Evaluation of simulated corn yields and associated uncertainty in different climate zones of China using Daycent Model

NASA Astrophysics Data System (ADS)

Fu, A.; Xue, Y.

2017-12-01

Corn is one of most important agricultural production in China. Research on the simulation of corn yields and the impacts of climate change and agricultural management practices on corn yields is important in maintaining the stable corn production. After climatic data including daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 1948 to 2010, soil properties, observed corn yields, and farmland management information were collected, corn yields grown in humidity and hot environment (Sichuang province) and cold and dry environment (Hebei province) in China in the past 63 years were simulated by Daycent, and the results was evaluated based on published yield record. The relationship between regional climate change, global warming and corn yield were analyzed, the uncertainties of simulation derived from agricultural management practices by changing fertilization levels, land fertilizer maintenance and tillage methods were reported. The results showed that: (1) Daycent model is capable to simulate corn yields under the different climatic background in China. (2) When studying the relationship between regional climate change and corn yields, it has been found that observed and simulated corn yields increased along with total regional climate change. (3) When studying the relationship between the global warming and corn yields, It was discovered that newly-simulated corn yields after removing the global warming trend of original temperature data were lower than before.

An Investigation of Bomb Cyclogenesis in NCEP's CFS Model

NASA Astrophysics Data System (ADS)

Alvarez, F. M.; Eichler, T.; Gottschalck, J.

2008-12-01

With the concerns, impacts and consequences of climate change increasing, the need for climate models to simulate daily weather is very important. Given the improvements in resolution and physical parameterizations, climate models are becoming capable of resolving extreme weather events. A particular type of extreme event which has large impacts on transportation, industry and the general public is a rapidly intensifying cyclone referred to as a "bomb." In this study, bombs are investigated using the National Center for Environmental Prediction's (NCEP) Climate Forecast System (CFS) model. We generate storm tracks based on 6-hourly sea-level pressure (SLP) from long-term climate runs of the CFS model. Investigation of this dataset has revealed that the CFS model is capable of producing bombs. We show a case study of a bomb in the CFS model and demonstrate that it has characteristics similar to the observed. Since the CFS model is capable of producing bombs, future work will focus on trends in their frequency and intensity so that an assessment of the potential role of the bomb in climate change can be assessed.

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

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

2001-01-01

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Predicting future threats to the long-term survival of Gila Trout using a high-resolution simulation of climate change

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

Kennedy, Thomas L.; Gutzler, David S.; Leung, Lai R.

2008-11-20

Regional climates are a major factor in determining the distribution of many species. Anthropogenic inputs of greenhouse gases into the atmosphere have been predicted to cause rapid climatic changes in the next 50-100 years. Species such as the Gila Trout (Onchorhynchus gilae) that have small ranges, limited dispersal capabilities, and narrow physiological tolerances will become increasingly susceptible to extinction as their climate envelope changes. This study uses a regional climate change simulation (Leung et al. 2004) to determine changes in the climate envelope for Gila Trout, which is sensitive to maximum temperature, associated with a plausible scenario for greenhouse gasmore » increases. The model predicts approximately a 2° C increase in temperature and a doubling by the mid 21st Century in the annual number of days during which temperature exceeds 37°C, and a 25% increase in the number of days above 32°C, across the current geographical range of Gila Trout. At the same time summer rainfall decreases by more than 20%. These climate changes would reduce their available habitat by decreasing the size of their climate envelope. Warmer temperatures coupled with a decrease in summer precipitation would also tend to increase the intensity and frequency of forest fires that are a major threat to their survival. The climate envelope approach utilized here could be used to assess climate change threats to other rare species with limited ranges and dispersal capabilities.« less

Approaches to incorporating climate change effects in state and transition simulation models of vegetation

Treesearch

Becky K. Kerns; Miles A. Hemstrom; David Conklin; Gabriel I. Yospin; Bart Johnson; Dominique Bachelet; Scott Bridgham

2012-01-01

Understanding landscape vegetation dynamics often involves the use of scientifically-based modeling tools that are capable of testing alternative management scenarios given complex ecological, management, and social conditions. State-and-transition simulation model (STSM) frameworks and software such as PATH and VDDT are commonly used tools that simulate how landscapes...

The Community Climate System Model.

NASA Astrophysics Data System (ADS)

Blackmon, Maurice; Boville, Byron; Bryan, Frank; Dickinson, Robert; Gent, Peter; Kiehl, Jeffrey; Moritz, Richard; Randall, David; Shukla, Jagadish; Solomon, Susan; Bonan, Gordon; Doney, Scott; Fung, Inez; Hack, James; Hunke, Elizabeth; Hurrell, James; Kutzbach, John; Meehl, Jerry; Otto-Bliesner, Bette; Saravanan, R.; Schneider, Edwin K.; Sloan, Lisa; Spall, Michael; Taylor, Karl; Tribbia, Joseph; Washington, Warren

2001-11-01

The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users. The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a flux coupler that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1% per year. In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several pro-jections of the climate of the twenty-first century. The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface temperature in the central and eastern tropical Pacific is also more realistic in simulations with the updated model. Scientific challenges to be addressed with future versions of the CCSM include realistic simulation of the whole atmosphere, including the middle and upper atmosphere, as well as the troposphere; simulation of changes in the chemical composition of the atmosphere through the incorporation of an integrated chemistry model; inclusion of global, prognostic biogeochemical components for land, ocean, and atmosphere; simulations of past climates, including times of extensive continental glaciation as well as times with little or no ice; studies of natural climate variability on seasonal-to-centennial timescales; and investigations of anthropogenic climate change. In order to make such studies possible, work is under way to improve all components of the model. Plans call for a new version of the CCSM to be released in 2002. Planned studies with the CCSM will require much more computer power than is currently available.

Towards a unified Global Weather-Climate Prediction System

NASA Astrophysics Data System (ADS)

Lin, S. J.

2016-12-01

The 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 and kilometer scale regional climate simulations within a unified global modeling system. The foundation of this flexible modeling system is the nonhydrostatic Finite-Volume Dynamical Core on the Cubed-Sphere (FV3). A unique aspect of FV3 is that it is "vertically Lagrangian" (Lin 2004), essentially reducing the equation sets to two dimensions, and is the single most important reason why FV3 outperforms other non-hydrostatic cores. Owning to its accuracy, adaptability, and computational efficiency, the FV3 has been selected as the "engine" for NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched grid, a two-way regional-global nested grid, and an optimal combination of the stretched and two-way nests capability, making kilometer-scale regional simulations within a global modeling system feasible. Our main scientific goal 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, with the FV3, it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornado-like vortices using a global model that was originally designed for climate simulations. The development and tuning strategy between traditional weather and climate models are fundamentally different due to different metrics. We were able to adapt and use traditional "climate" metrics or standards, such as angular momentum conservation, energy conservation, and flux balance at top of the atmosphere, and gain insight into problems of traditional weather prediction model for medium-range weather prediction, and vice versa. Therefore, the unification in weather and climate models can happen not just at the algorithm or parameterization level, but also in the metric and tuning strategy used for both applications, and ultimately, with benefits to both weather and climate applications.

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

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

1998-01-01

The goal of this research is the continued development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. This work involves a combination of modeling and analysis efforts involving 4DDA datasets and simulations from the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) coordinate model and the GEOS GCM.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE PAGES

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin; ...

2017-01-10

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

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

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users

USGS Publications Warehouse

Hostetler, S.W.; Alder, J.R.; Allan, A.M.

2011-01-01

We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

CWRF performance at downscaling China climate characteristics

NASA Astrophysics Data System (ADS)

Liang, Xin-Zhong; Sun, Chao; Zheng, Xiaohui; Dai, Yongjiu; Xu, Min; Choi, Hyun I.; Ling, Tiejun; Qiao, Fengxue; Kong, Xianghui; Bi, Xunqiang; Song, Lianchun; Wang, Fang

2018-05-01

The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980-2015 simulation at 30 km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities.

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.

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

What Can Earth Paleoclimates Reveal About the Resiliency of Habitable States? An Example from the Neoproterozoic Snowball Earth

NASA Astrophysics Data System (ADS)

Sohl, L.

2014-04-01

The Neoproterozoic "Snowball Earth" glaciations ( 750-635 Ma) have been a special focus for outer habitable zone investigations, owing in large part to a captivating and controversial hypothesis suggesting that Earth may have only narrowly escaped a runaway icehouse state on multiple occasions (a.k.a. "the hard snowball"; Hoffman and Schrag 2001). A review of climate simulations exploring snowball inception (Godderis et al. 2011) reveals that a broad range of models (EBMs, EMICs and AGCMs) tend to yield hard snowball solutions, whereas models with greater 3-D dynamic response capabilities (AOGCMs) typically do not, unless some of their climate feedback responses (e.g., wind-driven ocean circulation, cloud forcings) are disabled (Poulsen and Jacobs 2004). This finding raises the likelihood that models incorporating dynamic climate feedbacks are essential to understanding how much flexibility there may be in the definition of a planet's habitable zone boundaries for a given point in its history. In the first of a series of new Snowball Earth simulations, we use the NASA/GISS ModelE2 Global Climate Model - a 3-D coupled atmosphere/ocean model with dynamic sea ice response - to explore the impacts of wind-driven ocean circulation, clouds and deep ocean circulation on the sea ice front when solar luminosity and atmospheric carbon dioxide are reduced to Neoproterozoic levels (solar = 94%, CO2 = 40 ppmv). The simulation includes a realistic Neoproterozoic land mass distribution, which is concentrated at mid- to tropical latitudes. After 300 years, the sea ice front is established near 30 degrees latitude, and after 600 years it remains stable. As with earlier coupled model simulations we conclude that runaway glacial states would have been difficult to achieve during the Neoproterozoic, and would be more likely to have occurred during earlier times in Earth history when solar luminosity was less. Inclusion of dynamic climate feedback capabilities in habitable zone modeling studies is likely to result in an expansion of our view of what a "Goldilocks" state can entail. Future simulations with a modified version of the NASA/GISS GCM, ROCKE-3D, will take advantage of newly-added model capabilities that evaluate the influence of rotation rate, solar spectral variability, CO2 surface condensation and CO2 clouds on the outer edge of Earth's habitable zone.

One-way coupling of an atmospheric and a hydrologic model in Colorado

USGS Publications Warehouse

Hay, L.E.; Clark, M.P.; Pagowski, M.; Leavesley, G.H.; Gutowski, W.J.

2006-01-01

This paper examines the accuracy of high-resolution nested mesoscale model simulations of surface climate. The nesting capabilities of the atmospheric fifth-generation Pennsylvania State University (PSU)-National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) were used to create high-resolution, 5-yr climate simulations (from 1 October 1994 through 30 September 1999), starting with a coarse nest of 20 km for the western United States. During this 5-yr period, two finer-resolution nests (5 and 1.7 km) were run over the Yampa River basin in northwestern Colorado. Raw and bias-corrected daily precipitation and maximum and minimum temperature time series from the three MM5 nests were used as input to the U.S. Geological Survey's distributed hydrologic model [the Precipitation Runoff Modeling System (PRMS)] and were compared with PRMS results using measured climate station data. The distributed capabilities of PRMS were provided by partitioning the Yampa River basin into hydrologic response units (HRUs). In addition to the classic polygon method of HRU definition, HRUs for PRMS were defined based on the three MM5 nests. This resulted in 16 datasets being tested using PRMS. The input datasets were derived using measured station data and raw and bias-corrected MM5 20-, 5-, and 1.7-km output distributed to 1) polygon HRUs and 2) 20-, 5-, and 1.7-km-gridded HRUs, respectively. Each dataset was calibrated independently, using a multiobjective, stepwise automated procedure. Final results showed a general increase in the accuracy of simulated runoff with an increase in HRU resolution. In all steps of the calibration procedure, the station-based simulations of runoff showed higher accuracy than the MM5-based simulations, although the accuracy of MM5 simulations was close to station data for the high-resolution nests. Further work is warranted in identifying the causes of the biases in MM5 local climate simulations and developing methods to remove them. ?? 2006 American Meteorological Society.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Astrophysics Data System (ADS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A. D.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.; Tsigaridis, K.

2017-07-01

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower to more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Technical Reports Server (NTRS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.;

ARM-Led Improvements Aerosols in Climate and Climate Models

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

Ghan, Steven J.; Penner, Joyce E.

2016-07-25

The DOE ARM program has played a foundational role in efforts to quantify aerosol effects on climate, beginning with the early back-of-the-envelope estimates of direct radiative forcing by anthropogenic sulfate and biomass burning aerosol (Penner et al., 1994). In this chapter we review the role that ARM has played in subsequent detailed estimates based on physically-based representations of aerosols in climate models. The focus is on quantifying the direct and indirect effects of anthropogenic aerosol on the planetary energy balance. Only recently have other DOE programs applied the aerosol modeling capability to simulate the climate response to the radiative forcing.

Ultrascale Visualization of Climate Data

NASA Technical Reports Server (NTRS)

Williams, Dean N.; Bremer, Timo; Doutriaux, Charles; Patchett, John; Williams, Sean; Shipman, Galen; Miller, Ross; Pugmire, David R.; Smith, Brian; Steed, Chad;

The Regional Climate Model Evaluation System: A Systematic Evaluation Of CORDEX Simulations Using Obs4MIPs

NASA Astrophysics Data System (ADS)

Goodman, A.; Lee, H.; Waliser, D. E.; Guttowski, W.

