Evaluating lossy data compression on climate simulation data within a large ensemble

DOE PAGES

Baker, Allison H.; Hammerling, Dorit M.; Mickelson, Sheri A.; ...

2016-12-07

High-resolution Earth system model simulations generate enormous data volumes, and retaining the data from these simulations often strains institutional storage resources. Further, these exceedingly large storage requirements negatively impact science objectives, for example, by forcing reductions in data output frequency, simulation length, or ensemble size. To lessen data volumes from the Community Earth System Model (CESM), we advocate the use of lossy data compression techniques. While lossy data compression does not exactly preserve the original data (as lossless compression does), lossy techniques have an advantage in terms of smaller storage requirements. To preserve the integrity of the scientific simulation data,more » the effects of lossy data compression on the original data should, at a minimum, not be statistically distinguishable from the natural variability of the climate system, and previous preliminary work with data from CESM has shown this goal to be attainable. However, to ultimately convince climate scientists that it is acceptable to use lossy data compression, we provide climate scientists with access to publicly available climate data that have undergone lossy data compression. In particular, we report on the results of a lossy data compression experiment with output from the CESM Large Ensemble (CESM-LE) Community Project, in which we challenge climate scientists to examine features of the data relevant to their interests, and attempt to identify which of the ensemble members have been compressed and reconstructed. We find that while detecting distinguishing features is certainly possible, the compression effects noticeable in these features are often unimportant or disappear in post-processing analyses. In addition, we perform several analyses that directly compare the original data to the reconstructed data to investigate the preservation, or lack thereof, of specific features critical to climate science. Overall, we conclude that applying lossy data compression to climate simulation data is both advantageous in terms of data reduction and generally acceptable in terms of effects on scientific results.« less

Evaluating lossy data compression on climate simulation data within a large ensemble

NASA Astrophysics Data System (ADS)

Baker, Allison H.; Hammerling, Dorit M.; Mickelson, Sheri A.; Xu, Haiying; Stolpe, Martin B.; Naveau, Phillipe; Sanderson, Ben; Ebert-Uphoff, Imme; Samarasinghe, Savini; De Simone, Francesco; Carbone, Francesco; Gencarelli, Christian N.; Dennis, John M.; Kay, Jennifer E.; Lindstrom, Peter

2016-12-01

High-resolution Earth system model simulations generate enormous data volumes, and retaining the data from these simulations often strains institutional storage resources. Further, these exceedingly large storage requirements negatively impact science objectives, for example, by forcing reductions in data output frequency, simulation length, or ensemble size. To lessen data volumes from the Community Earth System Model (CESM), we advocate the use of lossy data compression techniques. While lossy data compression does not exactly preserve the original data (as lossless compression does), lossy techniques have an advantage in terms of smaller storage requirements. To preserve the integrity of the scientific simulation data, the effects of lossy data compression on the original data should, at a minimum, not be statistically distinguishable from the natural variability of the climate system, and previous preliminary work with data from CESM has shown this goal to be attainable. However, to ultimately convince climate scientists that it is acceptable to use lossy data compression, we provide climate scientists with access to publicly available climate data that have undergone lossy data compression. In particular, we report on the results of a lossy data compression experiment with output from the CESM Large Ensemble (CESM-LE) Community Project, in which we challenge climate scientists to examine features of the data relevant to their interests, and attempt to identify which of the ensemble members have been compressed and reconstructed. We find that while detecting distinguishing features is certainly possible, the compression effects noticeable in these features are often unimportant or disappear in post-processing analyses. In addition, we perform several analyses that directly compare the original data to the reconstructed data to investigate the preservation, or lack thereof, of specific features critical to climate science. Overall, we conclude that applying lossy data compression to climate simulation data is both advantageous in terms of data reduction and generally acceptable in terms of effects on scientific results.

Evaluating lossy data compression on climate simulation data within a large ensemble

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

Baker, Allison H.; Hammerling, Dorit M.; Mickelson, Sheri A.

High-resolution Earth system model simulations generate enormous data volumes, and retaining the data from these simulations often strains institutional storage resources. Further, these exceedingly large storage requirements negatively impact science objectives, for example, by forcing reductions in data output frequency, simulation length, or ensemble size. To lessen data volumes from the Community Earth System Model (CESM), we advocate the use of lossy data compression techniques. While lossy data compression does not exactly preserve the original data (as lossless compression does), lossy techniques have an advantage in terms of smaller storage requirements. To preserve the integrity of the scientific simulation data,more » the effects of lossy data compression on the original data should, at a minimum, not be statistically distinguishable from the natural variability of the climate system, and previous preliminary work with data from CESM has shown this goal to be attainable. However, to ultimately convince climate scientists that it is acceptable to use lossy data compression, we provide climate scientists with access to publicly available climate data that have undergone lossy data compression. In particular, we report on the results of a lossy data compression experiment with output from the CESM Large Ensemble (CESM-LE) Community Project, in which we challenge climate scientists to examine features of the data relevant to their interests, and attempt to identify which of the ensemble members have been compressed and reconstructed. We find that while detecting distinguishing features is certainly possible, the compression effects noticeable in these features are often unimportant or disappear in post-processing analyses. In addition, we perform several analyses that directly compare the original data to the reconstructed data to investigate the preservation, or lack thereof, of specific features critical to climate science. Overall, we conclude that applying lossy data compression to climate simulation data is both advantageous in terms of data reduction and generally acceptable in terms of effects on scientific results.« less

GCM simulations of volcanic aerosol forcing. I - Climate changes induced by steady-state perturbations

NASA Technical Reports Server (NTRS)

Pollack, James B.; Rind, David; Lacis, Andrew; Hansen, James E.; Sato, Makiko; Ruedy, Reto

1993-01-01

The response of the climate system to a temporally and spatially constant amount of volcanic particles is simulated using a general circulation model (GCM). The optical depth of the aerosols is chosen so as to produce approximately the same amount of forcing as results from doubling the present CO2 content of the atmosphere and from the boundary conditions associated with the peak of the last ice age. The climate changes produced by long-term volcanic aerosol forcing are obtained by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. The simulations indicate that a significant cooling of the troposphere and surface can occur at times of closely spaced multiple sulfur-rich volcanic explosions that span time scales of decades to centuries. The steady-state climate response to volcanic forcing includes a large expansion of sea ice, especially in the Southern Hemisphere; a resultant large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature.

Visualization and Analysis of Climate Simulation Performance Data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Adamidis, Panagiotis; Behrens, Jörg

2015-04-01

Visualization is the key process of transforming abstract (scientific) data into a graphical representation, to aid in the understanding of the information hidden within the data. Climate simulation data sets are typically quite large, time varying, and consist of many different variables sampled on an underlying grid. A large variety of climate models - and sub models - exist to simulate various aspects of the climate system. Generally, one is mainly interested in the physical variables produced by the simulation runs, but model developers are also interested in performance data measured along with these simulations. Climate simulation models are carefully developed complex software systems, designed to run in parallel on large HPC systems. An important goal thereby is to utilize the entire hardware as efficiently as possible, that is, to distribute the workload as even as possible among the individual components. This is a very challenging task, and detailed performance data, such as timings, cache misses etc. have to be used to locate and understand performance problems in order to optimize the model implementation. Furthermore, the correlation of performance data to the processes of the application and the sub-domains of the decomposed underlying grid is vital when addressing communication and load imbalance issues. High resolution climate simulations are carried out on tens to hundreds of thousands of cores, thus yielding a vast amount of profiling data, which cannot be analyzed without appropriate visualization techniques. This PICO presentation displays and discusses the ICON simulation model, which is jointly developed by the Max Planck Institute for Meteorology and the German Weather Service and in partnership with DKRZ. The visualization and analysis of the models performance data allows us to optimize and fine tune the model, as well as to understand its execution on the HPC system. We show and discuss our workflow, as well as present new ideas and solutions that greatly aided our understanding. The software employed is based on Avizo Green, ParaView and SimVis, as well as own developed software extensions.

Evaluation and comparison of different RCMs simulations of the Mediterranean climate: a view on the impact of model resolution and Mediterranean sea coupling.

NASA Astrophysics Data System (ADS)

Panthou, Gérémy; Vrac, Mathieu; Drobinski, Philippe; Bastin, Sophie; Somot, Samuel; Li, Laurent

2015-04-01

As regularly stated by numerous authors, the Mediterranean climate is considered as one major climate 'hot spot'. At least, three reasons may explain this statement. First, this region is known for being regularly affected by extreme hydro-meteorological events (heavy precipitation and flash-floods during the autumn season; droughts and heat waves during spring and summer). Second, the vulnerability of populations in regard of these extreme events is expected to increase during the XXIst century (at least due to the projected population growth in this region). At last, Global Circulation Models project that this regional climate will be highly sensitive to climate change. Moreover, global warming is expected to intensify the hydrological cycle and thus to increase the frequency of extreme hydro-meteorological events. In order to propose adaptation strategies, the robust estimation of the future evolution of the Mediterranean climate and the associated extreme hydro-meteorological events (in terms of intensity/frequency) is of great relevance. However, these projections are characterized by large uncertainties. Many components of the simulation chain can explain these large uncertainties : (i) uncertainties concerning the emission scenario; (ii) climate model simulations suffer of parametrization errors and uncertainties concerning the initial state of the climate; and (iii) the additional uncertainties given by the (dynamical or statistical) downscaling techniques and the impact model. Narrowing (as fine as possible) these uncertainties is a major challenge of the actual climate research. One way for that is to reduce the uncertainties associated with each component. In this study, we are interested in evaluating the potential improvement of : (i) coupled RCM simulations (with the Mediterranean Sea) in comparison with atmosphere only (stand-alone) RCM simulations and (ii) RCM simulations at a finer resolution in comparison with larger resolution. For that, three different RCMs (WRF, ALADIN, LMDZ4) were run, forced by ERA-Interim reanalyses, within the MED-CORDEX experiment. For each RCM, different versions (coupled/stand-alone, high/low resolution) were realized. A large set of scores was developed and applied in order to evaluate the performances of these different RCMs simulations. These scores were applied for three variables (daily precipitation amount, mean daily air temperature and the dry spell lengths). A particular attention was given to the RCM capability to reproduce the seasonal and spatial pattern of extreme statistics. Results show that the differences between coupled and stand-alone RCMs are localized very near the Mediterranean sea and that the model resolution has a slight impact on the scores obtained. Globally, the main differences between the RCM simulations come from the RCM used. Keywords: Mediterranean climate, extreme hydro-meteorological events, RCM simulations, evaluation of climate simulations

Decadal climate prediction in the large ensemble limit

NASA Astrophysics Data System (ADS)

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.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

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.

Large-eddy simulation of subtropical cloud-topped boundary layers: 1. A forcing framework with closed surface energy balance

NASA Astrophysics Data System (ADS)

Tan, Zhihong; Schneider, Tapio; Teixeira, João.; Pressel, Kyle G.

2016-12-01

Large-eddy simulation (LES) of clouds has the potential to resolve a central question in climate dynamics, namely, how subtropical marine boundary layer (MBL) clouds respond to global warming. However, large-scale processes need to be prescribed or represented parameterically in the limited-area LES domains. It is important that the representation of large-scale processes satisfies constraints such as a closed energy balance in a manner that is realizable under climate change. For example, LES with fixed sea surface temperatures usually do not close the surface energy balance, potentially leading to spurious surface fluxes and cloud responses to climate change. Here a framework of forcing LES of subtropical MBL clouds is presented that enforces a closed surface energy balance by coupling atmospheric LES to an ocean mixed layer with a sea surface temperature (SST) that depends on radiative fluxes and sensible and latent heat fluxes at the surface. A variety of subtropical MBL cloud regimes (stratocumulus, cumulus, and stratocumulus over cumulus) are simulated successfully within this framework. However, unlike in conventional frameworks with fixed SST, feedbacks between cloud cover and SST arise, which can lead to sudden transitions between cloud regimes (e.g., stratocumulus to cumulus) as forcing parameters are varied. The simulations validate this framework for studies of MBL clouds and establish its usefulness for studies of how the clouds respond to climate change.

Changes of climate regimes during the last millennium and the twenty-first century simulated by the Community Earth System Model

NASA Astrophysics Data System (ADS)

Huang, Wei; Feng, Song; Liu, Chang; Chen, Jie; Chen, Jianhui; Chen, Fahu

2018-01-01

This study examines the shifts in terrestrial climate regimes using the Köppen-Trewartha (K-T) climate classification by analyzing the Community Earth System Model Last Millennium Ensemble (CESM-LME) simulations for the period 850-2005 and CESM Medium Ensemble (CESM-ME), CESM Large Ensemble (CESM-LE) and CESM with fixed aerosols Medium Ensemble (CESM-LE_FixA) simulations for the period 1920-2080. We compare K-T climate types from the Medieval Climate Anomaly (MCA) (950-1250) with the Little Ice Age (LIA) (1550-1850), from present day (PD) (1971-2000) with the last millennium (LM) (850-1850), and from the future (2050-2080) with the LM in order to place anthropogenic changes in the context of changes due to natural forcings occurring during the last millennium. For CESM-LME, we focused on the simulations with all forcings, though the impacts of individual forcings (e.g., solar activities, volcanic eruptions, greenhouse gases, aerosols and land use changes) were also analyzed. We found that the climate types changed slightly between the MCA and the LIA due to weak changes in temperature and precipitation. The climate type changes in PD relative to the last millennium have been largely driven by greenhouse gas-induced warming, but anthropogenic aerosols have also played an important role on regional scales. At the end of the twenty-first century, the anthropogenic forcing has a much greater effect on climate types than the PD. Following the reduction of aerosol emissions, the impact of greenhouse gases will further promote global warming in the future. Compared to precipitation, changes in climate types are dominated by greenhouse gas-induced warming. The large shift in climate types by the end of this century suggests possible wide-spread redistribution of surface vegetation and a significant change in species distributions.

Effects of global climate change on the US forest sector: response functions derived from a dynamic resource and market simulator.

Treesearch

Bruce A. McCarl; Darius M. Adams; Ralph J. Alig; Diana Burton; Chi-Chung. Chen

2000-01-01

A multiperiod, regional, mathematical programming economic model is used to evaluate the potential economic impacts of global climatic change on the US forest sector. A wide range of scenarios for the biological response of forests to climate change are developed, ranging from small to large changes in forest growth rates. These scenarios are simulated in the economic...

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

NASA Astrophysics Data System (ADS)

Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

2016-05-01

A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Climate change streamflow scenarios designed for critical period water resources planning studies

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

2003-04-01

Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the Pacific Northwest (PNW) region of the US, and the resulting streamflow scenarios will be made freely available on the internet for a large number of sites in the PNW to help defray the costs of including climate change information in other studies.

An increase in aerosol burden due to the land-sea warming contrast

NASA Astrophysics Data System (ADS)

Hassan, T.; Allen, R.; Randles, C. A.

2017-12-01

Climate models simulate an increase in most aerosol species in response to warming, particularly over the tropics and Northern Hemisphere midlatitudes. This increase in aerosol burden is related to a decrease in wet removal, primarily due to reduced large-scale precipitation. Here, we show that the increase in aerosol burden, and the decrease in large-scale precipitation, is related to a robust climate change phenomenon—the land/sea warming contrast. Idealized simulations with two state of the art climate models, the National Center for Atmospheric Research Community Atmosphere Model version 5 (NCAR CAM5) and the Geophysical Fluid Dynamics Laboratory Atmospheric Model 3 (GFDL AM3), show that muting the land-sea warming contrast negates the increase in aerosol burden under warming. This is related to smaller decreases in near-surface relative humidity over land, and in turn, smaller decreases in large-scale precipitation over land—especially in the NH midlatitudes. Furthermore, additional idealized simulations with an enhanced land/sea warming contrast lead to the opposite result—larger decreases in relative humidity over land, larger decreases in large-scale precipitation, and larger increases in aerosol burden. Our results, which relate the increase in aerosol burden to the robust climate projection of enhanced land warming, adds confidence that a warmer world will be associated with a larger aerosol burden.

Interactive Correlation Analysis and Visualization of Climate Data

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

Ma, Kwan-Liu

The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods formore » visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.« less

Large historical growth in global terrestrial gross primary production

DOE PAGES

Campbell, J. E.; Berry, J. A.; Seibt, U.; ...

2017-04-05

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less

Large historical growth in global terrestrial gross primary production

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

Campbell, J. E.; Berry, J. A.; Seibt, U.

Growth in terrestrial gross primary production (GPP) may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. In consequence, model estimates of terrestrial carbon storage and carbon cycle –climate feedbacks remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century based on long-term atmospheric carbonyl sulphide (COS) records derived from ice core, firn, and ambient air samples. Here, we interpret these records using a model that simulates changes in COS concentration due to changes in its sources and sinks, including amore » large sink that is related to GPP. We find that the COS record is most consistent with climate-carbon cycle model simulations that assume large GPP growth during the twentieth century (31% ± 5%; mean ± 95% confidence interval). Finally, while this COS analysis does not directly constrain estimates of future GPP growth it provides a global-scale benchmark for historical carbon cycle simulations.« less

Simulated influences of Lake Agassiz on the climate of central North America 11,000 years ago

USGS Publications Warehouse

Hostetler, S.W.; Bartlein, P.J.; Clark, P.U.; Small, E.E.; Solomon, A.M.

2000-01-01

Eleven thousand years ago, large lakes existed in central and eastern North America along the margin of the Laurentide Ice Sheet. The large-scale North American climate at this time has been simulated with atmospheric general circulation models, but these relatively coarse global models do not resolve potentially important features of the mesoscale circulation that arise from interactions among the atmosphere, ice sheet, and proglacial lakes. Here we present simulations of the climate of central and eastern North America 11,000 years ago with a high-resolution, regional climate model nested within a general circulation model. The simulated climate is in general agreement with that inferred from palaeoecological evidence. Our experiments indicate that through mesoscale atmospheric feedbacks, the annual delivery of moisture to the Laurentide Ice Sheet was diminished at times of a large, cold Lake Agassiz relative to periods of lower lake stands. The resulting changes in the mass balance of the ice sheet may have contributed to fluctuations of the ice margin, thus affecting the routing of fresh water to the North Atlantic Ocean. A retreating ice margin during periods of high lake level may have opened an outlet for discharge of Lake Agassiz into the North Atlantic. A subsequent advance of the ice margin due to greater moisture delivery associated with a low lake level could have dammed the outlet, thereby reducing discharge to the North Atlantic. These variations may have been decisive in causing the Younger Dryas cold even.

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

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.

The influence of large-scale wind power on global climate.

PubMed

Keith, David W; Decarolis, Joseph F; Denkenberger, David C; Lenschow, Donald H; Malyshev, Sergey L; Pacala, Stephen; Rasch, Philip J

2004-11-16

Large-scale use of wind power can alter local and global climate by extracting kinetic energy and altering turbulent transport in the atmospheric boundary layer. We report climate-model simulations that address the possible climatic impacts of wind power at regional to global scales by using two general circulation models and several parameterizations of the interaction of wind turbines with the boundary layer. We find that very large amounts of wind power can produce nonnegligible climatic change at continental scales. Although large-scale effects are observed, wind power has a negligible effect on global-mean surface temperature, and it would deliver enormous global benefits by reducing emissions of CO(2) and air pollutants. Our results may enable a comparison between the climate impacts due to wind power and the reduction in climatic impacts achieved by the substitution of wind for fossil fuels.

Evaluation of regional climate simulations for air quality modelling purposes

NASA Astrophysics Data System (ADS)

Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

2013-05-01

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Summary of results of January climate simulations with the GISS coarse-mesh model

NASA Technical Reports Server (NTRS)

Spar, J.; Cohen, C.; Wu, P.

1981-01-01

The large scale climates generated by extended runs of the model are relatively independent of the initial atmospheric conditions, if the first few months of each simulation are discarded. The perpetual January simulations with a specified SST field produced excessive snow accumulation over the continents of the Northern Hemisphere. Mass exchanges between the cold (warm) continents and the warm (cold) adjacent oceans produced significant surface pressure changes over the oceans as well as over the land. The effect of terrain and terrain elevation on the amount of precipitation was examined. The evaporation of continental moisture was calculated to cause large increases in precipitation over the continents.

Climate change effects on historical range and variability of two large landscapes in western Montana, USA

Treesearch

Robert E. Keane; Lisa M. Holsinger; Russell A. Parsons; Kathy Gray

2008-01-01

Quantifying the historical range and variability of landscape composition and structure using simulation modeling is becoming an important means of assessing current landscape condition and prioritizing landscapes for ecosystem restoration. However, most simulated time series are generated using static climate conditions which fail to account for the predicted major...

Development of a station based climate database for SWAT and APEX assessments in the U.S.

USDA-ARS?s Scientific Manuscript database

Water quality simulation models such as the Soil and Water Assessment Tool (SWAT) and Agricultural Policy EXtender (APEX) are widely used in the U.S. These models require large amounts of spatial and tabular data to simulate the natural world. Accurate and seamless daily climatic data are critical...

Wave climate and trends along the eastern Chukchi Arctic Alaska coast

USGS Publications Warehouse

Erikson, L.H.; Storlazzi, C.D.; Jensen, R.E.

2011-01-01

Due in large part to the difficulty of obtaining measurements in the Arctic, little is known about the wave climate along the coast of Arctic Alaska. In this study, numerical model simulations encompassing 40 years of wave hind-casts were used to assess mean and extreme wave conditions. Results indicate that the wave climate was strongly modulated by large-scale atmospheric circulation patterns and that mean and extreme wave heights and periods exhibited increasing trends in both the sea and swell frequency bands over the time-period studied (1954-2004). Model simulations also indicate that the upward trend was not due to a decrease in the minimum icepack extent. ?? 2011 ASCE.

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

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).

Convergence in France facing Big Data era and Exascale challenges for Climate Sciences

NASA Astrophysics Data System (ADS)

Denvil, Sébastien; Dufresne, Jean-Louis; Salas, David; Meurdesoif, Yann; Valcke, Sophie; Caubel, Arnaud; Foujols, Marie-Alice; Servonnat, Jérôme; Sénési, Stéphane; Derouillat, Julien; Voury, Pascal

2014-05-01

The presentation will introduce a french national project : CONVERGENCE that has been funded for four years. This project will tackle big data and computational challenges faced by climate modeling community in HPC context. Model simulations are central to the study of complex mechanisms and feedbacks in the climate system and to provide estimates of future and past climate changes. Recent trends in climate modelling are to add more physical components in the modelled system, increasing the resolution of each individual component and the more systematic use of large suites of simulations to address many scientific questions. Climate simulations may therefore differ in their initial state, parameter values, representation of physical processes, spatial resolution, model complexity, and degree of realism or degree of idealisation. In addition, there is a strong need for evaluating, improving and monitoring the performance of climate models using a large ensemble of diagnostics and better integration of model outputs and observational data. High performance computing is currently reaching the exascale and has the potential to produce this exponential increase of size and numbers of simulations. However, post-processing, analysis, and exploration of the generated data have stalled and there is a strong need for new tools to cope with the growing size and complexity of the underlying simulations and datasets. Exascale simulations require new scalable software tools to generate, manage and mine those simulations ,and data to extract the relevant information and to take the correct decision. The primary purpose of this project is to develop a platform capable of running large ensembles of simulations with a suite of models, to handle the complex and voluminous datasets generated, to facilitate the evaluation and validation of the models and the use of higher resolution models. We propose to gather interdisciplinary skills to design, using a component-based approach, a specific programming environment for scalable scientific simulations and analytics, integrating new and efficient ways of deploying and analysing the applications on High Performance Computing (HPC) system. CONVERGENCE, gathering HPC and informatics expertise that cuts across the individual partners and the broader HPC community, will allow the national climate community to leverage information technology (IT) innovations to address its specific needs. Our methodology consists in developing an ensemble of generic elements needed to run the French climate models with different grids and different resolution, ensuring efficient and reliable execution of these models, managing large volume and number of data and allowing analysis of the results and precise evaluation of the models. These elements include data structure definition and input-output (IO), code coupling and interpolation, as well as runtime and pre/post-processing environments. A common data and metadata structure will allow transferring consistent information between the various elements. All these generic elements will be open source and publicly available. The IPSL-CM and CNRM-CM climate models will make use of these elements that will constitute a national platform for climate modelling. This platform will be used, in its entirety, to optimise and tune the next version of the IPSL-CM model and to develop a global coupled climate model with a regional grid refinement. It will also be used, at least partially, to run ensembles of the CNRM-CM model at relatively high resolution and to run a very-high resolution prototype of this model. The climate models we developed are already involved in many international projects. For instance we participate to the CMIP (Coupled Model Intercomparison Project) project that is very demanding but has a high visibility: its results are widely used and are in particular synthesised in the IPCC (Intergovernmental Panel on Climate Change) assessment reports. The CONVERGENCE project will constitute an invaluable step for the French climate community to prepare and better contribute to the next phase of the CMIP project.

Climate change impacts on extreme events in the United States: an uncertainty analysis

EPA Science Inventory

Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in mean changes. As a result, the uncertainty in future changes ...

The CESM Large Ensemble Project: Inspiring New Ideas and Understanding

NASA Astrophysics Data System (ADS)

Kay, J. E.; Deser, C.

2016-12-01

While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.

Parameterization Interactions in Global Aquaplanet Simulations

NASA Astrophysics Data System (ADS)

Bhattacharya, Ritthik; Bordoni, Simona; Suselj, Kay; Teixeira, João.

2018-02-01

Global climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large-scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large-scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large-scale, convection, and cloud microphysics tendencies.

Application of regional climate models to the Indian winter monsoon over the western Himalayas.

PubMed

Dimri, A P; Yasunari, T; Wiltshire, A; Kumar, P; Mathison, C; Ridley, J; Jacob, D

2013-12-01

The Himalayan region is characterized by pronounced topographic heterogeneity and land use variability from west to east, with a large variation in regional climate patterns. Over the western part of the region, almost one-third of the annual precipitation is received in winter during cyclonic storms embedded in westerlies, known locally as the western disturbance. In the present paper, the regional winter climate over the western Himalayas is analyzed from simulations produced by two regional climate models (RCMs) forced with large-scale fields from ERA-Interim. The analysis was conducted by the composition of contrasting (wet and dry) winter precipitation years. The findings showed that RCMs could simulate the regional climate of the western Himalayas and represent the atmospheric circulation during extreme precipitation years in accordance with observations. The results suggest the important role of topography in moisture fluxes, transport and vertical flows. Dynamical downscaling with RCMs represented regional climates at the mountain or even event scale. However, uncertainties of precipitation scale and liquid-solid precipitation ratios within RCMs are still large for the purposes of hydrological and glaciological studies. Copyright © 2013 Elsevier B.V. All rights reserved.

Impact of climate change upon vector born diseases in Europe and Africa using ENSEMBLES Regional Climate Models

NASA Astrophysics Data System (ADS)

Caminade, Cyril; Morse, Andy

2010-05-01

Climate variability is an important component in determining the incidence of a number of diseases with significant human/animal health and socioeconomic impacts. The most important diseases affecting health are vector-borne, such as malaria, Rift Valley Fever and including those that are tick borne, with over 3 billion of the world population at risk. Malaria alone is responsible for at least one million deaths annually, with 80% of malaria deaths occurring in sub-Saharan Africa. The climate has a large impact upon the incidence of vector-borne diseases; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the environmental conditions. A large ensemble of regional climate model simulations has been produced within the ENSEMBLES project framework for both the European and African continent. This work will present recent progress in human and animal disease modelling, based on high resolution climate observations and regional climate simulations. Preliminary results will be given as an illustration, including the impact of climate change upon bluetongue (disease affecting the cattle) over Europe and upon malaria and Rift Valley Fever over Africa. Malaria scenarios based on RCM ensemble simulations have been produced for West Africa. These simulations have been carried out using the Liverpool Malaria Model. Future projections highlight that the malaria incidence decreases at the northern edge of the Sahel and that the epidemic belt is shifted southward in autumn. This could lead to significant public health problems in the future as the demography is expected to dramatically rise over Africa for the 21st century.

Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

NASA Astrophysics Data System (ADS)

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).

Multi-Scale Simulations of Past and Future Projections of Hydrology in Lake Tahoe Basin, California-Nevada (Invited)

NASA Astrophysics Data System (ADS)

Niswonger, R. G.; Huntington, J. L.; Dettinger, M. D.; Rajagopal, S.; Gardner, M.; Morton, C. G.; Reeves, D. M.; Pohll, G. M.

2013-12-01

Water resources in the Tahoe basin are susceptible to long-term climate change and extreme events because it is a middle-altitude, snow-dominated basin that experiences large inter-annual climate variations. Lake Tahoe provides critical water supply for its basin and downstream populations, but changes in water supply are obscured by complex climatic and hydrologic gradients across the high relief, geologically complex basin. An integrated surface and groundwater model of the Lake Tahoe basin has been developed using GSFLOW to assess the effects of climate change and extreme events on surface and groundwater resources. Key hydrologic mechanisms are identified with this model that explains recent changes in water resources of the region. Critical vulnerabilities of regional water-supplies and hazards also were explored. Maintaining a balance between (a) accurate representation of spatial features (e.g., geology, streams, and topography) and hydrologic response (i.e., groundwater, stream, lake, and wetland flows and storages), and (b) computational efficiency, is a necessity for the desired model applications. Potential climatic influences on water resources are analyzed here in simulations of long-term water-availability and flood responses to selected 100-year climate-model projections. GSFLOW is also used to simulate a scenario depicting an especially extreme storm event that was constructed from a combination of two historical atmospheric-river storm events as part of the USGS MultiHazards Demonstration Project. Historical simulated groundwater levels, streamflow, wetlands, and lake levels compare well with measured values for a 30-year historical simulation period. Results are consistent for both small and large model grid cell sizes, due to the model's ability to represent water table altitude, streams, and other hydrologic features at the sub-grid scale. Simulated hydrologic responses are affected by climate change, where less groundwater resources will be available during more frequent droughts. Simulated floods for the region indicate issues related to drainage in the developed areas around Lake Tahoe, and necessary dam releases that create downstream flood risks.

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less

Simulation and analysis of soil-water conditions in the Great Plains and adjacent areas, central United States, 1951-80

USGS Publications Warehouse

Dugan, Jack T.; Zelt, Ronald B.

2000-01-01

Ground-water recharge and consumptive-irrigation requirements in the Great Plains and adjacent areas largely depend upon an environment extrinsic to the ground-water system. This extrinsic environment, which includes climate, soils, and vegetation, determines the water demands of evapotranspiration, the availability of soil water to meet these demands, and the quantity of soil water remaining for potential ground-water recharge after these demands are met. The geographic extent of the Great Plains contributes to large regional differences among all elements composing the extrinsic environment, particularly the climatic factors. A soil-water simulation program, SWASP, which synthesizes selected climatic, soil, and vegetation factors, was used to simulate the regional soil-water conditions during 1951-80. The output from SWASP consists of several soil-water characteristics, including surface runoff, infiltration, consumptive water requirements, actual evapotranspiration, potential recharge or deep percolation under various conditions, consumptive irrigation requirements, and net fluxes from the ground-water system under irrigated conditions. Simulation results indicate that regional patterns of potential recharge, consumptive irrigation requirements, and net fluxes from the ground-water system under irrigated conditions are largely determined by evapotranspiration and precipitation. The local effects of soils and vegetation on potential recharge cause potential recharge to vary by more than 50 percent in some areas having similar climatic conditions.

Mean-state acceleration of cloud-resolving models and large eddy simulations

DOE PAGES

Jones, C. R.; Bretherton, C. S.; Pritchard, M. S.

2015-10-29

In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate themore » evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.« less

The Influence of the Green River Lake System on the Local Climate During the Early Eocene Period

NASA Astrophysics Data System (ADS)

Elguindi, N.; Thrasher, B.; Sloan, L. C.

2006-12-01

Several modeling efforts have attempted to reproduce the climate of the early Eocene North America. However when compared to proxy data, General Circulation Models (GCMs) tend to produce a large-scale cold-bias. Although higher resolution Regional Climate Models (RCMs) that are able to resolve many of the sub-GCM scale forcings improve this cold bias, RCMs are still unable to reproduce the warm climate of the Eocene. From geologic data, we know that the greater Green River and the Uinta basins were intermontane basins with a large lake system during portions of the Eocene. We speculate that the lack of presence of these lakes in previous modeling studies may explain part of the persistent cold-bias of GCMs and RCMs. In this study, we utilize a regional climate model coupled with a 1D-lake model in an attempt to reduce the uncertainties and biases associated with climate simulations over Eocene western North American. Specifically, we include the Green River Lake system in our RCM simulation and compare climates with and without lakes to proxy data.

Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate

NASA Astrophysics Data System (ADS)

Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.

2017-12-01

Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.

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

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of climate extremes and associated impacts. [1] http://www.climateprediction.net/weatherathome/

A conditional approach to determining the effect of anthropogenic climate change on very rare events.

NASA Astrophysics Data System (ADS)

Wehner, Michael; Pall, Pardeep; Zarzycki, Colin; Stone, Daithi

2016-04-01

Probabilistic extreme event attribution is especially difficult for weather events that are caused by extremely rare large-scale meteorological patterns. Traditional modeling techniques have involved using ensembles of climate models, either fully coupled or with prescribed ocean and sea ice. Ensemble sizes for the latter case ranges from several 100 to tens of thousand. However, even if the simulations are constrained by the observed ocean state, the requisite large-scale meteorological pattern may not occur frequently enough or even at all in free running climate model simulations. We present a method to ensure that simulated events similar to the observed event are modeled with enough fidelity that robust statistics can be determined given the large scale meteorological conditions. By initializing suitably constrained short term ensemble hindcasts of both the actual weather system and a counterfactual weather system where the human interference in the climate system is removed, the human contribution to the magnitude of the event can be determined. However, the change (if any) in the probability of an event of the observed magnitude is conditional not only on the state of the ocean/sea ice system but also on the prescribed initial conditions determined by the causal large scale meteorological pattern. We will discuss the implications of this technique through two examples; the 2013 Colorado flood and the 2014 Typhoon Haiyan.

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

Chen, Gang

Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less

Large-scale drivers of local precipitation extremes in convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kendon, Elizabeth J.; Roberts, Nigel M.; Fowler, Hayley J.; Blenkinsop, Stephen

2016-04-01

The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

The use of perturbed physics ensembles and emulation in palaeoclimate reconstruction (Invited)

NASA Astrophysics Data System (ADS)

Edwards, T. L.; Rougier, J.; Collins, M.

2010-12-01

Climate is a coherent process, with correlations and dependencies across space, time, and climate variables. However, reconstructions of palaeoclimate traditionally consider individual pieces of information independently, rather than making use of this covariance structure. Such reconstructions are at risk of being unphysical or at least implausible. Climate simulators such as General Circulation Models (GCMs), on the other hand, contain climate system theory in the form of dynamical equations describing physical processes, but are imperfect and computationally expensive. These two datasets - pointwise palaeoclimate reconstructions and climate simulator evaluations - contain complementary information, and a statistical synthesis can produce a palaeoclimate reconstruction that combines them while not ignoring their limitations. We use an ensemble of simulators with perturbed parameterisations, to capture the uncertainty about the simulator variant, and our method also accounts for structural uncertainty. The resulting reconstruction contains a full expression of climate uncertainty, not just pointwise but also jointly over locations. Such joint information is crucial in determining spatially extensive features such as isotherms, or the location of the tree-line. A second outcome of the statistical analysis is a refined distribution for the simulator parameters. In this way, information from palaeoclimate observations can be used directly in quantifying uncertainty in future climate projections. The main challenge is the expense of running a large scale climate simulator: each evaluation of an atmosphere-ocean GCM takes several months of computing time. The solution is to interpret the ensemble of evaluations within an 'emulator', which is a statistical model of the simulator. This technique has been used fruitfully in the statistical field of Computer Models for two decades, and has recently been applied in estimating uncertainty in future climate predictions in the UKCP09 (http://ukclimateprojections.defra.gov.uk). But only in the last couple of years has it developed to the point where it can be applied to large-scale spatial fields. We construct an emulator for the mid-Holocene (6000 calendar years BP) temperature anomaly over North America, at the resolution of our simulator (2.5° latitude by 3.75° longitude). This allows us to explore the behaviour of simulator variants that we could not afford to evaluate directly. We introduce the technique of 'co-emulation' of two versions of the climate simulator: the coupled atmosphere-ocean model HadCM3, and an equivalent with a simplified ocean, HadSM3. Running two different versions of a simulator is a powerful tool for increasing the information yield from a fixed budget of computer time, but the results must be combined statistically to account for the reduced fidelity of the quicker version. Emulators provide the appropriate framework.

Emerging Cyber Infrastructure for NASA's Large-Scale Climate Data Analytics

NASA Astrophysics Data System (ADS)

Duffy, D.; Spear, C.; Bowen, M. K.; Thompson, J. H.; Hu, F.; Yang, C. P.; Pierce, D.

2016-12-01

The resolution of NASA climate and weather simulations have grown dramatically over the past few years with the highest-fidelity models reaching down to 1.5 KM global resolutions. With each doubling of the resolution, the resulting data sets grow by a factor of eight in size. As the climate and weather models push the envelope even further, a new infrastructure to store data and provide large-scale data analytics is necessary. The NASA Center for Climate Simulation (NCCS) has deployed the Data Analytics Storage Service (DASS) that combines scalable storage with the ability to perform in-situ analytics. Within this system, large, commonly used data sets are stored in a POSIX file system (write once/read many); examples of data stored include Landsat, MERRA2, observing system simulation experiments, and high-resolution downscaled reanalysis. The total size of this repository is on the order of 15 petabytes of storage. In addition to the POSIX file system, the NCCS has deployed file system connectors to enable emerging analytics built on top of the Hadoop File System (HDFS) to run on the same storage servers within the DASS. Coupled with a custom spatiotemporal indexing approach, users can now run emerging analytical operations built on MapReduce and Spark on the same data files stored within the POSIX file system without having to make additional copies. This presentation will discuss the architecture of this system and present benchmark performance measurements from traditional TeraSort and Wordcount to large-scale climate analytical operations on NetCDF data.

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.

2014-12-01

We will demonstrate several interactive, computer-based simulations, games, and other interactive multimedia. These resources were developed for weather, climate, atmospheric science, and related Earth system science education. The materials were created by the UCAR Center for Science Education. These materials have been disseminated via our web site (SciEd.ucar.edu), webinars, online courses, teacher workshops, and large touchscreen displays in weather and Sun-Earth connections exhibits in NCAR's Mesa Lab facility in Boulder, Colorado. Our group has also assembled a web-based list of similar resources, especially simulations and games, from other sources that touch upon weather, climate, and atmospheric science topics. We'll briefly demonstrate this directory. More info available at: scied.ucar.edu/events/agu-2014-games-simulations-sessions

Future projections of total snowfall and heavy snowfall in Japan simulated by large ensemble regional climate simulations.

NASA Astrophysics Data System (ADS)

Kawase, H.; Sasaki, H.; Murata, A.; Nosaka, M.; Ito, R.; Dairaku, K.; Sasai, T.; Yamazaki, T.; Sugimoto, S.; Watanabe, S.; Fujita, M.; Kawazoe, S.; Okada, Y.; Ishii, M.; Mizuta, R.; Takayabu, I.

2017-12-01

We performed large ensemble climate experiments to investigate future changes in extreme weather events using Meteorological Research Institute-Atmospheric General Circulation Model (MRI-AGCM) with about 60 km grid spacing and Non-Hydrostatic Regional Climate Model with 20 km grid spacing (NHRCM20). The global climate simulations are prescribed by the past and future sea surface temperature (SST). Two future climate simulations are conducted so that the global-mean surface air temperature rise 2 K and 4 K from the pre-industrial period. The non-warming simulations are also conducted by MRI-AGCM and NHRCM20. We focus on the future changes in snowfall in Japan. In winter, the Sea of Japan coast experiences heavy snowfall due to East Asian winter monsoon. The cold and dry air from the continent obtains abundant moisture from the warm Sea of Japan, causing enormous amount of snowfall especially in the mountainous area. The NHRCM20 showed winter total snowfall decreases in the most parts of Japan. In contrast, extremely heavy daily snowfall could increase at mountainous areas in the Central Japan and Northern parts of Japan when strong cold air outbreak occurs and the convergence zone appears over the Sea of Japan. The warmer Sea of Japan in the future climate could supply more moisture than that in the present climate, indicating that the cumulus convections could be enhanced around the convergence zone in the Sea of Japan. However, the horizontal resolution of 20 km is not enough to resolve Japan`s complex topography. Therefore, dynamical downscaling with 5 km grid spacing (NHRCM05) is also conducted using NHRCM20. The NHRCM05 does a better job simulating the regional boundary of snowfall and shows more detailed changes in future snowfall characteristics. The future changes in total and extremely heavy snowfall depend on the regions, elevations, and synoptic conditions around Japan.

Regional projections of North Indian climate for adaptation studies.

PubMed

Mathison, Camilla; Wiltshire, Andrew; Dimri, A P; Falloon, Pete; Jacob, Daniela; Kumar, Pankaj; Moors, Eddy; Ridley, Jeff; Siderius, Christian; Stoffel, Markus; Yasunari, T

2013-12-01

Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes. Copyright © 2012 Elsevier B.V. All rights reserved.

Model Sensitivity to North Atlantic Freshwater Forcing at 8.2 Ka

NASA Technical Reports Server (NTRS)

Morrill, Carrie; Legrande, Allegra Nicole; Renssen, H.; Bakker, P.; Otto-Bliesner, B. L.

2013-01-01

We compared four simulations of the 8.2 ka event to assess climate model sensitivity and skill in responding to North Atlantic freshwater perturbations. All of the simulations used the same freshwater forcing, 2.5 Sv for one year, applied to either the Hudson Bay (northeastern Canada) or Labrador Sea (between Canada's Labrador coast and Greenland). This freshwater pulse induced a decadal-mean slowdown of 10-25%in the Atlantic Meridional Overturning Circulation (AMOC) of the models and caused a large-scale pattern of climate anomalies that matched proxy evidence for cooling in the Northern Hemisphere and a southward shift of the Intertropical Convergence Zone. The multi-model ensemble generated temperature anomalies that were just half as large as those from quantitative proxy reconstructions, however. Also, the duration of AMOC and climate anomalies in three of the simulations was only several decades, significantly shorter than the duration of approx.150 yr in the paleoclimate record. Possible reasons for these discrepancies include incorrect representation of the early Holocene climate and ocean state in the North Atlantic and uncertainties in the freshwater forcing estimates.

Mechanisms of elevation-dependent warming over complex terrain in high-resolution simulations of regional climate change

NASA Astrophysics Data System (ADS)

Minder, J. R.; Letcher, T.; Liu, C.

2016-12-01

Numerous observational and modeling studies have suggested that over mountainous terrain certain elevations can experience systematically enhanced rates of near-surface climate warming relative to the surrounding region, a phenomenon referred to as elevation-dependent warming (EDW). In many of these studies high-elevation locations were found to experience the fastest warming rates. A variety of physical mechanisms for EDW have been proposed but there is no consensus as to the dominant cause. We examine EDW in regional climate model (RCM) simulations with very high horizontal resolution (4-km horizontal grid). The simulation domain centers on the Rocky Mountains and intermountain west of the United States. Climate change simulations are conducted using the "pseudo global warming" framework to focus on the regional response to large-scale thermodynamic and radiative climate changes representative of mid-century anthropogenic global climate change. Substantial EDW is found in these simulations. Warming varies with elevation by up to 1°C depending on the season considered. The structure of EDW is only weakly sensitive to variations in horizontal grid spacing ranging from 4 to 36 km. The snow-albedo feedback (SAF) plays a major role in causing the simulated EDW. The elevation band of maximum warming varies seasonally, mostly following the margin of the seasonal snowpack where snow cover and albedo reductions are maximized under climate warming. Additional simulations where the SAF is artificially suppressed demonstrate that EDW variations of up to 0.6°C can be attributed to the SAF. Simulations with a suppressed SAF still exhibit EDW variations up to 0.8°C that must be explained by other mechanisms. This remaining EDW shows a near linear increase in warming with elevation in most months and does not appear to be inherited from the profile of large-scale free-tropospheric warming. Simple theoretical calculations suggest that the non-linear dependence of surface emission on temperature offers one promising mechanism. The role of water vapor and cloud feedbacks are also considered as alternative mechanisms.

Biome changes in Asia since the mid-Holocene - an analysis of different transient Earth system model simulations

NASA Astrophysics Data System (ADS)

Dallmeyer, Anne; Claussen, Martin; Ni, Jian; Cao, Xianyong; Wang, Yongbo; Fischer, Nils; Pfeiffer, Madlene; Jin, Liya; Khon, Vyacheslav; Wagner, Sebastian; Haberkorn, Kerstin; Herzschuh, Ulrike

2017-02-01

The large variety of atmospheric circulation systems affecting the eastern Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate-vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere-ocean(-vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions.In all simulations, substantial biome shifts during the last 6000 years are confined to the high northern latitudes and the monsoon-westerly wind transition zone, but the temporal evolution and amplitude of change strongly depend on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4° in the ensemble mean, ranging from 1.5 to 6° in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21 % during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert-steppe margin is shifted westward by 5° (1-9° in the individual simulations). The forest biomes are expanded north-westward by 2°, ranging from 0 to 4° in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north-central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear since the mid-Holocene.

How Unusual were Hurricane Harvey's Rains?

NASA Astrophysics Data System (ADS)

Emanuel, K.

2017-12-01

We apply an advanced technique for hurricane risk assessment to evaluate the probability of hurricane rainfall of Harvey's magnitude. The technique embeds a detailed computational hurricane model in the large-scale conditions represented by climate reanalyses and by climate models. We simulate 3700 hurricane events affecting the state of Texas, from each of three climate reanalyses spanning the period 1980-2016, and 2000 events from each of six climate models for each of two periods: the period 1981-2000 from historical simulations, and the period 2081-2100 from future simulations under Representative Concentration Pathway (RCP) 8.5. On the basis of these simulations, we estimate that hurricane rain of Harvey's magnitude in the state of Texas would have had an annual probability of 0.01 in the late twentieth century, and will have an annual probability of 0.18 by the end of this century, with remarkably small scatter among the six climate models downscaled. If the event frequency is changing linearly over time, this would yield an annual probability of 0.06 in 2017.

Greenland-Wide Seasonal Temperatures During the Last Deglaciation

NASA Astrophysics Data System (ADS)

Buizert, C.; Keisling, B. A.; Box, J. E.; He, F.; Carlson, A. E.; Sinclair, G.; DeConto, R. M.

2018-02-01

The sensitivity of the Greenland ice sheet to climate forcing is of key importance in assessing its contribution to past and future sea level rise. Surface mass loss occurs during summer, and accounting for temperature seasonality is critical in simulating ice sheet evolution and in interpreting glacial landforms and chronologies. Ice core records constrain the timing and magnitude of climate change but are largely limited to annual mean estimates from the ice sheet interior. Here we merge ice core reconstructions with transient climate model simulations to generate Greenland-wide and seasonally resolved surface air temperature fields during the last deglaciation. Greenland summer temperatures peak in the early Holocene, consistent with records of ice core melt layers. We perform deglacial Greenland ice sheet model simulations to demonstrate that accounting for realistic temperature seasonality decreases simulated glacial ice volume, expedites the deglacial margin retreat, mutes the impact of abrupt climate warming, and gives rise to a clear Holocene ice volume minimum.

Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

2010-12-01

There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

Robust Spring Drying in the Southwestern U.S. and Seasonal Migration of Wet/Dry Patterns in a Warmer Climate

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

Gao, Yang; Leung, Lai-Yung R.; Lu, Jian

2014-03-16

This study compares climate simulations over the United States produced by a regional climate model with the driving global climate simulations as well as a large multi-model ensemble of global climate simulations to investigate robust changes in water availability (precipitation (P) – evapotranspiration (E)). A robust spring dry signal across multiple models is identified in the Southwest that results from a decrease in P and an increase in E in the future. In the boreal winter and summer, the prominent changes in P – E are associated with a north – south dipole pattern, while in spring, the prominent changesmore » in P – E appear as an east – west dipole pattern. The progression of the north – south and east – west dipole patterns through the seasons manifests clearly as a seasonal “clockwise” migration of wet/dry patterns, which is shown to be a robust feature of water availability changes in the US consistent across regional and global climate simulations.« less

Drought in the Horn of Africa: attribution of a damaging and repeating extreme event

NASA Astrophysics Data System (ADS)

Marthews, Toby; Otto, Friederike; Mitchell, Daniel; Dadson, Simon; Jones, Richard

2015-04-01

We have applied detection and attribution techniques to the severe drought that hit the Horn of Africa in 2014. The short rains failed in late 2013 in Kenya, South Sudan, Somalia and southern Ethiopia, leading to a very dry growing season January to March 2014, and subsequently to the current drought in many agricultural areas of the sub-region. We have made use of the weather@home project, which uses publicly-volunteered distributed computing to provide a large ensemble of simulations sufficient to sample regional climate uncertainty. Based on this, we have estimated the occurrence rates of the kinds of the rare and extreme events implicated in this large-scale drought. From land surface model runs based on these ensemble simulations, we have estimated the impacts of climate anomalies during this period and therefore we can reliably identify some factors of the ongoing drought as attributable to human-induced climate change. The UNFCCC's Adaptation Fund is attempting to support projects that bring about an adaptation to "the adverse effects of climate change", but in order to formulate such projects we need a much clearer way to assess how much climate change is human-induced and how much is a consequence of climate anomalies and large-scale teleconnections, which can only be provided by robust attribution techniques.

Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.

PubMed

Braconnot, Pascale; Kageyama, Masa

2015-11-13

Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results. © 2015 The Author(s).

Impact of spectral nudging on the downscaling of tropical cyclones in regional climate simulations

NASA Astrophysics Data System (ADS)

Choi, Suk-Jin; Lee, Dong-Kyou

2016-06-01

This study investigated the simulations of three months of seasonal tropical cyclone (TC) activity over the western North Pacific using the Advanced Research WRF Model. In the control experiment (CTL), the TC frequency was considerably overestimated. Additionally, the tracks of some TCs tended to have larger radii of curvature and were shifted eastward. The large-scale environments of westerly monsoon flows and subtropical Pacific highs were unreasonably simulated. The overestimated frequency of TC formation was attributed to a strengthened westerly wind field in the southern quadrants of the TC center. In comparison with the experiment with the spectral nudging method, the strengthened wind speed was mainly modulated by large-scale flow that was greater than approximately 1000 km in the model domain. The spurious formation and undesirable tracks of TCs in the CTL were considerably improved by reproducing realistic large-scale atmospheric monsoon circulation with substantial adjustment between large-scale flow in the model domain and large-scale boundary forcing modified by the spectral nudging method. The realistic monsoon circulation took a vital role in simulating realistic TCs. It revealed that, in the downscaling from large-scale fields for regional climate simulations, scale interaction between model-generated regional features and forced large-scale fields should be considered, and spectral nudging is a desirable method in the downscaling method.

Effects of land use/land cover and climate changes on surface runoff in a semi-humid and semi-arid transition zone in northwest China

NASA Astrophysics Data System (ADS)

Yin, Jing; He, Fan; Jiu Xiong, Yu; Qiu, Guo Yu

2017-01-01

Water resources, which are considerably affected by land use/land cover (LULC) and climate changes, are a key limiting factor in highly vulnerable ecosystems in arid and semi-arid regions. The impacts of LULC and climate changes on water resources must be assessed in these areas. However, conflicting results regarding the effects of LULC and climate changes on runoff have been reported in relatively large basins, such as the Jinghe River basin (JRB), which is a typical catchment (> 45 000 km2) located in a semi-humid and arid transition zone on the central Loess Plateau, northwest China. In this study, we focused on quantifying both the combined and isolated impacts of LULC and climate changes on surface runoff. We hypothesized that under climatic warming and drying conditions, LULC changes, which are primarily caused by intensive human activities such as the Grain for Green Program, will considerably alter runoff in the JRB. The Soil and Water Assessment Tool (SWAT) was adopted to perform simulations. The simulated results indicated that although runoff increased very little between the 1970s and the 2000s due to the combined effects of LULC and climate changes, LULC and climate changes affected surface runoff differently in each decade, e.g., runoff increased with increased precipitation between the 1970s and the 1980s (precipitation contributed to 88 % of the runoff increase). Thereafter, runoff decreased and was increasingly influenced by LULC changes, which contributed to 44 % of the runoff changes between the 1980s and 1990s and 71 % of the runoff changes between the 1990s and 2000s. Our findings revealed that large-scale LULC under the Grain for Green Program has had an important effect on the hydrological cycle since the late 1990s. Additionally, the conflicting findings regarding the effects of LULC and climate changes on runoff in relatively large basins are likely caused by uncertainties in hydrological simulations.

Untangling climatic and autogenic signals in peat records

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andrew J.; Young, Dylan M.; Swindles, Graeme T.

