development effort will be to optimize the performance of WRF and ROMS over several thousand of cores by focusing on both the parallel communication libraries and the I/O interfaces, in order to achieve the sustained throughput needed to perform simulations on such fine resolution grids. The CRCM model will be developed within the framework of the Coupler (CPL7) software that is part of the NCAR Community Earth System Model (CESM). Through efforts at PNNL and within the community, WRF and CLM have already been coupled via CPL7. Using the flux coupler approach for the whole CRCM model will allow us to flexibly couple WRF, ROMS, and CLM with each model running on its own grid at different resolutions. In addition, this framework will allow us to easily port parameterizations between CESM and the CRCM, and potentially allow partial coupling between the CESM and the CRCM. TAMU and PNNL will contribute cooperatively to this research endeavor. The TAMU team led by Chang and Saravanan has considerable experience in studying atmosphere-ocean interactions within tropical Atlantic sector and will focus on modeling issues that relate to coupling WRF and ROMS. The PNNL team led by Leung has extensive expertise in atmosphere-land interaction and will be responsible for improving the land surface parameterization. Both teams will jointly work on integrating WRF-ROMS and WRF-CLM to couple WRF, ROMS, and CLM through CPL7. Montuoro of the TAMU Supercomputing Center will be responsible for improving the MPI and Parallel IO interfaces of the CRCM. Both teams will contribute to the design and execution of the proposed numerical experiments and jointly perform analysis of the numerical experiments.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27979008','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27979008">Association Between Perceived Medical School Diversity Climate and Change in Depressive Symptoms Among Medical Students: A Report from the Medical Student CHANGE Study.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Hardeman, Rachel R; Przedworski, Julia M; Burke, Sara; Burgess, Diana J; Perry, Sylvia; Phelan, Sean; Dovidio, John F; van Ryn, Michelle 2016-01-01 To determine whether perceptions of the medical school diversity climate are associated with depression symptoms among medical students. Longitudinal web-based survey conducted in the fall of 2010 and spring of 2014 administered to a national sample of medical students enrolled in 49 schools across the U.S. (n = 3756). Negative diversity climate measured by perceptions of the institution's racial climate; exposure to negative role modeling by medical educators; frequency of witnessing discrimination in medical school. Depression symptoms measured by the PROMIS Emotional Distress-Depression Short-Form. 64% of students reported a negative racial climate; 81% reported witnessing discrimination toward other students at least once, and 94% reported witnessing negative role modeling. Negative racial climate, witnessed discrimination, and negative role modeling were independently and significantly associated with an increase in depression symptoms between baseline and follow-up. Adjusting for students' personal experiences of mistreatment, associations between depressive symptoms and negative racial climate and negative role modeling, remained significant (.72 [.51-.93]; .33 [.12-.54], respectively). Among medical students, greater exposure to a negative medical school diversity climate was associated with an increase in self-reported depressive symptoms. Copyright © 2016 National Medical Association. All rights reserved. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4792408','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4792408">Wave–turbulence interaction-induced vertical mixing and its effects in ocean and climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Qiao, Fangli; Yuan, Yeli; Deng, Jia; Dai, Dejun; Song, Zhenya 2016-01-01 Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability. PMID:26953182 </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active">15</li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active">16</li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23185568','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23185568">Climate change: believing and seeing implies adapting.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Blennow, Kristina; Persson, Johannes; Tomé, Margarida; Hanewinkel, Marc 2012-01-01 Knowledge of factors that trigger human response to climate change is crucial for effective climate change policy communication. Climate change has been claimed to have low salience as a risk issue because it cannot be directly experienced. Still, personal factors such as strength of belief in local effects of climate change have been shown to correlate strongly with responses to climate change and there is a growing literature on the hypothesis that personal experience of climate change (and/or its effects) explains responses to climate change. Here we provide, using survey data from 845 private forest owners operating in a wide range of bio-climatic as well as economic-social-political structures in a latitudinal gradient across Europe, the first evidence that the personal strength of belief and perception of local effects of climate change, highly significantly explain human responses to climate change. A logistic regression model was fitted to the two variables, estimating expected probabilities ranging from 0.07 (SD ± 0.01) to 0.81 (SD ± 0.03) for self-reported adaptive measures taken. Adding socio-demographic variables improved the fit, estimating expected probabilities ranging from 0.022 (SD ± 0.008) to 0.91 (SD ± 0.02). We conclude that to explain and predict adaptation to climate change, the combination of personal experience and belief must be considered. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50..777T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50..777T">Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Toh, Ying Ying; Turner, Andrew G.; Johnson, Stephanie J.; Holloway, Christopher E. 2018-02-01 The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model's local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3857548','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3857548">A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M. 2013-01-01 We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26145454','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26145454">Results of a community-based survey of construction safety climate for Hispanic workers.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Marin, Luz S; Cifuentes, Manuel; Roelofs, Cora 2015-01-01 Hispanic construction workers experience high rates of occupational injury, likely influenced by individual, organizational, and social factors. To characterize the safety climate of Hispanic construction workers using worker, contractor, and supervisor perceptions of the workplace. We developed a 40-item interviewer-assisted survey with six safety climate dimensions and administered it in Spanish and English to construction workers, contractors, and supervisors. A safety climate model, comparing responses and assessing contributing factors was created based on survey responses. While contractors and construction supervisors' (n = 128) scores were higher, all respondents shared a negative perception of safety climate. Construction workers had statistically significantly lower safety climate scores compared to supervisors and contractors (30·6 vs 46·5%, P<0·05). Safety climate scores were not associated with English language ability or years lived in the United States. We found that Hispanic construction workers in this study experienced a poor safety climate. The Hispanic construction safety climate model we propose can serve as a framework to guide organizational safety interventions and evaluate safety climate improvements. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4597011','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4597011">Results of a community-based survey of construction safety climate for Hispanic workers</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Marin, Luz S; Cifuentes, Manuel; Roelofs, Cora 2015-01-01 Background: Hispanic construction workers experience high rates of occupational injury, likely influenced by individual, organizational, and social factors. Objectives: To characterize the safety climate of Hispanic construction workers using worker, contractor, and supervisor perceptions of the workplace. Methods: We developed a 40-item interviewer-assisted survey with six safety climate dimensions and administered it in Spanish and English to construction workers, contractors, and supervisors. A safety climate model, comparing responses and assessing contributing factors was created based on survey responses. Results: While contractors and construction supervisors’ (n = 128) scores were higher, all respondents shared a negative perception of safety climate. Construction workers had statistically significantly lower safety climate scores compared to supervisors and contractors (30.6 vs 46.5%, P<0.05). Safety climate scores were not associated with English language ability or years lived in the United States. Conclusions: We found that Hispanic construction workers in this study experienced a poor safety climate. The Hispanic construction safety climate model we propose can serve as a framework to guide organizational safety interventions and evaluate safety climate improvements. PMID:26145454 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19880046502&hterms=climate+change+evidence&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dclimate%2Bchange%2Bevidence','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19880046502&hterms=climate+change+evidence&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dclimate%2Bchange%2Bevidence">The greenhouse theory of climate change - A test by an inadvertent global experiment</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Ramanathan, V. 1988-01-01 The greenhouse theory of climate change has reached the crucial stage of verification. Surface warming as large as that predicted by models would be unprecedented during an interglacial period such as the present. The theory, its scope for verification, and the emerging complexities of the climate feedback mechanisms are discussed in this paper. The evidence for change is described and competing nonclimatic forcings are discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3893R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3893R">Multiple causes of the Younger Dryas cold period: new insights from coupled model experiments constrained by data assimilation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Renssen, Hans; Mairesse, Aurélien; Goosse, Hugues; Mathiot, Pierre; Heiri, Oliver; Roche, Didier M.; Nisancioglu, Kerim H.; Valdes, Paul J. 2016-04-01 The Younger Dryas cooling event disrupted the overall warming trend in the North Atlantic region during the last deglaciation. Climate change during the Younger Dryas was abrupt, and thus provides insights into the sensitivity of the climate system to perturbations. The sudden Younger Dryas cooling has traditionally been attributed to a shut-down of the Atlantic meridional overturning circulation by meltwater discharges. However, alternative explanations such as strong negative radiative forcing and a shift in atmospheric circulation have also been offered. In this study we investigate the importance of these different forcings in coupled climate model experiments constrained by data assimilation. We find that the Younger Dryas climate signal as registered in proxy evidence is best simulated using a combination of processes: a weakened Atlantic meridional overturning circulation, moderate negative radiative forcing and an altered atmospheric circulation. We conclude that none of the individual mechanisms alone provide a plausible explanation for the Younger Dryas cold period. We suggest that the triggers for abrupt climate changes like the Younger Dryas are more complex than suggested so far, and that studies on the response of the climate system to perturbations should account for this complexity. Reference: Renssen, H. et al. (2015) Multiple causes of the Younger Dryas cold period. Nature Geoscience 8, 946-949. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1710715V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1710715V">Detecting hydrological changes through conceptual model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo 2015-04-01 Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9026C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9026C">The new climate data record of total and spectral solar irradiance: Current progress and future steps</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Coddington, Odele; Lean, Judith; Rottman, Gary; Pilewskie, Peter; Snow, Martin; Lindholm, Doug 2016-04-01 We present a climate data record of Total Solar Irradiance (TSI) and Solar Spectral Irradiance (SSI), with associated time and wavelength dependent uncertainties, from 1610 to the present. The data record was developed jointly by the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder and the Naval Research Laboratory (NRL) as part of the National Oceanographic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) Climate Data Record (CDR) Program, where the data record, source code, and supporting documentation are archived. TSI and SSI are constructed from models that determine the changes from quiet Sun conditions arising from bright faculae and dark sunspots on the solar disk using linear regression of proxies of solar magnetic activity with observations from the SOlar Radiation and Climate Experiment (SORCE) Total Irradiance Monitor (TIM), Spectral Irradiance Monitor (SIM), and SOlar Stellar Irradiance Comparison Experiment (SOLSTICE). We show that TSI can be separately modeled to within TIM's measurement accuracy from solar rotational to solar cycle time scales and we assume that SSI measurements are reliable on solar rotational time scales. We discuss the model formulation, uncertainty estimates, and operational implementation and present comparisons of the modeled TSI and SSI with the measurement record and with other solar irradiance models. We also discuss ongoing work to assess the sensitivity of the modeled irradiances to model assumptions, namely, the scaling of solar variability from rotational-to-cycle time scales and the representation of the sunspot darkening index. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H41D1359R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H41D1359R">Comparisons with observational and experimental manipulation data imply needed conceptual changes to ESM land models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Riley, W. J.; Zhu, Q.; Tang, J. 2016-12-01 The land models integrated in Earth System Models (ESMs) are critical components necessary to predict soil carbon dynamics and carbon-climate interactions under a changing climate. Yet, these models have been shown to have poor predictive power when compared with observations and ignore many processes known to the observational communities to influence above and belowground carbon dynamics. Here I will report work to tightly couple observations and perturbation experiment results with development of an ESM land model (ALM), focusing on nutrient constraints of the terrestrial C cycle. Using high-frequency flux tower observations and short-term nitrogen and phosphorus perturbation experiments, we show that conceptualizing plant and soil microbe interactions as a multi-substrate, multi-competitor kinetic network allows for accurate prediction of nutrient acquisition. Next, using multiple-year FACE and fertilization response observations at many forest sites, we show that capturing the observed responses requires representation of dynamic allocation to respond to the resulting stresses. Integrating the mechanisms implied by these observations into ALM leads to much lower observational bias and to very different predictions of long-term soil and aboveground C stocks and dynamics, and therefore C-climate feedbacks. I describe how these types of observational constraints are being integrated into the open-source International Land Model Benchmarking (ILAMB) package, and end with the argument that consolidating as many observations of all sorts for easy use by modelers is an important goal to improve C-climate feedback predictions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20140011122&hterms=Chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DChemistry','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20140011122&hterms=Chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DChemistry">The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140011122'); toggleEditAbsImage('author_20140011122_show'); toggleEditAbsImage('author_20140011122_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140011122_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140011122_hide"> 2013-01-01 The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19840014040&hterms=Turbidity+atlantic+west&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DTurbidity%2Batlantic%2Bwest','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19840014040&hterms=Turbidity+atlantic+west&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DTurbidity%2Batlantic%2Bwest">The sensitivity of a general circulation model to Saharan dust heating</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Randall, D. A.; Carlson, T.; Mintz, Y. 1984-01-01 During the Northern summer, sporadic outbreaks of wind borne Saharan dust are carried out over the Atlantic by the tropical easterlies. Optical depths due to the dust can reach 3 near the African coast, and the dust cloud can be detected as far west as the Caribbean Sea (Carlson, 1979). In order to obtain insight into the possible effects of Saharan dust on the weather and climate of North Africa and the tropical Atlantic Ocean, simulation experiments have been performed with the Climate Model of the Goddard Laboratory for Atmospheric Sciences. The most recent version of the model is described by Randall (1982). The model produces realistic simulations of many aspects of the observed climate and its seasonal variation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ArtSa..51..107W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ArtSa..51..107W">Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals - g2 Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Winska, M. 2016-12-01 The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C53A0830M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C53A0830M">Flowline Modeling of the Quelccaya Icecap to Constrain Tropical Climate Fluctuations During the Holocene</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Malone, A.; Pierrehumbert, R.; Insel, N.; Lowell, T. V.; Kelly, M. A. 2012-12-01 The response of the tropics to climate forcing mechanisms is poorly understood, and there is limited data regarding past tropical climate fluctuations. Past climate fluctuations often leave a detectable record of glacial response in the location of moraines. Computer reconstructions of glacial length variations can thus help constrain past climate fluctuations. Chronology and position data for Holocene moraines are available for the Quelccaya Ice Cap in the Peruvian Andes. The Quelccaya Ice Cap is the equatorial region's largest glaciated area, and given its size and the available data, it is an ideal location at which to use a computer glacier model to reconstruct past glacial extents and constrain past tropical climate fluctuations. We can reproduce the current length and shape of the glacier in the Huancane Valley of the Quelccaya Ice Cap using a 1-D mountain glacier flowline model with an orographic precipitation scheme, an energy balance model for the ablation scheme, and reasonable modern climate conditions. We conduct two experiments. First, we determine the amount of cooling necessary to reproduce the observed Holocene moraine locations by holding the precipitation profile constant and varying the mean sea surface temperature (SST) values. Second, we determine the amount of precipitation increase necessary to reproduce the observed moraine locations by holding the mean SST value constant and varying the maximum precipitation values. We find that the glacier's length is highly sensitive to changes in temperature while only weakly sensitive to changes in precipitation. In the constant precipitation experiment, a decrease in the mean SST of only 0.35 °C can reproduce the nearest Holocene moraine downslope from the current glacier terminus and a decrease in the mean SST of only 1.43 °C can reproduce the furthest Holocene moraine downslope from the current terminus. In the experiment with constant SST, the necessary increase in maximum precipitation is much greater. An increase in the maximum precipitation of 30% is necessary to reproduce the nearest Holocene moraine and an increase in the maximum precipitation of 130% is necessary to reproduce the furthest Holocene moraine. Our results provide a range of values for the mean SST and maximum precipitation that can reproduce the location of Holocene glacial moraines, constraining some of the climate fluctuations in the tropics during the Holocene. These constraints can be used to test hypotheses for climate forcing mechanisms during Holocene events such as the Little Ice Age and possibly provide insight into future tropical climate fluctuations given current and future forcing mechanisms. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=climate+AND+organizational&pg=7&id=EJ973674','ERIC'); return false;" href="https://eric.ed.gov/?q=climate+AND+organizational&pg=7&id=EJ973674">Exploring the Postgraduate Research Climate and the Postgraduate Research Experience: A Conceptual Model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a> Govender, K. K. 2011-01-01 The objective of this article is to develop a conceptual model aimed at improving the postgraduate research students' experience. Since postgraduate students "vote with their feet" an improved understanding of the postgraduate research service encounter may result in improving the quality of the encounter and so increasing throughput and… </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1499L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1499L">The influence of atmospheric grid resolution in a climate model-forced ice sheet simulation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lofverstrom, Marcus; Liakka, Johan 2018-04-01 Coupled climate-ice sheet simulations have been growing in popularity in recent years. Experiments of this type are however challenging as ice sheets evolve over multi-millennial timescales, which is beyond the practical integration limit of most Earth system models. A common method to increase model throughput is to trade resolution for computational efficiency (compromise accuracy for speed). Here we analyze how the resolution of an atmospheric general circulation model (AGCM) influences the simulation quality in a stand-alone ice sheet model. Four identical AGCM simulations of the Last Glacial Maximum (LGM) were run at different horizontal resolutions: T85 (1.4°), T42 (2.8°), T31 (3.8°), and T21 (5.6°). These simulations were subsequently used as forcing of an ice sheet model. While the T85 climate forcing reproduces the LGM ice sheets to a high accuracy, the intermediate resolution cases (T42 and T31) fail to build the Eurasian ice sheet. The T21 case fails in both Eurasia and North America. Sensitivity experiments using different surface mass balance parameterizations improve the simulations of the Eurasian ice sheet in the T42 case, but the compromise is a substantial ice buildup in Siberia. The T31 and T21 cases do not improve in the same way in Eurasia, though the latter simulates the continent-wide Laurentide ice sheet in North America. The difficulty to reproduce the LGM ice sheets in the T21 case is in broad agreement with previous studies using low-resolution atmospheric models, and is caused by a substantial deterioration of the model climate between the T31 and T21 resolutions. It is speculated that this deficiency may demonstrate a fundamental problem with using low-resolution atmospheric models in these types of experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040082190&hterms=Asian&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DAsian','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040082190&hterms=Asian&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DAsian">The North Pacific as a Regulator of Summertime Climate Over North America and the Asian Monsoon</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Lau, William K. M.; Wang, H. 2004-01-01 The interannual variability of summertime rainfall over the U.S. may be linked to climate anomalies over Pacific and East Asia through teleconnection patterns that may be components of recurring global climate modes in boreal summer (Lau and Weng 2002). In this study, maintenance of the boreal summer teleconnection patterns is investigated. The particular focus is on the potential effects of North Pacific air-sea interaction on climate anomalies over the U.S. Observational data, reanalysis and outputs of a series of NASA NSIPP AGCM and AGCM coupled to NASA GSFC MLO model experiments are used. Statistical analysis of observations and NSIPP AMIP type simulations indicates that, the interannual variability of observed warm season precipitation over the U.S. is related to SST variation in both tropical and North Pacific, whereas the NSIPP AMIP simulated summertime US. precipitation variation mainly reflects impact of ENS0 in tropical Pacific. This implies the potential importance of air-sea interaction in North Pacific in contributing to the interannual variability of observed summer climate over the U.S. The anomalous atmospheric circulation associated with the dominant summertime teleconnection modes in both observations and NSIPP AMIP simulations are further diagnosed, using stationary wave modeling approach. In observations, for the two dominant modes, both anomalous diabatic heating and anomalous transients significantly contribute to the anomalous circulation. The distributions of the anomalous diabatic heating and transient forcing are quadrature configured over North Pacific and North America, so that both forcings act constructively to maintain the teleconnection patterns. The contrast between observations and NSIPP AMIP simulations from stationary wave modeling diagnosis confirms the previous conclusion based on statistical analysis. To better appreciate the role of extra-tropical air-sea interaction in maintaining the summertime teleconnection pattern, various dynamical and physical fields and their inter- linkage in the series of NSIPP AGCM and AGCM coupled to MLO model experiments are examined in-depth. Based on comparison between different model experiments, we will discuss the physical and dynamical mechanisms through which the air-sea interaction in extratropics, and transient mean flow interactions over the North Pacific, affects interannual variation of U.S. climate during boreal summer. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B43B0464K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B43B0464K">Vulnerability on the Roof of the World: Resilience to Climate Change and Natural Resource Policies on the Tibetan Plateau</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Klein, J. A.; Hopping, K. A.; Yeh, E.; Hu, J.; Nyima, Y.; Boone, R.; Galvin, K.; Kang, S.; Ojima, D. S. 2010-12-01 Pastoralists on the Tibetan Plateau are a marginalized people living in an extreme environment and may be especially vulnerable as the system approaches critical thresholds. In Tibet, temperatures are increasing several times more than the global average while the frequency and severity of severe snowstorms is predicted to increase. Pastoralists are also experiencing reduced mobility and severe grazing restrictions. We are using interdisciplinary frameworks and methods that include a multifactor ecological experiment, household interviews, remote sensing, and a coupled ecosystem and household decision-making model to examine herder and ecosystem vulnerability to climate change and extreme weather events within the context of changing natural resource policies in China. The fully factorial ecological experiment includes two climate changes (warming and spring snow additions) and two types of grazing (yak and pika). We established the experiment in 2008 within the Tibet Autonomous Region (4,870 m) and are monitoring microclimate, vegetation, nutrient availability, carbon fluxes and stable isotopes. We are investigating the sensitivity of the system, whether it is likely to cross critical thresholds, and how resilient this system may be to predicted climate and land use changes. Semi-structured interviews on indigenous knowledge and vulnerability complement the ecological experimental work. We are asking herders about climatic and ecological change and vulnerability to snow disasters. To integrate our ecological and social findings, we are coupling an ecosystem model to an agent-based pastoral household model. Our results from the experiment and the indigenous knowledge study suggest that Kobresia pygmaea, the dominant species and primary grazing resource, is vulnerable to warming. Snow additions can partially mediate this effect. Herders throughout this region share common knowledge about both climatic and ecological changes, but appear to be more closely attuned to ecological shifts than to gradual climate changes. Herder perceptions about climate trends often contradict local weather station data, but herders tend to be in strong agreement that grassland health has declined. These results suggest that rangeland degradation has occurred, and that climate warming may be one driver responsible for these changes. While additional snow may improve ecological conditions, the warming-induced degradation may make the social-ecological system more vulnerable to large snowstorm events. Our findings suggest that climate adaptation strategies should address the effects of both warming and extreme weather events and should also encourage land use policies that will maintain these systems under change. The vulnerability of ecosystems on the roof of the world has implications for the 1x109 people living downstream and for feedbacks to the Earth’s climate system. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ClDy...37.1293P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ClDy...37.1293P">Diagnosing GCM errors over West Africa using relaxation experiments. Part I: summer monsoon climatology and interannual variability</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pohl, Benjamin; Douville, Hervé 2011-10-01 The CNRM atmospheric general circulation model Arpege-Climat is relaxed towards atmospheric reanalyses outside the 10°S-32°N 30°W-50°E domain in order to disentangle the regional versus large-scale sources of climatological biases and interannual variability of the West African monsoon (WAM). On the one hand, the main climatological features of the monsoon, including the spatial distribution of summer precipitation, are only weakly improved by the nudging, thereby suggesting the regional origin of the Arpege-Climat biases. On the other hand, the nudging technique is relatively efficient to control the interannual variability of the WAM dynamics, though the impact on rainfall variability is less clear. Additional sensitivity experiments focusing on the strong 1994 summer monsoon suggest that the weak sensitivity of the model biases is not an artifact of the nudging design, but the evidence that regional physical processes are the main limiting factors for a realistic simulation of monsoon circulation and precipitation in the Arpege-Climat model. Sensitivity experiments to soil moisture boundary conditions are also conducted and highlight the relevance of land-atmosphere coupling for the amplification of precipitation biases. Nevertheless, the land surface hydrology is not the main explanation for the model errors that are rather due to deficiencies in the atmospheric physics. The intraseasonal timescale and the model internal variability are discussed in a companion paper. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp..108W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp..108W">Spatiotemporal characteristics of heat waves over China in regional climate simulations within the CORDEX-EA project</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, Pinya; Tang, Jianping; Sun, Xuguang; Liu, Jianyong; Juan, Fang 2018-03-01 Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active">16</li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active">17</li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4312984','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4312984">On the relationship between personal experience, affect and risk perception: The case of climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> van der Linden, Sander 2014-01-01 Examining the conceptual relationship between personal experience, affect, and risk perception is crucial in improving our understanding of how emotional and cognitive process mechanisms shape public perceptions of climate change. This study is the first to investigate the interrelated nature of these variables by contrasting three prominent social-psychological theories. In the first model, affect is viewed as a fast and associative information processing heuristic that guides perceptions of risk. In the second model, affect is seen as flowing from cognitive appraisals (i.e., affect is thought of as a post-cognitive process). Lastly, a third, dual-process model is advanced that integrates aspects from both theoretical perspectives. Four structural equation models were tested on a national sample (N = 808) of British respondents. Results initially provide support for the “cognitive” model, where personal experience with extreme weather is best conceptualized as a predictor of climate change risk perception and, in turn, risk perception a predictor of affect. Yet, closer examination strongly indicates that at the same time, risk perception and affect reciprocally influence each other in a stable feedback system. It is therefore concluded that both theoretical claims are valid and that a dual-process perspective provides a superior fit to the data. Implications for theory and risk communication are discussed. © 2014 The Authors. European Journal of Social Psychology published by John Wiley & Sons, Ltd. PMID:25678723 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC43C0745D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC43C0745D">Increased flood risks in the Sacramento-San Joaquin Valleys, CA, under climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Das, T.; Hidalgo-Leon, H.; Dettinger, M.; Cayan, D. 2008-12-01 Natural calamities like floods cause immense damages to human society globally, and California is no exception. A simulation analysis of flood generation in the western Sierra Nevada of California was carried out on simulated by the Variable Infiltration Capacity (VIC) hydrologic model under prescribed changes in precipitation (+10 percent) and temperature (+3oC and +5oC) to evaluate likely changes in 3-day flood- frequency curves under climate change. An additional experiment was carried out where snow production was artificially turned off in VIC. All these experiments showed larger flood magnitudes from California's Northern Sierra Nevada (NSN) and Southern Sierra Nevada (SSN), but the changes (for floods larger than the historical 20-year floods) were significant (at 90 percent confidence level) only in the SSN for severe warming cases. Another analysis using downscaled daily precipitation and temperature projections from three General Circulation Models (CNRM CM3, GFDL CM2.1 and NCAR PCM1) and emission scenario A2 as input to VIC yielded a general increase in the 3-days annual maximum flows under climate change. The increases are significant (at 90 percent confidence level) in the SSN for the period 2051-2099 with all the three climate models analyzed. In the NSN the increases are significant only with the CNRM CM3 model. In general, the frequency of floods increases or stayed same under the projected future climates, and some of the projected floods were unprecedentedly large when compared to historical simulations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9721P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9721P">The climate4impact portal: bridging the CMIP5 and CORDEX data infrastructure to impact users</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Plieger, Maarten; Som de Cerff, Wim; Pagé, Christian; Tatarinova, Natalia; Cofiño, Antonio; Vega Saldarriaga, Manuel; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Sjökvist, Elin 2015-04-01 The aim of climate4impact is to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. The portal is based on 21 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. It has been developed within the European projects IS-ENES and IS-ENES2 for more than 5 years, and its development currently continues within IS-ENES2 and CLIPC. As the climate impact community is very broad, the focus is mainly on the scientific impact community. This work has resulted in the ENES portal interface for climate impact communities and can be visited at www.climate4impact.eu. The climate4impact is connected to the Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and regional climate model data (RCM) data from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services using OpenID, and offers a user interface for searching, visualizing and downloading global climate model data and more. A challenging task was to describe the available model data and how it can be used. The portal tries to inform users about possible caveats when using climate model data. All impact use cases are described in the documentation section, using highlighted keywords pointing to detailed information in the glossary. During the project, the content management system Drupal was used to enable partners to contribute on the documentation section. In this presentation the architecture and following items will be detailed: - Visualization: Visualize data from ESGF data nodes using ADAGUC Web Map Services. - Processing: Transform data, subset, export into other formats, and perform climate indices calculations using Web Processing Services implemented by PyWPS, based on NCAR NCPP OpenClimateGIS and IS-ENES2 icclim. - Security: Login using OpenID for access to the ESGF data nodes. The ESGF works in conjunction with several external websites and systems. The climate4impact portal uses X509 based short lived credentials, generated on behalf of the user with a MyProxy service. Single Sign-on (SSO) is used to make these websites and systems work together. - Discovery: Facetted search based on e.g. variable name, model and institute using the ESGF search services. A catalog browser allows for browsing through CMIP5 and any other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA). - Download: Directly from ESGF nodes and other THREDDS catalogs This architecture will also be used for the future Copernicus platform, developed in the EU FP7 CLIPC project. - Connection with the downscaling portal of the university of Cantabria - Experiences on the question and answer site via Askbot The current main objectives for climate4impact can be summarized in two objectives. The first one is to work on a web interface which automatically generates a graphical user interface on WPS endpoints. The WPS calculates climate indices and subset data using OpenClimateGIS/icclim on data stored in ESGF data nodes. Data is then transmitted from ESGF nodes over secured OpenDAP and becomes available in a new, per user, secured OpenDAP server. The results can then be visualized again using ADAGUC WMS. Dedicated wizards for processing of climate indices will be developed in close collaboration with users. The second one is to expose climate4impact services, so as to offer standardized services which can be used by other portals. This has the advantage to add interoperability between several portals, as well as to enable the design of specific portals aimed at different impact communities, either thematic or national, for example. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC43C1046B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC43C1046B">A network-base analysis of CMIP5 "historical" experiments</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bracco, A.; Foudalis, I.; Dovrolis, C. 2012-12-01 In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.B31D0348W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.B31D0348W">Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R. 2011-12-01 Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612972V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612972V">SysSon: A Sonification Platform for Climate Data</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Visda, Goudarzi; Hanns Holger, Rutz; Katharina, Vogt 2014-05-01 Climate data provide a challenging working basis for sonification. Both model data and measured data are assessed in collaboration with the Wegener Center for Climate and Global Change. The multi dimensionality and multi variety of climate data has a great potential for auditory displays. Furthermore, there is consensus on global climate change and the necessity of intensified climate research today in the scientific community and general public. Sonification provides a new means to communicate scientific results and inform a wider audience. SysSon is a user centered auditory platform for climate scientists to analyze data. It gives scientists broader insights by extracting hidden patterns and features from data that is not possible using a single modal visual interface. A variety of soundscapes to chose from lessens the fatigue that comes with repeated and sustained listening to long streams of data. Initial needs assessments and user tests made the work procedures and the terminology of climate scientists clear and informed the architecture of our system. Furthermore, experiments evaluated the sound design which led to a more advanced soundscape and improvement of the auditory display. We present a novel interactive sonification tool which combines a workspace for the scientists with a development environment for sonification models. The tool runs on different operating systems and is released as open source. In the standalone desktop application, multiple data sources can be imported, navigated and manipulated either via text or a graphical interface, including traditional plotting facilities. Sound models are built from unit generator graphs which are enhanced with matrix manipulation functions. They allow us to systematically experiment with elements known from the visual domain, such as range selections, scaling, thresholding, markers and labels. The models are organized in an extensible library, from which the user can choose and parametrize. Importance is given to the persistence of all configurations, in order to faithfully reproduce sonification instances. Finally, the platform is prepared to allow the composition of interactive sound installations, transitioning between the scientific lab and the gallery space. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1511535B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1511535B">WRF4SG: A Scientific Gateway for climate experiment workflows</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Blanco, Carlos; Cofino, Antonio S.; Fernandez-Quiruelas, Valvanuz 2013-04-01 The Weather Research and Forecasting model (WRF) is a community-driven and public domain model widely used by the weather and climate communities. As opposite to other application-oriented models, WRF provides a flexible and computationally-efficient framework which allows solving a variety of problems for different time-scales, from weather forecast to climate change projection. Furthermore, WRF is also widely used as a research tool in modeling physics, dynamics, and data assimilation by the research community. Climate experiment workflows based on Weather Research and Forecasting (WRF) are nowadays among the one of the most cutting-edge applications. These workflows are complex due to both large storage and the huge number of simulations executed. In order to manage that, we have developed a scientific gateway (SG) called WRF for Scientific Gateway (WRF4SG) based on WS-PGRADE/gUSE and WRF4G frameworks to ease achieve WRF users needs (see [1] and [2]). WRF4SG provides services for different use cases that describe the different interactions between WRF users and the WRF4SG interface in order to show how to run a climate experiment. As WS-PGRADE/gUSE uses portlets (see [1]) to interact with users, its portlets will support these use cases. A typical experiment to be carried on by a WRF user will consist on a high-resolution regional re-forecast. These re-forecasts are common experiments used as input data form wind power energy and natural hazards (wind and precipitation fields). In the cases below, the user is able to access to different resources such as Grid due to the fact that WRF needs a huge amount of computing resources in order to generate useful simulations: * Resource configuration and user authentication: The first step is to authenticate on users' Grid resources by virtual organizations. After login, the user is able to select which virtual organization is going to be used by the experiment. * Data assimilation: In order to assimilate the data sources, the user has to select them browsing through LFC Portlet. * Design Experiment workflow: In order to configure the experiment, the user will define the type of experiment (i.e. re-forecast), and its attributes to simulate. In this case the main attributes are: the field of interest (wind, precipitation, ...), the start and end date simulation and the requirements of the experiment. * Monitor workflow: In order to monitor the experiment the user will receive notification messages based on events and also the gateway will display the progress of the experiment. * Data storage: Like Data assimilation case, the user is able to browse and view the output data simulations using LFC Portlet. The objectives of WRF4SG can be described by considering two goals. The first goal is to show how WRF4SG facilitates to execute, monitor and manage climate workflows based on the WRF4G framework. And the second goal of WRF4SG is to help WRF users to execute their experiment workflows concurrently using heterogeneous computing resources such as HPC and Grid. [1] Kacsuk, P.: P-GRADE portal family for grid infrastructures. Concurrency and Computation: Practice and Experience. 23, 235-245 (2011). [2] http://www.meteo.unican.es/software/wrf4g </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A13A0280S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A13A0280S">The impact of climatological model biases in the North Atlantic jet on predicted future circulation change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Simpson, I. 2015-12-01 A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113097D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113097D">Land-Use and Climate : first results from the LUCID experiments ; implications for experimental design in IPCC-AR5</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> de Noblet, N.; Pitman, A.; Participants, Lucid 2009-04-01 The project "Land-Use and Climate, IDentification of robust impacts" (LUCID) was conceived under the auspices of IGBP-iLEAPS and GEWEX-GLASS, to address the robustness of 'local' and possible remote impacts of land-use induced land-cover changes (LCC). LUCID explores, using methodologies that major climate modelling groups recognise, those impacts of LCC that are robust - that is, above the noise generated by model variability and consistent across a suite of climate models. To start with, seven climate models were run, in ensemble mode (5 realisations per 31-years long experiment), with prescribed observed sea-surface temperatures (SSTs) and sea ice extent (SIc). Pre-industrial and present-day simulations were used to explore the impacts of biogeophysical impacts of human-induced land cover change. The imposed LCC perturbation led to statistically significant changes in latent heat flux and near-surface temperature over the regions of land cover change, but few significant changes in precipitation. Our results show no common remote impacts of land cover change. They also highlight a dilemma for both historical hind-casts and future projections; land cover change is regionally important, but it is not feasible within the time frame of the next IPCC (AR5) assessment to implement this change commonly across multiple models. Further analysis are in progress and will be presented to identify the continental regions where changes in LCC may have been more important than the combined changes in SSTs, SIc and CO2 between the pre-industrial times and nowadays. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005IJCli..25.1265W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005IJCli..25.1265W">A compound reconstructed prediction model for nonstationary climate processes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Wang, Geli; Yang, Peicai 2005-07-01 Based on the idea of climate hierarchy and the theory of state space reconstruction, a local approximation prediction model with the compound structure is built for predicting some nonstationary climate process. By means of this model and the data sets consisting of north Indian Ocean sea-surface temperature, Asian zonal circulation index and monthly mean precipitation anomaly from 37 observation stations in the Inner Mongolia area of China (IMC), a regional prediction experiment for the winter precipitation of IMC is also carried out. When using the same sign ratio R between the prediction field and the actual field to measure the prediction accuracy, an averaged R of 63% given by 10 predictions samples is reached. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/14654317','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/14654317">Potential effect of climate change on malaria transmission in Africa.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Tanser, Frank C; Sharp, Brian; le Sueur, David 2003-11-29 Climate change is likely to affect transmission of vector-borne diseases such as malaria. We quantitatively estimated current malaria exposure and assessed the potential effect of projected climate scenarios on malaria transmission. We produced a spatiotemporally validated (against 3791 parasite surveys) model of Plasmodium falciparum malaria transmission in Africa. Using different climate scenarios from the Hadley Centre global climate model (HAD CM3) climate experiments, we projected the potential effect of climate change on transmission patterns. Our model showed sensitivity and specificity of 63% and 96%, respectively (within 1 month temporal accuracy), when compared with the parasite surveys. We estimate that on average there are 3.1 billion person-months of exposure (445 million people exposed) in Africa per year. The projected scenarios would estimate a 5-7% potential increase (mainly altitudinal) in malaria distribution with surprisingly little increase in the latitudinal extents of the disease by 2100. Of the overall potential increase (although transmission will decrease in some countries) of 16-28% in person-months of exposure (assuming a constant population), a large proportion will be seen in areas of existing transmission. The effect of projected climate change indicates that a prolonged transmission season is as important as geographical expansion in correct assessment of the effect of changes in transmission patterns. Our model constitutes a valid baseline against which climate scenarios can be assessed and interventions planned. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3324023','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3324023">Insights from past millennia into climatic impacts on human health and survival</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> McMichael, Anthony J. 2012-01-01 Climate change poses threats to human health, safety, and survival via weather extremes and climatic impacts on food yields, fresh water, infectious diseases, conflict, and displacement. Paradoxically, these risks to health are neither widely nor fully recognized. Historical experiences of diverse societies experiencing climatic changes, spanning multicentury to single-year duration, provide insights into population health vulnerability—even though most climatic changes were considerably less than those anticipated this century and beyond. Historical experience indicates the following. (i) Long-term climate changes have often destabilized civilizations, typically via food shortages, consequent hunger, disease, and unrest. (ii) Medium-term climatic adversity has frequently caused similar health, social, and sometimes political consequences. (iii) Infectious disease epidemics have often occurred in association with briefer episodes of temperature shifts, food shortages, impoverishment, and social disruption. (iv) Societies have often learnt to cope (despite hardship for some groups) with recurring shorter-term (decadal to multiyear) regional climatic cycles (e.g., El Niño Southern Oscillation)—except when extreme phases occur. (v) The drought–famine–starvation nexus has been the main, recurring, serious threat to health. Warming this century is not only likely to greatly exceed the Holocene's natural multidecadal temperature fluctuations but to occur faster. Along with greater climatic variability, models project an increased geographic range and severity of droughts. Modern societies, although larger, better resourced, and more interconnected than past societies, are less flexible, more infrastructure-dependent, densely populated, and hence are vulnerable. Adverse historical climate-related health experiences underscore the case for abating human-induced climate change. PMID:22315419 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..4410549K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..4410549K">Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.; Chang, Ping 2017-10-01 We alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ˜8-50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the global average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC22F..06K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC22F..06K">The Effects of Anthropogenic Land Cover Change on Global and Regional Climate in the Preindustrial Holocene: A Review</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kaplan, J. O. 2014-12-01 The recent development of anthropogenic land cover change (ALCC) scenarios that cover all or part of the preindustrial Holocene (11,700 BP to ~AD 1850) has led to a number of modelling studies on the impacts of land cover change on climate, using both GCMs and regional climate models. Because most ALCC scenarios arrive at similar estimates of anthropogenic deforestation by the late preindustrial, most models agree that the net biogeophysical effect of ALCC by AD 1850 is regional cooling at mid- to high-latitudes and warming and drying over the tropics and subtropics. In particular, tropical deforestation appears to lead to local amplification of externally forced drought cycles, e.g., from ENSO. The spatial extent of these climate changes varies between models because the choice of ALCC scenario leads to large differences in the initial forcing. Those model studies that considered biogeochemical feedbacks show that the importance of preindustrial CO2 emissions ranges from being insignificant to larger than the global biogeophysical feedback, depending on assumptions made about potential natural atmospheric CO2 at the beginning of the Industrial Revolution. While the net magnitude of deforestation is similar among ALCC scenarios at AD 1850, the timing of deforestation varies widely, which, in addition to affecting the inferred importance of biogeochemical feedbacks, leads to large differences in the estimated importance of ALCC on climate earlier in the Holocene. For example, modelling experiments performed on Europe and the Mediterranean representing conditions at the peak of the Roman Empire or in Mesoamerica for the Classic Maya period show large differences in the estimated importance of the biogeophysical feedback to regional climate depending on the ALCC scenario used. The wide variety of results gained so far from ALCC and climate modelling experiments shows that the question of "how much did humans influence the state of the Earth System before the Industrial Revolution?" is far from being resolved. Future improvements to ALCC scenarios that improve thematic resolution to go beyond simple deforestation are essential, for example to include locally important types of historical land use such as irrigation and forest pasture, and Earth System models should move towards coupling between ALCC and climate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC13D1178Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC13D1178Z">Biases in simulation of the rice phenology models when applied in warmer climates</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Zhang, T.; Li, T.; Yang, X.; Simelton, E. 2015-12-01 The current model inter-comparison studies highlight the difference in projections between crop models when they are applied to warmer climates, but these studies do not provide results on how the accuracy of the models would change in these projections because the adequate observations under largely diverse growing season temperature (GST) are often unavailable. Here, we investigate the potential changes in the accuracy of rice phenology models when these models were applied to a significantly warmer climate. We collected phenology data from 775 trials with 19 cultivars in 5 Asian countries (China, India, Philippines, Bangladesh and Thailand). Each cultivar encompasses the phenology observations under diverse GST regimes. For a given rice cultivar in different trials, the GST difference reaches 2.2 to 8.2°C, which allows us to calibrate the models under lower GST and validate under higher GST (i.e., warmer climates). Four common phenology models representing major algorithms on simulations of rice phenology, and three model calibration experiments were conducted. The results suggest that the bilinear and beta models resulted in gradually increasing phenology bias (Figure) and double yield bias per percent increase in phenology bias, whereas the growing-degree-day (GDD) and exponential models maintained a comparatively constant bias when applied in warmer climates (Figure). Moreover, the bias of phenology estimated by the bilinear and beta models did not reduce with increase in GST when all data were used to calibrate models. These suggest that variations in phenology bias are primarily attributed to intrinsic properties of the respective phenology model rather than on the calibration dataset. Therefore we conclude that using the GDD and exponential models has more chances of predicting rice phenology correctly and thus, production under warmer climates, and result in effective agricultural strategic adaptation to and mitigation of climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC43G..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC43G..04S">Increasing the relevance of GCM simulations for Climate Services</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Smith, L. A.; Suckling, E. 2012-12-01 The design and interpretation of model simulations for climate services differ significantly from experimental design for the advancement of the fundamental research on predictability that underpins it. Climate services consider the sources of best information available today; this calls for a frank evaluation of model skill in the face of statistical benchmarks defined by empirical models. The fact that Physical simulation models are thought to provide the only reliable method for extrapolating into conditions not previously observed has no bearing on whether or not today's simulation models outperform empirical models. Evidence on the length scales on which today's simulation models fail to outperform empirical benchmarks is presented; it is illustrated that this occurs even on global scales in decadal prediction. At all timescales considered thus far (as of July 2012), predictions based on simulation models are improved by blending with the output of statistical models. Blending is shown to be more interesting in the climate context than it is in the weather context, where blending with a history-based climatology is straightforward. As GCMs improve and as the Earth's climate moves further from that of the last century, the skill from simulation models and their relevance to climate services is expected to increase. Examples from both seasonal and decadal forecasting will be used to discuss a third approach that may increase the role of current GCMs more quickly. Specifically, aspects of the experimental design in previous hind cast experiments are shown to hinder the use of GCM simulations for climate services. Alternative designs are proposed. The value in revisiting Thompson's classic approach to improving weather forecasting in the fifties in the context of climate services is discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1222892-exploring-multi-resolution-approach-using-amip-simulations','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1222892-exploring-multi-resolution-approach-using-amip-simulations"></a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Sakaguchi, Koichi; Leung, Lai-Yung R.; Zhao, Chun This study presents a diagnosis of a multi-resolution approach using the Model for Prediction Across Scales - Atmosphere (MPAS-A) for simulating regional climate. Four AMIP experiments are conducted for 1999-2009. In the first two experiments, MPAS-A is configured using global quasi-uniform grids at 120 km and 30 km grid spacing. In the other two experiments, MPAS-A is configured using variable-resolution (VR) mesh with local refinement at 30 km over North America and South America embedded inside a quasi-uniform domain at 120 km elsewhere. Precipitation and related fields in the four simulations are examined to determine how well the VR simulationsmore » reproduce the features simulated by the globally high-resolution model in the refined domain. In previous analyses of idealized aqua-planet simulations, the characteristics of the global high-resolution simulation in moist processes only developed near the boundary of the refined region. In contrast, the AMIP simulations with VR grids are able to reproduce the high-resolution characteristics across the refined domain, particularly in South America. This indicates the importance of finely resolved lower-boundary forcing such as topography and surface heterogeneity for the regional climate, and demonstrates the ability of the MPAS-A VR to replicate the large-scale moisture transport as simulated in the quasi-uniform high-resolution model. Outside of the refined domain, some upscale effects are detected through large-scale circulation but the overall climatic signals are not significant at regional scales. Our results provide support for the multi-resolution approach as a computationally efficient and physically consistent method for modeling regional climate.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001GPC....30..309D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001GPC....30..309D">Impacts of deforestation and afforestation in the Mediterranean region as simulated by the MPI atmospheric GCM</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dümenil Gates, Lydia; Ließ, Stefan 2001-10-01 For two reasons it is important to study the sensitivity of the global climate to changes in the vegetation cover over land. First, in the real world, changes in the vegetation cover may have regional and global implications. Second, in numerical simulations, the sensitivity of the simulated climate may depend on the specific parameterization schemes employed in the model and on the model's large-scale systematic errors. The Max-Planck-Institute's global general circulation model ECHAM4 has been used to study the sensitivity of the local and global climate during a full annual cycle to deforestation and afforestation in the Mediterranean region. The deforestation represents an extreme desertification scenario for this region. The changes in the afforestation experiment are based on the pattern of the vegetation cover 2000 years before present when the climate in the Mediterranean was more humid. The comparison of the deforestation integration to the control shows a slight cooling at the surface and reduced precipitation during the summer as a result of less evapotranspiration of plants and less evaporation from the assumption of eroded soils. There is no significant signal during the winter season due to the stronger influence of the mid-latitude baroclinic disturbances. In general, the results of the afforestation experiment are opposite to those of the deforestation case. A significant response was found in the vicinity of grid points where the land surface characteristics were modified. The response in the Sahara in the afforestation experiment is in agreement with the results from other general circulation model studies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19980220230&hterms=sensitivity+scale&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsensitivity%2Bscale','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19980220230&hterms=sensitivity+scale&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsensitivity%2Bscale">Sensitivity of Regional Climate to Deforestation in the Amazon Basin</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Eltahir, Elfatih A. B.; Bras, Rafael L. 1994-01-01 The deforestation results in several adverse effect on the natural environment. The focus of this paper is on the effects of deforestation on land-surface processes and regional climate of the Amazon basin. In general, the effect of deforestation on climate are likely to depend on the scale of the defrosted area. In this study, we are interested in the effects due to deforestation of areas with a scale of about 250 km. Hence, a meso-scale climate model is used in performing numerical experiments on the sensitivity of regional climate to deforestation of areas with that size. It is found that deforestation results in less net surface radiation, less evaporation, less rainfall, and warmer surface temperature. The magnitude of the of the change in temperature is of the order 0.5 C, the magnitudes of the changes in the other variables are of the order of IO%. In order to verify some of he results of the numerical experiments, the model simulations of net surface radiation are compared to recent observations of net radiation over cleared and undisturbed forest in the Amazon. The results of the model and the observations agree in the following conclusion: the difference in net surface radiation between cleared and undisturbed forest is, almost, equally partioned between net solar radiation and net long-wave radiation. This finding contributes to our understanding of the basic physics in the deforestation problem. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B13L..08K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B13L..08K">Exploring tropical forest vegetation dynamics using the FATES model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C. 2017-12-01 Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active">17</li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active">18</li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JGRG..116.1029S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JGRG..116.1029S">Natural and drought scenarios in an east central Amazon forest: Fidelity of the Community Land Model 3.5 with three biogeochemical models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sakaguchi, Koichi; Zeng, Xubin; Christoffersen, Bradley J.; Restrepo-Coupe, Natalia; Saleska, Scott R.; Brando, Paulo M. 2011-03-01 Recent development of general circulation models involves biogeochemical cycles: flows of carbon and other chemical species that circulate through the Earth system. Such models are valuable tools for future projections of climate, but still bear large uncertainties in the model simulations. One of the regions with especially high uncertainty is the Amazon forest where large-scale dieback associated with the changing climate is predicted by several models. In order to better understand the capability and weakness of global-scale land-biogeochemical models in simulating a tropical ecosystem under the present day as well as significantly drier climates, we analyzed the off-line simulations for an east central Amazon forest by the Community Land Model version 3.5 of the National Center for Atmospheric Research and its three independent biogeochemical submodels (CASA', CN, and DGVM). Intense field measurements carried out under Large Scale Biosphere-Atmosphere Experiment in Amazonia, including forest response to drought from a throughfall exclusion experiment, are utilized to evaluate the whole spectrum of biogeophysical and biogeochemical aspects of the models. Our analysis shows reasonable correspondence in momentum and energy turbulent fluxes, but it highlights three processes that are not in agreement with observations: (1) inconsistent seasonality in carbon fluxes, (2) biased biomass size and allocation, and (3) overestimation of vegetation stress to short-term drought but underestimation of biomass loss from long-term drought. Without resolving these issues the modeled feedbacks from the biosphere in future climate projections would be questionable. We suggest possible directions for model improvements and also emphasize the necessity of more studies using a variety of in situ data for both driving and evaluating land-biogeochemical models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUSM.A24A..01F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUSM.A24A..01F">Progress in Earth System Modeling since the ENIAC Calculation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fung, I. 2009-05-01 The success of the first numerical weather prediction experiment on the ENIAC computer in 1950 was hinged on the expansion of the meteorological observing network, which led to theoretical advances in atmospheric dynamics and subsequently the implementation of the simplified equations on the computer. This paper briefly reviews the progress in Earth System Modeling and climate observations, and suggests a strategy to sustain and expand the observations needed to advance climate science and prediction. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29311324','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29311324">Host and parasite thermal ecology jointly determine the effect of climate warming on epidemic dynamics.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Gehman, Alyssa-Lois M; Hall, Richard J; Byers, James E 2018-01-23 Host-parasite systems have intricately coupled life cycles, but each interactor can respond differently to changes in environmental variables like temperature. Although vital to predicting how parasitism will respond to climate change, thermal responses of both host and parasite in key traits affecting infection dynamics have rarely been quantified. Through temperature-controlled experiments on an ectothermic host-parasite system, we demonstrate an offset in the thermal optima for survival of infected and uninfected hosts and parasite production. We combine experimentally derived thermal performance curves with field data on seasonal host abundance and parasite prevalence to parameterize an epidemiological model and forecast the dynamical responses to plausible future climate-warming scenarios. In warming scenarios within the coastal southeastern United States, the model predicts sharp declines in parasite prevalence, with local parasite extinction occurring with as little as 2 °C warming. The northern portion of the parasite's current range could experience local increases in transmission, but assuming no thermal adaptation of the parasite, we find no evidence that the parasite will expand its range northward under warming. This work exemplifies that some host populations may experience reduced parasitism in a warming world and highlights the need to measure host and parasite thermal performance to predict infection responses to climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.B51J..03K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.B51J..03K">Using a Multi-Method Approach to Examine Social-Ecological Vulnerability to Climate Change and Natural Resource Policies on the Tibetan Plateau</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Klein, J.; Hopping, K. A.; Yeh, E.; Nyima, Y.; Galvin, K.; Boone, R.; Dorje, T.; Ojima, D. S. 2012-12-01 Pastoralists and ecosystems on the Tibetan Plateau are facing a suite of novel stresses. Temperatures are increasing several times more than the global average. The frequency and severity of severe snowstorms, which lead to critical losses of livestock, are also increasing. Pastoralists are also experiencing changes to their livelihood activities, including reduced mobility and severe grazing restrictions. We are using interdisciplinary frameworks and methods that integrate results from a multifactor ecological experiment, household interviews, remote sensing, and a coupled ecosystem and household decision-making model to examine herder and ecosystem vulnerability to climate change and extreme weather events (snow disasters) within the context of changing natural resource management policies in China. The fully factorial ecological experiment includes two climate changes (warming and spring snow additions) and two types of grazing (yak and pika) that are being affected by current policy. We established the experiment in 2008 within the Tibet Autonomous Region. We are monitoring microclimate, vegetation, nutrient availability, ecosystem carbon fluxes and stable isotope signatures of select plant species. Through this experiment, we are investigating the sensitivity of the system, whether it can cross critical thresholds, and how resilient this system may be to predicted future climate and land use changes. Semi-structured, in-depth interviews on indigenous knowledge and vulnerability complement the ecological experimental work. We are asking herders about climate and ecological change and their drivers and are also conducting interviews on vulnerability to snow disasters across a three site, 300-500mm precipitation gradient. We are using remote sensing to identify biophysical landscape change over time. To integrate our ecological and social findings, we are coupling the Savanna ecosystem model to the DECUMA agent-based pastoral household model. Our results to date from the experiment and the indigenous knowledge study suggest that Kobresia pygmaea, the dominant plant species and the primary grazing resource, is vulnerable to warming. Moreover, several lines of evidence suggest that warming is causing delayed spring phenology, with important ecosystem and livelihood implications. Herders are observing climatic and ecological changes, knowledge which is important for adaptation, but people whose livelihoods are most directly derived from the rangelands, those situated at higher elevations, and those who are more mobile across the landscape are most attuned to these changes. These results suggest that rangeland degradation and delayed spring phenology are occurring, and that climate warming may be responsible for these changes. While additional snow may improve ecological conditions, the warming-induced degradation may make the social-ecological system more vulnerable to large snowstorm events. Our findings suggest that climate adaptation strategies should address the effects of both climate warming and the changing nature of extreme weather events and should also encourage land use policies that will maintain these systems under change. Moreover, policies that encourage mobility and rangeland-based livelihoods will enhance adaptation to climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED22A..07G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED22A..07G">Show Me the Evidence: How a Unit Challenge Can Support Middle School Teachers and Students in Investigating Climate Change Using Real-World Data and Science Practices</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gochis, E. E.; Tubman, S.; Grazul, K.; Bluth, G.; Huntoon, J. E. 2017-12-01 Michigan Science Teaching and Assessment Reform (Mi-STAR) is developing an NGSS-aligned integrated science middle school curriculum and associated teacher professional learning program that addresses all performance expectations for the 6-8 grade-band. The Mi-STAR instructional model is a unit- and lesson-level model that scaffolds students in using science practices to investigate scientific phenomena and apply engineering principles to address a real-world challenge. Mi-STAR has developed an 8th grade unit on climate change based on the Mi-STAR instructional model and NGSS performance expectations. The unit was developed in collaboration with Michigan teachers, climate scientists, and curriculum developers. The unit puts students in the role of advisers to local officials who need an evidence-based explanation of climate change and recommendations about community-based actions to address it. Students discover puzzling signs of global climate change, ask questions about these signs, and engage in a series of investigations using simulations and real data to develop scientific models for the mechanisms of climate change. Students use their models as the basis for evidence-based arguments about the causes and impacts of climate change and employ engineering practices to propose local actions in their community to address climate change. Dedicated professional learning supports teachers before and during implementation of the unit. Before implementing the unit, all teachers complete an online self-paced "unit primer" during which they assume the role of their students as they are introduced to the unit challenge. During this experience, teachers experience science as a practice by using real data and simulations to develop a model of the causes of climate change, just as their students will later do. During unit implementation, teachers are part of a professional learning community led by a teacher facilitator in their local area or school. This professional learning community serves as a resource both for implementing student-directed pedagogy and for the development of content knowledge. Eight teachers pilot tested the unit with more than 500 students in spring 2017, and teachers who participated in the first professional learning cohort are currently implementing the unit around Michigan. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMGC44A..08T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMGC44A..08T">Understanding Climate Uncertainty with an Ocean Focus</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Tokmakian, R. T. 2009-12-01 Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ESD.....3...63S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ESD.....3...63S">Solar irradiance reduction to counteract radiative forcing from a quadrupling of CO2: climate responses simulated by four earth system models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Schmidt, H.; Alterskjær, K.; Karam, D. Bou; Boucher, O.; Jones, A.; Kristjánsson, J. E.; Niemeier, U.; Schulz, M.; Aaheim, A.; Benduhn, F.; Lawrence, M.; Timmreck, C. 2012-06-01 In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of two model intercomparison projects: GeoMIP (Geoengineering Model Intercomparison Project) and IMPLICC (EU project "Implications and risks of engineering solar radiation to limit climate change"). In G1, the radiative forcing from an instantaneous quadrupling of the CO2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged compared to the control simulation, the meridional temperature gradient is reduced in all models. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. In comparison to the climate response to a quadrupling of CO2 alone, the temperature responses are small in experiment G1. Precipitation responses are, however, in many regions of comparable magnitude but globally of opposite sign. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5226776','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5226776">Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Abe, Manabu; Kinoshita, Tsuguki; Hasegawa, Tomoko; Kawase, Hiroaki; Kushida, Kazuhide; Masui, Toshihiko; Oka, Kazutaka; Shiogama, Hideo; Takahashi, Kiyoshi; Tatebe, Hiroaki; Yoshikawa, Minoru 2017-01-01 In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods. PMID:28076446 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.7004S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.7004S">Adapting wheat to uncertain future</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Semenov, Mikhail; Stratonovitch, Pierre 2015-04-01 This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 RCPs, RCP4.5 and RCP8.5, were integrated with LARS-WG. Climate sensitivity indexes for temperature and precipitation were computed for all GCMs and for 21 regions in the world. For computationally demanding impact assessments, where it is not practical to explore all possible combinations of GCM × RCP, climate sensitivity indexes could be used to select a subset of GCMs from CMIP5 with contrasting climate sensitivity. This would allow to quantify uncertainty in impacts resulting from the CMIP5 ensemble by conducting fewer simulation experiments. As an example, an in silico design of wheat ideotype optimised for future climate scenarios in Europe was described. Two contrasting GCMs were selected for the analysis, "hot" HadGEM2-ES and "cool" GISS-E2-R-CC, along with 2 RCPs. Despite large uncertainty in climate projections, several wheat traits were identified as beneficial for the high-yielding wheat ideotypes that could be used as targets for wheat improvement by breeders. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9420V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9420V">Assessment of bias correction under transient climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Van Schaeybroeck, Bert; Vannitsem, Stéphane 2015-04-01 Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp.2437D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp.2437D">Benefits of explicit urban parameterization in regional climate modeling to study climate and city interactions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Daniel, M.; Lemonsu, Aude; Déqué, M.; Somot, S.; Alias, A.; Masson, V. 2018-06-01 Most climate models do not explicitly model urban areas and at best describe them as rock covers. Nonetheless, the very high resolutions reached now by the regional climate models may justify and require a more realistic parameterization of surface exchanges between urban canopy and atmosphere. To quantify the potential impact of urbanization on the regional climate, and evaluate the benefits of a detailed urban canopy model compared with a simpler approach, a sensitivity study was carried out over France at a 12-km horizontal resolution with the ALADIN-Climate regional model for 1980-2009 time period. Different descriptions of land use and urban modeling were compared, corresponding to an explicit modeling of cities with the urban canopy model TEB, a conventional and simpler approach representing urban areas as rocks, and a vegetated experiment for which cities are replaced by natural covers. A general evaluation of ALADIN-Climate was first done, that showed an overestimation of the incoming solar radiation but satisfying results in terms of precipitation and near-surface temperatures. The sensitivity analysis then highlighted that urban areas had a significant impact on modeled near-surface temperature. A further analysis on a few large French cities indicated that over the 30 years of simulation they all induced a warming effect both at daytime and nighttime with values up to + 1.5 °C for the city of Paris. The urban model also led to a regional warming extending beyond the urban areas boundaries. Finally, the comparison to temperature observations available for Paris area highlighted that the detailed urban canopy model improved the modeling of the urban heat island compared with a simpler approach. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1223159-modeling-study-irrigation-effects-global-surface-water-groundwater-resources-under-changing-climate','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1223159-modeling-study-irrigation-effects-global-surface-water-groundwater-resources-under-changing-climate">A modeling study of irrigation effects on global surface water and groundwater resources under a changing climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong In this paper, the effects of irrigation on global surface water (SW) and groundwater (GW) resources are investigated by performing simulations using Community Land Model 4.0 (CLM4) at 0.5-degree resolution driven by downscaled/bias-corrected historical simulations and future projections from five General Circulation Models (GCMs) for 1950-2099. For each climate scenario, three sets of numerical experiments were configured: (1) a control experiment (CTRL) in which all crops are assumed to be rainfed; (2) an irrigation experiment (IRRIG) in which the irrigation module using only SW for irrigation is activated; and (3) a groundwater pumping experiment (PUMP) in which a groundwater pumpingmore » scheme coupled with the irrigation module is activated for conjunctive use of SW and GW for irrigation. The parameters associated with irrigation and groundwater pumping are calibrated based on a global inventory of census-based SW and GW use compiled by the Food and Agricultural Organization (FAO). Our results suggest that irrigation could lead to two major opposing effects: SW depletion/GW accumulation in regions with irrigation primarily fed by SW, and SW accumulation/GW depletion in regions with irrigation fed primarily by GW. Furthermore, irrigation depending primarily on SW tends to have larger impacts on low-flow than high-flow conditions, suggesting the potential to increase vulnerability to drought. By the end of the 21st century (2070-2099), climate change significantly increases (relative to 1971-2000) irrigation water demand across the world. Combined with the increased temporal-spatial variability of water supply, this may lead to severe issues of local water scarcity for irrigation. Regionally, irrigation has the potential to aggravate/alleviate climate-induced changes of SW/GW although such effects are negligible when averaged globally. Our results emphasize the importance of accounting for irrigation effects and irrigation sources in regional climate change impact assessment.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1223159-modeling-study-irrigation-effects-global-surface-water-groundwater-resources-under-changing-climate','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1223159-modeling-study-irrigation-effects-global-surface-water-groundwater-resources-under-changing-climate">A modeling study of irrigation effects on global surface water and groundwater resources under a changing climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong; ... 2015-08-25 In this paper, the effects of irrigation on global surface water (SW) and groundwater (GW) resources are investigated by performing simulations using Community Land Model 4.0 (CLM4) at 0.5-degree resolution driven by downscaled/bias-corrected historical simulations and future projections from five General Circulation Models (GCMs) for 1950-2099. For each climate scenario, three sets of numerical experiments were configured: (1) a control experiment (CTRL) in which all crops are assumed to be rainfed; (2) an irrigation experiment (IRRIG) in which the irrigation module using only SW for irrigation is activated; and (3) a groundwater pumping experiment (PUMP) in which a groundwater pumpingmore » scheme coupled with the irrigation module is activated for conjunctive use of SW and GW for irrigation. The parameters associated with irrigation and groundwater pumping are calibrated based on a global inventory of census-based SW and GW use compiled by the Food and Agricultural Organization (FAO). Our results suggest that irrigation could lead to two major opposing effects: SW depletion/GW accumulation in regions with irrigation primarily fed by SW, and SW accumulation/GW depletion in regions with irrigation fed primarily by GW. Furthermore, irrigation depending primarily on SW tends to have larger impacts on low-flow than high-flow conditions, suggesting the potential to increase vulnerability to drought. By the end of the 21st century (2070-2099), climate change significantly increases (relative to 1971-2000) irrigation water demand across the world. Combined with the increased temporal-spatial variability of water supply, this may lead to severe issues of local water scarcity for irrigation. Regionally, irrigation has the potential to aggravate/alleviate climate-induced changes of SW/GW although such effects are negligible when averaged globally. Our results emphasize the importance of accounting for irrigation effects and irrigation sources in regional climate change impact assessment.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC13F0828D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC13F0828D">Quantifying the probability of record-setting heat events in the historical record and at different levels of climate forcing</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Diffenbaugh, N. S. 2017-12-01 Severe heat provides one of the most direct, acute, and rapidly changing impacts of climate on people and ecostystems. Theory, historical observations, and climate model simulations all suggest that global warming should increase the probability of hot events that fall outside of our historical experience. Given the acutre impacts of extreme heat, quantifying the probability of historically unprecedented hot events at different levels of climate forcing is critical for climate adaptation and mitigation decisions. However, in practice that quantification presents a number of methodological challenges. This presentation will review those methodological challenges, including the limitations of the observational record and of climate model fidelity. The presentation will detail a comprehensive approach to addressing these challenges. It will then demonstrate the application of that approach to quantifying uncertainty in the probability of record-setting hot events in the current climate, as well as periods with lower and higher greenhouse gas concentrations than the present. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1995EOSTr..76..265C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1995EOSTr..76..265C">Ice sheets play important role in climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Clark, Peter U.; MacAyeal, Douglas R.; Andrews, John T.; Bartlein, Patrick J. Ice sheets once were viewed as passive elements in the climate system enslaved to orbitally generated variations in solar radiation. Today, modeling results and new geologic records suggest that ice sheets actively participated in late-Pleistocene climate change, amplifying or driving significant variability at millennial as well as orbital timescales. Although large changes in global ice volume were ultimately caused by orbital variations (the Milankovitch hypothesis), once in existence, the former ice sheets behaved dynamically and strongly influenced regional and perhaps even global climate by altering atmospheric and oceanic circulation and temperature.Experiments with General Circulation Models (GCMs) yielded the first inklings of ice sheets' climatic significance. Manabe and Broccoli [1985], for example, found that the topographic and albedo effects of ice sheets alone explain much of the Northern Hemisphere cooling identified in paleoclimatic records of the last glacial maximum (˜21 ka). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918727P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918727P">The climate4impact platform: Providing, tailoring and facilitating climate model data access</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael 2017-04-01 One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European contribution to ESGF and contributes to the ESGF open source effort, notably through the development of search, monitoring, quality control, and metadata services. In its second phase, IS-ENES2 supports the implementation of regional climate model results from the international Coordinated Regional Downscaling Experiments (CORDEX). These services were extended within the European FP7 Climate Information Portal for Copernicus (CLIPC) project, and some could be later integrated into the European Copernicus platform. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/36894','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/36894">Mixed-conifer understory response to climate change, nitrogen, and fire</a> <a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a> Matthew Hurteau; Malcom North 2008-01-01 Californiaâs Sierra Nevada mountains are predicted to experience greater variation in annual precipitation according to climate change models, while nitrogen deposition from pollution continues to increase. These changes may significantly affect understory communities and fuels in forests where managers are attempting to restore historic conditions after a century of... </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=conservation+AND+restoration&pg=2&id=EJ785676','ERIC'); return false;" href="https://eric.ed.gov/?q=conservation+AND+restoration&pg=2&id=EJ785676">Carrion--It's What's for Dinner: Wolves Reduce the Impact of Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a> Consitble, Juanita M.; Sandro, Luke H.; Lee, Richard E., Jr. 2008-01-01 The restoration of wolves to Yellowstone National park after a 7-year absence created a natural experiment on the ecological effects of top predators. In this activity, students use mathematical models to explore how carrion from wolf kills can reduce negative effects of climate change on scavengers in the park. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011360','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011360">Assessing Confidence in Pliocene Sea Surface Temperatures to Evaluate Predictive Models</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling. M.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140011360'); toggleEditAbsImage('author_20140011360_show'); toggleEditAbsImage('author_20140011360_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140011360_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140011360_hide"> 2012-01-01 In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.33.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history.This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70044255','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70044255">Assessing confidence in Pliocene sea surface temperatures to evaluate predictive models</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Dowsett, Harry J.; Robinson, Marci M.; Haywood, Alan M.; Hill, Daniel J.; Dolan, Aisling M.; Stoll, Danielle K.; Chan, Wing-Le; Abe-Ouchi, Ayako; Chandler, Mark A.; Rosenbloom, Nan A.; Otto-Bliesner, Bette L.; Bragg, Fran J.; Lunt, Daniel J.; Foley, Kevin M.; Riesselman, Christina R. 2012-01-01 In light of mounting empirical evidence that planetary warming is well underway, the climate research community looks to palaeoclimate research for a ground-truthing measure with which to test the accuracy of future climate simulations. Model experiments that attempt to simulate climates of the past serve to identify both similarities and differences between two climate states and, when compared with simulations run by other models and with geological data, to identify model-specific biases. Uncertainties associated with both the data and the models must be considered in such an exercise. The most recent period of sustained global warmth similar to what is projected for the near future occurred about 3.3–3.0 million years ago, during the Pliocene epoch. Here, we present Pliocene sea surface temperature data, newly characterized in terms of level of confidence, along with initial experimental results from four climate models. We conclude that, in terms of sea surface temperature, models are in good agreement with estimates of Pliocene sea surface temperature in most regions except the North Atlantic. Our analysis indicates that the discrepancy between the Pliocene proxy data and model simulations in the mid-latitudes of the North Atlantic, where models underestimate warming shown by our highest-confidence data, may provide a new perspective and insight into the predictive abilities of these models in simulating a past warm interval in Earth history. This is important because the Pliocene has a number of parallels to present predictions of late twenty-first century climate. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active">18</li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active">19</li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140016851','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140016851">Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Krakauer, N.Y.; Puma, Michael J.; Cook, B. I. 2013-01-01 Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ThApC.tmp..491K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ThApC.tmp..491K">Regional climate projections for Northeast India: an appraisal from CORDEX South Asia experiment</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kumar, D.; Dimri, A. P. 2017-11-01 An appraisal of the recent changes in the present climate (1970-2005) followed by the possible future (2006-2100) changes in the climate has been carried out in the current study using the observations and regional climate model (REMO) over the Northeast Indian region. The regional climate model simulation has been used from the COordinated Regional climate Downscaling EXperiment (CORDEX) South Asia framework. A consistent warming for the winter (December, January, and February (DJF)) and post-monsoon (October and November (ON)) has been observed for the present climate especially in the northern and eastern parts of the region. The changes in the near future (2020-2049) and far future (2070-2099) temperature climatology suggest a rise in temperature by 3-8 °C across different representative concentration pathways (RCPs). The rate of long-term (1970-2099) increase in temperature has been found ranging between 0.01 and 0.07 °C/year across the region in the least emission (RCP2.6) to strongest emission (RCP8.5) scenarios. The daily mean precipitation statistics suggests an overall increasing trends of precipitation during the pre-monsoon (March, April, and May (MAM)) for the present across the region with a mixed trend in other seasons. A change in daily mean precipitation ranging from - 60% (during winter) to + 40% during post-monsoon has been projected by the model across different RCPs. RCP4.5 and RCP8.5 show a strong deficit in precipitation in the warmer climate across the region as compared to RCP2.6. This fact is also confirmed from the long-term trend of precipitation where a consistent decreasing trend dominates in the RCP4.5- and RCP8.5-simulated precipitations by the end of the twenty-first century. A large model bias in temperature and precipitation along with high amount of uncertainty is associated with the model simulations; thus, in order to use the projections, a more careful approach to improve the utility of downscaled product should be adopted. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B51D0446D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B51D0446D">Sorghum production under future climate in the Southwestern USA: model projections of yield, greenhouse gas emissions and soil C fluxes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Duval, B.; Ghimire, R.; Hartman, M. D.; Marsalis, M. 2016-12-01 Large tracts of semi-arid land in the Southwestern USA are relatively less important for food production than the US Corn Belt, and represent a promising area for expansion of biofuel/bioproduct crops. However, high temperatures, low available water and high solar radiation in the SW represent a challenge to suitable feedstock development, and future climate change scenarios predict that portions of the SW will experience increased temperature and temporal shifts in precipitation distribution. Sorghum (Sorghum bicolor) is a valuable forage crop with promise as a biofuel feedstock, given its high biomass under semi-arid conditions, relatively lower N fertilizer requirements compared to corn, and salinity tolerance. To evaluate the environmental impact of expanded sorghum cultivation under future climate in the SW USA, we used the DayCent model in concert with a suite of downscaled future weather projections to predict biogeochemical consequences (greenhouse gas flux and impacts on soil carbon) of sorghum cultivation in New Mexico. The model showed good correspondence with yield data from field trials including both dryland and irrigated sorghum (measured vs. modeled; r2 = 0.75). Simulation experiments tested the effect of dryland production versus irrigation, low N versus high N inputs and delayed fertilizer application. Nitrogen application timing and irrigation impacted yield and N2O emissions less than N rate and climate. Across N and irrigation treatments, future climate simulations resulted in 6% increased yield and 20% lower N2O emissions compared to current climate. Soil C pools declined under future climate. The greatest declines in soil C were from low N input sorghum simulations, regardless of irrigation (>20% declines in SOM in both cases), and requires further evaluation to determine if changing future climate is driving these declines, or if they are a function of prolonged sorghum-fallow rotations in the model. The relatively small gain in yield for irrigated sorghum, and strong control of N rate on N2O emissions suggests that a dryland sorghum bioproduct system could be environmentally sustainable in the Southwestern US with effective N management, and warrants further investigation in field trials. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70190665','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70190665">A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Milly, Paul; Dunne, Krista A. 2017-01-01 For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (Ep) as inputs. Because Ep is not a climate-model output, an intermediary model of Ep must be introduced to connect the climate model to the hydrologic model. Several Ep methods are used. The suitability of each can be assessed by noting a credible Ep method for offline analyses should be able to reproduce climate models’ ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress (Ew). We quantified this ability for seven commonly used Ep methods and for a simple proportionality with available energy (“energy-only” method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in Ep associated with ACC. In an offline hydrologic model, the Ep-change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H21F1115P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H21F1115P">An ecohydrological model to quantify the risk of drought-induced forest mortality events across climate regimes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Parolari, A.; Katul, G. G.; Porporato, A. M. 2013-12-01 Regional scale drought-induced forest mortality events are projected to become more frequent under future climates due to changes in rainfall patterns. However, the ability to predict the conditions under which such events occur is currently lacking. To quantify and understand the underlying causes of drought-induced forest mortality, we propose a stochastic ecohydrological model that explicitly couples tree water and carbon use strategies with climate characteristics, such as the frequency and severity of drought. Using the model and results from a controlled drought experiment, we identify the soil, vegetation, and climate factors that underlie tree water and carbon deficits and, ultimately, the risk of drought-induced forest mortality. This mortality risk is then compared across the spectrum of anisohydric-isohydric stomatal control strategies and a range of rainfall regimes. These results suggest certain soil-plant combinations may maximize the survivable drought length in a given climate. Finally, we discuss how this approach can be expanded to estimate the effect of anticipated climate change on drought-induced forest mortality and associated consequences for forest water and carbon balances. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/535502-land-atmosphere-interactions-over-continental-united-states','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/535502-land-atmosphere-interactions-over-continental-united-states">Land-atmosphere interactions over the continental United States</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Zeng, Xubin This paper briefly discusses four suggested modifications for land surface modeling in climate models. The impact of the modifications on climate simulations is analyzed with the Biosphere-Atmosphere Transfer Scheme (BATS) land surface model. It is found that the modifications can improve BATS simulations. In particular, the sensitivity of BATS to the prescribed value of physical root fraction which cannot be observed from satellite remote sensing or field experiments is improved. These modifications significantly reduce the excessive summer land surface temperature over the continental United States simulated by the National Center for Atmospheric Research Community Climate Model (CCM2) coupled with BATS.more » A land-atmosphere interaction mechanism involving energy and water cycles is proposed to explain the results. 9 refs., 1 fig.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006GPC....54..163M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006GPC....54..163M">Potential individual versus simultaneous climate change effects on soybean (C 3) and maize (C 4) crops: An agrotechnology model based study</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mera, Roberto J.; Niyogi, Dev; Buol, Gregory S.; Wilkerson, Gail G.; Semazzi, Fredrick H. M. 2006-11-01 Landuse/landcover change induced effects on regional weather and climate patterns and the associated plant response or agricultural productivity are coupled processes. Some of the basic responses to climate change can be detected via changes in radiation ( R), precipitation ( P), and temperature ( T). Past studies indicate that each of these three variables can affect LCLUC response and the agricultural productivity. This study seeks to address the following question: What is the effect of individual versus simultaneous changes in R, P, and T on plant response such as crop yields in a C 3 and a C 4 plant? This question is addressed by conducting model experiments for soybean (C 3) and maize (C 4) crops using the DSSAT: Decision Support System for Agrotechnology Transfer, CROPGRO (soybean), and CERES-Maize (maize) models. These models were configured over an agricultural experiment station in Clayton, NC [35.65°N, 78.5°W]. Observed weather and field conditions corresponding to 1998 were used as the control. In the first set of experiments, the CROPGRO (soybean) and CERES-Maize (maize) responses to individual changes in R and P (25%, 50%, 75%, 150%) and T (± 1, ± 2 °C) with respect to control were studied. In the second set, R, P, and T were simultaneously changed by 50%, 150%, and ± 2 °C, and the interactions and direct effects of individual versus simultaneous variable changes were analyzed. For the model setting and the prescribed environmental changes, results from the first set of experiments indicate: (i) precipitation changes were most sensitive and directly affected yield and water loss due to evapotranspiration; (ii) radiation changes had a non-linear effect and were not as prominent as precipitation changes; (iii) temperature had a limited impact and the response was non-linear; (iv) soybeans and maize responded differently for R, P, and T, with maize being more sensitive. The results from the second set of experiments indicate that simultaneous change analyses do not necessarily agree with those from individual changes, particularly for temperature changes. Our analysis indicates that for the changing climate, precipitation (hydrological), temperature, and radiative feedbacks show a non-linear effect on yield. Study results also indicate that for studying the feedback between the land surface and the atmospheric changes, (i) there is a need for performing simultaneous parameter changes in the response assessment of cropping patterns and crop yield based on ensembles of projected climate change, and (ii) C 3 crops are generally considered more sensitive than C 4; however, the temperature-radiation related changes shown in this study also effected significant changes in C 4 crops. Future studies assessing LCLUC impacts, including those from agricultural cropping patterns and other LCULC-climate couplings, should advance beyond the sensitivity mode and consider multivariable, ensemble approaches to identify the vulnerability and feedbacks in estimating climate-related impacts. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5120834','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5120834">Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Upson, Rebecca; Williams, Jennifer J.; Wilkinson, Tim P.; Maclean, Ilya M. D.; McAdam, Jim H.; Moat, Justin F. 2016-01-01 The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020–2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements. PMID:27880846 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27880846','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27880846">Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Upson, Rebecca; Williams, Jennifer J; Wilkinson, Tim P; Clubbe, Colin P; Maclean, Ilya M D; McAdam, Jim H; Moat, Justin F 2016-01-01 The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020-2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011CliPa...7.1075B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011CliPa...7.1075B">Uncertainties in modelling CH4 emissions from northern wetlands in glacial climates: the role of vegetation parameters</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Berrittella, C.; van Huissteden, J. 2011-10-01 Marine Isotope Stage 3 (MIS 3) interstadials are marked by a sharp increase in the atmospheric methane (CH4) concentration, as recorded in ice cores. Wetlands are assumed to be the major source of this CH4, although several other hypotheses have been advanced. Modelling of CH4 emissions is crucial to quantify CH4 sources for past climates. Vegetation effects are generally highly generalized in modelling past and present-day CH4 fluxes, but should not be neglected. Plants strongly affect the soil-atmosphere exchange of CH4 and the net primary production of the vegetation supplies organic matter as substrate for methanogens. For modelling past CH4 fluxes from northern wetlands, assumptions on vegetation are highly relevant since paleobotanical data indicate large differences in Last Glacial (LG) wetland vegetation composition as compared to modern wetland vegetation. Besides more cold-adapted vegetation, Sphagnum mosses appear to be much less dominant during large parts of the LG than at present, which particularly affects CH4 oxidation and transport. To evaluate the effect of vegetation parameters, we used the PEATLAND-VU wetland CO2/CH4 model to simulate emissions from wetlands in continental Europe during LG and modern climates. We tested the effect of parameters influencing oxidation during plant transport (fox), vegetation net primary production (NPP, parameter symbol Pmax), plant transport rate (Vtransp), maximum rooting depth (Zroot) and root exudation rate (fex). Our model results show that modelled CH4 fluxes are sensitive to fox and Zroot in particular. The effects of Pmax, Vtransp and fex are of lesser relevance. Interactions with water table modelling are significant for Vtransp. We conducted experiments with different wetland vegetation types for Marine Isotope Stage 3 (MIS 3) stadial and interstadial climates and the present-day climate, by coupling PEATLAND-VU to high resolution climate model simulations for Europe. Experiments assuming dominance of one vegetation type (Sphagnum vs. Carex vs. Shrubs) show that Carex-dominated vegetation can increase CH4 emissions by 50% to 78% over Sphagnum-dominated vegetation depending on the modelled climate, while for shrubs this increase ranges from 42% to 72%. Consequently, during the LG northern wetlands may have had CH4 emissions similar to their present-day counterparts, despite a colder climate. Changes in dominant wetland vegetation, therefore, may drive changes in wetland CH4 fluxes, in the past as well as in the future. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ESD.....9..413A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ESD.....9..413A">Earth system model simulations show different feedback strengths of the terrestrial carbon cycle under glacial and interglacial conditions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Adloff, Markus; Reick, Christian H.; Claussen, Martin 2018-04-01 In simulations with the MPI Earth System Model, we study the feedback between the terrestrial carbon cycle and atmospheric CO2 concentrations under ice age and interglacial conditions. We find different sensitivities of terrestrial carbon storage to rising CO2 concentrations in the two settings. This result is obtained by comparing the transient response of the terrestrial carbon cycle to a fast and strong atmospheric CO2 concentration increase (roughly 900 ppm) in Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP)-type simulations starting from climates representing the Last Glacial Maximum (LGM) and pre-industrial times (PI). In this set-up we disentangle terrestrial contributions to the feedback from the carbon-concentration effect, acting biogeochemically via enhanced photosynthetic productivity when CO2 concentrations increase, and the carbon-climate effect, which affects the carbon cycle via greenhouse warming. We find that the carbon-concentration effect is larger under LGM than PI conditions because photosynthetic productivity is more sensitive when starting from the lower, glacial CO2 concentration and CO2 fertilization saturates later. This leads to a larger productivity increase in the LGM experiment. Concerning the carbon-climate effect, it is the PI experiment in which land carbon responds more sensitively to the warming under rising CO2 because at the already initially higher temperatures, tropical plant productivity deteriorates more strongly and extratropical carbon is respired more effectively. Consequently, land carbon losses increase faster in the PI than in the LGM case. Separating the carbon-climate and carbon-concentration effects, we find that they are almost additive for our model set-up; i.e. their synergy is small in the global sum of carbon changes. Together, the two effects result in an overall strength of the terrestrial carbon cycle feedback that is almost twice as large in the LGM experiment as in the PI experiment. For PI, ocean and land contributions to the total feedback are of similar size, while in the LGM case the terrestrial feedback is dominant. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED22A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED22A..01S">The Iowa K-12 Climate Science Education Initiative: a comprehensive approach to meeting in-service teachers' stated needs for teaching climate literacy with NGSS</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stanier, C. O.; Spak, S.; Neal, T. A.; Herder, S.; Malek, A.; Miller, Z. 2017-12-01 The Iowa Board of Education voted unanimously in 2015 to adopt NGSS performance standards. The CGRER - College of Education Iowa K-12 Climate Science Education Initiative was established in 2016 to work directly with Iowa inservice teachers to provide what teachers need most to teach climate literacy and climate science content through investigational learning aligned with NGSS. Here we present teachers' requests for teaching climate with NGSS, and an approach to provide resources for place-based authentic inquiry on climate, developed, tested, and refined in partnership with inservice and preservice teachers. A survey of inservice middle school and high school science teachers was conducted at the 2016 Iowa Council of Teachers of Mathematics/Iowa Academy of Sciences - Iowa Science Teaching Section Fall Conference and online in fall 2016. Participants (n=383) were asked about their prior experience and education, the resources they use and need, their level of comfort in teaching climate science, perceived barriers, and how they address potential controversy. Teachers indicated preference for professional development on climate content and complete curricula packaged with lessons and interactive models aligned to Iowa standards, as well as training on instructional strategies to enhance students' ability to interpret scientific evidence. We identify trends in responses by teaching experience, climate content knowledge and its source, grade level, and urban and rural districts. Less than 20% of respondents reported controversy or negativity in teaching climate to date, and a majority were comfortable teaching climate science and climate change, with equal confidence in teaching climate and other STEM content through investigational activities. We present an approach and materials to meet these stated needs, created and tested in collaboration with Iowa teachers. We combine professional development and modular curricula with bundled standards, concepts, models, data, field activities, and sequences of individual and group investigational and student-driven inquiry prompts on climate science, climate change, and climate impacts. We identify key resource availability needed to teach place-based climate literacy aligned with NGSS as a standalone curriculum and through local impacts. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.131..937A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.131..937A">Assessing the link between Atlantic Niño 1 and drought over West Africa using CORDEX regional climate models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Adeniyi, Mojisola Oluwayemisi; Dilau, Kabiru Alabi 2018-02-01 The skill of Coordinated Regional Climate Downscaling Experiment (CORDEX) models (ARPEGE, CCLM, HIRHAM, RACMO, REMO, PRECIS, RegCM3, RCA, WRF and CRCM) in simulating the climate (precipitation, temperature and drought) of West Africa is determined using a process-based metric. This is done by comparing the CORDEX models' simulated and observed correlation coefficients between Atlantic Niño Index 1 (ATLN1) and the climate over West Africa. Strong positive correlation is observed between ATLN1 and the climate parameters at the Guinea Coast (GC). The Atlantic Ocean has Niño behaviours through the ATLN indices which influence the climate of the tropics. Drought has distinct dipole structure of correlation with ATLN1 (negative at the Sahel); precipitation does not have distinct dipole structure of correlation, while temperature has almost a monopole correlation structure with ATLN1 over West Africa. The magnitude of the correlation increases with closeness to the equatorial eastern Atlantic. Correlations between ATLN1 and temperature are mostly stronger than those between ATLN1 and precipitation over the region. Most models have good performance over the GC, but ARPEGE has the highest skill at GC. The PRECIS is the most skilful over Savannah and RCA over Sahel. These models can be used to downscale the projected climate at the region of their highest skill. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23129709','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23129709">Changing currents: a strategy for understanding and predicting the changing ocean circulation.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bryden, Harry L; Robinson, Carol; Griffiths, Gwyn 2012-12-13 Within the context of UK marine science, we project a strategy for ocean circulation research over the next 20 years. We recommend a focus on three types of research: (i) sustained observations of the varying and evolving ocean circulation, (ii) careful analysis and interpretation of the observed climate changes for comparison with climate model projections, and (iii) the design and execution of focused field experiments to understand ocean processes that are not resolved in coupled climate models so as to be able to embed these processes realistically in the models. Within UK-sustained observations, we emphasize smart, cost-effective design of the observational network to extract maximum information from limited field resources. We encourage the incorporation of new sensors and new energy sources within the operational environment of UK-sustained observational programmes to bridge the gap that normally separates laboratory prototype from operational instrument. For interpreting the climate-change records obtained through a variety of national and international sustained observational programmes, creative and dedicated UK scientists should lead efforts to extract the meaningful signals and patterns of climate change and to interpret them so as to project future changes. For the process studies, individual scientists will need to work together in team environments to combine observational and process modelling results into effective improvements in the coupled climate models that will lead to more accurate climate predictions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1435594-ecosystem-biogeochemistry-model-parameterization-do-more-flux-data-result-better-model-predicting-carbon-flux','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1435594-ecosystem-biogeochemistry-model-parameterization-do-more-flux-data-result-better-model-predicting-carbon-flux">Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Zhu, Qing; Zhuang, Qianlai 2015-12-21 Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1435594','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1435594">Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Zhu, Qing; Zhuang, Qianlai Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN13D..02R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN13D..02R">Earth System Model Development and Analysis using FRE-Curator and Live Access Servers: On-demand analysis of climate model output with data provenance.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Radhakrishnan, A.; Balaji, V.; Schweitzer, R.; Nikonov, S.; O'Brien, K.; Vahlenkamp, H.; Burger, E. F. 2016-12-01 There are distinct phases in the development cycle of an Earth system model. During the model development phase, scientists make changes to code and parameters and require rapid access to results for evaluation. During the production phase, scientists may make an ensemble of runs with different settings, and produce large quantities of output, that must be further analyzed and quality controlled for scientific papers and submission to international projects such as the Climate Model Intercomparison Project (CMIP). During this phase, provenance is a key concern:being able to track back from outputs to inputs. We will discuss one of the paths taken at GFDL in delivering tools across this lifecycle, offering on-demand analysis of data by integrating the use of GFDL's in-house FRE-Curator, Unidata's THREDDS and NOAA PMEL's Live Access Servers (LAS).Experience over this lifecycle suggests that a major difficulty in developing analysis capabilities is only partially the scientific content, but often devoted to answering the questions "where is the data?" and "how do I get to it?". "FRE-Curator" is the name of a database-centric paradigm used at NOAA GFDL to ingest information about the model runs into an RDBMS (Curator database). The components of FRE-Curator are integrated into Flexible Runtime Environment workflow and can be invoked during climate model simulation. The front end to FRE-Curator, known as the Model Development Database Interface (MDBI) provides an in-house web-based access to GFDL experiments: metadata, analysis output and more. In order to provide on-demand visualization, MDBI uses Live Access Servers which is a highly configurable web server designed to provide flexible access to geo-referenced scientific data, that makes use of OPeNDAP. Model output saved in GFDL's tape archive, the size of the database and experiments, continuous model development initiatives with more dynamic configurations add complexity and challenges in providing an on-demand visualization experience to our GFDL users. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017CliPa..13..421P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017CliPa..13..421P">Reconstructing paleoclimate fields using online data assimilation with a linear inverse model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Perkins, Walter A.; Hakim, Gregory J. 2017-05-01 We examine the skill of a new approach to climate field reconstructions (CFRs) using an online paleoclimate data assimilation (PDA) method. Several recent studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs) and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational cost by employing an empirical forecast model (linear inverse model, LIM), which has been shown to have skill comparable to CGCMs for forecasting annual-to-decadal surface temperature anomalies. We reconstruct annual-average 2 m air temperature over the instrumental period (1850-2000) using proxy records from the PAGES 2k Consortium Phase 1 database; proxy models for estimating proxy observations are calibrated on GISTEMP surface temperature analyses. We compare results for LIMs calibrated using observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data relative to a control offline reconstruction method. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial fields and global mean temperature (GMT). Specifically, the coefficient of efficiency (CE) skill metric for detrended GMT increases by an average of 57 % over the offline benchmark. LIM experiments display a common pattern of skill improvement in the spatial fields over Northern Hemisphere land areas and in the high-latitude North Atlantic-Barents Sea corridor. Experiments for non-CGCM-calibrated LIMs reveal region-specific reductions in spatial skill compared to the offline control, likely due to aspects of the LIM calibration process. Overall, the CGCM-calibrated LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the linear dynamical constraints of the forecast and not simply persistence of temperature anomalies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850006082&hterms=analysis+climatic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Danalysis%2Bclimatic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19850006082&hterms=analysis+climatic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Danalysis%2Bclimatic">Spectral Energetics Diagnoses and FGGE Special Observing Periods and Energetics Analyses of Forecast Experiments with GLAS GCM</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Kung, E. C. 1984-01-01 Energetics characteristics of Goddard Laboratory for Atmospheric Sciences (GLAS) General Circulation Models (GCM) as they are reflected on the First GARD GLobal Experiment (FGGE) analysis data set are discussed. Energetics descriptions of GLAS GCM forecast experiments are discussed as well as Eneretics response of GLAS GCM climatic simulation experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70175393','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70175393">Implications of climate change for wetland-dependent birds in the Prairie Pothole Region</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Steen, Valerie; Skagen, Susan K.; Melcher, Cynthia P. 2016-01-01 The habitats and food resources required to support breeding and migrant birds dependent on North American prairie wetlands are threatened by impending climate change. The North American Prairie Pothole Region (PPR) hosts nearly 120 species of wetland-dependent birds representing 21 families. Strategic management requires knowledge of avian habitat requirements and assessment of species most vulnerable to future threats. We applied bioclimatic species distribution models (SDMs) to project range changes of 29 wetland-dependent bird species using ensemble modeling techniques, a large number of General Circulation Models (GCMs), and hydrological climate covariates. For the U.S. PPR, mean projected range change, expressed as a proportion of currently occupied range, was −0.31 (± 0.22 SD; range − 0.75 to 0.16), and all but two species were projected to lose habitat. Species associated with deeper water were expected to experience smaller negative impacts of climate change. The magnitude of climate change impacts was somewhat lower in this study than earlier efforts most likely due to use of different focal species, varying methodologies, different modeling decisions, or alternative GCMs. Quantification of the projected species-specific impacts of climate change using species distribution modeling offers valuable information for vulnerability assessments within the conservation planning process. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active">19</li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active">20</li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H43P..02R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H43P..02R">High Resolution Climate Modeling of the Water Cycle over the Western United States Including Potential Climate Change Impacts</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rasmussen, R.; Liu, C.; Ikeda, K. 2016-12-01 The NCAR Water System program strives to improve the full representation of the water cycle in both regional and global models. Our previous high-resolution simulations using the WRF model over the Rocky Mountains revealed that proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing (< 6 km horizontal) and parameterizations. The climate sensitivity experiment consistent with expected climate change showed an altered hydrological cycle with increased fraction of rain versus snow, increased snowfall at high altitudes, earlier melting of snowpack, and decreased total runoff. In order to investigate regional differences between the Rockies and other major mountain barriers and to study climate change impacts over other regions of the contiguous U.S. (CONUS), we have expanded our prior CO Headwaters modeling study to encompass most of North America at a horizontal grid spacing of 4 km (see figure below). A domain expansion provides the opportunity to assess changes in orographic precipitation across different mountain ranges in the western USA. This study will examine the water cycle over Western U.S. seven U.S. mountain ranges, including likely changes to amount of snowpack and spring melt-off, critical to agriculture in the western U.S. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/666195','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/666195">Exploring the concept of climate surprises. A review of the literature on the concept of surprise and how it is related to climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Glantz, M.H.; Moore, C.M.; Streets, D.G. This report examines the concept of climate surprise and its implications for environmental policymaking. Although most integrated assessment models of climate change deal with average values of change, it is usually the extreme events or surprises that cause the most damage to human health and property. Current models do not help the policymaker decide how to deal with climate surprises. This report examines the literature of surprise in many aspects of human society: psychology, military, health care, humor, agriculture, etc. It draws together various ways to consider the concept of surprise and examines different taxonomies of surprise that have beenmore » proposed. In many ways, surprise is revealed to be a subjective concept, triggered by such factors as prior experience, belief system, and level of education. How policymakers have reacted to specific instances of climate change or climate surprise in the past is considered, particularly with regard to the choices they made between proactive and reactive measures. Finally, the report discusses techniques used in the current generation of assessment models and makes suggestions as to how climate surprises might be included in future models. The report concludes that some kinds of surprises are simply unpredictable, but there are several types that could in some way be anticipated and assessed, and their negative effects forestalled.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMED51A0806R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMED51A0806R">CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rose, B. E. J. 2015-12-01 Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70156907','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70156907">Warming experiments underpredict plant phenological responses to climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Wolkovich, Elizabeth M.; Cook, Benjamin I.; Allen, Jenica M.; Crimmins, Theresa M.; Betancourt, Julio L.; Travers, Steven E.; Pau, Stephanie; Regetz, James; Davies, T. Jonathan; Kraft, Nathan J.B.; Ault, Toby R.; Bolmgren, Kjell; Mazer, Susan J.; McCabe, Gregory J.; McGill, Brian J.; Parmesan, Camille; Salamin, Nicolas; Schwartz, Mark D.; Cleland, Elsa E. 2012-01-01 Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010939','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010939">Warming Experiments Underpredict Plant Phenological Responses to Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Wolkovich, E. M.; Cook, B. I.; Allen, J. M.; Crimmins, T. M.; Betancourt, J. L.; Travers, S. E.; Pau, S.; Regetz, J.; Davies, T. J.; Kraft, N. J. B.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140010939'); toggleEditAbsImage('author_20140010939_show'); toggleEditAbsImage('author_20140010939_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140010939_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140010939_hide"> 2012-01-01 Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMPP51A2106L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMPP51A2106L">Climate along the crest of the US Rocky Mountains during the last glaciation: preliminary insights from numerical modeling of paleoglaciers</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Leonard, E. M.; Laabs, B. J.; Plummer, M. A.; Huss, E.; Spiess, V. M.; Mackall, B. T.; Jacobsen, R. E.; Quirk, B. 2012-12-01 Climate conditions at the time of the local Last Glacial Maximum (LGM) in the US Rocky Mountains were assessed using a 2-d coupled glacier energy/mass-balance and ice-flow model (Plummer and Phillips, 2003). The model was employed to understand the conditions that would be necessary to sustain valley glaciers and small mountain icecaps at their maximum extents in eight areas distributed along the crest of the range from northern New Mexico (35.8oN) to northern Montana (48.6oN). For each setting, model experiments yield a set of temperature and precipitation combinations that may have accompanied the local LGM. If the results of global and regional climate models are used to constrain temperature depression estimates from our model experiments, the following precipitation pattern emerges for the local LGM. In the northern Rocky Mountains in Montana and northern Wyoming, model results suggest a strong reduction in precipitation of 50% or more. In the central Rocky Mountains of southern Wyoming and Colorado, precipitation appears to have been 50-90% of modern. By contrast, precipitation appears to have been strongly enhanced in the southern Rocky Mountains of New Mexico. These results are broadly consistent with a pattern of precipitation observed in global and regional climate simulations of the LGM in the western U.S., in which precipitation was reduced in the northern Rocky Mountains but increased in the southern Rocky Mountains. This pattern may reflect a southward displacement of mean position the Pacific Jet Stream in western North America during and possibly following the LGM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70155916','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70155916">Urgent need for warming experiments in tropical forests</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Calaveri, Molly A.; Reed, Sasha C.; Smith, W. Kolby; Wood, Tana E. 2015-01-01 Although tropical forests account for only a fraction of the planet's terrestrial surface, they exchange more carbon dioxide with the atmosphere than any other biome on Earth, and thus play a disproportionate role in the global climate. In the next 20 years, the tropics will experience unprecedented warming, yet there is exceedingly high uncertainty about their potential responses to this imminent climatic change. Here, we prioritize research approaches given both funding and logistical constraints in order to resolve major uncertainties about how tropical forests function and also to improve predictive capacity of earth system models. We investigate overall model uncertainty of tropical latitudes and explore the scientific benefits and inevitable trade-offs inherent in large-scale manipulative field experiments. With a Coupled Model Intercomparison Project Phase 5 analysis, we found that model variability in projected net ecosystem production was nearly 3 times greater in the tropics than for any other latitude. Through a review of the most current literature, we concluded that manipulative warming experiments are vital to accurately predict future tropical forest carbon balance, and we further recommend the establishment of a network of comparable studies spanning gradients of precipitation, edaphic qualities, plant types, and/or land use change. We provide arguments for long-term, single-factor warming experiments that incorporate warming of the most biogeochemically active ecosystem components (i.e. leaves, roots, soil microbes). Hypothesis testing of underlying mechanisms should be a priority, along with improving model parameterization and constraints. No single tropical forest is representative of all tropical forests; therefore logistical feasibility should be the most important consideration for locating large-scale manipulative experiments. Above all, we advocate for multi-faceted research programs, and we offer arguments for what we consider the most powerful and urgent way forward in order to improve our understanding of tropical forest responses to climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25641092','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25641092">Urgent need for warming experiments in tropical forests.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Cavaleri, Molly A; Reed, Sasha C; Smith, W Kolby; Wood, Tana E 2015-06-01 Although tropical forests account for only a fraction of the planet's terrestrial surface, they exchange more carbon dioxide with the atmosphere than any other biome on Earth, and thus play a disproportionate role in the global climate. In the next 20 years, the tropics will experience unprecedented warming, yet there is exceedingly high uncertainty about their potential responses to this imminent climatic change. Here, we prioritize research approaches given both funding and logistical constraints in order to resolve major uncertainties about how tropical forests function and also to improve predictive capacity of earth system models. We investigate overall model uncertainty of tropical latitudes and explore the scientific benefits and inevitable trade-offs inherent in large-scale manipulative field experiments. With a Coupled Model Intercomparison Project Phase 5 analysis, we found that model variability in projected net ecosystem production was nearly 3 times greater in the tropics than for any other latitude. Through a review of the most current literature, we concluded that manipulative warming experiments are vital to accurately predict future tropical forest carbon balance, and we further recommend the establishment of a network of comparable studies spanning gradients of precipitation, edaphic qualities, plant types, and/or land use change. We provide arguments for long-term, single-factor warming experiments that incorporate warming of the most biogeochemically active ecosystem components (i.e. leaves, roots, soil microbes). Hypothesis testing of underlying mechanisms should be a priority, along with improving model parameterization and constraints. No single tropical forest is representative of all tropical forests; therefore logistical feasibility should be the most important consideration for locating large-scale manipulative experiments. Above all, we advocate for multi-faceted research programs, and we offer arguments for what we consider the most powerful and urgent way forward in order to improve our understanding of tropical forest responses to climate change. © 2015 John Wiley & Sons Ltd. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009WRR....45.8419L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009WRR....45.8419L">From climate model ensembles to climate change impacts and adaptation: A case study of water resource management in the southwest of England</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lopez, Ana; Fung, Fai; New, Mark; Watts, Glenn; Weston, Alan; Wilby, Robert L. 2009-08-01 The majority of climate change impacts and adaptation studies so far have been based on at most a few deterministic realizations of future climate, usually representing different emissions scenarios. Large ensembles of climate models are increasingly available either as ensembles of opportunity or perturbed physics ensembles, providing a wealth of additional data that is potentially useful for improving adaptation strategies to climate change. Because of the novelty of this ensemble information, there is little previous experience of practical applications or of the added value of this information for impacts and adaptation decision making. This paper evaluates the value of perturbed physics ensembles of climate models for understanding and planning public water supply under climate change. We deliberately select water resource models that are already used by water supply companies and regulators on the assumption that uptake of information from large ensembles of climate models will be more likely if it does not involve significant investment in new modeling tools and methods. We illustrate the methods with a case study on the Wimbleball water resource zone in the southwest of England. This zone is sufficiently simple to demonstrate the utility of the approach but with enough complexity to allow a variety of different decisions to be made. Our research shows that the additional information contained in the climate model ensemble provides a better understanding of the possible ranges of future conditions, compared to the use of single-model scenarios. Furthermore, with careful presentation, decision makers will find the results from large ensembles of models more accessible and be able to more easily compare the merits of different management options and the timing of different adaptation. The overhead in additional time and expertise for carrying out the impacts analysis will be justified by the increased quality of the decision-making process. We remark that even though we have focused our study on a water resource system in the United Kingdom, our conclusions about the added value of climate model ensembles in guiding adaptation decisions can be generalized to other sectors and geographical regions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA576320','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA576320">The Impact of Spring Subsurface Soil Temperature Anomaly in the Western U.S. on North American Summer Precipitation: A Case Study Using Regional Climate Model Downscaling</a> <a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a> 2012-06-02 regional climate model downscaling , J. Geophys. Res., 117, D11103, doi:10.1029/2012JD017692. 1. Introduction [2] Modeling studies and data analyses...based on ground and satellite data have demonstrated that the land surface state variables, such as soil moisture, snow, vegetation, and soil temperature... downscaling rather than simply applying reanal- ysis data as LBC for both Eta control and sensitivity experiments as done in many RCM sensitivity studies </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC51A0735M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC51A0735M">Superensemble of a Regional Climate Model for the Western US using Climateprediction.net</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mote, P.; Salahuddin, A.; Allen, M.; Jones, R. 2010-12-01 For over a decade, a citizen science experiment called climateprediction.net organized by Oxford University has used computer time contributed by over 80,000 volunteers around the world to create superensembles of global climate simulations. A new climateprediction.net experiment built by the UK Meteorological Office and Oxford, and released in late summer 2010, brings these computing resources to bear on regional climate modeling for the Western US, western Europe, and southern Africa. For the western US, the spatial resolution of 25km permits important topological features -- mountain ranges and valleys -- to be resolved and to influence simulated climate, which consequently includes many important observed features of climate like the fact that California’s Central Valley is hottest at the north and south ends in summer, and cooler in the middle owing to the maritime influence that leaks through the gap in the coast range in the San Francisco area. We designed the output variables to satisfy both research needs and societal and environmental impacts needs. These include atmospheric circulation on regional and global scales, surface fluxes of energy, and hydrologic variables; extremes of temperature, precipitation, and wind; and derived quantities like frost days and number of consecutive dry days. Early results from pre-release beta testing suggest that the simulated fields compare favorably with available observations, and that the model performs as well in the distributed computing environment as on a dedicated high-performance machine. The advantages of a superensemble in interpreting regional climate change will permit an unprecedented combination of statistical completeness and spatial resolution. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A33A0215W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A33A0215W">Predicting Summer Dryness Under a Warmer Climate: Modeling Land Surface Processes in the Midwestern United States</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Winter, J. M.; Eltahir, E. A. 2009-12-01 One of the most significant impacts of climate change is the potential alteration of local hydrologic cycles over agriculturally productive areas. As the world’s food supply continues to be taxed by its burgeoning population, a greater percentage of arable land will need to be utilized and land currently producing food must become more efficient. This study seeks to quantify the effects of climate change on soil moisture in the American Midwest. A series of 24-year numerical experiments were conducted to assess the ability of Regional Climate Model Version 3 coupled to Integrated Biosphere Simulator (RegCM3-IBIS) and Biosphere-Atmosphere Transfer Scheme 1e (RegCM3-BATS1e) to simulate the observed hydroclimatology of the midwestern United States. Model results were evaluated using NASA Surface Radiation Budget, NASA Earth Radiation Budget Experiment, Illinois State Water Survey, Climate Research Unit Time Series 2.1, Global Soil Moisture Data Bank, and regional-scale estimations of evapotranspiration. The response of RegCM3-IBIS and RegCM3-BATS1e to a surrogate climate change scenario, a warming of 3oC at the boundaries and doubling of CO2, was explored. Precipitation increased significantly during the spring and summer in both RegCM3-IBIS and RegCM3-BATS1e, leading to additional runoff. In contrast, enhancement of evapotranspiration and shortwave radiation were modest. Soil moisture remained relatively unchanged in RegCM3-IBIS, while RegCM3-BATS1e exhibited some fall and winter wetting. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H34D..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H34D..01S">Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H. 2017-12-01 Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A22F..02G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A22F..02G">The Regional Climate Model Evaluation System: A Systematic Evaluation Of CORDEX Simulations Using Obs4MIPs</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Goodman, A.; Lee, H.; Waliser, D. E.; Guttowski, W. 2017-12-01 Observation-based evaluations of global climate models (GCMs) have been a key element for identifying systematic model biases that can be targeted for model improvements and for establishing uncertainty associated with projections of global climate change. However, GCMs are limited in their ability to represent physical phenomena which occur on smaller, regional scales, including many types of extreme weather events. In order to help facilitate projections in changes of such phenomena, simulations from regional climate models (RCMs) for 14 different domains around the world are being provided by the Coordinated Regional Climate Downscaling Experiment (CORDEX; www.cordex.org). However, although CORDEX specifies standard simulation and archiving protocols, these simulations are conducted independently by individual research and modeling groups representing each of these domains often with different output requirements and data archiving and exchange capabilities. Thus, with respect to similar efforts using GCMs (e.g., the Coupled Model Intercomparison Project, CMIP), it is more difficult to achieve a standardized, systematic evaluation of the RCMs for each domain and across all the CORDEX domains. Using the Regional Climate Model Evaluation System (RCMES; rcmes.jpl.nasa.gov) developed at JPL, we are developing easy to use templates for performing systematic evaluations of CORDEX simulations. Results from the application of a number of evaluation metrics (e.g., biases, centered RMS, and pattern correlations) will be shown for a variety of physical quantities and CORDEX domains. These evaluations are performed using products from obs4MIPs, an activity initiated by DOE and NASA, and now shepherded by the World Climate Research Program's Data Advisory Council. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70129256','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70129256">The key role of dry days in changing regional climate and precipitation regimes</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Polade, Suraj; Pierce, David W.; Cayan, Daniel R.; Gershunov, Alexander; Dettinger, Michael D. 2014-01-01 Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change in number of dry days dominates the annual changes in precipitation and accounts for a large part of the change in interannual precipitation variability. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913864M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913864M">Human health impacts avoided under the Paris Agreement on climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Mitchell, Dann 2017-04-01 This analyses makes use of the experiments and model data from the Half a degree Additional warming; Prognosis and Projected Impacts (HAPPI; www.happimip.org) analysis (Mitchell et al, 2016a). HAPPI is unique in that it is specifically designed to address the Paris Agreement priorities on climate impacts, by using equilibrated climates and super-ensembles, thereby enabling robust analysis of extremes. Here we first look at extreme hot and cold spells, and then make use of the most recent heat-mortality models, and heat stress metrics to look at any differences between 1.5C and 2C worlds compared to normal. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3140741','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3140741">The future of terrestrial mammals in the Mediterranean basin under climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Maiorano, Luigi; Falcucci, Alessandra; Zimmermann, Niklaus E.; Psomas, Achilleas; Pottier, Julien; Baisero, Daniele; Rondinini, Carlo; Guisan, Antoine; Boitani, Luigi 2011-01-01 The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition. PMID:21844047 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A41D0095R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A41D0095R">High Resolution Climate Modeling of the Water Cycle over the Contiguous United States Including Potential Climate Change Scenarios</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rasmussen, R.; Ikeda, K.; Liu, C.; Gochis, D.; Chen, F.; Barlage, M. J.; Dai, A.; Dudhia, J.; Clark, M. P.; Gutmann, E. D.; Li, Y. 2015-12-01 The NCAR Water System program strives to improve the full representation of the water cycle in both regional and global models. Our previous high-resolution simulations using the WRF model over the Rocky Mountains revealed that proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing (< 6 km horizontal) and parameterizations. The climate sensitivity experiment consistent with expected climate change showed an altered hydrological cycle with increased fraction of rain versus snow, increased snowfall at high altitudes, earlier melting of snowpack, and decreased total runoff. In order to investigate regional differences between the Rockies and other major mountain barriers and to study climate change impacts over other regions of the contiguous U.S. (CONUS), we have expanded our prior CO Headwaters modeling study to encompass most of North America at a horizontal grid spacing of 4 km. A domain expansion provides the opportunity to assess changes in orographic precipitation across different mountain ranges in the western USA, as well as the very dominant role of convection in the eastern half of the USA. The high resolution WRF-downscaled climate change data will also become a valuable community resource for many university groups who are interested in studying regional climate changes and impacts but unable to perform such long-duration and high-resolution WRF-based downscaling simulations of their own. The scientific goals and details of the model dataset will be presented including some preliminary results. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012MsT.........14H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012MsT.........14H">Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Holmes, Keith Richard Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.3536B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.3536B">Implications of land use change in tropical West Africa under global warming</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Brücher, Tim; Claussen, Martin 2015-04-01 Northern Africa, and the Sahel in particular, are highly vulnerable to climate change, due to strong exposure to increasing temperature, precipitation variability, and population growth. A major link between climate and humans in this region is land use and associated land cover change, mainly where subsistence farming prevails. But how strongly does climate change affect land use and how strongly does land use feeds back into climate change? To which extent may climate-induced water, food and wood shortages exacerbate conflict potential and lead changes in land use and to migration? Estimates of possible changes in African climate vary among the Earth System Models participating in the recent Coupled Model Intercomparison (CMIP5) exercise, except for the region adjacent to the Mediterranean Sea, where a significant decrease of precipitation emerges. While all models agree in a strong temperature increase, rainfall uncertainties for most parts of the Sahara, Sahel, and Sudan are higher. Here we present results of complementary experiments based on extreme and idealized land use change scenarios within a future climate.. We use the MPI-ESM forced with a strong green house gas scenario (RCP8.5) and apply an additional land use forcing by varying largely the intensity and kind of agricultural practice. By these transient experiments (until 2100) we elaborate the additional impact on climate due to strong land use forcing. However, the differences are mostly insignificant. The greenhouse gas caused temperature increase and the high variability in the West African Monsoon rainfall superposes the minor changes in climate due to land use. While simulated climate key variables like precipitation and temperature are not distinguishable from the CMIP5 RCP8.5 results, an additional greening is simulated, when crops are demanded. Crops have lower water usage than pastureland has. This benefits available soil water, which is taken up by the natural vegetation and makes it more productive. Given the limitations of an ESM, the findings of our study show that changes in the kind and intensity of land use have minor effects on the climate. Consequently, implications of extreme land use on e.g. human security, conflict or migration can be investigated in offline simulations. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active">20</li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active">21</li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990024954','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990024954">Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 1997-01-01 This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the Goddard Institute for Space Studies (GISS) 8 deg x lO deg atmospheric General Circulation Model (GCM) to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910015372','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910015372">The impact of greenhouse climate change on the energetics and hydrologic processes of mid-latitude transient eddies</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Branscome, Lee E.; Gutowski, William J., Jr. 1991-01-01 Atmospheric transient eddies contribute significantly to mid-latitude energy and water vapor transports. Changes in the global climate, as induced by greenhouse enhancement, will likely alter transient eddy behavior. Unraveling all the feedbacks that occur in general circulation models (GCMs) can be difficult. The transient eddies are isolated from the feedbacks and are focused on the response of the eddies to zonal-mean climate changes that result from CO2-doubling. Using a primitive-equation spectral model, the impact of climate change on the life cycles of transient eddies is examined. Transient eddy behavior in experiments is compared with initial conditions that are given by the zonal-mean climates of the GCMs with current and doubled amounts of CO2. The smaller meridional temperature gradient in a doubled CO2 climate leads to a reduction in eddy kinetic energy, especially in the subtropics. The decrease in subtropical eddy energy is related to a substantial reduction in equatorward flux of eddy activity during the latter part of the life cycle. The reduction in equatorward energy flux alters the moisture cycle. Eddy meridional transport of water vapor is shifted slightly poleward and subtropical precipitation is reduced. The water vapor transport exhibits a relatively small change in magnitude, compared to changes in eddy energy, due to the compensating effect of higher specific humidity in the doubled-CO2 climate. An increase in high-latitude precipitation is related to the poleward shift in eddy water vapor flux. Surface evaporation amplifies climatic changes in water vapor transport and precipitation in the experiments. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C23A1212A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C23A1212A">Responses of Basal Melting of Antarctic Ice Shelves to the Climatic Forcing of the Last Glacial Maximum and CO2 Doubling</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Abe-Ouchi, A.; Obase, T. 2017-12-01 Basal melting of the Antarctic ice shelves is an important factor in determining the stability of the Antarctic ice sheet. This study used the climatic outputs of an atmosphere?ocean general circulation model to force a circumpolar ocean model that resolves ice shelf cavity circulation to investigate the response of Antarctic ice shelf melting to different climatic conditions, i.e., to an increase (doubling) of CO2 and the Last Glacial Maximum conditions. We also conducted sensitivity experiments to investigate the role of surface atmospheric change, which strongly affects sea ice production, and the change of oceanic lateral boundary conditions. We found that the rate of change of basal melt due to climate warming is much greater (by an order of magnitude) than due to cooling. This is mainly because the intrusion of warm water onto the continental shelves, linked to sea ice production and climate change, is crucial in determining the basal melt rate of many ice shelves. Sensitivity experiments showed that changes of atmospheric heat flux and ocean temperature are both important for warm and cold climates. The offshore wind change together with atmospheric heat flux change strongly affected the production of sea ice and high-density water, preventing warmer water approaching the ice shelves under a colder climate. These results reflect the importance of both water mass formation in the Antarctic shelf seas and subsurface ocean temperature in understanding the long-term response to climate change of the melting of Antarctic ice shelves. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813933T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813933T">Historical influence of irrigation on climate extremes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Thiery, Wim; Davin, Edouard L.; Lawrence, Dave; Hauser, Mathias; Seneviratne, Sonia I. 2016-04-01 Land irrigation is an essential practice sustaining global food production and many regional economies. During the last decades, irrigation amounts have been growing rapidly. Emerging scientific evidence indicates that land irrigation substantially affects mean climate conditions in different regions of the world. However, a thorough understanding of the impact of irrigation on extreme climatic conditions, such as heat waves, droughts or intense precipitation, is currently still lacking. In this context, we aim to assess the historical influence of irrigation on the occurrence of climate extremes. To this end, two simulations are conducted over the period 1910-2010 with a state-of-the-art global climate model (the Community Earth System Model, CESM): a control simulation including all major anthropogenic and natural external forcings except for irrigation and a second experiment with transient irrigation enabled. The two simulations are evaluated for their ability to represent (i) hot, dry and wet extremes using the HadEX2 and ERA-Interim datasets as a reference, and (ii) latent heat fluxes using LandFlux-EVAL. Assuming a linear combination of climatic responses to different forcings, the difference between both experiments approximates the influence of irrigation. We will analyse the impact of irrigation on a number of climate indices reflecting the intensity and duration of heat waves. Thereby, particular attention is given to the role of soil moisture changes in modulating climate extremes. Furthermore, the contribution of individual biogeophysical processes to the total impact of irrigation on hot extremes is quantified by application of a surface energy balance decomposition technique to the 90th and 99th percentile surface temperature changes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1613362H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1613362H">WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald 2014-05-01 Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are accompanied by the WASCAL Graduate Research Program on the West African Climate System. The GRP-WACS provides ten scholarships per year for West African PhD students with a duration of three years. Present and future WASCAL PhD students will constitute one important user group of the Linux cluster that will be installed at the Competence Center in Ouagadougou, Burkina Faso. Regional Land-Atmosphere Simulations A key research activity of the WASCAL Core Research Program is the analysis of interactions between the land surface and the atmosphere to investigate how land surface changes affect hydro-meteorological surface fluxes such as evapotranspiration. Since current land surface models of global and regional climate models neglect dominant lateral hydrological processes such as surface runoff, a novel land surface model is used, the NCAR Distributed Hydrological Modeling System (NDHMS). This model can be coupled to WRF (WRF-Hydro) to perform two-way coupled atmospheric-hydrological simulations for the watershed of interest. Hardware and network prerequisites include a HPC cluster, network switches, internal storage media, Internet connectivity of sufficient bandwidth. Competences needed are HPC, storage, and visualization systems optimized for climate research, parallelization and optimization of climate models and workflows, efficient management of highest data volumes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70042367','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70042367">The response of soil organic carbon of a rich fen peatland in interior Alaska to projected climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Fan, Zhaosheng; McGuire, Anthony David; Turetsky, Merritt R.; Harden, Jennifer W.; Waddington, James Michael; Kane, Evan S. 2013-01-01 It is important to understand the fate of carbon in boreal peatland soils in response to climate change because a substantial change in release of this carbon as CO2 and CH4 could influence the climate system. The goal of this research was to synthesize the results of a field water table manipulation experiment conducted in a boreal rich fen into a process-based model to understand how soil organic carbon (SOC) of the rich fen might respond to projected climate change. This model, the peatland version of the dynamic organic soil Terrestrial Ecosystem Model (peatland DOS-TEM), was calibrated with data collected during 2005–2011 from the control treatment of a boreal rich fen in the Alaska Peatland Experiment (APEX). The performance of the model was validated with the experimental data measured from the raised and lowered water-table treatments of APEX during the same period. The model was then applied to simulate future SOC dynamics of the rich fen control site under various CO2 emission scenarios. The results across these emissions scenarios suggest that the rate of SOC sequestration in the rich fen will increase between year 2012 and 2061 because the effects of warming increase heterotrophic respiration less than they increase carbon inputs via production. However, after 2061, the rate of SOC sequestration will be weakened and, as a result, the rich fen will likely become a carbon source to the atmosphere between 2062 and 2099. During this period, the effects of projected warming increase respiration so that it is greater than carbon inputs via production. Although changes in precipitation alone had relatively little effect on the dynamics of SOC, changes in precipitation did interact with warming to influence SOC dynamics for some climate scenarios. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.4468M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.4468M">Putting Climate Change on the Map: A Translation from Time to Space</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Marzeion, B.; Bethke, I.; Drange, H. 2009-04-01 By increasing the concentrations of atmospheric greenhouses gases, man is changing the physical geography of planet Earth. This message is often given to the public in form of rather abstract numbers, such as changes in the annual mean surface temperature. Therefore, one of the difficulties to overcome when educating the public about climate change is to translate these abstract numbers into everyday experiences - a task that is not easy given the statistical and thereby abstract definition of the term 'climate' itself. However, climate does not only vary with time, but also with space, and people generally have a better idea of what it would be like to live in another place, than to experience an annual mean temperature rise of e.g. 3 K. We used the model calculations from the fourth assessment report of the Intergovernmental Panel on Climate Change to translate the projected temperature change into a change of location: Each point on a geographical map is shifted to the closest location that in the year 2000 has the annual mean temperature that the point is projected to have at some time in the future. With this method, it is possible to create a new kind of accessible and visually appealing illustration of climate change, answering the question: Where do I have to go today to experience tomorrow's climate? Similarly, it is possible to answer a related question: Where would I have to move if I want to continue living in today's climate? </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC51H..09F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC51H..09F">Changes in extremes due to half a degree warming in observations and models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fischer, E. M.; Schleussner, C. F.; Pfleiderer, P. 2017-12-01 Assessing the climate impacts of half-a-degree warming increments is high on the post-Paris science agenda. Discriminating those effects is particularly challenging for climate extremes such as heavy precipitation and heat extremes for which model uncertainties are generally large, and for which internal variability is so important that it can easily offset or strongly amplify the forced local changes induced by half a degree warming. Despite these challenges we provide evidence for large-scale changes in the intensity and frequency of climate extremes due to half a degree warming. We first assess the difference in extreme climate indicators in observational data for the 1960s and 1970s versus the recent past, two periods differ by half a degree. We identify distinct differences for the global and continental-scale occurrence of heat and heavy precipitation extremes. We show that those observed changes in heavy precipitation and heat extremes broadly agree with simulated historical differences and are informative for the projected differences between 1.5 and 2°C warming despite different radiative forcings. We therefore argue that evidence from the observational record can inform the debate about discernible climate impacts in the light of model uncertainty by providing a conservative estimate of the implications of 0.5°C warming. A limitation of using the observational record arises from potential non-linearities in the response of climate extremes to a certain level of warming. We test for potential non-linearities in the response of heat and heavy precipitation extremes in a large ensemble of transient climate simulations. We further quantify differences between a time-window approach in a coupled model large ensemble vs. time-slice experiments using prescribed SST experiments performed in the context of the HAPPI-MIP project. Thereby we provide different lines of evidence that half a degree warming leads to substantial changes in the expected occurrence of heat and heavy precipitation extremes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006Natur.441...73V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006Natur.441...73V">Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Vecchi, Gabriel A.; Soden, Brian J.; Wittenberg, Andrew T.; Held, Isaac M.; Leetmaa, Ants; Harrison, Matthew J. 2006-05-01 Since the mid-nineteenth century the Earth's surface has warmed, and models indicate that human activities have caused part of the warming by altering the radiative balance of the atmosphere. Simple theories suggest that global warming will reduce the strength of the mean tropical atmospheric circulation. An important aspect of this tropical circulation is a large-scale zonal (east-west) overturning of air across the equatorial Pacific Ocean-driven by convection to the west and subsidence to the east-known as the Walker circulation. Here we explore changes in tropical Pacific circulation since the mid-nineteenth century using observations and a suite of global climate model experiments. Observed Indo-Pacific sea level pressure reveals a weakening of the Walker circulation. The size of this trend is consistent with theoretical predictions, is accurately reproduced by climate model simulations and, within the climate models, is largely due to anthropogenic forcing. The climate model indicates that the weakened surface winds have altered the thermal structure and circulation of the tropical Pacific Ocean. These results support model projections of further weakening of tropical atmospheric circulation during the twenty-first century. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.G32A..04Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.G32A..04Y">The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yang, Z. 2011-12-01 I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B31D0599K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B31D0599K">Modelling carbon in permafrost soils from preindustrial to the future</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kleinen, T.; Brovkin, V. 2015-12-01 The carbon release from thawing permafrost soils constitutes one of the large uncertainties in the carbon cycle under future climate change. Analysing the problem further, this uncertainty results from an uncertainty about the total amount of C that is stored in frozen soils, combined with an uncertainty about the areas where soils might thaw under a particular climate change scenario, as well as an uncertainty about the decomposition product since some of the decomposed C might result the release of CH4 as well as CO2. We use the land surface model JSBACH, part of the Max Planck Institute Earth System Model MPI-ESM, to quantify the release of soil carbon from thawing permafrost soils. We have extended the soil carbon model YASSO by introducing carbon storages in frozen soils, with increasing fractions of C being available to decomposition as permafrost thaws. In order to quantify the amount of carbon released as CH4, as opposed to CO2, we have also implemented a TOPMODEL-based wetland scheme, as well as anaerobic C decomposition and methane transport. We initialise the soil C pools for the preindustrial climate state from the Northern Circumpolar Soil Carbon Database to insure initial C pool sizes close to measurements. We then determine changes in soil C storage in transient model experiments following historical and future climate changes under RCP 8.5. Based on these experiments, we quantify the greenhouse gas release from permafrost C decomposition, determining both CH4 and CO2 emissions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1989PhDT.......196M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1989PhDT.......196M">a Physical Parameterization of Snow Albedo for Use in Climate Models.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Marshall, Susan Elaine The albedo of a natural snowcover is highly variable ranging from 90 percent for clean, new snow to 30 percent for old, dirty snow. This range in albedo represents a difference in surface energy absorption of 10 to 70 percent of incident solar radiation. Most general circulation models (GCMs) fail to calculate the surface snow albedo accurately, yet the results of these models are sensitive to the assumed value of the snow albedo. This study replaces the current simple empirical parameterizations of snow albedo with a physically-based parameterization which is accurate (within +/- 3% of theoretical estimates) yet efficient to compute. The parameterization is designed as a FORTRAN subroutine (called SNOALB) which can be easily implemented into model code. The subroutine requires less then 0.02 seconds of computer time (CRAY X-MP) per call and adds only one new parameter to the model calculations, the snow grain size. The snow grain size can be calculated according to one of the two methods offered in this thesis. All other input variables to the subroutine are available from a climate model. The subroutine calculates a visible, near-infrared and solar (0.2-5 μm) snow albedo and offers a choice of two wavelengths (0.7 and 0.9 mu m) at which the solar spectrum is separated into the visible and near-infrared components. The parameterization is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, version 1 (CCM1), and the results of a five -year, seasonal cycle, fixed hydrology experiment are compared to the current model snow albedo parameterization. The results show the SNOALB albedos to be comparable to the old CCM1 snow albedos for current climate conditions, with generally higher visible and lower near-infrared snow albedos using the new subroutine. However, this parameterization offers a greater predictability for climate change experiments outside the range of current snow conditions because it is physically-based and not tuned to current empirical results. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPA43B2196S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPA43B2196S">Experiences with collaborative climate impacts assessments for regional governments in southwestern British Columbia</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sobie, S. R.; Murdock, T. Q. 2016-12-01 Infrastructure vulnerability assessments and adaptation planning have created demand for detailed information about climate change and extreme events from local and regional governments. Individual communities often have distinct priorities regarding climate change impacts. While projections from climate models are available to investigate these impacts, they are not always applicable or easily interpreted by local agencies. We discuss a series of climate impacts assessments for several regional and local governments in southwestern British Columbia. Each of the assessments was conducted with input from the users on project definition from the start of the process and on interpretation of results throughout each project. To produce sufficient detail for the assessment regions, we produce high-resolution (800m) simulations of precipitation and temperature using downscaled climate model projections. Sets of derived climate parameters tailored to each region are calculated from both standard indices such as CLIMDEX and from an energy-balance snowpack model. Involving user groups from the beginning of the analysis helps to convey the meaning and confidence of each set of climate change parameters to users and also clarifies what projections are feasible or not for impact assessments. We discuss the different levels of involvement and collaboration with each organization, and the resulting decisions implemented following each of the projects. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B51B1790L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B51B1790L">Investigate the plant biomass response to climate warming in permafrost ecosystem using matrix-based data assimilation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lu, X.; Du, Z.; Schuur, E.; Luo, Y. 2017-12-01 Permafrost is one of the most vulnerable regions on the earth with over 40% world soil C represented in this region. Future climate warming potentially has a great impact on this region. On one hand, rising temperature accelerates permafrost soil thaw and release more C from land. On the other hand, warming may also increase the plant growing season length and therefore negatively feedback to climate change by increasing annual land C uptake. However, whether permafrost vegetation biomass change in response to warming can sequester more C has not been well understood. Manipulated air warming experiments reported that air warming has very limited impacts on grass land productivity and biomass growth in permafrost region [Mauritz et al., 2017]. It is hard to reveal the mechanisms behind the limited air warming response directly from experiment data. We employ a vegetation C cycle matrix model based on Community land model 4.5 (CLM4.5) and data assimilation technique to investigate how much do phenology and physiology processes contribute to the response respectively. Our results indicate phenology contributes the most in response to warming. The shift of vegetation parameter distributions after 2012 indicate vegetation acclimation may explain the modest response in plant biomass to air warming. The results suggest future model development need to take vegetation acclimation more seriously. The novel matrix-based model allows data assimilation to be conducted more efficiently. It provides more functional understanding of the models as well as the mechanism behind experiment data. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020061380','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020061380">Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Tao, W. K.; Wang, Y.; Qian, J.; Shie, C. -L.; Lau, W. K. -M.; Kakar, R.; Starr, David O' C. (Technical Monitor) 2002-01-01 The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GPC...162..235D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GPC...162..235D">Future changes over the Himalayas: Mean temperature</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dimri, A. P.; Kumar, D.; Choudhary, A.; Maharana, P. 2018-03-01 An assessment of the projection of near surface air temperature over the Himalayan region from the COordinated Regional Climate Downscaling EXperiment- South Asia (hereafter, CORDEX-SA) regional climate model (RCM) experiments have been carried out for different Representative Concentration Pathway (RCP) scenarios. The purpose of this study is to assess the probable future changes in the mean temperature climatology and its long term trend for different seasons under greenhouse gas forcing scenarios for different seasons till the end of 21st century. A number of statistical measures such as changes in mean climatology, long term trend and probability distribution function have been used in order to detect the signals of changes in climate. Moreover, the associated uncertainties among different model experiments and their ensemble in space, time and different seasons in particular have been quantified. Despite of strong cold bias in the model experiments over Himalayan region (Nengker et al., 2017), statistically significant strong rate of warming (0.03-0.09 °C/year) across all the seasons and RCPs have been projected by all the models and their ensemble. Season specific response towards the warming is indicated by ensemble under future climate while ON season shows comparable magnitude of warming than DJF. Such warming intensifies with the increase in the radiative forcing under a range of greenhouse gas scenarios from RCP2.6 to RCP8.5. In addition to this, a wide range of spatial variability and disagreements in the trend magnitude between different models describes the uncertainty associated with the model projections and scenarios. A substantial seasonal response to warming with respect to elevation was also found, as DJF season followed by ON portrays highest rate of warming, specifically at higher elevation sites such as western Himalayas and northern part of central Himalayas. The different elevation classes respond differently to the projected future warming under different RCPs and seasons. Such higher warming during DJF may have consequences as changes in the fractional distribution of the solid and liquid precipitation as well as the melting of the glacial deposits with ultimately affecting the streamflow response and water resources in the downstream areas. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9260E..2RS','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9260E..2RS">Topographical effects of climate dataset and their impacts on the estimation of regional net primary productivity</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sun, L. Qing; Feng, Feng X. 2014-11-01 In this study, we first built and compared two different climate datasets for Wuling mountainous area in 2010, one of which considered topographical effects during the ANUSPLIN interpolation was referred as terrain-based climate dataset, while the other one did not was called ordinary climate dataset. Then, we quantified the topographical effects of climatic inputs on NPP estimation by inputting two different climate datasets to the same ecosystem model, the Boreal Ecosystem Productivity Simulator (BEPS), to evaluate the importance of considering relief when estimating NPP. Finally, we found the primary contributing variables to the topographical effects through a series of experiments given an overall accuracy of the model output for NPP. The results showed that: (1) The terrain-based climate dataset presented more reliable topographic information and had closer agreements with the station dataset than the ordinary climate dataset at successive time series of 365 days in terms of the daily mean values. (2) On average, ordinary climate dataset underestimated NPP by 12.5% compared with terrain-based climate dataset over the whole study area. (3) The primary climate variables contributing to the topographical effects of climatic inputs for Wuling mountainous area were temperatures, which suggest that it is necessary to correct temperature differences for estimating NPP accurately in such a complex terrain. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC44A..02L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC44A..02L">Impacts of historic and projected land-cover, land-use, and land-management change on carbon and water fluxes: The Land Use Model Intercomparison Project (LUMIP)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lawrence, D. M.; Lombardozzi, D. L.; Lawrence, P.; Hurtt, G. C. 2017-12-01 Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to intensify to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the broad question of impacts of land-use and land-cover change (LULCC) as well as more detailed science questions to get at process-level attribution, uncertainty, and data requirements in more depth and sophistication than possible in a multi-model context to date. LUMIP is multi-faceted and aims to advance our understanding of land-use change from several perspectives. In particular, LUMIP includes a factorial set of land-only simulations that differ from each other with respect to the specific treatment of land use or land management (e.g., irrigation active or not, crop fertilization active or not, wood harvest on or not), or in terms of prescribed climate. This factorial series of experiments serves several purposes and is designed to provide a detailed assessment of how the specification of land-cover change and land management affects the carbon, water, and energy cycle response to land-use change. The potential analyses that are possible through this set of experiments are vast. For example, comparing a control experiment with all land management active to an experiment with no irrigation allows a multi-model assessment of whether or not the increasing use of irrigation during the 20th century is likely to have significantly altered trends of regional water and energy fluxes (and therefore climate) and/or crop yield and carbon fluxes in agricultural regions. Here, we will present preliminary results from the factorial set of experiments utilizing the Community Land Model (CLM5). The analyses presented here will help guide multi-model analyses once the full set of LUMIP simulations are available. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.8786B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.8786B">Future Climate Change in the Baltic Sea Area</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Bøssing Christensen, Ole; Kjellström, Erik; Zorita, Eduardo; Sonnenborg, Torben; Meier, Markus; Grinsted, Aslak 2015-04-01 Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to downscaling and impact models is relatively small, but more are emerging. A large number of coupled climate-environmental scenario simulations for the Baltic Sea have been performed within the BONUS+ projects (ECOSUPPORT, INFLOW, AMBER and Baltic-C (2009-2011)), using various combinations of output from GCMs, RCMs, hydrological models and scenarios for load and emission of nutrients as forcing for Baltic Sea models. Such a large ensemble of scenario simulations for the Baltic Sea has never before been produced and enables for the first time an estimation of uncertainties. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AGUFMGC11A0123W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFMGC11A0123W">Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Williams, C.; Kniveton, D.; Layberry, R. 2007-12-01 It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active">21</li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active">22</li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT........21S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT........21S">Regional and global implications of land-use change and climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Stauffer, Heidi Lada This dissertation has two main components. The first is a longterm regional climate modeling study of the effects of different types of land use changes on Southeast Asian climate under present-day climate conditions and under future projected climate conditions at the end of the 21st Century. The focus of the second component is to estimate daily heat index for projected extreme temperatures at the end of the 21st Century and projecting the number of people affected by those heat conditions. The first component of this study uses a high-resolution regional climate model centered on the Southeast Asian region to compare two land use change scenarios under modern climate and future projected climate conditions. Results from experiments under modern climate conditions indicate that changes in regional climate including widespread surface cooling, increased precipitation, and increased latent heat flux are primarily due to deforestation. As expected from other studies, future climate projections indicate increasing surface temperature and total precipitation. However, the combination of increasing global temperatures and irrigation appears to increase latent heat flux and evapotranspiration, leading to decrease in the surface temperature nearly the same magnitude, increasing both specific humidity and relative humidity. The increasing relative humidity causes low clouds to form, and the net surface solar absorbed flux decreases in response, which further cools the surface. These results imply that deforestation and irrigation have differing complex regional climate responses and the presence of irrigation could mask future surface temperature increases, at least in the short term and reinforce the importance of incorporating land use changes, particularly irrigation, into any studies of future regional climate. The second component of this study uses global daily maximum heat indices derived from future climate future climate simulations for 2098 and projected population density to estimate how many people will be affected by rising temperatures. Our results show that over 4 billion people annually will experience prolonged periods of Danger heat index conditions, under which heat exhaustion and heat stroke are likely. In addition, a majority of people subjected to prolonged high heat stress conditions are located in tropical developing nations, such as those in south and Southeast Asia, where population density is high and large numbers of people work outdoors. Many countries in these regions lack the resources to mitigate the impact of heat stress on the large numbers of people likely to experience heat-related illness and death. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29732409','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29732409">Climate models predict increasing temperature variability in poor countries.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bathiany, Sebastian; Dakos, Vasilis; Scheffer, Marten; Lenton, Timothy M 2018-05-01 Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C -1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5931768','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5931768">Climate models predict increasing temperature variability in poor countries</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Dakos, Vasilis; Scheffer, Marten 2018-01-01 Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C−1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate. PMID:29732409 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1816253R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1816253R">3D visualization of ultra-fine ICON climate simulation data</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Röber, Niklas; Spickermann, Dela; Böttinger, Michael 2016-04-01 Advances in high performance computing and model development allow the simulation of finer and more detailed climate experiments. The new ICON model is based on an unstructured triangular grid and can be used for a wide range of applications, ranging from global coupled climate simulations down to very detailed and high resolution regional experiments. It consists of an atmospheric and an oceanic component and scales very well for high numbers of cores. This allows us to conduct very detailed climate experiments with ultra-fine resolutions. ICON is jointly developed in partnership with DKRZ by the Max Planck Institute for Meteorology and the German Weather Service. This presentation discusses our current workflow for analyzing and visualizing this high resolution data. The ICON model has been used for eddy resolving (<10km) ocean simulations, as well as for ultra-fine cloud resolving (120m) atmospheric simulations. This results in very large 3D time dependent multi-variate data that need to be displayed and analyzed. We have developed specific plugins for the free available visualization software ParaView and Vapor, which allows us to read and handle that much data. Within ParaView, we can additionally compare prognostic variables with performance data side by side to investigate the performance and scalability of the model. With the simulation running in parallel on several hundred nodes, an equal load balance is imperative. In our presentation we show visualizations of high-resolution ICON oceanographic and HDCP2 atmospheric simulations that were created using ParaView and Vapor. Furthermore we discuss our current efforts to improve our visualization capabilities, thereby exploring the potential of regular in-situ visualization, as well as of in-situ compression / post visualization. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC13J0811C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC13J0811C">Impacts of Land Cover Changes on Climate over China</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Chen, L.; Frauenfeld, O. W. 2014-12-01 Land cover changes can influence regional climate through modifying the surface energy balance and water fluxes, and can also affect climate at large scales via changes in atmospheric general circulation. With rapid population growth and economic development, China has experienced significant land cover changes, such as deforestation, grassland degradation, and farmland expansion. In this study, the Community Earth System Model (CESM) is used to investigate the climate impacts of anthropogenic land cover changes over China. To isolate the climatic effects of land cover change, we focus on the CAM and CLM models, with prescribed climatological sea surface temperature and sea ice cover. Two experiments were performed, one with current vegetation and the other with potential vegetation. Current vegetation conditions were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, and potential vegetation over China was obtained from Ramankutty and Foley's global potential vegetation dataset. Impacts of land cover changes on surface air temperature and precipitation are assessed based on the difference of the two experiments. Results suggest that land cover changes have a cold-season cooling effect in a large region of China, but a warming effect in summer. These temperature changes can be reconciled with albedo forcing and evapotranspiration. Moreover, impacts on atmospheric circulation and the Asian Monsoon is also discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.2778S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.2778S">Enabling the use of climate model data in the Dutch climate effect community</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Som de Cerff, Wim; Plieger, Maarten 2010-05-01 Within the climate effect community the usage of climate model data is emerging. Where mostly climate time series and weather generators were used, there is a shift to incorporate climate model data into climate effect models. The use of climate model data within the climate effect models is difficult, due to missing metadata, resolution and projection issues, data formats and availability of the parameters of interest. Often the climate effect modelers are not aware of available climate model data or are not aware of how they can use it. Together with seven other partners (CERFACS, CNR-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 IS ENES (http://www.enes.org) project work package 10/JRA5 ‘Bridging Climate Research Data and the Needs of the Impact Community. The aims of this work package are to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. Phase one is to define use cases together with the Dutch climate effect community, which describe the intended use of climate model data in climate effect models. We defined four use cases: 1) FEWS hydrological Framework (Deltares) 2) METAPHOR, a plants and species dispersion model (Wageningen University) 3) Natuurplanner, an Ecological model suite (Wageningen University) 4) Land use models (Free University/JRC). Also the other partners in JRA5 have defined use cases, which are representative for the climate effect and impact communities in their country. Goal is to find commonalities between all defined use cases. The common functionality will be implemented as e-tools and incorporated in the IS-ENES data portal. Common issues relate to e.g., need for high resolution: downscaling from GCM to local scale (also involves interpolation); parameter selection; finding extremes; averaging methods. At the conference we will describe the FEWS case in more detail: Delft FEWS is an open shell system (in development since 1995) for performing hydrological predictions and the handling of time series data. The most important capabilities of FEWS are importing of meteorological and hydrological data and organizing the workflows of the different models which can be used within FEWS, like the Netherlands Hydrological Instrumentarium (NHI). Besides predictions, the system is currently being used for hydrological climate effects studies. Currently regionally downscaled data are used, but using model data will be the next step. This coupling of climate model data to FEWS will open a wider rage of climate impact and effect research, but it is a difficult task to accomplish. Issues to be dealt with are: regridding, downscaling, format conversion, extraction of required data and addition of descriptive metadata, including quality and uncertainty parameters. Finding an appropriate solution involves several iterations: first, the use case was defined, then we just provided a single data file containing some data of interest provided via FTP, next this data was offered through OGC services. Currently we are working on providing larger datasets and improving on the parameters and metadata. We will present the results (e-tools/data) and experiences gained on implementing the described use cases. Note that we are currently using experimental data, as the official climate model runs are not available yet. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19880062499&hterms=effect+global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Deffect%2Bglobal%2Bwarming','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19880062499&hterms=effect+global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Deffect%2Bglobal%2Bwarming">Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Hansen, J.; Fung, I.; Lacis, A.; Rind, D.; Lebedeff, S.; Ruedy, R.; Russell, G. 1988-01-01 The global climate effects of time-dependent atmospheric trace gas and aerosol variations are simulated by NASA-Goddard's three-dimensional climate model II, which possesses 8 x 10-deg horizontal resolution, for the cases of a 100-year control run and three different atmospheric composition scenarios in which trace gas growth is respectively a continuation of current exponential trends, a reduced linear growth, and a rapid curtailment of emissions due to which net climate forcing no longer increases after the year 2000. The experiments begin in 1958, run to the present, and encompass measured or estimated changes in CO2, CH4, N2O, chlorofluorocarbons, and stratospheric aerosols. It is shown that the greenhouse warming effect may be clearly identifiable in the 1990s. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC24B..01L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC24B..01L">The Land Use Model Intercomparison Project (LUMIP) Contribution to CMIP6: Rationale and Experimental Design</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lawrence, D. M.; Hurtt, G. C.; Arneth, A.; Brovkin, V.; Calvin, K. V.; Jones, A. D.; Jones, C.; Lawrence, P.; De Noblet-Ducoudré, N.; Pongratz, J.; Seneviratne, S. I.; Shevliakova, E. 2016-12-01 Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the impacts of land-use and land-cover change (LULCC) on climate, specifically addressing the questions: (1) What are the effects of LULCC on climate and biogeochemical cycling (past-future)? (2) What are the impacts of land management on surface fluxes of carbon, water, and energy and (3) Are there regional land-management strategies with promise to help mitigate against climate change? LUMIP will also address a range of more detailed science questions to get at process-level attribution, uncertainty, data requirements, and other related issues in more depth and sophistication than possible in a multi-model context to date. Foci will include separation and quantification of the effects on climate from LULCC relative to all forcings, separation of biogeochemical from biogeophysical effects of land-use, the unique impacts of land-cover change versus land management change, modulation of land-use impact on climate by land-atmosphere coupling strength, and the extent that CO2 fertilization is modulated by past and future land use. LUMIP involves three sets of activities: (1) development of an updated and expanded historical and future land-use dataset, (2) an experimental protocol for LUMIP experiments, and (3) definition of metrics that quantify model performance with respect to LULCC. LUMIP experiments are designed to be complementary to simulations requested in the CMIP6 DECK and historical simulations and other CMIP6 MIPs including ScenarioMIP, C4MIP, LS3MIP, and DAMIP. LUMIP includes idealized coupled and land-only model simulations designed to advance process-level understanding of LULCC impacts on climate. LUMIP also includes simulations that allow quantification of the historic impact of land use and the potential for future land management decisions to aid in mitigation of climate change. We will present the experimental protocol in detail, explain the rationale, outlines plans for analysis, and describe a new subgrid land-use tile data request for selected variables (reporting model output data separately for primary and secondary land, crops, pasture, and urban land-use types). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22328649','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22328649">Functions of parental involvement and effects of school climate on bullying behaviors among South Korean middle school students.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Lee, Chang-Hun; Song, Juyoung 2012-08-01 This study uses an ecological systems theory to understand bullying behavior. Emphasis is given to overcome limitations found in the literature, such as very little empirical research on functions of parental involvement and the impacts of school climate on bullying as an outcome variable. Two functions of parental involvement investigated are (a) bridging the negative experiences within the family with bullying behaviors at schools, and (b) influencing school climate. Bullying behaviors were measured by a modified Korean version of Olweus' bully/victim questionnaire (reliability range: .78-.84) from 1,238 randomly selected Korean middle school students in 2007. Findings from structural equation modeling (SEM) analyses showed that (a) individual traits are one of the most important influence on bullying, (b) negative experiences in the family do not have direct influence on bullying behaviors at school, (c) parental involvement influences school climate, and (d) positive school climate was negatively related to bullying behaviors. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.6369M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.6369M">Splitting turbulence algorithm for mixing parameterization embedded in the ocean climate model. Examples of data assimilation and Prandtl number variations.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Moshonkin, Sergey; Gusev, Anatoly; Zalesny, Vladimir; Diansky, Nikolay 2017-04-01 Series of experiments were performed with a three-dimensional, free surface, sigma coordinate eddy-permitting ocean circulation model for Atlantic (from 30°S) - Arctic and Bering sea domain (0.25 degrees resolution, Institute of Numerical Mathematics Ocean Model or INMOM) using vertical grid refinement in the zone of fully developed turbulence (40 sigma-levels). The model variables are horizontal velocity components, potential temperature, and salinity as well as free surface height. For parameterization of viscosity and diffusivity, the original splitting turbulence algorithm (STA) is used when total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF) split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage the analytical solution was obtained for TKE and TDF as functions of the buoyancy and velocity shift frequencies (BF and VSF). The proposed model with STA is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. For mixing simulation in the zone of turbulence decay, the two kind numerical experiments were carried out, as with assimilation of annual mean climatic buoyancy frequency, as with variation of Prandtl number function dependence upon the BF, VSF, TKE and TDF. The CORE-II data for 1948-2009 were used for experiments. Quality of temperature T and salinity S structure simulation is estimated by the comparison of model monthly profiles T and S averaged for 1980-2009, with T and S monthly data from the World Ocean Atlas 2013. Form of coefficients in equations for TKE and TDF on the generation-dissipation stage makes it possible to assimilate annual mean climatic buoyancy frequency in a varying degree that cardinally improves adequacy of model results to climatic data in all analyzed model domain. The numerical experiments with modified Prandtl number presents possibility for essential improvement of the TKE attenuation with depth and more realistic water entrainment from pycnocline into the mixed layer. The high sensitivity is revealed of the eddy-permitting circulation stable model solution to the change of the used above mixing parameterizations. This sensitivity is connected with significant changes of density fields in the upper baroclinic ocean layer over the total considered area. For instance, assimilation of annual mean climatic buoyancy frequency in equations for TKE and TDF leads to more realistic circulation in the North Atlantic. Variations of Prandtl number made it possible to simulate intense circulation in Beaufort Gyre owing to steric effect during the whole period under consideration. The research was supported by the Russian Foundation for Basic Research (grants №16-05-00534 and 15-05-00557). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H51J1397G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H51J1397G">Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Gampe, D.; Ludwig, R. 2017-12-01 Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and detect potential model biases with respect to each reference data set. The RCMs are then ranked based on various statistical measures for each indicator and a score matrix is derived to select a subset of RCMs. We show the impact and importance of the reference data set with respect to the resulting climate change signal on the catchment scale. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70176525','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70176525">Non-linear responses of glaciated prairie wetlands to climate warming</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Johnson, W. Carter; Werner, Brett; Guntenspergen, Glenn R. 2016-01-01 The response of ecosystems to climate warming is likely to include threshold events when small changes in key environmental drivers produce large changes in an ecosystem. Wetlands of the Prairie Pothole Region (PPR) are especially sensitive to climate variability, yet the possibility that functional changes may occur more rapidly with warming than expected has not been examined or modeled. The productivity and biodiversity of these wetlands are strongly controlled by the speed and completeness of a vegetation cover cycle driven by the wet and dry extremes of climate. Two thresholds involving duration and depth of standing water must be exceeded every few decades or so to complete the cycle and to produce highly functional wetlands. Model experiments at 19 weather stations employing incremental warming scenarios determined that wetland function across most of the PPR would be diminished beyond a climate warming of about 1.5–2.0 °C, a critical temperature threshold range identified in other climate change studies. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.8753D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.8753D">Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim 2016-04-01 The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24257163','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24257163">Redesigning mental healthcare delivery: is there an effect on organizational climate?</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Joosten, T C M; Bongers, I M B; Janssen, R T J M 2014-02-01 Many studies have investigated the effect of redesign on operational performance; fewer studies have evaluated the effects on employees' perceptions of their working environment (organizational climate). Some authors state that redesign will lead to poorer organizational climate, while others state the opposite. The goal of this study was to empirically investigate this relation. Organizational climate was measured in a field experiment, before and after a redesign intervention. At one of the sites, a redesign project was conducted. At the other site, no redesign efforts took place. Two Dutch child- and adolescent-mental healthcare providers. Professionals that worked at one of the units at the start and/or the end of the intervention period. The main intervention was a redesign project aimed at improving timely delivery of services (modeled after the breakthrough series). Scores on the four models of the organizational climate measure, a validated questionnaire that measures organizational climate. Our analysis showed that climate at the intervention site changed on factors related to productivity and goal achievement (rational goal model). The intervention group scored worse than the comparison group on the part of the questionnaire that focuses on sociotechnical elements of organizational climate. However, observed differences were so small, that their practical relevance seems rather limited. Redesign efforts in healthcare, so it seems, do not influence organizational climate as much as expected. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160000368&hterms=analysis+climatic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Danalysis%2Bclimatic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160000368&hterms=analysis+climatic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Danalysis%2Bclimatic">Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160000368'); toggleEditAbsImage('author_20160000368_show'); toggleEditAbsImage('author_20160000368_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160000368_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160000368_hide"> 2014-01-01 Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020046683','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020046683">Comparison of Mean Climate Trends in the Northern Hemisphere Between N.C.E.P. and Two Atmosphere-Ocean Model Forced Runs</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Lucarini, Valerio; Russell, Gary L.; Hansen, James E. (Technical Monitor) 2002-01-01 Results are presented for two greenhouse gas experiments of the Goddard Institute for Space Studies Atmosphere-Ocean Model (AOM). The computed trends of surface pressure, surface temperature, 850, 500 and 200 mb geopotential heights and related temperatures of the model for the time frame 1960-2000 are compared to those obtained from the National Centers for Environmental Prediction observations. A spatial correlation analysis and mean value comparison are performed, showing good agreement. A brief general discussion about the statistics of trend detection is presented. The domain of interest is the Northern Hemisphere (NH) because of the higher reliability of both the model results and the observations. The accuracy that this AOM has in describing the observed regional and NH climate trends makes it reliable in forecasting future climate changes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27594725','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27594725">Climate Shocks and Migration: An Agent-Based Modeling Approach.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree 2016-09-01 This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H34D..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H34D..01S">A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M. 2016-12-01 Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5004973','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5004973">Climate Shocks and Migration: An Agent-Based Modeling Approach</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree 2016-01-01 This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29769728','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29769728">Emerging trends in global freshwater availability.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Rodell, M; Famiglietti, J S; Wiese, D N; Reager, J T; Beaudoing, H K; Landerer, F W; Lo, M-H 2018-05-01 Freshwater availability is changing worldwide. Here we quantify 34 trends in terrestrial water storage observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during 2002-2016 and categorize their drivers as natural interannual variability, unsustainable groundwater consumption, climate change or combinations thereof. Several of these trends had been lacking thorough investigation and attribution, including massive changes in northwestern China and the Okavango Delta. Others are consistent with climate model predictions. This observation-based assessment of how the world's water landscape is responding to human impacts and climate variations provides a blueprint for evaluating and predicting emerging threats to water and food security. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active">22</li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active">23</li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.1383D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.1383D">Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Christensen, Hannah M.; Juricke, Stephan; Subramanian, Aneesh; Watson, Peter A. G.; Weisheimer, Antje; Palmer, Tim N. 2017-03-01 The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), together with coupled transient runs (1850-2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate - specifically the Madden-Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations). </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.B24D..03R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.B24D..03R">Dryland feedbacks to climatic change: Results from a climate manipulation experiment on the Colorado Plateau</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Reed, S.; Belnap, J.; Ferrenberg, S.; Wertin, T. M.; Darrouzet-Nardi, A.; Tucker, C.; Rutherford, W. A. 2015-12-01 Arid and semiarid ecosystems cover ~40% of Earth's terrestrial surface and make up ~35% of the U.S., yet we know surprisingly little about how climate change will affect these widespread landscapes. Like many dryland regions, the Colorado Plateau in the southwestern U.S. is predicted to experience climate change as elevated temperature and altered timing and amount of annual precipitation. We are using a long-term (>10 yr) factorial warming and supplemental rainfall experiment on the Colorado Plateau to explore how predicted changes in climate will affect vascular plant and biological soil crust community composition, biogeochemical cycling, and energy balance (biocrusts are a surface soil community of moss, lichen, and cyanobacteria that can make up as much as 70% of the living cover in drylands). While some of the responses we have observed were expected, many of the results are surprising. For example, we documented biocrust community composition shifts in response to altered climate that were significantly faster and more dramatic than considered likely for these soil communities that typically change over decadal and centennial timescales. Further, while we continue to observe important climate change effects on carbon cycling - including reduced net photosynthesis in vascular plants, increased CO2 losses from biocrust soils during some seasons, and changes to the interactions between water and carbon cycles - we have also found marked treatment effects on the albedo and spectral signatures of dryland soils. In addition to demonstrating the effects of these treatments, the strong relationships we observed in our experiments between biota and climate provide a quantitative framework for improving our representation of dryland responses to climate change. In this talk we will cover a range of datasets that, taken together, show: (1) large climate-driven changes to dryland biogeochemical cycling may be the result of both effects on existing communities, as well of relatively rapid shifts in community composition; (2) drylands could provide feedbacks to future climate not only though altered carbon cycling but also via changes to surface albedo; and (3) models of dryland responses to climate change may need significant revision, but such a revision is well within reach. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMSH42A..02K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMSH42A..02K">Quantifying uncertainties of climate signals related to the 11-year solar cycle</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kruschke, T.; Kunze, M.; Matthes, K. B.; Langematz, U.; Wahl, S. 2017-12-01 Although state-of-the-art reconstructions based on proxies and (semi-)empirical models converge in terms of total solar irradiance, they still significantly differ in terms of spectral solar irradiance (SSI) with respect to the mean spectral distribution of energy input and temporal variability. This study aims at quantifying uncertainties for the Earth's climate related to the 11-year solar cycle by forcing two chemistry-climate models (CCMs) - CESM1(WACCM) and EMAC - with five different SSI reconstructions (NRLSSI1, NRLSSI2, SATIRE-T, SATIRE-S, CMIP6-SSI) and the reference spectrum RSSV1-ATLAS3, derived from observations. We conduct a unique set of timeslice experiments. External forcings and boundary conditions are fixed and identical for all experiments, except for the solar forcing. The set of analyzed simulations consists of one solar minimum simulation, employing RSSV1-ATLAS3 and five solar maximum experiments. The latter are a result of adding the amplitude of solar cycle 22 according to the five reconstructions to RSSV1-ATLAS3. Our results show that the climate response to the 11y solar cycle is generally robust across CCMs and SSI forcings. However, analyzing the variance of the solar maximum ensemble by means of ANOVA-statistics reveals additional information on the uncertainties of the mean climate signals. The annual mean response agrees very well between the two CCMs for most parts of the lower and middle atmosphere. Only the upper mesosphere is subject to significant differences related to the choice of the model. However, the different SSI forcings lead to significant differences in ozone concentrations, shortwave heating rates, and temperature throughout large parts of the mesosphere and upper stratosphere. Regarding the seasonal evolution of the climate signals, our findings for short wave heating rates, and temperature are similar to the annual means with respect to the relative importance of the choice of the model or the SSI forcing for the respective atmospheric layer. On the other hand, the predominantly dynamically driven signal in zonal wind is quite dependent on the choice of a CCM, mainly due to spatio-temporal shifts of similar responses. Within a given "model world" dynamical signals related to the different SSI forcings agree very well even under this monthly perspective. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC22D..07A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC22D..07A">Regional Climate Change Impact on Agricultural Land Use in West Africa</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ahmed, K. F.; Wang, G.; You, L. 2014-12-01 Agriculture is a key element of the human-induced land use land cover change (LULCC) that is influenced by climate and can potentially influence regional climate. Temperature and precipitation directly impact the crop yield (by controlling photosynthesis, respiration and other physiological processes) that then affects agricultural land use pattern. In feedback, the resulting changes in land use and land cover play an important role to determine the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. The assessment of future agricultural land use is, therefore, of great importance in climate change study. In this study, we develop a prototype land use projection model and, using this model, project the changes to land use pattern and future land cover map accounting for climate-induced yield changes for major crops in West Africa. Among the inputs to the land use projection model are crop yield changes simulated by the crop model DSSAT, driven with the climate forcing data from the regional climate model RegCM4.3.4-CLM4.5, which features a projected decrease of future mean crop yield and increase of inter-annual variability. Another input to the land use projection model is the projected changes of food demand in the future. In a so-called "dumb-farmer scenario" without any adaptation, the combined effect of decrease in crop yield and increase in food demand will lead to a significant increase in agricultural land use in future years accompanied by a decrease in forest and grass area. Human adaptation through land use optimization in an effort to minimize agricultural expansion is found to have little impact on the overall areas of agricultural land use. While the choice of the General Circulation Model (GCM) to derive initial and boundary conditions for the regional climate model can be a source of uncertainty in projecting the future LULCC, results from sensitivity experiments indicate that the changes in land use pattern are robust. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1409263-climate-impacts-calipso-guided-corrections-black-carbon-aerosol-vertical-distributions-global-climate-model','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1409263-climate-impacts-calipso-guided-corrections-black-carbon-aerosol-vertical-distributions-global-climate-model">Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R. Here, we alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ~8–50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the globalmore » average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1409263-climate-impacts-calipso-guided-corrections-black-carbon-aerosol-vertical-distributions-global-climate-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1409263-climate-impacts-calipso-guided-corrections-black-carbon-aerosol-vertical-distributions-global-climate-model">Climate Impacts of CALIPSO-Guided Corrections to Black Carbon Aerosol Vertical Distributions in a Global Climate Model</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Kovilakam, Mahesh; Mahajan, Salil; Saravanan, R.; ... 2017-09-13 Here, we alleviate the bias in the tropospheric vertical distribution of black carbon aerosols (BC) in the Community Atmosphere Model (CAM4) using the Cloud-Aerosol and Infrared Pathfinder Satellite Observations (CALIPSO)-derived vertical profiles. A suite of sensitivity experiments are conducted with 1x, 5x, and 10x the present-day model estimated BC concentration climatology, with (corrected, CC) and without (uncorrected, UC) CALIPSO-corrected BC vertical distribution. The globally averaged top of the atmosphere radiative flux perturbation of CC experiments is ~8–50% smaller compared to uncorrected (UC) BC experiments largely due to an increase in low-level clouds. The global average surface temperature increases, the globalmore » average precipitation decreases, and the ITCZ moves northward with the increase in BC radiative forcing, irrespective of the vertical distribution of BC. Further, tropical expansion metrics for the poleward extent of the Northern Hemisphere Hadley cell (HC) indicate that simulated HC expansion is not sensitive to existing model biases in BC vertical distribution.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.6546S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.6546S">Reforestation in a high-CO2 world -- Higher mitigation potential than expected, lower adaptation potential than hoped for</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Sonntag, Sebastian; Pongratz, Julia; Reick, Christian H.; Schmidt, Hauke 2016-06-01 We assess the potential and possible consequences for the global climate of a strong reforestation scenario for this century. We perform model experiments using the Max Planck Institute Earth System Model (MPI-ESM), forced by fossil-fuel CO2 emissions according to the high-emission scenario Representative Concentration Pathway (RCP) 8.5, but using land use transitions according to RCP4.5, which assumes strong reforestation. Thereby, we isolate the land use change effects of the RCPs from those of other anthropogenic forcings. We find that by 2100 atmospheric CO2 is reduced by 85 ppm in the reforestation model experiment compared to the reference RCP8.5 model experiment. This reduction is higher than previous estimates and is due to increased forest cover in combination with climate and CO2 feedbacks. We find that reforestation leads to global annual mean temperatures being lower by 0.27 K in 2100. We find large annual mean warming reductions in sparsely populated areas, whereas reductions in temperature extremes are also large in densely populated areas. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1613964I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1613964I">Uncertainties in Decadal Model Evaluation due to the Choice of Different Reanalysis Products</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Illing, Sebastian; Kadow, Christopher; Kunst, Oliver; Cubasch, Ulrich 2014-05-01 In recent years decadal predictions have become very popular in the climate science community. A major task is the evaluation and validation of a decadal prediction system. Therefore hindcast experiments are performed and evaluated against observation based or reanalysis data-sets. That is, various metrics and skill scores like the anomaly correlation or the mean squared error skill score (MSSS) are calculated to estimate potential prediction skill of the model system. Our results will mostly feature the Baseline 1 hindcast experiments from the MiKlip decadal prediction system. MiKlip (www.fona-miklip.de) is a project for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) and has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. There are various reanalysis and observation based products covering at least the last forty years which can be used for model evaluation, for instance the 20th Century Reanalysis from NOAA-CIRES, the Climate Forecast System Reanalysis from NCEP or the Interim Reanalysis from ECMWF. Each of them is based on different climate models and observations. We will show that the choice of the reanalysis product has a huge impact on the value of various skill metrics. In some cases this may actually lead to a change in the interpretation of the results, e.g. when one tries to compare two model versions and the anomaly correlation difference changes its sign for two different reanalysis products. We will also show first results of our studies investigating the influence and effect of this source of uncertainty for decadal model evaluation. Furthermore we point out regions which are most affected by this uncertainty and where one has to cautious interpreting skill scores. In addition we introduce some strategies to overcome or at least reduce this source of uncertainty. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..521A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..521A">Constructing optimal ensemble projections for predictive environmental modelling in Northern Eurasia</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Anisimov, Oleg; Kokorev, Vasily 2013-04-01 Large uncertainties in climate impact modelling are associated with the forcing climate data. This study is targeted at the evaluation of the quality of GCM-based climatic projections in the specific context of predictive environmental modelling in Northern Eurasia. To accomplish this task, we used the output from 36 CMIP5 GCMs from the IPCC AR-5 data base for the control period 1975-2005 and calculated several climatic characteristics and indexes that are most often used in the impact models, i.e. the summer warmth index, duration of the vegetation growth period, precipitation sums, dryness index, thawing degree-day sums, and the annual temperature amplitude. We used data from 744 weather stations in Russia and neighbouring countries to analyze the spatial patterns of modern climatic change and to delineate 17 large regions with coherent temperature changes in the past few decades. GSM results and observational data were averaged over the coherent regions and compared with each other. Ultimately, we evaluated the skills of individual models, ranked them in the context of regional impact modelling and identified top-end GCMs that "better than average" reproduce modern regional changes of the selected meteorological parameters and climatic indexes. Selected top-end GCMs were used to compose several ensembles, each combining results from the different number of models. Ensembles were ranked using the same algorithm and outliers eliminated. We then used data from top-end ensembles for the 2000-2100 period to construct the climatic projections that are likely to be "better than average" in predicting climatic parameters that govern the state of environment in Northern Eurasia. The ultimate conclusions of our study are the following. • High-end GCMs that demonstrate excellent skills in conventional atmospheric model intercomparison experiments are not necessarily the best in replicating climatic characteristics that govern the state of environment in Northern Eurasia, and independent model evaluation on regional level is necessary to identify "better than average" GCMs. • Each of the ensembles combining results from several "better than average" models replicate selected meteorological parameters and climatic indexes better than any single GCM. The ensemble skills are parameter-specific and depend on models it consists of. The best results are not necessarily those based on the ensemble comprised by all "better than average" models. • Comprehensive evaluation of climatic scenarios using specific criteria narrows the range of uncertainties in environmental projections. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045752&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045752&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DParkinsons">The role of sea ice in 2 x CO2 climate model sensitivity. Part 1: The total influence of sea ice thickness and extent</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rind, D.; Healy, R.; Parkinson, C.; Martinson, D. 1995-01-01 As a first step in investigating the effects of sea ice changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple sea ice model while varying the sea ice distributions and thicknesses in the control run. Thinner ice amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner ice to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater sea ice extent in the control run, which provides more opportunity for sea ice reduction. An experiment with sea ice not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of sea ice on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to sea ice variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the sea ice impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying sea level increases of varying magnitude or no change. These results highlight the importance of properly constraining the sea ice response to climate perturbations, necessitating the use of more realistic sea ice and ocean models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9544M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9544M">Extrapolating carbon dynamics of tropical dry forests into future climates: improving simulation models with empirical observations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Medvigy, David; Waring, Bonnie; Vargas, German; Xu, Xiangtao; Smith, Christina; Becknell, Justin; Trierweiler, Annette; Brodribb, Timothy; Powers, Jennifer 2017-04-01 Tropical dry forests occur in areas with warm temperatures and a pronounced dry season with little to no rainfall that lasts 3 to 7 months. The potential area covered by this biome is vast: globally, 47% of all forest occurs in tropical and subtropical latitudes, and of all tropical forests approximately 42% are classified as dry forests. Throughout the last several centuries, the area covered by tropical dry forests has been dramatically reduced through conversion to grazing and croplands, and they are now considered the most threatened tropical biome. However, in many regions, tropical dry forests are now growing back. There is growing concern that this recovery process will be strongly impacted by climate variability and change. Observations show that climate is changing in the seasonal tropics, and climate models forecast that neotropical dry forests will receive significantly less rainfall in the 21st century than in the 20th century. Rates of nitrogen deposition are also changing rapidly in this sector, and the fertility of some soils may still be recovering from past land use. We are engaged in several efforts to understand how water and nutrients limit the productivity of these forests, including manipulative experiments, modeling, and investigation of responses to natural climate variability. In 2015, at a well-characterized site in Guanacaste, Costa Rica, we established a full-factorial fertilization experiment with N and P in diverse mature forest stands. Initial responses highlight stronger ecosystem sensitivity to P addition than to N addition. Intriguingly, pre-experiment numerical simulations with a mechanistic ecosystem model had indicated the reverse. Work is ongoing to use field observations to better represent critical processes in the model, and ultimately to improve the model's sensitivity to nutrients and water. In addition, in 2016, we established a full factorial nutrient addition and drought experiment in plantations. Thus far, soil moisture has been successfully reduced in the drought treatments. Finally, we are investigating the impact of an extreme climatic event, the 2015 drought, on the productivity of this forest. The fingerprint of the drought on tree mortality is very strong. We found that plot-level mortality rates were two to three times higher during the drought than before the drought, and varied from 0 to >50% among species. In contrast to observations at moist tropical forests, tree size had little influence on mortality. In terms of functional groups, mortality rates of evergreen oaks growing on nutrient-poor soils particularly increased during drought. However, elevated mortality rates were not clearly correlated with commonly-measured traits like wood density or specific leaf area. In addition, trees that died during the drought tended to have smaller relative growth rate prior to the drought than trees that survived the drought. Mechanistic models are able to simulate stand-level mortality following the drought, and model-data comparison highlights different tree hydraulic strategies that can mitigate drought effects. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC23A1209H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC23A1209H">Toward Evaluating the Predictability of Arctic-related Climate Variations: Initial Results from ArCS Project Theme 5</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Hasumi, H. 2016-12-01 We present initial results from the theme 5 of the project ArCS, which is a national flagship project for Arctic research in Japan. The goal of theme 5 is to evaluate the predictability of Arctic-related climate variations, wherein we aim to: (1) establish the scientific basis of climate predictability; and (2) develop a method for predicting/projecting medium- and long-term climate variations. Variability in the Arctic environment remotely influences middle and low latitudes. Since some of the processes specific to the Arctic environment function as a long memory of the state of the climate, understanding of the process of remote connections would lead to higher-precision and longer-term prediction of global climate variations. Conventional climate models have large uncertainty in the Arctic region. By making Arctic processes in climate models more sophisticated, we aim to clarify the role of multi-sphere interaction in the Arctic environment. In this regard, our newly developed high resolution ice-ocean model has revealed the relationship between the oceanic heat transport into the Arctic Ocean and the synoptic scale atmospheric variability. We also aim to reveal the mechanism of remote connections by conducting climate simulations and analyzing various types of climate datasets. Our atmospheric model experiments under possible future situations of Arctic sea ice cover indicate that reduction of sea ice qualitatively alters the basic mechanism of remote connection. Also, our analyses of climate data have identified the cause of recent more frequent heat waves at Eurasian mid-to-high latitudes and clarified the dynamical process which forms the West Pacific pattern, a dominant mode of the atmospheric anomalous circulation in the West Pacific region which also exhibits a significant signal in the Arctic stratosphere. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20180000152&hterms=climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclimate%2Bchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20180000152&hterms=climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dclimate%2Bchange">Interactive Nature of Climate Change and Aerosol Forcing</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Nazarenko, L.; Rind, D.; Tsigaridis, K.; Del Genio, A. D.; Kelley, M.; Tausnev, N. 2017-01-01 The effect of changing cloud cover on climate, based on cloud-aerosol interactions, is one of the major unknowns for climate forcing and climate sensitivity. It has two components: (1) the impact of aerosols on clouds and climate due to in-situ interactions (i.e., rapid response); and (2) the effect of aerosols on the cloud feedback that arises as climate changes - climate feedback response. We examine both effects utilizing the NASA GISS ModelE2 to assess the indirect effect, with both mass-based and microphysical aerosol schemes, in transient twentieth-century simulations. We separate the rapid response and climate feedback effects by making simulations with a coupled version of the model as well as one with no sea surface temperature or sea ice response (atmosphere-only simulations). We show that the indirect effect of aerosols on temperature is altered by the climate feedbacks following the ocean response, and this change differs depending upon which aerosol model is employed. Overall the effective radiative forcing (ERF) for the direct effect of aerosol-radiation interaction (ERFari) ranges between -0.2 and -0.6 W/sq m for atmosphere-only experiments while the total effective radiative forcing, including the indirect effect (ERFari+aci) varies between about -0.4 and -1.1 W/sq m for atmosphere-only simulations; both ranges are in agreement with those given in IPCC (2013). Including the full feedback of the climate system lowers these ranges to -0.2 to -0.5 W/sq m for ERFari, and -0.3 to -0.74 W/sq m for ERFari+aci. With both aerosol schemes, the climate change feedbacks have reduced the global average indirect radiative effect of atmospheric aerosols relative to what the emission changes would have produced, at least partially due to its effect on tropical upper tropospheric clouds. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19516338','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19516338">The proportionality of global warming to cumulative carbon emissions.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Matthews, H Damon; Gillett, Nathan P; Stott, Peter A; Zickfeld, Kirsten 2009-06-11 The global temperature response to increasing atmospheric CO(2) is often quantified by metrics such as equilibrium climate sensitivity and transient climate response. These approaches, however, do not account for carbon cycle feedbacks and therefore do not fully represent the net response of the Earth system to anthropogenic CO(2) emissions. Climate-carbon modelling experiments have shown that: (1) the warming per unit CO(2) emitted does not depend on the background CO(2) concentration; (2) the total allowable emissions for climate stabilization do not depend on the timing of those emissions; and (3) the temperature response to a pulse of CO(2) is approximately constant on timescales of decades to centuries. Here we generalize these results and show that the carbon-climate response (CCR), defined as the ratio of temperature change to cumulative carbon emissions, is approximately independent of both the atmospheric CO(2) concentration and its rate of change on these timescales. From observational constraints, we estimate CCR to be in the range 1.0-2.1 degrees C per trillion tonnes of carbon (Tt C) emitted (5th to 95th percentiles), consistent with twenty-first-century CCR values simulated by climate-carbon models. Uncertainty in land-use CO(2) emissions and aerosol forcing, however, means that higher observationally constrained values cannot be excluded. The CCR, when evaluated from climate-carbon models under idealized conditions, represents a simple yet robust metric for comparing models, which aggregates both climate feedbacks and carbon cycle feedbacks. CCR is also likely to be a useful concept for climate change mitigation and policy; by combining the uncertainties associated with climate sensitivity, carbon sinks and climate-carbon feedbacks into a single quantity, the CCR allows CO(2)-induced global mean temperature change to be inferred directly from cumulative carbon emissions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.7944G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.7944G">Evaluation of hydrological cycle in the major European midlatitude river basins in the frame of the CORDEX project</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Georgievski, Goran; Keuler, Klaus 2013-04-01 Water supply and its potential to increase social, economic and environmental risks are among the most critical challenges for the upcoming decades. Therefore, the assessment of the reliability of regional climate models (RCMs) to represent present-day hydrological balance of river basins is one of the most challenging tasks with high priority for climate modelling in order to estimate range of possible socio-economic impacts of the climate change. However, previous work in the frame of 4th IPCC AR and corresponding regional downscaling experiments (with focus on Europe and Danube river basin) showed that even the meteorological re-analyses provide unreliable data set for evaluations of climate model performance. Furthermore, large discrepancies among the RCMs are caused by internal model deficiencies (for example: systematic errors in dynamics, land-soil parameterizations, large-scale condensation and convection schemes), and in spite of higher resolution RCMs do not always improve much the results from GCMs, but even deteriorate it in some cases. All that has a consequence that capturing impact of climate change on hydrological cycle is not an easy task. Here we present state of the art of RCMs in the frame of the CORDEX project for Europe. First analysis shows again that even the up to date ERA-INTERIM re-analysis is not reliable for evaluation of hydrological cycle in major European midlatitude river basins (Seine, Rhine, Elbe, Oder, Vistula, Danube, Po, Rhone, Garonne and Ebro). Therefore, terrestrial water storage, a quasi observed parameter which is a combination of river discharge (from Global River Discharge Centre data set) and atmospheric moisture fluxes from ERA-INTERIM re-analysis, is used for verification. It shows qualitatively good agreement with COSMO-CLM (CCLM) regional climate simulation (abbreviated CCLM_eval) at 0.11 degrees horizontal resolution forced by ERA-INTERIM re-analysis. Furthermore, intercomparison of terrestrial water storage seasonal cycle averaged in Danube river basin for the ten years (1990-1999) overlapping period between CCLM historical experiment (abbreviated CCLM_hist), its forcing GCM (MPI-ESM-LR, here abbreviated MPI_hist) and CCLM_eval is performed. It reveals that CCLM_hist simulation is in better agreement with quasi observed terrestrial water storage than MPI_hist and CCLM_eval. This result seems promising for the assessment of impact of climate change on hydrological cycle. However, evaluation of the whole ensemble of regional climate downscaling experiments participated in CORDEX-Europe project would provide a more robust estimate. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040031721&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dclimate%2Bchange%2Banthropogenic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040031721&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dclimate%2Bchange%2Banthropogenic">Solar Effects on Climate and the Maunder Minimum: Minimum Certainty</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Rind, David 2003-01-01 The current state of our understanding of solar effects on climate is reviewed. As an example of the relevant issues, the climate during the Maunder Minimum is compared with current conditions in GCM simulations that include a full stratosphere and parameterized ozone response to solar spectral irradiance variability and trace gas changes. The GISS Global Climate/Middle Atmosphere Model coupled to a q-flux/mixed layer model is used for the simulations, which begin in 1500 and extend to the present. Experiments were made to investigate the effect of total versus spectrally-varying solar irradiance changes; spectrally-varying solar irradiance changes on the stratospheric ozone/climate response with both pre-industrial and present trace gases; and the impact on climate and stratospheric ozone of the preindustrial trace gases and aerosols by themselves. The results showed that: (1) the Maunder Minimum cooling relative to today was primarily associated with reduced anthropogenic radiative forcing, although the solar reduction added 40% to the overall cooling. There is no obvious distinguishing surface climate pattern between the two forcings. (2)The global and tropical response was greater than 1 C, in a model with a sensitivity of 1.2 C per W m-2. To reproduce recent low-end estimates would require a sensitivity 1/4 as large. (3) The global surface temperature change was similar when using the total and spectral irradiance prescriptions, although the tropical response was somewhat greater with the former, and the stratospheric response greater with the latter. (4) Most experiments produce a relative negative phase of the NAO/AO during the Maunder Minimum, with both solar and anthropogenic forcing equally capable, associated with the tropical cooling and relative poleward EP flux refraction. (5) A full stratosphere appeared to be necessary for the negative AO/NAO phase, as was the case with this model for global warming experiments, unless the cooling was very large, while the ozone response played a minor role and did not influence surface temperature significantly. (6) Stratospheric ozone was most affected by the difference between present day and preindustrial atmospheric composition and chemistry, with increases in the upper and lower stratosphere during the Maunder Minimum. While the estimated UV reduction led to ozone decreases, this was generally less important than the anthropogenic effect except in the upper middle stratosphere, as judged by two different ozone photochemistry schemes. (7) The effect of the reduced solar irradiance on stratospheric ozone and on climate was similar in Maunder Minimum and current atmospheric conditions. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5819387','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5819387">Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Scanlon, Bridget R.; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y.; van Beek, Ludovicus P. H.; Wiese, David N.; Reedy, Robert C.; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F. P. 2018-01-01 Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. PMID:29358394 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29358394','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29358394">Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Scanlon, Bridget R; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y; Müller Schmied, Hannes; van Beek, Ludovicus P H; Wiese, David N; Wada, Yoshihide; Long, Di; Reedy, Robert C; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F P 2018-02-06 Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤-0.5 km 3 /y) and increasing (≥0.5 km 3 /y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km 3 /y, whereas most models estimate decreasing trends (-71 to 11 km 3 /y). Land water storage trends, summed over all basins, are positive for GRACE (∼71-82 km 3 /y) but negative for models (-450 to -12 km 3 /y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. Copyright © 2018 the Author(s). Published by PNAS. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1988JCli....1..807C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1988JCli....1..807C">Stationary Waves of the Ice Age Climate.</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Cook, Kerry H.; Held, Isaac M. 1988-08-01 A linearized, steady state, primitive equation model is used to simulate the climatological zonal asymmetries (stationary eddies) in the wind and temperature fields of the 18 000 YBP climate during winter. We compare these results with the eddies simulated in the ice age experiments of Broccoli and Manabe, who used CLIMAP boundary conditions and reduced atmospheric CO2 in an atmospheric general circulation model (GCM) coupled with a static mixed layer ocean model. The agreement between the models is good, indicating that the linear model can be used to evaluate the relative influences of orography, diabatic heating, and transient eddy heat and momentum transports in generating stationary waves. We find that orographic forcing dominates in the ice age climate. The mechanical influence of the continental ice sheets on the atmosphere is responsible for most of the changes between the present day and ice age stationary eddies. This concept of the ice age climate is complicated by the sensitivity of the stationary eddies to the large increase in the magnitude of the zonal mean meridional temperature gradient simulated in the ice age GCM. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC51G..03J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC51G..03J">Impact of climate, CO2 and land use on terrestrial carbon and water fluxes in China based on a multi-model analysis</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Jia, B.; Xie, Z. 2017-12-01 Climate change and anthropogenic activities have been exerting profound influences on ecosystem function and processes, including tightly coupled terrestrial carbon and water cycles. However, their relative contributions of the key controlling factors, e.g., climate, CO2 fertilization, land use and land cover change (LULCC), on spatial-temporal patterns of terrestrial carbon and water fluxes in China are still not well understood due to the lack of ecosystem-level flux observations and uncertainties in single terrestrial biosphere model (TBM). In the present study, we quantified the effect of climate, CO2, and LULCC on terrestrial carbon and water fluxes in China using multi-model simulations for their inter-annual variability (IAV), seasonal cycle amplitude (SCA) and long-term trend during the past five decades (1961-2010). In addition, their relative contributions to the temporal variations of gross primary productivity (GPP), net ecosystem productivity (NEP) and evapotranspiration (ET) were investigated through factorial experiments. Finally, the discussions about the inter-model differences and model uncertainties were presented. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active">23</li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active">24</li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009ERL.....4d5106M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009ERL.....4d5106M">Toward ethical norms and institutions for climate engineering research</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Morrow, David R.; Kopp, Robert E.; Oppenheimer, Michael 2009-10-01 Climate engineering (CE), the intentional modification of the climate in order to reduce the effects of increasing greenhouse gas concentrations, is sometimes touted as a potential response to climate change. Increasing interest in the topic has led to proposals for empirical tests of hypothesized CE techniques, which raise serious ethical concerns. We propose three ethical guidelines for CE researchers, derived from the ethics literature on research with human and animal subjects, applicable in the event that CE research progresses beyond computer modeling. The Principle of Respect requires that the scientific community secure the global public's consent, voiced through their governmental representatives, before beginning any empirical research. The Principle of Beneficence and Justice requires that researchers strive for a favorable risk-benefit ratio and a fair distribution of risks and anticipated benefits, all while protecting the basic rights of affected individuals. Finally, the Minimization Principle requires that researchers minimize the extent and intensity of each experiment by ensuring that no experiments last longer, cover a greater geographical extent, or have a greater impact on the climate, ecosystem, or human welfare than is necessary to test the specific hypotheses in question. Field experiments that might affect humans or ecosystems in significant ways should not proceed until a full discussion of the ethics of CE research occurs and appropriate institutions for regulating such experiments are established. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990040408','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990040408">Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> 1998-01-01 This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040031738&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dclimate%2Bchange%2Banthropogenic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040031738&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dclimate%2Bchange%2Banthropogenic">Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS</a> <a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a> Pawson, Steven; Kodera, Kunihiko 2003-01-01 The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9244F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9244F">On procedures for model selection in providing climate scenario data for impact studies - A challenge to both communities</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Fox Maule, Cathrine; Sloth Madsen, Marianne; May, Wilhelm; Hesselbjerg Christensen, Jens; Yang, Shuting; Christensen, Ole B. 2015-04-01 Climate impact studies are based on climate simulations originating from regional or global climate models, provided either through the climate modeling centers directly or through climate data portals. In order to give the most beneficial results, the climate model data need to fulfill various requirements related to the respective impact models. These requirements, however, are often not well defined and subjected to individual impact models, and hence, can lead to discrepancies between the climate data provided by the climate modeling community and the data required by the impact models. As the climate model data are the first step in a process chain, limitations and problems with these data will affect the studies based on the results by the impact models and, hence, might confine the value of a project working with these results. DMI has over the past years provided climate scenario data for impact studies in several international and national research projects, including ENSEMBLES, WATCH, CRES and HYACINTS as well as the still ongoing projects IMPRESSIONS, IMPACT2C and MODEXTREME, dealing with numerous different impact sectors. Thus DMI has gained experience with a wide range of projects from very different disciplines including agriculture, hydrology, socio-economics, air-pollution and sea-level rise. The lessons learned from all these projects is that there is no standard procedure that can be implemented, but rather that individual solutions have to be constructed on a case-by-case basis for each project. This is due to the fact that the requirements for different impact models differ. For example, some impact models may need monthly input data, while others need daily data. Some need very high horizontal resolution while others may make do with relatively coarse resolution; some operate on global scale while others focus on regional or local scale. Some models need only a few variables as e.g. precipitation and temperature, while others also require e.g. radiation and evaporation. All of these requirements - and many more - shape the outcome of each individual project. Here, we highlight some of the procedures developed in some of the projects we have been involved in, and reason why the given steps were taken in those projects; focus is on MODEXTREME and IMPRESSIONS. We also point out some of the limiting factors that arise in concrete cases, often due to lack of useful observations or simulations. To conclude, we suggest a flow chart for decision as guidance to ease the procedure of providing suitable climate model output data for impact studies in future projects. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.4758O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.4758O">Characterizing bias correction uncertainty in wheat yield predictions</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam 2017-04-01 Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1420443-active-role-ocean-temporal-evolution-climate-sensitivity','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1420443-active-role-ocean-temporal-evolution-climate-sensitivity">The Active Role of the Ocean in the Temporal Evolution of Climate Sensitivity</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Garuba, Oluwayemi A.; Lu, Jian; Liu, Fukai; ... 2017-11-30 Here, the temporal evolution of the effective climate sensitivity is shown to be influenced by the changing pattern of sea surface temperature (SST) and ocean heat uptake (OHU), which in turn have been attributed to ocean circulation changes. A set of novel experiments are performed to isolate the active role of the ocean by comparing a fully coupled CO 2 quadrupling community Earth System Model (CESM) simulation against a partially coupled one, where the effect of the ocean circulation change and its impact on surface fluxes are disabled. The active OHU is responsible for the reduced effective climate sensitivity andmore » weaker surface warming response in the fully coupled simulation. The passive OHU excites qualitatively similar feedbacks to CO 2 quadrupling in a slab ocean model configuration due to the similar SST spatial pattern response in both experiments. Additionally, the nonunitary forcing efficacy of the active OHU (1.7) explains the very different net feedback parameters in the fully and partially coupled responses.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45..306G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45..306G">The Active Role of the Ocean in the Temporal Evolution of Climate Sensitivity</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Garuba, Oluwayemi A.; Lu, Jian; Liu, Fukai; Singh, Hansi A. 2018-01-01 The temporal evolution of the effective climate sensitivity is shown to be influenced by the changing pattern of sea surface temperature (SST) and ocean heat uptake (OHU), which in turn have been attributed to ocean circulation changes. A set of novel experiments are performed to isolate the active role of the ocean by comparing a fully coupled CO2 quadrupling community Earth System Model (CESM) simulation against a partially coupled one, where the effect of the ocean circulation change and its impact on surface fluxes are disabled. The active OHU is responsible for the reduced effective climate sensitivity and weaker surface warming response in the fully coupled simulation. The passive OHU excites qualitatively similar feedbacks to CO2 quadrupling in a slab ocean model configuration due to the similar SST spatial pattern response in both experiments. Additionally, the nonunitary forcing efficacy of the active OHU (1.7) explains the very different net feedback parameters in the fully and partially coupled responses. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1420443','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1420443">The Active Role of the Ocean in the Temporal Evolution of Climate Sensitivity</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Garuba, Oluwayemi A.; Lu, Jian; Liu, Fukai Here, the temporal evolution of the effective climate sensitivity is shown to be influenced by the changing pattern of sea surface temperature (SST) and ocean heat uptake (OHU), which in turn have been attributed to ocean circulation changes. A set of novel experiments are performed to isolate the active role of the ocean by comparing a fully coupled CO 2 quadrupling community Earth System Model (CESM) simulation against a partially coupled one, where the effect of the ocean circulation change and its impact on surface fluxes are disabled. The active OHU is responsible for the reduced effective climate sensitivity andmore » weaker surface warming response in the fully coupled simulation. The passive OHU excites qualitatively similar feedbacks to CO 2 quadrupling in a slab ocean model configuration due to the similar SST spatial pattern response in both experiments. Additionally, the nonunitary forcing efficacy of the active OHU (1.7) explains the very different net feedback parameters in the fully and partially coupled responses.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27216025','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27216025">Profiles of Student Perceptions of School Climate: Relations with Risk Behaviors and Academic Outcomes.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Shukla, Kathan; Konold, Timothy; Cornell, Dewey 2016-06-01 School climate has been linked to a variety of positive student outcomes, but there may be important within-school differences among students in their experiences of school climate. This study examined within-school heterogeneity among 47,631 high school student ratings of their school climate through multilevel latent class modeling. Student profiles across 323 schools were generated on the basis of multiple indicators of school climate: disciplinary structure, academic expectations, student willingness to seek help, respect for students, affective and cognitive engagement, prevalence of teasing and bullying, general victimization, bullying victimization, and bullying perpetration. Analyses identified four meaningfully different student profile types that were labeled positive climate, medium climate-low bullying, medium climate-high bullying, and negative climate. Contrasts among these profile types on external criteria revealed meaningful differences for race, grade-level, parent education level, educational aspirations, and frequency of risk behaviors. © Society for Community Research and Action 2016. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMED13G..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMED13G..07M">TV Weathercasters as Climate Educators: Rationale, Evidence for Effectiveness, and Potential for Nationwide Scale-Up. (Invited)</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Maibach, E.; Cullen, H. M.; Witte, J. 2013-12-01 Climate change is influencing every region of the nation through weather and climatic events including heat waves, droughts, extreme precipitation and floods, more intense hurricanes, and forest fires, yet most Americans continue to perceive climate change as a problem distant in time (with impacts a generation or more away), and in space (that will primarily affect other countries, not the United States). This may be caused, in part, due to the fact that climate change is often described in global, abstract, and analytical terms that are hard for people to connect to their own lives. The impacts of climate change, however, can be personally experienced at the local level, including through unusual weather events; cognitive science has shown that the human brain is more adept at learning through personal experience than through analytical reasoning. In this paper we will describe our efforts to enable America's TV weathercasters to embrace the role of climate educator. Weathercasters are a relatively small cohort of highly skilled communication professionals who are optimally positioned to reach a large majority of the American public, and help move their viewers beyond an abstract (distant) notion of global climate change and toward an understanding of climate change that is both local and concrete. Approximately 70% of American adults watch local TV news, and their primary reason for doing so is to learn about the weather. Our research has shown that TV weathercasters are second only to scientists and government science agencies as trusted sources of information about climate change. Our surveys have also shown that - in every region of the country - many TV weathercasters are willing to embrace the role of climate educator, if certain barriers can be overcome. Our experimental pilot-test - in Columbia, South Carolina - of a model developed to help overcome those barriers demonstrated that: when TV weathercasters make an effort to educate their viewers about the local ramifications of climate change, their viewers learn. Our current attempts to scale-up the model on a limited basis - in one state as a field experiment, and elsewhere around the nation on an uncontrolled basis - are showing promise in terms of attracting an increasing numbers of participating weathercasters. Lastly, professional associations that represent TV weathercasters (AMS and NWA), and government agencies that produce climate and weather data for meteorologists (NOAA and NASA), are committed to help scale up this model so that all interested TV weathercasters have easy access to localized information through which to educate their viewers about local weather and related implications of climate change. In sum, by engaging and empowering TV weathercasters as climate educators, we seek to increase public understanding of the relationships among climate, climate variability, climate change, weather extremes and community vulnerability, and we believe this model has considerable potential. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JHyd..517.1019F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JHyd..517.1019F">Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z. 2014-09-01 Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26331850','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26331850">Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Lee, Se-Yeun; Ryan, Maureen E; Hamlet, Alan F; Palen, Wendy J; Lawler, Joshua J; Halabisky, Meghan 2015-01-01 Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916-2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4557981','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4557981">Projecting the Hydrologic Impacts of Climate Change on Montane Wetlands</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Hamlet, Alan F.; Palen, Wendy J.; Lawler, Joshua J.; Halabisky, Meghan 2015-01-01 Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types. Here, we develop and demonstrate a new method for projecting climate-induced hydrologic changes in montane wetlands. Using observed wetland water levels and soil moisture simulated by the physically based Variable Infiltration Capacity (VIC) hydrologic model, we developed site-specific regression models relating soil moisture to observed wetland water levels to simulate the hydrologic behavior of four types of montane wetlands (ephemeral, intermediate, perennial, permanent wetlands) in the U. S. Pacific Northwest. The hybrid models captured observed wetland dynamics in many cases, though were less robust in others. We then used these models to a) hindcast historical wetland behavior in response to observed climate variability (1916–2010 or later) and classify wetland types, and b) project the impacts of climate change on montane wetlands using global climate model scenarios for the 2040s and 2080s (A1B emissions scenario). These future projections show that climate-induced changes to key driving variables (reduced snowpack, higher evapotranspiration, extended summer drought) will result in earlier and faster drawdown in Pacific Northwest montane wetlands, leading to systematic reductions in water levels, shortened wetland hydroperiods, and increased probability of drying. Intermediate hydroperiod wetlands are projected to experience the greatest changes. For the 2080s scenario, widespread conversion of intermediate wetlands to fast-drying ephemeral wetlands will likely reduce wetland habitat availability for many species. PMID:26331850 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JAMES..10..989L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JAMES..10..989L">Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei 2018-04-01 Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.2290W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.2290W">Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj 2016-04-01 In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMIN31A1751A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMIN31A1751A">Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B. 2015-12-01 Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1712788H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1712788H">Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi 2015-04-01 Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations from a variety of CMIP5 model ensembles. Here, we present results for the UK 2013/14 winter floods as proof of concept and we show validation and testing results that demonstrate the robustness of our method. We also revisit the record temperatures over Europe in 2014 and present a detailed analysis of this attribution exercise as it is one of the events to demonstrate that we can make a sensible statement of how the odds for such a year to occur have changed while it still unfolds. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.B33A0373V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.B33A0373V">Downscaling to the Climate Near the Ground: Measurements and Modeling Along the Macro-, Meso-, Topo-, and Microclimate Hierarchy</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> van de Ven, C.; Weiss, S. B. 2009-12-01 Most climate models are expressed at regional scales, with resolutions on the scales of kilometers. When used for ecological modeling, these climate models help explain only broad-scale trends, such as latitudinal and upslope migration of plants. However, more refined ecological models require down-scaled climate data at ecologically relevant spatial scales, and the goal of this presentation is to demonstrate robust downscaling methods. For example, in the White Mountains, eastern California, tree species, including bristlecone pine (Pinus longaeva) are seen moving not just upslope, but also sideways across aspects, and downslope into areas characterized by cold air drainage. Macroclimate in the White Mountains is semi-arid, residing in the rain shadow of the Sierra Nevada. Macroclimate is modified by mesoscale effects of mountain ranges, where climate becomes wetter and colder with elevation, the temperature decreasing according to the regionally and temporally-specific lapse rate. Local topography further modifies climate, where slope angle, aspect, and topographic position further impact the temperature at a given site. Finally, plants experience extremely localized microclimate, where surrounding vegetation provide differing degrees of shade. We measured and modeled topoclimate across the White Mountains using iButton Thermochron temperature data loggers during late summer in 2006 and 2008, and have documented effects of microclimatic temperature differences between sites in the open and shaded by shrubs. Starting with PRISM 800m data, we derived mesoscale lapse rates. Then, we calculated temperature differentials between each Thermochron and a long-term weather station in the middle of the range at Crooked Creek Valley. We modeled month-specific minimum temperature differentials by regressing the Thermochron-weather station minimum temperature differentials with various topographic parameters. Topographic position, the absolute value of topographic position, and slope combined to provide a very close fit (r2>0.9) to measured inversions of >8°C. Although topoclimatic maximum temperature models have been more elusive, regressions with degree hours greater than zero (DH>0) have been modeled with September insolation and slope (r2=0.7). In paired experiments, Thermochrons also recorded the temperature differences between the environment under sagebrush (Artemisia tridentata) and in the open, with an average minimum temperature difference of 2.1°C, and maximum temperature difference of 4.5°C. When we incorporate hourly weather station data, the strength of the inversion is weakened by wind, higher relative humidity, and cloudiness. This hierarchical modeling provides a template for downscaling climate and weather to ecologically relevant scales. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018NatCC...8..101C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018NatCC...8..101C">Challenges and opportunities for improved understanding of regional climate dynamics</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Collins, Matthew; Minobe, Shoshiro; Barreiro, Marcelo; Bordoni, Simona; Kaspi, Yohai; Kuwano-Yoshida, Akira; Keenlyside, Noel; Manzini, Elisa; O'Reilly, Christopher H.; Sutton, Rowan; Xie, Shang-Ping; Zolina, Olga 2018-01-01 Dynamical processes in the atmosphere and ocean are central to determining the large-scale drivers of regional climate change, yet their predictive understanding is poor. Here, we identify three frontline challenges in climate dynamics where significant progress can be made to inform adaptation: response of storms, blocks and jet streams to external forcing; basin-to-basin and tropical-extratropical teleconnections; and the development of non-linear predictive theory. We highlight opportunities and techniques for making immediate progress in these areas, which critically involve the development of high-resolution coupled model simulations, partial coupling or pacemaker experiments, as well as the development and use of dynamical metrics and exploitation of hierarchies of models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24955649','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24955649">Climate and atmosphere simulator for experiments on ecological systems in changing environments.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Verdier, Bruno; Jouanneau, Isabelle; Simonnet, Benoit; Rabin, Christian; Van Dooren, Tom J M; Delpierre, Nicolas; Clobert, Jean; Abbadie, Luc; Ferrière, Régis; Le Galliard, Jean-François 2014-01-01 Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active">24</li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active">25</li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B41G0532Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B41G0532Y">Integration of climatic water deficit and fine-scale physiography in process-based modeling of forest landscape resilience to large-scale tree mortality</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Yang, J.; Weisberg, P.; Dilts, T. 2016-12-01 Climate warming can lead to large-scale drought-induced tree mortality events and greatly affect forest landscape resilience. Climatic water deficit (CWD) and its physiographic variations provide a key mechanism in driving landscape dynamics in response to climate change. Although CWD has been successfully applied in niche-based species distribution models, its application in process-based forest landscape models is still scarce. Here we present a framework incorporating fine-scale influence of terrain on ecohydrology in modeling forest landscape dynamics. We integrated CWD with a forest landscape succession and disturbance model (LANDIS-II) to evaluate how tree species distribution might shift in response to different climate-fire scenarios across an elevation-aspect gradient in a semi-arid montane landscape of northeastern Nevada, USA. Our simulations indicated that drought-intolerant tree species such as quaking aspen could experience greatly reduced distributions in the more arid portions of their existing ranges due to water stress limitations under future climate warming scenarios. However, even at the most xeric portions of its range, aspen is likely to persist in certain environmental settings due to unique and often fine-scale combinations of resource availability, species interactions and disturbance regime. The modeling approach presented here allowed identification of these refugia. In addition, this approach helped quantify how the direction and magnitude of fire influences on species distribution would vary across topoclimatic gradients, as well as furthers our understanding on the role of environmental conditions, fire, and inter-specific competition in shaping potential responses of landscape resilience to climate change. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1068717','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1068717">The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Potter, Gerald L; Bader, David C; Riches, Michael Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session emphasized the scientific ideas that are the basis of PCMDI's success, summarizing their evolution and impact. Four speakers followed the various PCMDI-supported climate model intercomparison projects, beginning with early work on cloud representations in models, presented by Robert D. Cess (Distinguished Professor Emeritus, Stony Brook University), and then the latest Cloud Feedback Model Intercomparison Projects (CFMIPs) led by Sandrine Bony (Laboratoire de M'©t'©orologie Dynamique). Benjamin Santer (LLNL) presented a review of the climate change detection and attribution (D & A) work pioneered at PCMDI, and Gerald A. Meehl (NCAR) ended the day with a look toward the future of climate change research.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011HESSD...8.1541L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011HESSD...8.1541L">Spatial and temporal connections in groundwater contribution to evaporation</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lam, A.; Karssenberg, D.; van den Hurk, B. J. J. M.; Bierkens, M. F. P. 2011-02-01 In climate models, lateral terrestrial water fluxes are usually neglected. We estimated the contribution of vertical and lateral groundwater fluxes to the land surface water budget at a subcontinental scale, by modelling convergence of groundwater and surfacewater fluxes. We present a hydrological model of the entire Danube Basin at 5 km resolution, and use it to show the importance of groundwater for the surface climate. The contribution of groundwater to evaporation is significant, and can be upwards of 30% in summer. We show that this contribution is local by presenting the groundwater travel times and the magnitude of groundwater convergence. Throughout the Danube Basin the lateral fluxes of groundwater are negligible when modelling at this scale and resolution. Also, it is shown that the contribution of groundwater to evaporation has important temporal characteristics. An experiment with the same model shows that a wet episode influences groundwaters contribution to summer evaporation for several years afterwards. This indicates that modelling groundwater flow has the potential to augment the multi-year memory of climate models. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009IJAsB...8..207F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009IJAsB...8..207F">Climate modelling of mass-extinction events: a review</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Feulner, Georg 2009-07-01 Despite tremendous interest in the topic and decades of research, the origins of the major losses of biodiversity in the history of life on Earth remain elusive. A variety of possible causes for these mass-extinction events have been investigated, including impacts of asteroids or comets, large-scale volcanic eruptions, effects from changes in the distribution of continents caused by plate tectonics, and biological factors, to name but a few. Many of these suggested drivers involve or indeed require changes of Earth's climate, which then affect the biosphere of our planet, causing a global reduction in the diversity of biological species. It can be argued, therefore, that a detailed understanding of these climatic variations and their effects on ecosystems are prerequisites for a solution to the enigma of biological extinctions. Apart from investigations of the paleoclimate data of the time periods of mass extinctions, climate-modelling experiments should be able to shed some light on these dramatic events. Somewhat surprisingly, however, only a few comprehensive modelling studies of the climate changes associated with extinction events have been undertaken. These studies will be reviewed in this paper. Furthermore, the role of modelling in extinction research in general and suggestions for future research are discussed. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUSMOS24A..03P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUSMOS24A..03P">An overview of the South Atlantic Ocean climate variability and air-sea interaction processes</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Pezzi, L. P.; Parise, C. K.; Souza, R.; Gherardi, D. F.; Camargo, R.; Soares, H. C.; Silveira, I. 2013-05-01 The Ocean Modeling Group at the National Institute of Space Research (INPE) in Brazil has been developing several studies to understand the role of the Atlantic ocean on the South America climate. Studies include simulating the dynamics of the Tropical South-Atlantic Ocean and Southern Ocean. This is part of an ongoing international cooperation, in which Brazil participates with in situ observations, numerical modeling and statistical analyses. We have focused on the understanding of the impacts of extreme weather events over the Tropical South Atlantic Ocean and their prediction on different time-scales. One such study is aimed at analyzing the climate signal generated by imposing an extreme condition on the Antarctic sea ice and considering different complexities of the sea ice model. The influence of the Brazil-Malvinas Confluence (BMC) region on the marine atmospheric boundary layer (MABL) is also investigated through in situ data analysis of different cruises and numerical experiments with a regional numerical model. There is also an ongoing investigation that revealed basin-scale interannual climate variation with impacts on the Brazilian Large Marine Ecosystems (LMEs), which are strongly correlated with climate indices such as ENSO, AAO and PDO. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GPC...162..212D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GPC...162..212D">Future changes over the Himalayas: Maximum and minimum temperature</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Dimri, A. P.; Kumar, D.; Choudhary, A.; Maharana, P. 2018-03-01 An assessment of the projection of minimum and maximum air temperature over the Indian Himalayan region (IHR) from the COordinated Regional Climate Downscaling EXperiment- South Asia (hereafter, CORDEX-SA) regional climate model (RCM) experiments have been carried out under two different Representative Concentration Pathway (RCP) scenarios. The major aim of this study is to assess the probable future changes in the minimum and maximum climatology and its long-term trend under different RCPs along with the elevation dependent warming over the IHR. A number of statistical analysis such as changes in mean climatology, long-term spatial trend and probability distribution function are carried out to detect the signals of changes in climate. The study also tries to quantify the uncertainties associated with different model experiments and their ensemble in space, time and for different seasons. The model experiments and their ensemble show prominent cold bias over Himalayas for present climate. However, statistically significant higher warming rate (0.23-0.52 °C/decade) for both minimum and maximum air temperature (Tmin and Tmax) is observed for all the seasons under both RCPs. The rate of warming intensifies with the increase in the radiative forcing under a range of greenhouse gas scenarios starting from RCP4.5 to RCP8.5. In addition to this, a wide range of spatial variability and disagreements in the magnitude of trend between different models describes the uncertainty associated with the model projections and scenarios. The projected rate of increase of Tmin may destabilize the snow formation at the higher altitudes in the northern and western parts of Himalayan region, while rising trend of Tmax over southern flank may effectively melt more snow cover. Such combined effect of rising trend of Tmin and Tmax may pose a potential threat to the glacial deposits. The overall trend of Diurnal temperature range (DTR) portrays increasing trend across entire area with highest magnitude under RCP8.5. This higher rate of increase is imparted from the predominant rise of Tmax as compared to Tmin. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CliPa..12.2255R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CliPa..12.2255R">Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas 2016-12-01 Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.6114T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.6114T">Changes in future fire regimes under climate change</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Thonicke, Kirsten; von Bloh, Werner; Lutz, Julia; Knorr, Wolfgang; Wu, Minchao; Arneth, Almut 2013-04-01 Fires are expected to change under future climate change, climatic fire is is increasing due to increase in droughts and heat waves affecting vegetation productivity and ecosystem function. Vegetation productivity influences fuel production, but can also limit fire spread. Vegetation-fire models allow investigating the interaction between wildfires and vegetation dynamics, thus non-linear effects between changes in fuel composition and production on fire as well as changes in fire regimes on fire-related plant mortality and fuel combustion. Here we present results from simulation experiments, where the vegetation-fire models LPJmL-SPITFIRE and LPJ-GUESS are applied to future climate change scenarios from regional climate models in Europe and Northern Africa. Climate change impacts on fire regimes, vegetation dynamics and carbon fluxes are quantified and presented. New fire-prone regions are mapped and changes in fire regimes of ecosystems with a long-fire history are analyzed. Fuel limitation is likely to increase in Mediterranean-type ecosystems, indicating non-linear connection between increasing fire risk and fuel production. Increased warming in temperate ecosystems in Eastern Europe and continued fuel production leads to increases not only in climatic fire risk, but also area burnt and biomass burnt. This has implications for fire management, where adaptive capacity to this new vulnerability might be limited. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25432272','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25432272">Promoting an equitable and supportive school climate in high schools: the role of school organizational health and staff burnout.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Bottiani, Jessika H; Bradshaw, Catherine P; Mendelson, Tamar 2014-12-01 In response to persistent racial disparities in academic and behavioral outcomes between Black and White students, equitable school climate has drawn attention as a potential target for school reform. This study examined differences in Black and White students' experiences of school climate and explored whether indicators of school organizational health and staff burnout moderated differences in students' school experiences by race. Utilizing hierarchical linear modeling with a sample of 18,397 Black students (n=6228) and White students (n=12,169) and 2391 school staff in 53 schools, we found a consistent pattern of racial inequalities, such that Black students reported less positive experiences than White students across three indicators of school climate (caring γ=-0.08, p<.001; equity γ=-0.05, p=.007; and engagement γ=-0.05, p<.001). In addition, we found significant, positive associations between aggregated staff-report of school organizational health and student-reported school climate (e.g., staff affiliation and student-perceived equity, γ=0.07, p<.001). Surprisingly, a number of school organizational health indicators were more strongly associated with positive perceptions of school climate among White students than Black students, translating into greater racial disparities in perceived school climate at schools with greater organizational health (e.g., supportive leadership by race on student-perceived engagement, γ=-0.03, p=.042). We also found negative associations between staff-reported burnout and students' experience of equity, such that the racial gap was smaller in schools with high ratings of burnout (γ=0.04, p=.002). These findings have implications for educators and education researchers interested in promoting school social contexts that equitably support student engagement and success. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; ... 2017-04-28 A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient datamore » with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.5167R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.5167R">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; Ma, J.; Song, M.; Partridge, D. G.; Kirkevâg, A.; Leong, Y.; Hu, W. W.; Taylor, N. F.; Lambe, A.; Cerully, K.; Bougiatioti, A.; Liu, P.; Krejci, R.; Petäjä, T.; Percival, C.; Davidovits, P.; Worsnop, D. R.; Ekman, A. M. L.; Nenes, A.; Martin, S.; Jimenez, J. L.; Collins, D. R.; Topping, D. O.; Bertram, A. K.; Zuend, A.; Virtanen, A.; Riipinen, I. 2017-05-01 A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28781391','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28781391">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Rastak, N; Pajunoja, A; Acosta Navarro, J C; Ma, J; Song, M; Partridge, D G; Kirkevåg, A; Leong, Y; Hu, W W; Taylor, N F; Lambe, A; Cerully, K; Bougiatioti, A; Liu, P; Krejci, R; Petäjä, T; Percival, C; Davidovits, P; Worsnop, D R; Ekman, A M L; Nenes, A; Martin, S; Jimenez, J L; Collins, D R; Topping, D O; Bertram, A K; Zuend, A; Virtanen, A; Riipinen, I 2017-05-28 A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5518298','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5518298">Microphysical explanation of the RH‐dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C.; Ma, J.; Song, M.; Partridge, D. G.; Kirkevåg, A.; Leong, Y.; Hu, W. W.; Taylor, N. F.; Lambe, A.; Cerully, K.; Bougiatioti, A.; Liu, P.; Krejci, R.; Petäjä, T.; Percival, C.; Davidovits, P.; Worsnop, D. R.; Ekman, A. M. L.; Nenes, A.; Martin, S.; Jimenez, J. L.; Collins, D. R.; Topping, D.O.; Bertram, A. K.; Zuend, A.; Virtanen, A. 2017-01-01 Abstract A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH‐dependent SOA water‐uptake with solubility and phase separation; (2) show that laboratory data on IP‐ and MT‐SOA hygroscopicity are representative of ambient data with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single‐parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources. PMID:28781391 </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1358118-microphysical-explanation-rh-dependent-water-affinity-biogenic-organic-aerosol-its-importance-climate">Microphysical explanation of the RH-dependent water affinity of biogenic organic aerosol and its importance for climate</a> <a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a> Rastak, N.; Pajunoja, A.; Acosta Navarro, J. C. A large fraction of atmospheric organic aerosol (OA) originates from natural emissions that are oxidized in the atmosphere to form secondary organic aerosol (SOA). Isoprene (IP) and monoterpenes (MT) are the most important precursors of SOA originating from forests. The climate impacts from OA are currently estimated through parameterizations of water uptake that drastically simplify the complexity of OA. We combine laboratory experiments, thermodynamic modeling, field observations, and climate modeling to (1) explain the molecular mechanisms behind RH-dependent SOA water-uptake with solubility and phase separation; (2) show that laboratory data on IP- and MT-SOA hygroscopicity are representative of ambient datamore » with corresponding OA source profiles; and (3) demonstrate the sensitivity of the modeled aerosol climate effect to assumed OA water affinity. We conclude that the commonly used single-parameter hygroscopicity framework can introduce significant error when quantifying the climate effects of organic aerosol. The results highlight the need for better constraints on the overall global OA mass loadings and its molecular composition, including currently underexplored anthropogenic and marine OA sources.« less </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..253L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..253L">Analysis of anthropogenic contributions to record high Australian summer rainfall (2010-2012) using CMIP5 simulations</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Lewis, Sophie; Karoly, David 2013-04-01 Changes in extreme climate events pose significant challenges for both human and natural systems. Some climate extremes are likely to become "more frequent, more widespread and/or more intense during the 21st century" (Intergovernmental Panel on Climate Change, 2007) due to anthropogenic climate change. Particularly in Australia, El Niño-Southern Oscillation (ENSO) has a relationship to the relative frequency of temperature and precipitation extremes. In this study, we investigate the record high two-summer rainfall observed in Australia (2010-2011 and 2011-2012). This record rainfall occurred in association with a two year extended La Niña event and resulted in severe and extensive flooding. We examine simulated changes in seasonal-scale rainfall extremes in the Australian region in a suite of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). In particular, we utilise the novel CMIP5 detection and attribution historical experiments with various forcings (natural forcings only and greenhouse gas forcings only) to examine the impact of various anthropogenic forcings on seasonal-scale extreme rainfall across Australia. Using these standard detection and attribution experiments over the period of 1850 to 2005, we examine La Niña contributions to the 2-season record rainfall, as well as the longer-term climate change contribution to rainfall extremes. Was there an anthropogenic influence in the record high Australian summer rainfall over 2010 to 2012, and if so, how much influence? Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report on the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC53A0686K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC53A0686K">Projection of the change in future extremes over Japan using a cloud-resolving model: (2) Precipitation Extremes and the results of the NHM-1km experiments</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Kanada, S.; Nakano, M.; Nakamura, M.; Hayashi, S.; Kato, T.; Kurihara, K.; Sasaki, H.; Uchiyama, T.; Aranami, K.; Honda, Y.; Kitoh, A. 2008-12-01 In order to study changes in the regional climate in the vicinity of Japan during the summer rainy season due to global warming, experiments by a semi-cloud resolving non-hydrostatic model with a horizontal resolution of 5km (NHM-5km) have been conducted from June to October by nesting within the results of the 10-year time-integrated experiments using a hydrostatic atmospheric general circulation model with a horizontal grid of 20 km (AGCM-20km: TL959L60) for the present and future up to the year 2100. A non-hydrostatic model developed by the Japan Meteorological Agency (JMA) (JMA-NHM; Saito et al. 2001, 2006) was adopted. Detailed descriptions of the NHM-5km are shown by the poster of Nakano et al. Our results show that rainy days over most of the Japanese Islands will decrease in June and July and increase in August and September in the future climate. Especially, remarkable increases in intense precipitations such as larger than 150 - 300 mm/day are projected from the present to future climate. The 90th percentiles of regional largest values among maximum daily precipitations (R-MDPs) grow 156 to 207 mm/day in the present and future climates, respectively. It is well-known that the horizontal distribution of precipitation, especially the heavy rainfall in the vicinity of Japan, much depends on the topography. Therefore, higher resolution experiments by a cloud-resolving model with a horizontal resolution of 1km (NHM-1km) are one-way nested within the results of NHM-5km. The basic frame and design of the NHM-1km is the same as those of the NHM-5km, but the topography is finer and no cumulus parameterization is used in the NHM-1km experiments. The NHM-1km, which treats the convection and cloud microphysics explicitly, can represent not only horizontal distributions of rainfall in detail but also the 3-dimensional structures of meso-beta-scale convective systems (MCSs). Because of the limitation of computation resources, only heavy rainfall events that rank in top 10 % of all rainfall events are selected for the NHM-1km experiments (Heavy rainfall events are defined by R-MDPs > 156 and 207 mm/day for the present and future climates, respectively, from the results of the NHM-5km). Tentative comparisons between the results of the NHM-1km and NHM-1km experiments reveal that the NHM-1km can re-produce more detailed and realistic horizontal distributions of rainfall in many cases. (This study is supported by the Ministry of Education, Culture, Sports, Science and Technology under the framework of the KAKUSHIN program. Numerical simulations are performed in the Earth Simulator) </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A52B..03H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A52B..03H">Unexpected Results are Usually Wrong, but Often Interesting</a> <a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a> Huber, M. 2014-12-01 In climate modeling, an unexpected result is usually wrong, arising from some sort of mistake. Despite the fact that we all bemoan uncertainty in climate, the field is underlain by a robust, successful body of theory and any properly conducted modeling experiment is posed and conducted within that context. Consequently, if results from a complex climate model disagree with theory or from expectations from simpler models, much skepticism is in order. But, this exposes the fundamental tension of using complex, sophisticated models. If simple models and theory were perfect there would be no reason for complex models--the entire point of sophisticated models is to see if unexpected phenomena arise as emergent properties of the system. In this talk, I will step through some paleoclimate examples, drawn from my own work, of unexpected results that emerge from complex climate models arising from mistakes of two kinds. The first kind of mistake, is what I call a 'smart mistake'; it is an intentional incorporation of assumptions, boundary conditions, or physics that is in violation of theoretical or observational constraints. The second mistake, a 'dumb mistake', is just that, an unintentional violation. Analysis of such mistaken simulations provides some potentially novel and certainly interesting insights into what is possible and right in paleoclimate modeling by forcing the reexamination of well-held assumptions and theories. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/circ/1380/downloads/Chapter10.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/circ/1380/downloads/Chapter10.pdf">The Borderlands and climate change: Chapter 10 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science</a> <a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a> Fitzpatrick, Joan; Gray, Floyd; Dubiel, Russell; Langman, Jeff; Moring, J. Bruce; Norman, Laura M.; Page, William R.; Parcher, Jean W. 2013-01-01 The prediction of global climate change in response to both natural forces and human activity is one of the defining issues of our times. The unprecedented observational capacity of modern earth-orbiting satellites coupled with the development of robust computational representations (models) of the Earth’s weather and climate systems afford us the opportunity to observe and investigate how these systems work now, how they have worked in the past, and how they will work in the future when forced in specific ways. In the most recent report on global climate change by the Intergovernmental Panel on Climate Change (IPCC; Solomon and others, 2007), analyses using multiple climate models support recent observations that the Earth’s climate is changing in response to a combination of natural and human-induced causes. These changes will be significant in the United States–Mexican border region, where the process of climate change affects all of the Borderlands challenge themes discussed in the preceding chapters. The dual possibilities of both significantly-changed climate and increasing variability in climate make it challenging to take full measure of the potential effects because the Borderlands already experience a high degree of interannual variability and climatological extremes. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23902908','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23902908">Evolution under changing climates: climatic niche stasis despite rapid evolution in a non-native plant.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Alexander, Jake M 2013-09-22 A topic of great current interest is the capacity of populations to adapt genetically to rapidly changing climates, for example by evolving the timing of life-history events, but this is challenging to address experimentally. I use a plant invasion as a model system to tackle this question by combining molecular markers, a common garden experiment and climatic niche modelling. This approach reveals that non-native Lactuca serriola originates primarily from Europe, a climatic subset of its native range, with low rates of admixture from Asia. It has rapidly refilled its climatic niche in the new range, associated with the evolution of flowering phenology to produce clines along climate gradients that mirror those across the native range. Consequently, some non-native plants have evolved development times and grow under climates more extreme than those found in Europe, but not among populations from the native range as a whole. This suggests that many plant populations can adapt rapidly to changed climatic conditions that are already within the climatic niche space occupied by the species elsewhere in its range, but that evolution to conditions outside of this range is more difficult. These findings can also help to explain the prevalence of niche conservatism among non-native species. </li> <li> <a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23579833','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23579833">Soil moisture dynamics modeling considering multi-layer root zone.</a> <a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a> Kumar, R; Shankar, V; Jat, M K 2013-01-01 The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass. </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active">25</li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> </div> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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