2017-12-01

Observation-based evaluations of global climate models (GCMs) have been a key element for identifying systematic model biases that can be targeted for model improvements and for establishing uncertainty associated with projections of global climate change. However, GCMs are limited in their ability to represent physical phenomena which occur on smaller, regional scales, including many types of extreme weather events. In order to help facilitate projections in changes of such phenomena, simulations from regional climate models (RCMs) for 14 different domains around the world are being provided by the Coordinated Regional Climate Downscaling Experiment (CORDEX; www.cordex.org). However, although CORDEX specifies standard simulation and archiving protocols, these simulations are conducted independently by individual research and modeling groups representing each of these domains often with different output requirements and data archiving and exchange capabilities. Thus, with respect to similar efforts using GCMs (e.g., the Coupled Model Intercomparison Project, CMIP), it is more difficult to achieve a standardized, systematic evaluation of the RCMs for each domain and across all the CORDEX domains. Using the Regional Climate Model Evaluation System (RCMES; rcmes.jpl.nasa.gov) developed at JPL, we are developing easy to use templates for performing systematic evaluations of CORDEX simulations. Results from the application of a number of evaluation metrics (e.g., biases, centered RMS, and pattern correlations) will be shown for a variety of physical quantities and CORDEX domains. These evaluations are performed using products from obs4MIPs, an activity initiated by DOE and NASA, and now shepherded by the World Climate Research Program's Data Advisory Council.

Toward 10-km mesh global climate simulations

NASA Astrophysics Data System (ADS)

Ohfuchi, W.; Enomoto, T.; Takaya, K.; Yoshioka, M. K.

2002-12-01

An atmospheric general circulation model (AGCM) that runs very efficiently on the Earth Simulator (ES) was developed. The ES is a gigantic vector-parallel computer with the peak performance of 40 Tflops. The AGCM, named AFES (AGCM for ES), was based on the version 5.4.02 of an AGCM developed jointly by the Center for Climate System Research, the University of Tokyo and the Japanese National Institute for Environmental Sciences. The AFES was, however, totally rewritten in FORTRAN90 and MPI while the original AGCM was written in FORTRAN77 and not capable of parallel computing. The AFES achieved 26 Tflops (about 65 % of the peak performance of the ES) at resolution of T1279L96 (10-km horizontal resolution and 500-m vertical resolution in middle troposphere to lower stratosphere). Some results of 10- to 20-day global simulations will be presented. At this moment, only short-term simulations are possible due to data storage limitation. As ten tera flops computing is achieved, peta byte data storage are necessary to conduct climate-type simulations at this super-high resolution global simulations. Some possibilities for future research topics in global super-high resolution climate simulations will be discussed. Some target topics are mesoscale structures and self-organization of the Baiu-Meiyu front over Japan, cyclogenecsis over the North Pacific and typhoons around the Japan area. Also improvement in local precipitation with increasing horizontal resolution will be demonstrated.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

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

Way, M. J.; Aleinov, I.; Amundsen, David S.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower tomore » more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.« less

Accelerating Time Integration for the Shallow Water Equations on the Sphere Using GPUs

DOE PAGES

Archibald, R.; Evans, K. J.; Salinger, A.

2015-06-01

The push towards larger and larger computational platforms has made it possible for climate simulations to resolve climate dynamics across multiple spatial and temporal scales. This direction in climate simulation has created a strong need to develop scalable timestepping methods capable of accelerating throughput on high performance computing. This study details the recent advances in the implementation of implicit time stepping of the spectral element dynamical core within the United States Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) on graphical processing units (GPU) based machines. We demonstrate how solvers in the Trilinos project are interfaced with ACMEmore » and GPU kernels to increase computational speed of the residual calculations in the implicit time stepping method for the atmosphere dynamics. We demonstrate the optimization gains and data structure reorganization that facilitates the performance improvements.« less

Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information

NASA Astrophysics Data System (ADS)

Yang, Tiantian; Asanjan, Ata Akbari; Welles, Edwin; Gao, Xiaogang; Sorooshian, Soroosh; Liu, Xiaomang

2017-04-01

Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for many purposes. Efficient reservoir operation requires policy makers and operators to understand how reservoir inflows are changing under different hydrological and climatic conditions to enable forecast-informed operations. Over the last decade, the uses of Artificial Intelligence and Data Mining [AI & DM] techniques in assisting reservoir streamflow subseasonal to seasonal forecasts have been increasing. In this study, Random Forest [RF), Artificial Neural Network (ANN), and Support Vector Regression (SVR) are employed and compared with respect to their capabilities for predicting 1 month-ahead reservoir inflows for two headwater reservoirs in USA and China. Both current and lagged hydrological information and 17 known climate phenomenon indices, i.e., PDO and ENSO, etc., are selected as predictors for simulating reservoir inflows. Results show (1) three methods are capable of providing monthly reservoir inflows with satisfactory statistics; (2) the results obtained by Random Forest have the best statistical performances compared with the other two methods; (3) another advantage of Random Forest algorithm is its capability of interpreting raw model inputs; (4) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow; and (5) different climate conditions are autocorrelated with up to several months, and the climatic information and their lags are cross correlated with local hydrological conditions in our case studies.

Representation of Precipitation in a Decade-long Continental-Scale Convection-Resolving Climate Simulation

NASA Astrophysics Data System (ADS)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2017-12-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Regional climate simulations using horizontal resolutions of O(1km) allow to explicitly resolve deep convection leading to an improved representation of the water cycle. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. A new version of the Consortium for Small-Scale Modeling weather and climate model (COSMO) is capable of exploiting new supercomputer architectures employing GPU accelerators, and allows convection-resolving climate simulations on computational domains spanning continents and time periods up to one decade. We present results from a decade-long, convection-resolving climate simulation on a European-scale computational domain. The simulation has a grid spacing of 2.2 km, 1536x1536x60 grid points, covers the period 1999-2008, and is driven by the ERA-Interim reanalysis. Specifically we present an evaluation of hourly rainfall using a wide range of data sets, including several rain-gauge networks and a remotely-sensed lightning data set. Substantial improvements are found in terms of the diurnal cycles of precipitation amount, wet-hour frequency and all-hour 99th percentile. However the results also reveal substantial differences between regions with and without strong orographic forcing. Furthermore we present an index for deep-convective activity based on the statistics of vertical motion. Comparison of the index with lightning data shows that the convection-resolving climate simulations are able to reproduce important features of the annual cycle of deep convection in Europe. Leutwyler D., D. Lüthi, N. Ban, O. Fuhrer, and C. Schär (2017): Evaluation of the Convection-Resolving Climate Modeling Approach on Continental Scales , J. Geophys. Res. Atmos., 122, doi:10.1002/2016JD026013.

NASA Center for Climate Simulation (NCCS) Presentation

NASA Technical Reports Server (NTRS)

Webster, William P.

2012-01-01

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

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

Gustafson, William I.; Vogelmann, Andrew M.; Cheng, Xiaoping

The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability has been named the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project. The initial focus of LASSO is on shallow convection at the ARM Southern Great Plains (SGP) Climate Research Facility. The availability of LES simulations with concurrent observations will serve many purposes. LES helps bridge the scale gap between DOE ARM observations and models, and the use of routine LES addsmore » value to observations. It provides a self-consistent representation of the atmosphere and a dynamical context for the observations. Further, it elucidates unobservable processes and properties. LASSO will generate a simulation library for researchers that enables statistical approaches beyond a single-case mentality. It will also provide tools necessary for modelers to reproduce the LES and conduct their own sensitivity experiments. Many different uses are envisioned for the combined LASSO LES and observational library. For an observationalist, LASSO can help inform instrument remote sensing retrievals, conduct Observation System Simulation Experiments (OSSEs), and test implications of radar scan strategies or flight paths. For a theoretician, LASSO will help calculate estimates of fluxes and co-variability of values, and test relationships without having to run the model yourself. For a modeler, LASSO will help one know ahead of time which days have good forcing, have co-registered observations at high-resolution scales, and have simulation inputs and corresponding outputs to test parameterizations. Further details on the overall LASSO project are available at https://www.arm.gov/capabilities/modeling/lasso.« less

Energy Exascale Earth System Model (E3SM) Project Strategy

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

Bader, D.

The E3SM project will assert and maintain an international scientific leadership position in the development of Earth system and climate models at the leading edge of scientific knowledge and computational capabilities. With its collaborators, it will demonstrate its leadership by using these models to achieve the goal of designing, executing, and analyzing climate and Earth system simulations that address the most critical scientific questions for the nation and DOE.

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

NASA Technical Reports Server (NTRS)

Putnam, WilliamM.

2011-01-01

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Multidecadal simulation of coastal fog with a regional climate model

NASA Astrophysics Data System (ADS)

O'Brien, Travis A.; Sloan, Lisa C.; Chuang, Patrick Y.; Faloona, Ian C.; Johnstone, James A.

2013-06-01

In order to model stratocumulus clouds and coastal fog, we have coupled the University of Washington boundary layer model to the regional climate model, RegCM (RegCM-UW). By comparing fog occurrences observed at various coastal airports in the western United States, we show that RegCM-UW has success at modeling the spatial and temporal (diurnal, seasonal, and interannual) climatology of northern California coastal fog. The quality of the modeled fog estimate depends on whether coast-adjacent ocean or land grid cells are used; for the model runs shown here, the oceanic grid cells seem to be most appropriate. The interannual variability of oceanic northern California summertime fog, from a multi-decadal simulation, has a high and statistically significant correlation with the observed interannual variability ( r = 0.72), which indicates that RegCM-UW is capable of investigating the response of fog to long-term climatological forcing. While RegCM-UW has a number of aspects that would benefit from further investigation and development, RegCM-UW is a new tool for investigating the climatology of coastal fog and the physical processes that govern it. We expect that with appropriate physical parameterizations and moderate horizontal resolution, other climate models should be capable of simulating coastal fog. The source code for RegCM-UW is publicly available, under the GNU license, through the International Centre for Theoretical Physics.

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012

PubMed Central

Bai, Jie; Li, Longhui

2017-01-01

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang. PMID:28841645

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012.

PubMed

Yuan, Xiuliang; Bai, Jie; Li, Longhui; Kurban, Alishir; De Maeyer, Philippe

2017-01-01

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang.

The contribution of future agricultural trends in the US Midwest to global climate change mitigation

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

Thomson, Allison M.; Kyle, G. Page; Zhang, Xuesong

2014-01-19

Land use change is a complex response to changing environmental and socioeconomic systems. Historical drivers of land use change include changes in the natural resource availability of a region, changes in economic conditions for production of certain products and changing policies. Most recently, introduction of policy incentives for biofuel production have influenced land use change in the US Midwest, leading to concerns that bioenergy production systems may compete with food production and land conservation. Here we explore how land use may be impacted by future climate mitigation measures by nesting a high resolution agricultural model (EPIC – Environmental Policy Indicatormore » Climate) for the US Midwest within a global integrated assessment model (GCAM – Global Change Assessment Model). This approach is designed to provide greater spatial resolution and detailed agricultural practice information by focusing on the climate mitigation potential of agriculture and land use in a specific region, while retaining the global economic context necessary to understand the far ranging effects of climate mitigation targets. We find that until the simulated carbon prices are very high, the US Midwest has a comparative advantage in producing traditional food and feed crops over bioenergy crops. Overall, the model responds to multiple pressures by adopting a mix of future responses. We also find that the GCAM model is capable of simulations at multiple spatial scales and agricultural technology resolution, which provides the capability to examine regional response to global policy and economic conditions in the context of climate mitigation.« less

Simulation of the summer circulation over South America by two regional climate models. Part I: Mean climatology

NASA Astrophysics Data System (ADS)

Fernandez, J. P. R.; Franchito, S. H.; Rao, V. B.

2006-09-01

This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model - EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America.

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

NASA Astrophysics Data System (ADS)

Wu, Yenan; Zhong, Ping-an; Xu, Bin; Zhu, Feilin; Fu, Jisi

2017-06-01

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960-2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001-2010) and the predicting period (2011-2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.

Progress in and prospects for fluvial flood modelling.

PubMed

Wheater, H S

2002-07-15

Recent floods in the UK have raised public and political awareness of flood risk. There is an increasing recognition that flood management and land-use planning are linked, and that decision-support modelling tools are required to address issues of climate and land-use change for integrated catchment management. In this paper, the scientific context for fluvial flood modelling is discussed, current modelling capability is considered and research challenges are identified. Priorities include (i) appropriate representation of spatial precipitation, including scenarios of climate change; (ii) development of a national capability for continuous hydrological simulation of ungauged catchments; (iii) improved scientific understanding of impacts of agricultural land-use and land-management change, and the development of new modelling approaches to represent those impacts; (iv) improved representation of urban flooding, at both local and catchment scale; (v) appropriate parametrizations for hydraulic simulation of in-channel and flood-plain flows, assimilating available ground observations and remotely sensed data; and (vi) a flexible decision-support modelling framework, incorporating developments in computing, data availability, data assimilation and uncertainty analysis.

The influence of model resolution on the simulated sensitivity of North Atlantic tropical cyclone maximum intensity to sea surface temperature

DOE PAGES

Strazzo, S. E.; Elsner, J. B.; LaRow, T. E.; ...