2016-04-01

Raised bogs contain potentially valuable information about Holocene climate change. However, autogenic processes may disconnect peatland hydrological behaviour from climate, and overwrite and degrade climatic signals in peat records. How can genuine climate signals be separated from autogenic changes? What level of detail of climatic information should we expect to be able to recover from peat-based reconstructions? We used an updated version of the DigiBog model to simulate peatland development and response to reconstructed Holocene rainfall and temperature reconstructions. The model represents key processes that are influential in peatland development and climate signal preservation, and includes a network of feedbacks between peat accumulation, decomposition, hydraulic structure and hydrological processes. It also incorporates the effects of temperature upon evapotranspiration, plant (litter) productivity and peat decomposition. Negative feedbacks in the model cause simulated water-table depths and peat humification records to exhibit homeostatic recovery from prescribed changes in rainfall, chiefly through changes in drainage. However, the simulated bogs show less resilience to changes in temperature, which cause lasting alterations to peatland structure and function and may therefore be more readily detectable in peat records. The network of feedbacks represented in DigiBog also provide both high- and low-pass filters for climatic information, meaning that the fidelity with which climate signals are preserved in simulated peatlands is determined by both the magnitude and the rate of climate change. Large-magnitude climatic events of an intermediate frequency (i.e., multi-decadal to centennial) are best preserved in the simulated bogs. We found that simulated humification records are further degraded by a phenomenon known as secondary decomposition. Decomposition signals are consistently offset from the climatic events that generate them, and decomposition records of dry-wet-dry climate sequences appear to be particularly vulnerable to overwriting. Our findings have direct implications not only for the interpretation of peat-based records of past climates, but also for understanding the likely vulnerability of peatland ecosystems and carbon stocks to future climate change.

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles

NASA Astrophysics Data System (ADS)

Vergara-Temprado, Jesús; Miltenberger, Annette K.; Furtado, Kalli; Grosvenor, Daniel P.; Shipway, Ben J.; Hill, Adrian A.; Wilkinson, Jonathan M.; Field, Paul R.; Murray, Benjamin J.; Carslaw, Ken S.

2018-03-01

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions.

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles

PubMed Central

Miltenberger, Annette K.; Furtado, Kalli; Grosvenor, Daniel P.; Shipway, Ben J.; Hill, Adrian A.; Wilkinson, Jonathan M.; Field, Paul R.

2018-01-01

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions. PMID:29490918

iClimate: a climate data and analysis portal

NASA Astrophysics Data System (ADS)

Goodman, P. J.; Russell, J. L.; Merchant, N.; Miller, S. J.; Juneja, A.

2015-12-01

We will describe a new climate data and analysis portal called iClimate that facilitates direct comparisons between available climate observations and climate simulations. Modeled after the successful iPlant Collaborative Discovery Environment (www.iplantcollaborative.org) that allows plant scientists to trade and share environmental, physiological and genetic data and analyses, iClimate provides an easy-to-use platform for large-scale climate research, including the storage, sharing, automated preprocessing, analysis and high-end visualization of large and often disparate observational and model datasets. iClimate will promote data exploration and scientific discovery by providing: efficient and high-speed transfer of data from nodes around the globe (e.g. PCMDI and NASA); standardized and customized data/model metrics; efficient subsampling of datasets based on temporal period, geographical region or variable; and collaboration tools for sharing data, workflows, analysis results, and data visualizations with collaborators or with the community at large. We will present iClimate's capabilities, and demonstrate how it will simplify and enhance the ability to do basic or cutting-edge climate research by professionals, laypeople and students.

Large-scale tropospheric transport in the Chemistry-Climate Model Initiative (CCMI) simulations

NASA Astrophysics Data System (ADS)

Orbe, Clara; Yang, Huang; Waugh, Darryn W.; Zeng, Guang; Morgenstern, Olaf; Kinnison, Douglas E.; Lamarque, Jean-Francois; Tilmes, Simone; Plummer, David A.; Scinocca, John F.; Josse, Beatrice; Marecal, Virginie; Jöckel, Patrick; Oman, Luke D.; Strahan, Susan E.; Deushi, Makoto; Tanaka, Taichu Y.; Yoshida, Kohei; Akiyoshi, Hideharu; Yamashita, Yousuke; Stenke, Andreas; Revell, Laura; Sukhodolov, Timofei; Rozanov, Eugene; Pitari, Giovanni; Visioni, Daniele; Stone, Kane A.; Schofield, Robyn; Banerjee, Antara

2018-05-01

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

Determing Credibility of Regional Simulations of Future Climate

NASA Astrophysics Data System (ADS)

Mearns, L. O.

2009-12-01

Climate models have been evaluated or validated ever since they were first developed. Establishing that a climate model can reproduce (some) aspects of the current climate of the earth on various spatial and temporal scales has long been a standard procedure for providing confidence in the model's ability to simulate future climate. However, direct links between the successes and failures of models in reproducing the current climate with regard to what future climates the models simulate has been largely lacking. This is to say that the model evaluation process has been largely divorced from the projections of future climate that the models produce. This is evidenced in the separation in the Intergovernmental Panel on Climate Change (IPCC) WG1 report of the chapter on evaluation of models from the chapter on future climate projections. There has also been the assumption of 'one model, one vote, that is, that each model projection is given equal weight in any multi-model ensemble presentation of the projections of future climate. There have been various attempts at determing measures of credibility that would avoid the 'ultrademocratic' assumption of the IPCC. Simple distinctions between models were made by research such as in Giorgi and Mearns (2002), Tebaldi et al., (2005), and Greene et al., (2006). But the metrics used were rather simplistic. More ambitous means of discriminating among the quality of model simulations have been made through the production of complex multivariate metrics, but insufficent work has been produced to verify that the metrics successfully discriminate in meaningful ways. Indeed it has been suggested that we really don't know what a model must successfully model to establish confidence in its regional-scale projections (Gleckler et al., 2008). Perhaps a more process oriented regional expert judgment approach is needed to understand which errors in climate models really matter for the model's response to future forcing. Such an approach is being attempted in the North American Climate Change Assessment Program (NARCCAP) whereby multiple global models are used to drive multiple regional models for the current period and the mid-21st century over the continent. Progress in this endeavor will be reported.

Winter and summer simulations with the GLAS climate model

NASA Technical Reports Server (NTRS)

Shukla, J.; Straus, D.; Randall, D.; Sud, Y.; Marx, L.

1981-01-01

The GLAS climate model is a general circulation model based on the primitive equations in sigma coordinates on a global domain in the presence of orography. The model incorporates parameterizations of the effects of radiation, convection, large scale latent heat release, turbulent and boundary layer fluxes, and ground hydrology. Winter and summer simulations were carried out with this model, and the resulting data are compared to observations.

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.

2013-12-01

We will demonstrate several interactive, computer-based simulations, games, and other interactive multimedia. These resources were developed for weather, climate, atmospheric science, and related Earth system science education. The materials were created by education groups at NCAR/UCAR in Boulder, primarily Spark and the COMET Program. These materials have been disseminated via Spark's web site (spark.ucar.edu), webinars, online courses, teacher workshops, and large touchscreen displays in weather and Sun-Earth connections exhibits in NCAR's Mesa Lab facility. Spark has also assembled a web-based list of similar resources, especially simulations and games, from other sources that touch upon weather, climate, and atmospheric science topics. We'll briefly demonstrate this directory.

Games and Simulations for Climate, Weather and Earth Science Education

NASA Astrophysics Data System (ADS)

Russell, R. M.; Clark, S.

2015-12-01

We will demonstrate several interactive, computer-based simulations, games, and other interactive multimedia. These resources were developed for weather, climate, atmospheric science, and related Earth system science education. The materials were created by the UCAR Center for Science Education. These materials have been disseminated via our web site (SciEd.ucar.edu), webinars, online courses, teacher workshops, and large touchscreen displays in weather and Sun-Earth connections exhibits in NCAR's Mesa Lab facility in Boulder, Colorado. Our group has also assembled a web-based list of similar resources, especially simulations and games, from other sources that touch upon weather, climate, and atmospheric science topics. We'll briefly demonstrate this directory.

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

PubMed

Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

2014-01-01

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

DOE PAGES

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

2016-01-01

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

Eum, Hyung-Il; Gachon, Philippe; Laprise, René

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

West African Monsoon dynamics in idealized simulations: the competitive roles of SST warming and CO2

NASA Astrophysics Data System (ADS)

Gaetani, Marco; Flamant, Cyrille; Hourdin, Frederic; Bastin, Sophie; Braconnot, Pascale; Bony, Sandrine

2015-04-01

The West African Monsoon (WAM) is affected by large climate variability at different timescales, from interannual to multidecadal, with strong environmental and socio-economic impacts associated to climate-related rainfall variability, especially in the Sahelian belt. State-of-the-art coupled climate models still show poor ability in correctly simulating the WAM past variability and also a large spread is observed in future climate projections. In this work, the July-to-September (JAS) WAM variability in the period 1979-2008 is studied in AMIP-like simulations (SST-forced) from CMIP5. The individual roles of global SST warming and CO2 concentration increasing are investigated through idealized experiments simulating a 4K warmer SST and a 4x CO2 concentration, respectively. Results show a dry response in Sahel to SST warming, with dryer conditions over western Sahel. On the contrary, wet conditions are observed when CO2 is increased, with the strongest response over central-eastern Sahel. The precipitation changes are associated to modifications in the regional atmospheric circulation: dry (wet) conditions are associated with reduced (increased) convergence in the lower troposphere, a southward (northward) shift of the African Easterly Jet, and a weaker (stronger) Tropical Easterly Jet. The co-variability between global SST and WAM precipitation is also investigated, highlighting a reorganization of the main co-variability modes. Namely, in the 4xCO2 simulation the influence of Tropical Pacific is dominant, while it is reduced in the 4K simulation, which also shows an increased coupling with the eastern Pacific and the Indian Ocean. The above results suggest a competitive action of SST warming and CO2 increasing on the WAM climate variability, with opposite effects on precipitation. The combination of the observed positive and negative response in precipitation, with wet conditions in central-eastern Sahel and dry conditions in western Sahel, is consistent with the future precipitation trends over West Africa resulting from CMIP5 coupled simulations. It is argued that the large spread in CMIP5 future projections may be related to the weight given to SST warming and direct CO2 effect by individual models. The capability of climate models in reproducing the SST-precipitation relationship appears to be crucial in this respect.

An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

NASA Astrophysics Data System (ADS)

Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

2013-12-01

This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

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

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

Code modernization and modularization of APEX and SWAT watershed simulation models

USDA-ARS?s Scientific Manuscript database

SWAT (Soil and Water Assessment Tool) and APEX (Agricultural Policy / Environmental eXtender) are respectively large and small watershed simulation models derived from EPIC Environmental Policy Integrated Climate), a field-scale agroecology simulation model. All three models are coded in FORTRAN an...

Evolution of Precipitation Extremes in Three Large Ensembles of Climate Simulations - Impact of Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.

2017-12-01

Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.

Solar influence on climate during the past millennium: Results from transient simulations with the NCAR Climate System Model

PubMed Central

Ammann, Caspar M.; Joos, Fortunat; Schimel, David S.; Otto-Bliesner, Bette L.; Tomas, Robert A.

2007-01-01

The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century. PMID:17360418

Development of a database system for near-future climate change projections under the Japanese National Project SI-CAT

NASA Astrophysics Data System (ADS)

Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.

2017-12-01

Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017. Techniques of the database system for near-future climate change projections might be quite useful for simulation and observational data in other research fields. We report current status of development and some case studies of the database system for near-future climate change projections.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

Impact of Desiccation of Aral Sea on the Regional Climate of Central Asia Using WRF Model

NASA Astrophysics Data System (ADS)

Sharma, Ashish; Huang, Huei-Ping; Zavialov, Peter; Khan, Valentina

2018-01-01

This study explores the impacts of the desiccation of the Aral Sea and large-scale climate change on the regional climate of Central Asia in the post-1960 era. A series of climate downscaling experiments for the 1960's and 2000's decades were performed using the Weather Research and Forecast model at 12-km horizontal resolution. To quantify the impacts of the changing surface boundary condition, a set of simulations with an identical lateral boundary condition but different extents of the Aral Sea were performed. It was found that the desiccation of the Aral Sea leads to more snow (and less rain) as desiccated winter surface is relatively much colder than water surface. In summer, desiccation led to substantial warming over the Aral Sea. These impacts were largely confined to within the area covered by the former Aral Sea and its immediate vicinity, although desiccation of the Sea also led to minor cooling over the greater Central Asia in winter. A contrasting set of simulations with an identical surface boundary condition but different lateral boundary conditions produced more identifiable changes in regional climate over the greater Central Asia which was characterized by a warming trend in both winter and summer. Simulations also showed that while the desiccation of the Aral Sea has significant impacts on the local climate over the Sea, the climate over the greater Central Asia on inter-decadal time scale was more strongly influenced by the continental or global-scale climate change on that time scale.

A Coupled Regional Climate Simulator for the Gulf of St. Lawrence, Canada

NASA Astrophysics Data System (ADS)

Faucher, M.; Saucier, F.; Caya, D.

2003-12-01

The climate of Eastern Canada is characterized by atmosphere-ocean-ice interactions due to the closeness of the North Atlantic Ocean and the Labrador Sea. Also, there are three relatively large inner basins: the Gulf of St-Lawrence, the Hudson Bay / Hudson Strait / Foxe Basin system and the Great Lakes, influencing the evolution of weather systems and therefore the regional climate. These basins are characterized by irregular coastlines and variables sea-ice in winter, so that the interactions between the atmosphere and the ocean are more complex. There are coupled general circulation models (GCMs) that are available to study the climate of Eastern Canada, but their resolution (near 350km) is to low to resolve the details of the regional climate of this area and to provide valuable information for climate impact studies. The goal of this work is to develop a coupled regional climate simulator for Eastern Canada to study the climate and its variability, necessary to assess the future climate in a double CO2 situation. An off-line coupling strategy through the interacting fields is used to link the Canadian Regional Climate Model developed at the "Universite du Quebec a Montreal" (CRCM, Caya and Laprise 1999) to the Gulf of St. Lawrence ocean model developed at the "Institut Maurice-Lamontagne" (GOM, Saucier et al. 2002). This strategy involves running both simulators separately and alternatively, using variables from the other simulator to supply the needed forcing fields every day. We present the results of a first series of seasonal simulations performed with this system to show the ability of our climate simulator to reproduce the known characteristics of the regional circulation such as mesoscale oceanic features, fronts and sea-ice. The simulations were done for the period from December 1st, 1989 to March 31st, 1990. The results are compared with those of previous uncoupled runs (Faucher et al. 2003) and with observations.

Convection-Resolving Climate Change Simulations: Intensification of Heavy Hourly Precipitation Events

NASA Astrophysics Data System (ADS)

Ban, N.; Schmidli, J.; Schar, C.

2014-12-01

Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Schӓr (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478

The effect of changing wind forcing on Antarctic ice shelf melting in high-resolution, global sea ice-ocean simulations with the Accelerated Climate Model for Energy (ACME)

NASA Astrophysics Data System (ADS)

Asay-Davis, Xylar; Price, Stephen; Petersen, Mark; Wolfe, Jonathan

2017-04-01

The capability for simulating sub-ice shelf circulation and submarine melting and freezing has recently been added to the U.S. Department of Energy's Accelerated Climate Model for Energy (ACME). With this new capability, we use an eddy permitting ocean model to conduct two sets of simulations in the spirit of Spence et al. (GRL, 41, 2014), who demonstrate increased warm water upwelling along the Antarctic coast in response to poleward shifting and strengthening of Southern Ocean westerly winds. These characteristics, symptomatic of a positive Southern Annular Mode (SAM), are projected to continue into the 21st century under anthropogenic climate change (Fyfe et al., J. Clim., 20, 2007). In our first simulation, we force the climate model using the standard CORE interannual forcing dataset (Large and Yeager; Clim. Dyn., 33, 2009). In our second simulation, we force our climate model using an altered version of CORE interannual forcing, based on the latter half of the full time series, which we take as a proxy for a future climate state biased towards a positive SAM. We compare ocean model states and sub-ice shelf melt rates with observations, exploring sources of model biases as well as the effects of the two forcing scenarios.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Simulating climate and stable water isotopes during the Last Interglacial using a coupled climate-isotope model

NASA Astrophysics Data System (ADS)

Gierz, Paul; Werner, Martin; Lohmann, Gerrit

2017-09-01

Understanding the dynamics of warm climate states has gained increasing importance in the face of anthropogenic climate change, and while it is possible to simulate warm interglacial climates, these simulated results cannot be evaluated without the aid of geochemical proxies. One such proxy is δ18O, which allows for inference about both a climate state's hydrology and temperature. We utilize a stable water isotope equipped climate model to simulate three stages during the Last Interglacial (LIG), corresponding to 130, 125, and 120 kyr before present, using forcings for orbital configuration as well as greenhouse gases. We discover heterogeneous responses in the mean δ18O signal to the climate forcing, with large areas of depletion in the LIG δ18O signal over the tropical Atlantic, the Sahel, and the Indian subcontinent, and with enrichment over the Pacific and Arctic Oceans. While we find that the climatology mean relationship between δ18O and temperature remains stable during the LIG, we also discover that this relationship is not spatially consistent. Our results suggest that great care must be taken when comparing δ18O records of different paleoclimate archives with the results of climate models as both the qualitative and quantitative interpretation of δ18O variations as a proxy for past temperature changes may be problematic due to the complexity of the signals.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

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.

Can climate models be tuned to simulate the global mean absolute temperature correctly?

NASA Astrophysics Data System (ADS)

Duan, Q.; Shi, Y.; Gong, W.

2016-12-01

The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

Progress in fast, accurate multi-scale climate simulations

DOE PAGES

Collins, W. D.; Johansen, H.; Evans, K. J.; ...

2015-06-01

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enablingmore » improved accuracy and fidelity in simulation of dynamics and allowing more complete representations of climate features at the global scale. At the same time, partnerships with computer science teams have focused on taking advantage of evolving computer architectures such as many-core processors and GPUs. As a result, approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Multi-year global climatic effects of atmospheric dust from large bolide impacts

NASA Technical Reports Server (NTRS)

Thompson, Starley L.

1988-01-01

The global climatic effects of dust generated by the impact of a 10 km-diameter bolide was simulated using a one-dimensional (vertical only) globally-averaged climate model by Pollack et al. The goal of the simulation is to examine the regional climate effects, including the possibility of coastal refugia, generated by a global dust cloud in a model having realistic geographic resolution. The climate model assumes the instantaneous appearance of a global stratospheric dust cloud with initial optical depth of 10,000. The time history of optical depth decreases according to the detailed calculations of Pollack et al., reaching an optical depth of unity at day 160, and subsequently decreasing with an e-folding time of 1 year. The simulation is carried out for three years in order to examine the atmospheric effects and recovery over several seasons. The simulation does not include any effects of NOx, CO2, or wildfire smoke injections that may accompany the creation of the dust cloud. The global distribution of surface temperature changes, freezing events, precipitation and soil moisture effects and sea ice increases will be discussed.

Potential economic benefits of adapting agricultural production systems to future climate change

USGS Publications Warehouse

Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

2010-01-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Potential economic benefits of adapting agricultural production systems to future climate change.

PubMed

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Southern Hemisphere climate variability forced by Northern Hemisphere ice-sheet topography

NASA Astrophysics Data System (ADS)

Jones, T. R.; Roberts, W. H. G.; Steig, E. J.; Cuffey, K. M.; Markle, B. R.; White, J. W. C.

2018-02-01

The presence of large Northern Hemisphere ice sheets and reduced greenhouse gas concentrations during the Last Glacial Maximum fundamentally altered global ocean-atmosphere climate dynamics. Model simulations and palaeoclimate records suggest that glacial boundary conditions affected the El Niño-Southern Oscillation, a dominant source of short-term global climate variability. Yet little is known about changes in short-term climate variability at mid- to high latitudes. Here we use a high-resolution water isotope record from West Antarctica to demonstrate that interannual to decadal climate variability at high southern latitudes was almost twice as large at the Last Glacial Maximum as during the ensuing Holocene epoch (the past 11,700 years). Climate model simulations indicate that this increased variability reflects an increase in the teleconnection strength between the tropical Pacific and West Antarctica, owing to a shift in the mean location of tropical convection. This shift, in turn, can be attributed to the influence of topography and albedo of the North American ice sheets on atmospheric circulation. As the planet deglaciated, the largest and most abrupt decline in teleconnection strength occurred between approximately 16,000 years and 15,000 years ago, followed by a slower decline into the early Holocene.

FACE-IT. A Science Gateway for Food Security Research

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

Montella, Raffaele; Kelly, David; Xiong, Wei

Progress in sustainability science is hindered by challenges in creating and managing complex data acquisition, processing, simulation, post-processing, and intercomparison pipelines. To address these challenges, we developed the Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE-IT) for crop and climate impact assessments. This integrated data processing and simulation framework enables data ingest from geospatial archives; data regridding, aggregation, and other processing prior to simulation; large-scale climate impact simulations with agricultural and other models, leveraging high-performance and cloud computing; and post-processing to produce aggregated yields and ensemble variables needed for statistics, for model intercomparison, and to connectmore » biophysical models to global and regional economic models. FACE-IT leverages the capabilities of the Globus Galaxies platform to enable the capture of workflows and outputs in well-defined, reusable, and comparable forms. We describe FACE-IT and applications within the Agricultural Model Intercomparison and Improvement Project and the Center for Robust Decision-making on Climate and Energy Policy.« less

Reassessing Pliocene temperature gradients

NASA Astrophysics Data System (ADS)

Tierney, J. E.

2017-12-01

With CO2 levels similar to present, the Pliocene Warm Period (PWP) is one of our best analogs for climate change in the near future. Temperature proxy data from the PWP describe dramatically reduced zonal and meridional temperature gradients that have proved difficult to reproduce with climate model simulations. Recently, debate has emerged regarding the interpretation of the proxies used to infer Pliocene temperature gradients; these interpretations affect the magnitude of inferred change and the degree of inconsistency with existing climate model simulations of the PWP. Here, I revisit the issue using Bayesian proxy forward modeling and prediction that propagates known uncertainties in the Mg/Ca, UK'37, and TEX86 proxy systems. These new spatiotemporal predictions are quantitatively compared to PWP simulations to assess probabilistic agreement. Results show generally good agreement between existing Pliocene simulations from the PlioMIP ensemble and SST proxy data, suggesting that exotic changes in the ocean-atmosphere are not needed to explain the Pliocene climate state. Rather, the spatial changes in SST during the Pliocene are largely consistent with elevated CO2 forcing.

Different regional climatic drivers of Holocene large wildfires in boreal forests of northeastern America

NASA Astrophysics Data System (ADS)

Remy, Cécile C.; Hély, Christelle; Blarquez, Olivier; Magnan, Gabriel; Bergeron, Yves; Lavoie, Martin; Ali, Adam A.

2017-03-01

Global warming could increase climatic instability and large wildfire activity in circumboreal regions, potentially impairing both ecosystem functioning and human health. However, links between large wildfire events and climatic and/or meteorological conditions are still poorly understood, partly because few studies have covered a wide range of past climate-fire interactions. We compared palaeofire and simulated climatic data over the last 7000 years to assess causes of large wildfire events in three coniferous boreal forest regions in north-eastern Canada. These regions span an east-west cline, from a hilly region influenced by the Atlantic Ocean currently dominated by Picea mariana and Abies balsamea to a flatter continental region dominated by Picea mariana and Pinus banksiana. The largest wildfires occurred across the entire study zone between 3000 and 1000 cal. BP. In western and central continental regions these events were triggered by increases in both the fire-season length and summer/spring temperatures, while in the eastern region close to the ocean they were likely responses to hydrological (precipitation/evapotranspiration) variability. The impact of climatic drivers on fire size varied spatially across the study zone, confirming that regional climate dynamics could modulate effects of global climate change on wildfire regimes.

Simulation of the modern arctic climate by the NCAR CCM1

NASA Technical Reports Server (NTRS)

Bromwich, David H.; Tzeng, Ren-Yow; Parish, Thomas, R.

1994-01-01

The National Center of Atmospheric Research (NCAR) Community Climate Model Version 1 (CCM1's) simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much storm activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenland topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial circum-Greenland trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the model simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. The moisture budget analysis shows that the model's net annual precipitation (P-E) between 70 deg N and the North Pole is 6.6 times larger than the observations and the model transports six times more moisture into this region. The bias in the advection term is attributed to the positive moisture fixer scheme and the distorted flow pattern. However, the excessive moisture transport into the Arctic basin does not solely result from the advection term. The contribution by the moisture fixer is as large as from advection. By contrast, the semi-Lagrangian transport scheme used in the CCM2 significantly improves the moisture simulation for this region; however, globally the error is as serious as for the positive moisture fixer scheme. Finally, because the model has such serious problems in simulating the present arctic climate, its simulations of past and future climate change for this region are questionable.

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2011-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major reason for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. The central theme of this paper is to review past efforts and summarize our current understanding of the effect of aerosols on precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations will be presented. Specifically, this paper will address the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large-scale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions on aerosol - precipitation interactions are suggested.

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

Simulations of the Mid-Pliocene Warm Period Using Two Versions of the NASA-GISS ModelE2-R Coupled Model

NASA Technical Reports Server (NTRS)

Chandler, M. A.; Sohl, L. E.; Jonas, J. A.; Dowsett, H. J.; Kelley, M.

2013-01-01

The mid-Pliocene Warm Period (mPWP) bears many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change (IPCC, 2007). Both marine and terrestrial data point to high-latitude temperature amplification, including large decreases in sea ice and land ice, as well as expansion of warmer climate biomes into higher latitudes. Here we present our most recent simulations of the mid-Pliocene climate using the CMIP5 version of the NASAGISS Earth System Model (ModelE2-R). We describe the substantial impact associated with a recent correction made in the implementation of the Gent-McWilliams ocean mixing scheme (GM), which has a large effect on the simulation of ocean surface temperatures, particularly in the North Atlantic Ocean. The effect of this correction on the Pliocene climate results would not have been easily determined from examining its impact on the preindustrial runs alone, a useful demonstration of how the consequences of code improvements as seen in modern climate control runs do not necessarily portend the impacts in extreme climates.Both the GM-corrected and GM-uncorrected simulations were contributed to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. The corrected version yields results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene, especially the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea, which in the new simulation appears to be far more realistic than previously found with older versions of the GISS model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterisations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

Biomes computed from simulated climatologies

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

Claussen, M.; Esch, M.

1994-01-01

The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a differencemore » in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting chances in vegetation patterns due to a rapid climate change, the latter simulation to be taken as a prediction of chances in conditions favourable for the existence of certain biomes, not as a reduction of a future distribution of biomes. 15 refs., 8 figs., 2 tabs.« less

Evaluation of large-scale meteorological patterns associated with temperature extremes in the NARCCAP regional climate model simulations

NASA Astrophysics Data System (ADS)

Loikith, Paul C.; Waliser, Duane E.; Lee, Huikyo; Neelin, J. David; Lintner, Benjamin R.; McGinnis, Seth; Mearns, Linda O.; Kim, Jinwon

2015-12-01

Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of well-simulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts.

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

NASA Astrophysics Data System (ADS)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for better informed decision-making on adaptation strategies. References 1. Coumou, D. & Rahmstorf, S. A decade of extremes. Nature Clim. Change, 2, 491-496 (2012). 2. Rötter, R. P., Carter, T. R., Olesen, J. E. & Porter, J. R. Crop-climate models need an overhaul. Nature Clim. Change, 1, 175-177 (2011). 3. Asseng, S. et al., Uncertainty in simulating wheat yields under climate change. Nature Clim. Change. 10.1038/nclimate1916. (2013). 4. Porter, J.R., & Semenov, M., Crop responses to climatic variation . Trans. R. Soc. B., 360, 2021-2035 (2005). 5. Porter, J.R. & Christensen, S. Deconstructing crop processes and models via identities. Plant, Cell and Environment . doi: 10.1111/pce.12107 (2013). 6. Boogaard, H.L., van Diepen C.A., Rötter R.P., Cabrera J.M. & van Laar H.H. User's guide for the WOFOST 7.1 crop growth simulation model and Control Center 1.5, Alterra, Wageningen, The Netherlands. (1998) 7. Tao, F. & Zhang, Z. Climate change, wheat productivity and water use in the North China Plain: a new super-ensemble-based probabilistic projection. Agric. Forest Meteorol., 170, 146-165. (2013).

"The Effect of Alternative Representations of Lake ...

EPA Pesticide Factsheets

Lakes can play a significant role in regional climate, modulating inland extremes in temperature and enhancing precipitation. Representing these effects becomes more important as regional climate modeling (RCM) efforts focus on simulating smaller scales. When using the Weather Research and Forecasting (WRF) model to downscale future global climate model (GCM) projections into RCM simulations, model users typically must rely on the GCM to represent temperatures at all water points. However, GCMs have insufficient resolution to adequately represent even large inland lakes, such as the Great Lakes. Some interpolation methods, such as setting lake surface temperatures (LSTs) equal to the nearest water point, can result in inland lake temperatures being set from sea surface temperatures (SSTs) that are hundreds of km away. In other cases, a single point is tasked with representing multiple large, heterogeneous lakes. Similar consequences can result from interpolating ice from GCMs to inland lake points, resulting in lakes as large as Lake Superior freezing completely in the space of a single timestep. The use of a computationally-efficient inland lake model can improve RCM simulations where the input data is too coarse to adequately represent inland lake temperatures and ice (Gula and Peltier 2012). This study examines three scenarios under which ice and LSTs can be set within the WRF model when applied as an RCM to produce 2-year simulations at 12 km gri

Uncertainties in the Modelled CO2 Threshold for Antarctic Glaciation

NASA Technical Reports Server (NTRS)

Gasson, E.; Lunt, D. J.; DeConto, R.; Goldner, A.; Heinemann, M.; Huber, M.; LeGrande, A. N.; Pollard, D.; Sagoo, N.; Siddall, M.;

Present-day Antarctic climatology of the NCAR Community Climate Model Version 1

NASA Technical Reports Server (NTRS)

Tzeng, Ren-Yow; Bromwich, David H.; Parish, Thomas R.

1993-01-01

The ability of the NCAR Community Climate Model Version 1 (CCM1) with R 15 resolution to simulate the present-day climate of Antarctica was evaluated using the five-year seasonal cycle output produced by the CCM1 and comparing the model results with observed horizontal syntheses and point data. The results showed that the CCM1 with R 15 resolution can simulate to some extent the dynamics of Antarctic climate on the synoptic scale as well as some mesoscale features. The model can also simulate the phase and the amplitude of the annual and semiannual variation of the temperature, sea level pressure, and zonally averaged zonal (E-W) wind. The main shortcomings of the CCM1 model are associated with the model's anomalously large precipitation amounts at high latitudes, due to the tendency of the scheme to suppress negative moisture values.

Deforestation Induced Climate Change: Effects of Spatial Scale.

PubMed

Longobardi, Patrick; Montenegro, Alvaro; Beltrami, Hugo; Eby, Michael

2016-01-01

Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scal land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we examine the effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is simulated over low latitude deforested areas. Mid latitude SAT response is mixed. In all simulations deforested areas tend to become drier and have lower SAT, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation cause an increase in soil carbon large enough to produce a net decrease of atmospheric CO2. Our results reveal the complex interactions between soil carbon dynamics and other climate subsystems in the energy partition responses to land cover change.

Deforestation Induced Climate Change: Effects of Spatial Scale

PubMed Central

Longobardi, Patrick; Montenegro, Alvaro; Beltrami, Hugo; Eby, Michael

2016-01-01

Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scal land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we examine the effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is simulated over low latitude deforested areas. Mid latitude SAT response is mixed. In all simulations deforested areas tend to become drier and have lower SAT, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation cause an increase in soil carbon large enough to produce a net decrease of atmospheric CO2. Our results reveal the complex interactions between soil carbon dynamics and other climate subsystems in the energy partition responses to land cover change. PMID:27100667

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles.

PubMed

Vergara-Temprado, Jesús; Miltenberger, Annette K; Furtado, Kalli; Grosvenor, Daniel P; Shipway, Ben J; Hill, Adrian A; Wilkinson, Jonathan M; Field, Paul R; Murray, Benjamin J; Carslaw, Ken S

2018-03-13

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions. Copyright © 2018 the Author(s). Published by PNAS.

New Directions: Understanding Interactions of Air Quality and Climate Change at Regional Scales

EPA Science Inventory

The estimates of the short-lived climate forcers’ (SLCFs) impacts and mitigation effects on the radiation balance have large uncertainty because the current global model set-ups and simulations contain simplified parameterizations and do not completely cover the full range of air...

Interaction of ice sheets and climate during the past 800 000 years

NASA Astrophysics Data System (ADS)

Stap, L. B.; van de Wal, R. S. W.; de Boer, B.; Bintanja, R.; Lourens, L. J.

2014-12-01

During the Cenozoic, land ice and climate interacted on many different timescales. On long timescales, the effect of land ice on global climate and sea level is mainly set by large ice sheets in North America, Eurasia, Greenland and Antarctica. The climatic forcing of these ice sheets is largely determined by the meridional temperature profile resulting from radiation and greenhouse gas (GHG) forcing. As a response, the ice sheets cause an increase in albedo and surface elevation, which operates as a feedback in the climate system. To quantify the importance of these climate-land ice processes, a zonally averaged energy balance climate model is coupled to five one-dimensional ice sheet models, representing the major ice sheets. In this study, we focus on the transient simulation of the past 800 000 years, where a high-confidence CO2 record from ice core samples is used as input in combination with Milankovitch radiation changes. We obtain simulations of atmospheric temperature, ice volume and sea level that are in good agreement with recent proxy-data reconstructions. We examine long-term climate-ice-sheet interactions by a comparison of simulations with uncoupled and coupled ice sheets. We show that these interactions amplify global temperature anomalies by up to a factor of 2.6, and that they increase polar amplification by 94%. We demonstrate that, on these long timescales, the ice-albedo feedback has a larger and more global influence on the meridional atmospheric temperature profile than the surface-height-temperature feedback. Furthermore, we assess the influence of CO2 and insolation by performing runs with one or both of these variables held constant. We find that atmospheric temperature is controlled by a complex interaction of CO2 and insolation, and both variables serve as thresholds for northern hemispheric glaciation.

Knowledge Discovery from Climate Data using Graph-Based Methods

NASA Astrophysics Data System (ADS)

Steinhaeuser, K.

2012-04-01

Climate and Earth sciences have recently experienced a rapid transformation from a historically data-poor to a data-rich environment, thus bringing them into the realm of the Fourth Paradigm of scientific discovery - a term coined by the late Jim Gray (Hey et al. 2009), the other three being theory, experimentation and computer simulation. In particular, climate-related observations from remote sensors on satellites and weather radars, in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale simulations, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer a significant opportunity for advancing climate science and our understanding of the global climate system, yet current analysis techniques are not able to fully realize their potential benefits. We describe a class of computational approaches, specifically from the data mining and machine learning domains, which may be novel to the climate science domain and can assist in the analysis process. Computer scientists have developed spatial and spatio-temporal analysis techniques for a number of years now, and many of them may be applicable and/or adaptable to problems in climate science. We describe a large-scale, NSF-funded project aimed at addressing climate science question using computational analysis methods; team members include computer scientists, statisticians, and climate scientists from various backgrounds. One of the major thrusts is in the development of graph-based methods, and several illustrative examples of recent work in this area will be presented.

An 'Observational Large Ensemble' to compare observed and modeled temperature trend uncertainty due to internal variability.

NASA Astrophysics Data System (ADS)

Poppick, A. N.; McKinnon, K. A.; Dunn-Sigouin, E.; Deser, C.

2017-12-01

Initial condition climate model ensembles suggest that regional temperature trends can be highly variable on decadal timescales due to characteristics of internal climate variability. Accounting for trend uncertainty due to internal variability is therefore necessary to contextualize recent observed temperature changes. However, while the variability of trends in a climate model ensemble can be evaluated directly (as the spread across ensemble members), internal variability simulated by a climate model may be inconsistent with observations. Observation-based methods for assessing the role of internal variability on trend uncertainty are therefore required. Here, we use a statistical resampling approach to assess trend uncertainty due to internal variability in historical 50-year (1966-2015) winter near-surface air temperature trends over North America. We compare this estimate of trend uncertainty to simulated trend variability in the NCAR CESM1 Large Ensemble (LENS), finding that uncertainty in wintertime temperature trends over North America due to internal variability is largely overestimated by CESM1, on average by a factor of 32%. Our observation-based resampling approach is combined with the forced signal from LENS to produce an 'Observational Large Ensemble' (OLENS). The members of OLENS indicate a range of spatially coherent fields of temperature trends resulting from different sequences of internal variability consistent with observations. The smaller trend variability in OLENS suggests that uncertainty in the historical climate change signal in observations due to internal variability is less than suggested by LENS.

Global and Arctic climate engineering: numerical model studies.

PubMed

Caldeira, Ken; Wood, Lowell

2008-11-13

We perform numerical simulations of the atmosphere, sea ice and upper ocean to examine possible effects of diminishing incoming solar radiation, insolation, on the climate system. We simulate both global and Arctic climate engineering in idealized scenarios in which insolation is diminished above the top of the atmosphere. We consider the Arctic scenarios because climate change is manifesting most strongly there. Our results indicate that, while such simple insolation modulation is unlikely to perfectly reverse the effects of greenhouse gas warming, over a broad range of measures considering both temperature and water, an engineered high CO2 climate can be made much more similar to the low CO2 climate than would be a high CO2 climate in the absence of such engineering. At high latitudes, there is less sunlight deflected per unit albedo change but climate system feedbacks operate more powerfully there. These two effects largely cancel each other, making the global mean temperature response per unit top-of-atmosphere albedo change relatively insensitive to latitude. Implementing insolation modulation appears to be feasible.

High resolution global climate modelling; the UPSCALE project, a large simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.

2014-01-01

The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environmental Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the high performance computing center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE dataset. This dataset is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.

2014-08-01

The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environment Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

Impact of geoengineered aerosols on the troposphere and stratosphere

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

Tilmes, S.; Garcia, Rolando R.; Kinnison, Douglas E.

2009-06-27

A coupled chemistry climate model, the Whole Atmosphere Community Climate Model was used to perform a transient climate simulation to quantify the impact of geoengineered aerosols on atmospheric processes. In contrast to previous model studies, the impact on stratospheric chemistry, including heterogeneous chemistry in the polar regions, is considered in this simulation. In the geoengineering simulation, a constant stratospheric distribution of volcanic-sized, liquid sulfate aerosols is imposed in the period 2020–2050, corresponding to an injection of 2 Tg S/a. The aerosol cools the troposphere compared to a baseline simulation. Assuming an Intergovernmental Panel on Climate Change A1B emission scenario, globalmore » warming is delayed by about 40 years in the troposphere with respect to the baseline scenario. Large local changes of precipitation and temperatures may occur as a result of geoengineering. Comparison with simulations carried out with the Community Atmosphere Model indicates the importance of stratospheric processes for estimating the impact of stratospheric aerosols on the Earth’s climate. Changes in stratospheric dynamics and chemistry, especially faster heterogeneous reactions, reduce the recovery of the ozone layer in middle and high latitudes for the Southern Hemisphere. In the geoengineering case, the recovery of the Antarctic ozone hole is delayed by about 30 years on the basis of this model simulation. For the Northern Hemisphere, a onefold to twofold increase of the chemical ozone depletion occurs owing to a simulated stronger polar vortex and colder temperatures compared to the baseline simulation, in agreement with observational estimates.« less

A Review on Regional Convection-Permitting Climate Modeling: Demonstrations, Prospects, and Challenges

NASA Astrophysics Data System (ADS)

Prein, A. F.; Langhans, W.; Fosser, G.; Ferrone, A.; Ban, N.; Goergen, K.; Keller, M.; Tölle, M.; Gutjahr, O.; Feser, F.; Brisson, E.; Kollet, S. J.; Schmidli, J.; Van Lipzig, N. P. M.; Leung, L. R.

2015-12-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. We aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Past climates primary productivity changes in the Indian Ocean

NASA Astrophysics Data System (ADS)

Le Mézo, P. K.; Kageyama, M.; Bopp, L.; Beaufort, L.; Braconnot, P.; Bassinot, F. C.

2016-02-01

Organic climate recorders, e.g., coccolithophorids and foraminifera, are widely used to reconstruct past climate conditions, such as the Indian monsoon intensity and variability, since they are sensitive to climate-induced fluctuations of their environment. In the Indian Ocean, it is commonly accepted that a stronger summer monsoon will enhance productivity in the Arabian Sea and therefore the amount of organisms in a sediment core should reflect monsoon intensity. In this study, we use the coupled Earth System Model IPSLCM5A, which has a biogeochemical component PISCES that simulates primary production. We use 8 climate simulations of the IPSL-CM5A model, from -72kyr BP climate conditions to a preindustrial state. Our simulations have different orbital forcing (precession, obliquity and eccentricity), greenhouse gas concentrations as well as different ice sheet covers. The objective of this work is to characterize the mechanisms behind the changes in primary productivity between the different time periods. Our model shows that in climates where monsoon is enhanced (due to changes in precession) we do not necessarily see an increase in summer productivity in the Arabian Sea, and inversely. It seems that the glacial-interglacial state of the simulation is important in driving productivity changes in this region of the world. We try to explain the changes in productivity in the Arabian Sea with the local climate and then to link the changes in local climate to large scale atmospheric forcing and commonly used Indian monsoon definitions.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges.

PubMed

Prein, Andreas F; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P M; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

NASA Astrophysics Data System (ADS)

Prein, Andreas F.; Langhans, Wolfgang; Fosser, Giorgia; Ferrone, Andrew; Ban, Nikolina; Goergen, Klaus; Keller, Michael; Tölle, Merja; Gutjahr, Oliver; Feser, Frauke; Brisson, Erwan; Kollet, Stefan; Schmidli, Juerg; van Lipzig, Nicole P. M.; Leung, Ruby

2015-06-01

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.; Dey, Rima

2017-01-01

We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.

Forecasting European cold waves based on subsampling strategies of CMIP5 and Euro-CORDEX ensembles

NASA Astrophysics Data System (ADS)

Cordero-Llana, Laura; Braconnot, Pascale; Vautard, Robert; Vrac, Mathieu; Jezequel, Aglae

2016-04-01

Forecasting future extreme events under the present changing climate represents a difficult task. Currently there are a large number of ensembles of simulations for climate projections that take in account different models and scenarios. However, there is a need for reducing the size of the ensemble to make the interpretation of these simulations more manageable for impact studies or climate risk assessment. This can be achieved by developing subsampling strategies to identify a limited number of simulations that best represent the ensemble. In this study, cold waves are chosen to test different approaches for subsampling available simulations. The definition of cold waves depends on the criteria used, but they are generally defined using a minimum temperature threshold, the duration of the cold spell as well as their geographical extend. These climate indicators are not universal, highlighting the difficulty of directly comparing different studies. As part of the of the CLIPC European project, we use daily surface temperature data obtained from CMIP5 outputs as well as Euro-CORDEX simulations to predict future cold waves events in Europe. From these simulations a clustering method is applied to minimise the number of ensembles required. Furthermore, we analyse the different uncertainties that arise from the different model characteristics and definitions of climate indicators. Finally, we will test if the same subsampling strategy can be used for different climate indicators. This will facilitate the use of the subsampling results for a wide number of impact assessment studies.

Evaluating synoptic systems in the CMIP5 climate models over the Australian region

NASA Astrophysics Data System (ADS)

Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

2016-10-01

Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

A new climate modeling framework for convection-resolving simulation at continental scale

NASA Astrophysics Data System (ADS)

Charpilloz, Christophe; di Girolamo, Salvatore; Arteaga, Andrea; Fuhrer, Oliver; Hoefler, Torsten; Schulthess, Thomas; Schär, Christoph

2017-04-01

Major uncertainties remain in our understanding of the processes that govern the water cycle in a changing climate and their representation in weather and climate models. Of particular concern are heavy precipitation events of convective origin (thunderstorms and rain showers). The aim of the crCLIM project [1] is to propose a new climate modeling framework that alleviates the I/O-bottleneck in large-scale, convection-resolving climate simulations and thus to enable new analysis techniques for climate scientists. Due to the large computational costs, convection-resolving simulations are currently restricted to small computational domains or very short time scales, unless the largest available supercomputers system such as hybrid CPU-GPU architectures are used [3]. Hence, the COSMO model has been adapted to run on these architectures for research and production purposes [2]. However, the amount of generated data also increases and storing this data becomes infeasible making the analysis of simulations results impractical. To circumvent this problem and enable high-resolution models in climate we propose a data-virtualization layer (DVL) that re-runs simulations on demand and transparently manages the data for the analysis, that means we trade off computational effort (time) for storage (space). This approach also requires a bit-reproducible version of the COSMO model that produces identical results on different architectures (CPUs and GPUs) [4] that will be coupled with a performance model in order enable optimal re-runs depending on requirements of the re-run and available resources. In this contribution, we discuss the strategy to develop the DVL, a first performance model, the challenge of bit-reproducibility and the first results of the crCLIM project. [1] http://www.c2sm.ethz.ch/research/crCLIM.html [2] O. Fuhrer, C. Osuna, X. Lapillonne, T. Gysi, M. Bianco, and T. Schulthess. "Towards gpu-accelerated operational weather forecasting." In The GPU Technology Conference, GTC. 2013. [3] D. Leutwyler, O. Fuhrer, X. Lapillonne, D. Lüthi, and C. Schär. "Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19." Geoscientific Model Development 9, no. 9 (2016): 3393. [4] A. Arteaga, O. Fuhrer, and T. Hoefler. "Designing bit-reproducible portable high-performance applications." In Parallel and Distributed Processing Symposium, 2014 IEEE 28th International, pp. 1235-1244. IEEE, 2014.

The World Climate Exercise: Is (Simulated) Experience Our Best Teacher?

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer

2018-02-01

Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.

Vegetation-induced warming of high-latitude regions during the Late Cretaceous period

NASA Astrophysics Data System (ADS)

Otto-Bliesner, Bette L.; Upchurch, Garland R.

1997-02-01

Modelling studies of pre-Quaternary (>2 million years ago) climate implicate atmospheric carbon dioxide concentrations1, land elevation2 and land-sea distribution3-5 as important factors influencing global climate change over geological timescales. But during times of global warmth, such as the Cretaceous period and Eocene epoch, there are large discrepancies between model simulations of high-latitude and continental-interior temperatures and those indicated by palaeotemperature records6,7. Here we use a global climate model for the latest Cretaceous (66 million years ago) to examine the role played by high- and middle-latitude forests in surface temperature regulation. In our simulations, this forest vegetation warms the global climate by 2.2 °C. The low-albedo deciduous forests cause high-latitude land areas to warm, which then transfer more heat to adjacent oceans, thus delaying sea-ice formation and increasing winter temperatures over coastal land. Overall, the inclusion of some of the physical and physiological climate feedback effects of high-latitude forest vegetation in our simulations reduces the existing discrepancies between observed and modelled climates of the latest Cretaceous, suggesting that these forests may have made an important contribution to climate regulation during periods of global warmth.

Role of Atmospheric Chemistry in the Climate Impacts of Stratospheric Volcanic Injections

NASA Technical Reports Server (NTRS)

Legrande, Allegra N.; Tsigaridis, Kostas; Bauer, Susanne E.

2016-01-01

The climate impact of a volcanic eruption is known to be dependent on the size, location and timing of the eruption. However, the chemistry and composition of the volcanic plume also control its impact on climate. It is not just sulfur dioxide gas, but also the coincident emissions of water, halogens and ash that influence the radiative and climate forcing of an eruption. Improvements in the capability of models to capture aerosol microphysics, and the inclusion of chemistry and aerosol microphysics modules in Earth system models, allow us to evaluate the interaction of composition and chemistry within volcanic plumes in a new way. These modeling efforts also illustrate the role of water vapor in controlling the chemical evolution, and hence climate impacts, of the plume. A growing realization of the importance of the chemical composition of volcanic plumes is leading to a more sophisticated and realistic representation of volcanic forcing in climate simulations, which in turn aids in reconciling simulations and proxy reconstructions of the climate impacts of past volcanic eruptions. More sophisticated simulations are expected to help, eventually, with predictions of the impact on the Earth system of any future large volcanic eruptions.

The causality analysis of climate change and large-scale human crisis

PubMed Central

Zhang, David D.; Lee, Harry F.; Wang, Cong; Li, Baosheng; Pei, Qing; Zhang, Jane; An, Yulun

2011-01-01

Recent studies have shown strong temporal correlations between past climate changes and societal crises. However, the specific causal mechanisms underlying this relation have not been addressed. We explored quantitative responses of 14 fine-grained agro-ecological, socioeconomic, and demographic variables to climate fluctuations from A.D. 1500–1800 in Europe. Results show that cooling from A.D. 1560–1660 caused successive agro-ecological, socioeconomic, and demographic catastrophes, leading to the General Crisis of the Seventeenth Century. We identified a set of causal linkages between climate change and human crisis. Using temperature data and climate-driven economic variables, we simulated the alternation of defined “golden” and “dark” ages in Europe and the Northern Hemisphere during the past millennium. Our findings indicate that climate change was the ultimate cause, and climate-driven economic downturn was the direct cause, of large-scale human crises in preindustrial Europe and the Northern Hemisphere. PMID:21969578

The causality analysis of climate change and large-scale human crisis.

PubMed

Zhang, David D; Lee, Harry F; Wang, Cong; Li, Baosheng; Pei, Qing; Zhang, Jane; An, Yulun

2011-10-18

Recent studies have shown strong temporal correlations between past climate changes and societal crises. However, the specific causal mechanisms underlying this relation have not been addressed. We explored quantitative responses of 14 fine-grained agro-ecological, socioeconomic, and demographic variables to climate fluctuations from A.D. 1500-1800 in Europe. Results show that cooling from A.D. 1560-1660 caused successive agro-ecological, socioeconomic, and demographic catastrophes, leading to the General Crisis of the Seventeenth Century. We identified a set of causal linkages between climate change and human crisis. Using temperature data and climate-driven economic variables, we simulated the alternation of defined "golden" and "dark" ages in Europe and the Northern Hemisphere during the past millennium. Our findings indicate that climate change was the ultimate cause, and climate-driven economic downturn was the direct cause, of large-scale human crises in preindustrial Europe and the Northern Hemisphere.

Effects of Ensemble Configuration on Estimates of Regional Climate Uncertainties

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

Goldenson, N.; Mauger, G.; Leung, L. R.

Internal variability in the climate system can contribute substantial uncertainty in climate projections, particularly at regional scales. Internal variability can be quantified using large ensembles of simulations that are identical but for perturbed initial conditions. Here we compare methods for quantifying internal variability. Our study region spans the west coast of North America, which is strongly influenced by El Niño and other large-scale dynamics through their contribution to large-scale internal variability. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find that internal variability can be quantified consistently using a large ensemble or an ensemble ofmore » opportunity that includes small ensembles from multiple models and climate scenarios. The latter also produce estimates of uncertainty due to model differences. We conclude that projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible, which has implications for ensemble design in large modeling efforts.« less

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

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

Notz, Dirk; Jahn, Alexandra; Holland, Marika

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

DOE PAGES

Notz, Dirk; Jahn, Alexandra; Holland, Marika; ...

2016-09-23

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standardmore » for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.« less

Investigating added value of regional climate modeling in North American winter storm track simulations

NASA Astrophysics Data System (ADS)

Poan, E. D.; Gachon, P.; Laprise, R.; Aider, R.; Dueymes, G.

2018-03-01

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981-2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal `seriality', as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century

PubMed Central

Emanuel, Kerry A.

2013-01-01

A recently developed technique for simulating large [O(104)] numbers of tropical cyclones in climate states described by global gridded data is applied to simulations of historical and future climate states simulated by six Coupled Model Intercomparison Project 5 (CMIP5) global climate models. Tropical cyclones downscaled from the climate of the period 1950–2005 are compared with those of the 21st century in simulations that stipulate that the radiative forcing from greenhouse gases increases by over preindustrial values. In contrast to storms that appear explicitly in most global models, the frequency of downscaled tropical cyclones increases during the 21st century in most locations. The intensity of such storms, as measured by their maximum wind speeds, also increases, in agreement with previous results. Increases in tropical cyclone activity are most prominent in the western North Pacific, but are evident in other regions except for the southwestern Pacific. The increased frequency of events is consistent with increases in a genesis potential index based on monthly mean global model output. These results are compared and contrasted with other inferences concerning the effect of global warming on tropical cyclones. PMID:23836646

Changing Characteristics of convective storms: Results from a continental-scale convection-permitting climate simulations

NASA Astrophysics Data System (ADS)

Prein, A. F.; Ikeda, K.; Liu, C.; Bullock, R.; Rasmussen, R.