2016-07-10

Global climate models (GCMs) are routinely relied upon to study the possible impacts of climate change on a wide range of meteorological phenomena, including tropical cyclones (TCs). Previous studies addressed whether GCMs are capable of reproducing observed TC frequency and intensity distributions. This research builds upon earlier studies by examining how well GCMs capture the physically relevant relationship between TC intensity and SST. Specifically, the influence of model resolution on the ability of a GCM to reproduce the sensitivity of simulated TC intensity to SST is examined for the MRI-AGCM (20 km), the GFDL-HiRAM (50 km), the FSU-COAPS (0.94°) model,more » and two versions of the CAM5 (1° and 0.25°). Results indicate that while a 1°C increase in SST corresponds to a 5.5–7.0 m s -1 increase in observed maximum intensity, the same 1°C increase in SST is not associated with a statistically significant increase in simulated TC maximum intensity for any of the models examined. However, it also is shown that the GCMs all capably reproduce the observed sensitivity of potential intensity to SST. The models generate the thermodynamic environment suitable for the development of strong TCs over the correct portions of the Nort h Atlantic basin, but strong simulated TCs do not develop over these areas, even for models that permit Category 5 TCs. This result supports the notion that direct simulation of TC eyewall convection is necessary to accurately represent TC intensity and intensification processes in climate models, although additional explanations are also explored.« less

Mesh infrastructure for coupled multiprocess geophysical simulations

DOE PAGES

Garimella, Rao V.; Perkins, William A.; Buksas, Mike W.; ...

2014-01-01

We have developed a sophisticated mesh infrastructure capability to support large scale multiphysics simulations such as subsurface flow and reactive contaminant transport at storage sites as well as the analysis of the effects of a warming climate on the terrestrial arctic. These simulations involve a wide range of coupled processes including overland flow, subsurface flow, freezing and thawing of ice rich soil, accumulation, redistribution and melting of snow, biogeochemical processes involving plant matter and finally, microtopography evolution due to melting and degradation of ice wedges below the surface. In addition to supporting the usual topological and geometric queries about themore » mesh, the mesh infrastructure adds capabilities such as identifying columnar structures in the mesh, enabling deforming of the mesh subject to constraints and enabling the simultaneous use of meshes of different dimensionality for subsurface and surface processes. The generic mesh interface is capable of using three different open source mesh frameworks (MSTK, MOAB and STKmesh) under the hood allowing the developers to directly compare them and choose one that is best suited for the application's needs. We demonstrate the results of some simulations using these capabilities as well as present a comparison of the performance of the different mesh frameworks.« less

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).

Using climate model simulations to assess the current climate risk to maize production

NASA Astrophysics Data System (ADS)

Kent, Chris; Pope, Edward; Thompson, Vikki; Lewis, Kirsty; Scaife, Adam A.; Dunstone, Nick

2017-05-01

The relationship between the climate and agricultural production is of considerable importance to global food security. However, there has been relatively little exploration of climate-variability related yield shocks. The short observational yield record does not adequately sample natural inter-annual variability thereby limiting the accuracy of probability assessments. Focusing on the United States and China, we present an innovative use of initialised ensemble climate simulations and a new agro-climatic indicator, to calculate the risk of severe water stress. Combined, these regions provide 60% of the world’s maize, and therefore, are crucial to global food security. To probe a greater range of inter-annual variability, the indicator is applied to 1400 simulations of the present day climate. The probability of severe water stress in the major maize producing regions is quantified, and in many regions an increased risk is found compared to calculations from observed historical data. Analysis suggests that the present day climate is also capable of producing unprecedented severe water stress conditions. Therefore, adaptation plans and policies based solely on observed events from the recent past may considerably under-estimate the true risk of climate-related maize shocks. The probability of a major impact event occurring simultaneously across both regions—a multi-breadbasket failure—is estimated to be up to 6% per decade and arises from a physically plausible climate state. This novel approach highlights the significance of climate impacts on crop production shocks and provides a platform for considerably improving food security assessments, in the present day or under a changing climate, as well as development of new risk based climate services.

Making objective summaries of climate model behavior more accessible

NASA Astrophysics Data System (ADS)

Gleckler, P. J.

2016-12-01

For multiple reasons, a more efficient and systematic evaluation of publically available climate model simulations is urgently needed. The IPCC, national assessments, and an assortment of other public and policy-driven needs place taxing demands on researchers. While cutting edge research is essential to meeting these needs, so too are results from well-established analysis, and these should be more efficiently produced, widely accessible, and be highly traceable. Furthermore, the number of simulations used by the research community is already large and expected to dramatically increase with the 6th phase of the Coupled Model Intercomparison Project (CMIP6). To help meet the demands on the research community and synthesize results from the rapidly expanding number and complexity of model simulations, well-established characteristics from all CMIP DECK (Diagnosis, Evaluation and Characterization of Klima) experiments will be routinely produced and made accessible. This presentation highlights the PCMDI Metrics Package (PMP), a capability that is designed to provide a diverse suite of objective summary statistics across spatial and temporal scales, gauging the agreement between models and observations. In addition to the PMP, ESMValTool is being developed to broadly diagnose CMIP simulations, and a variety of other packages target specialized sets of analysis. The challenges and opportunities of working towards coordinating these community-based capabilities will be discussed.

Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Lin, Zhaohui; Rhoades, Alan M.; Ullrich, Paul A.; Zarzycki, Colin M.; Lu, Zheng; Rahimi-Esfarjani, Stefan R.

2017-10-01

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10-40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

Toward a Climate OSSE for NASA Earth Sciences

NASA Astrophysics Data System (ADS)

Leroy, S. S.; Collins, W. D.; Feldman, D.; Field, R. D.; Ming, Y.; Pawson, S.; Sanderson, B.; Schmidt, G. A.

2016-12-01

In the Continuity Study, the National Academy of Sciences advised that future space missions be rated according to five categories: the importance of a well-defined scientific objective, the utility of the observation in addressing the scientific objective, the quality with which the observation can be made, the probability of the mission's success, and the mission's affordability. The importance, probability, and affordability are evaluated subjectively by scientific consensus, by engineering review panels, and by cost models; however, the utility and quality can be evaluated objectively by a climate observation system simulation experiment (COSSE). A discussion of the philosophical underpinnings of a COSSE for NASA Earth Sciences will be presented. A COSSE is built upon a perturbed physics ensemble of a sophisticated climate model that can simulate a mission's prospective observations and its well-defined quantitative scientific objective and that can capture the uncertainty associated with each. A strong correlation between observation and scientific objective after consideration of physical uncertainty leads to a high quality. Persistence of a high correlation after inclusion of the proposed measurement error leads to a high utility. There are five criteria that govern that nature of a particular COSSE: (1) whether the mission's scientific objective is one of hypothesis testing or climate prediction, (2) whether the mission is empirical or inferential, (3) whether the core climate model captures essential physical uncertainties, (4) the level of detail of the simulated observations, and (5) whether complementarity or redundancy of information is to be valued. Computation of the quality and utility is done using Bayesian statistics, as has been done previously for multi-decadal climate prediction conditioned on existing data. We advocate for a new program within NASA Earth Sciences to establish a COSSE capability. Creation of a COSSE program within NASA Earth Sciences will require answers from the climate research community to basic questions, such as whether a COSSE capability should be centralized or de-centralized. Most importantly, the quantified scientific objective of a proposed mission must be defined with extreme specificity for a COSSE to be applied.

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

Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

USDA-ARS?s Scientific Manuscript database

With the availability of advanced hydrologic data in the public domain such as remotely sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable ...

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

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

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

Simulating the characteristics of tropical cyclones over the South West Indian Ocean using a Stretched-Grid Global Climate Model

NASA Astrophysics Data System (ADS)

Maoyi, Molulaqhooa L.; Abiodun, Babatunde J.; Prusa, Joseph M.; Veitch, Jennifer J.

2018-03-01

Tropical cyclones (TCs) are one of the most devastating natural phenomena. This study examines the capability of a global climate model with grid stretching (CAM-EULAG, hereafter CEU) in simulating the characteristics of TCs over the South West Indian Ocean (SWIO). In the study, CEU is applied with a variable increment global grid that has a fine horizontal grid resolution (0.5° × 0.5°) over the SWIO and coarser resolution (1° × 1°—2° × 2.25°) over the rest of the globe. The simulation is performed for the 11 years (1999-2010) and validated against the Joint Typhoon Warning Center (JTWC) best track data, global precipitation climatology project (GPCP) satellite data, and ERA-Interim (ERAINT) reanalysis. CEU gives a realistic simulation of the SWIO climate and shows some skill in simulating the spatial distribution of TC genesis locations and tracks over the basin. However, there are some discrepancies between the observed and simulated climatic features over the Mozambique channel (MC). Over MC, CEU simulates a substantial cyclonic feature that produces a higher number of TC than observed. The dynamical structure and intensities of the CEU TCs compare well with observation, though the model struggles to produce TCs with a deep pressure centre as low as the observed. The reanalysis has the same problem. The model captures the monthly variation of TC occurrence well but struggles to reproduce the interannual variation. The results of this study have application in improving and adopting CEU for seasonal forecasting over the SWIO.

Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Lapillonne, Xavier; Lüthi, Daniel; Schär, Christoph

2016-09-01

The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Using horizontal grid spacings of O(1km), convection-resolving weather and climate models allows one to explicitly resolve deep convection. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in supercomputing have led to new hybrid node designs, mixing conventional multi-core hardware and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to these architectures is the COSMO (Consortium for Small-scale Modeling) model.Here we present the convection-resolving COSMO model on continental scales using a version of the model capable of using GPU accelerators. The verification of a week-long simulation containing winter storm Kyrill shows that, for this case, convection-parameterizing simulations and convection-resolving simulations agree well. Furthermore, we demonstrate the applicability of the approach to longer simulations by conducting a 3-month-long simulation of the summer season 2006. Its results corroborate the findings found on smaller domains such as more credible representation of the diurnal cycle of precipitation in convection-resolving models and a tendency to produce more intensive hourly precipitation events. Both simulations also show how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. This includes the formation of sharp cold frontal structures, convection embedded in fronts and small eddies, or the formation and organization of propagating cold pools. Finally, we assess the performance gain from using heterogeneous hardware equipped with GPUs relative to multi-core hardware. With the COSMO model, we now use a weather and climate model that has all the necessary modules required for real-case convection-resolving regional climate simulations on GPUs.

Understanding Climate Uncertainty with an Ocean Focus

NASA Astrophysics Data System (ADS)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599.

Space-borne profiling of atmospheric thermodynamic variables with raman lidar

NASA Astrophysics Data System (ADS)

Di Girolamo, Paolo; Behrendt, Andreas; Wulfmeyer, Volker

2018-04-01

The performance of a space-borne water vapour and temperature Raman lidar has been simulated, with a specific attention to the Earth Explorer Missions in the frame of ESA's Living Planet Program. We report simulations under a variety of atmospheric scenarios, demonstrating the capability of a space Raman lidar to provide global-scale water vapour and temperature measurements in the troposphere with an accuracy fulfilling most observational requirements for numerical weather prediction (NWP) and climate research.

Climate Modeling: Ocean Cavities below Ice Shelves

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

Petersen, Mark Roger

The Accelerated Climate Model for Energy (ACME), a new initiative by the U.S. Department of Energy, includes unstructured-mesh ocean, land-ice, and sea-ice components using the Model for Prediction Across Scales (MPAS) framework. The ability to run coupled high-resolution global simulations efficiently on large, high-performance computers is a priority for ACME. Sub-ice shelf ocean cavities are a significant new capability in ACME, and will be used to better understand how changing ocean temperature and currents influence glacial melting and retreat. These simulations take advantage of the horizontal variable-resolution mesh and adaptive vertical coordinate in MPAS-Ocean, in order to place high resolutionmore » below ice shelves and near grounding lines.« less

Outreach/education interface for Cryosphere models using the Virtual Ice Sheet Laboratory

NASA Astrophysics Data System (ADS)

Larour, E. Y.; Halkides, D. J.; Romero, V.; Cheng, D. L.; Perez, G.

2014-12-01

In the past decade, great strides have been made in the development of models capable of projecting the future evolution of glaciers and the polar ice sheets in a changing climate. These models are now capable of replicating some of the trends apparent in satellite observations. However, because this field is just now maturing, very few efforts have been dedicated to adapting these capabilities to education. Technologies that have been used in outreach efforts in Atmospheric and Oceanic sciences still have not been extended to Cryospheric Science. We present a cutting-edge, technologically driven virtual laboratory, geared towards outreach and k-12 education, dedicated to the polar ice sheets on Antarctica and Greenland, and their role as major contributors to sea level rise in coming decades. VISL (Virtual Ice Sheet Laboratory) relies on state-of-the art Web GL rendering of polar ice sheets, Android/iPhone and web portability using Javascript, as well as C++ simulations (back-end) based on the Ice Sheet System Model, the NASA model for simulating the evolution of polar ice sheets. Using VISL, educators and students can have an immersive experience into the world of polar ice sheets, while at the same exercising the capabilities of a state-of-the-art climate model, all of it embedded into an education experience that follows the new STEM standards for education.This work was performed at the California Institute of Technology's Jet Propulsion Laboratory under a contract with the National Aeronautics and Space Administration's Cryosphere Science Program.

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Development of a numerical model to simulate groundwater flow in the shallow aquifer system of Assateague Island, Maryland and Virginia

USGS Publications Warehouse

Masterson, John P.; Fienen, Michael N.; Gesch, Dean B.; Carlson, Carl S.

2013-01-01

A three-dimensional groundwater-flow model was developed for Assateague Island in eastern Maryland and Virginia to simulate both groundwater flow and solute (salt) transport to evaluate the groundwater system response to sea-level rise. The model was constructed using geologic and spatial information to represent the island geometry, boundaries, and physical properties and was calibrated using an inverse modeling parameter-estimation technique. An initial transient solute-transport simulation was used to establish the freshwater-saltwater boundary for a final calibrated steady-state model of groundwater flow. This model was developed as part of an ongoing investigation by the U.S. Geological Survey Climate and Land Use Change Research and Development Program to improve capabilities for predicting potential climate-change effects and provide the necessary tools for adaptation and mitigation of potentially adverse impacts.

Determination of Earth outgoing radiation using a constellation of satellites

NASA Astrophysics Data System (ADS)

Gristey, Jake; Chiu, Christine; Gurney, Robert; Han, Shin-Chan; Morcrette, Cyril

2017-04-01

The outgoing radiation fluxes at the top of the atmosphere, referred to as Earth outgoing radiation (EOR), constitute a vital component of the Earth's energy budget. This EOR exhibits strong diurnal signatures and is inherently connected to the rapidly evolving scene from which the radiation originates, so our ability to accurately monitor EOR with sufficient temporal resolution and spatial coverage is crucial for weather and climate studies. Despite vast improvements in satellite observations in recent decades, achieving these criteria remains challenging from current measurements. A technology revolution in small satellites and sensor miniaturisation has created a new and exciting opportunity for a novel, viable and sustainable observation strategy from a constellation of satellites, capable of providing both global coverage and high temporal resolution simultaneously. To explore the potential of a constellation approach for observing EOR we perform a series of theoretical simulation experiments. Using the results from these simulation experiments, we will demonstrate a baseline constellation configuration capable of accurately monitoring global EOR at unprecedented temporal resolution. We will also show whether it is possible to reveal synoptic scale, fast evolving phenomena by applying a deconvolution technique to the simulated measurements. The ability to observe and understand the relationship between these phenomena and changes in EOR is of fundamental importance in constraining future warming of our climate system.

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

Evaluation of Boreal Summer Monsoon Intraseasonal Variability in the GASS-YOTC Multi-Model Physical Processes Experiment

NASA Astrophysics Data System (ADS)

Mani, N. J.; Waliser, D. E.; Jiang, X.

2014-12-01

While the boreal summer monsoon intraseasonal variability (BSISV) exerts profound influence on the south Asian monsoon, the capability of present day dynamical models in simulating and predicting the BSISV is still limited. The global model evaluation project on vertical structure and diabatic processes of the Madden Julian Oscillations (MJO) is a joint venture, coordinated by the Working Group on Numerical Experimentation (WGNE) MJO Task Force and GEWEX Atmospheric System Study (GASS) program, for assessing the model deficiencies in simulating the ISV and for improving our understanding of the underlying processes. In this study the simulation of the northward propagating BSISV is investigated in 26 climate models with special focus on the vertical diabatic heating structure and clouds. Following parallel lines of inquiry as the MJO Task Force has done with the eastward propagating MJO, we utilize previously proposed and newly developed model performance metrics and process diagnostics and apply them to the global climate model simulations of BSISV.

Simulation of future stream alkalinity under changing deposition and climate scenarios.

PubMed

Welsch, Daniel L; Cosby, B Jack; Hornberger, George M

2006-08-31

Models of soil and stream water acidification have typically been applied under scenarios of changing acidic deposition, however, climate change is usually ignored. Soil air CO2 concentrations have potential to increase as climate warms and becomes wetter, thus affecting soil and stream water chemistry by initially increasing stream alkalinity at the expense of reducing base saturation levels on soil exchange sites. We simulate this change by applying a series of physically based coupled models capable of predicting soil air CO2 and stream water chemistry. We predict daily stream water alkalinity for a small catchment in the Virginia Blue Ridge for 60 years into the future given stochastically generated daily climate values. This is done for nine different combinations of climate and deposition. The scenarios for both climate and deposition include a static scenario, a scenario of gradual change, and a scenario of abrupt change. We find that stream water alkalinity continues to decline for all scenarios (average decrease of 14.4 microeq L-1) except where climate is gradually warming and becoming more moist (average increase of 13 microeq L-1). In all other scenarios, base cation removal from catchment soils is responsible for limited alkalinity increase resulting from climate change. This has implications given the extent that acidification models are used to establish policy and legislation concerning deposition and emissions.

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.

Simulation of corn yields and parameters uncertainties analysis in Hebei and Sichuang, China

NASA Astrophysics Data System (ADS)

Fu, A.; Xue, Y.; Hartman, M. D.; Chandran, A.; Qiu, B.; Liu, Y.

2016-12-01

Corn is one of most important agricultural production in China. Research on the impacts of climate change and human activities on corn yields is important in understanding and mitigating the negative effects of environmental factors on corn yields and maintaining the stable corn production. Using climatic data, including daily temperature, precipitation, and solar radiation from 1948 to 2010, soil properties, observed corn yields, and farmland management information, corn yields in Sichuang and Hebei Provinces of China in the past 63 years were simulated using the Daycent model, and the results was evaluated using Root mean square errors, bias, simulation efficiency, and standard deviation. The primary climatic factors influencing corn yields were examined, the uncertainties of climatic factors was analyzed, and the uncertainties of human activity parameters were also studied by changing fertilization levels and cultivated ways. The results showed that: (1) Daycent model is capable to simulate corn yields in Sichuang and Hebei provinces of China. Observed and simulated corn yields have the similar increasing trend with time. (2) The minimum daily temperature is the primary factor influencing corn yields in Sichuang. In Hebei Province, daily temperature, precipitation and wind speed significantly affect corn yields.(3) When the global warming trend of original data was removed, simulated corn yields were lower than before, decreased by about 687 kg/hm2 from 1992 to 2010; When the fertilization levels, cultivated ways were increased and decreased by 50% and 75%, respectively in the Schedule file in Daycent model, the simulated corn yields increased by 1206 kg/hm2 and 776 kg/hm2, respectively, with the enhancement of fertilization level and the improvement of cultivated way. This study provides a scientific base for selecting a suitable fertilization level and cultivated way in corn fields in China.

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.

Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

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

Wan, Hui; Rasch, Philip J.; Zhang, Kai

2014-09-08

This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivitymore » of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.« less

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

Interactive Photochemistry in Earth System Models to Assess Uncertainty in Ozone and Greenhouse Gases. Final report

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

Prather, Michael J.; Hsu, Juno; Nicolau, Alex

Atmospheric chemistry controls the abundances and hence climate forcing of important greenhouse gases including N 2O, CH 4, HFCs, CFCs, and O 3. Attributing climate change to human activities requires, at a minimum, accurate models of the chemistry and circulation of the atmosphere that relate emissions to abundances. This DOE-funded research provided realistic, yet computationally optimized and affordable, photochemical modules to the Community Earth System Model (CESM) that augment the CESM capability to explore the uncertainty in future stratospheric-tropospheric ozone, stratospheric circulation, and thus the lifetimes of chemically controlled greenhouse gases from climate simulations. To this end, we have successfullymore » implemented Fast-J (radiation algorithm determining key chemical photolysis rates) and Linoz v3.0 (linearized photochemistry for interactive O 3, N 2O, NO y and CH 4) packages in LLNL-CESM and for the first time demonstrated how change in O2 photolysis rate within its uncertainty range can significantly impact on the stratospheric climate and ozone abundances. From the UCI side, this proposal also helped LLNL develop a CAM-Superfast Chemistry model that was implemented for the IPCC AR5 and contributed chemical-climate simulations to CMIP5.« less

The Virtual Climate Data Server (vCDS): An iRODS-Based Data Management Software Appliance Supporting Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation

NASA Technical Reports Server (NTRS)

Schnase, John L.; Tamkin, Glenn S.; Ripley, W. David III; Stong, Savannah; Gill, Roger; Duffy, Daniel Q.

2012-01-01

Scientific data services are becoming an important part of the NASA Center for Climate Simulation's mission. Our technological response to this expanding role is built around the concept of a Virtual Climate Data Server (vCDS), repetitive provisioning, image-based deployment and distribution, and virtualization-as-a-service. The vCDS is an iRODS-based data server specialized to the needs of a particular data-centric application. We use RPM scripts to build vCDS images in our local computing environment, our local Virtual Machine Environment, NASA s Nebula Cloud Services, and Amazon's Elastic Compute Cloud. Once provisioned into one or more of these virtualized resource classes, vCDSs can use iRODS s federation capabilities to create an integrated ecosystem of managed collections that is scalable and adaptable to changing resource requirements. This approach enables platform- or software-asa- service deployment of vCDS and allows the NCCS to offer virtualization-as-a-service: a capacity to respond in an agile way to new customer requests for data services.

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Projected Applications of a ``Climate in a Box'' Computing System at the NASA Short-term Prediction Research and Transition (SPoRT) Center

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Molthan, A.; Zavodsky, B.; Case, J.; Lafontaine, F.

2010-12-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to “Climate in a Box” systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the “Climate in a Box” system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA’s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the “Climate in a Box” system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Molthan, Andrew L.; Zavodsky, Bradley; Case, Jonathan L.; LaFontaine, Frank J.

2010-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Ecological Assimilation of Land and Climate Observations - the EALCO model

NASA Astrophysics Data System (ADS)

Wang, S.; Zhang, Y.; Trishchenko, A.

2004-05-01

Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net radiation, evapotranspiration, gross primary production, net primary production, and net ecosystem production were discussed.

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.

Flexible Environments for Grand-Challenge Simulation in Climate Science

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R.

2004-12-01

Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability.

The Future of Climate Science (Invited)

NASA Astrophysics Data System (ADS)

Bishop, R.

2010-12-01

High Performance Computing is currently deployed in several centers for climate research, but not at the levels needed to achieve substantial success on a global basis, given the complexity of the problem. A quantum leap in capabilities will be necessary to handle next-generation climate models that integrate newly emerging sciences, high-resolution grids, and voluminous observational data from satellites and sophisticated ground devices. Dr. Bishop will discuss efforts to build an International Centre for Earth Simulation (ICES) based in Switzerland that takes an holistic systems approach, and that has the competence and resources to achieve new insights in this new decade, and is capable to globally influence public policy with respect to weather, climate, environment, disaster risk reduction and socio-economic development. On this progressively crowded and fragile planet, such a capability will be invaluable, Bishop believes, if not imperative, for our long-term survival. ICES could serve as a test-bed for large scale public and private development planning. Decision makers could ask ‘what if’ questions for major construction projects (such as China’s Three Gorges Dam), and then interactively evaluate alternative scenarios. Likewise, ICES could help uncover the possible unintended consequences of climate remediation and adaptation strategies, geo-engineering ideas, CO2 sequestration, deep sea drilling, etc. ICES would be a resource for building more resilient societies in an era of rapid climate change and frequent natural disasters (such as flooding, extreme weather events and volcanic ash clouds), and therefore of great consequence to our future well-being. It would ultimately play a major role in the education and training of policy-makers, the public, and future Earth Scientists - in conjunction with the current national and regional centers.

Can beaches survive climate change?

USGS Publications Warehouse

Vitousek, Sean; Barnard, Patrick L.; Limber, Patrick W.

2017-01-01

Anthropogenic climate change is driving sea level rise, leading to numerous impacts on the coastal zone, such as increased coastal flooding, beach erosion, cliff failure, saltwater intrusion in aquifers, and groundwater inundation. Many beaches around the world are currently experiencing chronic erosion as a result of gradual, present-day rates of sea level rise (about 3 mm/year) and human-driven restrictions in sand supply (e.g., harbor dredging and river damming). Accelerated sea level rise threatens to worsen coastal erosion and challenge the very existence of natural beaches throughout the world. Understanding and predicting the rates of sea level rise and coastal erosion depends on integrating data on natural systems with computer simulations. Although many computer modeling approaches are available to simulate shoreline change, few are capable of making reliable long-term predictions needed for full adaption or to enhance resilience. Recent advancements have allowed convincing decadal to centennial-scale predictions of shoreline evolution. For example, along 500 km of the Southern California coast, a new model featuring data assimilation predicts that up to 67% of beaches may completely erode by 2100 without large-scale human interventions. In spite of recent advancements, coastal evolution models must continue to improve in their theoretical framework, quantification of accuracy and uncertainty, computational efficiency, predictive capability, and integration with observed data, in order to meet the scientific and engineering challenges produced by a changing climate.

Hadoop for High-Performance Climate Analytics: Use Cases and Lessons Learned

NASA Technical Reports Server (NTRS)

Tamkin, Glenn

2013-01-01

Scientific data services are a critical aspect of the NASA Center for Climate Simulations mission (NCCS). Hadoop, via MapReduce, provides an approach to high-performance analytics that is proving to be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. The NCCS is particularly interested in the potential of Hadoop to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we prototyped a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. The initial focus was on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. After preliminary results suggested that this approach improves efficiencies within data intensive analytic workflows, we invested in building a cyber infrastructure resource for developing a new generation of climate data analysis capabilities using Hadoop. This resource is focused on reducing the time spent in the preparation of reanalysis data used in data-model inter-comparison, a long sought goal of the climate community. This paper summarizes the related use cases and lessons learned.