2016-12-01

Convective storms are causing extremes such as flooding, landslides, and wind gusts and are related to the development of tornadoes and hail. Convective storms are also the dominant source of summer precipitation in most regions of the Contiguous United States. So far little is known about how convective storms might change due to global warming. This is mainly because of the coarse grid spacing of state-of-the-art climate models that are not able to resolve deep convection explicitly. Instead, coarse resolution models rely on convective parameterization schemes that are a major source of errors and uncertainties in climate change projections. Convection-permitting climate simulations, with grid-spacings smaller than 4 km, show significant improvements in the simulation of convective storms by representing deep convection explicitly. Here we use a pair of 13-year long current and future convection-permitting climate simulations that cover large parts of North America. We use the Method for Object-Based Diagnostic Evaluation (MODE) that incorporates the time dimension (MODE-TD) to analyze the model performance in reproducing storm features in the current climate and to investigate their potential future changes. We show that the model is able to accurately reproduce the main characteristics of convective storms in the present climate. The comparison with the future climate simulation shows that convective storms significantly increase in frequency, intensity, and size. Furthermore, they are projected to move slower which could result in a substantial increase in convective storm-related hazards such as flash floods, debris flows, and landslides. Some regions, such as the North Atlantic, might experience a regime shift that leads to significantly stronger storms that are unrepresented in the current climate.

Simulating the effects of climatic variation on stem carbon accumulation of a ponderosa pine stand: comparison with annual growth increment data.

PubMed

Hunt, E R; Martin, F C; Running, S W

1991-01-01

Simulation models of ecosystem processes may be necessary to separate the long-term effects of climate change on forest productivity from the effects of year-to-year variations in climate. The objective of this study was to compare simulated annual stem growth with measured annual stem growth from 1930 to 1982 for a uniform stand of ponderosa pine (Pinus ponderosa Dougl.) in Montana, USA. The model, FOREST-BGC, was used to simulate growth assuming leaf area index (LAI) was either constant or increasing. The measured stem annual growth increased exponentially over time; the differences between the simulated and measured stem carbon accumulations were not large. Growth trends were removed from both the measured and simulated annual increments of stem carbon to enhance the year-to-year variations in growth resulting from climate. The detrended increments from the increasing LAI simulation fit the detrended increments of the stand data over time with an R(2) of 0.47; the R(2) increased to 0.65 when the previous year's simulated detrended increment was included with the current year's simulated increment to account for autocorrelation. Stepwise multiple linear regression of the detrended increments of the stand data versus monthly meteorological variables had an R(2) of 0.37, and the R(2) increased to 0.47 when the previous year's meteorological data were included to account for autocorrelation. Thus, FOREST-BGC was more sensitive to the effects of year-to-year climate variation on annual stem growth than were multiple linear regression models.

Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: effect of large-scale spectral nudging and of empirical correction of sea-surface temperature

NASA Astrophysics Data System (ADS)

Takhsha, Maryam; Nikiéma, Oumarou; Lucas-Picher, Philippe; Laprise, René; Hernández-Díaz, Leticia; Winger, Katja

2017-10-01

As part of the CORDEX project, the fifth-generation Canadian Regional Climate Model (CRCM5) is used over the Arctic for climate simulations driven by reanalyses and by the MPI-ESM-MR coupled global climate model (CGCM) under the RCP8.5 scenario. The CRCM5 shows adequate skills capturing general features of mean sea level pressure (MSLP) for all seasons. Evaluating 2-m temperature (T2m) and precipitation is more problematic, because of inconsistencies between observational reference datasets over the Arctic that suffer of a sparse distribution of weather stations. In our study, we additionally investigated the effect of large-scale spectral nudging (SN) on the hindcast simulation driven by reanalyses. The analysis shows that SN is effective in reducing the spring MSLP bias, but otherwise it has little impact. We have also conducted another experiment in which the CGCM-simulated sea-surface temperature (SST) is empirically corrected and used as lower boundary conditions over the ocean for an atmosphere-only global simulation (AGCM), which in turn provides the atmospheric lateral boundary conditions to drive the CRCM5 simulation. This approach, so-called 3-step approach of dynamical downscaling (CGCM-AGCM-RCM), which had considerably improved the CRCM5 historical simulations over Africa, exhibits reduced impact over the Arctic domain. The most notable positive effect over the Arctic is a reduction of the T2m bias over the North Pacific Ocean and the North Atlantic Ocean in all seasons. Future projections using this method are compared with the results obtained with the traditional 2-step dynamical downscaling (CGCM-RCM) to assess the impact of correcting systematic biases of SST upon future-climate projections. The future projections are mostly similar for the two methods, except for precipitation.

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.; Einaudi, Franco (Technical Monitor)

2000-01-01

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Next-Generation Climate Modeling Science Challenges for Simulation, Workflow and Analysis Systems

NASA Astrophysics Data System (ADS)

Koch, D. M.; Anantharaj, V. G.; Bader, D. C.; Krishnan, H.; Leung, L. R.; Ringler, T.; Taylor, M.; Wehner, M. F.; Williams, D. N.

2016-12-01

We will present two examples of current and future high-resolution climate-modeling research that are challenging existing simulation run-time I/O, model-data movement, storage and publishing, and analysis. In each case, we will consider lessons learned as current workflow systems are broken by these large-data science challenges, as well as strategies to repair or rebuild the systems. First we consider the science and workflow challenges to be posed by the CMIP6 multi-model HighResMIP, involving around a dozen modeling groups performing quarter-degree simulations, in 3-member ensembles for 100 years, with high-frequency (1-6 hourly) diagnostics, which is expected to generate over 4PB of data. An example of science derived from these experiments will be to study how resolution affects the ability of models to capture extreme-events such as hurricanes or atmospheric rivers. Expected methods to transfer (using parallel Globus) and analyze (using parallel "TECA" software tools) HighResMIP data for such feature-tracking by the DOE CASCADE project will be presented. A second example will be from the Accelerated Climate Modeling for Energy (ACME) project, which is currently addressing challenges involving multiple century-scale coupled high resolution (quarter-degree) climate simulations on DOE Leadership Class computers. ACME is anticipating production of over 5PB of data during the next 2 years of simulations, in order to investigate the drivers of water cycle changes, sea-level-rise, and carbon cycle evolution. The ACME workflow, from simulation to data transfer, storage, analysis and publication will be presented. Current and planned methods to accelerate the workflow, including implementing run-time diagnostics, and implementing server-side analysis to avoid moving large datasets will be presented.

Using historical and projected future climate model simulations as drivers of agricultural and biological models (Invited)

NASA Astrophysics Data System (ADS)

Stefanova, L. B.

2013-12-01

Climate model evaluation is frequently performed as a first step in analyzing climate change simulations. Atmospheric scientists are accustomed to evaluating climate models through the assessment of model climatology and biases, the models' representation of large-scale modes of variability (such as ENSO, PDO, AMO, etc) and the relationship between these modes and local variability (e.g. the connection between ENSO and the wintertime precipitation in the Southeast US). While these provide valuable information about the fidelity of historical and projected climate model simulations from an atmospheric scientist's point of view, the application of climate model data to fields such as agriculture, ecology and biology may require additional analyses focused on the particular application's requirements and sensitivities. Typically, historical climate simulations are used to determine a mapping between the model and observed climate, either through a simple (additive for temperature or multiplicative for precipitation) or a more sophisticated (such as quantile matching) bias correction on a monthly or seasonal time scale. Plants, animals and humans however are not directly affected by monthly or seasonal means. To assess the impact of projected climate change on living organisms and related industries (e.g. agriculture, forestry, conservation, utilities, etc.), derivative measures such as the heating degree-days (HDD), cooling degree-days (CDD), growing degree-days (GDD), accumulated chill hours (ACH), wet season onset (WSO) and duration (WSD), among others, are frequently useful. We will present a comparison of the projected changes in such derivative measures calculated by applying: (a) the traditional temperature/precipitation bias correction described above versus (b) a bias correction based on the mapping between the historical model and observed derivative measures themselves. In addition, we will present and discuss examples of various application-based climate model evaluations, such as: (a) agricultural crop yield estimates and (b) species population viability estimates modeled using observed climate data vs. historical climate simulations.

Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

NASA Technical Reports Server (NTRS)

Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

2016-01-01

We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against observations.

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.

Evolution of precipitation extremes in two large ensembles of climate simulations

NASA Astrophysics Data System (ADS)

Martel, Jean-Luc; Mailhot, Alain; Talbot, Guillaume; Brissette, François; Ludwig, Ralf; Frigon, Anne; Leduc, Martin; Turcotte, Richard

2017-04-01

Recent studies project significant changes in the future distribution of precipitation extremes due to global warming. It is likely that extreme precipitation intensity will increase in a future climate and that extreme events will be more frequent. In this work, annual maxima daily precipitation series from the Canadian Earth System Model (CanESM2) 50-member large ensemble (spatial resolution of 2.8°x2.8°) and the Community Earth System Model (CESM1) 40-member large ensemble (spatial resolution of 1°x1°) are used to investigate extreme precipitation over the historical (1980-2010) and future (2070-2100) periods. The use of these ensembles results in respectively 1 500 (30 years x 50 members) and 1200 (30 years x 40 members) simulated years over both the historical and future periods. These large datasets allow the computation of empirical daily extreme precipitation quantiles for large return periods. Using the CanESM2 and CESM1 large ensembles, extreme daily precipitation with return periods ranging from 2 to 100 years are computed in historical and future periods to assess the impact of climate change. Results indicate that daily precipitation extremes generally increase in the future over most land grid points and that these increases will also impact the 100-year extreme daily precipitation. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety. Estimated increases in precipitation associated to very extreme precipitation events (e.g. 100 years) will drastically change the likelihood of flooding and their extent in future climate. These results, although interesting, need to be extended to sub-daily durations, relevant for urban flooding protection and urban infrastructure design (e.g. sewer networks, culverts). Models and simulations at finer spatial and temporal resolution are therefore needed.

Future changes in regional precipitation simulated by a half-degree coupled climate model: Sensitivity to horizontal resolution

DOE PAGES

Shields, Christine A.; Kiehl, Jeffrey T.; Meehl, Gerald A.

2016-06-02

The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the halfdegree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to highermore » resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clear drying signal across Southern Europe due to increased greenhouse warming. As a result, differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.« less

Modeling water scarcity over south Asia: Incorporating crop growth and irrigation models into the Variable Infiltration Capacity (VIC) model

NASA Astrophysics Data System (ADS)

Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.

2013-04-01

Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.

C4MIP - The Coupled Climate-Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6

NASA Astrophysics Data System (ADS)

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.

Novel Methods to Explore Building Energy Sensitivity to Climate and Heat Waves Using PNNL's BEND Model

NASA Astrophysics Data System (ADS)

Burleyson, C. D.; Voisin, N.; Taylor, T.; Xie, Y.; Kraucunas, I.

2017-12-01

The DOE's Pacific Northwest National Laboratory (PNNL) has been developing the Building ENergy Demand (BEND) model to simulate energy usage in residential and commercial buildings responding to changes in weather, climate, population, and building technologies. At its core, BEND is a mechanism to aggregate EnergyPlus simulations of a large number of individual buildings with a diversity of characteristics over large spatial scales. We have completed a series of experiments to explore methods to calibrate the BEND model, measure its ability to capture interannual variability in energy demand due to weather using simulations of two distinct weather years, and understand the sensitivity to the number and location of weather stations used to force the model. The use of weather from "representative cities" reduces computational costs, but often fails to capture spatial heterogeneity that may be important for simulations aimed at understanding how building stocks respond to a changing climate (Fig. 1). We quantify the potential reduction in temperature and load biases from using an increasing number of weather stations across the western U.S., ranging from 8 to roughly 150. Using 8 stations results in an average absolute summertime temperature bias of 4.0°C. The mean absolute bias drops to 1.5°C using all available stations. Temperature biases of this magnitude translate to absolute summertime mean simulated load biases as high as 13.8%. Additionally, using only 8 representative weather stations can lead to a 20-40% bias of peak building loads under heat wave or cold snap conditions, a significant error for capacity expansion planners who may rely on these types of simulations. This analysis suggests that using 4 stations per climate zone may be sufficient for most purposes. Our novel approach, which requires no new EnergyPlus simulations, could be useful to other researchers designing or calibrating aggregate building model simulations - particularly those looking at the impact of future climate scenarios. Fig. 1. An example of temperature bias that results from using 8 representative weather stations: (a) surface temperature from NLDAS on 5-July 2008 at 2000 UTC; (b) temperature from 8 representative stations at the same time mapped to all counties within a given IECC climate zone; (c) the difference between (a) and (b).

Canary in the coal mine: Historical oxygen decline in the Gulf of St. Lawrence due to large scale climate changes

NASA Astrophysics Data System (ADS)

Claret, M.; Galbraith, E. D.; Palter, J. B.; Gilbert, D.; Bianchi, D.; Dunne, J. P.

2016-02-01

The regional signature of anthropogenic climate change on the atmosphere and upper ocean is often difficult to discern from observational timeseries, dominated as they are by decadal climate variability. Here we argue that a long-term decline of dissolved oxygen concentrations observed in the Gulf of S. Lawrence (GoSL) is consistent with anthropogenic climate change. Oxygen concentrations in the GoSL have declined markedly since 1930 due primarily to an increase of oxygen-poor North Atlantic Central Waters relative to Labrador Current Waters (Gilbert et al. 2005). We compare these observations to a climate warming simulation using a very high-resolution global coupled ocean-atmospheric climate model. The numerical model (CM2.6), developed by the Geophysical Fluid Dynamics Laboratory, is strongly eddying and includes a biogeochemical module with dissolved oxygen. The warming scenario shows that oxygen in the GoSL decreases and it is associated to changes in western boundary currents and wind patterns in the North Atlantic. We speculate that the large-scale changes behind the simulated decrease in GoSL oxygen have also been at play in the real world over the past century, although they are difficult to resolve in noisy atmospheric data.

Particulate matter air pollution in Europe in a +2 °C warming world

NASA Astrophysics Data System (ADS)

Lacressonnière, Gwendoline; Watson, Laura; Gauss, Michael; Engardt, Magnuz; Andersson, Camilla; Beekmann, Matthias; Colette, Augustin; Foret, Gilles; Josse, Béatrice; Marécal, Virginie; Nyiri, Agnes; Siour, Guillaume; Sobolowski, Stefan; Vautard, Robert

2017-04-01

In the framework of the IMPACT2C project, we have evaluated the future European particulate matter concentrations under the influence of climate change and anthropogenic emission reductions. To do so, 30-year simulations for present and future scenarios were performed with an ensemble of four regional Chemical Transport Models. +2 °C scenarios were issued from different regional climate simulations belonging to the CORDEX experiment (RCP4.5 scenario). Comparing present day simulations to observations shows that these simulations meet the requested quality criteria even if some biases do exist. Also, we showed that using regional climate models instead of meteorological reanalysis was not critical for the quality of our simulations. Present day as well as future scenarios show the large variability between models associated with different meteorology and process parameterizations. Future projections of PM concentrations show a large reduction of PM10 and PM2.5 concentrations in a +2 °C climate over the European continent (especially over Benelux), which can be mostly attributed to emission reduction policies. Under a current legislation scenario, annual PM10 could be reduced by between 1.8 and 2.9 μg m-3 (14.1-20.4%). If maximum technologically feasible emission reductions were implemented, further reductions of 1.4-1.9 μg m-3 (18.6-20.9%) are highlighted. Changes due to a +2 °C warming, in isolation from emission changes, are in general much weaker (-1.1 to +0.4 μg m-3,-0.3 to +5.1% for annual PM10 averaged over the European domain). Even if large differences exist between models, we have determined that the decrease of PM over Europe associated with emission reduction is a robust result. The patterns of PM changes resulting from climate change (for example the increase of PM over Spain and southern France and the decrease of PM10 over eastern Europe) are also robustly predicted even if its amplitude remains weak compared to changes associated with emission reductions.

Carbon stocks and fluxes in the high latitudes: using site-level data to evaluate Earth system models

NASA Astrophysics Data System (ADS)

Chadburn, Sarah E.; Krinner, Gerhard; Porada, Philipp; Bartsch, Annett; Beer, Christian; Belelli Marchesini, Luca; Boike, Julia; Ekici, Altug; Elberling, Bo; Friborg, Thomas; Hugelius, Gustaf; Johansson, Margareta; Kuhry, Peter; Kutzbach, Lars; Langer, Moritz; Lund, Magnus; Parmentier, Frans-Jan W.; Peng, Shushi; Van Huissteden, Ko; Wang, Tao; Westermann, Sebastian; Zhu, Dan; Burke, Eleanor J.

2017-11-01

It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow. We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI. The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate biological and physical soil processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models. Thus, we identify three priority areas for model development: (1) dynamic vegetation including (a) climate and (b) nutrient limitation effects; (2) adding moss as a plant functional type; and an (3) improved vertical profile of soil carbon including peat processes.

How do the methodological choices of your climate change study affect your results? A hydrologic case study across the Pacific Northwest

NASA Astrophysics Data System (ADS)

Chegwidden, O.; Nijssen, B.; Rupp, D. E.; Kao, S. C.; Clark, M. P.

2017-12-01

We describe results from a large hydrologic climate change dataset developed across the Pacific Northwestern United States and discuss how the analysis of those results can be seen as a framework for other large hydrologic ensemble investigations. This investigation will better inform future modeling efforts and large ensemble analyses across domains within and beyond the Pacific Northwest. Using outputs from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we provide projections of hydrologic change for the domain through the end of the 21st century. The dataset is based upon permutations of four methodological choices: (1) ten global climate models (2) two representative concentration pathways (3) three meteorological downscaling methods and (4) four unique hydrologic model set-ups (three of which entail the same hydrologic model using independently calibrated parameter sets). All simulations were conducted across the Columbia River Basin and Pacific coastal drainages at a 1/16th ( 6 km) resolution and at a daily timestep. In total, the 172 distinct simulations offer an updated, comprehensive view of climate change projections through the end of the 21st century. The results consist of routed streamflow at 400 sites throughout the domain as well as distributed spatial fields of relevant hydrologic variables like snow water equivalent and soil moisture. In this presentation, we discuss the level of agreement with previous hydrologic projections for the study area and how these projections differ with specific methodological choices. By controlling for some methodological choices we can show how each choice affects key climatic change metrics. We discuss how the spread in results varies across hydroclimatic regimes. We will use this large dataset as a case study for distilling a wide range of hydroclimatological projections into useful climate change assessments.

A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges

DOE PAGES

Prein, Andreas; Langhans, Wolfgang; Fosser, Giorgia; ...

2015-05-27

Regional climate modeling using convection permitting models (CPMs) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs). CPMs do not use convection parameterization schemes, known as a major source of errors and uncertainties, and have more accurate surface and orography elds. The drawback of CPMs is their high demand on computational resources. For this reason, the CPM climate simulations only appeared a decade ago. In this study we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic.more » The most important components in CPM, such as physical parameterizations and dynamical formulations are discussed, and an outlook on required future developments and computer architectures that would support the application of CPMs is given. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Most improvements are found for processes related to deep convection (e.g., precipitation during summer), for mountainous regions, and for the soil-vegetation-atmosphere interactions. The climate change signals of CPM simulations reveal increases in short and extreme rainfall events and an increased ratio of liquid precipitation at the surface (a decrease of hail) potentially leading to more frequent ash oods. Concluding, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to assess their full potential and support their development.« less

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread among the ensemble members of individual model, strong teleconnection (correlation analysis) with SST, coefficient of variation, inter-annual variability, analysis of Taylor diagram, etc. suggest that there is a need to improve coupled model instead of uncoupled model for the development of a better dynamical seasonal forecast system.

Impact of volcanic eruptions on the climate of the 1st millennium AD in a comprehensive climate simulation

NASA Astrophysics Data System (ADS)

Wagner, Sebastian; Zorita, Eduardo

2015-04-01

The climate of the 1st millennium AD shows some remarkable differences compared to the last millennium concerning variation in external forcings. Together with an orbitally induced increased solar insolation during the northern hemisphere summer season and a general lack of strong solar minima, the frequency and intensity of large tropical and extratropical eruptions is decreased. Here we present results of a new climate simulation carried out with the comprehensive Earth System Model MPI-ESM-P forced with variations in orbital, solar, volcanic and greenhouse gas variations and land use changes for the last 2,100 years. The atmospheric model has a horizontal resolution of T63 (approx. 125x125 km) and therefore also allows investigations of regional-to-continental scale climatic phenomena. The volcanic forcing was reconstructed based on a publication by Sigl et al. (2013) using the sulfate records of the NEEM and WAIS ice cores. To obtain information on the aerosol optical depth (AOD) these sulfate records were scaled to an established reconstruction from Crowley and Unterman (2010), which is also a standard forcing in the framework of CMIP5/PMIP3. A comparison between the newly created data set with the Crowley and Unterman dataset reveals that the new reconstruction shows in general weaker intensities, especially of the large tropical outbreaks and fewer northern hemispheric small-to-medium scale eruptions. However, the general pattern in the overlapping period is similar. A hypothesis that can be tested with the simulation is whether the reduced volcanic intensity of the 1st millennium AD contributed to the elevated temperature levels over Europe, evident within a new proxy-based reconstruction. On the other hand, the few but large volcanic eruptions, e.g. the 528 AD event, also induced negative decadal-scale temperature anomalies. Another interesting result of the simulation relates to the 79 AD eruption of the Vesuvius, which caused the collapse of the city of Pompeii and its surroundings. Despite its severe local effects the eruption does not show a clear-cut hemispheric or global cooling. Therefore the simulation allows investigations on the effect of individual and clustered eruptions on the climate in the 1st millennium AD and its potential influence to human induced migration periods and decay of cultures in different regions.

Simulated Changes in Northwest U.S. Climate in Response to Amazon Deforestation

EPA Science Inventory

Numerical models have long predicted that the deforestation of the Amazon would lead to large regional changes in precipitation and temperature, but the extratropical effects of deforestation have been a matter of controversy. This paper investigates the simulated impacts of defo...

Continental-scale temperature covariance in proxy reconstructions and climate models

NASA Astrophysics Data System (ADS)

Hartl-Meier, Claudia; Büntgen, Ulf; Smerdon, Jason; Zorita, Eduardo; Krusic, Paul; Ljungqvist, Fredrik; Schneider, Lea; Esper, Jan

2017-04-01

Inter-continental temperature variability over the past millennium has been reported to be more coherent in climate model simulations than in multi-proxy-based reconstructions, a finding that undermines the representation of spatial variability in either of these approaches. We assess the covariance of summer temperatures among Northern Hemisphere continents by comparing tree-ring based temperature reconstructions with state-of-the-art climate model simulations over the past millennium. We find inter-continental temperature covariance to be larger in tree-ring-only reconstructions compared to those derived from multi-proxy networks, thus enhancing the agreement between proxy- and model-based spatial representations. A detailed comparison of simulated temperatures, however, reveals substantial spread among the models. Over the past millennium, inter-continental temperature correlations are driven by the cooling after major volcanic eruptions in 1257, 1452, 1601, and 1815. The coherence of these synchronizing events appears to be elevated in several climate simulations relative to their own covariance baselines and the proxy reconstructions, suggesting these models overestimate the amplitude of cooling in response to volcanic forcing at large spatial scales.

Supporting observation campaigns with high resolution modeling

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Voigt, Aiko

2017-04-01

High resolution simulation in support of measurement campaigns offers a promising and emerging way to create large-scale context for small-scale observations of clouds and precipitation processes. As these simulation include the coupling of measured small-scale processes with the circulation, they also help to integrate the research communities from modeling and observations and allow for detailed model evaluations against dedicated observations. In connection with the measurement campaign NARVAL (August 2016 and December 2013) simulations with a grid-spacing of 2.5 km for the tropical Atlantic region (9000x3300 km), with local refinement to 1.2 km for the western part of the domain, were performed using the icosahedral non-hydrostatic (ICON) general circulation model. These simulations are again used to drive large eddy resolving simulations with the same model for selected days in the high definition clouds and precipitation for advancing climate prediction (HD(CP)2) project. The simulations are presented with the focus on selected results showing the benefit for the scientific communities doing atmospheric measurements and numerical modeling of climate and weather. Additionally, an outlook will be given on how similar simulations will support the NAWDEX measurement campaign in the North Atlantic and AC3 measurement campaign in the Arctic.

Volcanic Contribution to Decadal Changes in Tropospheric Temperature

NASA Technical Reports Server (NTRS)

Santer, Benjamin D.; Bonfils, Celine; Painter, Jeffrey F.; Zelinka, Mark D.; Mears, Carl; Solomon, Susan; Schmidt, Gavin A.; Fyfe, John C.; Cole, Jason N.S.; Nazarenko, Larissa;

Predicting Coupled Ocean-Atmosphere Modes with a Climate Modeling Hierarchy -- Final Report

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

Michael Ghil, UCLA; Andrew W. Robertson, IRI, Columbia Univ.; Sergey Kravtsov, U. of Wisconsin, Milwaukee

The goal of the project was to determine midlatitude climate predictability associated with tropical-extratropical interactions on interannual-to-interdecadal time scales. Our strategy was to develop and test a hierarchy of climate models, bringing together large GCM-based climate models with simple fluid-dynamical coupled ocean-ice-atmosphere models, through the use of advanced probabilistic network (PN) models. PN models were used to develop a new diagnostic methodology for analyzing coupled ocean-atmosphere interactions in large climate simulations made with the NCAR Parallel Climate Model (PCM), and to make these tools user-friendly and available to other researchers. We focused on interactions between the tropics and extratropics throughmore » atmospheric teleconnections (the Hadley cell, Rossby waves and nonlinear circulation regimes) over both the North Atlantic and North Pacific, and the ocean’s thermohaline circulation (THC) in the Atlantic. We tested the hypothesis that variations in the strength of the THC alter sea surface temperatures in the tropical Atlantic, and that the latter influence the atmosphere in high latitudes through an atmospheric teleconnection, feeding back onto the THC. The PN model framework was used to mediate between the understanding gained with simplified primitive equations models and multi-century simulations made with the PCM. The project team is interdisciplinary and built on an existing synergy between atmospheric and ocean scientists at UCLA, computer scientists at UCI, and climate researchers at the IRI.« less

Supplement of: The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

NASA Technical Reports Server (NTRS)

Colose, Christopher; LeGrande, Allegra N.; Vuille, Mathias

2016-01-01

Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El NioSouthern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium.An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records.Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the amount effect. During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is larger than the rather weak and spatially less coherent precipitation signal, complicating the isotopic response to changes in the hydrologic cycle.

The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

NASA Technical Reports Server (NTRS)

Colose, Christopher M.; LeGrande, Allegra N.; Vuille, Mathias

2016-01-01

Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El Niño-Southern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850 CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium. An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records. Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the "amount effect". During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is larger than the rather weak and spatially less coherent precipitation signal, complicating the isotopic response to changes in the hydrologic cycle.

Simulating high spatial resolution high severity burned area in Sierra Nevada forests for California Spotted Owl habitat climate change risk assessment and management.

NASA Astrophysics Data System (ADS)

Keyser, A.; Westerling, A. L.; Jones, G.; Peery, M. Z.

2017-12-01

Sierra Nevada forests have experienced an increase in very large fires with significant areas of high burn severity, such as the Rim (2013) and King (2014) fires, that have impacted habitat of endangered species such as the California spotted owl. In order to support land manager forest management planning and risk assessment activities, we used historical wildfire histories from the Monitoring Trends in Burn Severity project and gridded hydroclimate and land surface characteristics data to develope statistical models to simulate the frequency, location and extent of high severity burned area in Sierra Nevada forest wildfires as functions of climate and land surface characteristics. We define high severity here as BA90 area: the area comprising patches with ninety percent or more basal area killed within a larger fire. We developed a system of statistical models to characterize the probability of large fire occurrence, the probability of significant BA90 area present given a large fire, and the total extent of BA90 area in a fire on a 1/16 degree lat/lon grid over the Sierra Nevada. Repeated draws from binomial and generalized pareto distributions using these probabilities generated a library of simulated histories of high severity fire for a range of near (50 yr) future climate and fuels management scenarios. Fuels management scenarios were provided by USFS Region 5. Simulated BA90 area was then downscaled to 30 m resolution using a statistical model we developed using Random Forest techniques to estimate the probability of adjacent 30m pixels burning with ninety percent basal kill as a function of fire size and vegetation and topographic features. The result is a library of simulated high resolution maps of BA90 burned areas for a range of climate and fuels management scenarios with which we estimated conditional probabilities of owl nesting sites being impacted by high severity wildfire.

The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model

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

Dickinson, Robert E.; Oleson, Keith; Bonan, Gordon

2006-01-01

Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on themore » simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.« less

Nitrogen-Related Constraints of Carbon Uptake by Large-Scale Forest Expansion: Simulation Study for Climate Change and Management Scenarios

NASA Astrophysics Data System (ADS)

Kracher, Daniela

2017-11-01

Increase of forest areas has the potential to increase the terrestrial carbon (C) sink. However, the efficiency for C sequestration depends on the availability of nutrients such as nitrogen (N), which is affected by climatic conditions and management practices. In this study, I analyze how N limitation affects C sequestration of afforestation and how it is influenced by individual climate variables, increased harvest, and fertilizer application. To this end, JSBACH, the land component of the Earth system model of the Max Planck Institute for Meteorology is applied in idealized simulation experiments. In those simulations, large-scale afforestation increases the terrestrial C sink in the 21st century by around 100 Pg C compared to a business as usual land-use scenario. N limitation reduces C sequestration roughly by the same amount. The relevance of compensating effects of uptake and release of carbon dioxide by plant productivity and soil decomposition, respectively, gets obvious from the simulations. N limitation of both fluxes compensates particularly in the tropics. Increased mineralization under global warming triggers forest expansion, which otherwise is restricted by N availability. Due to compensating higher plant productivity and soil respiration, the global net effect of warming for C sequestration is however rather small. Fertilizer application and increased harvest enhance C sequestration as well as boreal expansion. The additional C sequestration achieved by fertilizer application is offset to a large part by additional emissions of nitrous oxide.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707

Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Paleoclimatology Supports Physics: Our Energy Choices Will Have Large and Long-Lasting Consequences for Climate and Ecosystems

NASA Astrophysics Data System (ADS)

Harland, B.; Bradley, R. S.; Schlosser, P.; Rignot, E. J.; Dickens, G. R.; Boslough, M.; Alley, R. B.

2016-12-01

Interpretations of the paleoclimatic record show with increasing clarity and confidence that CO2 has been the most important of the many controls on Earth's climate history, providing a slow stabilizer but fast destabilizer through both forcing and feedbacks. From the Faint Young Sun through Snowball Earth, the warmth of the Cretaceous, the PETM, ice-age cycling, and many events between, our best understanding shows that CO2 has been an essential player. Many climate reconstructions are based on the biological record; we know what CO2 did to the climate in part from the ways that living things responded. If our climate models have a shortcoming, the full climate response to CO2 is larger than simulated for shorter times. Surprisingly large response may prove to be especially important for ice sheets and sea level.

Influence of blocking on Northern European and Western Russian heatwaves in large climate model ensembles

NASA Astrophysics Data System (ADS)

Schaller, N.; Sillmann, J.; Anstey, J.; Fischer, E. M.; Grams, C. M.; Russo, S.

2018-05-01

Better preparedness for summer heatwaves could mitigate their adverse effects on society. This can potentially be attained through an increased understanding of the relationship between heatwaves and one of their main dynamical drivers, atmospheric blocking. In the 1979–2015 period, we find that there is a significant correlation between summer heatwave magnitudes and the number of days influenced by atmospheric blocking in Northern Europe and Western Russia. Using three large global climate model ensembles, we find similar correlations, indicating that these three models are able to represent the relationship between extreme temperature and atmospheric blocking, despite having biases in their simulation of individual climate variables such as temperature or geopotential height. Our results emphasize the need to use large ensembles of different global climate models as single realizations do not always capture this relationship. The three large ensembles further suggest that the relationship between summer heatwaves and atmospheric blocking will not change in the future. This could be used to statistically model heatwaves with atmospheric blocking as a covariate and aid decision-makers in planning disaster risk reduction and adaptation to climate change.

LPJ-GUESS Simulated Western North America Mid-latitude Vegetation Changes for 15-10 ka Using the CCSM3 TraCE Climate Simulation

NASA Astrophysics Data System (ADS)

Shafer, S. L.; Bartlein, P. J.

2017-12-01

The period from 15-10 ka was a time of rapid vegetation changes in North America. Continental ice sheets in northern North America were receding, exposing new habitat for vegetation, and regions distant from the ice sheets experienced equally large environmental changes. Northern hemisphere temperatures during this period were increasing, promoting transitions from cold-adapted to temperate plant taxa at mid-latitudes. Long, transient paleovegetation simulations can provide important information on vegetation responses to climate changes, including both the spatial dynamics and rates of species distribution changes over time. Paleovegetation simulations also can fill the spatial and temporal gaps in observed paleovegetation records (e.g., pollen data from lake sediments), allowing us to test hypotheses about past vegetation changes (e.g., the location of past refugia). We used the CCSM3 TraCE transient climate simulation as input for LPJ-GUESS, a general ecosystem model, to simulate vegetation changes from 15-10 ka for parts of western North America at mid-latitudes ( 35-55° N). For these simulations, LPJ-GUESS was parameterized to simulate key tree taxa for western North America (e.g., Pseudotsuga, Tsuga, Quercus, etc.). The CCSM3 TraCE transient climate simulation data were regridded onto a 10-minute grid of the study area. We analyzed the simulated spatial and temporal dynamics of these taxa and compared the simulated changes with observed paleovegetation changes recorded in pollen and plant macrofossil data (e.g., data from the Neotoma Paleoecology Database). In general, the LPJ-GUESS simulations reproduce the general patterns of paleovegetation responses to climate change, although the timing of some simulated vegetation changes do not match the observed paleovegetation record. We describe the areas and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of the simulated climate and vegetation data. The magnitude and rate of the simulated past vegetation changes are compared with projected future vegetation changes for the region.

Evaluation on Asian Dust Aerosol and Simulated Processes in CanAM4.2 Using Satellite Measurements and Station Data

NASA Astrophysics Data System (ADS)

Yiran, P.; Li, J.; von Salzen, K.; Dai, T.; Liu, D.

2014-12-01

Mineral dust is a significant contributor to global and Asian aerosol burden. Currently, large uncertainties still exist in simulated aerosol processes in global climate models (GCMs), which lead to a diversity in dust mass loading and spatial distribution of GCM projections. In this study, satellite measurements from CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) and observed aerosol data from Asian stations are compared with modelled aerosol in the Canadian Atmospheric Global Climate Model (CanAM4.2). Both seasonal and annual variations in Asian dust distribution are investigated. Vertical profile of simulated aerosol in troposphere is evaluated with CALIOP Level 3 products and local observed extinction for dust and total aerosols. Physical processes in GCM such as horizontal advection, vertical mixing, dry and wet removals are analyzed according to model simulation and available measurements of aerosol. This work aims to improve current understanding of Asian dust transport and vertical exchange on a large scale, which may help to increase the accuracy of GCM simulation on aerosols.

CLARREO shortwave observing system simulation experiments of the twenty-first century: Simulator design and implementation

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

Feldman, D.R.; Algieri, C.A.; Ong, J.R.

2011-04-01

Projected changes in the Earth system will likely be manifested in changes in reflected solar radiation. This paper introduces an operational Observational System Simulation Experiment (OSSE) to calculate the signals of future climate forcings and feedbacks in top-of-atmosphere reflectance spectra. The OSSE combines simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report for the NCAR Community Climate System Model (CCSM) with the MODTRAN radiative transfer code to calculate reflectance spectra for simulations of current and future climatic conditions over the 21st century. The OSSE produces narrowband reflectances and broadband fluxes, the latter of which have been extensivelymore » validated against archived CCSM results. The shortwave reflectance spectra contain atmospheric features including signals from water vapor, liquid and ice clouds, and aerosols. The spectra are also strongly influenced by the surface bidirectional reflectance properties of predicted snow and sea ice and the climatological seasonal cycles of vegetation. By comparing and contrasting simulated reflectance spectra based on emissions scenarios with increasing projected and fixed present-day greenhouse gas and aerosol concentrations, we find that prescribed forcings from increases in anthropogenic sulfate and carbonaceous aerosols are detectable and are spatially confined to lower latitudes. Also, changes in the intertropical convergence zone and poleward shifts in the subsidence zones and the storm tracks are all detectable along with large changes in snow cover and sea ice fraction. These findings suggest that the proposed NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to measure shortwave reflectance spectra may help elucidate climate forcings, responses, and feedbacks.« less

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations.

PubMed

Tang, Ying; Winkler, Julie; Zhong, Shiyuan; Bian, Xindi; Doubler, Dana; Yu, Lejiang; Walters, Claudia

2017-07-10

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereas current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. The choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.

Predicting Impacts of Climate Change on the Aboveground Carbon Sequestration Rate of a Temperate Forest in Northeastern China

PubMed Central

Ma, Jun; Hu, Yuanman; Bu, Rencang; Chang, Yu; Deng, Huawei; Qin, Qin

2014-01-01

The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species. PMID:24763409

Predicting impacts of climate change on the aboveground carbon sequestration rate of a temperate forest in northeastern China.

PubMed

Ma, Jun; Hu, Yuanman; Bu, Rencang; Chang, Yu; Deng, Huawei; Qin, Qin

2014-01-01

The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species.

Establishing the common patterns of future tropospheric ozone under diverse climate change scenarios

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Gómez-Navarro, Juan J.; Jerez, Sonia; Lorente-Plazas, Raquel; Baro, Rocio; Montávez, Juan P.

2013-04-01

The impacts of climate change on air quality may affect long-term air quality planning. However, the policies aimed at improving air quality in the EU directives have not accounted for the variations in the climate. Climate change alone influences future air quality through modifications of gas-phase chemistry, transport, removal, and natural emissions. As such, the aim of this work is to check whether the projected changes in gas-phase air pollution over Europe depends on the scenario driving the regional simulation. For this purpose, two full-transient regional climate change-air quality projections for the first half of the XXI century (1991-2050) have been carried out with MM5+CHIMERE system, including A2 and B2 SRES scenarios. Experiments span the periods 1971-2000, as a reference, and 2071-2100, as future enhanced greenhouse gas and aerosol scenarios (SRES A2 and B2). The atmospheric simulations have a horizontal resolution of 25 km and 23 vertical layers up to 100 mb, and were driven by ECHO-G global climate model outputs. The analysis focuses on the connection between meteorological and air quality variables. Our simulations suggest that the modes of variability for tropospheric ozone and their main precursors hardly change under different SRES scenarios. The effect of changing scenarios has to be sought in the intensity of the changing signal, rather than in the spatial structure of the variation patterns, since the correlation between the spatial patterns of variability in A2 and B2 simulation is r > 0.75 for all gas-phase pollutants included in this study. In both cases, full-transient simulations indicate an enhanced enhanced chemical activity under future scenarios. The causes for tropospheric ozone variations have to be sought in a multiplicity of climate factors, such as increased temperature, different distribution of precipitation patterns across Europe, increased photolysis of primary and secondary pollutants due to lower cloudiness, etc. Nonetheless, according to the results of this work future ozone is conditioned by the dependence of biogenic emissions on the climatological patterns of variability. In this sense, ozone over Europe is mainly driven by the warming-induced increase in biogenic emitting activity (vegetation is kept invariable in the simulations, but estimations of these emissions strongly depends on shortwave radiation and temperature, which are substantially modified in climatic simulations). Moreover, one of the most important drivers for ozone increase is the decrease of cloudiness (related to stronger solar radiation) mostly over southern Europe at the first half of the XXI century. However, given the large uncertainty isoprene sensitivity to climate change and the large uncertainties associated to the cloudiness projections, these results should be carefully considered.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

The North American Regional Climate Change Assessment Program (NARCCAP): Status and results

NASA Astrophysics Data System (ADS)

Gutowski, W. J.

2009-12-01

NARCCAP is a multi-institutional program that is investigating systematically the uncertainties in regional scale simulations of contemporary climate and projections of future climate. NARCCAP is supported by multiple federal agencies. NARCCAP is producing an ensemble of high-resolution climate-change scenarios by nesting multiple RCMs in reanalyses and multiple atmosphere-ocean GCM simulations of contemporary and future-scenario climates. The RCM domains cover the contiguous U.S., northern Mexico, and most of Canada. The simulation suite also includes time-slice, high resolution GCMs that use sea-surface temperatures from parent atmosphere-ocean GCMs. The baseline resolution of the RCMs and time-slice GCMs is 50 km. Simulations use three sources of boundary conditions: National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) AMIP-II Reanalysis, GCMs simulating contemporary climate and GCMs using the A2 SRES emission scenario for the twenty-first century. Simulations cover 1979-2004 and 2038-2060, with the first 3 years discarded for spin-up. The resulting RCM and time-slice simulations offer opportunity for extensive analysis of RCM simulations as well as a basis for multiple high-resolution climate scenarios for climate change impacts assessments. Geophysical statisticians are developing measures of uncertainty from the ensemble. To enable very high-resolution simulations of specific regions, both RCM and high-resolution time-slice simulations are saving output needed for further downscaling. All output is publically available to the climate analysis and the climate impacts assessment community, through an archiving and data-distribution plan. Some initial results show that the models closely reproduce ENSO-related precipitation variations in coastal California, where the correlation between the simulated and observed monthly time series exceeds 0.94 for all models. The strong El Nino events of 1982-83 and 1997-98 are well reproduced for the Pacific coastal region of the U.S. in all models. ENSO signals are less well reproduced in other regions. The models also produce well extreme monthly precipitation in coastal California and the Upper Midwest. Model performance tends to deteriorate from west to east across the domain, or roughly from the inflow boundary toward the outflow boundary. This deterioration with distance from the inflow boundary is ameliorated to some extent in models formulated such that large-scale information is included in the model solution, whether implemented by spectral nudging or by use of a perturbation form of the governing equations.

Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes

USGS Publications Warehouse

Bartlein, P.J.; Edwards, M.E.; Hostetler, Steven W.; Shafer, Sarah; Anderson, P.M.; Brubaker, L. B; Lozhkin, A. V

2015-01-01

Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modeling and paleo-observations. The subcontinental region of Beringia (northeastern Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia's early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present-day simulations of regional climate – one with modern and one with 11 ka geography – plus another simulation for 6 ka. In addition, we performed five ~ 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka Control, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present-day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present-day distribution of lakes and wetlands, and (v) post-11 ka All, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season.

Regional-Scale Climate Change: Observations and Model Simulations

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

Bradley, Raymond S; Diaz, Henry F

2010-12-14

This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, andmore » we conducted studies of changes in phonological indicators based on various climatic thresholds.« less

Investigating Added Value of Regional Climate Modeling in North American Winter Storm Track Simulations

NASA Astrophysics Data System (ADS)

Poan, E.; Gachon, P., Sr.; Laprise, R.; Aider, R.; Dueymes, G.

2017-12-01

This study describes a framework using possibilities given by regional climate models (RCMs) to gain insight into extratropical cyclone (EC) activity during winter over North America (NA). Recent past climate period (1981 - 2005) is firstly considered using the NCEP regional reanalysis (NARR) as a reference, along with the European global reanalysis ERA-Interim (ERAI) and two CMIP5 Global Climate Models (GCMs) used to drive the Canadian RCM - version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological EC track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while their intensity is well captured. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over the eastern coast. In addition, storm occurrence from GCMs over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with main relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value from the CRCM5 is less prominent and systematic, except over western areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Finally, time period near the end of the 21st century (2071-2100) is considered to analyze EC characteristic trends and changes relative to the current climate conditions, showing important modifications in storm activity for certain winter months, especially in term of intensity over the eastern coast.

Comparison of Radiative Energy Flows in Observational Datasets and Climate Modeling

NASA Technical Reports Server (NTRS)

Raschke, Ehrhard; Kinne, Stefan; Rossow, William B.; Stackhouse, Paul W. Jr.; Wild, Martin

2016-01-01

This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10Wm(exp -2) each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30Wmexp -2) over trade wind cumulus regions, yet smaller CRE by about -30Wm(exp -2) over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15Wm(exp -2) smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.

A Last Glacial Maximum world-ocean simulation at eddy-permitting resolution - Part 1: Experimental design and basic evaluation

NASA Astrophysics Data System (ADS)

Ballarotta, M.; Brodeau, L.; Brandefelt, J.; Lundberg, P.; Döös, K.

2013-01-01

Most state-of-the-art climate models include a coarsely resolved oceanic component, which has difficulties in capturing detailed dynamics, and therefore eddy-permitting/eddy-resolving simulations have been developed to reproduce the observed World Ocean. In this study, an eddy-permitting numerical experiment is conducted to simulate the global ocean state for a period of the Last Glacial Maximum (LGM, ~ 26 500 to 19 000 yr ago) and to investigate the improvements due to taking into account these higher spatial scales. The ocean general circulation model is forced by a 49-yr sample of LGM atmospheric fields constructed from a quasi-equilibrated climate-model simulation. The initial state and the bottom boundary condition conform to the Paleoclimate Modelling Intercomparison Project (PMIP) recommendations. Before evaluating the model efficiency in representing the paleo-proxy reconstruction of the surface state, the LGM experiment is in this first part of the investigation, compared with a present-day eddy-permitting hindcast simulation as well as with the available PMIP results. It is shown that the LGM eddy-permitting simulation is consistent with the quasi-equilibrated climate-model simulation, but large discrepancies are found with the PMIP model analyses, probably due to the different equilibration states. The strongest meridional gradients of the sea-surface temperature are located near 40° N and S, this due to particularly large North-Atlantic and Southern-Ocean sea-ice covers. These also modify the locations of the convection sites (where deep-water forms) and most of the LGM Conveyor Belt circulation consequently takes place in a thinner layer than today. Despite some discrepancies with other LGM simulations, a glacial state is captured and the eddy-permitting simulation undertaken here yielded a useful set of data for comparisons with paleo-proxy reconstructions.

Large-Scale Ocean Circulation-Cloud Interactions Reduce the Pace of Transient Climate Change

NASA Technical Reports Server (NTRS)

Trossman, D. S.; Palter, J. B.; Merlis, T. M.; Huang, Y.; Xia, Y.

2016-01-01

Changes to the large scale oceanic circulation are thought to slow the pace of transient climate change due, in part, to their influence on radiative feedbacks. Here we evaluate the interactions between CO2-forced perturbations to the large-scale ocean circulation and the radiative cloud feedback in a climate model. Both the change of the ocean circulation and the radiative cloud feedback strongly influence the magnitude and spatial pattern of surface and ocean warming. Changes in the ocean circulation reduce the amount of transient global warming caused by the radiative cloud feedback by helping to maintain low cloud coverage in the face of global warming. The radiative cloud feedback is key in affecting atmospheric meridional heat transport changes and is the dominant radiative feedback mechanism that responds to ocean circulation change. Uncertainty in the simulated ocean circulation changes due to CO2 forcing may contribute a large share of the spread in the radiative cloud feedback among climate models.

Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

NASA Astrophysics Data System (ADS)

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.

Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures

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

Sanderson, Benjamin M.; Xu, Yangyang; Tebaldi, Claudia

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 andmore » 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.« less

Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures

DOE PAGES

Sanderson, Benjamin M.; Xu, Yangyang; Tebaldi, Claudia; ...

2017-09-19

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 andmore » 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.« less

Spatially explicit shallow landslide susceptibility mapping over large areas

Treesearch

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

Impact of spectral nudging on regional climate simulation over CORDEX East Asia using WRF

NASA Astrophysics Data System (ADS)

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.

Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

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.

Change in atmospheric mineral aerosols in response to climate: Last glacial period, preindustrial, modern, and doubled carbon dioxide climates

USGS Publications Warehouse

Mahowald, N.M.; Muhs, D.R.; Levis, S.; Rasch, P.J.; Yoshioka, M.; Zender, C.S.; Luo, C.

2006-01-01

Desert dust simulations generated by the National Center for Atmospheric Research's Community Climate System Model for the current climate are shown to be consistent with present day satellite and deposition data. The response of the dust cycle to last glacial maximum, preindustrial, modern, and doubled-carbon dioxide climates is analyzed. Only natural (non-land use related) dust sources are included in this simulation. Similar to some previous studies, dust production mainly responds to changes in the source areas from vegetation changes, not from winds or soil moisture changes alone. This model simulates a +92%, +33%, and -60% change in dust loading for the last glacial maximum, preindustrial, and doubled-carbon dioxide climate, respectively, when impacts of carbon dioxide fertilization on vegetation are included in the model. Terrestrial sediment records from the last glacial maximum compiled here indicate a large underestimate of deposition in continental regions, probably due to the lack of simulation of glaciogenic dust sources. In order to include the glaciogenic dust sources as a first approximation, we designate the location of these sources, and infer the size of the sources using an inversion method that best matches the available data. The inclusion of these inferred glaciogenic dust sources increases our dust flux in the last glacial maximum from 2.1 to 3.3 times current deposition. Copyright 2006 by the American Geophysical Union.

Hydrologic and water quality sensitivity to climate and land ...

EPA Pesticide Factsheets

This page describes a current EPA ORD project. No project report or other download is available at this time. Please see the section Next Steps below for a timeline of anticipated products of this work. Background: Projected changes in climate during the next century could cause or contribute to increased flooding, drought, water quality degradation, and ecosystem impairment. The effects of climate change in different watersheds will vary due to regional differences in climate change, physiographic setting, and interaction with land-use, pollutant sources, and water management in different locations. EPA is conducting watershed modeling to develop hydrologic and water quality change scenarios for 20 relatively large U.S. watersheds. Watershed modeling will be conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil Water Assessment Tool (SWAT) watershed models. Study areas range from about 10,000-15,000 square miles in size, and will cover nearly every ecoregion in the United States and a range of hydro-climatic conditions. A range of hydrologic and water quality endpoints will be determined for each watershed simulation. Endpoints will be selected to inform upon a range of stream flow, water quality, aquatic ecosystem, and EPA program management goals and targets. Model simulations will be conducted to evaluate a range of projected future (2040-2070) changes in climate and land-use. Simulations will include baseline conditions,

Changes in extremes due to half a degree warming in observations and models

NASA Astrophysics Data System (ADS)

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.

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

Prein, Andreas; Langhans, Wolfgang; Fosser, Giorgia

Regional climate modeling using convection permitting models (CPMs) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs). CPMs do not use convection parameterization schemes, known as a major source of errors and uncertainties, and have more accurate surface and orography elds. The drawback of CPMs is their high demand on computational resources. For this reason, the CPM climate simulations only appeared a decade ago. In this study we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic.more » The most important components in CPM, such as physical parameterizations and dynamical formulations are discussed, and an outlook on required future developments and computer architectures that would support the application of CPMs is given. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Most improvements are found for processes related to deep convection (e.g., precipitation during summer), for mountainous regions, and for the soil-vegetation-atmosphere interactions. The climate change signals of CPM simulations reveal increases in short and extreme rainfall events and an increased ratio of liquid precipitation at the surface (a decrease of hail) potentially leading to more frequent ash oods. Concluding, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to assess their full potential and support their development.« less

Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change

Treesearch

Wen J. Wang; Hong S. He; Frank R. Thompson; Martin A. Spetich; Jacob S. Fraser

2018-01-01

Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are notwell represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts.We investigate how species biological...

Impact of large-scale circulation changes in the North Atlantic sector on the current and future Mediterranean winter hydroclimate

NASA Astrophysics Data System (ADS)

Barcikowska, Monika J.; Kapnick, Sarah B.; Feser, Frauke

2018-03-01

The Mediterranean region, located in the transition zone between the dry subtropical and wet European mid-latitude climate, is very sensitive to changes in the global mean climate state. Projecting future changes of the Mediterranean hydroclimate under global warming therefore requires dynamic climate models to reproduce the main mechanisms controlling regional hydroclimate with sufficiently high resolution to realistically simulate climate extremes. To assess future winter precipitation changes in the Mediterranean region we use the Geophysical Fluid Dynamics Laboratory high-resolution general circulation model for control simulations with pre-industrial greenhouse gas and aerosol concentrations which are compared to future scenario simulations. Here we show that the coupled model is able to reliably simulate the large-scale winter circulation, including the North Atlantic Oscillation and Eastern Atlantic patterns of variability, and its associated impacts on the mean Mediterranean hydroclimate. The model also realistically reproduces the regional features of daily heavy rainfall, which are absent in lower-resolution simulations. A five-member future projection ensemble, which assumes comparatively high greenhouse gas emissions (RCP8.5) until 2100, indicates a strong winter decline in Mediterranean precipitation for the coming decades. Consistent with dynamical and thermodynamical consequences of a warming atmosphere, derived changes feature a distinct bipolar behavior, i.e. wetting in the north—and drying in the south. Changes are most pronounced over the northwest African coast, where the projected winter precipitation decline reaches 40% of present values. Despite a decrease in mean precipitation, heavy rainfall indices show drastic increases across most of the Mediterranean, except the North African coast, which is under the strong influence of the cold Canary Current.