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.

The Science of Climate Responsibility

NASA Astrophysics Data System (ADS)

Mitchell, D.; Frumhoff, P. C.; Sparrow, S.; Allen, M. R.

2015-12-01

Extreme events linked with human induced climate change have now been reported around the globe. Among the most troublesome impacts are increased wild fires, failed crop yields, extreme flooding and increase human mortality (Hansen and Cramer, 2015). Many of these impacts are predicted to increase into the future. Non-industrialised communities around the world will be the least capable of adapting, while the industrial communities, who are often responsible for historical carbon emissions, will find adaptation easier. Such a situation lends itself to the issue of responsibility. In order to assess responsibility, it must first be established where the major carbon and methane emissions are originating. It must then be estimated how these emissions project onto localised climate, which is often the primary indicator behind impacts on society. In this study, we address this question using a 25 km regional climate model capable of simulating climate thousands of times under the Weather@home citizen science project. The use of this framework allows us to generate huge data sample sizes, which can be put in the context of very low sample sizes of observational data. We concentrate on the 2003 heat wave over Europe, but show how this method could be applied to less data rich regions, including the Middle East and the Horn of Africa.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

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

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

Information-computational platform for collaborative multidisciplinary investigations of regional climatic changes and their impacts

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through unified graphical web-interface. Partial support of RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2 and Projects 69, 131, 140 and APN CBA2012-16NSY project is acknowledged.

Impacts of Climate Change on Energy Consumption and Peak Demand in Buildings: A Detailed Regional Approach

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

Dirks, James A.; Gorrissen, Willy J.; Hathaway, John E.

2015-01-01

This paper presents the results of numerous commercial and residential building simulations, with the purpose of examining the impact of climate change on peak and annual building energy consumption over the portion of the Eastern Interconnection (EIC) located in the United States. The climate change scenario considered (IPCC A2 scenario as downscaled from the CASCaDE data set) has changes in mean climate characteristics as well as changes in the frequency and duration of intense weather events. This investigation examines building energy demand for three annual periods representative of climate trends in the CASCaDE data set at the beginning, middle, andmore » end of the century--2004, 2052, and 2089. Simulations were performed using the Building ENergy Demand (BEND) model which is a detailed simulation platform built around EnergyPlus. BEND was developed in collaboration with the Platform for Regional Integrated Modeling and Analysis (PRIMA), a modeling framework designed to simulate the complex interactions among climate, energy, water, and land at decision-relevant spatial scales. Over 26,000 building configurations of different types, sizes, vintages, and, characteristics which represent the population of buildings within the EIC, are modeled across the 3 EIC time zones using the future climate from 100 locations within the target region, resulting in nearly 180,000 spatially relevant simulated demand profiles for each of the 3 years. In this study, the building stock characteristics are held constant based on the 2005 building stock in order to isolate and present results that highlight the impact of the climate signal on commercial and residential energy demand. Results of this analysis compare well with other analyses at their finest level of specificity. This approach, however, provides a heretofore unprecedented level of specificity across multiple spectrums including spatial, temporal, and building characteristics. This capability enables the ability to perform detailed hourly impact studies of building adaptation and mitigation strategies on energy use and electricity peak demand within the context of the entire grid and economy.« less

A modelling study of the event-based retention performance of green roof under the hot-humid tropical climate in Kuching.

PubMed

Chai, C T; Putuhena, F J; Selaman, O S

2017-12-01

The influences of climate on the retention capability of green roof have been widely discussed in existing literature. However, knowledge on how the retention capability of green roof is affected by the tropical climate is limited. This paper highlights the retention performance of the green roof situated in Kuching under hot-humid tropical climatic conditions. Using the green roof water balance modelling approach, this study simulated the hourly runoff generated from a virtual green roof from November 2012 to October 2013 based on past meteorological data. The result showed that the overall retention performance was satisfactory with a mean retention rate of 72.5% from 380 analysed rainfall events but reduced to 12.0% only for the events that potentially trigger the occurrence of flash flood. By performing the Spearman rank's correlation analysis, it was found that the rainfall depth and mean rainfall intensity, individually, had a strong negative correlation with event retention rate, suggesting that the retention rate increases with decreased rainfall depth. The expected direct relationship between retention rate and antecedent dry weather period was found to be event size dependent.

What can we learn about the dynamics of DO-events from studying the high resolution ice core records?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2017-04-01

The causes for and possible predictions of rapid climate changes are poorly understood. The most pronounced changes observed, beside the glacial terminations, are the Dansgaard-Oeschger events. Present day general circulation climate models simulating glacial conditions are not capable of reproducing these rapid shifts. It is thus not known if they are due to bifurcations in the structural stability of the climate or if they are induced by stochastic fluctuations. By analyzing a high resolution ice core record we exclude the bifurcation scenario, which strongly suggests that they are noise induced and thus have very limited predictability. Ref: Peter Ditlevsen, "Tipping points in the climate system", in Nonlinear and Stochastic Climate Dynamics, Cambridge University Press (C. Franzke and T. O'Kane, eds.) (2016) P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, L19703, 2010

High-Resolution Modeling to Assess Tropical Cyclone Activity in Future Climate Regimes

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

Lackmann, Gary

2013-06-10

Applied research is proposed with the following objectives: (i) to determine the most likely level of tropical cyclone intensity and frequency in future climate regimes, (ii) to provide a quantitative measure of uncertainty in these predictions, and (iii) to improve understanding of the linkage between tropical cyclones and the planetary-scale circulation. Current mesoscale weather forecasting models, such as the Weather Research and Forecasting (WRF) model, are capable of simulating the full intensity of tropical cyclones (TC) with realistic structures. However, in order to accurately represent both the primary and secondary circulations in these systems, model simulations must be configured withmore » sufficient resolution to explicitly represent convection (omitting the convective parameterization scheme). Most previous numerical studies of TC activity at seasonal and longer time scales have not utilized such explicit convection (EC) model runs. Here, we propose to employ the moving nest capability of WRF to optimally represent TC activity on a seasonal scale using a downscaling approach. The statistical results of a suite of these high-resolution TC simulations will yield a realistic representation of TC intensity on a seasonal basis, while at the same time allowing analysis of the feedback that TCs exert on the larger-scale climate system. Experiments will be driven with analyzed lateral boundary conditions for several recent Atlantic seasons, spanning a range of activity levels and TC track patterns. Results of the ensemble of WRF simulations will then be compared to analyzed TC data in order to determine the extent to which this modeling setup can reproduce recent levels of TC activity. Next, the boundary conditions (sea-surface temperature, tropopause height, and thermal/moisture profiles) from the recent seasons will be altered in a manner consistent with various future GCM/RCM scenarios, but that preserves the large-scale shear and incipient disturbance activity. This will allow (i) a direct comparison of future TC activity that could be expected for an active or inactive season in an altered climate regime, and (ii) a measure of the level of uncertainty and variability in TC activity resulting from different carbon emission scenarios.« less

Calibrated Hydrothermal Parameters, Barrow, Alaska, 2013

DOE Data Explorer

Atchley, Adam; Painter, Scott; Harp, Dylan; Coon, Ethan; Wilson, Cathy; Liljedahl, Anna; Romanovsky, Vladimir

2015-01-29

A model-observation-experiment process (ModEx) is used to generate three 1D models of characteristic micro-topographical land-formations, which are capable of simulating present active thaw layer (ALT) from current climate conditions. Each column was used in a coupled calibration to identify moss, peat and mineral soil hydrothermal properties to be used in up-scaled simulations. Observational soil temperature data from a tundra site located near Barrow, AK (Area C) is used to calibrate thermal properties of moss, peat, and sandy loam soil to be used in the multiphysics Advanced Terrestrial Simulator (ATS) models. Simulation results are a list of calibrated hydrothermal parameters for moss, peat, and mineral soil hydrothermal parameters.

Dynamic Emulation of NASA Missions for IVandV: A Case Study of JWST and SLS

NASA Technical Reports Server (NTRS)

Yokum, Steve

2015-01-01

Software-Only-Simulations are an emerging but quickly developing field of study throughout NASA. The NASA Independent Verification Validation (IVV) Independent Test Capability (ITC) team has been rapidly building a collection of simulators for a wide range of NASA missions. ITC specializes in full end-to-end simulations that enable developers, VV personnel, and operators to test-as-you-fly. In four years, the team has delivered a wide variety of spacecraft simulations ranging from low complexity science missions such as the Global Precipitation Management (GPM) satellite and the Deep Space Climate Observatory (DSCOVR), to the extremely complex missions such as the James Webb Space Telescope (JWST) and Space Launch System (SLS).

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

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

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Signal-transfer Modeling for Regional Assessment of Forest Responses to Environmental Changes in the Southeastern United States

Treesearch

Robert J. Luxmoore; William W. Hargrove; M. Lynn Tharp; Wilfred M. Post; Michael W. Berry; Karen S. Minser; Wendell P. Cropper; Dale W. Johnson; Boris Zeide; Ralph L. Amateis; Harold E. Burkhart; V. Clark Baldwin; Kelly D. Peterson

2000-01-01

Stochastic transfer of information in a hierarchy of simulators is offered as a conceptual approach for assessing forest responses to changing climate and air quality across 13 southeastern states of the USA. This assessment approach combines geographic information system and Monte Carlo capabilities with several scales of computer modeling for southern pine species...

Modeling Urban Energy Savings Scenarios Using Earth System Microclimate and Urban Morphology

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rose, A.; New, J. R.; Yuan, J.; Omitaomu, O.; Sylvester, L.; Branstetter, M. L.; Carvalhaes, T. M.; Seals, M.; Berres, A.

2017-12-01

We analyze and quantify the relationships among climatic conditions, urban morphology, population, land cover, and energy use so that these relationships can be used to inform energy-efficient urban development and planning. We integrate different approaches across three research areas: earth system modeling; impacts, adaptation and vulnerability; and urban planning in order to address three major gaps in the existing capability in these areas: i) neighborhood resolution modeling and simulation of urban micrometeorological processes and their effect on and from regional climate; ii) projections for future energy use under urbanization and climate change scenarios identifying best strategies for urban morphological development and energy savings; iii) analysis and visualization tools to help planners optimally use these projections.

WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

NASA Astrophysics Data System (ADS)

Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

2014-05-01

Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are accompanied by the WASCAL Graduate Research Program on the West African Climate System. The GRP-WACS provides ten scholarships per year for West African PhD students with a duration of three years. Present and future WASCAL PhD students will constitute one important user group of the Linux cluster that will be installed at the Competence Center in Ouagadougou, Burkina Faso. Regional Land-Atmosphere Simulations A key research activity of the WASCAL Core Research Program is the analysis of interactions between the land surface and the atmosphere to investigate how land surface changes affect hydro-meteorological surface fluxes such as evapotranspiration. Since current land surface models of global and regional climate models neglect dominant lateral hydrological processes such as surface runoff, a novel land surface model is used, the NCAR Distributed Hydrological Modeling System (NDHMS). This model can be coupled to WRF (WRF-Hydro) to perform two-way coupled atmospheric-hydrological simulations for the watershed of interest. Hardware and network prerequisites include a HPC cluster, network switches, internal storage media, Internet connectivity of sufficient bandwidth. Competences needed are HPC, storage, and visualization systems optimized for climate research, parallelization and optimization of climate models and workflows, efficient management of highest data volumes.

Composite Study Of Aerosol Long-Range Transport Events From East Asia And North America

NASA Astrophysics Data System (ADS)

Jiang, X.; Waliser, D. E.; Guan, B.; Xavier, P.; Petch, J.; Klingaman, N. P.; Woolnough, S.

2011-12-01

While the Madden-Julian Oscillation (MJO) exerts pronounced influences on global climate and weather systems, current general circulation models (GCMs) exhibit rather limited capability in representing this prominent tropical variability mode. Meanwhile, the fundamental physics of the MJO are still elusive. Given the central role of the diabatic heating for prevailing MJO theories and demands for reducing the model deficiencies in simulating the MJO, a global model inter-comparison project on diabatic processes and vertical heating structure associated with the MJO has been coordinated through a joint effort by the WCRP-WWRP/THORPEX YOTC MJO Task Force and GEWEX GASS Program. In this presentation, progress of this model inter-comparison project will be reported, with main focus on climate simulations from about 27 atmosphere-only and coupled GCMs. Vertical structures of heating and diabatic processes associated with the MJO based on multi-model simulations will be presented along with their reanalysis and satellite estimate counterparts. Key processes possibly responsible for a realistic simulation of the MJO, including moisture-convection interaction, gross moist stability, ocean coupling, and surface heat flux, will be discussed.

Planning the Next Decade of Coordinated Research to Better Understand and Simulate Marine Low Clouds

NASA Technical Reports Server (NTRS)

Wood, Robert; Jensen, Michael P.; Wang, Jian; Bretherton, Christopher S.; Burrows, Susannah M.; Del Genio, Anthony; Fridlind, Ann M.; Ghan, Steven J.; Ghate, Virendra P.; Kollias, Pavlos;

Planning the Next Decade of Coordinated Research to Better Understand and Simulate Marine Low Clouds

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

Wood, Robert; Jensen, Michael P.; Wang, Jian

Marine low clouds have a large impact on the Earth’s energy and hydrologic cycle. They strongly reflect incoming solar radiation, with little compensating impact on outgoing longwave radiation resulting in a net cooling of the climate. The representation of marine low clouds in climate models is one of the largest uncertainties in the estimation of climate sensitivity (e.g. Bony and Dufresne 2005), and marine low clouds are critical mediators of global aerosol radiative forcing (Zelinka et al. 2014). Despite the importance of these cloud systems to the Earth’s climate, their parameterization continues to be challenging, due to an incomplete understandingmore » of key processes that regulate them and insufficient resolution of these processes in models. To help define research pathways to address outstanding issues related to our understanding of marine low clouds, a workshop was held January 27-29, 2016 at Brookhaven National Laboratory. The overarching goal was to identify current gaps in knowledge or simulation capabilities and promising strategies for addressing them, with a particular emphasis on improving the representation of marine low clouds in climate models and contributions that could be made with U.S. Department of Energy Atmospheric System Research support using Atmospheric Radiation Measurement facility measurements.« less

System Dynamics based Dengue modeling environment to simulate evolution of Dengue infection under different climate scenarios

NASA Astrophysics Data System (ADS)

Anwar, R.; Khan, R.; Usmani, M.; Colwell, R. R.; Jutla, A.

2017-12-01

Vector borne infectious diseases such as Dengue, Zika and Chikungunya remain a public health threat. An estimate of the World Health Organization (WHO) suggests that about 2.5 billion people, representing ca. 40% of human population,are at increased risk of dengue; with more than 100 million infection cases every year. Vector-borne infections cannot be eradicated since disease causing pathogens survive in the environment. Over the last few decades dengue infection has been reported in more than 100 countries and is expanding geographically. Female Ae. Aegypti mosquito, the daytime active and a major vector for dengue virus, is associated with urban population density and regional climatic processes. However, mathematical quantification of relationships on abundance of vectors and climatic processes remain a challenge, particularly in regions where such data are not routinely collected. Here, using system dynamics based feedback mechanism, an algorithm integrating knowledge from entomological, meteorological and epidemiological processes is developed that has potential to provide ensemble simulations on risk of occurrence of dengue infection in human population. Using dataset from satellite remote sensing, the algorithm was calibrated and validated using actual dengue case data of Iquitos, Peru. We will show results on model capabilities in capturing initiation and peak in the observed time series. In addition, results from several simulation scenarios under different climatic conditions will be discussed.

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

MERRA Analytic Services

NASA Astrophysics Data System (ADS)

Schnase, J. L.; Duffy, D. Q.; McInerney, M. A.; Tamkin, G. S.; Thompson, J. H.; Gill, R.; Grieg, C. M.

2012-12-01

MERRA Analytic Services (MERRA/AS) is a cyberinfrastructure resource for developing and evaluating a new generation of climate data analysis capabilities. MERRA/AS supports OBS4MIP activities by reducing the time spent in the preparation of Modern Era Retrospective-Analysis for Research and Applications (MERRA) data used in data-model intercomparison. It also provides a testbed for experimental development of high-performance analytics. MERRA/AS is a cloud-based service built around the Virtual Climate Data Server (vCDS) technology that is currently used by the NASA Center for Climate Simulation (NCCS) to deliver Intergovernmental Panel on Climate Change (IPCC) data to the Earth System Grid Federation (ESGF). Crucial to its effectiveness, MERRA/AS's servers will use a workflow-generated realizable object capability to perform analyses over the MERRA data using the MapReduce approach to parallel storage-based computation. The results produced by these operations will be stored by the vCDS, which will also be able to host code sets for those who wish to explore the use of MapReduce for more advanced analytics. While the work described here will focus on the MERRA collection, these technologies can be used to publish other reanalysis, observational, and ancillary OBS4MIP data to ESGF and, importantly, offer an architectural approach to climate data services that can be generalized to applications and customers beyond the traditional climate research community. In this presentation, we describe our approach, experiences, lessons learned,and plans for the future.; (A) MERRA/AS software stack. (B) Example MERRA/AS interfaces.

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

NASA Astrophysics Data System (ADS)

Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

2017-04-01

Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.

Seasonality of Overstory and Understory Fluxes in a Semi-Arid Oak Savanna: What can be Learned from Comparing Measured and Modeled Fluxes?

NASA Astrophysics Data System (ADS)

Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Chen, J. M.; Verfaillie, J. G.; Ma, S.; Baldocchi, D. D.

2011-12-01

Semi-arid climates experience large seasonal and inter-annual variability in radiation and precipitation, creating natural conditions adequate to study how year-to-year changes affect atmosphere-biosphere fluxes. Especially, savanna ecosystems, that combine tree and below-canopy components, create a unique environment in which phenology dramatically changes between seasons. We used a 10-year flux database in order to define seasonal and interannual variability of climatic inputs and fluxes, and evaluate model capability to reproduce observed variability. This is based on the perception that model capability to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site is a low density and low LAI (0.8) semi-arid savanna, located at Tonzi Ranch, Northern California. In this system, trees are active during the warm season (Mar - Oct), and grasses are active during the wet season (Dec - May). Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Fluxes were simulated using bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Models were partly capable of reproducing fluxes on daily scales (R2=0.66). We then compared model outputs for different ecosystem components and seasons, and found distinct seasons with high correlations while other seasons were purely represented. Comparison was much higher for ET than for GPP. The understory was better simulated than the overstory. CANOAK overestimated spring understory fluxes, probably due to the capability to directly calculated 3D radiative transfer. BEPS underestimated spring understory fluxes, following the pre-description of grass die-off. Both models underestimated peak spring overstory fluxes. During winter tree dormant, modeled fluxes were null, but occasional high fluxes of both ET and GPP were measured following precipitation events, likely produced by an adverse measurement effect. This analysis enabled to pinpoint specific areas where models break, and stress that model capability to reproduce fluxes vary among seasons and ecosystem components. The combined response was such, that comparison decreases when ecosystem fluxes were partitioned between overstory and understory fluxes. Model performance decreases with time scale; while performance was high for some seasons, models were less capable of reproducing the high variability in understory fluxes vs. the conservative overstory fluxes on annual scales. Discrepancies were not always a result of models' faults; comparison largely improved when measurements of overstory fluxes during precipitation events were excluded. Conclusions raised from this research enable to answer the critical question of the level and type of details needed in order to correctly predict ecosystem respond to environmental and climatic change.

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

NASA Technical Reports Server (NTRS)

Maxwell, Thomas

2012-01-01

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Significance of model credibility in estimating climate projection distributions for regional hydroclimatological risk assessments

USGS Publications Warehouse

Brekke, L.D.; Dettinger, M.D.; Maurer, E.P.; Anderson, M.

2008-01-01

Ensembles of historical climate simulations and climate projections from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset were investigated to determine how model credibility affects apparent relative scenario likelihoods in regional risk assessments. Methods were developed and applied in a Northern California case study. An ensemble of 59 twentieth century climate simulations from 17 WCRP CMIP3 models was analyzed to evaluate relative model credibility associated with a 75-member projection ensemble from the same 17 models. Credibility was assessed based on how models realistically reproduced selected statistics of historical climate relevant to California climatology. Metrics of this credibility were used to derive relative model weights leading to weight-threshold culling of models contributing to the projection ensemble. Density functions were then estimated for two projected quantities (temperature and precipitation), with and without considering credibility-based ensemble reductions. An analysis for Northern California showed that, while some models seem more capable at recreating limited aspects twentieth century climate, the overall tendency is for comparable model performance when several credibility measures are combined. Use of these metrics to decide which models to include in density function development led to local adjustments to function shapes, but led to limited affect on breadth and central tendency, which were found to be more influenced by 'completeness' of the original ensemble in terms of models and emissions pathways. ?? 2007 Springer Science+Business Media B.V.

Convection-Permitting Regional Climate Simulations over the Contiguous United States Including Potential Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Liu, Changhai; Rasmussen, Roy; Ikeda, Kyoko; Barlage, Michael; Chen, Fei; Clark, Martyn; Dai, Aiguo; Dudhia, Jimy; Gochis, David; Gutmann, Ethan; Li, Yanping; Newman, Andrew; Thompson, Gregory

2016-04-01

The WRF model with a domain size of 1360x1016x51 points, using a 4 km spacing to encompass most of North America, is employed to investigate the water cycle and climate change impacts over the Contiguous United States (CONUS). Four suites of numerical experiments are being conducted, consisting of a 13-year retrospective simulation forced with ERA-I reanalysis, a 13-year climate sensitivity or Pseudo-Global Warming (PGW) simulation, and two 10-year CMIP5-based historical/future period simulations based on a revised bias-correction method. The major objectives are: 1) to evaluate high-resolution WRF's capability to capture orographic precipitation and snow mass balance over the western CONUS and convective precipitation over the eastern CONUS; 2) to assess future changes of seasonal snowfall and snowpack and associated hydrological cycles along with their regional variability across the different mountain barriers and elevation dependency, in response to the CMIP5 projected 2071-2100 climate warming; 3) to examine the precipitation changes under the projected global warming, with an emphasis on precipitation extremes and the warm-season precipitation corridor in association with MCS tracks in the central US; and 4) to provide a valuable community dataset for regional climate change and impact studies. Preliminary analysis of the retrospective simulation shows both seasonal/sub-seasonal precipitation and temperature are well reproduced, with precipitation bias being within 10% of the observations and temperature bias being below 1 degree C in most seasons and locations. The observed annual cycle of snow water equivalent (SWE), such as peak time and disappearance time, is also realistically replicated, even though the peak value is somewhat underestimated. The PGW simulation shows a large cold-season warming in northeast US and eastern Canada, possibly associated with snow albedo feedback, and a strong summer warming in north central US in association with precipitation reduction. There is an increase in annual rainfall/precipitation, but a sharp reduction in snowfall/snowpack in response to the global warming. A pronounced seasonal feature is the suppressed summertime precipitation in central US for the warmer climate. More detailed analysis of the modeling results is presently under way and will be presented in the meeting.

Objective tropical cyclone extratropical transition detection in high-resolution reanalysis and climate model data

DOE PAGES

Zarzycki, Colin M.; Thatcher, Diana R.; Jablonowski, Christiane

2017-01-22

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km).more » The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.« less

Simulating the Dependence of Aspen on Redistributed Snow

NASA Astrophysics Data System (ADS)

Soderquist, B.; Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Winstral, A. H.

2013-12-01

In mountainous regions across the western USA, the distribution of aspen (Populus tremuloides) is often directly related to heterogeneous soil moisture subsidies resulting from redistributed snow. With decades of climate and precipitation data across elevational and precipitation gradients, the Reynolds Creek Experimental Watershed (RCEW) in southwest Idaho provides a unique opportunity to study the relationship between aspen and redistributed snow. Within the RCEW, the total amount of precipitation has not changed in the past 50 years, but there are sharp declines in the percentage of the precipitation falling as snow. As shifts in the distribution of available moisture continue, future trends in aspen net primary productivity (NPP) remain uncertain. In order to assess the importance of snowdrift subsidies, NPP of three aspen stands was simulated at sites spanning elevational and precipitation gradients using the biogeochemical process model BIOME-BGC. At the aspen site experiencing the driest climate and lowest amount of precipitation from snow, approximately 400 mm of total precipitation was measured from November to March of 2008. However, peak measured snow water equivalent (SWE) held in drifts directly upslope of this stand was approximately 2100 mm, 5 times more moisture than the uniform winter precipitation layer initially assumed by BIOME-BGC. BIOME-BGC simulations in dry years forced by adjusted precipitation data resulted in NPP values approximately 30% higher than simulations assuming a uniform precipitation layer. Using BIOME-BGC and climate data from 1985-2011, the relationship between simulated NPP and measured basal area increments (BAI) improved after accounting for redistributed snow, indicating increased simulation representation. In addition to improved simulation capabilities, soil moisture data, diurnal branch water potential, and stomatal conductance observations at each site detail the use of soil moisture in the rooting zone and the onset of drought stress occurring in stands located along a precipitation phase gradient. These results further emphasize the importance of redistributed snow in heterogeneous landscapes along with the need to account for temporal shifts in water resource availability when assessing ecosystem vulnerability to climate change.

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

2017-12-01

Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

Spatiotemporal characteristics of heat waves over China in regional climate simulations within the CORDEX-EA project

NASA Astrophysics Data System (ADS)

Wang, Pinya; Tang, Jianping; Sun, Xuguang; Liu, Jianyong; Juan, Fang

2018-03-01

Using the Weather Research and Forecasting (WRF) model, this paper analyzes the spatiotemporal features of heat waves in 20-year regional climate simulations over East Asia, and investigates the capability of WRF to reproduce observational heat waves in China. Within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX), the WRF model is driven by the ERA-Interim (ERAIN) reanalysis, and five continuous simulations are conducted from 1989 to 2008. Of these, four runs apply the interior spectral nudging (SN) technique with different wavenumbers, nudging variables and nudging coefficients. Model validations show that WRF can reasonably reproduce the spatiotemporal features of heat waves in China. Compared with the experiment without SN, the application of SN is effectie on improving the skill of the model in simulating both the spatial distributions and temporal variations of heat waves of different intensities. The WRF model shows advantages in reproducing the synoptic circulations with SN and therefore yields better representations for heat wave events. Besides, the SN method is able to preserve the variability of large-scale circulations quite well, which in turn adjusts the extreme temperature variability towards the observation. Among the four SN experiments, those with stronger nudging coefficients perform better in modulating both the spatial and temporal features of heat waves. In contrast, smaller nudging coefficients weaken the effects of SN on improving WRF's performances.