Insights into low-latitude cloud feedbacks from high-resolution models.

PubMed

Bretherton, Christopher S

2015-11-13

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes. © 2015 The Author(s).

El Niño/Southern Oscillation response to global warming

PubMed Central

Latif, M.; Keenlyside, N. S.

2009-01-01

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO2, accelerating global warming. PMID:19060210

Plant functional diversity affects climate-vegetation interaction

NASA Astrophysics Data System (ADS)

Groner, Vivienne P.; Raddatz, Thomas; Reick, Christian H.; Claussen, Martin

2018-04-01

We present how variations in plant functional diversity affect climate-vegetation interaction towards the end of the African Humid Period (AHP) in coupled land-atmosphere simulations using the Max Planck Institute Earth system model (MPI-ESM). In experiments with AHP boundary conditions, the extent of the green Sahara varies considerably with changes in plant functional diversity. Differences in vegetation cover extent and plant functional type (PFT) composition translate into significantly different land surface parameters, water cycling, and surface energy budgets. These changes have not only regional consequences but considerably alter large-scale atmospheric circulation patterns and the position of the tropical rain belt. Towards the end of the AHP, simulations with the standard PFT set in MPI-ESM depict a gradual decrease of precipitation and vegetation cover over time, while simulations with modified PFT composition show either a sharp decline of both variables or an even slower retreat. Thus, not the quantitative but the qualitative PFT composition determines climate-vegetation interaction and the climate-vegetation system response to external forcing. The sensitivity of simulated system states to changes in PFT composition raises the question how realistically Earth system models can actually represent climate-vegetation interaction, considering the poor representation of plant diversity in the current generation of land surface models.

El Nino/Southern Oscillation response to global warming.

PubMed

Latif, M; Keenlyside, N S

2009-12-08

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO(2), accelerating global warming.

How Continuous Observations of Shortwave Reflectance Spectra Can Narrow the Range of Shortwave Climate Feedbacks

NASA Astrophysics Data System (ADS)

Feldman, D.; Collins, W. D.; Wielicki, B. A.; Shea, Y.; Mlynczak, M. G.; Kuo, C.; Nguyen, N.

2017-12-01

Shortwave feedbacks are a persistent source of uncertainty for climate models and a large contributor to the diagnosed range of equilibrium climate sensitivity (ECS) for the international multi-model ensemble. The processes that contribute to these feedbacks affect top-of-atmosphere energetics and produce spectral signatures that may be time-evolving. We explore the value of such spectral signatures for providing an observational constraint on model ECS by simulating top-of-atmosphere shortwave reflectance spectra across much of the energetically-relevant shortwave bandpass (300 to 2500 nm). We present centennial-length shortwave hyperspectral simulations from low, medium and high ECS models that reported to the CMIP5 archive as part of an Observing System Simulation Experiment (OSSE) in support of the CLimate Absolute Radiance and Refractivity Observatory (CLARREO). Our framework interfaces with CMIP5 archive results and is agnostic to the choice of model. We simulated spectra from the INM-CM4 model (ECS of 2.08 °K/2xCO2), the MIROC5 model (ECS of 2.70 °K/2xCO2), and the CSIRO Mk3-6-0 (ECS of 4.08 °K/2xCO2) based on those models' integrations of the RCP8.5 scenario for the 21st Century. This approach allows us to explore how perfect data records can exclude models of lower or higher climate sensitivity. We find that spectral channels covering visible and near-infrared water-vapor overtone bands can potentially exclude a low or high sensitivity model with under 15 years' of absolutely-calibrated data. These different spectral channels are sensitive to model cloud radiative effect and cloud height changes, respectively. These unprecedented calculations lay the groundwork for spectral simulations of perturbed-physics ensembles in order to identify those shortwave observations that can help narrow the range in shortwave model feedbacks and ultimately help reduce the stubbornly-large range in model ECS.

Projected changes in extreme precipitation over Scotland and Northern England using a high-resolution regional climate model

NASA Astrophysics Data System (ADS)

Chan, Steven C.; Kahana, Ron; Kendon, Elizabeth J.; Fowler, Hayley J.

2018-03-01

The UK Met Office has previously conducted convection-permitting climate simulations over the southern UK (Kendon et al. in Nat Clim Change 4:570-576, 2014). The southern UK simulations have been followed up by a new set of northern UK simulations using the same model configuration. Here we present the mean and extreme precipitation projections from these new simulations. Relative to the southern UK, the northern UK projections show a greater summertime increase of return levels and extreme precipitation intensity in both 1.5 km convection-permitting and 12 km convection-parameterised simulations, but this increase is against a backdrop of large decreases in summertime mean precipitation and precipitation frequency. Similar to the southern UK, projected change is model resolution dependent and the convection-permitting simulation projects a larger intensification. For winter, return level increases are somewhat lower than for the southern UK. Analysis of model biases highlight challenges in simulating the diurnal cycle over high terrain, sensitivity to domain size and driving-GCM biases, and quality issues of radar precipitation observations, which are relevant to the wider regional climate modelling community.

Paleodynamics of large closed lakes as a standard for climate modeling data verification

NASA Astrophysics Data System (ADS)

Kislov, Alexander

2015-04-01

Observed and reconstructed variations of large lakes can serve as a standard for assessing the quality of the model run off simulated by climate models. It provides the opportunity to assess whether models designed for future scenarios are skillful in 'out-of sample' climate change experiments. Based on general ideas about the laws of temporal dynamics relating to massive inertial objects, slow changes of the lake level under the semi-steady climate state can be represented as resulting from the accumulation of small anomalies in the water regime; it appears like a kind of "self-developing" system. To test this hypothesis, the water balance model of the Caspian Sea (CS) was used. Time scale for the CS is estimated as ~20 years. Model is interpreted as stochastic, and from this perspective, it is a Langevin equation that incorporates the action of precipitation and evaporation like random white noise, so that the whole can be thought of as an analogue of Brownian motion. Under these conditions, the CS palaeostages during the Holocene is represented by a system undergoing random walk. It should be emphasized that modeling results are interpreted from the probabilistic point of view, despite the fact that the model is deterministically based on the physical law of conservation of water mass. Despite the CS, another candidate to be as a potential evaluation tool for climate model simulations is the Black Sea (BS) until its merger with the Mediterranean. Therefore, although the image of the CS, BS and other lakes within the climate models is very simplified (or absent), changes in the levels could be used to assess the ability of climate models to reproduce the water budget over the catchment areas. For the CS or the BS, they are the large parts of the East European Plane and can be as indicators of climate model quality. However, the use of reconstructed data of other closed lakes is problematic. It is due to its water budget components cannot be simulated with needed accuracy because they are either too small (the size of the largest closed Siberian lake (the Chany) is less than the typical grid box of climate model) or they are located in mountain region (like the Issyk-Kul Lake, located in the northern Tian Shan mountains) where the lake variability is determined by badly reproduced glacier melting.

Land surface modeling in convection permitting simulations

NASA Astrophysics Data System (ADS)

van Heerwaarden, Chiel; Benedict, Imme

2017-04-01

The next generation of weather and climate models permits convection, albeit at a grid spacing that is not sufficient to resolve all details of the clouds. Whereas much attention is being devoted to the correct simulation of convective clouds and associated precipitation, the role of the land surface has received far less interest. In our view, convective permitting simulations pose a set of problems that need to be solved before accurate weather and climate prediction is possible. The heart of the problem lies at the direct runoff and at the nonlinearity of the surface stress as a function of soil moisture. In coarse resolution simulations, where convection is not permitted, precipitation that reaches the land surface is uniformly distributed over the grid cell. Subsequently, a fraction of this precipitation is intercepted by vegetation or leaves the grid cell via direct runoff, whereas the remainder infiltrates into the soil. As soon as we move to convection permitting simulations, this precipitation falls often locally in large amounts. If the same land-surface model is used as in simulations with parameterized convection, this leads to an increase in direct runoff. Furthermore, spatially non-uniform infiltration leads to a very different surface stress, when scaled up to the course resolution of simulations without convection. Based on large-eddy simulation of realistic convection events at a large domain, this study presents a quantification of the errors made at the land surface in convection permitting simulation. It compares the magnitude of the errors to those made in the convection itself due to the coarse resolution of the simulation. We find that, convection permitting simulations have less evaporation than simulations with parameterized convection, resulting in a non-realistic drying of the atmosphere. We present solutions to resolve this problem.

Challenges in global modeling of wetland extent and wetland methane dynamics

NASA Astrophysics Data System (ADS)

Spahni, R.; Melton, J. R.; Wania, R.; Stocker, B. D.; Zürcher, S.; Joos, F.

2012-12-01

Global wetlands are known to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. Modelling of global wetland extent and wetland CH4 dynamics remains a challenge. Here we present results from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) that investigated our present ability to simulate large scale wetland characteristics (e.g. wetland type, water table, carbon cycling, gas transport, etc.) and corresponding CH4 emissions. Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The WETCHIMP experiments showed that while models disagree in spatial and temporal patterns of simulated CH4 emissions and wetland areal extent, they all do agree on a strong positive response to increased carbon dioxide concentrations. WETCHIMP made clear that we currently lack observation data sets that are adequate to evaluate model CH4 soil-atmosphere fluxes at a spatial scale comparable to model grid cells. Thus there are substantial parameter and structural uncertainties in large-scale CH4 emission models. As an illustration of the implications of CH4 emissions on climate we show results of the LPX-Bern model, as one of the models participating in WETCHIMP. LPX-Bern is forced with observed 20th century climate and climate output from an ensemble of five comprehensive climate models for a low and a high emission scenario till 2100 AD. In the high emission scenario increased substrate availability for methanogenesis due to a strong stimulation of net primary productivity, and faster soil turnover leads to an amplification of CH4 emissions with the sharpest increase in peatlands (+180% compared to present). Combined with prescribed anthropogenic CH4 emissions, simulated atmospheric CH4 concentration reaches ~4500 ppbv by 2100 AD, about 800 ppbv more than in standard IPCC scenarios. This represents a significant contribution to radiative forcing of global climate.

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

USGS Publications Warehouse

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Frid, Leonardo; Zhu, Zhiliang

2015-01-01

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

2014-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Predicted effects of gypsy moth defoliation and climate change on forest carbon dynamics in the New Jersey pine barrens.

PubMed

Kretchun, Alec M; Scheller, Robert M; Lucash, Melissa S; Clark, Kenneth L; Hom, John; Van Tuyl, Steve

2014-01-01

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years.

Predicted Effects of Gypsy Moth Defoliation and Climate Change on Forest Carbon Dynamics in the New Jersey Pine Barrens

PubMed Central

Kretchun, Alec M.; Scheller, Robert M.; Lucash, Melissa S.; Clark, Kenneth L.; Hom, John; Van Tuyl, Steve

2014-01-01

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years. PMID:25119162

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.

GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

NASA Astrophysics Data System (ADS)

Lin, S. J.

2015-12-01

The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.

The uncertainty of crop yield projections is reduced by improved temperature response functions.

PubMed

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rötter, Reimund P; Kimball, Bruce A; Ottman, Michael J; Wall, Gerard W; White, Jeffrey W; Reynolds, Matthew P; Alderman, Phillip D; Aggarwal, Pramod K; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andrew J; De Sanctis, Giacomo; Doltra, Jordi; Fereres, Elias; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A; Izaurralde, Roberto C; Jabloun, Mohamed; Jones, Curtis D; Kersebaum, Kurt C; Koehler, Ann-Kristin; Liu, Leilei; Müller, Christoph; Naresh Kumar, Soora; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E; Palosuo, Taru; Priesack, Eckart; Eyshi Rezaei, Ehsan; Ripoche, Dominique; Ruane, Alex C; Semenov, Mikhail A; Shcherbak, Iurii; Stöckle, Claudio; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wallach, Daniel; Wang, Zhimin; Wolf, Joost; Zhu, Yan; Asseng, Senthold

2017-07-17

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

NASA Technical Reports Server (NTRS)

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rotter, Reimund P.; Kimball, Bruce A.; Ottman, Michael J.; White, Jeffrey W.; Reynolds, Matthew P.;

Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; John, N. J.; van der Linden, M.

2015-12-01

Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Contrasting fire responses to climate and management: insights from two Australian ecosystems.

PubMed

King, Karen J; Cary, Geoffrey J; Bradstock, Ross A; Marsden-Smedley, Jonathan B

2013-04-01

This study explores effects of climate change and fuel management on unplanned fire activity in ecosystems representing contrasting extremes of the moisture availability spectrum (mesic and arid). Simulation modelling examined unplanned fire activity (fire incidence and area burned, and the area burned by large fires) for alternate climate scenarios and prescribed burning levels in: (i) a cool, moist temperate forest and wet moorland ecosystem in south-west Tasmania (mesic); and (ii) a spinifex and mulga ecosystem in central Australia (arid). Contemporary fire activity in these case study systems is limited, respectively, by fuel availability and fuel amount. For future climates, unplanned fire incidence and area burned increased in the mesic landscape, but decreased in the arid landscape in accordance with predictions based on these limiting factors. Area burned by large fires (greater than the 95th percentile of historical, unplanned fire size) increased with future climates in the mesic landscape. Simulated prescribed burning was more effective in reducing unplanned fire activity in the mesic landscape. However, the inhibitory effects of prescribed burning are predicted to be outweighed by climate change in the mesic landscape, whereas in the arid landscape prescribed burning reinforced a predicted decline in fire under climate change. The potentially contrasting direction of future changes to fire will have fundamentally different consequences for biodiversity in these contrasting ecosystems, and these will need to be accommodated through contrasting, innovative management solutions. © 2012 Blackwell Publishing Ltd.

Widespread, Very Heavy Precipitation Events in Contemporary and Scenario Summer Climates from NARCCAP Simulations

NASA Astrophysics Data System (ADS)

Kawazoe, S.; Gutowski, W. J., Jr.

2015-12-01

We analyze the ability of regional climate models (RCMs) to simulate very heavy daily precipitation and supporting processes for both contemporary and future-scenario simulations during summer (JJA). RCM output comes from North American Regional Climate Change Assessment Program (NARCCAP) simulations, which are all run at a spatial resolution of 50 km. Analysis focuses on the upper Mississippi basin for summer, between 1982-1998 for the contemporary climate, and 2052-2068 during the scenario climate. We also compare simulated precipitation and supporting processes with those obtained from observed precipitation and reanalysis atmospheric states. Precipitation observations are from the University of Washington (UW) and the Climate Prediction Center (CPC) gridded dataset. Utilizing two observational datasets helps determine if any uncertainties arise from differences in precipitation gridding schemes. Reanalysis fields come from the North American Regional Reanalysis. The NARCCAP models generally reproduce well the precipitation-vs.-intensity spectrum seen in observations, while producing overly strong precipitation at high intensity thresholds. In the future-scenario climate, there is a decrease in frequency for light to moderate precipitation intensities, while an increase in frequency is seen for the higher intensity events. Further analysis focuses on precipitation events exceeding the 99.5 percentile that occur simultaneously at several points in the region, yielding so-called "widespread events". For widespread events, we analyze local and large scale environmental parameters, such as 2-m temperature and specific humidity, 500-hPa geopotential heights, Convective Available Potential Energy (CAPE), vertically integrated moisture flux convergence, among others, to compare atmospheric states and processes leading to such events in the models and observations. The results suggest that an analysis of atmospheric states supporting very heavy precipitation events is a more fruitful path for understanding and detecting changes than simply looking at precipitation itself.

North-western Mediterranean sea-breeze circulation in a regional climate system model

NASA Astrophysics Data System (ADS)

Drobinski, Philippe; Bastin, Sophie; Arsouze, Thomas; Béranger, Karine; Flaounas, Emmanouil; Stéfanon, Marc

2017-04-01

In the Mediterranean basin, moisture transport can occur over large distance from remote regions by the synoptic circulation or more locally by sea breezes, driven by land-sea thermal contrast. Sea breezes play an important role in inland transport of moisture especially between late spring and early fall. In order to explicitly represent the two-way interactions at the atmosphere-ocean interface in the Mediterranean region and quantify the role of air-sea feedbacks on regional meteorology and climate, simulations at 20 km resolution performed with WRF regional climate model (RCM) and MORCE atmosphere-ocean regional climate model (AORCM) coupling WRF and NEMO-MED12 in the frame of HyMeX/MED-CORDEX are compared. One result of this study is that these simulations reproduce remarkably well the intensity, direction and inland penetration of the sea breeze and even the existence of the shallow sea breeze despite the overestimate of temperature over land in both simulations. The coupled simulation provides a more realistic representation of the evolution of the SST field at fine scale than the atmosphere-only one. Temperature and moisture anomalies are created in direct response to the SST anomaly and are advected by the sea breeze over land. However, the SST anomalies are not of sufficient magnitude to affect the large-scale sea-breeze circulation. The temperature anomalies are quickly damped by strong surface heating over land, whereas the water vapor mixing ratio anomalies are transported further inland. The inland limit of significance is imposed by the vertical dilution in a deeper continental boundary-layer.

Realism of the Indian Ocean Dipole in CMIP5 models, and the Implication for Climate Projections

NASA Astrophysics Data System (ADS)

Weller, E.; Cai, W.; Cowan, T.

2012-12-01

An assessment of how well climate models simulate the Indian Ocean Dipole (IOD) is undertaken using coupled models that have partaken in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Compared to CMIP3 models, no substantial improvement is evident in the simulation of the IOD pattern and/or amplitude during its peak season in austral spring (September-October-November, or SON). The majority of CMIP5 models generate a larger variance of sea surface temperature (SST) in the Sumatra-Java upwelling region and an IOD amplitude that is far greater than what is observed. Although the relationship between precipitation and the tropical Indian Ocean SST is well simulated, future projections of SON rainfall changes over IOD-influenced regions are intrinsically linked to the IOD-rainfall teleconnection and IOD amplitude in the model present-day climate. The diversity of the simulated IOD amplitudes in CMIP5 (and CMIP3) models which tend to be overly large, results in a wide range of future modelled SON rainfall trends over IOD-influenced regions. Our results highlight the importance of realistically simulating the present-day IOD properties and the caveat that needs to be exercised in interpreting climate projections in the IOD-affected regions.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Simulating a Dynamic Antarctic Ice Sheet in the Early to Middle Miocene

NASA Astrophysics Data System (ADS)

Gasson, E.; DeConto, R.; Pollard, D.; Levy, R. H.

2015-12-01

There are a variety of sources of geological data that suggest major variations in the volume and extent of the Antarctic ice sheet during the early to middle Miocene. Simulating such variability using coupled climate-ice sheet models is problematic due to a strong hysteresis effect caused by height-mass balance feedback and albedo feedback. This results in limited retreat of the ice sheet once it has reached the continental size, as likely occurred prior to the Miocene. Proxy records suggest a relatively narrow range of atmospheric CO2 during the early to middle Miocene, which exacerbates this problem. We use a new climate forcing which accounts for ice sheet-climate feedbacks through an asynchronous GCM-RCM coupling, which is able to better resolve the narrow Antarctic ablation zone in warm climate simulations. When combined with recently suggested mechanisms for retreat into subglacial basins due to ice shelf hydrofracture and ice cliff failure, we are able to simulate large-scale variability of the Antarctic ice sheet in the Miocene. This variability is equivalent to a seawater oxygen isotope signal of ~0.5 ‰, or a sea level equivalent change of ~35 m, for a range of atmospheric CO2 between 280 - 500 ppm.

Extreme weather: Subtropical floods and tropical cyclones

NASA Astrophysics Data System (ADS)

Shaevitz, Daniel A.

Extreme weather events have a large effect on society. As such, it is important to understand these events and to project how they may change in a future, warmer climate. The aim of this thesis is to develop a deeper understanding of two types of extreme weather events: subtropical floods and tropical cyclones (TCs). In the subtropics, the latitude is high enough that quasi-geostrophic dynamics are at least qualitatively relevant, while low enough that moisture may be abundant and convection strong. Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent, and large latent heat release. In the first part of this thesis, I examine the possible triggering of convection by the large-scale dynamics and investigate the coupling between the two. Specifically two examples of extreme precipitation events in the subtropics are analyzed, the 2010 and 2014 floods of India and Pakistan and the 2015 flood of Texas and Oklahoma. I invert the quasi-geostrophic omega equation to decompose the large-scale vertical motion profile to components due to synoptic forcing and diabatic heating. Additionally, I present model results from within the Column Quasi-Geostrophic framework. A single column model and cloud-revolving model are forced with the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. It is found that convection was triggered primarily by mechanically forced orographic ascent over the Himalayas during the India/Pakistan flood and by upper-level Potential Vorticity disturbances during the Texas/Oklahoma flood. Furthermore, a climate attribution analysis was conducted for the Texas/Oklahoma flood and it is found that anthropogenic climate change was responsible for a small amount of rainfall during the event but the intensity of this event may be greatly increased if it occurs in a future climate. In the second part of this thesis, I examine the ability of high-resolution global atmospheric models to simulate TCs. Specifically, I present an intercomparison of several models' ability to simulate the global characteristics of TCs in the current climate. This is a necessary first step before using these models to project future changes in TCs. Overall, the models were able to reproduce the geographic distribution of TCs reasonably well, with some of the models performing remarkably well. The intensity of TCs varied widely between the models, with some of this difference being due to model resolution.

Simulations of the future precipitation climate of the Central Andes using a coupled regional climate model

NASA Astrophysics Data System (ADS)

Nicholls, S.; Mohr, K. I.

2014-12-01

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models, although capable of resolving synoptic-scale South American climate features, are inadequate for fully-resolving the strong gradients between climate regimes and the complex orography which define the Tropical Andes given their low spatial and temporal resolution. Recent computational advances now make practical regional climate modeling with prognostic mesoscale atmosphere-ocean coupled models, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, to climate research. Previous work has shown COAWST to reasonably simulate the both the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual cycle of rainfall (Oct 2003 - Oct 2004) with historical climate model input. Using future global climate model input for COAWST, the present work involves year-long cycle spanning October to October for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. COAWST output is used to investigate how global climate change impacts the spatial distribution, precipitation rates, and diurnal cycle of precipitation patterns in the Central Andes vary in these yearly "snapshots". Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features (such as the Bolivian High).

Attribution of changes in precipitation patterns in African rainforests

NASA Astrophysics Data System (ADS)

Otto, F. E.; Jones, R. G.; Halladay, K.; Allen, M. R.

2013-12-01

The effects of projected future global and regional climate change on the water cycle and thus on global water security are amongst the most economically and politically important challenges that society faces in the 21st century. The provision of secure access to water resources and the protection of communities from water-related risks have emerged as top priorities amongst policymakers within the public and private sectors alike. Investment decisions on water infrastructure rely heavily on quantitative assessments of risks and uncertainties associated with future changes in water-related threats. Especially with the introduction of loss and damages on the agenda of the UNFCCC additionally the attribution of such changes to anthropogenic climate change and other external climate drivers is crucial. Probabilistic event attribution (PEA) provides a method of evaluating the extent to which human-induced climate change is affecting localised weather events and impacts of such events that relies on good observations as well as climate modelling. The overall approach is to simulate both, the statistics of observed weather, and the statistics of the weather that would have occurred had specific external drivers of climate change been absent. The majority of studies applying PEA have focused on quantifying attributable risk, with changes in risk depending on an assumption of 'all other things being equal', including natural drivers of climate change and vulnerability. Most previous attribution studies have focused on European extreme weather events, but the most vulnerable regions to climate change are in Asia and Africa. One of the most complex hydrological systems is the tropical rainforest, with the rainforests in tropical Africa being some of the most under-researched regions in the world. Research in the Amazonian rainforest suggests potential vulnerability to climate change. We will present results from using the large ensemble of atmosphere-only general circulation model (AGCM) simulations within the weather@home project, and analysing statistics of precipitation in the dry season of the Congo Basin rainforests. Because observed data sets in that region are of very poor quality we show how validation methods not only relying on such data have been used to investigate the applicability of PEA analysis from large model ensembles to this tropical region. Additionally we will present results for the same region but generated with a very large ensemble of regional climate simulations which allows analysing the importance of a realistic simulation of small scale precipitation processes for attribution studies in a tropical climate. We highlight that PEA analysis has the potential to provide valuable scientific evidence of recent or anticipated climatological changes in the water cycle, especially in regions with sparse observational data and unclear projections of future changes. However, the strong influence of SST tele-connection patterns on tropical precipitation provides more challenges in the set-up of attribution studies than studies on mid-latitude rainfall.

Regional Climate Modeling of Volcanic Eruptions and the Arctic Climate System: A Baffin Island Case Study

NASA Astrophysics Data System (ADS)

Losic, M.; Robock, A.

2010-12-01

It is well-understood that the effects of volcanic aerosol loading into the stratosphere are transient, with global cooling lasting only a few years after a single large eruption. Geological evidence collected from Northern Baffin Island, Canada, suggests ice cap growth began soon after a succession of several large eruptions in the 13th century, and they did not start to melt until roughly a century ago. We investigate which feedbacks allowed these ice caps to be maintained long after the transient forcing of the volcanic aerosols, by conducting sensitivity studies with the Weather Research and Forecasting (WRF) Model and Polar WRF, a version of WRF developed specifically for the polar regions. Results from an ensemble of month-long regional simulations over Baffin Island suggest that better treatment of snow and ice in Polar WRF improves our regional climate simulations. Thus, sensitivity test results from decade-long runs with imposed changes to boundary condition temperatures and carbon dioxide concentrations using Polar WRF are presented. Preliminary findings suggest that not only large scale but localized climate feedbacks play an important role in the responses of the ice caps after temperature and carbon dioxide forcings are applied. The results from these and further sensitivity tests will provide insight into the influence of regional feedbacks on the persistence of these ice caps long after the 13th century eruptions.

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations

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

Tang, Ying; Winkler, Julie; Zhong, Shiyuan

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We also assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereasmore » current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. Furthemore, the choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.« less

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations

DOE PAGES

Tang, Ying; Winkler, Julie; Zhong, Shiyuan; ...

2017-07-10

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We also assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereasmore » current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. Furthemore, the choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.« less

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

Hinzman, Larry D.; Bolton, William Robert; Young-Robertson, Jessica

This project improves meso-scale hydrologic modeling in the boreal forest by: (1) demonstrating the importance of capturing the heterogeneity of the landscape using small scale datasets for parameterization for both small and large basins; (2) demonstrating that in drier parts of the landscape and as the boreal forest dries with climate change, modeling approaches must consider the sensitivity of simulations to soil hydraulic parameters - such as residual water content - that are usually held constant. Thus, variability / flexibility in residual water content must be considered for accurate simulation of hydrologic processes in the boreal forest; (3) demonstrating thatmore » assessing climate change impacts on boreal forest hydrology through multiple model integration must account for direct effects of climate change (temperature and precipitation), and indirect effects from climate impacts on landscape characteristics (permafrost and vegetation distribution). Simulations demonstrated that climate change will increase runoff, but will increase ET to a greater extent and result in a drying of the landscape; and (4) vegetation plays a significant role in boreal hydrologic processes in permafrost free areas that have deciduous trees. This landscape type results in a decoupling of ET and precipitation, a tight coupling of ET and temperature, low runoff, and overall soil drying.« less

Evaluating Regional Scale Deforestation in the University of Victoria Earth System Climate Model

NASA Astrophysics Data System (ADS)

Longobardi, P.; Montenegro, A.; Beltrami, H.; Eby, M.

2011-12-01

Forests play a key role in influencing the Earths climate and at the same time are affected by changing climates. At this point it is estimated that 15-30% of Earths natural forests have already been converted to pasture or cropland. With such large amounts of forest being converted to cropland and grassland, it is important to determine the climatic effects of these actions. To date, most modelling efforts towards understanding the climatic effects of deforestation have simulated global deforestation or have been based on experiments where trees were removed from large areas, i.e. the entire Amazon or all forests above 50 N. Here we use the University of Victoria Earth System Climate model which contains a fully coupled carbon cycle, to evaluate the response to deforestation of 10%, 25%, 50% and 100% of the forested areas in three latitude bands: high (above 50°N), mid (above ± 30°) and low (between ± 30°). All simulations were transient simulations, allowing for changes to atmospheric forcings following the A2 emissions scenario. High latitude deforestation lead to cooling (-.05 °C to -0.45 °C) and increase in soil carbon (0.5 to 3 x 1014 kg) for all fractions of deforestation. Due in part to the increase in soil carbon, there was a decrease in atmospheric CO2 in the 50% (-20 ppm) and 100% (-60 ppm) high-latitude deforestation simulations. Low-latitude deforestation initially produced warming in all scenarios (0.1 to 0.25 °C), although all were colder (-0.05 to -0.1 °C) than the control by the end of the simulation. Atmospheric CO2 increased in all simulations (40 to 80 ppm), as well as soil carbon (2 to 16 x 1013 kg). Mid-latitude deforestation also lead to initial warming (0.01 to 0.1 °C) followed by cooling (-0.01 to -0.1 °C). Mid latitude deforestation also produced an increase in soil carbon (2 to 10 x 1013 kg), and atmospheric CO2 (0 to 25ppm). In all three latitude bands forest dieback was observed. Results range from 7% to 37% for high latitudes, 21% to 40% for mid latitudes and 36% to 70% in low latitudes.

Parameterization of Nitrogen Limitation for a Dynamic Ecohydrological Model: a Case Study from the Luquillo Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Bastola, S.; Bras, R. L.

2017-12-01

Feedbacks between vegetation and the soil nutrient cycle are important in ecosystems where nitrogen limits plant growth, and consequently influences the carbon balance in the plant-soil system. However, many biosphere models do not include such feedbacks, because interactions between carbon and the nitrogen cycle can be complex, and remain poorly understood. In this study we coupled a nitrogen cycle model with an eco-hydrological model by using the concept of carbon cost economics. This concept accounts for different "costs" to the plant of acquiring nitrogen via different pathways. This study builds on tRIBS-VEGGIE, a spatially explicit hydrological model coupled with a model of photosynthesis, stomatal resistance, and energy balance, by combining it with a model of nitrogen recycling. Driven by climate and spatially explicit data of soils, vegetation and topography, the model (referred to as tRIBS-VEGGIE-CN) simulates the dynamics of carbon and nitrogen in the soil-plant system; the dynamics of vegetation; and different components of the hydrological cycle. The tRIBS-VEGGIE-CN is applied in a humid tropical watershed at the Luquillo Critical Zone Observatory (LCZO). The region is characterized by high availability and cycling of nitrogen, high soil respiration rates, and large carbon stocks.We drive the model under contemporary CO2 and hydro-climatic forcing and compare results to a simulation under doubling CO2 and a range of future climate scenarios. The results with parameterization of nitrogen limitation based on carbon cost economics show that the carbon cost of the acquisition of nitrogen is 14% of the net primary productivity (NPP) and the N uptake cost for different pathways vary over a large range depending on leaf nitrogen content, turnover rates of carbon in soil and nitrogen cycling processes. Moreover, the N fertilization simulation experiment shows that the application of N fertilizer does not significantly change the simulated NPP. Furthermore, an experiment with doubling of the CO2 concentration level shows a significant increase of the NPP and turnover of plant tissues. The simulation with future climate scenarios shows consistent decrease in NPP but the uncertainties in projected NPP arising from selection of climate model and scenario is large.

Simulated Response of Mercury and Nitrogen to Land Management and Land Use Change in a Large River Basin

EPA Science Inventory

Increases in nitrogen cascading from headwater systems to coastal waterways and bioaccumulation of mercury in aquatic ecosystems have become primary environmental concerns in recent decades. Studies assessing the effects of land use or climate change on water quality in large ri...

Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts.

PubMed

Krause, Andreas; Pugh, Thomas A M; Bayer, Anita D; Li, Wei; Leung, Felix; Bondeau, Alberte; Doelman, Jonathan C; Humpenöder, Florian; Anthoni, Peter; Bodirsky, Benjamin L; Ciais, Philippe; Müller, Christoph; Murray-Tortarolo, Guillermo; Olin, Stefan; Popp, Alexander; Sitch, Stephen; Stehfest, Elke; Arneth, Almut

2018-07-01

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy. © 2018 John Wiley & Sons Ltd.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2010-02-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled substantial interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1 °C over land installations. In contrast, surface cooling exceeding 1 °C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2009-09-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled legitimate interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1°C over land installations. In contrast, surface cooling exceeding 1°C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Hadley circulation extent and strength in a wide range of simulated climates

NASA Astrophysics Data System (ADS)

D'Agostino, Roberta; Adam, Ori; Lionello, Piero; Schneider, Tapio

2017-04-01

Understanding the Hadley circulation (HC) dynamics is crucial because its changes affect the seasonal migration of the ITCZ, the extent of subtropical arid regions and the strength of the monsoons. Despite decades of study, the factors controlling its strength and extent have remained unclear. Here we analyse how HC strength and extent change over a wide range of climate conditions from the Last Glacial Maximum to future projections. The large climate change between paleoclimate simulations and future scenarios offers the chance to analyse robust HC changes and their link to large-scale factors. The HC shrinks and strengthens in the coldest simulation relative to the warmest. A progressive poleward shift of its edges is evident as the climate warms (at a rate of 0.35°lat./K in each hemisphere). The HC extent and strength both depend on the isentropic slope, which in turn is related to the meridional temperature gradient, subtropical static stability and tropopause height. In multiple robust regression analysis using these as predictors, we find that the tropical tropopause height does not add relevant information to the model beyond surface temperature. Therefore, primarily the static stability and secondarily the meridional temperature contrast together account for the bulk of the almost the total HC variance. However, the regressions leave some of the northern HC edge and southern HC strength variance unexplained. The effectiveness of this analysis is limited by the correlation among the predictors and their relationship with mean temperature. In fact, for all simulations, the tropical temperature explains well the variations of HC except its southern hemisphere intensity. Hence, it can be used as the sole predictor to diagnose the HC response to greenhouse-induced global warming. How to account for the evolution of the southern HC strength remains unclear, because of the large inter-model spread in this quantity.

TECA: A Parallel Toolkit for Extreme Climate Analysis

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

Prabhat, Mr; Ruebel, Oliver; Byna, Surendra

2012-03-12

We present TECA, a parallel toolkit for detecting extreme events in large climate datasets. Modern climate datasets expose parallelism across a number of dimensions: spatial locations, timesteps and ensemble members. We design TECA to exploit these modes of parallelism and demonstrate a prototype implementation for detecting and tracking three classes of extreme events: tropical cyclones, extra-tropical cyclones and atmospheric rivers. We process a modern TB-sized CAM5 simulation dataset with TECA, and demonstrate good runtime performance for the three case studies.

Climate and marine biogeochemistry during the Holocene from transient model simulations

NASA Astrophysics Data System (ADS)

Segschneider, Joachim; Schneider, Birgit; Khon, Vyacheslav

2018-06-01

Climate and marine biogeochemistry changes over the Holocene are investigated based on transient global climate and biogeochemistry model simulations over the last 9500 years. The simulations are forced by accelerated and non-accelerated orbital parameters, respectively, and atmospheric pCO2, CH4, and N2O. The analysis focusses on key climatic parameters of relevance to the marine biogeochemistry, and on the physical and biogeochemical processes that drive atmosphere-ocean carbon fluxes and changes in the oxygen minimum zones (OMZs). The simulated global mean ocean temperature is characterized by a mid-Holocene cooling and a late Holocene warming, a common feature among Holocene climate simulations which, however, contradicts a proxy-derived mid-Holocene climate optimum. As the most significant result, and only in the non-accelerated simulation, we find a substantial increase in volume of the OMZ in the eastern equatorial Pacific (EEP) continuing into the late Holocene. The concurrent increase in apparent oxygen utilization (AOU) and age of the water mass within the EEP OMZ can be attributed to a weakening of the deep northward inflow into the Pacific. This results in a large-scale mid-to-late Holocene increase in AOU in most of the Pacific and hence the source regions of the EEP OMZ waters. The simulated expansion of the EEP OMZ raises the question of whether the deoxygenation that has been observed over the last 5 decades could be a - perhaps accelerated - continuation of an orbitally driven decline in oxygen. Changes in global mean biological production and export of detritus remain of the order of 10 %, with generally lower values in the mid-Holocene. The simulated atmosphere-ocean CO2 flux would result in atmospheric pCO2 changes of similar magnitudes to those observed for the Holocene, but with different timing. More technically, as the increase in EEP OMZ volume can only be simulated with the non-accelerated model simulation, non-accelerated model simulations are required for an analysis of the marine biogeochemistry in the Holocene. Notably, the long control experiment also displays similar magnitude variability to the transient experiment for some parameters. This indicates that also long control runs are required when investigating Holocene climate and marine biogeochemistry, and that some of the Holocene variations could be attributed to internal variability of the atmosphere-ocean system.

A new space-time characterization of Northern Hemisphere drought in model simulations of the past and future as compared to the paleoclimate record

NASA Astrophysics Data System (ADS)

Coats, S.; Smerdon, J. E.; Stevenson, S.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The observational record, which provides only limited sampling of past climate variability, has made it difficult to quantitatively analyze the complex spatio-temporal character of drought. To provide a more complete characterization of drought, machine learning based methods that identify drought in three-dimensional space-time are applied to climate model simulations of the last millennium and future, as well as tree-ring based reconstructions of hydroclimate over the Northern Hemisphere extratropics. A focus is given to the most persistent and severe droughts of the past 1000 years. Analyzing reconstructions and simulations in this context allows for a validation of the spatio-temporal character of persistent and severe drought in climate model simulations. Furthermore, the long records provided by the reconstructions and simulations, allows for sufficient sampling to constrain projected changes to the spatio-temporal character of these features using the reconstructions. Along these lines, climate models suggest that there will be large increases in the persistence and severity of droughts over the coming century, but little change in their spatial extent. These models, however, exhibit biases in the spatio-temporal character of persistent and severe drought over parts of the Northern Hemisphere, which may undermine their usefulness for future projections. Despite these limitations, and in contrast to previous claims, there are no systematic changes in the character of persistent and severe droughts in simulations of the historical interval. This suggests that climate models are not systematically overestimating the hydroclimate response to anthropogenic forcing over this period, with critical implications for confidence in hydroclimate projections.

Impact of Climate Change on Projected Runoff from Mountain Snowpack of the King's Rivershed in California

NASA Astrophysics Data System (ADS)

Dialesandro, J.; Elias, E.; Rango, A.; Steele, C. M.

2016-12-01

The Central Valley of California, like most dryland agricultural areas in the Southwest United States, relies heavily on winter snowpack for water resources. Projections of future climate in the Sierra Mountains of California calls for a warmer climate regime that will impact the snowpack in the Sierra Mountains and thus the water supply for downstream agriculture and municipal uses within California's Central Valley. We simulate the impacts of two future time windows (2040-2069 and 2070-2099) and two future climate scenarios (RCP 4.5 and 8.5) on King's River using the Snowmelt Runoff Model. Snow depletion curves for 2010 are generated using MODIS and SRM parameters are adjusted until measured and simulated runoff reach acceptable agreement (R2 = .81). Future projections are based upon the multimodel mean of 20 CMIP5 models for seasonal future temperature and precipitation at high and low elevation points in the watershed from the multivariate adaptive constructed analogs (MACA) downscaled dataset. Changes in monthly inflow to Pineflat Reservoir, at the pour point of King's River watersheds, show a large decline in June and July inflow for all future climate simulations. Conversely, simulated spring inflow to Pineflat Reservoir is larger in the future. Impacts are most pronounced for end of the century (2070-2099), business as usual (RCP 8.5) simulation. Results are discussed with regard to implications for reservoir storage, groundwater recharge and creative solutions to cope with anticipated changes in runoff.

Climate Change and Hydrological Extreme Events - Risks and Perspectives for Water Management in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, R.

2017-12-01

There is as yet no confirmed knowledge whether and how climate change contributes to the magnitude and frequency of hydrological extreme events and how regional water management could adapt to the corresponding risks. The ClimEx project (2015-2019) investigates the effects of climate change on the meteorological and hydrological extreme events and their implications for water management in Bavaria and Québec. High Performance Computing is employed to enable the complex simulations in a hydro-climatological model processing chain, resulting in a unique high-resolution and transient (1950-2100) dataset of climatological and meteorological forcing and hydrological response: (1) The climate module has developed a large ensemble of high resolution data (12km) of the CRCM5 RCM for Central Europe and North-Eastern North America, downscaled from 50 members of the CanESM2 GCM. The dataset is complemented by all available data from the Euro-CORDEX project to account for the assessment of both natural climate variability and climate change. The large ensemble with several thousand model years provides the potential to catch rare extreme events and thus improves the process understanding of extreme events with return periods of 1000+ years. (2) The hydrology module comprises process-based and spatially explicit model setups (e.g. WaSiM) for all major catchments in Bavaria and Southern Québec in high temporal (3h) and spatial (500m) resolution. The simulations form the basis for in depth analysis of hydrological extreme events based on the inputs from the large climate model dataset. The specific data situation enables to establish a new method for `virtual perfect prediction', which assesses climate change impacts on flood risk and water resources management by identifying patterns in the data which reveal preferential triggers of hydrological extreme events. The presentation will highlight first results from the analysis of the large scale ClimEx model ensemble, showing the current and future ratio of natural variability and climate change impacts on meteorological extreme events. Selected data from the ensemble is used to drive a hydrological model experiment to illustrate the capacity to better determine the recurrence periods of hydrological extreme events under conditions of climate change.

Quantifying carbon budget and nitrous oxide emissions of terrestrial ecosystems in the Eurasian Arctic and the Dry Latitudinal Belt of Northern Eurasia

NASA Astrophysics Data System (ADS)

Zhuang, Q.; Yu, T.; Qu, Y.; Kicklighter, D. W.; Melillo, J. M.; Sokolov, A. P.; Reilly, J. M.; Monier, E.

2017-12-01

The largest increase of surface air temperature and related climate extremes has occurred in Northern Eurasia in recent decades, and is projected to continue during the 21st century. The changing climate will affect the fate of the large reservoir of organic matter stored in the region. Given a large amount of carbon-based gases CO2 and CH4 is exchanged between the atmosphere and land ecosystems, we hypothesize that the emissions of another potent greenhouse gas N2O are not small. This study used a process-based biogeochemistry model to estimate soil N2O emissions in Northern Eurasia for the latter half of the 20th century and the 21st century. We find that, in the latter half of the 20th century, there was a slight decreasing trend for the regional N2O emissions from 1.4 Tg N yr-1 to 1.17 Tg N yr-1. Boreal forests are the largest source due to their large area and high flux density. Two contrasting climate scenarios with no-policy and policy for future greenhouse gas emissions and with different climate sensitivities (high, medium and low) of a global climate model are used to drive the biogeochemistry model for the 21st century. Simulations indicate that there will be an increasing trend of N2O emissions under the no-policy climate scenario. By 2100, the emissions are 1.28, 1.40 and 1.73 Tg N yr-1 under climate conditions projected considering low, intermediate, and high level of climate sensitivity, respectively. In contrast, under the policy climate scenarios, there will be a decreasing trend and the emissions are 0.89, 1.02, and 1.06 Tg N yr-1 by 2100, respectively. This study suggests that the large increase of air temperature will enhance regional N2O emissions. Future changes in precipitation and depleting organic nitrogen pools also play a role in affecting future emission strengths in Northern Eurasia. In this presentation, we will also present ensemble simulations of carbon budget for the Dry Latitudinal Belt of Northern Eurasia under various future climate conditions.

Understanding observed and simulated historical temperature trends in California

NASA Astrophysics Data System (ADS)

Bonfils, C. J.; Duffy, P. B.; Santer, B. D.; Lobell, D. B.; Wigley, T. M.

2006-12-01

In our study, we attempt 1) to improve our understanding of observed historical temperature trends and their underlying causes in the context of regional detection of climate change and 2) to identify possible neglected forcings and errors in the model response to imposed forcings at the origin of inconsistencies between models and observations. From eight different observational datasets, we estimate California-average temperature trends over 1950- 1999 and compare them to trends from a suite of IPCC control simulations of natural internal climate variability. We find that the substantial night-time warming occurring from January to September is inconsistent with model-based estimates of natural internal climate variability, and thus requires one or more external forcing agents to be explained. In contrast, we find that a significant day-time warming occurs only from January to March. Our confidence in these findings is increased because there is no evidence that the models systematically underestimate noise on interannual and decadal timescales. However, we also find that IPCC simulations of the 20th century that include combined anthropogenic and natural forcings are not able to reproduce such a pronounced seasonality of the trends. Our first hypothesis is that the warming of Californian winters over the second half of the twentieth century is associated with changes in large-scale atmospheric circulation that are likely to be human-induced. This circulation change is underestimated in the historical simulations, which may explain why the simulated warming of Californian winters is too weak. We also hypothesize that the lack of a detectable observed increase in summertime maximum temperature arises from a cooling associated with large-scale irrigation. This cooling may have, until now, counteracted the warming induced by increasing greenhouse gases and urbanization effects. Omitting to include this forcing in the simulations can result in overestimating the summertime maximum temperature trends. We conduct an empirical study based on observed climate and irrigation changes to evaluate this assumption.

Natural and drought scenarios in an east central Amazon forest: Fidelity of the Community Land Model 3.5 with three biogeochemical models

NASA Astrophysics Data System (ADS)

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.

Large-scale assessment of present day and future groundwater recharge and its sensitivity to climate variability in Europe's karst regions

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Gleeson, T. P.; Wagener, T.; Wada, Y.

2016-12-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Regional assessment of the hydropower potential of rivers in West Africa

NASA Astrophysics Data System (ADS)

Kling, Harald; Stanzel, Philipp; Fuchs, Martin

2016-04-01

The 15 countries of the Economic Community of West African States (ECOWAS) face a constant shortage of energy supply, which limits sustained economic growth. Currently there are about 50 operational hydropower plants and about 40 more are under construction or refurbishment. The potential for future hydropower development - especially for small-scale plants in rural areas - is assumed to be large, but exact data are missing. This study supports the energy initiatives of the "ECOWAS Centre for Renewable Energy and Energy Efficiency" (ECREEE) by assessing the hydropower potential of all rivers in West Africa. For more than 500,000 river reaches the hydropower potential was computed from channel slope and mean annual discharge. In large areas there is a lack of discharge observations. Therefore, an annual water balance model was used to simulate discharge. The model domain covers 5 Mio km², including e.g. the Niger, Volta, and Senegal River basins. The model was calibrated with observed data of 410 gauges, using precipitation and potential evapotranspiration data as inputs. Historic variations of observed annual discharge between 1950 and 2010 are simulated well by the model. As hydropower plants are investments with a lifetime of several decades we also assessed possible changes in future discharge due to climate change. To this end the water balance model was driven with bias-corrected climate projections of 15 Regional Climate Models for two emission scenarios of the CORDEX-Africa ensemble. The simulation results for the river network were up-scaled to sub-areas and national summaries. This information gives a regional quantification of the hydropower potential, expected climate change impacts, as well as a regional classification for general suitability (or non-suitability) of hydropower plant size - from small-scale to large projects.

Precipitation Organization in a Warmer Climate

NASA Astrophysics Data System (ADS)

Rickenbach, T. M.; Nieto Ferreira, R.; Nissenbaum, M.

2014-12-01

This study will investigate changes in precipitation organization in a warmer climate using the Weather Research and Forecasting (WRF) model and CMIP-5 ensemble climate simulations. This work builds from an existing four-year NEXRAD radar-based precipitation climatology over the southeastern U.S. that uses a simple two-category framework of precipitation organization based on instantaneous precipitating feature size. The first category - mesoscale precipitation features (MPF) - dominates winter precipitation and is linked to the more predictable large-scale forcing provided by the extratropical cyclones. In contrast, the second category - isolated precipitation - dominates the summer season precipitation in the southern coastal and inland regions but is linked to less predictable mesoscale circulations and to local thermodynamics more crudely represented in climate models. Most climate modeling studies suggest that an accelerated water cycle in a warmer world will lead to an overall increase in precipitation, but few studies have addressed how precipitation organization may change regionally. To address this, WRF will simulate representative wintertime and summertime precipitation events in the Southeast US under the current and future climate. These events will be simulated in an environment resembling the future climate of the 2090s using the pseudo-global warming (PGW) approach based on an ensemble of temperature projections. The working hypothesis is that the higher water vapor content in the future simulation will result in an increase in the number of isolated convective systems, while MPFs will be more intense and longer-lasting. In the context of the seasonal climatology of MPF and isolated precipitation, these results have implications for assessing the predictability of future regional precipitation in the southeastern U.S.

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

2014-10-01

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

NASA Astrophysics Data System (ADS)

Strigaro, Daniele; Moretti, Massimiliano; Mattavelli, Matteo; Frigerio, Ivan; Amicis, Mattia De; Maggi, Valter

2016-09-01

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

Regional Climate Change across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations

NASA Astrophysics Data System (ADS)

Otte, T. L.; Nolte, C. G.; Otte, M. J.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

2011-12-01

Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. Preliminary results from downscaling NASA/GISS ModelE simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model will be used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0.

Assess Climate Change's Impact on Coastal Rivers using a Coupled Climate-Hydrology Model

NASA Astrophysics Data System (ADS)

Xue, Z. G.; Gochis, D.; Yu, W.; Zang, Z.; Sampson, K. M.; Keim, B. D.

2016-12-01

In this study we present a coupled climate-hydrological model reproducing the water cycle of three coastal river basins along the northern Gulf of Mexico for the past three decades (1985-2014). Model simulated climate condition, surface physics, and streamflow were well validated against in situ data and satellite-derived products, giving us the confidence that the newly developed WRF-Hydro model can be a robust tool for evaluating climate change's impact on hydrological regime. Trend analysis of model simulated monthly and annual time series indicates that local climate is getting hotter and dryer, specifically during the growing season. Wavelet analysis reveals that local evapotranspiration is strongly correlated with temperature, while soil moisture, water surplus, and streamflow are coupled with precipitation. In addition, local climate is closely correlated with large-scale climate dynamics such as AMO and ENSO. A possible change-point is detected around year 2004, after which, the monthly precipitation decreased by 14.2%, evapotranspiration increased by 2.9%, and water surplus decreased by 36.5%. The implication of the difference between the water surplus (runoff) calculated using the classic Thornthwaite method and river discharge estimated using streamflow records to the coastal environment is also discussed.

Volcanic Eruptions and Climate

NASA Technical Reports Server (NTRS)

LeGrande, Allegra N.; Anchukaitis, Kevin J.

2015-01-01

Volcanic eruptions represent some of the most climatically important and societally disruptive short-term events in human history. Large eruptions inject ash, dust, sulfurous gases (e.g. SO2, H2S), halogens (e.g. Hcl and Hbr), and water vapor into the Earth's atmosphere. Sulfurous emissions principally interact with the climate by converting into sulfate aerosols that reduce incoming solar radiation, warming the stratosphere and altering ozone creation, reducing global mean surface temperature, and suppressing the hydrological cycle. In this issue, we focus on the history, processes, and consequences of these large eruptions that inject enough material into the stratosphere to significantly affect the climate system. In terms of the changes wrought on the energy balance of the Earth System, these transient events can temporarily have a radiative forcing magnitude larger than the range of solar, greenhouse gas, and land use variability over the last millennium. In simulations as well as modern and paleoclimate observations, volcanic eruptions cause large inter-annual to decadal-scale changes in climate. Active debates persist concerning their role in longer-term (multi-decadal to centennial) modification of the Earth System, however.

Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liang, S.; Hurteau, M. D.; Westerling, A. L.

2014-12-01

The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

Evaluating simulated functional trait patterns and quantifying modelled trait diversity effects on simulated ecosystem fluxes

NASA Astrophysics Data System (ADS)

Pavlick, R.; Schimel, D.

2014-12-01

Dynamic Global Vegetation Models (DGVMs) typically employ only a small set of Plant Functional Types (PFTs) to represent the vast diversity of observed vegetation forms and functioning. There is growing evidence, however, that this abstraction may not adequately represent the observed variation in plant functional traits, which is thought to play an important role for many ecosystem functions and for ecosystem resilience to environmental change. The geographic distribution of PFTs in these models is also often based on empirical relationships between present-day climate and vegetation patterns. Projections of future climate change, however, point toward the possibility of novel regional climates, which could lead to no-analog vegetation compositions incompatible with the PFT paradigm. Here, we present results from the Jena Diversity-DGVM (JeDi-DGVM), a novel traits-based vegetation model, which simulates a large number of hypothetical plant growth strategies constrained by functional tradeoffs, thereby allowing for a more flexible temporal and spatial representation of the terrestrial biosphere. First, we compare simulated present-day geographical patterns of functional traits with empirical trait observations (in-situ and from airborne imaging spectroscopy). The observed trait patterns are then used to improve the tradeoff parameterizations of JeDi-DGVM. Finally, focusing primarily on the simulated leaf traits, we run the model with various amounts of trait diversity. We quantify the effects of these modeled biodiversity manipulations on simulated ecosystem fluxes and stocks for both present-day conditions and transient climate change scenarios. The simulation results reveal that the coarse treatment of plant functional traits by current PFT-based vegetation models may contribute substantial uncertainty regarding carbon-climate feedbacks. Further development of trait-based models and further investment in global in-situ and spectroscopic plant trait observations are needed.