Realistic dust and water cycles in the MarsWRF GCM using coupled two-moment microphysics

NASA Astrophysics Data System (ADS)

Lee, Christopher; Richardson, Mark Ian; Mischna, Michael A.; Newman, Claire E.

2017-10-01

Dust and water ice aerosols significantly complicate the Martian climate system because the evolution of the two aerosol fields is coupled through microphysics and because both aerosols strongly interact with visible and thermal radiation. The combination of strong forcing feedback and coupling has led to various problems in understanding and modeling of the Martian climate: in reconciling cloud abundances at different locations in the atmosphere, in generating a stable dust cycle, and in preventing numerical instability within models.Using a new microphysics model inside the MarsWRF GCM we show that fully coupled simulations produce more realistic simulation of the Martian climate system compared to a dry, dust only simulations. In the coupled simulations, interannual variability and intra-annual variability are increased, strong 'solstitial pause' features are produced in both winter high latitude regions, and dust storm seasons are more varied, with early southern summer (Ls 180) dust storms and/or more than one storm occurring in some seasons.A new microphysics scheme was developed as a part of this work and has been included in the MarsWRF model. The scheme uses split spectral/spatial size distribution numerics with adaptive bin sizes to track particle size evolution. Significantly, this scheme is highly accurate, numerically stable, and is capable of running with time steps commensurate with those of the parent atmospheric model.

Continuously on-­going regional climate hindcast simulations for impact applications

NASA Astrophysics Data System (ADS)

Anders, Ivonne; Piringer, Martin; Kaufmann, Hildegard; Knauder, Werner; Resch, Gernot; Andre, Konrad

2017-04-01

Observational data for e.g. temperature, precipitation, radiation, or wind are often used as meteorological forcing for different impact models, like e.g. crop models, urban models, economic models and energy system models. To assess a climate signal, the time period covered by the observation is often too short, they have gaps in between, and are inhomogeneous over time, due to changes in the measurements itself or in the near surrounding. Thus output from global and regional climate models can close the gap and provide homogeneous and physically consistent time series of meteorological parameters. CORDEX evaluation runs performed for the IPCC-AR5 provide a good base for the regional scale. However, with respect to climate services, continuously on-going hindcast simulations are required for regularly updated applications. The Climate Research group at the national Austrian weather service, ZAMG, is focusing on high mountain regions and, especially on the Alps. The hindcast-simulation performed with the regional climate model COSMO-CLM is forced by ERAinterim and optimized for the Alpine Region. The simulation available for the period of 1979-2015 in a spatial resolution of about 10km is prolonged ongoing and fullfils the customer's needs with respect of output variables, levels, intervals and statistical measures. One of the main tasks is to capture strong precipitation events which often occur during summer when low pressure systems develop over the Golf of Genoa, moving to the Northeast. This leads to floods and landslide events in Austria, Czech Republic and Germany. Such events are not sufficiently represented in the CORDEX-evaluation runs. ZAMG use high quality gridded precipitation and temperature data for the Alpine Region (1-6km) to evaluate the model performance. Data is provided e.g. to hydrological modellers (high water, low water), but also to assess icing capability of infrastructure or the calculation the separation distances between livestock farming and residential area.

Capabilities of stochastic rainfall models as data providers for urban hydrology

NASA Astrophysics Data System (ADS)

Haberlandt, Uwe

2017-04-01

For planning of urban drainage systems using hydrological models, long, continuous precipitation series with high temporal resolution are needed. Since observed time series are often too short or not available everywhere, the use of synthetic precipitation is a common alternative. This contribution compares three precipitation models regarding their suitability to provide 5 minute continuous rainfall time series for a) sizing of drainage networks for urban flood protection and b) dimensioning of combined sewage systems for pollution reduction. The rainfall models are a parametric stochastic model (Haberlandt et al., 2008), a non-parametric probabilistic approach (Bárdossy, 1998) and a stochastic downscaling of dynamically simulated rainfall (Berg et al., 2013); all models are operated both as single site and multi-site generators. The models are applied with regionalised parameters assuming that there is no station at the target location. Rainfall and discharge characteristics are utilised for evaluation of the model performance. The simulation results are compared against results obtained from reference rainfall stations not used for parameter estimation. The rainfall simulations are carried out for the federal states of Baden-Württemberg and Lower Saxony in Germany and the discharge simulations for the drainage networks of the cities of Hamburg, Brunswick and Freiburg. Altogether, the results show comparable simulation performance for the three models, good capabilities for single site simulations but low skills for multi-site simulations. Remarkably, there is no significant difference in simulation performance comparing the tasks flood protection with pollution reduction, so the models are finally able to simulate both the extremes and the long term characteristics of rainfall equally well. Bárdossy, A., 1998. Generating precipitation time series using simulated annealing. Wat. Resour. Res., 34(7): 1737-1744. Berg, P., Wagner, S., Kunstmann, H., Schädler, G., 2013. High resolution regional climate model simulations for Germany: part I — validation. Climate Dynamics, 40(1): 401-414. Haberlandt, U., Ebner von Eschenbach, A.-D., Buchwald, I., 2008. A space-time hybrid hourly rainfall model for derived flood frequency analysis. Hydrol. Earth Syst. Sci., 12: 1353-1367.

Southern Ocean bottom water characteristics in CMIP5 models

NASA Astrophysics Data System (ADS)

Heuzé, CéLine; Heywood, Karen J.; Stevens, David P.; Ridley, Jeff K.

2013-04-01

Southern Ocean deep water properties and formation processes in climate models are indicative of their capability to simulate future climate, heat and carbon uptake, and sea level rise. Southern Ocean temperature and density averaged over 1986-2005 from 15 CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models are compared with an observed climatology, focusing on bottom water. Bottom properties are reasonably accurate for half the models. Ten models create dense water on the Antarctic shelf, but it mixes with lighter water and is not exported as bottom water as in reality. Instead, most models create deep water by open ocean deep convection, a process occurring rarely in reality. Models with extensive deep convection are those with strong seasonality in sea ice. Optimum bottom properties occur in models with deep convection in the Weddell and Ross Gyres. Bottom Water formation processes are poorly represented in ocean models and are a key challenge for improving climate predictions.

An Investigation of Bomb Cyclone Climatology: Reanalysis vs. NCEP's CFS Model

NASA Astrophysics Data System (ADS)

Alvarez, F. M.; Eichler, T.; Gottschalck, J.

2009-12-01

Given the concerns and potential impacts of climate change, the need for climate models to simulate weather phenomena is as important as ever. An example of such phenomena is rapidly intensifying cyclones, also known as "bombs." These intense cyclones have devastating effects on residential and marine commercial interests as well as the transportation industry. In this study, we generate a climatology of rapid cyclogenesis using the National Centers for Environmental Prediction’s (NCEP) Climate Forecast System (CFS) model. Results are compared to NCEP’s global reanalysis data to determine if the CFS model is capable of producing a realistic extreme storm climatology. This represents the first step in quantifying rapidly intensifying cyclones in the CFS model, which will be useful in contributing towards future model improvements, as well as gauging its ability in determining the role of synoptic-scale storms in climate change.

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.

Heat waves over Central Europe in regional climate model simulations

NASA Astrophysics Data System (ADS)

Lhotka, Ondřej; Kyselý, Jan

2014-05-01

Regional climate models (RCMs) have become a powerful tool for exploring impacts of global climate change on a regional scale. The aim of the study is to evaluate the capability of RCMs to reproduce characteristics of major heat waves over Central Europe in their simulations of the recent climate (1961-2000), with a focus on the most severe and longest Central European heat wave that occurred in 1994. We analyzed 7 RCM simulations with a high resolution (0.22°) from the ENSEMBLES project, driven by the ERA-40 reanalysis. In observed data (the E-OBS 9.0 dataset), heat waves were defined on the basis of deviations of daily maximum temperature (Tmax) from the 95% quantile of summer Tmax distribution in grid points over Central Europe. The same methodology was applied in the RCM simulations; we used corresponding 95% quantiles (calculated for each RCM and grid point) in order to remove the bias of modelled Tmax. While climatological characteristics of heat waves are reproduced reasonably well in the RCM ensemble, we found major deficiencies in simulating heat waves in individual years. For example, METNOHIRHAM simulated very severe heat waves in 1996, when no heat wave was observed. Focusing on the major 1994 heat wave, considerable differences in simulated temperature patterns were found among the RCMs. The differences in the temperature patterns were clearly linked to the simulated amount of precipitation during this event. The 1994 heat wave was almost absent in all RCMs that did not capture the observed precipitation deficit, while it was by far most pronounced in KNMI-RACMO that simulated virtually no precipitation over Central Europe during the 15-day period of the heat wave. By contrast to precipitation, values of evaporative fraction in the RCMs were not linked to severity of the simulated 1994 heat wave. This suggests a possible major contribution of other factors such as cloud cover and associated downward shortwave radiation. Therefore, a more detailed analysis of individual components of the energy budget over Central Europe during and before the 1994 heat wave was performed.

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Analysis of the present and future winter Pacific-North American teleconnection in the ECHAM5 global and RegCM3 regional climate models

USGS Publications Warehouse

Allan, Andrea M.; Hostetler, Steven W.; Alder, Jay R.

2014-01-01

We use the NCEP/NCAR Reanalysis (NCEP) and the MPI/ECHAM5 general circulation model to drive the RegCM3 regional climate model to assess the ability of the models to reproduce the spatiotemporal aspects of the Pacific-North American teleconnection (PNA) pattern. Composite anomalies of the NCEP-driven RegCM3 simulations for 1982–2000 indicate that the regional model is capable of accurately simulating the key features (500-hPa heights, surface temperature, and precipitation) of the positive and negative phases of the PNA with little loss of information in the downscaling process. The basic structure of the PNA is captured in both the ECHAM5 global and ECHAM5-driven RegCM3 simulations. The 1950–2000 ECHAM5 simulation displays similar temporal and spatial variability in the PNA index as that of NCEP; however, the magnitudes of the positive and negative phases are weaker than those of NCEP. The RegCM3 simulations clearly differentiate the climatology and associated anomalies of snow water equivalent and soil moisture of the positive and negative PNA phases. In the RegCM3 simulations of the future (2050–2100), changes in the location and extent of the Aleutian low and the continental high over North America alter the dominant flow patterns associated with positive and negative PNA modes. The future projections display a shift in the patterns of the relationship between the PNA and surface climate variables, which suggest the potential for changes in the PNA-related surface hydrology of North America.

Validation of catchment models for predicting land-use and climate change impacts. 1. Method

NASA Astrophysics Data System (ADS)

Ewen, J.; Parkin, G.

1996-02-01

Computer simulation models are increasingly being proposed as tools capable of giving water resource managers accurate predictions of the impact of changes in land-use and climate. Previous validation testing of catchment models is reviewed, and it is concluded that the methods used do not clearly test a model's fitness for such a purpose. A new generally applicable method is proposed. This involves the direct testing of fitness for purpose, uses established scientific techniques, and may be implemented within a quality assured programme of work. The new method is applied in Part 2 of this study (Parkin et al., J. Hydrol., 175:595-613, 1996).

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

Compressing climate model simulations: reducing storage burden while preserving information

NASA Astrophysics Data System (ADS)

Hammerling, Dorit; Baker, Allison; Xu, Haiying; Clyne, John; Li, Samuel

2017-04-01

Climate models, which are run at high spatial and temporal resolutions, generate massive quantities of data. As our computing capabilities continue to increase, storing all of the generated data is becoming a bottleneck, which negatively affects scientific progress. It is thus important to develop methods for representing the full datasets by smaller compressed versions, which still preserve all the critical information and, as an added benefit, allow for faster read and write operations during analysis work. Traditional lossy compression algorithms, as for example used for image files, are not necessarily ideally suited for climate data. While visual appearance is relevant, climate data has additional critical features such as the preservation of extreme values and spatial and temporal gradients. Developing alternative metrics to quantify information loss in a manner that is meaningful to climate scientists is an ongoing process still in its early stages. We will provide an overview of current efforts to develop such metrics to assess existing algorithms and to guide the development of tailored compression algorithms to address this pressing challenge.

EdGCM: Research Tools for Training the Climate Change Generation

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Developing Models for Predictive Climate Science

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

Drake, John B; Jones, Philip W

2007-01-01

The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strongmore » tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.« less

Parameterization of the 3-PG model for Pinus elliottii stands using alternative methods to estimate fertility rating, biomass partitioning and canopy closure

Treesearch

Carlos A. Gonzalez-Benecke; Eric J. Jokela; Wendell P. Cropper; Rosvel Bracho; Daniel J. Leduc

2014-01-01

The forest simulation model, 3-PG, has been widely applied as a useful tool for predicting growth of forest species in many countries. The model has the capability to estimate the effects of management, climate and site characteristics on many stand attributes using easily available data. Currently, there is an increasing interest in estimating biomass and assessing...