Controls of multi-modal wave conditions in a complex coastal setting

USGS Publications Warehouse

Hegermiller, Christie; Rueda, Ana C.; Erikson, Li H.; Barnard, Patrick L.; Antolinez, J.A.A.; Mendez, Fernando J.

2017-01-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Controls of Multimodal Wave Conditions in a Complex Coastal Setting

NASA Astrophysics Data System (ADS)

Hegermiller, C. A.; Rueda, A.; Erikson, L. H.; Barnard, P. L.; Antolinez, J. A. A.; Mendez, F. J.

2017-12-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science

NASA Astrophysics Data System (ADS)

De, S.; Agarwal, N. K.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Sahai, A. K.

2018-04-01

The interaction between cloud and large scale circulation is much less explored area in climate science. Unfolding the mechanism of coupling between these two parameters is imperative for improved simulation of Indian summer monsoon (ISM) and to reduce imprecision in climate sensitivity of global climate model. This work has made an effort to explore this mechanism with CFSv2 climate model experiments whose cloud has been modified by changing the critical relative humidity (CRH) profile of model during ISM. Study reveals that the variable CRH in CFSv2 has improved the nonlinear interactions between high and low frequency oscillations in wind field (revealed as internal dynamics of monsoon) and modulates realistically the spatial distribution of interactions over Indian landmass during the contrasting monsoon season compared to the existing CRH profile of CFSv2. The lower tropospheric wind error energy in the variable CRH simulation of CFSv2 appears to be minimum due to the reduced nonlinear convergence of error to the planetary scale range from long and synoptic scales (another facet of internal dynamics) compared to as observed from other CRH experiments in normal and deficient monsoons. Hence, the interplay between cloud and large scale circulation through CRH may be manifested as a change in internal dynamics of ISM revealed from scale interactive quasi-linear and nonlinear kinetic energy exchanges in frequency as well as in wavenumber domain during the monsoon period that eventually modify the internal variance of CFSv2 model. Conversely, the reduced wind bias and proper modulation of spatial distribution of scale interaction between the synoptic and low frequency oscillations improve the eastward and northward extent of water vapour flux over Indian landmass that in turn give feedback to the realistic simulation of cloud condensates attributing improved ISM rainfall in CFSv2.

Representation of deforestation impacts on climate, water, and nutrient cycles in the ACME earth system model

NASA Astrophysics Data System (ADS)

Cai, X.; Riley, W. J.; Zhu, Q.

2017-12-01

Deforestation causes a series of changes to the climate, water, and nutrient cycles. Employing a state-of-the-art earth system model—ACME (Accelerated Climate Modeling for Energy), we comprehensively investigate the impacts of deforestation on these processes. We first assess the performance of the ACME Land Model (ALM) in simulating runoff, evapotranspiration, albedo, and plant productivity at 42 FLUXNET sites. The single column mode of ACME is then used to examine climate effects (temperature cooling/warming) and responses of runoff, evapotranspiration, and nutrient fluxes to deforestation. This approach separates local effects of deforestation from global circulation effects. To better understand the deforestation effects in a global context, we use the coupled (atmosphere, land, and slab ocean) mode of ACME to demonstrate the impacts of deforestation on global climate, water, and nutrient fluxes. Preliminary results showed that the land component of ACME has advantages in simulating these processes and that local deforestation has potentially large impacts on runoff and atmospheric processes.

Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology

USGS Publications Warehouse

Read, Jordan S.; Winslow, Luke A.; Hansen, Gretchen J. A.; Van Den Hoek, Jamon; Hanson, Paul C.; Bruce, Louise C; Markfort, Corey D.

2014-01-01

Changes in water temperatures resulting from climate warming can alter the structure and function of aquatic ecosystems. Lake-specific physical characteristics may play a role in mediating individual lake responses to climate. Past mechanistic studies of lake-climate interactions have simulated generic lake classes at large spatial scales or performed detailed analyses of small numbers of real lakes. Understanding the diversity of lake responses to climate change across landscapes requires a hybrid approach that couples site-specific lake characteristics with broad-scale environmental drivers. This study provides a substantial advancement in lake ecosystem modeling by combining open-source tools with freely available continental-scale data to mechanistically model daily temperatures for 2,368 Wisconsin lakes over three decades (1979-2011). The model accurately predicted observed surface layer temperatures (RMSE: 1.74°C) and the presence/absence of stratification (81.1% agreement). Among-lake coherence was strong for surface temperatures and weak for the timing of stratification, suggesting individual lake characteristics mediate some - but not all - ecologically relevant lake responses to climate.

Optimization of black-box models with uncertain climatic inputs—Application to sunflower ideotype design

PubMed Central

Picheny, Victor; Trépos, Ronan; Casadebaig, Pierre

2017-01-01

Accounting for the interannual climatic variations is a well-known issue for simulation-based studies of environmental systems. It often requires intensive sampling (e.g., averaging the simulation outputs over many climatic series), which hinders many sequential processes, in particular optimization algorithms. We propose here an approach based on a subset selection in a large basis of climatic series, using an ad-hoc similarity function and clustering. A non-parametric reconstruction technique is introduced to estimate accurately the distribution of the output of interest using only the subset sampling. The proposed strategy is non-intrusive and generic (i.e. transposable to most models with climatic data inputs), and can be combined to most “off-the-shelf” optimization solvers. We apply our approach to sunflower ideotype design using the crop model SUNFLO. The underlying optimization problem is formulated as a multi-objective one to account for risk-aversion. Our approach achieves good performances even for limited computational budgets, outperforming significantly standard strategies. PMID:28542198

Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

NASA Astrophysics Data System (ADS)

Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

2005-12-01

Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

NASA Technical Reports Server (NTRS)

Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;

Stationary Waves of the Ice Age Climate.

NASA Astrophysics Data System (ADS)

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.

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

Collins, William D; Johansen, Hans; Evans, Katherine J

We present a survey of physical and computational techniques that have the potential to con- tribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth include the capture of remote forcings of localized hydrological extreme events, an accurate representation of cloud features over a range of spatial and temporal scales, and parallel, large ensembles of simulations to more effectively explore model sensitivities and uncertainties. Numerical techniques, such as adaptive mesh refinement, implicit time integration, and separate treatment of fast physical time scales are enabling improved accuracy andmore » fidelity in simulation of dynamics and allow more complete representations of climate features at the global scale. At the same time, part- nerships with computer science teams have focused on taking advantage of evolving computer architectures, such as many-core processors and GPUs, so that these approaches which were previously considered prohibitively costly have become both more efficient and scalable. In combination, progress in these three critical areas is poised to transform climate modeling in the coming decades.« less

Impact of global warming on tropical cyclone genesis in coupled and forced simulations: role of SST spatial anomalies

NASA Astrophysics Data System (ADS)

Royer, Jean-François; Chauvin, Fabrice; Daloz, Anne-Sophie

2010-05-01

The response of tropical cyclones (TC) activity to global warming has not yet reached a clear consensus in the Fourth Assessment Report (AR4) published by the Intergovernmental Panel on Climate Change (IPCC, 2007) or in the recent scientific literature. Observed series are neither long nor reliable enough for a statistically significant detection and attribution of past TC trends, and coupled climate models give widely divergent results for the future evolution of TC activity in the different ocean basins. The potential importance of the spatial structure of the future SST warming has been pointed out by Chauvin et al. (2006) in simulations performed at CNRM with the ARPEGE-Climat GCM. The current presentation describes a new set of simulations that have been performed with the ARPEGE-Climat model to try to understand the possible role of SST patterns in the TC cyclogenesis response in 15 CMIP3 coupled simulations analysed by Royer et al (2009). The new simulations have been performed with the atmospheric component of the ARPEGE-Climat GCM forced in 10 year simulations by the SST patterns from each of 15 CMIP3 simulations with different climate model at the end of the 21st century according to scenario A2. The TC analysis is based on the computation of a Convective Yearly Genesis Parameter (CYGP) and the Genesis Potential Index (GPI). The computed genesis indices for each of the ARPEGE-Climat forced simulations is compared with the indices computed directly from the initial coupled simulation. The influence of SST patterns can then be more easily assessed since all the ARPEGE-Climat simulations are performed with the same atmospheric model, whereas the original simulations used models with different parameterization and resolutions. The analysis shows that CYGP or GPI anomalies obtained with ARPEGE are as variable between each other as those obtained originally by the different IPCC models. The variety of SST patterns used to force ARPEGE explains a large part of the dispersion, though for a given SST pattern, ARPEGE does not necessarily reproduce the anomaly produced originally by the IPCC model which produced the SST anomaly. Many factors can contribute to this discrepancy, but the most prominent seems to be the absence of coupling between the forced atmospheric ARPEGE simulation and the underlying ocean. When the atmospheric model is forced by prescribed SST anomalies some retroactions between cyclogenesis and ocean are missing. There are however areas over the globe were models agree about the CYGP or GPI anomalies induced by global warming, such as the Indian Ocean that shows a better coherency in the coupled and forced responses. This could be an indication that interaction between ocean and atmosphere is not as strong there as in the other basins. Details of the results for all the other ocean basins will be presented. References: Chauvin F. and J.-F. Royer and M. Déqué , 2006: Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Climate Dynamics 27(4), 377-399. IPCC [Intergovernmental Panel for Climate Change], Climate change 2007: The physical science basis, in: S. Solomon et al. (eds.), Cambridge University Press. Royer JF, F Chauvin, 2009: Response of tropical cyclogenesis to global warming in an IPCC AR-4 scenario assessed by a modified yearly genesis parameter. "Hurricanes and Climate Change", J. B. Elsner and T. H. Jagger (Eds.), Springer, ISBN: 978-0-387-09409-0, pp 213-234.

Regional Simulations of Stratospheric Lofting of Smoke Plumes

NASA Astrophysics Data System (ADS)

Stenchikov, G. L.; Fromm, M.; Robock, A.

2006-12-01

The lifetime and spatial distribution of sooty aerosols from multiple fires that would cause major climate impact were debated in studies of climatic and environmental consequences of a nuclear war in the 1980s. The Kuwait oil fires in 1991 did not show a cumulative effect of multiple smoke plumes on large-scale circulation systems and smoke was mainly dispersed in the middle troposphere. However, recent observations show that smoke from large forest fires can be directly injected into the lower stratosphere by strong pyro-convective storms. Smoke plumes in the upper troposphere can be partially mixed into the lower stratosphere because of the same heating and lofting effect that was simulated in large-scale nuclear winter simulations with interactive aerosols. However nuclear winter simulations were conducted using climate models with grid spacing of more than 100 km, which do not account for the fine-scale dynamic processes. Therefore in this study we conduct fine-scale regional simulations of the aerosol plume using the Regional Atmospheric Modeling System (RAMS) mesoscale model which was modified to account for radiatively interactive tracers. To resolve fine-scale dynamic processes we use horizontal grid spacing of 25 km and 60 vertical layers, and initiate simulations with the NCEP reanalysis fields. We find that dense aerosol layers could be lofted from 1 to a few km per day, but this critically depends on the optical depth of aerosol layer, single scatter albedo, and how fast the plume is being diluted. Kuwaiti plumes from different small-area fires reached only 5-6 km altitude and were probably diffused and diluted in the lower and middle troposphere. A plume of 100 km spatial scale initially developed in the upper troposphere tends to penetrate into the stratosphere. Short-term cloud resolving simulations of such a plume show that aerosol heating intensifies small-scale motions that tend to mix smoke polluted air into the lower stratosphere. Regional simulations allow us to more accurately estimate the rate of lifting and spreading of aerosol clouds. But they do not reveal any dynamic processes that could prevent heating and lofting of absorbing aerosols.

Impact of air-sea drag coefficient for latent heat flux on large scale climate in coupled and atmosphere stand-alone simulations

NASA Astrophysics Data System (ADS)

Torres, Olivier; Braconnot, Pascale; Marti, Olivier; Gential, Luc

2018-05-01

The turbulent fluxes across the ocean/atmosphere interface represent one of the principal driving forces of the global atmospheric and oceanic circulation. Despite decades of effort and improvements, representation of these fluxes still presents a challenge due to the small-scale acting turbulent processes compared to the resolved scales of the models. Beyond this subgrid parameterization issue, a comprehensive understanding of the impact of air-sea interactions on the climate system is still lacking. In this paper we investigates the large-scale impacts of the transfer coefficient used to compute turbulent heat fluxes with the IPSL-CM4 climate model in which the surface bulk formula is modified. Analyzing both atmosphere and coupled ocean-atmosphere general circulation model (AGCM, OAGCM) simulations allows us to study the direct effect and the mechanisms of adjustment to this modification. We focus on the representation of latent heat flux in the tropics. We show that the heat transfer coefficients are highly similar for a given parameterization between AGCM and OAGCM simulations. Although the same areas are impacted in both kind of simulations, the differences in surface heat fluxes are substantial. A regional modification of heat transfer coefficient has more impact than uniform modification in AGCM simulations while in OAGCM simulations, the opposite is observed. By studying the global energetics and the atmospheric circulation response to the modification, we highlight the role of the ocean in dampening a large part of the disturbance. Modification of the heat exchange coefficient modifies the way the coupled system works due to the link between atmospheric circulation and SST, and the different feedbacks between ocean and atmosphere. The adjustment that takes place implies a balance of net incoming solar radiation that is the same in all simulations. As there is no change in model physics other than drag coefficient, we obtain similar latent heat flux between coupled simulations with different atmospheric circulations. Finally, we analyze the impact of model tuning and show that it can offset part of the feedbacks.

Simulating adaptive wood harvest in a changing climate

NASA Astrophysics Data System (ADS)

Yousefpour, Rasoul; Nabel, Julia; Pongratz, Julia

2016-04-01

The world's forest experience substantial carbon exchange fluxes between land and atmosphere. Large carbon sinks occur in response to changes in environmental conditions (such as climate change and increased atmospheric CO2 concentrations), removing about one quarter of current anthropogenic CO2-emissions. Large sinks also occur due to regrowth of forest on areas of agricultural abandonment or forest management. Forest management, on the other hand, also leads to substantial amounts of carbon being eventually released to the atmosphere. Both sinks and sources attributable to forests are therefore dependent on the intensity of management. Forest management in turn depends on the availability of resources, which is influenced by environmental conditions and sustainability of management systems applied. Estimating future carbon fluxes therefore requires accounting for the interaction of environmental conditions, forest growth, and management. However, this interaction is not fully captured by current modeling approaches: Earth system models depict in detail interactions between climate, the carbon cycle, and vegetation growth, but use prescribed information on management. Resource needs and land management, however, are simulated by Integrated Assessment Models that typically only have coarse representations of the influence of environmental changes on vegetation growth and are typically based on the demand for wood driven by regional population growth and energy needs. Here we present a study that provides the link between environmental conditions, forest growth and management. We extend the land component JSBACH of the Max Planck Institute's Earth system model (MPI-ESM) to simulate potential wood harvest in response to altered growth conditions and thus as adaptive to changing climate and CO2 conditions. We apply the altered model to estimate potential wood harvest for future climates (representative concentration pathways, RCPs) for the management scenario of "sustained yields" (SY), i.e. that wood harvest is not allowed to reduce wood carbon stocks below their present-day average state. We find that the potentials for SY range from about 420 to 610 PgC cumulatively until 2100 depending on assumed future climate (RCPs 2.6, 4.5 or 8.5). They are thus substantially higher than the harvest prescribed in the context of the same RCPs for the coupled model intercomparison project (CMIP5), which ranged from about 130 to 210 PgC. The underlying drivers of the higher potentials of SY as compared to the RCP harvest are in all scenarios foremost avoided natural mortality, followed by avoided losses due to fire and windbreak. Further, usage of the increase in forest carbon stocks simulated with time under RCP harvest plays a large role in the first decades of the 21st century. The potential wood harvest that we simulate accounting for environmental changes does not include considerations on biodiversity and other ecosystem services or technical feasibility. However, the substantially higher simulated harvest from SY as compared to that prescribed from the RCPs and the difference found between climate scenarios highlights the need to account for effects of environmental changes on vegetation growth also in socio-economic models and thus the need for a consistent representation of climate-landuse interactions.

Regional climate model sensitivity to domain size

NASA Astrophysics Data System (ADS)

Leduc, Martin; Laprise, René

2009-05-01

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

Development of incremental dynamical downscaling and analysis system for regional scale climate change projections

NASA Astrophysics Data System (ADS)

Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio

2013-04-01

Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical downscaling (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new downscaling method is named as the incremental dynamical downscaling and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.

Potential climatic impacts and reliability of large-scale offshore wind farms

NASA Astrophysics Data System (ADS)

Wang, Chien; Prinn, Ronald G.

2011-04-01

The vast availability of wind power has fueled substantial interest in this renewable energy source as a potential near-zero greenhouse gas emission technology for meeting future world energy needs while addressing the climate change issue. However, in order to provide even a fraction of the estimated future energy needs, a large-scale deployment of wind turbines (several million) is required. The consequent environmental impacts, and the inherent reliability of such a large-scale usage of intermittent wind power would have to be carefully assessed, in addition to the need to lower the high current unit wind power costs. Our previous study (Wang and Prinn 2010 Atmos. Chem. Phys. 10 2053) using a three-dimensional climate model suggested that a large deployment of wind turbines over land to meet about 10% of predicted world energy needs in 2100 could lead to a significant temperature increase in the lower atmosphere over the installed regions. A global-scale perturbation to the general circulation patterns as well as to the cloud and precipitation distribution was also predicted. In the later study reported here, we conducted a set of six additional model simulations using an improved climate model to further address the potential environmental and intermittency issues of large-scale deployment of offshore wind turbines for differing installation areas and spatial densities. In contrast to the previous land installation results, the offshore wind turbine installations are found to cause a surface cooling over the installed offshore regions. This cooling is due principally to the enhanced latent heat flux from the sea surface to lower atmosphere, driven by an increase in turbulent mixing caused by the wind turbines which was not entirely offset by the concurrent reduction of mean wind kinetic energy. We found that the perturbation of the large-scale deployment of offshore wind turbines to the global climate is relatively small compared to the case of land-based installations. However, the intermittency caused by the significant seasonal wind variations over several major offshore sites is substantial, and demands further options to ensure the reliability of large-scale offshore wind power. The method that we used to simulate the offshore wind turbine effect on the lower atmosphere involved simply increasing the ocean surface drag coefficient. While this method is consistent with several detailed fine-scale simulations of wind turbines, it still needs further study to ensure its validity. New field observations of actual wind turbine arrays are definitely required to provide ultimate validation of the model predictions presented here.

Assessing the Impact of Laurentide Ice-sheet Topography on Glacial Climate

NASA Technical Reports Server (NTRS)

Ullman, D. J.; LeGrande, A. N.; Carlson, A. E.; Anslow, F. S.; Licciardi, J. M.

2014-01-01

Simulations of past climates require altered boundary conditions to account for known shifts in the Earth system. For the Last Glacial Maximum (LGM) and subsequent deglaciation, the existence of large Northern Hemisphere ice sheets caused profound changes in surface topography and albedo. While ice-sheet extent is fairly well known, numerous conflicting reconstructions of ice-sheet topography suggest that precision in this boundary condition is lacking. Here we use a high-resolution and oxygen-isotopeenabled fully coupled global circulation model (GCM) (GISS ModelE2-R), along with two different reconstructions of the Laurentide Ice Sheet (LIS) that provide maximum and minimum estimates of LIS elevation, to assess the range of climate variability in response to uncertainty in this boundary condition.We present this comparison at two equilibrium time slices: the LGM, when differences in ice-sheet topography are maximized, and 14 ka, when differences in maximum ice-sheet height are smaller but still exist. Overall, we find significant differences in the climate response to LIS topography, with the larger LIS resulting in enhanced Atlantic Meridional Overturning Circulation and warmer surface air temperatures, particularly over northeastern Asia and the North Pacific. These up- and downstream effects are associated with differences in the development of planetary waves in the upper atmosphere, with the larger LIS resulting in a weaker trough over northeastern Asia that leads to the warmer temperatures and decreased albedo from snow and sea-ice cover. Differences between the 14 ka simulations are similar in spatial extent but smaller in magnitude, suggesting that climate is responding primarily to the larger difference in maximum LIS elevation in the LGM simulations. These results suggest that such uncertainty in ice-sheet boundary conditions alone may significantly impact the results of paleoclimate simulations and their ability to successfully simulate past climates, with implications for estimating climate sensitivity to greenhouse gas forcing utilizing past climate states.

ARM Cloud Radar Simulator Package for Global Climate Models Value-Added Product

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

Zhang, Yuying; Xie, Shaocheng

It has been challenging to directly compare U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ground-based cloud radar measurements with climate model output because of limitations or features of the observing processes and the spatial gap between model and the single-point measurements. To facilitate the use of ARM radar data in numerical models, an ARM cloud radar simulator was developed to converts model data into pseudo-ARM cloud radar observations that mimic the instrument view of a narrow atmospheric column (as compared to a large global climate model [GCM] grid-cell), thus allowing meaningful comparison between model outputmore » and ARM cloud observations. The ARM cloud radar simulator value-added product (VAP) was developed based on the CloudSat simulator contained in the community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) (Bodas-Salcedo et al., 2011), which has been widely used in climate model evaluation with satellite data (Klein et al., 2013, Zhang et al., 2010). The essential part of the CloudSat simulator is the QuickBeam radar simulator that is used to produce CloudSat-like radar reflectivity, but is capable of simulating reflectivity for other radars (Marchand et al., 2009; Haynes et al., 2007). Adapting QuickBeam to the ARM cloud radar simulator within COSP required two primary changes: one was to set the frequency to 35 GHz for the ARM Ka-band cloud radar, as opposed to 94 GHz used for the CloudSat W-band radar, and the second was to invert the view from the ground to space so as to attenuate the beam correctly. In addition, the ARM cloud radar simulator uses a finer vertical resolution (100 m compared to 500 m for CloudSat) to resolve the more detailed structure of clouds captured by the ARM radars. The ARM simulator has been developed following the COSP workflow (Figure 1) and using the capabilities available in COSP wherever possible. The ARM simulator is written in Fortran 90, just as is the COSP. It is incorporated into COSP to facilitate use by the climate modeling community. In order to evaluate simulator output, the observational counterpart of the simulator output, radar reflectivity-height histograms (CFAD) is also generated from the ARM observations. This report includes an overview of the ARM cloud radar simulator VAP and the required simulator-oriented ARM radar data product (radarCFAD) for validating simulator output, as well as a user guide for operating the ARM radar simulator VAP.« less

Warmer and drier conditions and nitrogen fertilizer application altered methanotroph abundance and methane emissions in a vegetable soil.

PubMed

Ran, Yu; Xie, Jianli; Xu, Xiaoya; Li, Yong; Liu, Yapeng; Zhang, Qichun; Li, Zheng; Xu, Jianming; Di, Hongjie

2017-01-01

Methane (CH 4 ) is a potent greenhouse gas, and soil can both be a source and sink for atmospheric CH 4 . It is not clear how future climate change may affect soil CH 4 emissions and related microbial communities. The aim of this study was to determine the interactive effects of a simulated warmer and drier climate scenarios and the application of different nitrogen (N) sources (urea and manure) on CH 4 emissions and related microbial community abundance in a vegetable soil. Greenhouses were used to control simulated climate conditions which gave 2.99 °C warmer and 6.2% lower water content conditions. The field experiment was divided into two phases. At the beginning of phase II, half of the greenhouses were removed to study possible legacy effects of the simulated warmer and drier conditions. The responses in methanogen and methanotroph abundance to a simulated climate change scenario were determined using real-time PCR. The results showed that the simulated warmer and drier conditions in the greenhouses significantly decreased CH 4 emissions largely due to the lower soil moisture content. For the same reason, CH 4 emissions of treatments in phase I were much lower than the same treatments in phase II. The abundance of methanotrophs showed a more significant response than methanogens to the simulated climate change scenario, increasing under simulated drier conditions. Methanogenic community abundance remained low, except where manure was applied which provided a source of organic C that stimulated methanogen growth. Soil moisture content was a major driver for methanotroph abundance and strongly affected CH 4 emissions. The application of N source decreased CH 4 emissions probably because of increased methanotrophic activity. CH 4 emissions were positively correlated to methanogenic abundance and negatively correlated to methanotrophic abundance. These results demonstrate that projected future climate change conditions can have a feedback impact on CH 4 emissions from the soil by altering soil conditions (particularly soil moisture) and related microbial communities.

Reanalysis of Mariner 9 UV spectrometer data for ozone, cloud, and dust abundances, and their interaction over climate timescales

NASA Technical Reports Server (NTRS)

Lindner, Bernhard Lee

1992-01-01

Research activities to date are discussed. Selected Mariner 9 UV spectra were obtained. Radiative transfer models were updated and then exercised to simulate spectra. Simulated and observed spectra compare favorably. It is noted that large amounts of ozone are currently not retrieved with reflectance spectroscopy, raising large doubts about earlier published ozone abundances. As these published abundances have been used as a benchmark for all theoretical photochemical models of Mars, this deserves further exploration. Three manuscripts were published, and one is in review. Papers were presented and published at three conferences, and are planned for five more conferences in the next six months. The research plan for the next reporting period is discussed and involves continuing studies of reflectance spectroscopy, further examination of Mariner 9 data, and climate change studies of ozone.

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

Regional carbon cycle responses to 25 years of variation in climate and disturbance in the US Pacific Northwest

Treesearch

David P. Turner; William D. Ritts; Robert E. Kennedy; Andrew N. Gray; Zhiqiang Yang

2016-01-01

Variation in climate, disturbance regime, and forest management strongly influence terrestrial carbon sources and sinks. Spatially distributed, process-based, carbon cycle simulation models provide a means to integrate information on these various influences to estimate carbon pools and flux over large domains. Here we apply the Biome-BGC model over the four-state...

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.

Regional variability of the frequency distribution of daily precipitation and the synoptic characteristics of heavy precipitation events in present and future climate simulations

NASA Astrophysics Data System (ADS)

DeAngelis, Anthony M.

Changes in the characteristics of daily precipitation in response to global warming may have serious impacts on human life and property. An analysis of precipitation in climate models is performed to evaluate how well the models simulate the present climate and how precipitation may change in the future. Models participating in phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) have substantial biases in their simulation of heavy precipitation intensity over parts of North America during the 20th century. Despite these biases, the large-scale atmospheric circulation accompanying heavy precipitation is either simulated realistically or the strength of the circulation is overestimated. The biases are not related to the large-scale flow in a simple way, pointing toward the importance of other model deficiencies, such as coarse horizontal resolution and convective parameterizations, for the accurate simulation of intense precipitation. Although the models may not sufficiently simulate the intensity of precipitation, their realistic portrayal of the large-scale circulation suggests that projections of future precipitation may be reliable. In the CMIP5 ensemble, the distribution of daily precipitation is projected to undergo substantial changes in response to future atmospheric warming. The regional distribution of these changes was investigated, revealing that dry days and days with heavy-extreme precipitation are projected to increase at the expense of light-moderate precipitation over much of the middle and low latitudes. Such projections have serious implications for future impacts from flood and drought events. In other places, changes in the daily precipitation distribution are characterized by a shift toward either wetter or drier conditions in the future, with heavy-extreme precipitation projected to increase in all but the driest subtropical subsidence regions. Further analysis shows that increases in heavy precipitation in midlatitudes are largely explained by thermodynamics, including increases in atmospheric water vapor. However, in low latitudes and northern high latitudes, changes in vertical velocity accompanying heavy precipitation are also important. The strength of the large-scale atmospheric circulation is projected to change in accordance with vertical velocity in many places, though the circulation patterns, and therefore physical mechanisms that generate heavy precipitation, may remain the same.

Modeled impact of anthropogenic land cover change on climate

USGS Publications Warehouse

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.

Long-term climate change commitment and reversibility: An EMIC intercomparison

NASA Astrophysics Data System (ADS)

Zickfeld, K.; Eby, M.; Weaver, A. J.

2012-12-01

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to: (i) quantify the climate change "commitment" of a range of radiative forcing trajectories, and (ii) explore the extent to which climate change is reversible if atmospheric CO2 is left to evolve freely or is artificially restored to pre-industrial levels. All commitment simulations follow the four Representative Concentration Pathways (RCPs) and their extensions to 2300. Most EMICs simulate significant surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The additional warming by the year 3000 is 0.0-0.6 °C for RCP4.5 and 0.0-1.2 °C for RCP8.5, and the additional sea level rise is 0.1-1.0 m for RCP4.5 and 0.4-2.6 m for RCP8.5. Elimination of anthropogenic CO2 emissions results in constant or slightly decreasing surface air temperature in all EMICs. Thermosteric sea level rise continues after elimination of anthropogenic CO2 emissions, with additional sea level rise between 2300 and 3000 of 0.0-0.5 m for RCP4.5 and 0.2-2.4 m for RCP8.5. The largest warming and sea level rise commitment are simulated for the case with constant year-2300 CO2 emissions. Restoration of atmospheric CO2 from RCP to pre-industrial levels over 100-1000 years does not result in the simultaneous return to pre-industrial climate conditions, as surface air temperature and sea level rise exhibit a substantial time lag relative to atmospheric CO2, and requires large artificial removal of CO2 from the atmosphere. Results of the climate change commitment and reversibility simulations differ widely among EMICs, both in the physical and biogeochemical response. Particularly large differences are identified in the response of the terrestrial carbon cycle to atmospheric CO2 and climate, highlighting the need for improved understanding and representation of land carbon cycle processes in Earth System models.

Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices

Treesearch

Haiganoush K. Preisler; Shyh-Chin Chen; Francis Fujioka; John W. Benoit; Anthony L. Westerling

2008-01-01

The National Fire Danger Rating System indices deduced from a regional simulation weather model were used to estimate probabilities and numbers of large fire events on monthly and 1-degree grid scales. The weather model simulations and forecasts are ongoing experimental products from the Experimental Climate Prediction Center at the Scripps Institution of Oceanography...

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

A High-Resolution WRF Tropical Channel Simulation Driven by a Global Reanalysis

NASA Astrophysics Data System (ADS)

Holland, G.; Leung, L.; Kuo, Y.; Hurrell, J.

2006-12-01

Since 2003, NCAR has invested in the development and application of Nested Regional Climate Model (NRCM) based on the Weather Research and Forecasting (WRF) model and the Community Climate System Model, as a key component of the Prediction Across Scales Initiative. A prototype tropical channel model has been developed to investigate scale interactions and the influence of tropical convection on large scale circulation and tropical modes. The model was developed based on the NCAR Weather Research and Forecasting Model (WRF), configured as a tropical channel between 30 ° S and 45 ° N, wide enough to allow teleconnection effects over the mid-latitudes. Compared to the limited area domain that WRF is typically applied over, the channel mode alleviates issues with reflection of tropical modes that could result from imposing east/west boundaries. Using a large amount of available computing resources on a supercomputer (Blue Vista) during its bedding in period, a simulation has been completed with the tropical channel applied at 36 km horizontal resolution for 5 years from 1996 to 2000, with large scale circulation provided by the NCEP/NCAR global reanalysis at the north/south boundaries. Shorter simulations of 2 years and 6 months have also been performed to include two-way nests at 12 km and 4 km resolution, respectively, over the western Pacific warm pool, to explicitly resolve tropical convection in the Maritime Continent. The simulations realistically captured the large-scale circulation including the trade winds over the tropical Pacific and Atlantic, the Australian and Asian monsoon circulation, and hurricane statistics. Preliminary analysis and evaluation of the simulations will be presented.

Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

2016-10-01

We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

NASA Astrophysics Data System (ADS)

Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

2016-09-01

Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

Observed and Simulated Radiative and Microphysical Properties of Tropical Convective Storms

NASA Technical Reports Server (NTRS)

DelGenio, Anthony D.; Hansen, James E. (Technical Monitor)

2001-01-01

Increases in the ice content, albedo and cloud cover of tropical convective storms in a warmer climate produce a large negative contribution to cloud feedback in the GISS GCM. Unfortunately, the physics of convective upward water transport, detrainment, and ice sedimentation, and the relationship of microphysical to radiative properties, are all quite uncertain. We apply a clustering algorithm to TRMM satellite microwave rainfall retrievals to identify contiguous deep precipitating storms throughout the tropics. Each storm is characterized according to its size, albedo, OLR, rain rate, microphysical structure, and presence/absence of lightning. A similar analysis is applied to ISCCP data during the TOGA/COARE experiment to identify optically thick deep cloud systems and relate them to large-scale environmental conditions just before storm onset. We examine the statistics of these storms to understand the relative climatic roles of small and large storms and the factors that regulate convective storm size and albedo. The results are compared to GISS GCM simulated statistics of tropical convective storms to identify areas of agreement and disagreement.

Regional impacts of Atlantic Forest deforestation on climate and vegetation dynamics

NASA Astrophysics Data System (ADS)

Holm, J. A.; Chambers, J. Q.

2012-12-01

The Brazilian Atlantic Forest was a large and important forest due to its high biodiversity, endemism, range in climate, and complex geography. The original Atlantic Forest was estimated to cover 150 million hectares, spanning large latitudinal, longitudinal, and elevation gradients. This unique environment helped contribute to a diverse assemblage of plants, mammals, birds, and reptiles. Unfortunately, due to land conversion into agriculture, pasture, urban areas, and increased forest fragmentation, only ~8-10% of the original Atlantic Forest remains. Tropical deforestation in the Americas can have considerable effects on local to global climates, and surrounding vegetation growth and survival. This study uses a fully coupled, global climate model (Community Earth System Model, CESM v.1.0.1) to simulate the full removal of the historical Atlantic Forest, and evaluate the regional climatic and vegetation responses due to deforestation. We used the fully coupled atmosphere and land surface components in CESM, and a partially interacting ocean component. The vegetated grid cell portion of the land surface component, the Community Landscape Model (CLM), is divided into 4 of 16 plant functional types (PFTs) with vertical layers of canopy, leaf area index, soil physical properties, and interacting hydrological features all tracking energy, water, and carbon state and flux variables, making CLM highly capable in predicting the complex nature and outcomes of large-scale deforestation. The Atlantic Forest removal (i.e. deforestation) was conducted my converting all woody stem PFTs to grasses in CLM, creating a land-use change from forest to pasture. By comparing the simulated historical Atlantic Forest (pre human alteration) to a deforested Atlantic Forest (close to current conditions) in CLM and CESM we found that live stem carbon, NPP (gC m-2 yr-1), and other vegetation dynamics inside and outside the Atlantic Forest region were largely altered. In addition to vegetation effects, regional surface air temperature (C°), precipitation (mm day-1), and emitted longwave radiation (W m-2) were highly affected in the location of the removed forest, and throughout surrounding areas of South America. For example climate patterns of increased temperature and decreased precipitation were affected as far as the Amazon Forest region. The use of fully coupled global climate and terrestrial models to study the effects of large-scale forest removal have been rarely applied. This study successfully showed the valuation of an important tropical forest, and the consequences of large deforestation through the reporting of complex earth-atmosphere interactions between vegetation dynamics and climate.

Using nudging to improve global-regional dynamic consistency in limited-area climate modeling: What should we nudge?

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2015-03-01

Regional climate modelling sometimes requires that the regional model be nudged towards the large-scale driving data to avoid the development of inconsistencies between them. These inconsistencies are known to produce large surface temperature and rainfall artefacts. Therefore, it is essential to maintain the synoptic circulation within the simulation domain consistent with the synoptic circulation at the domain boundaries. Nudging techniques, initially developed for data assimilation purposes, are increasingly used in regional climate modeling and offer a workaround to this issue. In this context, several questions on the "optimal" use of nudging are still open. In this study we focus on a specific question which is: What variable should we nudge? in order to maintain the consistencies between the regional model and the driving fields as much as possible. For that, a "Big Brother Experiment", where a reference atmospheric state is known, is conducted using the weather research and forecasting (WRF) model over the Euro-Mediterranean region. A set of 22 3-month simulations is performed with different sets of nudged variables and nudging options (no nudging, indiscriminate nudging, spectral nudging) for summer and winter. The results show that nudging clearly improves the model capacity to reproduce the reference fields. However the skill scores depend on the set of variables used to nudge the regional climate simulations. Nudging the tropospheric horizontal wind is by far the key variable to nudge to simulate correctly surface temperature and wind, and rainfall. To a lesser extent, nudging tropospheric temperature also contributes to significantly improve the simulations. Indeed, nudging tropospheric wind or temperature directly impacts the simulation of the tropospheric geopotential height and thus the synoptic scale atmospheric circulation. Nudging moisture improves the precipitation but the impact on the other fields (wind and temperature) is not significant. As an immediate consequence, nudging tropospheric wind, temperature and moisture in WRF gives by far the best results with respect to the Big-Brother simulation. However, we noticed that a residual bias of the geopotential height persists due to a negative surface pressure anomaly which suggests that surface pressure is the missing quantity to nudge. Nudging the geopotential has no discernible effect. Finally, it should be noted that the proposed strategy ensures a dynamical consistency between the driving field and the simulated small-scale field but it does not ensure the best "observed" fine scale field because of the possible impact of incorrect driving large-scale field.

Climate variability in China during the last millennium based on reconstructions and simulations

NASA Astrophysics Data System (ADS)

García-Bustamante, E.; Luterbacher, J.; Xoplaki, E.; Werner, J. P.; Jungclaus, J.; Zorita, E.; González-Rouco, J. F.; Fernández-Donado, L.; Hegerl, G.; Ge, Q.; Hao, Z.; Wagner, S.

2012-04-01

Multi-decadal to centennial climate variability in China during the last millennium is analysed. We compare the low frequency temperature and precipitation variations from proxy-based reconstructions and palaeo-simulations from climate models. Focusing on the regional responses to the global climate evolution is of high relevance due to the complexity of the interactions between physical mechanisms at different spatio-temporal scales and the potential severity of the derived multiple socio-economic impacts. China stands out as a particularly interesting region, not only due to its complex climatic features, ranging from the semiarid northwestern Tibetan Plateau to the tropical monsoon southeastern climates, but also because of its wealth of proxy data. However, comprehensive assessments of proxy- and model-based information about palaeo-climatic variations in China are, to our knowledge, still lacking. In addition, existing studies depict a general lack of agreement between reconstructions and model simulations with respect to the amplitude and/or occurrence of warmer/colder and wetter/drier periods during the last millennium and the magnitude of the 20th century warming trend. Furthermore, these works are mainly focused on eastern China regions that show a denser proxy data coverage. We investigate how last millennium palaeo-runs compare to independent evidences from an unusual large number of proxy reconstructions over the study area by employing state-of-the-art palaeo-simulations with multi-member ensembles from the CMIP5/PMIP3 project. This shapes an ideal frame for the evaluation of the uncertainties associated to internal and intermodel model variability. Preliminary results indicate that despite the strong regional and seasonal dependencies, temperature reconstructions in China evidence coherent variations among all regions at centennial scale, especially during the last 500 years. The spatial consistency of low frequency temperature changes is an interesting aspect and of relevance for the assessment of forced climatic responses in China. The comparison between reconstructions and simulations from climate models show that, apart from the 20th century warming trend, the variance of the reconstructed mean China temperature lies in the envelope (uncertainty range) spanned by the temperature simulations. The uncertainty arises from the internal (multi-member ensembles) and the inter-model variability. Centennial variations tend to be broadly synchronous in the reconstructions and the simulations. However, the simulations show a delay of the warm period 1000-1300 AD. This warm medieval period both in the simulations and the reconstructions is followed by cooling till 1800 AD. Based on the simulations, the recent warming is not unprecedented and is comparable to the medieval warming. Further steps of this study will address the individual contribution of anthropogenic and natural forcings on climate variability and change during the last millennium in China. We will make use of of models that provide runs including single forcings (fingerprints) for the attribution of climate variations from decadal to multi-centennial time scales. With this aim, we will implement statistical techniques for the detection of optimal signal-to-noise-ratio between external forcings and internal variability of reconstructed temperatures and precipitation. To apply these approaches the uncertainties associated with both reconstructions and simulations will be estimated. The latter will shed some light into the mechanisms behind current climate evolution and will help to constrain uncertainties in the sensitivity of model simulations to increasing CO2 scenarios of future climate change. This work will also contribute to the overall aims of the PAGES 2k initiative in Asia (http://www.pages.unibe.ch/workinggroups/2k-network)

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

The Aqua-Planet Experiment (APE): CONTROL SST Simulation

NASA Technical Reports Server (NTRS)

Blackburn, Michael; Williamson, David L.; Nakajima, Kensuke; Ohfuchi, Wataru; Takahashi, Yoshiyuki O.; Hayashi, Yoshi-Yuki; Nakamura, Hisashi; Ishiwatari, Masaki; Mcgregor, John L.; Borth, Hartmut;

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

A new framework for the analysis of continental-scale convection-resolving climate simulations

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Charpilloz, C.; Arteaga, A.; Ban, N.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Schulthess, T. C.; Christoph, S.

2017-12-01

High-resolution climate simulations at horizontal resolution of O(1-4 km) allow explicit treatment of deep convection (thunderstorms and rain showers). Explicitly treating convection by the governing equations reduces uncertainties associated with parametrization schemes and allows a model formulation closer to physical first principles [1,2]. But kilometer-scale climate simulations with long integration periods and large computational domains are expensive and data storage becomes unbearably voluminous. Hence new approaches to perform analysis are required. In the crCLIM project we propose a new climate modeling framework that allows scientists to conduct analysis at high spatial and temporal resolution. We tackle the computational cost by using the largest available supercomputers such as hybrid CPU-GPU architectures. For this the COSMO model has been adapted to run on such architectures [2]. We then alleviate the I/O-bottleneck by employing a simulation data-virtualizer (SDaVi) that allows to trade-off storage (space) for computational effort (time). This is achieved by caching the simulation outputs and efficiently launching re-simulations in case of cache misses. All this is done transparently from the analysis applications [3]. For the re-runs this approach requires a bit-reproducible version of COSMO. That is to say a model that produces identical results on different architectures to ensure coherent recomputation of the requested data [4]. In this contribution we present a version of SDaVi, a first performance model, and a strategy to obtain bit-reproducibility across hardware architectures.[1] N. Ban, J. Schmidli, C. Schär. Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos., 7889-7907, 2014.[2] D. Leutwyler, O. Fuhrer, X. Lapillonne, D. Lüthi, C. Schär. Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19. Geosci. Model Dev, 3393-3412, 2016.[3] S. Di Girolamo, P. Schmid, T. Schulthess, T. Hoefler. Virtualized Big Data: Reproducing Simulation Output on Demand. Submit. to the 23rd ACM Symposium on PPoPP 18, Vienna, Austria.[4] A. Arteaga, O. Fuhrer, T. Hoefler. Designing Bit-Reproducible Portable High-Performance Applications. IEEE 28th IPDPS, 2014.

Identifying a key physical factor sensitive to the performance of Madden-Julian oscillation simulation in climate models

NASA Astrophysics Data System (ADS)

Kim, Go-Un; Seo, Kyong-Hwan

2018-01-01

A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.

LES ARM Symbiotic Simulation and Observation (LASSO) Implementation Strategy

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

Gustafson Jr., WI; Vogelmann, AM

2015-09-01

This document illustrates the design of the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) workflow to provide a routine, high-resolution modeling capability to augment the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s high-density observations. LASSO will create a powerful new capability for furthering ARM’s mission to advance understanding of cloud, radiation, aerosol, and land-surface processes. The combined observational and modeling elements will enable a new level of scientific inquiry by connecting processes and context to observations and providing needed statistics for details that cannot be measured. The result will be improved process understandingmore » that facilitates concomitant improvements in climate model parameterizations. The initial LASSO implementation will be for ARM’s Southern Great Plains site in Oklahoma and will focus on shallow convection, which is poorly simulated by climate models due in part to clouds’ typically small spatial scale compared to model grid spacing, and because the convection involves complicated interactions of microphysical and boundary layer processes.« less

Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

PubMed

Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

2012-09-01

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

Urban adaptation can roll back warming of emerging megapolitan regions

PubMed Central

Georgescu, Matei; Morefield, Philip E.; Bierwagen, Britta G.; Weaver, Christopher P.

2014-01-01

Modeling results incorporating several distinct urban expansion futures for the United States in 2100 show that, in the absence of any adaptive urban design, megapolitan expansion, alone and separate from greenhouse gas-induced forcing, can be expected to raise near-surface temperatures 1–2 °C not just at the scale of individual cities but over large regional swaths of the country. This warming is a significant fraction of the 21st century greenhouse gas-induced climate change simulated by global climate models. Using a suite of regional climate simulations, we assessed the efficacy of commonly proposed urban adaptation strategies, such as green, cool roof, and hybrid approaches, to ameliorate the warming. Our results quantify how judicious choices in urban planning and design cannot only counteract the climatological impacts of the urban expansion itself but also, can, in fact, even offset a significant percentage of future greenhouse warming over large scales. Our results also reveal tradeoffs among different adaptation options for some regions, showing the need for geographically appropriate strategies rather than one size fits all solutions. PMID:24516126

Characterizing the "Time of Emergence" of Air Quality Climate Penalties

NASA Astrophysics Data System (ADS)

Rothenberg, D. A.; Garcia-Menendez, F.; Monier, E.; Solomon, S.; Selin, N. E.

2017-12-01

By driving not only local changes in temperature, but also precipitation and regional-scale changes in seasonal circulation patterns, climate change can directly and indirectly influence changes in air quality and its extremes. These changes - often referred to as "climate penalties" - can have important implications for human health, which is often targeted when assessing the potential co-benefits of climate policy. But because climate penalties are driven by slow, spatially-varying, temporal changes in the climate system, their emergence in the real world should also have a spatio-temporal component following regional variability in background air quality. In this work, we attempt to estimate the spatially-varying "time of emergence" of climate penalty signals by using an ensemble modeling framework based on the MIT Integrated Global System Model (MIT IGSM). With this framework we assess three climate policy scenarios assuming three different underlying climate sensitivities, and conduct a 5-member ensemble for each case to capture internal variability within the model. These simulations are used to drive offline chemical transport modeling (using CAM-Chem and GEOS-Chem). In these simulations, we find that the air quality response to climate change can vary dramatically across different regions of the globe. To analyze these regionally-varying climate signals, we employ a hierarchical clustering technique to identify regions with similar seasonal patterns of air quality change. Our simulations suggest that the earliest emergence of ozone climate penalties would occur in Southern Europe (by 2035), should the world neglect climate change and rely on a "business-as-usual" emissions policy. However, even modest climate policy dramatically pushes back the time of emergence of these penalties - to beyond 2100 - across most of the globe. The emergence of climate-forced changes in PM2.5 are much more difficult to detect, partially owing to the large role that changes in the frequency and spatial distribution of precipitation play in limiting the accumulation and duration of particulate pollution episodes.

The western Pacific monsoon in CMIP5 models: Model evaluation and projections

NASA Astrophysics Data System (ADS)

Brown, Josephine R.; Colman, Robert A.; Moise, Aurel F.; Smith, Ian N.

2013-11-01

ability of 35 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate the western Pacific (WP) monsoon is evaluated over four representative regions around Timor, New Guinea, the Solomon Islands and Palau. Coupled model simulations are compared with atmosphere-only model simulations (with observed sea surface temperatures, SSTs) to determine the impact of SST biases on model performance. Overall, the CMIP5 models simulate the WP monsoon better than previous-generation Coupled Model Intercomparison Project Phase 3 (CMIP3) models, but some systematic biases remain. The atmosphere-only models are better able to simulate the seasonal cycle of zonal winds than the coupled models, but display comparable biases in the rainfall. The CMIP5 models are able to capture features of interannual variability in response to the El Niño-Southern Oscillation. In climate projections under the RCP8.5 scenario, monsoon rainfall is increased over most of the WP monsoon domain, while wind changes are small. Widespread rainfall increases at low latitudes in the summer hemisphere appear robust as a large majority of models agree on the sign of the change. There is less agreement on rainfall changes in winter. Interannual variability of monsoon wet season rainfall is increased in a warmer climate, particularly over Palau, Timor and the Solomon Islands. A subset of the models showing greatest skill in the current climate confirms the overall projections, although showing markedly smaller rainfall increases in the western equatorial Pacific. The changes found here may have large impacts on Pacific island countries influenced by the WP monsoon.

Estimates of the long-term U.S. economic impacts of global climate change-induced drought.

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

Ehlen, Mark Andrew; Loose, Verne W.; Warren, Drake E.

2010-01-01

While climate-change models have done a reasonable job of forecasting changes in global climate conditions over the past decades, recent data indicate that actual climate change may be much more severe. To better understand some of the potential economic impacts of these severe climate changes, Sandia economists estimated the impacts to the U.S. economy of climate change-induced impacts to U.S. precipitation over the 2010 to 2050 time period. The economists developed an impact methodology that converts changes in precipitation and water availability to changes in economic activity, and conducted simulations of economic impacts using a large-scale macroeconomic model of themore » U.S. economy.« less

Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

The 'Year without summer 1816

NASA Astrophysics Data System (ADS)

Arfeuille, F.; Rozanov, E.; Peter, T.; Weisenstein, D.; Hadorn, G.; Bodenmann, T.; Brönnimann, S.

2010-09-01

One famous example of an extreme climatic event is the cold summer of 1816 in Europe and North America. This specific year, which was later called the "Year without summer 1816", had profound social and environmental effects. The cataclysmic eruption of Mt Tambora is now commonly known to have largely contributed to the negative temperature anomalies of the summer 1816, but some uncertainties remain. The eruption which occurred in April 1815 is the largest within the last 500 years and this extreme climatic forcing provides a real test for climate models. A crucial parameter to assess in order to simulate this eruption is the aerosol size distribution, which strongly influences the radiative impact of the aerosols (through changes in albedo and residence time in the stratosphere, among others) and the impacts on dynamics and chemistry. The representation of this major forcing is done by using the AER-2D aerosol model which calculates the size distribution of the aerosols formed after the eruption. The modeling of the climatic impacts is then done by the state-of-the-art Chemistry-Climate model (CCM) SOCOL. The characteristics of the Tambora eruption and results from simulations made using the aerosol model/CCM, with an emphasis on the radiative and chemical implications of the large aerosol, will be shown. For instance, the specific absorption/scattering ratio of Mt.Tambora aerosols induced a large stratospheric warming which will be analyzed. The climatic impacts will also be discussed in regards of the high sedimentation rate of Mt. Tambora aerosols, leading to a fast decrease of the atmospheric optical depth in the first two years after the eruption. The link will be made between the modeling results and proxy-reconstructions as well as with available historical daily data from Geneva, Switzerland. Finally, insights on the contemporary response to this climatic extreme will be shown.

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Human and climate impact on global riverine water and sediment fluxes - a distributed analysis

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Syvitski, J. P.

2013-05-01

Understanding riverine water and sediment dynamics is an important undertaking for both socially-relevant issues such as agriculture, water security and infrastructure management and for scientific analysis of climate, landscapes, river ecology, oceanography and other disciplines. Providing good quantitative and predictive tools in therefore timely particularly in light of predicted climate and landuse changes. The intensity and dynamics between man-made and climatic factors vary widely across the globe and are therefore hard to predict. Using sophisticated numerical models is therefore warranted. Here we use a distributed global riverine sediment and water discharge model (WBMsed) to simulate human and climate effect on our planet's large rivers.

High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2): Large Eddy Simulation Study Over Germany

NASA Astrophysics Data System (ADS)

Dipankar, A.; Stevens, B. B.; Zängl, G.; Pondkule, M.; Brdar, S.

2014-12-01

The effect of clouds on large scale dynamics is represented in climate models through parameterization of various processes, of which the parameterization of shallow and deep convection are particularly uncertain. The atmospheric boundary layer, which controls the coupling to the surface, and which defines the scale of shallow convection, is typically 1 km in depth. Thus, simulations on a O(100 m) grid largely obviate the need for such parameterizations. By crossing this threshold of O(100m) grid resolution one can begin thinking of large-eddy simulation (LES), wherein the sub-grid scale parameterization have a sounder theoretical foundation. Substantial initiatives have been taken internationally to approach this threshold. For example, Miura et al., 2007 and Mirakawa et al., 2014 approach this threshold by doing global simulations, with (gradually) decreasing grid resolution, to understand the effect of cloud-resolving scales on the general circulation. Our strategy, on the other hand, is to take a big leap forward by fixing the resolution at O(100 m), and gradually increasing the domain size. We believe that breaking this threshold would greatly help in improving the parameterization schemes and reducing the uncertainty in climate predictions. To take this forward, the German Federal Ministry of Education and Research has initiated a project on HD(CP)2 that aims for a limited area LES at resolution O(100 m) using the new unified modeling system ICON (Zängl et al., 2014). In the talk, results from the HD(CP)2 evaluation simulation will be shown that targets high resolution simulation over a small domain around Jülich, Germany. This site is chosen because high resolution HD(CP)2 Observational Prototype Experiment took place in this region from 1.04.2013 to 31.05.2013, in order to critically evaluate the model. Nesting capabilities of ICON is used to gradually increase the resolution from the outermost domain, which is forced from the COSMO-DE data, to the innermost and finest resolution domain centered around Jülich (see Fig. 1 top panel). Furthermore, detailed analyses of the simulation results against the observation data will be presented. A reprsentative figure showing time series of column integrated water vapor (IWV) for both model and observation on 24.04.2013 is shown in bottom panel of Fig. 1.

Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Wong, Takmeng; Allan, Richard; Slingo, Anthony; Kiehl, Jeffrey T.; Soden, Brian J.; Gordon, C. T.; Miller, Alvin J.; Yang, Shi-Keng; Randall, David R.;

European climate change at global mean temperature increases of 1.5 and 2 °C above pre-industrial conditions as simulated by the EURO-CORDEX regional climate models

NASA Astrophysics Data System (ADS)

Kjellström, Erik; Nikulin, Grigory; Strandberg, Gustav; Bøssing Christensen, Ole; Jacob, Daniela; Keuler, Klaus; Lenderink, Geert; van Meijgaard, Erik; Schär, Christoph; Somot, Samuel; Sørland, Silje Lund; Teichmann, Claas; Vautard, Robert

2018-05-01

We investigate European regional climate change for time periods when the global mean temperature has increased by 1.5 and 2 °C compared to pre-industrial conditions. Results are based on regional downscaling of transient climate change simulations for the 21st century with global climate models (GCMs) from the fifth-phase Coupled Model Intercomparison Project (CMIP5). We use an ensemble of EURO-CORDEX high-resolution regional climate model (RCM) simulations undertaken at a computational grid of 12.5 km horizontal resolution covering Europe. The ensemble consists of a range of RCMs that have been used for downscaling different GCMs under the RCP8.5 forcing scenario. The results indicate considerable near-surface warming already at the lower 1.5 °C of warming. Regional warming exceeds that of the global mean in most parts of Europe, being the strongest in the northernmost parts of Europe in winter and in the southernmost parts of Europe together with parts of Scandinavia in summer. Changes in precipitation, which are less robust than the ones in temperature, include increases in the north and decreases in the south with a borderline that migrates from a northerly position in summer to a southerly one in winter. Some of these changes are already seen at 1.5 °C of warming but are larger and more robust at 2 °C. Changes in near-surface wind speed are associated with a large spread among individual ensemble members at both warming levels. Relatively large areas over the North Atlantic and some parts of the continent show decreasing wind speed while some ocean areas in the far north show increasing wind speed. The changes in temperature, precipitation and wind speed are shown to be modified by changes in mean sea level pressure, indicating a strong relationship with the large-scale circulation and its internal variability on decade-long timescales. By comparing to a larger ensemble of CMIP5 GCMs we find that the RCMs can alter the results, leading either to attenuation or amplification of the climate change signal in the underlying GCMs. We find that the RCMs tend to produce less warming and more precipitation (or less drying) in many areas in both winter and summer.

Influence of dimethyl sulfide on the carbon cycle and biological production

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

Wang, Shanlin; Maltrud, Mathew; Elliott, Scott

Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to examine the sign and strength of phytoplankton-DMS-climate feedbacks for the first time. Simulation results show small differences in the DMS production and emissions between pre-industrial and present climate scenarios, except for some areas in the Southern Ocean. There are clear changes in surface ocean DMS concentrations moving into the future, and they are attributable to changes inmore » phytoplankton production and competition driven by complex spatially varying mechanisms. Comparisons between parallel simulations with and without DMS fluxes into the atmosphere show significant differences in marine ecosystems and physical fields. Without DMS, the missing subsequent aerosol indirect effects on clouds and radiative forcing lead to fewer clouds, more solar radiation, and a much warmer climate. Phaeocystis, a uniquely efficient organosulfur producer with a growth advantage under cooler climate states, can benefit from producing the compound through cooling effects of DMS in the climate system. Our results show a tight coupling between the sulfur and carbon cycles. The ocean carbon uptake declines without DMS emissions to the atmosphere. The analysis indicates a weak positive phytoplankton-DMS-climate feedback at the global scale, with large spatial variations driven by individual autotrophic functional groups and complex mechanisms. The sign and strength of the feedback vary with climate states and phytoplankton groups. This highlights the importance of a dynamic marine ecosystem module and the sulfur cycle mechanism in climate projections.« less

Influence of dimethyl sulfide on the carbon cycle and biological production

DOE PAGES

Wang, Shanlin; Maltrud, Mathew; Elliott, Scott; ...

2018-02-27

Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to examine the sign and strength of phytoplankton-DMS-climate feedbacks for the first time. Simulation results show small differences in the DMS production and emissions between pre-industrial and present climate scenarios, except for some areas in the Southern Ocean. There are clear changes in surface ocean DMS concentrations moving into the future, and they are attributable to changes inmore » phytoplankton production and competition driven by complex spatially varying mechanisms. Comparisons between parallel simulations with and without DMS fluxes into the atmosphere show significant differences in marine ecosystems and physical fields. Without DMS, the missing subsequent aerosol indirect effects on clouds and radiative forcing lead to fewer clouds, more solar radiation, and a much warmer climate. Phaeocystis, a uniquely efficient organosulfur producer with a growth advantage under cooler climate states, can benefit from producing the compound through cooling effects of DMS in the climate system. Our results show a tight coupling between the sulfur and carbon cycles. The ocean carbon uptake declines without DMS emissions to the atmosphere. The analysis indicates a weak positive phytoplankton-DMS-climate feedback at the global scale, with large spatial variations driven by individual autotrophic functional groups and complex mechanisms. The sign and strength of the feedback vary with climate states and phytoplankton groups. This highlights the importance of a dynamic marine ecosystem module and the sulfur cycle mechanism in climate projections.« less

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

Cook, Kerry H.; Vizy, Edward

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

Chasing Perfection: Should We Reduce Model Uncertainty in Carbon Cycle-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Lombardozzi, D.; Wieder, W. R.; Lindsay, K. T.; Thomas, R. Q.

2015-12-01

Earth system model simulations of the terrestrial carbon (C) cycle show large multi-model spread in the carbon-concentration and carbon-climate feedback parameters. Large differences among models are also seen in their simulation of global vegetation and soil C stocks and other aspects of the C cycle, prompting concern about model uncertainty and our ability to faithfully represent fundamental aspects of the terrestrial C cycle in Earth system models. Benchmarking analyses that compare model simulations with common datasets have been proposed as a means to assess model fidelity with observations, and various model-data fusion techniques have been used to reduce model biases. While such efforts will reduce multi-model spread, they may not help reduce uncertainty (and increase confidence) in projections of the C cycle over the twenty-first century. Many ecological and biogeochemical processes represented in Earth system models are poorly understood at both the site scale and across large regions, where biotic and edaphic heterogeneity are important. Our experience with the Community Land Model (CLM) suggests that large uncertainty in the terrestrial C cycle and its feedback with climate change is an inherent property of biological systems. The challenge of representing life in Earth system models, with the rich diversity of lifeforms and complexity of biological systems, may necessitate a multitude of modeling approaches to capture the range of possible outcomes. Such models should encompass a range of plausible model structures. We distinguish between model parameter uncertainty and model structural uncertainty. Focusing on improved parameter estimates may, in fact, limit progress in assessing model structural uncertainty associated with realistically representing biological processes. Moreover, higher confidence may be achieved through better process representation, but this does not necessarily reduce uncertainty.

Investigating NARCCAP Precipitation Extremes via Bivariate Extreme Value Theory (Invited)

NASA Astrophysics Data System (ADS)

Weller, G. B.; Cooley, D. S.; Sain, S. R.; Bukovsky, M. S.; Mearns, L. O.

2013-12-01

We introduce methodology from statistical extreme value theory to examine the ability of reanalysis-drive regional climate models to simulate past daily precipitation extremes. Going beyond a comparison of summary statistics such as 20-year return values, we study whether the most extreme precipitation events produced by climate model simulations exhibit correspondence to the most extreme events seen in observational records. The extent of this correspondence is formulated via the statistical concept of tail dependence. We examine several case studies of extreme precipitation events simulated by the six models of the North American Regional Climate Change Assessment Program (NARCCAP) driven by NCEP reanalysis. It is found that the NARCCAP models generally reproduce daily winter precipitation extremes along the Pacific coast quite well; in contrast, simulation of past daily summer precipitation extremes in a central US region is poor. Some differences in the strength of extremal correspondence are seen in the central region between models which employ spectral nudging and those which do not. We demonstrate how these techniques may be used to draw a link between extreme precipitation events and large-scale atmospheric drivers, as well as to downscale extreme precipitation simulated by a future run of a regional climate model. Specifically, we examine potential future changes in the nature of extreme precipitation along the Pacific coast produced by the pineapple express (PE) phenomenon. A link between extreme precipitation events and a "PE Index" derived from North Pacific sea-surface pressure fields is found. This link is used to study PE-influenced extreme precipitation produced by a future-scenario climate model run.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

The Importance of Simulation Workflow and Data Management in the Accelerated Climate Modeling for Energy Project

NASA Astrophysics Data System (ADS)

Bader, D. C.

2015-12-01

The Accelerated Climate Modeling for Energy (ACME) Project is concluding its first year. Supported by the Office of Science in the U.S. Department of Energy (DOE), its vision is to be "an ongoing, state-of-the-science Earth system modeling, modeling simulation and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE." Included in the "laboratory resources," is a large investment in computational, network and information technologies that will be utilized to both build better and more accurate climate models and broadly disseminate the data they generate. Current model diagnostic analysis and data dissemination technologies will not scale to the size of the simulations and the complexity of the models envisioned by ACME and other top tier international modeling centers. In this talk, the ACME Workflow component plans to meet these future needs will be described and early implementation examples will be highlighted.

Projected changes over western Canada using convection-permitting regional climate model and the pseudo-global warming method

NASA Astrophysics Data System (ADS)

Li, Y.; Kurkute, S.; Chen, L.

2017-12-01

Results from the General Circulation Models (GCMs) suggest more frequent and more severe extreme rain events in a climate warmer than the present. However, current GCMs cannot accurately simulate extreme rainfall events of short duration due to their coarse model resolutions and parameterizations. This limitation makes it difficult to provide the detailed quantitative information for the development of regional adaptation and mitigation strategies. Dynamical downscaling using nested Regional Climate Models (RCMs) are able to capture key regional and local climate processes with an affordable computational cost. Recent studies have demonstrated that the downscaling of GCM results with weather-permitting mesoscale models, such as the pseudo-global warming (PGW) technique, could be a viable and economical approach of obtaining valuable climate change information on regional scales. We have conducted a regional climate 4-km Weather Research and Forecast Model (WRF) simulation with one domain covering the whole western Canada, for a historic run (2000-2015) and a 15-year future run to 2100 and beyond with the PGW forcing. The 4-km resolution allows direct use of microphysics and resolves the convection explicitly, thus providing very convincing spatial detail. With this high-resolution simulation, we are able to study the convective mechanisms, specifically the control of convections over the Prairies, the projected changes of rainfall regimes, and the shift of the convective mechanisms in a warming climate, which has never been examined before numerically at such large scale with such high resolution.

The global gridded crop model intercomparison: Data and modeling protocols for Phase 1 (v1.0)

DOE PAGES

Elliott, J.; Müller, C.; Deryng, D.; ...

2015-02-11

We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project consist of global simulations of yields, phenologies, and many land-surface fluxes using 12–15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification ofmore » key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.« less

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Climate Change Transforms Fire Regimes but Does not Eliminate Forest Carbon Sequestration in the Greater Yellowstone Ecosystem

NASA Astrophysics Data System (ADS)

Henne, P. D.; Hawbaker, T. J.; Berryman, E.

2017-12-01

Annual area burned in the Rocky Mountains varies with climatic conditions. However, projecting long-term changes in wildfire presents an enduring challenge because climate also constrains vegetation and fuel availability. We combined an aridity-threshold fire model with the Landis-II dynamic landscape vegetation model (NECN extension) to project climate change impacts on vegetation, area burned, and ecosystem carbon balance in the Greater Yellowstone Ecosystem (GYE). We developed a fire model that relates drought stress to area burned by quantifying an aridity threshold separating large and small years in 15 ecoregions in the Intermountain West. A significant positive correlation (r2 = 0.97) exists between mean fire-season aridity and ecoregion-specific aridity thresholds. We simulated vegetation and fire dynamics in the GYE at 250 m spatial resolution with Landis-II, using projections from five climate models and two emissions scenarios for the period 1980-2100 AD. We determined if each simulation year exceeded the regional aridity threshold, then randomly drew the number of fires and size of individual fires from fire-size distributions from large or small fire years. Burned area increases dramatically in most climate scenarios, especially after 2060, when most years exceed the aridity threshold. Productivity gains due to rising temperatures partially offset biomass lost to fire, but C stocks plateau or decline after 2060 in most simulations as burned area increases, and drought stress causes post-fire regeneration to decline at low elevations. However, species level changes (e.g. expansion by drought-tolerant Pseuodotsuga menziesii) help maintain productivity in sites where water becomes limiting. Fire-adapted Pinus contorta occupies less total area, but a greater proportion of remaining forests, and Picea engelmannii and Abies lasiocarpa significantly decline. Although fire and climate change will alter species distributions and forest structure, our results suggest that the GYE can maintain a C sink through 2100. However, C stocks will likely shift to higher elevations, and forests will be less resilient to disturbance, in a warmer future. Our landscape-level approach identifies regions likely to maintain high conservation value and ecosystem services under multiple climate scenarios.

Hydrologic Effects of Global Climate Change on a Large Drained Pine Forest

Treesearch

Devendra M. Amatya; Ge Sun; R. W. Skaggs; G. M Chescheir; J. E. Nettles

2006-01-01

A simulation study using a watershed scale forest hydrology model (DRAINWAT) was conducted to evaluate potential effects of climate change on the hydrology of a 3,000 ha managed pine forest in coastal North Carolina. The model was first validated with a five-year (1996-2000) data set fro111 the study site and then run with 50-years (1951-00) of historic weather data...

On the possibility of ice on Greenland during the Eocene-Oligocene transition

NASA Astrophysics Data System (ADS)

Langebroek, Petra M.; Nisancioglu, Kerim H.; Lunt, Daniel J.; Kathrine Pedersen, Vivi; Nele Meckler, A.; Gasson, Edward

2017-04-01

The Eocene-Oligocene transition ( 34 Ma) is one of the major climate transitions of the Cenozoic era. Atmospheric CO2 decreased from the high levels of the Greenhouse world (>1000 ppm) to values of about 600-700 ppm in the early Oligocene. High latitude temperatures dropped by several degrees, causing a large-scale expansion of the Antarctic ice sheet. Concurrently, in the Northern Hemisphere, the inception of ice caps on Greenland is suggested by indirect evidence from ice-rafted debris and changes in erosional regime. However, ice sheet models have not been able to simulate extensive ice on Greenland under the warm climate of the Eocene-Oligocene transition. We show that elevated bedrock topography is key in solving this inconsistency. During the late Eocene / early Oligocene, East Greenland bedrock elevations were likely higher than today due to tectonic and deep-Earth processes related to the break-up of the North Atlantic and the position of the Icelandic plume. When allowing for higher initial bedrock topography, we do simulate a large ice cap on Greenland under the still relatively warm climate of the early Oligocene. Ice inception takes place at high elevations in the colder regions of North and Northeast Greenland; with the size of the ice cap being strongly dependent on the climate forcing and the bedrock topography applied.

Can We Use Single-Column Models for Understanding the Boundary Layer Cloud-Climate Feedback?

NASA Astrophysics Data System (ADS)

Dal Gesso, S.; Neggers, R. A. J.

2018-02-01

This study explores how to drive Single-Column Models (SCMs) with existing data sets of General Circulation Model (GCM) outputs, with the aim of studying the boundary layer cloud response to climate change in the marine subtropical trade wind regime. The EC-EARTH SCM is driven with the large-scale tendencies and boundary conditions as derived from two different data sets, consisting of high-frequency outputs of GCM simulations. SCM simulations are performed near Barbados Cloud Observatory in the dry season (January-April), when fair-weather cumulus is the dominant low-cloud regime. This climate regime is characterized by a near equilibrium in the free troposphere between the long-wave radiative cooling and the large-scale advection of warm air. In the SCM, this equilibrium is ensured by scaling the monthly mean dynamical tendency of temperature and humidity such that it balances that of the model physics in the free troposphere. In this setup, the high-frequency variability in the forcing is maintained, and the boundary layer physics acts freely. This technique yields representative cloud amount and structure in the SCM for the current climate. Furthermore, the cloud response to a sea surface warming of 4 K as produced by the SCM is consistent with that of the forcing GCM.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Modelling the Holderness coast, eastern England: Past, present and future

NASA Astrophysics Data System (ADS)

Barkwith, A.; Limber, P. W.; Thomas, C. W.; Murray, A.; Jordan, H. M.; Ellis, M. A.

2012-12-01

The Holderness coast of eastern Yorkshire, England, is the most rapidly eroding coastline in Europe. Erosion can locally exceed 10 m in a single year and rates average 0.5 to 3 m yr-1, generally increasing from north to south. Pinned in the north by a chalk headland, the soft till coastline has a characteristic open spiral form terminated by a spit to the south. Erosion currently threatens local communities and infrastructure, including nationally important gas installations. Interventions to restrict local erosion usually result in enhanced erosion in adjacent, unprotected sections of coast, mirroring morphology seen on the large scale. We have initiated a modelling study to investigate the key controls on the form and evolution of this coastline, and its response to climate change, building on the Coastline Evolution Model (CEM) developed at Duke University, NC. We have adapted the CEM to permit an ensemble of simulations to be undertaken, based upon modified offshore wave climates, initial conditions and forcing factors. The CEM follows a standard 1d approach, where the cross-shore is collapsed into a single data point, allowing the planform shoreline shape and dynamics to be simulated. The model facilitates study of a coast with variable erosion rates, and enables simulation of coastline evolution when sediment is supplied from an eroding shoreface. Additionally, the CEM is adapted to use an observed two year, offshore wave climate data set as input. Initial work focussed on reconstruction of current coastline shape from an ensemble of hypothetical early Holocene shoreface positions and past wave climates. First order reconstruction of shoreline shape was achieved using several differing initial conditions and wave climates. For the majority of successful simulations, a steady state was noted for proceeding years, where erosion proceeds at an equal rate along the length of the coast south of the headland. Together with a sensitivity analysis, the derivation of the current coastline provided initial conditions for the second phase of the work: simulating the morphological response of the Holderness coastline to possible future changes in climate over the next century. An ensemble of future possible wave climate perturbations was generated from predictions of the likely response of the North Sea to future climate change over the next century, and applied linearly to the observed wave climate as each simulation progressed. The ensemble output was compared to a baseline simulation, run for a century under current wave climate, to assess the impact of predicted future climate on coastal erosion. Although this study does not currently take into account the changes in storm frequency, rises in sea level or the anthropogenic inputs that could influence the results, the initial output indicates erosional rates over the next century are likely to be retarded for the Holderness coastline under a changing climate.

Stress Testing Water Resource Systems at Regional and National Scales with Synthetic Drought Event Sets

NASA Astrophysics Data System (ADS)

Hall, J. W.; Mortazavi-Naeini, M.; Coxon, G.; Guillod, B. P.; Allen, M. R.

2017-12-01

Water resources systems can fail to deliver the services required by water users (and deprive the environment of flow requirements) in many different ways. In an attempt to make systems more resilient, they have also been made more complex, for example through a growing number of large-scale transfers, optimized storages and reuse plants. These systems may be vulnerable to complex variants of hydrological variability in space and time, and behavioural adaptations by water users. In previous research we have used non-parametric stochastic streamflow generators to test the vulnerability of water resource systems. Here we use a very large ensemble of regional climate model outputs from the weather@home crowd-sourced citizen science project, which has generated more than 30,000 years of synthetic weather for present and future climates in the UK and western Europe, using the HadAM3P regional climate model. These simulations have been constructed in order to preserve prolonged drought characteristics, through treatment of long-memory processes in ocean circulations and soil moisture. The weather simulations have been propagated through the newly developed DynaTOP national hydrological for Britain, in order to provide low flow simulations at points of water withdrawal for public water supply, energy and agricultural abstractors. We have used the WATHNET water resource simulation model, set up for the Thames Basin and for all of the large water resource zones in England, to simulate the frequency, severity and duration of water shortages in all of these synthetic weather conditions. In particular, we have sought to explore systemic vulnerabilities associated with inter-basin transfers and the trade-offs between different water users. This analytical capability is providing the basis for (i) implementation of the Duty of Resilience, which has been placed upon the water industry in the 2014 Water Act and (ii) testing reformed abstraction arrangements which the UK government is committed to implementing.

Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

USGS Publications Warehouse

Jeton, A.E.; Dettinger, M.D.; Smith, J. LaRue

1996-01-01

Precipitation-runoff models of the East Fork Carson and North Fork American Rivers were developed and calibrated for use in evaluating the sensitivity of streamflow in the north-central Sierra Nevada to climate change. The East Fork Carson River drains part of the rain-shadowed, eastern slope of the Sierra Nevada and is generally higher than the North Fork American River, which drains the wetter, western slope. First, a geographic information system was developed to describe the spatial variability of basin characteristics and to help estimate model parameters. The result was a partitioning of each basin into noncontiguous, but hydrologically uniform, land units. Hydrologic descriptions of these units were developed and the Precipitation- Runoff Modeling System (PRMS) was used to simulate water and energy balances for each unit in response to daily weather conditions. The models were calibrated and verified using historical streamflows over 22-year (Carson River) and 42-year (American River) periods. Simulated annual streamflow errors average plus 10 percent of the observed flow for the East Fork Carson River basin and plus 15 percent for the North Fork American River basin. Interannual variability is well simulated overall, but, at daily scales, wet periods are simulated more accurately than drier periods. The simulated water budgets for the two basins are significantly different in seasonality of streamflow, sublimation, evapotranspiration, and snowmelt. The simulations indicate that differences in snowpack and snowmelt timing can play pervasive roles in determining the sensitivity of water resources to climate change, in terms of both resource availability and amount. The calibrated models were driven by more than 25 hypothetical climate-change scenarios, each 100 years long. The scenarios were synthesized and spatially disaggregated by methods designed to preserve realistic daily, monthly, annual, and spatial statistics. Simulated streamflow timing was not very sensitive to changes in mean precipitation, but was sensitive to changes in mean temperatures. Changes in annual streamflow amounts were amplified reflections of imposed mean precipitation changes, with especially large responses to wetter climates. In contrast, streamflow amount was surprisingly insensitive to mean temperature changes as a result of temporal links between peak snowmelt and the beginning of warm-season evapotranspiration. Comparisons of simulations driven by temporally detailed climate-model changes in which mean temperature changes vary from month to month and simulations in which uniform climate changes were imposed throughout the year indicate that the snowpack accumulates the influences of short-term conditions so that season average climate changes were more important than shorter term changes.

The FireBGCv2 landscape fire and succession model: a research simulation platform for exploring fire and vegetation dynamics

Treesearch

Robert E. Keane; Rachel A. Loehman; Lisa M. Holsinger

2011-01-01

Fire management faces important emergent issues in the coming years such as climate change, fire exclusion impacts, and wildland-urban development, so new, innovative means are needed to address these challenges. Field studies, while preferable and reliable, will be problematic because of the large time and space scales involved. Therefore, landscape simulation...

Projections of Future Precipitation Extremes Over Europe: A Multimodel Assessment of Climate Simulations

NASA Astrophysics Data System (ADS)

Rajczak, Jan; Schär, Christoph

2017-10-01

Projections of precipitation and its extremes over the European continent are analyzed in an extensive multimodel ensemble of 12 and 50 km resolution EURO-CORDEX Regional Climate Models (RCMs) forced by RCP2.6, RCP4.5, and RCP8.5 (Representative Concentration Pathway) aerosol and greenhouse gas emission scenarios. A systematic intercomparison with ENSEMBLES RCMs is carried out, such that in total information is provided for an unprecedentedly large data set of 100 RCM simulations. An evaluation finds very reasonable skill for the EURO-CORDEX models in simulating temporal and geographical variations of (mean and heavy) precipitation at both horizontal resolutions. Heavy and extreme precipitation events are projected to intensify across most of Europe throughout the whole year. All considered models agree on a distinct intensification of extremes by often more than +20% in winter and fall and over central and northern Europe. A reduction of rainy days and mean precipitation in summer is simulated by a large majority of models in the Mediterranean area, but intermodel spread between the simulations is large. In central Europe and France during summer, models project decreases in precipitation but more intense heavy and extreme rainfalls. Comparison to previous RCM projections from ENSEMBLES reveals consistency but slight differences in summer, where reductions in southern European precipitation are not as pronounced as previously projected. The projected changes of the European hydrological cycle may have substantial impact on environmental and anthropogenic systems. In particular, the simulations indicate a rising probability of summertime drought in southern Europe and more frequent and intense heavy rainfall across all of Europe.

Simulation-optimization of large agro-hydrosystems using a decomposition approach

NASA Astrophysics Data System (ADS)

Schuetze, Niels; Grundmann, Jens

2014-05-01

In this contribution a stochastic simulation-optimization framework for decision support for optimal planning and operation of water supply of large agro-hydrosystems is presented. It is based on a decomposition solution strategy which allows for (i) the usage of numerical process models together with efficient Monte Carlo simulations for a reliable estimation of higher quantiles of the minimum agricultural water demand for full and deficit irrigation strategies at small scale (farm level), and (ii) the utilization of the optimization results at small scale for solving water resources management problems at regional scale. As a secondary result of several simulation-optimization runs at the smaller scale stochastic crop-water production functions (SCWPF) for different crops are derived which can be used as a basic tool for assessing the impact of climate variability on risk for potential yield. In addition, microeconomic impacts of climate change and the vulnerability of the agro-ecological systems are evaluated. The developed methodology is demonstrated through its application on a real-world case study for the South Al-Batinah region in the Sultanate of Oman where a coastal aquifer is affected by saltwater intrusion due to excessive groundwater withdrawal for irrigated agriculture.

The UPSCALE project: a large simulation campaign

NASA Astrophysics Data System (ADS)

Mizielinski, Matthew; Roberts, Malcolm; Vidale, Pier Luigi; Schiemann, Reinhard; Demory, Marie-Estelle; Strachan, Jane

2014-05-01

The development of a traceable hierarchy of HadGEM3 global climate models, based upon the Met Office Unified Model, at resolutions from 135 km to 25 km, now allows the impact of resolution on the mean state, variability and extremes of climate to be studied in a robust fashion. In 2011 we successfully obtained a single-year grant of 144 million core hours of supercomputing time from the PRACE organization to run ensembles of 27 year atmosphere-only (HadGEM3-A GA3.0) climate simulations at 25km resolution, as used in present global weather forecasting, on HERMIT at HLRS. Through 2012 the UPSCALE project (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) ran over 650 years of simulation at resolutions of 25 km (N512), 60 km (N216) and 135 km (N96) to look at the value of high resolution climate models in the study of both present climate and a potential future climate scenario based on RCP8.5. Over 400 TB of data was produced using HERMIT, with additional simulations run on HECToR (UK supercomputer) and MONSooN (Met Office NERC Supercomputing Node). The data generated was transferred to the JASMIN super-data cluster, hosted by STFC CEDA in the UK, where analysis facilities are allowing rapid scientific exploitation of the data set. Many groups across the UK and Europe are already taking advantage of these facilities and we welcome approaches from other interested scientists. This presentation will briefly cover the following points; Purpose and requirements of the UPSCALE project and facilities used. Technical implementation and hurdles (model porting and optimisation, automation, numerical failures, data transfer). Ensemble specification. Current analysis projects and access to the data set. A full description of UPSCALE and the data set generated has been submitted to Geoscientific Model development, with overview information available from http://proj.badc.rl.ac.uk/upscale .

rpe v5: an emulator for reduced floating-point precision in large numerical simulations

NASA Astrophysics Data System (ADS)

Dawson, Andrew; Düben, Peter D.

2017-06-01

This paper describes the rpe (reduced-precision emulator) library which has the capability to emulate the use of arbitrary reduced floating-point precision within large numerical models written in Fortran. The rpe software allows model developers to test how reduced floating-point precision affects the result of their simulations without having to make extensive code changes or port the model onto specialized hardware. The software can be used to identify parts of a program that are problematic for numerical precision and to guide changes to the program to allow a stronger reduction in precision.The development of rpe was motivated by the strong demand for more computing power. If numerical precision can be reduced for an application under consideration while still achieving results of acceptable quality, computational cost can be reduced, since a reduction in numerical precision may allow an increase in performance or a reduction in power consumption. For simulations with weather and climate models, savings due to a reduction in precision could be reinvested to allow model simulations at higher spatial resolution or complexity, or to increase the number of ensemble members to improve predictions. rpe was developed with a particular focus on the community of weather and climate modelling, but the software could be used with numerical simulations from other domains.

How predictable is the timing of a summer ice-free Arctic?

NASA Astrophysics Data System (ADS)

Jahn, Alexandra; Kay, Jennifer E.; Holland, Marika M.; Hall, David M.

2016-09-01

Climate model simulations give a large range of over 100 years for predictions of when the Arctic could first become ice free in the summer, and many studies have attempted to narrow this uncertainty range. However, given the chaotic nature of the climate system, what amount of spread in the prediction of an ice-free summer Arctic is inevitable? Based on results from large ensemble simulations with the Community Earth System Model, we show that internal variability alone leads to a prediction uncertainty of about two decades, while scenario uncertainty between the strong (Representative Concentration Pathway (RCP) 8.5) and medium (RCP4.5) forcing scenarios adds at least another 5 years. Common metrics of the past and present mean sea ice state (such as ice extent, volume, and thickness) as well as global mean temperatures do not allow a reduction of the prediction uncertainty from internal variability.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

Climate Sensitivity Controls Uncertainty in Future Terrestrial Carbon Sink

NASA Astrophysics Data System (ADS)

Schurgers, Guy; Ahlström, Anders; Arneth, Almut; Pugh, Thomas A. M.; Smith, Benjamin

2018-05-01

For the 21st century, carbon cycle models typically project an increase of terrestrial carbon with increasing atmospheric CO2 and a decrease with the accompanying climate change. However, these estimates are poorly constrained, primarily because they typically rely on a limited number of emission and climate scenarios. Here we explore a wide range of combinations of CO2 rise and climate change and assess their likelihood with the climate change responses obtained from climate models. Our results demonstrate that the terrestrial carbon uptake depends critically on the climate sensitivity of individual climate models, representing a large uncertainty of model estimates. In our simulations, the terrestrial biosphere is unlikely to become a strong source of carbon with any likely combination of CO2 and climate change in the absence of land use change, but the fraction of the emissions taken up by the terrestrial biosphere will decrease drastically with higher emissions.

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

NASA Technical Reports Server (NTRS)

De Boer, G.; Shupe, M.D.; Caldwell, P.M.; Bauer, Susanne E.; Persson, O.; Boyle, J.S.; Kelley, M.; Klein, S.A.; Tjernstrom, M.

2014-01-01

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

Climatic Changes and Consequences on the French West Indies (C3AF), Hurricane and Tsunami Hazards Assessment

NASA Astrophysics Data System (ADS)

Arnaud, G.; Krien, Y.; Zahibo, N.; Dudon, B.

2017-12-01

Coastal hazards are among the most worrying threats of our time. In a context of climate change coupled to a large population increase, tropical areas could be the most exposed zones of the globe. In such circumstances, understanding the underlying processes can help to better predict storm surges and the associated global risks.Here we present the partial preliminary results integrated in a multidisciplinary project focused on climatic change effects over the coastal threat in the French West Indies and funded by the European Regional Development Fund. The study aims to provide a coastal hazard assessment based on hurricane surge and tsunami modeling including several aspects of climate changes that can affect hazards such as sea level rise, crustal subsidence/uplift, coastline changes etc. Several tsunamis scenarios have been simulated including tele-tsunamis to ensure a large range of tsunami hazards. Surge level of hurricane have been calculated using a large number of synthetic hurricanes to cover the actual and forecasted climate over the tropical area of Atlantic ocean. This hazard assessment will be later coupled with stakes assessed over the territory to provide risk maps.

Large scale spatially explicit modeling of blue and green water dynamics in a temperate mid-latitude basin

NASA Astrophysics Data System (ADS)

Du, Liuying; Rajib, Adnan; Merwade, Venkatesh

2018-07-01

Looking only at climate change impacts provides partial information about a changing hydrologic regime. Understanding the spatio-temporal nature of change in hydrologic processes, and the explicit contributions from both climate and land use drivers, holds more practical value for water resources management and policy intervention. This study presents a comprehensive assessment on the spatio-temporal trend of Blue Water (BW) and Green Water (GW) in a 490,000 km2 temperate mid-latitude basin (Ohio River Basin) over the past 80 years (1935-2014), and from thereon, quantifies the combined as well as relative contributions of climate and land use changes. The Soil and Water Assessment Tool (SWAT) is adopted to simulate hydrologic fluxes. Mann-Kendall and Theil-Sen statistical tests are performed on the modeled outputs to detect respectively the trend and magnitude of changes at three different spatial scales - the entire basin, regional level, and sub-basin level. Despite the overall volumetric increase of both BW and GW in the entire basin, changes in their annual average values during the period of simulation reveal a distinctive spatial pattern. GW has increased significantly in the upper and lower parts of the basin, which can be related to the prominent land use change in those areas. BW has increased significantly only in the lower part, likely being associated with the notable precipitation change there. Furthermore, the simulation under a time-varying climate but constant land use scenario identifies climate change in the Ohio River Basin to be influential on BW, while the impact is relatively nominal on GW; whereas, land use change increases GW remarkably, but is counterproductive on BW. The approach to quantify combined/relative effects of climate and land use change as shown in this study can be replicated to understand BW-GW dynamics in similar large basins around the globe.

Impacts of Changing Climatic Drivers and Land use features on Future Stormwater Runoff in the Northwest Florida Basin: A Large-Scale Hydrologic Modeling Assessment

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2017-12-01

Potential changes in climatic drivers and land cover features can significantly influence the stormwater budget in the Northwest Florida Basin. We investigated the hydro-climatic and land use sensitivities of stormwater runoff by developing a large-scale process-based rainfall-runoff model for the large basin by using the EPA Storm Water Management Model (SWMM 5.1). Climatic and hydrologic variables, as well as land use/cover features were incorporated into the model to account for the key processes of coastal hydrology and its dynamic interactions with groundwater and sea levels. We calibrated and validated the model by historical daily streamflow observations during 2009-2012 at four major rivers in the basin. Downscaled climatic drivers (precipitation, temperature, solar radiation) projected by twenty GCMs-RCMs under CMIP5, along with the projected future land use/cover features were also incorporated into the model. The basin storm runoff was then simulated for the historical (2000s = 1976-2005) and two future periods (2050s = 2030-2059, and 2080s = 2070-2099). Comparative evaluation of the historical and future scenarios leads to important guidelines for stormwater management in Northwest Florida and similar regions under a changing climate and environment.

Increasing climate whiplash in 21st century California

NASA Astrophysics Data System (ADS)

Swain, D. L.; Langenbrunner, B.; Neelin, J. D.; Hall, A. D.

2017-12-01

Temperate "Mediterranean" climate regimes across the globe are particularly susceptible to wide swings between drought and flood—of which California's rapid transition from record multi-year dryness between 2012-2016 to extreme wetness during 2016-2017 provides a dramatic example. The wide-ranging human and environmental impacts of this recent "climate whiplash" event in a highly-populated, economically critical, and biodiverse region highlight the importance of understanding weather and climate extremes at both ends of the hydroclimatic spectrum. Previous studies have examined the potential contribution of anthropogenic warming to recent California extremes, but findings to date have been mixed and primarily drought-focused. Here, we use specific historical California flood and drought events as thresholds for quantifying long-term changes in precipitation extremes using a large ensemble of multi-decadal climate model simulations (CESM-LENS). We find that greenhouse gas emissions are already responsible for a detectable increase in both wet and dry extremes across portions of California, and that increasing 21st century "climate whiplash" will likely yield large increases in the frequency of both rapid "dry-to-wet" transitions and severe flood events over a wide range of timescales. This projected intensification of California's hydrological cycle would seriously challenge the region's existing water storage, conveyance, and flood control infrastructure—even absent large changes in mean precipitation.

Analysis of Present Day and Future OH and Methane Lifetime in the ACCMIP Simulations

NASA Technical Reports Server (NTRS)

Voulgarakis, A.; Naik, V.; Lamarque, J. -F.; Shindell, D. T.; Young, P. J.; Prather, M. J.; Wild, O.; Field, R. D.; Bergmann, D.; Cameron-Smith P.;

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

NASA Astrophysics Data System (ADS)

Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.

2017-12-01

Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

Analysis on flood generation processes by means of a continuous simulation model

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.

2006-03-01

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

Modeling of larch forest dynamics under a changing climate in eastern Siberia

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Iijima, Y.; Ohta, T.; Kotani, A.; Maximov, T. C.; Hiyama, T.

2017-12-01

According to the projection by an earth system model under RCP8.5 scenario, boreal forest in eastern Siberia (near Yakutsk) is predicted to experience significant changes in climate, in which the mean annual air temperature is projected to be positive and the annual precipitation will be doubled by the end of 21st century. Since the forest in this region is underlain by continuous permafrost, both increasing temperature and precipitation can affect the dynamics of forest through the soil water processes. To investigate such effects, we adopted a newly developed terrestrial ecosystem dynamics model named S-TEDy (SEIB-DGVM-originated Terrestrial Ecosystem Dynamics model), which mechanistically simulates "the way of life" of each individual tree and resulting tree mortality under the future climate conditions. This model was first developed for the simulation of the dynamics of a tropical rainforest in the Borneo Island, and successfully reproduced higher mortality of large trees due to a prolonged drought induced by ENSO event of 1997-1998. To apply this model to a larch forest in eastern Siberia, we are developing a soil submodel to consider the effect of thawing-freezing processes. We will present a simulation results using the future climate projection.

Monitoring and projecting snow on Hawaii Island

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Hamilton, Kevin; Wang, Yuqing

2017-05-01

The highest mountain peaks on Hawaii Island are snow covered for part of almost every year. This snow has aesthetic and recreational value as well as cultural significance for residents and visitors. Thus far there have been almost no systematic observations of snowfall, snow cover, or snow depth in Hawaii. Here we use satellite observations to construct a daily index of Hawaii Island snow cover starting from 2000. The seasonal mean of our index displays large interannual variations that are correlated with the seasonal mean freezing level and frequency of trade wind inversions as determined from nearby balloon soundings. Our snow cover index provides a diagnostic for monitoring climate variability and trends within the extensive area of the globe dominated by the North Pacific trade wind meteorological regime. We have also conducted simulations of the Hawaii climate with a regional atmospheric model. Retrospective simulations for 1990-2015 were run with boundary conditions prescribed from gridded observational analyses. Simulations for the end of 21st century employed boundary conditions based on global climate model projections that included standard scenarios for anticipated anthropogenic climate forcing. The future projections indicate that snowfall will nearly disappear by the end of the current century.

Present-day and future Antarctic ice sheet climate and surface mass balance in the Community Earth System Model

DOE PAGES

Lenaerts, Jan T. M.; Vizcaino, Miren; Fyke, Jeremy Garmeson; ...

2016-02-01

Here, we present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean–atmosphere–land Community Earth System Model (CESM) with a horizontal resolution of ~1° in the past, present and future (1850–2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131Gtyear –1, which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenariomore » RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 Gtyear –1 per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet’s edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content.« less

Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic climate

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick

2014-05-01

Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the albedo feedback dominates simulated warming in spring in all three scenarios, while in summer, evapotranspiration feedback, governing the partitioning of the return energy flux from the surface to the atmosphere into latent and sensible heat, exerts evaporative cooling effects, the magnitude of which depends on the severity of climate change, in turn driven by the underlying GHG emissions pathway, resulting in shift in the sign of net biophysical at higher levels of warming. Spatially, western Siberia is identified as the most susceptible location, experiencing the potential to reverse biophysical feedbacks in all seasons. We further analyze how the pattern of vegetation shifts triggers different signs of net effects of biophysical feedbacks.

Evolution of environmental factors affecting tropical cyclones from the LGM through the Holocene

NASA Astrophysics Data System (ADS)

Korty, R.

2010-12-01

The debate about whether and how tropical cyclones respond to warming climates has raised several interesting questions, but it has also revealed there is much we do not understand about controls on frequency and cumulative metrics of intensity and activity. In this work, I examine how the models used for anthropogenic climate predictions handle large-scale factors influencing tropical cyclone development in a different regime: the paleoclimate simulations of the LGM and Holocene. The models were forced under guidelines set forth by the second paleoclimate model intercomparison project (PMIP2), and produce equilibrium solutions for forcings far removed from small perturbations to the present-day world. (LGM has substantially lower CO2 and CH4 levels, while mid-Holocene cases have similar levels to today but different seasonal amplitudes from orbital variations.) The large-scale environmental factors that support tropical cyclones in today’s climate undergo complex and at times counter-intuitive changes in the colder simulations. The maximum potential intensity of tropical cyclones (MPI) is lower throughout the tropics in the mid-Holocene simulations, despite having SSTs very similar to today. MPI changes at LGM are more complex: lower in some regions but higher in much of the subtropics, while SSTs are uniformly lower than today. The water vapor deficits in the tropical midtroposphere change in such a way as to make tropical cyclone formation easier in the colder states; this is a counterintuitive result, but one consistent with the predictions of fewer storms in model simulations of a warmer climate by the end of the 21st century. I analyze the thermodynamic reasons behind the evolution in the large-scale environmental factors as well as relevant dynamic factors such as low-level vorticity and tropospheric wind shear. This analysis is the first part of a long-term project to analyze model prediction of tropical cyclone activity in the recent geologic past; the analysis provides a new line of evidence to compare with geologic proxies of tropical cyclone activity through the Holocene. Changes in midtropospheric entropy deficit from preindustrial (PI) climate to mid-Holocene (6ka) and LGM. Lower values indicate a smaller saturation deficit, which is conducive for tropical cyclone development.

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

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

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Peng, C.; Liu, J.; Wei, X.; Fang, X.; Liu, S.; Zhou, G.; Yu, S.

2011-01-01

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO2 concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009–2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO2 concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO2concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009–2099 under the constant climate scenario (i.e. using mean climate condition of 1951–2006 and CO2concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.

Global Weirding? - Using Very Large Ensembles and Extreme Value Theory to assess Changes in Extreme Weather Events Today

NASA Astrophysics Data System (ADS)

Otto, F. E. L.; Mitchell, D.; Sippel, S.; Black, M. T.; Dittus, A. J.; Harrington, L. J.; Mohd Saleh, N. H.

2014-12-01

A shift in the distribution of socially-relevant climate variables such as daily minimum winter temperatures and daily precipitation extremes, has been attributed to anthropogenic climate change for various mid-latitude regions. However, while there are many process-based arguments suggesting also a change in the shape of these distributions, attribution studies demonstrating this have not currently been undertaken. Here we use a very large initial condition ensemble of ~40,000 members simulating the European winter 2013/2014 using the distributed computing infrastructure under the weather@home project. Two separate scenarios are used:1. current climate conditions, and 2. a counterfactual scenario of "world that might have been" without anthropogenic forcing. Specifically focusing on extreme events, we assess how the estimated parameters of the Generalized Extreme Value (GEV) distribution vary depending on variable-type, sampling frequency (daily, monthly, …) and geographical region. We find that the location parameter changes for most variables but, depending on the region and variables, we also find significant changes in scale and shape parameters. The very large ensemble allows, furthermore, to assess whether such findings in the fitted GEV distributions are consistent with an empirical analysis of the model data, and whether the most extreme data still follow a known underlying distribution that in a small sample size might otherwise be thought of as an out-lier. The ~40,000 member ensemble is simulated using 12 different SST patterns (1 'observed', and 11 best guesses of SSTs with no anthropogenic warming). The range in SSTs, along with the corresponding changings in the NAO and high-latitude blocking inform on the dynamics governing some of these extreme events. While strong tele-connection patterns are not found in this particular experiment, the high number of simulated extreme events allows for a more thorough analysis of the dynamics than has been performed before. Therefore, combining extreme value theory with very large ensemble simulations allows us to understand the dynamics of changes in extreme events which is not possible just using the former but also shows in which cases statistics combined with smaller ensembles give as valid results as very large initial conditions.

Influence of reanalysis datasets on dynamically downscaling the recent past

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro B.; Evans, Jason P.; Sharma, Ashish

2017-08-01

Multiple reanalysis datasets currently exist that can provide boundary conditions for dynamic downscaling and simulating local hydro-climatic processes at finer spatial and temporal resolutions. Previous work has suggested that there are two reanalyses alternatives that provide the best lateral boundary conditions for downscaling over southern Africa. This study dynamically downscales these reanalyses (ERA-I and MERRA) over southern Africa to a high resolution (10 km) grid using the WRF model. Simulations cover the period 1981-2010. Multiple observation datasets were used for both surface temperature and precipitation to account for observational uncertainty when assessing results. Generally, temperature is simulated quite well, except over the Namibian coastal plain where the simulations show anomalous warm temperature related to the failure to propagate the influence of the cold Benguela current inland. Precipitation tends to be overestimated in high altitude areas, and most of southern Mozambique. This could be attributed to challenges in handling complex topography and capturing large-scale circulation patterns. While MERRA driven WRF exhibits slightly less bias in temperature especially for La Nina years, ERA-I driven simulations are on average superior in terms of RMSE. When considering multiple variables and metrics, ERA-I is found to produce the best simulation of the climate over the domain. The influence of the regional model appears to be large enough to overcome the small difference in relative errors present in the lateral boundary conditions derived from these two reanalyses.

Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Falloon, Pete; Ito, Akihiko; Smallman, T. Luke; Williams, Mathew

2018-02-01

Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) business as usual emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095-2099) compared to 2001-2005, which is 2-3 % stronger than the ensemble ISIMIP mean value of 24.2 Pg C y-1. Using REA also leads to a 45-68 % reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2 fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.

Long-term Ozone Changes and Associated Climate Impacts in CMIP5 Simulations

NASA Technical Reports Server (NTRS)

Eyring, V.; Arblaster, J. M.; Cionni, I.; Sedlacek, J.; Perlwitz, J.; Young, P. J.; Bekki, S.; Bergmann, D.; Cameron-Smith, P.; Collins, W. J.;

Forced and Internal Multi-Decadal Variability in the North Atlantic and their Climate Impacts

NASA Astrophysics Data System (ADS)

Ting, M.

2017-12-01

Atlantic Multidecadal Variability (AMV), a basin-wide North Atlantic sea surface temperature warming or cooling pattern varying on decadal and longer time scales, is one of the most important climate variations in the Atlantic basin. The AMV has shown to be associated with significant climate impacts regionally and globally, from Atlantic hurricane activities, frequency and severity of droughts across North America, as well as rainfall anomalies across the African Sahel and northeast Brazil. Despite the important impacts of the AMV, its mechanisms are not completely understood. In particular, it is not clear how much of the historical Atlantic SST fluctuations were forced by anthropogenic sources such as greenhouse warming and aerosol cooling, versus driven internally by changes in the coupled ocean-atmosphere processes in the Atlantic. Using climate models such as the NCAR large ensemble simulations, we were able to successfully separate the forced and internally generated North Atlantic sea surface temperature anomalies through a signal-to-noise maximizing Empirical Orthogonal Function (S/N EOF) analysis method. Two forced modes were identified with one representing a hemispherical symmetric mode and one asymmetric mode. The symmetric mode largely represents the greenhouse forced component while the asymmetric mode resembles the anthropogenic aerosol forcing. When statistically removing both of the forced modes, the residual multidecadal Atlantic SST variability shows a very similar structure as the AMV in the preindustrial simulation. The distinct climate impacts of each of these modes are also identified and the implications and challenges for decadal climate prediction will be discussed.

The climate response of the Indo-Pacific warm pool to glacial sea level

NASA Astrophysics Data System (ADS)

Di Nezio, Pedro N.; Timmermann, Axel; Tierney, Jessica E.; Jin, Fei-Fei; Otto-Bliesner, Bette; Rosenbloom, Nan; Mapes, Brian; Neale, Rich; Ivanovic, Ruza F.; Montenegro, Alvaro

2016-06-01

Growing climate proxy evidence suggests that changes in sea level are important drivers of tropical climate change on glacial-interglacial timescales. These paleodata suggest that rainfall patterns over the Indo-Pacific warm pool (IPWP) are highly sensitive to the landmass configuration of the Maritime Continent and that lowered sea level contributed to large-scale drying during the Last Glacial Maximum (LGM, approximately 21,000 years B.P.). Using the Community Earth System Model Version 1.2 (CESM1), we investigate the mechanisms by which lowered sea level influenced the climate of the IPWP during the LGM. The CESM1 simulations show that, in agreement with previous hypotheses, changes in atmospheric circulation are initiated by the exposure of the Sunda and Sahul shelves. Ocean dynamical processes amplify the changes in atmospheric circulation by increasing the east-west sea surface temperature (SST) gradient along the equatorial Indian Ocean. The coupled mechanism driving this response is akin to the Bjerknes feedback and results in a large-scale climatic reorganization over the Indian Ocean with impacts extending from east Africa to the western tropical Pacific. Unlike exposure of the Sunda shelf, exposure of Sahul shelf and the associated changes in surface albedo play a key role because of the positive feedback. This mechanism could explain the pattern of dry (wet) eastern (western) Indian Ocean identified in climate proxies and LGM simulations. However, this response also requires a strengthened SST gradient along the equatorial Indian Ocean, a pattern that is not evident in marine paleoreconstructions. Strategies to resolve this issue are discussed.

The limit of irrigation adaption due to the inter-crop conflict of water use under changing climate and landuse

NASA Astrophysics Data System (ADS)

Okada, M.; Iizumi, T.; Sakamoto, T.; Kotoku, M.; Sakurai, G.; Nishimori, M.

2017-12-01

Replacing rainfed cropping system by irrigated one is assumed to be an effective measure for climate change adaptation in agriculture. However, in many agricultural impact assessments, future irrigation scenarios are externally given and do not consider variations in the availability of irrigation water under changing climate and land use. Therefore, we assess the potential effects of adaption measure expanding irrigated area under climate change by using a large-scale crop-river coupled model, CROVER [Okada et al. 2015, JAMES]. The CROVER model simulates the large-scale terrestrial hydrological cycle and crop growth depending on climate, soil properties, landuse, crop cultivation management, socio-economic water demand, and reservoir operation management. The bias-corrected GCMs outputs under the RCP 8.5 scenario were used. The future expansion of irrigation area was estimated by using the extrapolation method based on the historical change in irrigated and rainfed areas. As the results, the irrigation adaptation has only a limited effect on the rice production in East Asia due to the conflict of water use for irrigation with the other crops, whose farmlands require unsustainable water extraction with the excessively expanding irrigated area. In contrast, the irrigation adaptation benefits maize production in Europe due to the little conflict of water use for irrigation. Our findings suggest the importance of simulating the river water availability and crop production in a single model for the more realistic assessment in the irrigation adaptation potential effects of crop production under changing climate and land use.

Application of MC1 to Wind Cave National Park: Lessons from a small-scale study: Chapter 8

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2015-01-01

MC1 was designed for application to large regions that include a wide range in elevation and topography, thereby encompassing a broad range in climates and vegetation types. The authors applied the dynamic global vegetation model MC1 to Wind Cave National Park (WCNP) in the southern Black Hills of South Dakota, USA, on the ecotone between ponderosa pine forest to the northwest and mixed-grass prairie to the southeast. They calibrated MC1 to simulate adequate fire effects in the warmer southeastern parts of the park to ensure grasslands there, while allowing forests to grow to the northwest, and then simulated future vegetation with climate projections from three GCMs. The results suggest that fire frequency, as affected by climate and/or human intervention, may be more important than the direct effects of climate in determining the distribution of ponderosa pine in the Black Hills region, both historically and in the future.

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

Adapting wheat to uncertain future

NASA Astrophysics Data System (ADS)

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.

A large ozone-circulation feedback and its implications for global warming assessments.

PubMed

Nowack, Peer J; Abraham, N Luke; Maycock, Amanda C; Braesicke, Peter; Gregory, Jonathan M; Joshi, Manoj M; Osprey, Annette; Pyle, John A

2015-01-01

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever 1 . Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations 1,2 . Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO 2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies 1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks 3-5 .

An integrated land change model for projecting future climate and land change scenarios

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.

2013-01-01

Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2010-05-01

In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

An Investigation of Aerosol-Cloud-Precipitation Interactions in the South-East Pacific Using DOE G-1 Data and WRF/Chem Large Eddy Simulations

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

McFarlane, Sally; Feingold, Graham; Kazil, Jan

2015-12-04

Under this grant, we investigated marine boundary layer clouds, their properties, behavior, and response to human activity and climate change, with a focus on scales and processes that cannot be studied with climate models. Investigated topics and results are summarized in this section. Detailed information are given in subsequent sections, followed by a list of resulting publications.

Combined climate and carbon-cycle effects of large-scale deforestation

PubMed Central

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

Combined climate and carbon-cycle effects of large-scale deforestation.

PubMed

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.

Web based visualization of large climate data sets

USGS Publications Warehouse

Alder, Jay R.; Hostetler, Steven W.

2015-01-01

We have implemented the USGS National Climate Change Viewer (NCCV), which is an easy-to-use web application that displays future projections from global climate models over the United States at the state, county and watershed scales. We incorporate the NASA NEX-DCP30 statistically downscaled temperature and precipitation for 30 global climate models being used in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), and hydrologic variables we simulated using a simple water-balance model. Our application summarizes very large, complex data sets at scales relevant to resource managers and citizens and makes climate-change projection information accessible to users of varying skill levels. Tens of terabytes of high-resolution climate and water-balance data are distilled to compact binary format summary files that are used in the application. To alleviate slow response times under high loads, we developed a map caching technique that reduces the time it takes to generate maps by several orders of magnitude. The reduced access time scales to >500 concurrent users. We provide code examples that demonstrate key aspects of data processing, data exporting/importing and the caching technique used in the NCCV.

Substantial large-scale feedbacks between natural aerosols and climate

NASA Astrophysics Data System (ADS)

Scott, C. E.; Arnold, S. R.; Monks, S. A.; Asmi, A.; Paasonen, P.; Spracklen, D. V.

2018-01-01

The terrestrial biosphere is an important source of natural aerosol. Natural aerosol sources alter climate, but are also strongly controlled by climate, leading to the potential for natural aerosol-climate feedbacks. Here we use a global aerosol model to make an assessment of terrestrial natural aerosol-climate feedbacks, constrained by observations of aerosol number. We find that warmer-than-average temperatures are associated with higher-than-average number concentrations of large (>100 nm diameter) particles, particularly during the summer. This relationship is well reproduced by the model and is driven by both meteorological variability and variability in natural aerosol from biogenic and landscape fire sources. We find that the calculated extratropical annual mean aerosol radiative effect (both direct and indirect) is negatively related to the observed global temperature anomaly, and is driven by a positive relationship between temperature and the emission of natural aerosol. The extratropical aerosol-climate feedback is estimated to be -0.14 W m-2 K-1 for landscape fire aerosol, greater than the -0.03 W m-2 K-1 estimated for biogenic secondary organic aerosol. These feedbacks are comparable in magnitude to other biogeochemical feedbacks, highlighting the need for natural aerosol feedbacks to be included in climate simulations.

Combined Climate and Carbon-Cycle Effects of Large-Scale Deforestation

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

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

The Eemian climate simulated by two models of different complexities

NASA Astrophysics Data System (ADS)

Nikolova, Irina; Yin, Qiuzhen; Berger, Andre; Singh, Umesh; Karami, Pasha

2013-04-01

The Eemian period, also known as MIS-5, experienced warmer than today climate, reduction in ice sheets and important sea-level rise. These interesting features have made the Eemian appropriate to evaluate climate models when forced with astronomical and greenhouse gas forcings different from today. In this work, we present the simulated Eemian climate by two climate models of different complexities, LOVECLIM (LLN Earth system model of intermediate complexity) and CCSM3 (NCAR atmosphere-ocean general circulation model). Feedbacks from sea ice, vegetation, monsoon and ENSO phenomena are discussed to explain the regional similarities/dissimilarities in both models with respect to the pre-industrial (PI) climate. Significant warming (cooling) over almost all the continents during boreal summer (winter) leads to a largely increased (reduced) seasonal contrast in the northern (southern) hemisphere, mainly due to the much higher (lower) insolation received by the whole Earth in boreal summer (winter). The arctic is warmer than at PI through the whole year, resulting from its much higher summer insolation and its remnant effect in the following fall-winter through the interactions between atmosphere, ocean and sea ice. Regional discrepancies exist in the sea-ice formation zones between the two models. Excessive sea-ice formation in CCSM3 results in intense regional cooling. In both models intensified African monsoon and vegetation feedback are responsible for the cooling during summer in North Africa and on the Arabian Peninsula. Over India precipitation maximum is found further west, while in Africa the precipitation maximum migrates further north. Trees and grassland expand north in Sahel/Sahara, trees being more abundant in the results from LOVECLIM than from CCSM3. A mix of forest and grassland occupies continents and expand deep in the high northern latitudes in line with proxy records. Desert areas reduce significantly in Northern Hemisphere, but increase in North Australia. Tropical Pacific sea-surface temperature (SST) annual cycle, modeled by CCSM3, suggests a minor shift towards an El Nino. However, the SST variability in our LOVECLIM simulations is particularly small due to the overestimated thermocline's depth. The simulated large-scale climate change during the Eemian compares reasonably well with proxy data, giving credit to both models and climate reconstructions. Acknowledgments This work and I. Nikolova, U. K. Singh and M. P. Karami are supported by the European Research Council Advanced Grant EMIS (No 227348 of the Program 'Ideas'). Q. Z. Yin is supported by the Belgian National Fund for Scientific Research (F. R. S. -FNRS). N. Herold is thanked for the simulations with CCSM3. Access to computer facilities was made easier through sponsorship from S. A. Electrabel, Belgium. Keywords: CCSM3, LOVECLIM, MIS-5, surface temperature, monsoon, vegetation, ENSO

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2012-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from largescale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol--cloud-precipitation interactions are suggested.

Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty.

PubMed

Leedale, Joseph; Tompkins, Adrian M; Caminade, Cyril; Jones, Anne E; Nikulin, Grigory; Morse, Andrew P

2016-03-31

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

Drought Persistence Errors in Global Climate Models

NASA Astrophysics Data System (ADS)

Moon, H.; Gudmundsson, L.; Seneviratne, S. I.

2018-04-01

The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, but the capability of current global climate models (GCMs) to simulate such events is subject to large uncertainties. In this study, the representation of drought persistence in GCMs is assessed by comparing state-of-the-art GCM model simulations to observation-based data sets. For doing so, we consider dry-to-dry transition probabilities at monthly and annual scales as estimates for drought persistence, where a dry status is defined as negative precipitation anomaly. Though there is a substantial spread in the drought persistence bias, most of the simulations show systematic underestimation of drought persistence at global scale. Subsequently, we analyzed to which degree (i) inaccurate observations, (ii) differences among models, (iii) internal climate variability, and (iv) uncertainty of the employed statistical methods contribute to the spread in drought persistence errors using an analysis of variance approach. The results show that at monthly scale, model uncertainty and observational uncertainty dominate, while the contribution from internal variability is small in most cases. At annual scale, the spread of the drought persistence error is dominated by the statistical estimation error of drought persistence, indicating that the partitioning of the error is impaired by the limited number of considered time steps. These findings reveal systematic errors in the representation of drought persistence in current GCMs and suggest directions for further model improvement.

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

Yim, Bo; Yeh, Sang -Wook; Sohn, Byung -Ju

Observational evidence shows that the Walker circulation (WC) in the tropical Pacific has strengthened in recent decades. In this study, we examine the WC trend for 1979–2005 and its relationship with the precipitation associated with the El Niño Southern Oscillation (ENSO) using the sea surface temperature (SST)-constrained Atmospheric Model Intercomparison Project (AMIP) simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. All of the 29 models show a strengthening of the WC trend in response to an increase in the SST zonal gradient along the equator. Despite the same SST-constrained AMIP simulations, however, a large diversity ismore » found among the CMIP5 climate models in the magnitude of the WC trend. The relationship between the WC trend and precipitation anomalies (PRCPAs) associated with ENSO (ENSO-related PRCPAs) shows that the longitudinal position of the ENSO-related PRCPAs in the western tropical Pacific is closely related to the magnitude of the WC trend. Specifically, it is found that the strengthening of the WC trend is large (small) in the CMIP5 AMIP simulations in which the ENSO-related PRCPAs are located relatively westward (eastward) in the western tropical Pacific. Furthermore, the zonal shift of the ENSO-related precipitation in the western tropical Pacific, which is associated with the climatological mean precipitation in the tropical Pacific, could play an important role in modifying the WC trend in the CMIP5 climate models.« less

Global environmental effects of impact-generated aerosols: Results from a general circulation model, revision 1

NASA Technical Reports Server (NTRS)

Covey, Curt; Ghan, Steven J.; Walton, John J.; Weissman, Paul R.

1989-01-01

Interception of sunlight by the high altitude worldwide dust cloud generated by impact of a large asteroid or comet would lead to substantial land surface cooling, according to our three-dimensional atmospheric general circulation model (GCM). This result is qualitatively similar to conclusions drawn from an earlier study that employed a one-dimensional atmospheric model, but in the GCM simulation the heat capacity of the oceans substantially mitigates land surface cooling, an effect that one-dimensional models cannot quantify. On the other hand, the low heat capacity of the GCM's land surface allows temperatures to drop more rapidly in the initial stage of cooling than in the one-dimensional model study. These two differences between three-dimensional and one-dimensional model simulations were noted previously in studies of nuclear winter; GCM-simulated climatic changes in the Alvarez-inspired scenario of asteroid/comet winter, however, are more severe than in nuclear winter because the assumed aerosol amount is large enough to intercept all sunlight falling on earth. Impacts of smaller objects could also lead to dramatic, though less severe, climatic changes, according to our GCM. Our conclusion is that it is difficult to imagine an asteroid or comet impact leading to anything approaching complete global freezing, but quite reasonable to assume that impacts at the Alvarez level, or even smaller, dramatically alter the climate in at least a patchy sense.

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

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

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

A basis set for exploration of sensitivity to prescribed ocean conditions for estimating human contributions to extreme weather in CAM5.1-1degree

DOE PAGES

Stone, Dáithí A.; Risser, Mark D.; Angélil, Oliver M.; ...

2018-03-01

This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are also specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change.The second contributionmore » takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.« less

The role of internal variability for decadal carbon uptake anomalies in the Southern Ocean

NASA Astrophysics Data System (ADS)

Spring, Aaron; Hi, Hongmei; Ilyina, Tatiana

2017-04-01

The Southern Ocean is a major sink for anthropogenic CO2 emissions and hence it plays an essential role in modulating global carbon cycle and climate change. Previous studies based on observations (e.g., Landschützer et al. 2015) show pronounced decadal variations of carbon uptake in the Southern Ocean in recent decades and this variability is largely driven by internal climate variability. However, due to limited ensemble size of simulations, the variability of this important ocean sink is still poorly assessed by the state-of-the-art earth system models (ESMs). To assess the internal variability of carbon sink in the Southern Ocean, we use a large ensemble of 100 member simulations based on the Max Planck Institute-ESM (MPI-ESM). The large ensemble of simulations is generated via perturbed initial conditions in the ocean and atmosphere. Each ensemble member includes a historical simulation from 1850 to 2005 with an extension until 2100 under Representative Concentration Pathway (RCP) 4.5 future projections. Here we use model simulations from 1980-2015 to compare with available observation-based dataset. We found several ensemble members showing decadal decreasing trends in the carbon sink, which are similar to the trend shown in observations. This result suggests that MPI-ESM large ensemble simulations are able to reproduce decadal variation of carbon sink in the Southern Ocean. Moreover, the decreasing trends of Southern Ocean carbon sink in MPI-ESM are mainly contributed by region between 50-60°S. To understand the internal variability of the air-sea carbon fluxes in the Southern Ocean, we further investigate the variability of underlying processes, such as physical climate variability and ocean biological processes. Our results indicate two main drivers for the decadal decreasing trend of carbon sink: i) Intensified winds enhance upwelling of old carbon-rich waters, this leads to increase of the ocean surface pCO2; ii) Primary production is reduced in area from 50-60°S, probably induced by reduced euphotic water column stability; therefore the biological drawdown of ocean surface pCO2 is weakened accordingly and hence the ocean is in favor of carbon outgassing. Landschützer, et al. (2015): The reinvigoration of the Southern Ocean carbon sink, Science, 349, 1221-1224.

Impacts of internal variability on temperature and precipitation trends in large ensemble simulations by two climate models

NASA Astrophysics Data System (ADS)

Dai, Aiguo; Bloecker, Christine E.

2018-02-01

It is known that internal climate variability (ICV) can influence trends seen in observations and individual model simulations over a period of decades. This makes it difficult to quantify the forced response to external forcing. Here we analyze two large ensembles of simulations from 1950 to 2100 by two fully-coupled climate models, namely the CESM1 and CanESM2, to quantify ICV's influences on estimated trends in annual surface air temperature (Tas) and precipitation (P) over different time periods. Results show that the observed trends since 1979 in global-mean Tas and P are within the spread of the CESM1-simulated trends while the CanESM2 overestimates the historical changes, likely due to its deficiencies in simulating historical non-CO2 forcing. Both models show considerable spreads in the Tas and P trends among the individual simulations, and the spreads decrease rapidly as the record length increases to about 40 (50) years for global-mean Tas (P). Because of ICV, local and regional P trends may remain statistically insignificant and differ greatly among individual model simulations over most of the globe until the later part of the twenty-first century even under a high emissions scenario, while local Tas trends since 1979 are already statistically significant over many low-latitude regions and are projected to become significant over most of the globe by the 2030s. The largest influences of ICV come from the Inter-decadal Pacific Oscillation and polar sea ice. In contrast to the realization-dependent ICV, the forced Tas response to external forcing has a temporal evolution that is similar over most of the globe (except its amplitude). For annual precipitation, however, the temporal evolution of the forced response is similar (opposite) to that of Tas over many mid-high latitude areas and the ITCZ (subtropical regions), but close to zero over the transition zones between the regions with positive and negative trends. The ICV in the transient climate change simulations is slightly larger than that in the control run for P (and other related variables such as water vapor), but similar for Tas. Thus, the ICV for P from a control run may need to be scaled up in detection and attribution analyses.

On the use of nudging techniques for regional climate modeling: application for tropical convection

NASA Astrophysics Data System (ADS)

Pohl, Benjamin; Crétat, Julien

2014-09-01

Using a large set of WRF ensemble simulations at 70-km horizontal resolution over a domain encompassing the Warm Pool region and its surroundings [45°N-45°S, 10°E-240°E], this study aims at quantifying how nudging techniques can modify the simulation of deep atmospheric convection. Both seasonal mean climate, transient variability at intraseasonal timescales, and the respective weight of internal (stochastic) and forced (reproducible) variability are considered. Sensitivity to a large variety of nudging settings (nudged variables and layers and nudging strength) and to the model physics (using 3 convective parameterizations) is addressed. Integrations are carried out during a 7-month season characterized by neutral background conditions and strong intraseasonal variability. Results show that (1) the model responds differently to the nudging from one parameterization to another. Biases are decreased by ~50 % for Betts-Miller-Janjic convection against 17 % only for Grell-Dévényi, the scheme producing yet the largest biases; (2) relaxing air temperature is the most efficient way to reduce biases, while nudging the wind increases most co-variability with daily observations; (3) the model's internal variability is drastically reduced and mostly depends on the nudging strength and nudged variables; (4) interrupting the relaxation before the end of the simulations leads to an abrupt convergence towards the model's natural solution, with no clear effects on the simulated climate after a few days. The usefulness and limitations of the approach are finally discussed through the example of the Madden-Julian Oscillation, that the model fails at simulating and that can be artificially and still imperfectly reproduced in relaxation experiments.

High-resolution RCMs as pioneers for future GCMs

NASA Astrophysics Data System (ADS)

Schar, C.; Ban, N.; Arteaga, A.; Charpilloz, C.; Di Girolamo, S.; Fuhrer, O.; Hoefler, T.; Leutwyler, D.; Lüthi, D.; Piaget, N.; Ruedisuehli, S.; Schlemmer, L.; Schulthess, T. C.; Wernli, H.

2017-12-01

Currently large efforts are underway to refine the horizontal resolution of global and regional climate models to O(1 km), with the intent to represent convective clouds explicitly rather than using semi-empirical parameterizations. This refinement will move the governing equations closer to first principles and is expected to reduce the uncertainties of climate models. High resolution is particularly attractive in order to better represent critical cloud feedback processes (e.g. related to global climate sensitivity and extratropical summer convection) and extreme events (such as heavy precipitation events, floods, and hurricanes). The presentation will be illustrated using decade-long simulations at 2 km horizontal grid spacing, some of these covering the European continent on a computational mesh with 1536x1536x60 grid points. To accomplish such simulations, use is made of emerging heterogeneous supercomputing architectures, using a version of the COSMO limited-area weather and climate model that is able to run entirely on GPUs. Results show that kilometer-scale resolution dramatically improves the simulation of precipitation in terms of the diurnal cycle and short-term extremes. The modeling framework is used to address changes of precipitation scaling with climate change. It is argued that already today, modern supercomputers would in principle enable global atmospheric convection-resolving climate simulations, provided appropriately refactored codes were available, and provided solutions were found to cope with the rapidly growing output volume. A discussion will be provided of key challenges affecting the design of future high-resolution climate models. It is suggested that km-scale RCMs should be exploited to pioneer this terrain, at a time when GCMs are not yet available at such resolutions. Areas of interest include the development of new parameterization schemes adequate for km-scale resolution, the exploration of new validation methodologies and data sets, the assessment of regional-scale climate feedback processes, and the development of alternative output analysis methodologies.

Development of ALARO-Climate regional climate model for a very high resolution

NASA Astrophysics Data System (ADS)

Skalak, Petr; Farda, Ales; Brozkova, Radmila; Masek, Jan

2013-04-01

ALARO-Climate is a new regional climate model (RCM) derived from the ALADIN LAM model family. It is based on the numerical weather prediction model ALARO and developed at the Czech Hydrometeorological Institute. The model is expected to able to work in the so called "grey zone" physics (horizontal resolution of 4 - 7 km) and at the same time retain its ability to be operated in resolutions in between 20 and 50 km, which are typical for contemporary generation of regional climate models. Here we present the main features of the RCM ALARO-Climate and results of the first model simulations on longer time-scales (1961-1990). The model was driven by the ERA-40/Interim re-analyses and run on the large pan-European integration domain ("ENSEMBLES / Euro-Cordex domain") with spatial resolution of 25 km. The simulated model climate was compared with the gridded observation of air temperature (mean, maximum, minimum) and precipitation from the E-OBS version 7 dataset. The validation of the first ERA-40 simulation has revealed significant cold biases in all seasons (between -4 and -2 °C) and overestimation of precipitation on 20% to 60% in the selected Central Europe target area (0° - 30° eastern longitude ; 40° - 60° northern latitude). The consequent adaptations in the model and their effect on the simulated properties of climate variables are illustrated. Acknowledgements: This study was performed within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation) and CzechGlobe Centre (CZ.1.05/1.1.00/02.0073). The partial support was also provided under the projects P209-11-0956 of the Czech Science Foundation and CZ.1.07/2.4.00/31.0056 (Operational Programme of Education for Competitiveness of Ministry of Education, Youth and Sports of the Czech Republic).

Can Regional Climate Models Improve Warm Season Forecasts in the North American Monsoon Region?

NASA Astrophysics Data System (ADS)

Dominguez, F.; Castro, C. L.

2009-12-01

The goal of this work is to improve warm season forecasts in the North American Monsoon Region. To do this, we are dynamically downscaling warm season CFS (Climate Forecast System) reforecasts from 1982-2005 for the contiguous U.S. using the Weather Research and Forecasting (WRF) regional climate model. CFS is the global coupled ocean-atmosphere model used by the Climate Prediction Center (CPC), a branch of the National Center for Environmental Prediction (NCEP), to provide official U.S. seasonal climate forecasts. Recently, NCEP has produced a comprehensive long-term retrospective ensemble CFS reforecasts for the years 1980-2005. These reforecasts show that CFS model 1) has an ability to forecast tropical Pacific SSTs and large-scale teleconnection patterns, at least as evaluated for the winter season; 2) has greater skill in forecasting winter than summer climate; and 3) demonstrates an increase in skill when a greater number of ensembles members are used. The decrease in CFS skill during the warm season is due to the fact that the physical mechanisms of rainfall at this time are more related to mesoscale processes, such as the diurnal cycle of convection, low-level moisture transport, propagation and organization of convection, and surface moisture recycling. In general, these are poorly represented in global atmospheric models. Preliminary simulations for years with extreme summer climate conditions in the western and central U.S. (specifically 1988 and 1993) show that CFS-WRF simulations can provide a more realistic representation of convective rainfall processes. Thus a RCM can potentially add significant value in climate forecasting of the warm season provided the downscaling methodology incorporates the following: 1) spectral nudging to preserve the variability in the large scale circulation while still permitting the development of smaller-scale variability in the RCM; and 2) use of realistic soil moisture initial condition, in this case provided by the North American Regional Reanalysis. With these conditions, downscaled CFS-WRF reforecast simulations can produce realistic continental-scale patterns of warm season precipitation. This includes a reasonable representation of the North American monsoon in the southwest U.S. and northwest Mexico, which is notoriously difficult to represent in a global atmospheric model. We anticipate that this research will help lead the way toward substantially improved real time operational forecasts of North American summer climate with a RCM.

Modeling the potential persistence of various ecological systems under CMIP5 future climate and land use scenarios throughout California, USA

NASA Astrophysics Data System (ADS)

Baker, B.; Ferschweiler, K.; Bachelet, D. M.; Sleeter, B. M.

2016-12-01

California's geographic location, topographic complexity and latitudinal climatic gradient give rise to great biological and ecological diversity. However, increased land use pressure, altered seasonal weather patterns, and changes in temperature and precipitation regimes are having pronounced effects on ecosystems and the multitude of services they provide for an increasing population. As a result, natural resource managers are faced with formidable challenges to maintain these critical services. The goals of this project were to better understand how projected 21st century climate and land-use change scenarios may alter ecosystem dynamics, the spatial distribution of various vegetation types and land-use patterns, and to provide a coarse scale "triage map" of where land managers may want to concentrate efforts to reduce ecological stress in order to mitigate the potential impacts of a changing climate. We used the MC2 dynamic global vegetation model and the LUCAS state-and-transition simulation model to simulate the potential effects of future climate and land-use change on ecological processes for the state of California. Historical climate data were obtained from the PRISM dataset and nine CMIP5 climate models were run for the RCP 8.5 scenario. Climate projections were combined with a business-as-usual land-use scenario based on local-scale land use histories. For ease of discussion, results from five simulation runs (historic, hot-dry, hot-wet, warm-dry, and warm-wet) are presented. Results showed large changes in the extent of urban and agricultural lands. In addition, several simulated potential vegetation types persisted in situ under all four future scenarios, although alterations in total area, total ecosystem carbon, and forest vigor (NPP/LAI) were noted. As might be expected, the majority of the forested types that persisted occurred on public lands. However, more than 78% of the simulated subtropical mixed forest and 26% of temperate evergreen needleleaf forest types persisted on private lands under all four future scenarios. Result suggest that building collaborations across management borders could be valuable tool to guide natural resource management actions into the future.

Tropical Cyclone Activity in the High-Resolution Community Earth System Model and the Impact of Ocean Coupling

NASA Astrophysics Data System (ADS)

Li, Hui; Sriver, Ryan L.

2018-01-01

High-resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Active air-sea coupling in a coupled model framework is essential to capturing TC-ocean interactions, which can influence TC-climate connections on interannual to decadal time scales. Here we investigate how the choices of ocean coupling can affect the directly simulated TCs using high-resolution configurations of the Community Earth System Model (CESM). We performed a suite of high-resolution, multidecadal, global-scale CESM simulations in which the atmosphere (˜0.25° grid spacing) is configured with three different levels of ocean coupling: prescribed climatological sea surface temperature (SST) (ATM), mixed layer ocean (SLAB), and dynamic ocean (CPL). We find that different levels of ocean coupling can influence simulated TC frequency, geographical distributions, and storm intensity. ATM simulates more storms and higher overall storm intensity than the coupled simulations. It also simulates higher TC track density over the eastern Pacific and the North Atlantic, while TC tracks are relatively sparse within CPL and SLAB for these regions. Storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions. Results help to improve our understanding about the representation of TCs in high-resolution coupled Earth system models, with important implications for TC-climate applications.

3D visualization of ultra-fine ICON climate simulation data

NASA Astrophysics Data System (ADS)

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.

Arctic climate response to geoengineering with stratospheric sulfate aerosols

NASA Astrophysics Data System (ADS)

McCusker, K. E.; Battisti, D. S.; Bitz, C. M.

2010-12-01

Recent warming and record summer sea-ice area minimums have spurred expressions of concern for arctic ecosystems, permafrost, and polar bear populations, among other things. Geoengineering by stratospheric sulfate aerosol injections to deliberately cancel the anthropogenic temperature rise has been put forth as a possible solution to restoring Arctic (and global) climate to modern conditions. However, climate is particularly sensitive in the northern high latitudes, responding easily to radiative forcing changes. To that end, we explore the extent to which tropical injections of stratospheric sulfate aerosol can accomplish regional cancellation in the Arctic. We use the Community Climate System Model version 3 global climate model to execute simulations with combinations of doubled CO2 and imposed stratospheric sulfate burdens to investigate the effects on high latitude climate. We further explore the sensitivity of the polar climate to ocean dynamics by running a suite of simulations with and without ocean dynamics, transiently and to equilibrium respectively. We find that, although annual, global mean temperature cancellation is accomplished, there is over-cooling on land in Arctic summer, but residual warming in Arctic winter, which is largely due to atmospheric circulation changes. Furthermore, the spatial extent of these features and their concurrent impacts on sea-ice properties are modified by the inclusion of ocean dynamical feedbacks.

Objective spatiotemporal proxy-model comparisons of the Asian monsoon for the last millennium

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Cook, E. R.; Ammann, C. M.; Buckley, B. M.; D'Arrigo, R. D.; Jacoby, G.; Wright, W. E.; Davi, N.; Li, J.

2008-12-01

The Asian monsoon system can be studied using a complementary proxy/simulation approach which evaluates climate models using estimates of past precipitation and temperature, and which subsequently applies the best understanding of the physics of the climate system as captured in general circulation models to evaluate the broad-scale dynamics behind regional paleoclimate reconstructions. Here, we use a millennial-length climate field reconstruction of monsoon season summer (JJA) drought, developed from tree- ring proxies, with coupled climate simulations from NCAR CSM1.4 and CCSM3 to evaluate the cause of large- scale persistent droughts over the last one thousand years. Direct comparisons are made between the external forced response within the climate model and the spatiotemporal field reconstruction. In order to identify patterns of drought associated with internal variability in the climate system, we use a model/proxy analog technique which objectively selects epochs in the model that most closely reproduce those observed in the reconstructions. The concomitant ocean-atmosphere dynamics are then interpreted in order to identify and understand the internal climate system forcing of low frequency monsoon variability. We examine specific periods of extensive or intensive regional drought in the 15th, 17th, and 18th centuries, many of which are coincident with major cultural changes in the region.

High Performance Computing-based Assessment of the Impacts of Climate Change on the Santa Cruz and San Pedro River Basin at Very High Resolution

NASA Astrophysics Data System (ADS)

Robles-Morua, A.; Vivoni, E. R.; Rivera-Fernandez, E. R.; Dominguez, F.; Meixner, T.

2012-12-01

Assessing the impact of climate change on large river basins in the southwestern United States is important given the natural water scarcity in the region. The bimodal distribution of annual precipitation also presents a challenge as differential climate impacts during the winter and summer seasons are not currently well understood. In this work, we focus on the hydrological consequences of climate change in the Santa Cruz and San Pedro river basins along the Arizona-Sonora border at high spatiotemporal resolutions (~100 m and ~1 hour). These river systems support rich ecological communities along riparian corridors that provide habitat to migratory birds and support recreational and economic activities. Determining the climate impacts on riparian communities involves assessing how river flows and groundwater recharge will change with altered temperature and precipitation regimes. In this study, we use a distributed hydrologic model, known as the TIN-based Real-time Integrated Basin Simulator (tRIBS), to generate simulated hydrological fields under historical (1991-2000) and climate change (2031-2040) scenarios obtained from an application of the Weather Research and Forecast (WRF) model. Using the distributed model, we transform the meteorological scenarios from WRF at 10-km, hourly resolution into predictions of the annual water budget, seasonal land surface fluxes and individual hydrographs of flood and recharge events. For this contribution, we selected two full years in the historical period and in the future scenario that represent wet and dry conditions for each decade. Given the size of the two basins, we rely on a high performance computing platform and a parallel domain discretization using sub-basin partitioning with higher resolutions maintained at experimental catchments in each river basin. Model simulations utilize best-available data across the Arizona-Sonora border on topography, land cover and soils obtained from analysis of remotely-sensed imagery and government databases. For the historical period, we build confidence in the model simulations through comparisons with streamflow estimates in the region. We also evaluate the WRF forcing outcomes with respect to meteorological inputs from ground rain gauges and the North American Land Data Assimilation System (NLDAS). We then analyze the high-resolution spatiotemporal predictions of soil moisture, evapotranspiration, runoff generation and recharge under past conditions and for the climate change scenario. A comparison with the historical period will yield a first-of-its-kind assessment at very high spatiotemporal resolution on the impacts of climate change on the hydrologic response of two large semiarid river basins of the southwestern United States.

Natural variability of marine ecosystems inferred from a coupled climate to ecosystem simulation

NASA Astrophysics Data System (ADS)

Le Mézo, Priscilla; Lefort, Stelly; Séférian, Roland; Aumont, Olivier; Maury, Olivier; Murtugudde, Raghu; Bopp, Laurent

2016-01-01

This modeling study analyzes the simulated natural variability of pelagic ecosystems in the North Atlantic and North Pacific. Our model system includes a global Earth System Model (IPSL-CM5A-LR), the biogeochemical model PISCES and the ecosystem model APECOSM that simulates upper trophic level organisms using a size-based approach and three interactive pelagic communities (epipelagic, migratory and mesopelagic). Analyzing an idealized (e.g., no anthropogenic forcing) 300-yr long pre-industrial simulation, we find that low and high frequency variability is dominant for the large and small organisms, respectively. Our model shows that the size-range exhibiting the largest variability at a given frequency, defined as the resonant range, also depends on the community. At a given frequency, the resonant range of the epipelagic community includes larger organisms than that of the migratory community and similarly, the latter includes larger organisms than the resonant range of the mesopelagic community. This study shows that the simulated temporal variability of marine pelagic organisms' abundance is not only influenced by natural climate fluctuations but also by the structure of the pelagic community. As a consequence, the size- and community-dependent response of marine ecosystems to climate variability could impact the sustainability of fisheries in a warming world.

A GCM comparison of Plio-Pleistocene interglacial-glacial periods in relation to Lake El'gygytgyn, NE Arctic Russia

NASA Astrophysics Data System (ADS)

Coletti, A. J.; DeConto, R. M.; Brigham-Grette, J.; Melles, M.

2014-08-01

Until now, the lack of time-continuous, terrestrial paleoenvironmental data from the Pleistocene Arctic has made model simulations of past interglacials difficult to assess. Here, we compare climate simulations of four warm interglacials at Marine Isotope Stage (MIS) 1 (9 ka), 5e (127 ka), 11c (409 ka), and 31 (1072 ka) with new proxy climate data recovered from Lake El'gygytgyn, NE Russia. Climate reconstructions of the Mean Temperature of the Warmest Month (MTWM) indicate conditions 2.1, 0.5 and 3.1 °C warmer than today during MIS 5e, 11c, and 31, respectively. While the climate model captures much of the observed warming during each interglacial, largely in response to boreal summer orbital forcing, the extraordinary warmth of MIS 11c relative to the other interglacials in the proxy records remain difficult to explain. To deconvolve the contribution of multiple influences on interglacial warming at Lake El'gygytgyn, we isolated the influence of vegetation, sea ice, and circum-Arctic land ice feedbacks on the climate of the Beringian interior. Simulations accounting for climate-vegetation-land surface feedbacks during all four interglacials show expanding boreal forest cover with increasing summer insolation intensity. A deglaciated Greenland is shown to have a minimal effect on Northeast Asian temperature during the warmth of stage 11c and 31 (Melles et al., 2012). A prescribed enhancement of oceanic heat transport into the Arctic ocean has some effect on Beringian climate, suggesting intrahemispheric coupling seen in comparisons between Lake El'gygytgyn and Antarctic sediment records might be related to linkages between Antarctic ice volume and ocean circulation. The exceptional warmth of MIS 11c remains enigmatic however, relative to the modest orbital and greenhouse gas forcing during that interglacial. Large Northern Hemisphere ice sheets during Plio-Pleistocene glaciation causes a substantial decrease in Mean Temperature of the Coldest Month (MTCM) and Mean Annual Precipitation (PANN) causing significant Arctic aridification. Aridification and cooling can be linked to a combination of mechanical forcing from the Laurentide and Fennoscandian ice sheets on mid-tropospheric westerly flow and expanded sea ice cover causing albedo-enhanced feedback.

Effects of local climate and hydrological conditions on the thermal regime of a reservoir at Tropic of Cancer, in southern China.

PubMed

Wang, Sheng; Qian, Xin; Han, Bo-Ping; Luo, Lian-Cong; Hamilton, David P

2012-05-15

Thermal regime is strongly associated with hydrodynamics in water, and it plays an important role in the dynamics of water quality and ecosystem succession of stratified reservoirs. Changes in both climate and hydrological conditions can modify thermal regimes. Liuxihe Reservoir (23°45'50″N; 113°46'52″E) is a large, stratified and deep reservoir in Guangdong Province, located at the Tropic of Cancer of southern China. The reservoir is a warm monomictic water body with a long period of summer stratification and a short period of mixing in winter. The vertical distribution of suspended particulate material and nutrients are influenced strongly by the thermal structure and the associated flow fields. The hypolimnion becomes anoxic in the stratified period, increasing the release of nutrients from the bottom sediments. Fifty-one years of climate and reservoir operational observations are used here to show the marked changes in local climate and reservoir operational schemes. The data show increasing air temperature and more violent oscillations in inflow volumes in the last decade, while the inter-annual water level fluctuations tend to be more moderate. To quantify the effects of changes in climate and hydrological conditions on thermal structure, we used a numerical simulation model to create scenarios incorporating different air temperatures, inflow volumes, and water levels. The simulations indicate that water column stability, the duration of the mixing period, and surface and outflow temperatures are influenced by both natural factors and by anthropogenic factors such as climate change and reservoir operation schemes. Under continuous warming and more stable storage in recent years, the simulations indicate greater water column stability and increased duration of stratification, while irregular large discharge events may reduce stability and lead to early mixing in autumn. Our results strongly suggest that more attention should be focused on water quality in years of extreme climate variation and hydrological conditions, and selective withdrawal of deep water may provide an efficient means to reduce internal loading in warm years. Copyright © 2012 Elsevier Ltd. All rights reserved.

Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

The Mediterranean surface wave climate inferred from future scenario simulations

NASA Astrophysics Data System (ADS)

Lionello, P.; Cogo, S.; Galati, M. B.; Sanna, A.

2008-09-01

This study is based on 30-year long simulations of the wind-wave field in the Mediterranean Sea carried out with the WAM model. Wave fields have been computed for the 2071-2100 period of the A2, B2 emission scenarios and for the 1961-1990 period of the present climate (REF). The wave model has been forced by the wind field computed by a regional climate model with 50 km resolution. The mean SWH (Significant Wave Height) field over large fraction of the Mediterranean sea is lower for the A2 scenario than for the present climate during winter, spring and autumn. During summer the A2 mean SWH field is also lower everywhere, except for two areas, those between Greece and Northern Africa and between Spain and Algeria, where it is significantly higher. All these changes are similar, though smaller and less significant, in the B2 scenario, except during winter in the north-western Mediterranean Sea, when the B2 mean SWH field is higher than in the REF simulation. Also extreme SWH values are smaller in future scenarios than in the present climate and such SWH change is larger for the A2 than for the B2 scenario. The only exception is the presence of higher SWH extremes in the central Mediterranean during summer for the A2 scenario. In general, changes of SWH, wind speed and atmospheric circulation are consistent, and results show milder marine storms in future scenarios than in the present climate.

Spatial and body-size dependent response of marine pelagic communities to projected global climate change.

PubMed

Lefort, Stelly; Aumont, Olivier; Bopp, Laurent; Arsouze, Thomas; Gehlen, Marion; Maury, Olivier

2015-01-01

Temperature, oxygen, and food availability directly affect marine life. Climate models project a global warming of the ocean's surface (~+3 °C), a de-oxygenation of the ocean's interior (~-3%) and a decrease in total marine net primary production (~-8%) under the 'business as usual' climate change scenario (RCP8.5). We estimated the effects of these changes on biological communities using a coupled biogeochemical (PISCES)--ecosystems (APECOSM) model forced by the physical outputs of the last generation of the IPSL-CM Earth System Model. The APECOSM model is a size-structured bio-energetic model that simulates the 3D dynamical distributions of three interactive pelagic communities (epipelagic, mesopelagic, and migratory) under the effects of multiple environmental factors. The PISCES-APECOSM model ran from 1850 to 2100 under historical forcing followed by RCP8.5. Our RCP8.5 simulation highlights significant changes in the spatial distribution, biomass, and maximum body-size of the simulated pelagic communities. Biomass and maximum body-size increase at high latitude over the course of the century, reflecting the capacity of marine organisms to respond to new suitable environment. At low- and midlatitude, biomass and maximum body-size strongly decrease. In those regions, large organisms cannot maintain their high metabolic needs because of limited and declining food availability. This resource reduction enhances the competition and modifies the biomass distribution among and within the three communities: the proportion of small organisms increases in the three communities and the migrant community that initially comprised a higher proportion of small organisms is favored. The greater resilience of small body-size organisms resides in their capacity to fulfill their metabolic needs under reduced energy supply and is further favored by the release of predation pressure due to the decline of large organisms. These results suggest that small body-size organisms might be more resilient to climate change than large ones. © 2014 John Wiley & Sons Ltd.

Impacts of large scale afforestation on regional climate: a case study in the Kubuqi Desert, Inner Mongolia based on WRF model

NASA Astrophysics Data System (ADS)

Wang, L.; Lin, G.; Feng, D.; Chen, S.; Schultz, N. M.; Fu, C.; Wei, Z.; Yin, C.; Wang, W.; Lee, X.

2017-12-01

To better design climate mitigation strategies, it is important to understand the response of regional climatic indicators and related biophysical forcings to large scale afforestation projects. The response of surface temperature (Ts) caused by afforestation activities in the Kubuqi Desert, Inner Mongolia, China is simulated by the weather research and forecasting (WRF) model and the temperature changes (ΔTs) are decomposed into contributions from changes in surface albedo, surface roughness, Bowen ratio and ground heat flux using the intrinsic biophysical mechanism (IBPM). The 30-m resolution land cover maps of the Kubuqi Desert corresponding to 2000 and 2010 conditions are analyzed and the major land use changes are found to be an increase in the area of grassland (6%) and shrubland (15%), but a decrease in the area of bare land (21%) owed to the aerial seeding afforestation activities organized by Elion Resources Group, Co. and local government agencies. Our WRF simulations show that during winter, the increased cover of vegetation mainly has a warming effect (0.38 K) in the daytime due to the changes in albedo (0.24 K) and Bowen ratio (0.15 K). In the nighttime, the vegetation has a slight warming effect (0.2 K) mainly caused by energy redistribution associated with roughness change (0.2 K) as a result of vegetation turbulence, which brought heat from aloft to the surface. Although both roughness change (-0.35 K) and Bowen ratio change (-0.35 K) have cooling effects during summer days, the warming effect caused by radiative forcing (0.93 K) dominates the ΔTs. During summer nights, the change in surface temperature is not significant. Our findings demonstrate that the large-scale afforestation project in the Kubuqi Desert during a decade alters the regional surface temperature and the analysis of biophysical forcings changes using WRF simulation provides useful information for developing climate change mitigation strategies in semi-arid and arid regions.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

An investigation of the Archean climate using the NCAR CCm

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

Jenkins, G.S.

1991-01-01

The Archean (2.5 to 3.8 billion years ago) is of interest climatically, because of the 'Faint-Young Sun Paradox', which can be characterized by the Sun's reduced energy output. This lower energy output leads to a frozen planet if the climate existed as it does today. But, the geologic record shows that water was flowing at the earth's surface 3.8 billion years ago. Energy Balance Models (EBMs) and one-dimensional radiative-convective (1DRC) models predict a frozen planet for this time period, unless large carbon dioxide (CO2) concentrations exist in the Archean atmosphere. The goal is to explore the Archean climate with themore » National Center for Atmospheric Research (NCAR), Community Climate Model (CCM). The search for negative feedbacks to explain the 'Faint-Young Sun Paradox' is the thrust of this study. This study undertakes a series of sensitivity simulations which first explores individual factors that may be important for the Archean. They include rotation rate, lower solar luminosity, and land fraction. Then, these climatic factors along with higher CO2 concentrations are combined into a set of experiments. A faster rotation rate may have existed in the Archean. The faster rotation rate simulations show warmer globally averaged surface temperatures that are caused by a 20 percent decrease in the total cloud fraction. The smaller cloud fraction is brought about by dynamical changes. A global ocean is a possibility for the Archean. A global ocean simulation predicts 4 K increase in global mean surface temperatures compared to the present-day climate control.« less

A Regional Climate Model Evaluation System based on Satellite and other Observations

NASA Astrophysics Data System (ADS)

Lean, P.; Kim, J.; Waliser, D. E.; Hall, A. D.; Mattmann, C. A.; Granger, S. L.; Case, K.; Goodale, C.; Hart, A.; Zimdars, P.; Guan, B.; Molotch, N. P.; Kaki, S.

2010-12-01

Regional climate models are a fundamental tool needed for downscaling global climate simulations and projections, such as those contributing to the Coupled Model Intercomparison Projects (CMIPs) that form the basis of the IPCC Assessment Reports. The regional modeling process provides the means to accommodate higher resolution and a greater complexity of Earth System processes. Evaluation of both the global and regional climate models against observations is essential to identify model weaknesses and to direct future model development efforts focused on reducing the uncertainty associated with climate projections. However, the lack of reliable observational data and the lack of formal tools are among the serious limitations to addressing these objectives. Recent satellite observations are particularly useful as they provide a wealth of information on many different aspects of the climate system, but due to their large volume and the difficulties associated with accessing and using the data, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL / UCLA is developing a model evaluation system to help make satellite observations, in conjunction with in-situ, assimilated, and reanalysis datasets, more readily accessible to the modeling community. The system includes a central database to store multiple datasets in a common format and codes for calculating predefined statistical metrics to assess model performance. This allows the time taken to compare model simulations with satellite observations to be reduced from weeks to days. Early results from the use this new model evaluation system for evaluating regional climate simulations over California/western US regions will be presented.

Diagnosis of boreal summer intraseasonal oscillation in high resolution NCEP climate forecast system

NASA Astrophysics Data System (ADS)

Abhik, S.; Mukhopadhyay, P.; Krishna, R. P. M.; Salunke, Kiran D.; Dhakate, Ashish R.; Rao, Suryachandra A.

2016-05-01

The present study examines the ability of high resolution (T382) National Centers for Environmental Prediction coupled atmosphere-ocean climate forecast system version 2 (CFS T382) in simulating the salient spatio-temporal characteristics of the boreal summertime mean climate and the intraseasonal variability. The shortcomings of the model are identified based on the observation and compared with earlier reported biases of the coarser resolution of CFS (CFS T126). It is found that the CFS T382 reasonably mimics the observed features of basic state climate during boreal summer. But some prominent biases are noted in simulating the precipitation, tropospheric temperature (TT) and sea surface temperature (SST) over the global tropics. Although CFS T382 primarily reproduces the observed distribution of the intraseasonal variability over the Indian summer monsoon region, some difficulty remains in simulating the boreal summer intraseasonal oscillation (BSISO) characteristics. The simulated eastward propagation of BSISO decays rapidly across the Maritime Continent, while the northward propagation appears to be slightly slower than observation. However, the northward propagating BSISO convection propagates smoothly from the equatorial region to the northern latitudes with observed magnitude. Moreover, the observed northwest-southeast tilted rain band is not well reproduced in CFS T382. The warm mean SST bias and inadequate simulation of high frequency modes appear to be responsible for the weak simulation of eastward propagating BSISO. Unlike CFS T126, the simulated mean SST and TT exhibit warm biases, although the mean precipitation and simulated BSISO characteristics are largely similar in both the resolutions of CFS. Further analysis of the convectively coupled equatorial waves (CCEWs) indicates that model overestimates the gravest equatorial Rossby waves and underestimates the Kelvin and mixed Rossby-gravity waves. Based on analysis of CCEWs, the study further explains the possible reasons behind the realistic simulation of northward propagating BSISO in CFS T382, even though the model shows substantial biases in simulating mean state and other BSISO modes.

Impact of derived global weather data on simulated crop yields

PubMed Central

van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

2013-01-01

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. PMID:23801639

Impact of derived global weather data on simulated crop yields.

PubMed

van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

2013-12-01

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. © 2013 John Wiley & Sons Ltd.

First Evaluation of the CCAM Aerosol Simulation over Africa: Implications for Regional Climate Modeling

NASA Astrophysics Data System (ADS)

Horowitz, H.; Garland, R. M.; Thatcher, M. J.; Naidoo, M.; van der Merwe, J.; Landman, W.; Engelbrecht, F.

2015-12-01

An accurate representation of African aerosols in climate models is needed to understand the regional and global radiative forcing and climate impacts of aerosols, at present and under future climate change. However, aerosol simulations in regional climate models for Africa have not been well-tested. Africa contains the largest single source of biomass-burning smoke aerosols and dust globally. Although aerosols are short-lived relative to greenhouse gases, black carbon in particular is estimated to be second only to carbon dioxide in contributing to warming on a global scale. Moreover, Saharan dust is exported great distances over the Atlantic Ocean, affecting nutrient transport to regions like the Amazon rainforest, which can further impact climate. Biomass burning aerosols are also exported from Africa, westward from Angola over the Atlantic Ocean and off the southeastern coast of South Africa to the Indian Ocean. Here, we perform the first extensive quantitative evaluation of the Conformal-Cubic Atmospheric Model (CCAM) aerosol simulation against monitored data, focusing on aerosol optical depth (AOD) observations over Africa. We analyze historical regional simulations for 1999 - 2012 from CCAM consistent with the experimental design of CORDEX at 50 km global horizontal resolution, through the dynamical downscaling of ERA-Interim data reanalysis data, with the CMIP5 emissions inventory (RCP8.5 scenario). CCAM has a prognostic aerosol scheme for organic carbon, black carbon, sulfate, and dust, and non-prognostic sea salt. The CCAM AOD at 550nm was compared to AOD (observed at 440nm, adjusted to 550nm with the Ångström exponent) from long-term AERONET stations across Africa. Sites strongly impacted by dust and biomass burning and with long continuous records were prioritized. In general, the model captures the monthly trends of the AERONET data. This presentation provides a basis for understanding how well aerosol particles are represented over Africa in regional climate modeling and the potential impact on climate predictions, and is the first large scale climate model-measurement verification of aerosols over Africa that we are aware of. CCAM is widely used for regional climate modeling applications, and we also discuss further improvements to the aerosol parameterizations based on our results.

The UK Earth System Model project

NASA Astrophysics Data System (ADS)

Tang, Yongming

2016-04-01

In this talk we will describe the development and current status of the UK Earth System Model (UKESM). This project is a NERC/Met Office collaboration and has two objectives; to develop and apply a world-leading Earth System Model, and to grow a community of UK Earth System Model scientists. We are building numerical models that include all the key components of the global climate system, and contain the important process interactions between global biogeochemistry, atmospheric chemistry and the physical climate system. UKESM will be used to make key CMIP6 simulations as well as long-time (e.g. millennium) simulations, large ensemble experiments and investigating a range of future carbon emission scenarios.

New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

QUAL-NET, a high temporal-resolution eutrophication model for large hydrographic networks

NASA Astrophysics Data System (ADS)

Minaudo, Camille; Curie, Florence; Jullian, Yann; Gassama, Nathalie; Moatar, Florentina

2018-04-01

To allow climate change impact assessment of water quality in river systems, the scientific community lacks efficient deterministic models able to simulate hydrological and biogeochemical processes in drainage networks at the regional scale, with high temporal resolution and water temperature explicitly determined. The model QUALity-NETwork (QUAL-NET) was developed and tested on the Middle Loire River Corridor, a sub-catchment of the Loire River in France, prone to eutrophication. Hourly variations computed efficiently by the model helped disentangle the complex interactions existing between hydrological and biological processes across different timescales. Phosphorus (P) availability was the most constraining factor for phytoplankton development in the Loire River, but simulating bacterial dynamics in QUAL-NET surprisingly evidenced large amounts of organic matter recycled within the water column through the microbial loop, which delivered significant fluxes of available P and enhanced phytoplankton growth. This explained why severe blooms still occur in the Loire River despite large P input reductions since 1990. QUAL-NET could be used to study past evolutions or predict future trajectories under climate change and land use scenarios.

The evolution of extreme precipitations in high resolution scenarios over France

NASA Astrophysics Data System (ADS)

Colin, J.; Déqué, M.; Somot, S.

2009-09-01

Over the past years, improving the modelling of extreme events and their variability at climatic time scales has become one of the challenging issue raised in the regional climate research field. This study shows the results of a high resolution (12 km) scenario run over France with the limited area model (LAM) ALADIN-Climat, regarding the representation of extreme precipitations. The runs were conducted in the framework of the ANR-SCAMPEI national project on high resolution scenarios over French mountains. As a first step, we attempt to quantify one of the uncertainties implied by the use of LAM : the size of the area on which the model is run. In particular, we address the issue of whether a relatively small domain allows the model to create its small scale process. Indeed, high resolution scenarios cannot be run on large domains because of the computation time. Therefore one needs to answer this preliminary question before producing and analyzing such scenarios. To do so, we worked in the framework of a « big brother » experiment. We performed a 23-year long global simulation in present-day climate (1979-2001) with the ARPEGE-Climat GCM, at a resolution of approximately 50 km over Europe (stretched grid). This first simulation, named ARP50, constitutes the « big brother » reference of our experiment. It has been validated in comparison with the CRU climatology. Then we filtered the short waves (up to 200 km) from ARP50 in order to obtain the equivalent of coarse resolution lateral boundary conditions (LBC). We have carried out three ALADIN-Climat simulations at a 50 km resolution with these LBC, using different configurations of the model : * FRA50, run over a small domain (2000 x 2000 km, centered over France), * EUR50, run over a larger domain (5000 x 5000 km, centered over France as well), * EUR50-SN, run over the large domain (using spectral nudging). Considering the facts that ARPEGE-Climat and ALADIN-Climat models share the same physics and dynamics and that both regional and global simulations were run at the same resolution, ARP50 can be regarded as a reference with which FRA50, EUR50 and EUR50-SN should each be compared. After an analysis of the differences between the regional simulations and ARP50 in annual and seasonal mean, we focus on the representation of rainfall extremes comparing two dimensional fields of various index inspired from STARDEX and quantile-quantile plots. The results show a good agreement with the ARP50 reference for all three regional simulations and little differences are found between them. This result indicates that the use of small domains is not significantly detrimental to the modelling of extreme precipitation events. It also shows that the spectral nudging technique has no detrimental effect on the extreme precipitation. Therefore, high resolution scenarios performed on a relatively small domain such as the ones run for SCAMPEI, can be regarded as good tools to explore their possible evolution in the future climate. Preliminary results on the response of precipitation extremes over South-East France are given.

[Research advances in dendrochronology].

PubMed

Fang, Ke-Yan; Chen, Qiu-Yan; Liu, Chang-Zhi; Cao, Chun-Fu; Chen, Ya-Jun; Zhou, Fei-Fei

2014-07-01

Tree-ring studies in China have achieved great advances since the 1990s, particularly for the dendroclimatological studies which have made some influence around the world. However, because of the uneven development, limited attention has been currently paid on the other branches of dendrochronology. We herein briefly compared the advances of dendrochronology in China and of the world and presented suggestions on future dendrochronological studies. Large-scale tree-ring based climate reconstructions in China are highly needed by employing mathematical methods and a high quality tree-ring network of the ring-width, density, stable isotope and wood anatomy. Tree-ring based field climate reconstructions provide potentials on explorations of climate forcings during the reconstructed periods via climate diagnosis and process simulation.

An approach for assessing the sensitivity of floods to regional climate change

NASA Astrophysics Data System (ADS)

Hughes, James P.; Lettenmaier, Dennis P.; Wood, Eric F.

1992-06-01

A high visibility afforded climate change issues is recent years has led to conflicts between and among decision makers and scientists. Decision makers inevitably feel pressure to assess the effect of climate change on the public welfare, while most climate modelers are, to a greater or lesser degree, concerned about the extent to which known inaccuracies in their models limit or preclude the use of modeling results for policy making. The water resources sector affords a good example of the limitations of the use of alternative climate scenarios derived from GCMs for decision making. GCM simulations of precipitation agree poorly between GCMs, and GCM predictions of runoff and evapotranspiration are even more uncertain. Further, water resources managers must be concerned about hydrologic extremes (floods and droughts) which are much more difficult to predict than ``average'' conditions. Most studies of the sensitivity of water resource systems and operating policies to climate change to data have been based on simple perturbations of historic hydroclimatological time series to reflect the difference between large area GCM simulations for an altered climate (e.g., CO2 doubling) and a GCM simulation of present climate. Such approaches are especially limited for assessment of the sensitivity of water resources systems under extreme conditions, conditions, since the distribution of storm inter-arrival times, for instance, is kept identical to that observed in the historic past. Further, such approaches have generally been based on the difference between the GCM altered and present climates for a single grid cell, primarily because the GCM spatial scale is often much larger than the scale at which climate interpretations are desired. The use of single grid cell GCM results is considered inadvisable by many GCM modelers, who feel the spatial scale for which interpretation of GCM results is most reasonable is on the order of several grid cells. In this paper, we demonstrate an alternative approach to assessing the implications of altered climates as predicted by GCMs for extreme (flooding) conditions. The approach is based on the characterization of regional atmospheric circulation patterns through a weather typing procedure, from which a stochastic model of the weather class occurrences is formulated. Weather types are identified through a CART (Classification and Regression Tree) approach. Precipitation occurence/non-occurence at multiple precipitation station is then predicted through a second stage stochastic model. Precipitation amounts are predicted conditional on the weather class identified from the large area circulation information.

Modeling the "Year without summer 1816" with the CCM SOCOL

NASA Astrophysics Data System (ADS)

Arfeuille, Florian; Rozanov, Eugene; Peter, Thomas; Fischer, Andreas. M.; Weisenstein, Debra; Brönnimann, Stefan

2010-05-01

The "Year without summer" 1816 had profound social and environmental effects, and although the cataclysmic eruption of Mt Tambora is now commonly known to have largely contributed to the negative temperature anomalies of the summer 1816 in Europe and North America, lots of uncertainties remain. The eruption of Mt. Tambora in April 1815 is the largest within the last 500 years. A crucial parameter to assess in order to simulate this eruption is the aerosol size distribution, which strongly influences the radiative impact of the aerosols (changes in albedo and residence time in the stratosphere, among others) and the impacts on dynamics and chemistry. The representation of this major forcing is done by using the AER-2D aerosol model which calculates the size distribution of the aerosols formed after the eruption. The modeling of the climatic impacts is then done by the state-of-the-art Chemistry-Climate model (CCM) SOCOL. The importance of stratospheric processes for the study of the "Year without summer" 1816 justifies the choice of a CCM which allows a precise analysis of the radiative, dynamical and chemical impacts of the Tambora eruption. The 1810's decade is an interesting period as it combines both a strong signal to noise ratio for the study of the impacts of the volcanic forcing, and an availability of several high resolution climate proxies allowing a credible reconstruction of interesting climatic components like Sea Surface Temperatures (SST) which are forced in the CCM . This can particularly provide a realistic description of the inter-annual variability linked to the major atmosphere/ocean coupled oscillations such as ENSO. Reconstructions based on inland natural proxies and early instrumental records can then be used to validate the simulated climate. I will present the characteristics of the Tambora eruption and show some results from simulations made using the aerosol model/CCM, with an emphasis on the radiative and chemical implications of the large aerosol sizes produced by the Mt. Tambora 60-80MT SO2 release. For instance, the specific absorption/scattering ratio of Mt.Tambora aerosols induced a very large stratospheric warming which will be analyzed. The climatic impacts will also be discussed in regards of the high sedimentation rate of Mt. Tambora aerosols, leading to a fast decrease of the atmospheric optical depth in the first two years after the eruption.

Synthetic drought event sets: thousands of meteorological drought events for risk-based management under present and future conditions

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Massey, Neil; Otto, Friederike E. L.; Allen, Myles R.; Jones, Richard; Hall, Jim W.

2016-04-01

Droughts and related water scarcity can have large impacts on societies and consist of interactions between a number of natural and human factors. Meteorological conditions are usually the first natural trigger of droughts, and climate change is expected to impact these and thereby the frequency and intensity of the events. However, extreme events such as droughts are, by definition, rare, and accurately quantifying the risk related to such events is therefore difficult. The MaRIUS project (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity) aims at quantifying the risks associated with droughts in the UK under present and future conditions. To do so, a large number of drought events, from climate model simulations downscaled at 25km over Europe, are being fed into hydrological models of various complexity and used for the estimation of drought risk associated with human and natural systems, including impacts on the economy, industry, agriculture, terrestrial and aquatic ecosystems, and socio-cultural aspects. Here, we present the hydro-meteorological drought event set that has been produced by weather@home [1] for MaRIUS. Using idle processor time on volunteers' computers around the world, we have run a very large number (10'000s) of Global Climate Model (GCM) simulations, downscaled at 25km over Europe by a nested Regional Climate Model (RCM). Simulations include the past 100 years as well as two future horizons (2030s and 2080s), and provide a large number of sequences of spatio-temporally consistent weather, which are consistent with the boundary forcing such as the ocean, greenhouse gases and solar forcing. The drought event set for use in impact studies is constructed by extracting sequences of dry conditions from these model runs, leading to several thousand drought events. In addition to describing methodological and validation aspects of the synthetic drought event sets, we provide insights into drought risk in the UK, its meteorological drivers, and how it can be expected to change in the future. Finally, we assess the applicability of this methodology to other regions. [1] Massey, N. et al., 2014, Q. J. R. Meteorol. Soc.

A strategy for representing the effects of convective momentum transport in multiscale models: Evaluation using a new superparameterized version of the Weather Research and Forecast model (SP-WRF)

NASA Astrophysics Data System (ADS)

Tulich, S. N.

2015-06-01

This paper describes a general method for the treatment of convective momentum transport (CMT) in large-scale dynamical solvers that use a cyclic, two-dimensional (2-D) cloud-resolving model (CRM) as a "superparameterization" of convective-system-scale processes. The approach is similar in concept to traditional parameterizations of CMT, but with the distinction that both the scalar transport and diagnostic pressure gradient force are calculated using information provided by the 2-D CRM. No assumptions are therefore made concerning the role of convection-induced pressure gradient forces in producing up or down-gradient CMT. The proposed method is evaluated using a new superparameterized version of the Weather Research and Forecast model (SP-WRF) that is described herein for the first time. Results show that the net effect of the formulation is to modestly reduce the overall strength of the large-scale circulation, via "cumulus friction." This statement holds true for idealized simulations of two types of mesoscale convective systems, a squall line, and a tropical cyclone, in addition to real-world global simulations of seasonal (1 June to 31 August) climate. In the case of the latter, inclusion of the formulation is found to improve the depiction of key synoptic modes of tropical wave variability, in addition to some aspects of the simulated time-mean climate. The choice of CRM orientation is also found to importantly affect the simulated time-mean climate, apparently due to changes in the explicit representation of wide-spread shallow convective regions.

Climate change and maize yield in southern Africa: what can farm management do?

PubMed

Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E

2015-12-01

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.

Estimation and Correction of bias of long-term simulated climate data from Global Circulation Models (GCMs)

NASA Astrophysics Data System (ADS)

Mehan, S.; Gitau, M. W.

2017-12-01

Global circulation models are often used in simulating long-term climate data for use in hydrologic studies. However, some bias (difference between simulated values and observed data) has been observed especially while simulating precipitation events. The bias is especially evident with respect to simulating dry and wet days. This is because GCMs tend to underestimate large precipitation events with the associated precipitation amounts being distributed to some dry days, thus, leading to a larger number of wet days each with some amount of rainfall. The accuracy of precipitation simulations impacts the accuracy of other simulated components such as flow and water quality. It is, thus, very important to correct the bias associated with precipitation before it is used for any modeling applications. This study aims to correct the bias specifically associated with precipitation events with a focus on the Western Lake Erie Basin (WLEB). Analytical, statistical, and extreme event analyses for three different stations (Adrian, MI; Norwalk, OH; and Fort Wayne, IN) in the WLEB were carried out to quantify the bias. Findings indicated that GCMs overestimated the wet sequences and underestimated dry day probabilities. The number of wet sequences simulated by nine GCMs each from two different open sources were 310-678 (Fort Wayne, IN); 318-600 (Adrian, MI); and 346-638 (Norwalk, OH) compared with 166, 150, and 180, respectively. Predicted conditional probabilities of a dry day followed by wet day (P (D|W)) ranged between 0.16-0.42 (Fort Wayne, IN); 0.29-0.41(Adrian, MI); and 0.13-0.40 (Norwalk, OH) from the different GCMs compared to 0.52 (Fort Wayne, IN and Norwalk, OH); and 0.54 (Adrian, MI) from the observed climate data. There was a difference of 0-8.5% between the distribution of simulated climate values and observed climate data for precipitation and temperature for all three stations (Cohen's d effective size < 0.2). Further work involves the use of Stochastic Weather Generators to correct the conditional probabilities and better capture the dry and wet events for use in the hydrologic and water resources modeling.

Global environmental effects of impact-generated aerosols: Results from a general circulation model

NASA Technical Reports Server (NTRS)

Covey, Curt; Ghan, Steven J.; Walton, John J.; Weissman, Paul R.

1989-01-01

Interception of sunlight by the high altitude worldwide dust cloud generated by impact of a large asteroid or comet would lead to substantial land surface cooling, according to the three-dimensional atmospheric general circulation model (GCM). This result is qualitatively similar to conclusions drawn from an earlier study that employed a one-dimensional atmospheric model, but in the GCM simulation the heat capacity of the oceans, not included in the one-dimensional model, substantially mitigates land surface cooling. On the other hand, the low heat capacity of the GCM's land surface allows temperatures to drop more rapidly in the initial stages of cooling than in the one-dimensional model study. GCM-simulated climatic changes in the scenario of asteroid/comet winter are more severe than in nuclear winter because the assumed aerosol amount is large enough to intercept all sunlight falling on earth. Impacts of smaller objects could also lead to dramatic, though of course less severe, climatic changes, according to the GCM. An asteroid or comet impact would not lead to anything approaching complete global freezing, but quite reasonable to assume that impacts would dramatically alter the climate in at least a patchy sense.

Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin.

PubMed

Piras, Monica; Mascaro, Giuseppe; Deidda, Roberto; Vivoni, Enrique R

2016-02-01

Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km(2)), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971-2000) and a future (2041-2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison.

PubMed

Peng, Jing; Dan, Li; Huang, Mei

2014-01-01

Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04 PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.

Sensitivity of Global and Regional Terrestrial Carbon Storage to the Direct CO2 Effect and Climate Change Based on the CMIP5 Model Intercomparison

PubMed Central

Peng, Jing; Dan, Li; Huang, Mei

2014-01-01

Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics. PMID:24748331

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.

Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high-latitude oceans

NASA Astrophysics Data System (ADS)

Brown, Patrick T.; Li, Wenhong; Jiang, Jonathan H.; Su, Hui

2016-12-01

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal time scales; thus, understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere-ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean is particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high-latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere. Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air-sea interaction at high latitudes.

An overview of mineral dust modeling over East Asia

NASA Astrophysics Data System (ADS)

Chen, Siyu; Huang, Jianping; Qian, Yun; Zhao, Chun; Kang, Litai; Yang, Ben; Wang, Yong; Liu, Yuzhi; Yuan, Tiangang; Wang, Tianhe; Ma, Xiaojun; Zhang, Guolong

2017-08-01

East Asian dust (EAD) exerts considerable impacts on the energy balance and climate/climate change of the earth system through its influence on solar and terrestrial radiation, cloud properties, and precipitation efficiency. Providing an accurate description of the life cycle and climate effects of EAD is therefore critical to better understanding of climate change and socioeconomic development in East Asia and even worldwide. Dust modeling has undergone substantial development since the late 1990s, associated with improved understanding of the role of EAD in the earth system. Here, we review the achievements and progress made in recent decades in terms of dust modeling research, including dust emissions, long-range transport, radiative forcing (RF), and climate effects of dust particles over East Asia. Numerous efforts in dust/EAD modeling have been directed towards furnishing more sophisticated physical and chemical processes into the models on higher spatial resolutions. Meanwhile, more systematic observations and more advanced retrieval methods for instruments that address EAD related science issues have made it possible to evaluate model results and quantify the role of EAD in the earth system, and to further reduce the uncertainties in EAD simulations. Though much progress has been made, large discrepancies and knowledge gaps still exist among EAD simulations. The deficiencies and limitations that pertain to the performance of the EAD simulations referred to in the present study are also discussed.

The role of sea-ice albedo in the climate of slowly rotating aquaplanets

NASA Astrophysics Data System (ADS)

Salameh, Josiane; Popp, Max; Marotzke, Jochem

2018-04-01

We investigate the influence of the rotation period (P_{rot}) on the mean climate of an aquaplanet, with a focus on the role of sea-ice albedo. We perform aquaplanet simulations with the atmospheric general circulation model ECHAM6 for various rotation periods from one Earth-day to 365 Earth-days in which case the planet is synchronously rotating. The global-mean surface temperature decreases with increasing P_{rot} and sea ice expands equatorwards. The cooling of the mean climate with increasing P_{rot} is caused partly by the high surface albedo of sea ice on the dayside and partly by the high albedo of the deep convective clouds over the substellar region. The cooling caused by these deep convective clouds is weak for non-synchronous rotations compared to synchronous rotation. Sensitivity simulations with the sea-ice model switched off show that the global-mean surface temperature is up to 27 K higher than in our main simulations with sea ice and thus highlight the large influence of sea ice on the climate. We present the first estimates of the influence of the rotation period on the transition of an Earth-like climate to global glaciation. Our results suggest that global glaciation of planets with synchronous rotation occurs at substantially lower incoming solar irradiation than for planets with slow but non-synchronous rotation.

The effects of atmospheric cloud radiative forcing on climate

NASA Technical Reports Server (NTRS)

Randall, David A.

1989-01-01

In order to isolate the effects of atmospheric cloud radiative forcing (ACRF) on climate, the general circulation of an ocean-covered earth called 'Seaworld' was simulated using the Colorado State University GCM. Most current climate models, however, do not include an interactive ocean. The key simplifications in 'Seaworld' are the fixed boundary temperature with no land points, the lack of mountains and the zonal uniformity of the boundary conditions. Two 90-day 'perpetual July' simulations were performed and analyzed the last sixty days of each. The first run included all the model's physical parameterizations, while the second omitted the effects of clouds in both the solar and terrestrial radiation parameterizations. Fixed and identical boundary temperatures were set for the two runs, and resulted in differences revealing the direct and indirect effects of the ACRF on the large-scale circulation and the parameterized hydrologic processes.

Climate change alters diffusion of forest pest: A model study

NASA Astrophysics Data System (ADS)

Jo, Woo Seong; Kim, Hwang-Yong; Kim, Beom Jun

2017-01-01

Population dynamics with spatial information is applied to understand the spread of pests. We introduce a model describing how pests spread in discrete space. The number of pest descendants at each site is controlled by local information such as temperature, precipitation, and the density of pine trees. Our simulation leads to a pest spreading pattern comparable to the real data for pine needle gall midge in the past. We also simulate the model in two different climate conditions based on two different representative concentration pathways scenarios for the future. We observe that after an initial stage of a slow spread of pests, a sudden change in the spreading speed occurs, which is soon followed by a large-scale outbreak. We found that a future climate change causes the outbreak point to occur earlier and that the detailed spatio-temporal pattern of the spread depends on the source position from which the initial pest infection starts.

Fewer clouds in the Mediterranean: consistency of observations and climate simulations

PubMed Central

Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.

2017-01-01

Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960

Weather and extremes in the last Millennium - a challenge for climate modelling

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Blumer, Sandro R.; Gomez-Navarro, Juan J.; Lehner, Flavio

2015-04-01

Changes in the climate mean state are expected to influence society, but the socio-economic sensitivity to extreme events might be even more severe. Whether or not the current frequency and severity of extreme events is a unique characteristic of anthropogenic-driven climate change can be assessed by putting the observed changes in a long-term perspective. In doing so, early instrumental series and proxy archives are a rich source to investigate also extreme events, in particular during the last millennium, yet they suffer from spatial and temporal scarcity. Therefore, simulations with coupled general circulation models (GCMs) could fill such gaps and help in deepening our process understanding. In this study, an overview of past and current efforts as well as challenges in modelling paleo weather and extreme events is presented. Using simulations of the last millennium we investigate extreme midlatitude cyclone characteristics, precipitation, and their connection to large-scale atmospheric patterns in the North Atlantic European region. In cold climate states such as the Maunder Minimum, the North Atlantic Oscillation (NAO) is found to be predominantly in its negative phase. In this sense, simulations of different models agree with proxy findings for this period. However, some proxy data available for this period suggests an increase in storminess during this period, which could be interpreted as a positive phase of the NAO - a superficial contradiction. The simulated cyclones are partly reduced over Europe, which is consistent with the aforementioned negative phase of the NAO. However, as the meridional temperature gradient is increased during this period - which constitutes a source of low-level baroclincity - they also intensify. This example illustrates how model simulations could be used to improve our proxy interpretation and to gain additional process understanding. Nevertheless, there are also limitations associated with climate modeling efforts to simulate the last millennium. In particular, these models still struggle to properly simulate atmospheric blocking events, an important dynamical feature for dry conditions during summer times. Finally, new and promising ways in improving past climate modelling are briefly introduced. In particular, the use of dynamical downscaling is a powerful tool to bridge the gap between the coarsely resolved GCMs and characteristics of the regional climate, which is potentially recorded in proxy archives. In particular, the representation of extreme events could be improved by dynamical downscaling as processes are better resolved than GCMs.

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

NASA Astrophysics Data System (ADS)

Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

2009-10-01

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

The Astronomical Forcing of Climate Change: Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Erb, M. P.; Broccoli, A. J.; Clement, A. C.

2010-12-01

Understanding the role that orbital forcing played in driving climate change over the Pleistocene has been a matter of ongoing research. While it is undeniable that variations in Earth’s orbit result in changes in the seasonal and latitudinal distribution of insolation, the specifics of how this forcing leads to the climate changes seen in the paleo record are not fully understood. To research this further, climate simulations have been conducted with the GFDL CM2.1, a coupled atmosphere-ocean GCM. Two simulations represent the extremes of obliquity during the past 600 kyr and four others show key times in the precessional cycle. All non-orbital variables are set to preindustrial levels to isolate the effects of astronomical forcing alone. It is expected that feedbacks should play a large role in dictating climate change, so to investigate this, the so-called “kernel method” is used to calculate the lapse rate, water vapor, albedo, and cloud feedbacks. Preliminary results of these experiments confirm that feedbacks are important in explaining the nature and, in places, even the sign of climate response to orbital forcing. In the case of low obliquity, for instance, a combination of climate feedbacks lead to global cooling in spite of zero global-average top of atmosphere insolation change. Feedbacks will be analyzed in the obliquity and precession experiments so that the role of feedbacks in contributing to climate change may be better understood.

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

NASA Technical Reports Server (NTRS)

Krueger, Steven K.

1998-01-01

The interactions between sea ice, open ocean, atmospheric radiation, and clouds over the Arctic Ocean exert a strong influence on global climate. Uncertainties in the formulation of interactive air-sea-ice processes in global climate models (GCMs) result in large differences between the Arctic, and global, climates simulated by different models. Arctic stratus clouds are not well-simulated by GCMs, yet exert a strong influence on the surface energy budget of the Arctic. Leads (channels of open water in sea ice) have significant impacts on the large-scale budgets during the Arctic winter, when they contribute about 50 percent of the surface fluxes over the Arctic Ocean, but cover only 1 to 2 percent of its area. Convective plumes generated by wide leads may penetrate the surface inversion and produce condensate that spreads up to 250 km downwind of the lead, and may significantly affect the longwave radiative fluxes at the surface and thereby the sea ice thickness. The effects of leads and boundary layer clouds must be accurately represented in climate models to allow possible feedbacks between them and the sea ice thickness. The FIRE III Arctic boundary layer clouds field program, in conjunction with the SHEBA ice camp and the ARM North Slope of Alaska and Adjacent Arctic Ocean site, will offer an unprecedented opportunity to greatly improve our ability to parameterize the important effects of leads and boundary layer clouds in GCMs.

Contribution of increasing CO2 and climate to carbon storage by ecosystems in the United States.

PubMed

Schimel, D; Melillo, J; Tian, H; McGuire, A D; Kicklighter, D; Kittel, T; Rosenbloom, N; Running, S; Thornton, P; Ojima, D; Parton, W; Kelly, R; Sykes, M; Neilson, R; Rizzo, B

2000-03-17

The effects of increasing carbon dioxide (CO2) and climate on net carbon storage in terrestrial ecosystems of the conterminous United States for the period 1895-1993 were modeled with new, detailed historical climate information. For the period 1980-1993, results from an ensemble of three models agree within 25%, simulating a land carbon sink from CO2 and climate effects of 0.08 gigaton of carbon per year. The best estimates of the total sink from inventory data are about three times larger, suggesting that processes such as regrowth on abandoned agricultural land or in forests harvested before 1980 have effects as large as or larger than the direct effects of CO2 and climate. The modeled sink varies by about 100% from year to year as a result of climate variability.

Contribution of increasing CO2 and climate to carbon storage by ecosystems in the United States

USGS Publications Warehouse

Schimel, D.; Melillo, J.; Tian, H.; McGuire, A.D.; Kicklighter, D.; Kittel, T.; Rosenbloom, N.; Running, S.; Thornton, P.; Ojima, D.; Parton, W.; Kelly, R.; Sykes, M.; Neilson, R.; Rizzo, B.

2000-01-01

The effects of increasing carbon dioxide (CO2) and climate on net carbon storage in terrestrial ecosystems of the conterminous United States for the period 1895-1993 were modeled with new, detailed historical climate information. For the period 1980-1993, results from an ensemble of three models agree within 25%, simulating a land carbon sink from CO2 and climate effects of 0.08 gigaton of carbon per year. The best estimates of the total sink from inventory data are about three times larger, suggesting that processes such as regrowth on abandoned agricultural land or in forests harvested before 1980 have effects as large as or larger than the direct effects of CO2 and climate. The modeled sink varies by about 100% from year to year as a result of climate variability.

Towards a Fine-Resolution Global Coupled Climate System for Prediction on Decadal/Centennial Scales

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

McClean, Julie L.

The over-arching goal of this project was to contribute to the realization of a fully coupled fine resolution Earth System Model simulation in which a weather-scale atmosphere is coupled to an ocean in which mesoscale eddies are largely resolved. Both a prototype fine-resolution fully coupled ESM simulation and a first-ever multi-decadal forced fine-resolution global coupled ocean/ice simulation were configured, tested, run, and analyzed as part of this grant. Science questions focused on the gains from the use of high horizontal resolution, particularly in the ocean and sea-ice, with respect to climatically important processes. Both these fine resolution coupled ocean/sea icemore » and fully-coupled simulations and precedent stand-alone eddy-resolving ocean and eddy-permitting coupled ocean/ice simulations were used to explore the high resolution regime. Overall, these studies showed that the presence of mesoscale eddies significantly impacted mixing processes and the global meridional overturning circulation in the ocean simulations. Fourteen refereed publications and a Ph.D. dissertation resulted from this grant.« less

Future Change of Snow Water Equivalent over Japan

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Kimura, F.; Fujita, M.; Ma, X.

2012-12-01

Western side of Honshu Island and Hokkaido Island in Japan are ones of the heaviest snowfall areas in the world. Although a heavy snowfall often brings disaster, snow is one of the major sources for agriculture, industrial, and house-use in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 C in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of the global warming, which is caused by an increase in greenhouse gases. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities. We performed a series of numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. The precipitation, snow depth, and surface air temperature of the hindcast simulations show good agreement with the AMeDAS station data. In much-snow cases, The decreasing rate of maximum total snow water equivalent over Japan due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is the air temperature rise due to global climate change. The difference in the precipitation amount between the present and the future simulations is small.

Snowmelt response to simulated warming across a large elevation gradient, southern Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Musselman, Keith N.; Molotch, Noah P.; Margulis, Steven A.

2017-12-01

In a warmer climate, the fraction of annual meltwater produced at high melt rates in mountainous areas is projected to decline due to a contraction of the snow-cover season, causing melt to occur earlier and under lower energy conditions. How snowmelt rates, including extreme events relevant to flood risk, may respond to a range of warming over a mountain front is poorly known. We present a model sensitivity study of snowmelt response to warming across a 3600 m elevation gradient in the southern Sierra Nevada, USA. A snow model was run for three distinct years and verified against extensive ground observations. To simulate the impact of climate warming on meltwater production, measured meteorological conditions were modified by +1 to +6 °C. The total annual snow water volume exhibited linear reductions (-10 % °C-1) consistent with previous studies. However, the sensitivity of snowmelt rates to successive degrees of warming varied nonlinearly with elevation. Middle elevations and years with more snowfall were prone to the largest reductions in snowmelt rates, with lesser changes simulated at higher elevations. Importantly, simulated warming causes extreme daily snowmelt (99th percentiles) to increase in spatial extent and intensity, and shift from spring to winter. The results offer insight into the sensitivity of mountain snow water resources and how the rate and timing of water availability may change in a warmer climate. The identification of future climate conditions that may increase extreme melt events is needed to address the climate resilience of regional flood control systems.

Global Trends and Variability in Integrated Water Vapor from Ground-Based GPS Data and Climate Models

NASA Astrophysics Data System (ADS)

Bock, O.; Parracho, A. C.; Bastin, S.; Hourdin, F.

2016-12-01

A high-quality, consistent, global, long-term dataset of integrated water vapor (IWV) was produced from Global Positioning System (GPS) measurements at more than 400 sites over the globe among which 120 sites have more than 15 years of data. The GPS delay data were converted to IWV using surface pressure and weighted mean temperature estimates from ERA-Interim reanalysis. A two-step screening method was developed to detect and remove outliers in the IWV data. It is based on: 1) GPS data processing information and delay formal errors, and 2) inter-comparison with ERA-Interim reanalysis data. The GPS IWV data are also homogenized to correct for offsets due to instrumental changes and other unknown factors. The differential homogenization method uses ERA-Interim IWV as a reference. The resulting GPS data are used to document the mean distribution, the global trends and the variability of IWV over the period 1995-2010, and to assess global climate model simulations extracted from the IPCC AR5 archive. Large coherent spatial patterns of moistening and drying are evidenced but significant discrepancies are also seen between GPS measurements, reanalysis and climate models in various regions. In terms of variability, the monthly mean anomalies are inter-compared. The temporal correlation between GPS and the climate model simulations is overall quite small but the spatial variation of the magnitude of the anomalies is globally well simulated. GPS IWV data prove to be useful to validate global climate model simulations and highlight deficiencies in their representation of the water cycle.

Astronomical Theory of Early Human Migration (Milutin Milankovic Medal Lecture)

NASA Astrophysics Data System (ADS)

Timmermann, Axel; Friedrich, Tobias

2017-04-01

Our climate system varies on a wide range of timescales, from seasons to several millions of years. A large part of this variability is internally generated as a result of instabilities of the coupled atmosphere-ocean-ice-carbon cycle system. Other modes of variability, such as glacial cycles, are caused by astronomical forcings with periods of 20, 40, 100 thousand years. These so-called Milankovitch Cycles are associated with earth's axis wobble, axis obliquity and shifts in the eccentricity of earth's orbit around the sun, respectively. When these cycles conspire, they can cause the climate system to plunge into an ice-age. This happened last time 110,000 years ago, when Northern Hemisphere summer radiation decreased substantially and ice-sheets started to form as a result. Around 100,000 years ago northern Hemisphere summer moved again closer to the sun and Homo sapiens started to leave Africa across vegetated corridors in Northeastern Africa and the Arabian Peninsula. This first migration wave must have been relatively weak, but it left unequivocal traces in the fossil and archaeological record. Why Homo sapiens embarked on its grand journey across our planet during glacial climate conditions has been subject of an intense debate in various scientific communities. Moreover, the archaeological records of an early exodus around 100 thousand years ago seem to be at odds with paleo-genetic evidences, that place the first dispersal out of Africa around 70-60 thousand years ago. To elucidate what role climate and environmental conditions played in the dispersal of Anatomically Modern Humans out of Africa, we have developed and applied one of the first integrated climate/human migration computer models. The model simulates ice-ages, abrupt climate change, the "peopling" of our planet and captures the arrival time of Homo sapiens in the Levant, Arabian Peninsula, Southern China and Australia in close agreement with paleo climate reconstructions, fossil and archaeological evidence. The human dispersal model simulates multiple prominent migration waves of Homo sapiens across the Arabian Peninsula and the Levant region around 106-94, 89-73, 59-47 and 45-29 thousand years ago. These waves were caused by earth's axis wobble and its corresponding changes in climate seasonality and resulting large-scale shifts in vegetation in tropical/subtropical regions. Such shifts opened up green corridors between Africa, the Sinai and the Arabian Peninsula, enabling Homo sapiens to leave Northeastern Africa and migrate into Asia, Europe, Australia and eventually into the Americas. The model also simulates a complex pattern of human dispersal out of Africa and back flow into Africa, that challenges the more unidirectional away-from-Africa perspective that is still very prevalent in anthropology and some genetic studies. Paleo-genetic reconstructions indicate that the first exodus out of Africa must have occurred around 70-60 thousand years ago. In contrast, our computer simulations and paleo-climate data show that northeastern Africa experienced one of its most severe long-term droughts during this time. The resulting large desert areas would have been an impenetrable natural border for early human migration. More research needs to be done to help reconcile and synthesize genetic, archaeological, climatological and anthropological data.

Response of the North Pacific Oscillation to global warming in the models of the Intergovernmental Panel on Climate Change Fourth Assessment Report

NASA Astrophysics Data System (ADS)

Chen, Zheng; Gan, Bolan; Wu, Lixin

2017-09-01

Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillation (NPO), which is the second most important factor determining the wintertime sea level pressure field in simulations of the pre-industrial control climate, and evaluate the NPO response to the future most reasonable global warming scenario (the A1B scenario). We reveal that while most models simulate the geographic distribution and amplitude of the NPO pattern satisfactorily, only 13 models capture both features well. However, the temporal variability of the simulated NPO could not be significantly correlated with the observations. Further analysis indicates the weakened NPO intensity for a scenario of strong global warming is attributable to the reduced lower-tropospheric baroclinicity at mid-latitudes, which is anticipated to disrupt large-scale and low-frequency atmospheric variability, resulting in the diminished transfer of energy to the NPO, together with its northward shift.

Variability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Climate Simulations

NASA Astrophysics Data System (ADS)

Mei, W.; Kamae, Y.; Xie, S. P.

2017-12-01

Forced and internal variability of North Atlantic hurricane frequency during 1951-2010 is studied using a large ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The simulations well capture the interannual-to-decadal variability of hurricane frequency in best track data, and further suggest a possible underestimate of hurricane counts in the current best track data prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the Main Development Region (MDR) accounts for more than 80% of the forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a simple but useful predictor; a one-degree increase in this SST difference produces 7.1±1.4 more hurricanes. The hurricane frequency also exhibits internal variability that is comparable in magnitude to the interannual variability. The 100-member ensemble allows us to address the following important questions: (1) Are the observations equivalent to one realization of such a large ensemble? (2) How many ensemble members are needed to reproduce the variability in observations and in the forced component of the simulations? The sources of the internal variability in hurricane frequency will be identified and discussed. The results provide an explanation for the relatively week correlation ( 0.6) between MDR GPI and hurricane frequency on interannual timescales in observations.

The CH2O column as a possible constraint on methane oxidation

NASA Astrophysics Data System (ADS)

Valin, L. C.; Fiore, A. M.; Lin, M.

2013-12-01

We explore the potential for space-based measurements of the CH2O column to quantify variations of methane oxidation in the remote atmosphere due to changes in climate (e.g., T, H2O, stratospheric O3) and atmospheric composition (e.g., NOxO, O3, CO, CH4). We investigate the variability of methane oxidation and the formaldehyde column using available global simulations (MOZART-2 chemistry-transport model, GFDL AM3 climate-chemistry model). Over a large region (135° - 175° W; 0° - 16° S), the rate of methane oxidation simulated in the models varies intraseasonally (×10%), seasonally (×20%) and interannually (×5%), and is well correlated with the simulated variability of the CH2O column (R2 = 0.75; ~1x1015 molecules cm-2). The precision of a single space-based measurement is approximately 1×1016 molecules cm-2, an order of magnitude larger than the simulated variability of the CH2O column. However, in a large region such as the tropical Pacific, UV/Vis spectrometers are capable of making thousands of measurements daily, enough sampling to theoretically increase the precision by √N, such that variations on the order of 1×1015 molecules cm-2 should be observable on intraseasonal and interannual timescales.

Simulation of the Central Indian Ocean Mode in CESM: Implications for the Indian Summer Monsoon System

NASA Astrophysics Data System (ADS)

Zhou, Lei; Murtugudde, Raghu; Neale, Richard B.; Jochum, Markus

2018-01-01

The simulation of the Indian summer monsoon and its pronounced intraseasonal component in a modern climate model remains a significant challenge. Recently, using observations and reanalysis products, the central Indian Ocean (CIO) mode was found to be a natural mode in the ocean-atmosphere coupled system and also shown to have a close mechanistic connection with the monsoon intraseasonal oscillation (MISO). In this study, the simulation of the actual CIO mode in historical Community Earth System Model (CESM) outputs is assessed by comparing with observations and reanalysis products. The simulation of the Madden-Julian Oscillation, a major component of tropical intraseasonal variabilities (ISVs), is satisfactory. However, the CIO mode is not well captured in any of the CESM simulations considered here. The force and response relationship between the atmosphere and the ocean associated with the CIO mode in CESM is opposite to that in nature. The simulated meridional gradient of large-scale zonal winds is too weak, which precludes the necessary energy conversion from the mean state to the ISVs and cuts off the energy source to MISO in CESM. The inability of CESM to reproduce the CIO mode seen clearly in nature highlights the CIO mode as a new dynamical framework for diagnosing the deficiencies in Indian summer monsoon simulation in climate models. The CIO mode is a coupled metric for evaluating climate models and may be a better indicator of a model's skill to accurately capture the tropical multiscale interactions over subseasonal to interannual timescales.

Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed

USGS Publications Warehouse

Valentin, Melissa M.; Viger, Roland J.; Van Beusekom, Ashley E.; Hay, Lauren E.; Hogue, Terri S.; Foks, Nathan Leon

2018-01-01

The U.S. Geological Survey monthly water balance model (MWBM) was enhanced with the capability to simulate glaciers in order to make it more suitable for simulating cold region hydrology. The new model, MWBMglacier, is demonstrated in the heavily glacierized and ecologically important Copper River watershed in Southcentral Alaska. Simulated water budget components compared well to satellite‐based observations and ground measurements of streamflow, evapotranspiration, snow extent, and total water storage, with differences ranging from 0.2% to 7% of the precipitation flux. Nash Sutcliffe efficiency for simulated and observed streamflow was greater than 0.8 for six of eight stream gages. Snow extent matched satellite‐based observations with Nash Sutcliffe efficiency values of greater than 0.89 in the four Copper River ecoregions represented. During the simulation period 1949 to 2009, glacier ice melt contributed 25% of total runoff, ranging from 12% to 45% in different tributaries, and glacierized area was reduced by 6%. Statistically significant (p < 0.05) decreasing and increasing trends in annual glacier mass balance occurred during the multidecade cool and warm phases of the Pacific Decadal Oscillation, respectively, reinforcing the link between climate perturbations and glacier mass balance change. The simulations of glaciers and total runoff for a large, remote region of Alaska provide useful data to evaluate hydrologic, cryospheric, ecologic, and climatic trends. MWBM glacier is a valuable tool to understand when, and to what extent, streamflow may increase or decrease as glaciers respond to a changing climate.

Simulation of the modern arctic climate by the NCAR CCM1

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

Bromwich, D.H.; Tzeng, R.Y.; Parish, T.R.

The NCAR CCM1's simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the ECMWF global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenlandmore » topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial [open quotes]circum-Greenland[close quotes] trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the modal simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. 26 refs., 14 figs., 42 tabs.« less

Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models

DOE PAGES

Andrews, Timothy; Gregory, Jonathan M.; Webb, Mark J.; ...

2012-05-15

We quantify forcing and feedbacks across available CMIP5 coupled atmosphere-ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing-feedback regression analysis of Gregory et al. (2004) to an ensemble of AOGCMs. The range of equilibrium climate sensitivity is 2.1–4.7 K. Differences in cloud feedbacks continue to be important contributors to this range. Some models show small deviations from a linear dependence of top-of-atmosphere radiative fluxes on global surface temperature change. We show that this phenomenon largely arises from shortwave cloud radiative effects overmore » the ocean and is consistent with independent estimates of forcing using fixed sea-surface temperature methods. Moreover, we suggest that future research should focus more on understanding transient climate change, including any time-scale dependence of the forcing and/or feedback, rather than on the equilibrium response to large instantaneous forcing.« less

Hadley circulation strength and width in a wide range of simulated climates

NASA Astrophysics Data System (ADS)

D'Agostino, R.; Adam, O.; Lionello, P.; Schneider, T.

2016-12-01

Understanding how the Hadley circulation (HC) responds to global warming is crucial because it determines climatic features such as the seasonal migration of the ITCZ, the extent of subtropical arid regions and the strength of the monsoons. Here we analyse changes in the HC strength and width in the set of PMIP3 and CMIP5 simulations, spanning a wide range of climate conditions from Last Glacial Maximum to future RCP projections. The large climate change signal emerging from comparing paleoclimate simulations to future scenarios offers the possibility to analyse the corresponding HC change and to investigate its response to large variations of the factors controlling it. The results confirm that the HC generally expands and weakens as the global mean temperature increases, consistent with results from other studies. Furthermore, we find an asymmetric HC response between the northern and southern hemisphere in the rate at which the HC edges shift poleward with global warming. The mid-latitude static stability and meridional temperature gradients affect the HC edges to different degrees in the two hemispheres. In the southern hemisphere the increase in the mid-latitude static stability is associated with a poleward shift of the southern HC edge, while in the northern hemisphere, the reduction in the meridional temperature gradient plays the dominant role in the poleward shift of the northern HC edge. The two hemispheres also exhibit very different changes of HC strength. The HC weakening with global warming occurs primarily in the northern hemisphere, while there is no change, or even a slighter weakening in the southern hemisphere. The HC changes also have pronounced seasonal signatures. The maximum poleward shift of the northern HC edge occurs one month later (from August to September) in future global warming scenarios than when comparing pre-industrial simulations with the Last Glacial Maximum.

Large projected increases in rain-on-snow flood potential over western North America

NASA Astrophysics Data System (ADS)

Musselman, K. N.; Ikeda, K.; Barlage, M. J.; Lehner, F.; Liu, C.; Newman, A. J.; Prein, A. F.; Mizukami, N.; Gutmann, E. D.; Clark, M. P.; Rasmussen, R.

2017-12-01

In the western US and Canada, some of the largest annual flood events occur when warm storm systems drop substantial rainfall on extensive snow-cover. For example, last winter's Oroville dam crisis in California was exacerbated by rapid snowmelt during a rain-on-snow (ROS) event. We present an analysis of ROS events with flood-generating potential over western North America simulated at high-resolution by the Weather Research and Forecasting (WRF) model run for both a 13-year control time period and re-run with a `business-as-usual' future (2071-2100) climate scenario. Daily ROS with flood-generating potential is defined as rainfall of at least 10 mm per day falling on snowpack of at least 10 mm water equivalent, where the sum of rainfall and snowmelt contains at least 20% snowmelt. In a warmer climate, ROS is less frequent in regions where it is historically common, and more frequent elsewhere. This is evidenced by large simulated reductions in snow-cover and ROS frequency at lower elevations, particularly in warmer, coastal regions, and greater ROS frequency at middle elevations and in inland regions. The same trend is reflected in the annual-average ROS runoff volume (rainfall + snowmelt) aggregated to major watersheds; large reductions of 25-75% are projected for much of the U.S. Pacific Northwest, while large increases are simulated for the Colorado River basin, western Canada, and the higher elevations of the Sierra Nevada. In the warmer climate, snowmelt contributes substantially less to ROS runoff per unit rainfall, particularly in inland regions. The reduction in snowmelt contribution is due to a shift in ROS timing from warm spring events to cooler winter conditions and/or from warm, lower elevations to cool, higher elevations. However, the slower snowmelt is offset by an increase in rainfall intensity, maintaining the flood potential of ROS at or above historical levels. In fact, we report large projected increases in the intensity of extreme ROS events. The projected increases in ROS flood potential are highest in historically flood-prone mountain basins and the Canadian Prairies. Increases in extreme ROS event intensity, together with a greater proportion of precipitation falling as rain, have critical implications on the climate resilience of regional flood control systems.

The foundation for climate services in Belgium: CORDEX.be

NASA Astrophysics Data System (ADS)

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.

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

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

Hu, Aixue; Meehl, Gerald; Stammer, Detlef

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

DOE PAGES

Hu, Aixue; Meehl, Gerald; Stammer, Detlef; ...

2017-06-05

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less

Enhanced recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-04-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

NASA Astrophysics Data System (ADS)

Akperov, Mirseid; Rinke, Annette; Mokhov, Igor I.; Matthes, Heidrun; Semenov, Vladimir A.; Adakudlu, Muralidhar; Cassano, John; Christensen, Jens H.; Dembitskaya, Mariya A.; Dethloff, Klaus; Fettweis, Xavier; Glisan, Justin; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Koldunov, Nikolay V.; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Scinocca, John F.; Sein, Dmitry; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin

2018-03-01

The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Simulation of how a geo-engineering intervention to restore arctic sea ice might work in practice

NASA Astrophysics Data System (ADS)

Jackson, L. S.; Crook, J. A.; Forster, P.; Jarvis, A.; Leedal, D.; Ridgwell, A. J.; Vaughan, N.

2013-12-01

The declining trend in annual minimum Arctic sea ice coverage and years of more pronounced drops like 2007 and 2012 raise the prospect of an Arctic Ocean largely free of sea ice in late summer and the potential for a climate crisis or emergency. In a novel computer simulation, we treated one realisation of a climate model (HadGEM2) as the real world and tried to restore its Arctic sea ice by the rapid deployment of geo-engineering with emission of SO2 into the Arctic stratosphere. The objective was to restore the annual minimum Arctic sea ice coverage to levels seen in the late twentieth century using as little geo-engineering as possible. We took intervention decisions as one might do in the real world: by committee, using a limited set of uncertain 'observations' from our simulated world and using models and control theory to plan the best intervention strategy for the coming year - so learning as we went and being thrown off course by future volcanoes and technological breakdowns. Uncertainties in real world observations were simulated by applying noise to emerging results from the climate model. Volcanic forcing of twenty-first century climate was included with the timing and magnitude of the simulated eruptions unknown by the 'geo-engineers' until after the year of the eruption. Monitoring of Arctic sea ice with the option to intervene with SO2 emissions started from 2018 and continued to 2075. Simulated SO2 emissions were made in January-May each year at a latitude of 79o N and an altitude within the range of contemporary tanker aircraft. The magnitude of emissions was chosen annually using a model predictive control process calibrated using results from CMIP5 models (excluding HadGEM2), using the simplified climate model MAGICC and assimilation of emerging annual results from the HadGEM2 'real world'. We found that doubts in the minds of the 'geo-engineers' of the effectiveness and the side effects of their past intervention, and the veracity of the models used for planning intervention were a constant feature of the simulation. As a result, their assumptions and intervention approaches were considerably revised as the simulation progressed. Side effects of the geo-engineering were difficult to explicitly determine without a control experiment. Nevertheless, we found wide spread changes in precipitation that were believed to be due to the geo-engineering - a later control experiment confirmed this belief. On termination of the SO2 geo-engineering, northern hemisphere temperatures rose sharply and Arctic sea ice area dropped dramatically. These termination effects were so large that attribution to the geo-engineering cessation was unambiguous.

Shaping climate change in the North Atlantic sector: The role of the atmospheric response to local SST changes vs. large-scale changes

NASA Astrophysics Data System (ADS)

Hand, Ralf; Keenlyside, Noel; Omrani, Nour-Eddine; Greatbatch, Richard; Bader, Jürgen

2017-04-01

Climate change simulations robustly show a warming hole in the sub-polar North Atlantic that results from slowing of the AMOC countering the global warming signal. Here we investigate how the distinct SST spatial structures, which include a sharpening of the Gulf Stream SST gradients, influence climate change in the NA sector in winter. For this we analyse the RCP8.5 scenario simulation of the MPI Earth System Model. Additional sensitivity experiments with the atmospheric model component, ECHAM5, are performed to deconstruct the effect of the local spatial structure of the SST change from those arising from large-scale warming of the ocean, remote SST pattern changes and changed radiative forcings. The MPI model simulation shows a signifcant decrease in precipitation to the south of the GS extension region in the future, despite a strong increase in underlying SST. While directly to the north there is a significant increase in precipitation. These distinct features in the precipitation response over the North Atlantic result from the local SST. Over the Gulf Stream, the differential structure of the precipitation changes reflects the changes of the local SST gradients there. Over the subpolar gyre the increase in precipitation is partly suppressed. In this region the Subpolar Gyre the weakened AMOC causes a SST warming, that is much weaker than the warming other regions of the ocean show at the same latitude. The large-scale response, which includes the overall increase in precipitation over the NA is due to the overall warming, remote SSTs and/or directly connected to the radiative forcing.

Technical Note: On the use of nudging for aerosol–climate model intercomparison studies

DOE PAGES

Zhang, K.; Wan, H.; Liu, X.; ...

2014-08-26

Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity ofmore » simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol–climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate.« less

Technical Note: On the use of nudging for aerosol-climate model intercomparison studies

NASA Astrophysics Data System (ADS)

Zhang, K.; Wan, H.; Liu, X.; Ghan, S. J.; Kooperman, G. J.; Ma, P.-L.; Rasch, P. J.; Neubauer, D.; Lohmann, U.

2014-08-01

Nudging as an assimilation technique has seen increased use in recent years in the development and evaluation of climate models. Constraining the simulated wind and temperature fields using global weather reanalysis facilitates more straightforward comparison between simulation and observation, and reduces uncertainties associated with natural variabilities of the large-scale circulation. On the other hand, the forcing introduced by nudging can be strong enough to change the basic characteristics of the model climate. In the paper we show that for the Community Atmosphere Model version 5 (CAM5), due to the systematic temperature bias in the standard model and the sensitivity of simulated ice formation to anthropogenic aerosol concentration, nudging towards reanalysis results in substantial reductions in the ice cloud amount and the impact of anthropogenic aerosols on long-wave cloud forcing. In order to reduce discrepancies between the nudged and unconstrained simulations, and meanwhile take the advantages of nudging, two alternative experimentation methods are evaluated. The first one constrains only the horizontal winds. The second method nudges both winds and temperature, but replaces the long-term climatology of the reanalysis by that of the model. Results show that both methods lead to substantially improved agreement with the free-running model in terms of the top-of-atmosphere radiation budget and cloud ice amount. The wind-only nudging is more convenient to apply, and provides higher correlations of the wind fields, geopotential height and specific humidity between simulation and reanalysis. Results from both CAM5 and a second aerosol-climate model ECHAM6-HAM2 also indicate that compared to the wind-and-temperature nudging, constraining only winds leads to better agreement with the free-running model in terms of the estimated shortwave cloud forcing and the simulated convective activities. This suggests nudging the horizontal winds but not temperature is a good strategy for the investigation of aerosol indirect effects since it provides well-constrained meteorology without strongly perturbing the model's mean climate.

Linking climate projections to performance: A yield-based decision scaling assessment of a large urban water resources system

NASA Astrophysics Data System (ADS)

Turner, Sean W. D.; Marlow, David; Ekström, Marie; Rhodes, Bruce G.; Kularathna, Udaya; Jeffrey, Paul J.

2014-04-01

Despite a decade of research into climate change impacts on water resources, the scientific community has delivered relatively few practical methodological developments for integrating uncertainty into water resources system design. This paper presents an application of the "decision scaling" methodology for assessing climate change impacts on water resources system performance and asks how such an approach might inform planning decisions. The decision scaling method reverses the conventional ethos of climate impact assessment by first establishing the climate conditions that would compel planners to intervene. Climate model projections are introduced at the end of the process to characterize climate risk in such a way that avoids the process of propagating those projections through hydrological models. Here we simulated 1000 multisite synthetic monthly streamflow traces in a model of the Melbourne bulk supply system to test the sensitivity of system performance to variations in streamflow statistics. An empirical relation was derived to convert decision-critical flow statistics to climatic units, against which 138 alternative climate projections were plotted and compared. We defined the decision threshold in terms of a system yield metric constrained by multiple performance criteria. Our approach allows for fast and simple incorporation of demand forecast uncertainty and demonstrates the reach of the decision scaling method through successful execution in a large and complex water resources system. Scope for wider application in urban water resources planning is discussed.

C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6

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

Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre

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 aremore » potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO 2 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 CO 2 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 study 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.« less

C4MIP – The Coupled Climate–Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6

DOE PAGES

Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre; ...

2016-08-25

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 aremore » potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO 2 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 CO 2 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 study 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.« less

The Impacts of Miyun Reservoirs on Local Climate: A Modeling Study Using WRF-Lake Model

NASA Astrophysics Data System (ADS)

Wang, F.; Xing, Y.; Sun, T.; Ni, G.

2016-12-01

Large reservoirs, where a great volume of water is stored for various purposes (e.g. hydropower generation, irrigation, transportation, recreation, etc.), play a key role in regional hydrological cycles as well as in modulating the local climate. In particular, to understand the impacts of reservoirs on local climate, numeric simulations are widely conducted using different weather prediction (NWP) models. However, some of these NWP models treat reservoirs as water surfaces with prescribed surface temperatures and thus the hydrothermal dynamics within water bodies are missing. In this study, we use the Weather Research Forecasting (WRF) model coupled with a lake module, which is equipped with the ability to simulate full thermal dynamics of water, to examine the impacts of Miyun Reservoir, the largest reservoir in Beijing, on the local climate. Simulations are conducted from July 1 to August 1, 2010 in a one-way nesting mode of three spatial resolutions (i.e., 9 km, 3 km and 1 km). Comparison between the simulation results and observations shows a general agreement and demonstrates the ability of WRF-Lake in simulating the summertime climate in the study area. The simulation results indicate the Miyun Reservoir significantly reduces daytime air temperature at 2 m above the water surface and its surroundings by a maximum of 4 K as compared with the case without a reservoir, and such impacts diminish at a distance of 90 km from the reservoir center (a decrease of 0.2 K). At night, a maximum increase of 1.4 K is simulated for the air temperature above the reservoir, but the influencing area is very limited. The reservoir also increases the local air specific humidity by 0.0025 kg kg-1. In addition to near surface meteorology, surface energy balance is remarkably changed as compared to the case without a reservoir: a daytime decrease of 100 W m-2 and a nighttime increase of 15 W m-2are simulated for the sensible heat flux. It is noteworthy that the latent heat flux decreases in the daytime and slightly increases at night. It should also be noted that the influencing area is strongly dependent on the wind direction. This study provides a better understanding of the water-atmosphere interactions by reservoirs and their impacts on local climate.

Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios

NASA Astrophysics Data System (ADS)

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.

Contributions of the ARM Program to Radiative Transfer Modeling for Climate and Weather Applications

NASA Technical Reports Server (NTRS)

Mlawer, Eli J.; Iacono, Michael J.; Pincus, Robert; Barker, Howard W.; Oreopoulos, Lazaros; Mitchell, David L.

2016-01-01

Accurate climate and weather simulations must account for all relevant physical processes and their complex interactions. Each of these atmospheric, ocean, and land processes must be considered on an appropriate spatial and temporal scale, which leads these simulations to require a substantial computational burden. One especially critical physical process is the flow of solar and thermal radiant energy through the atmosphere, which controls planetary heating and cooling and drives the large-scale dynamics that moves energy from the tropics toward the poles. Radiation calculations are therefore essential for climate and weather simulations, but are themselves quite complex even without considering the effects of variable and inhomogeneous clouds. Clear-sky radiative transfer calculations have to account for thousands of absorption lines due to water vapor, carbon dioxide, and other gases, which are irregularly distributed across the spectrum and have shapes dependent on pressure and temperature. The line-by-line (LBL) codes that treat these details have a far greater computational cost than can be afforded by global models. Therefore, the crucial requirement for accurate radiation calculations in climate and weather prediction models must be satisfied by fast solar and thermal radiation parameterizations with a high level of accuracy that has been demonstrated through extensive comparisons with LBL codes. See attachment for continuation.

Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

NASA Astrophysics Data System (ADS)

Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

2017-10-01

The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.