Data management and analysis for the Earth System Grid

NASA Astrophysics Data System (ADS)

Williams, D. N.; Ananthakrishnan, R.; Bernholdt, D. E.; Bharathi, S.; Brown, D.; Chen, M.; Chervenak, A. L.; Cinquini, L.; Drach, R.; Foster, I. T.; Fox, P.; Hankin, S.; Henson, V. E.; Jones, P.; Middleton, D. E.; Schwidder, J.; Schweitzer, R.; Schuler, R.; Shoshani, A.; Siebenlist, F.; Sim, A.; Strand, W. G.; Wilhelmi, N.; Su, M.

2008-07-01

The international climate community is expected to generate hundreds of petabytes of simulation data within the next five to seven years. This data must be accessed and analyzed by thousands of analysts worldwide in order to provide accurate and timely estimates of the likely impact of climate change on physical, biological, and human systems. Climate change is thus not only a scientific challenge of the first order but also a major technological challenge. In order to address this technological challenge, the Earth System Grid Center for Enabling Technologies (ESG-CET) has been established within the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC)-2 program, with support from the offices of Advanced Scientific Computing Research and Biological and Environmental Research. ESG-CET's mission is to provide climate researchers worldwide with access to the data, information, models, analysis tools, and computational capabilities required to make sense of enormous climate simulation datasets. Its specific goals are to (1) make data more useful to climate researchers by developing Grid technology that enhances data usability; (2) meet specific distributed database, data access, and data movement needs of national and international climate projects; (3) provide a universal and secure web-based data access portal for broad multi-model data collections; and (4) provide a wide-range of Grid-enabled climate data analysis tools and diagnostic methods to international climate centers and U.S. government agencies. Building on the successes of the previous Earth System Grid (ESG) project, which has enabled thousands of researchers to access tens of terabytes of data from a small number of ESG sites, ESG-CET is working to integrate a far larger number of distributed data providers, high-bandwidth wide-area networks, and remote computers in a highly collaborative problem-solving environment.

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

Zarzycki, Colin M.; Thatcher, Diana R.; Jablonowski, Christiane

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high-resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable-resolution Community Atmosphere Model (CAM) at two different resolutions (DX 55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, DX 38 km), and the ERA-Interim Reanalysis (ERA-I, DX 80 km).more » The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA-I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold-core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.« less

A Storm Surge and Inundation Model of the Back River Watershed at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Loftis, Jon Derek; Wang, Harry V.; DeYoung, Russell J.

2013-01-01

This report on a Virginia Institute for Marine Science project demonstrates that the sub-grid modeling technology (now as part of Chesapeake Bay Inundation Prediction System, CIPS) can incorporate high-resolution Lidar measurements provided by NASA Langley Research Center into the sub-grid model framework to resolve detailed topographic features for use as a hydrological transport model for run-off simulations within NASA Langley and Langley Air Force Base. The rainfall over land accumulates in the ditches/channels resolved via the model sub-grid was tested to simulate the run-off induced by heavy precipitation. Possessing both the capabilities for storm surge and run-off simulations, the CIPS model was then applied to simulate real storm events starting with Hurricane Isabel in 2003. It will be shown that the model can generate highly accurate on-land inundation maps as demonstrated by excellent comparison of the Langley tidal gauge time series data (CAPABLE.larc.nasa.gov) and spatial patterns of real storm wrack line measurements with the model results simulated during Hurricanes Isabel (2003), Irene (2011), and a 2009 Nor'easter. With confidence built upon the model's performance, sea level rise scenarios from the ICCP (International Climate Change Partnership) were also included in the model scenario runs to simulate future inundation cases.

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 Hydrology and Water Management of the San Juan Basin

NASA Astrophysics Data System (ADS)

Rich, P. M.; Weintraub, L. H.; Chen, L.; Herr, J.

2005-12-01

Recent climatic events, including regional drought and increased storm severity, have accentuated concerns that climatic extremes may be increasing in frequency and intensity due to global climate change. As part of the ZeroNet Water-Energy Initiative, the San Juan Decision Support System includes a basin-scale modeling tool to evaluate effects of climate change on water budgets under different climate and management scenarios. The existing Watershed Analysis Risk Management Framework (WARMF) was enhanced with iterative modeling capabilities to enable construction of climate scenarios based on historical and projected data. We applied WARMF to 42,000 km2 (16,000 mi2) of the San Juan Basin (CO, NM) to assess impacts of extended drought and increased temperature on surface water balance. Simulations showed that drought and increased temperature impact water availability for all sectors (agriculture, energy, municipal, industry), and lead to increased frequency of critical shortages. Implementation of potential management alternatives such as "shortage sharing" or degraded water usage during critical years helps improve available water supply. In the face of growing concern over climate change, limited water resources, and competing demands, integrative modeling tools can enable better understanding of complex interconnected systems, and enable better decisions.

GLORIA observations of de-/nitrification during the Arctic winter 2015/16 POLSTRACC campaign

NASA Astrophysics Data System (ADS)

Braun, Marleen; Woiwode, Wolfgang; Höpfner, Michael; Johansson, Sören; Friedl-Vallon, Felix; Oelhaf, Hermann; Preusse, Peter; Ungermann, Jörn; Grooß, Jens-Uwe; Jurkat, Tina; Khosrawi, Farahnaz; Kirner, Ole; Marsing, Andreas; Sinnhuber, Björn-Martin; Voigt, Christiane; Ziereis, Helmut; Orphal, Johannes

2017-04-01

Denitrification, the condensation and sedimentation of HNO3-containing particles in the winter stratosphere at high latitudes, is an important process affecting the deactivation of ozone-depleting halogen species. It modulates the vertical partitioning of chemically active NOy and the vertical redistribution of HNO3 can affect low stratospheric altitudes under sufficiently cold conditions. The capability of associated nitrification to disturb the NOy budget of the climate-relevant lowermost stratosphere (LMS) has hardly been investigated in detail and represents a challenge for model simulations. The Arctic winter 2015/16 was characterized by exceptionally cold stratospheric temperatures and widespread polar stratospheric clouds (PSCs) that were observed from mid-December 2015 until the end of February 2016 down to the LMS. Observations by the GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) spectrometer during the POLSTRACC (Polar Stratosphere in a Changing Climate) aircraft mission allow us to study the development of nitrification of the Arctic LMS during and after the 2015/16 PSC period with high vertical resolution. The vertical cross-sections of HNO3 distribution along the HALO (High Altitude and LOng range research aircraft) flight tracks derived from GLORIA observations show the result of significant vertical redistribution of NOy with strong nitrification of up to 6 ppbv in the LMS. We compare the results of the GLORIA observations with simulations by the state-of-the-art chemical-transport model CLaMS and the climate-chemistry model EMAC and discuss the capability of these models to reproduce nitrification of the Arctic LMS.

Deep Learning @15 Petaflops/second: Semi-supervised pattern detection for 15 Terabytes of climate data

NASA Astrophysics Data System (ADS)

Collins, W. D.; Wehner, M. F.; Prabhat, M.; Kurth, T.; Satish, N.; Mitliagkas, I.; Zhang, J.; Racah, E.; Patwary, M.; Sundaram, N.; Dubey, P.

2017-12-01

Anthropogenically-forced climate changes in the number and character of extreme storms have the potential to significantly impact human and natural systems. Current high-performance computing enables multidecadal simulations with global climate models at resolutions of 25km or finer. Such high-resolution simulations are demonstrably superior in simulating extreme storms such as tropical cyclones than the coarser simulations available in the Coupled Model Intercomparison Project (CMIP5) and provide the capability to more credibly project future changes in extreme storm statistics and properties. The identification and tracking of storms in the voluminous model output is very challenging as it is impractical to manually identify storms due to the enormous size of the datasets, and therefore automated procedures are used. Traditionally, these procedures are based on a multi-variate set of physical conditions based on known properties of the class of storms in question. In recent years, we have successfully demonstrated that Deep Learning produces state of the art results for pattern detection in climate data. We have developed supervised and semi-supervised convolutional architectures for detecting and localizing tropical cyclones, extra-tropical cyclones and atmospheric rivers in simulation data. One of the primary challenges in the applicability of Deep Learning to climate data is in the expensive training phase. Typical networks may take days to converge on 10GB-sized datasets, while the climate science community has ready access to O(10 TB)-O(PB) sized datasets. In this work, we present the most scalable implementation of Deep Learning to date. We successfully scale a unified, semi-supervised convolutional architecture on all of the Cori Phase II supercomputer at NERSC. We use IntelCaffe, MKL and MLSL libraries. We have optimized single node MKL libraries to obtain 1-4 TF on single KNL nodes. We have developed a novel hybrid parameter update strategy to improve scaling to 9600 KNL nodes (600,000 cores). We obtain 15PF performance over the course of the training run; setting a new watermark for the HPC and Deep Learning communities. This talk will share insights on how to obtain this extreme level of performance, current gaps/challenges and implications for the climate science community.

Green roofs'retention performances in different climates

NASA Astrophysics Data System (ADS)

Viola, Francesco; Hellies, Matteo; Deidda, Roberto

2017-04-01

The ongoing process of global urbanization contributes to increasing stormwater runoff from impervious surfaces, threatening also water quality. Green roofs have been proved to be an innovative stormwater management tool to partially restore natural state, enhancing interception, infiltration and evapotranspiration fluxes. The amount of water that is retained within green roofs depends mainly on both soil properties and climate. The evaluation of the retained water is not trivial since it depends on the stochastic soil moisture dynamics. The aim of this work is to explore performances of green roofs, in terms of water retention, as a function of their depth considering different climate regimes. The role of climate in driving water retention has been mainly represented by rainfall and potential evapotranspiration dynamics, which are simulated by a simple conceptual weather generator at daily time scale. The model is able to describe seasonal (in-phase and counter-phase) and stationary behaviors of climatic forcings. Model parameters have been estimated on more than 20,000 historical time series retrieved worldwide. Exemplifying cases are discussed for five different climate scenarios, changing the amplitude and/or the phase of daily mean rainfall and evapotranspiration forcings. The first scenario represents stationary climates, in two other cases the daily mean rainfall or the potential evapotranspiration evolve sinusoidally. In the latter two cases, we simulated the in-phase or in counter-phase conditions. Stochastic forcings have been then used as an input to a simple conceptual hydrological model which simulate soil moisture dynamics, evapotranspiration fluxes, runoff and leakage from soil pack at daily time scale. For several combinations of annual rainfall and potential evapotranspiration, the analysis allowed assessing green roofs' retaining capabilities, at annual time scale. Provided abacus allows a first approximation of possible hydrological benefits deriving from the implementation of intensive or extensive green roofs in different world areas, i.e. less input to sewer systems.

The Description and Validation of a Computationally-Efficient CH4-CO-OH (ECCOH) Module for 3D Model Applications

NASA Technical Reports Server (NTRS)

Elshorbany, Yasin F.; Duncan, Bryan N.; Strode, Sarah A.; Wang, James S.; Kouatchou, Jules

2015-01-01

We present the Efficient CH4-CO-OH Module (ECCOH) that allows for the simulation of the methane, carbon monoxide and hydroxyl radical (CH4-CO-OH cycle, within a chemistry climate model, carbon cycle model, or earth system model. The computational efficiency of the module allows many multi-decadal, sensitivity simulations of the CH4-CO-OH cycle, which primarily determines the global tropospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to relatively long-lived methane and the concomitant impacts on climate. We implemented the ECCOH module into the NASA GEOS-5 Atmospheric Global Circulation Model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over two decades, and evaluated the model output with surface and satellite datasets of methane and CO. The favorable comparison of output from the ECCOH module (as configured in the GEOS-5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.

The Description and Validation of a Computationally-Efficient CH4-CO-OH (ECCOHv1.01) Chemistry Module for 3D Model Applications

NASA Technical Reports Server (NTRS)

Elshorbany, Yasin F.; Duncan, Bryan N.; Strode, Sarah A.; Wang, James S.; Kouatchou, Jules

2016-01-01

We present the Efficient CH4-CO-OH (ECCOH) chemistry module that allows for the simulation of the methane, carbon monoxide, and hydroxyl radical (CH4-CO- OH) system, within a chemistry climate model, carbon cycle model, or Earth system model. The computational efficiency of the module allows many multi-decadal sensitivity simulations of the CH4-CO-OH system, which primarily determines the global atmospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to methane, CO, and OH, and the concomitant impacts on climate. We implemented the ECCOH chemistry module in the NASA GEOS-5 atmospheric global circulation model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over 2 decades, and evaluated the model output with surface and satellite data sets of methane and CO. The favorable comparison of output from the ECCOH chemistry module (as configured in the GEOS- 5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.

Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example

NASA Astrophysics Data System (ADS)

Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R.

2012-12-01

Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.

COSP: Satellite simulation software for model assessment

DOE PAGES

Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...

2011-08-01

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less

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.

Response of Vegetation Dynamics to Projected Climate Change based on NDVI Simulations using Stepwise Cluster Analysis in the Three-River Headwaters Region of China

NASA Astrophysics Data System (ADS)

Zheng, Y.; Lv, E.; Huang, Y.

2016-12-01

Located in the hinterland of the Qinghai-Tibetan Plateau, the Three-River Headwaters region (THR) features unique eco-environmental conditions and fragile ecosystems, and is very vulnerable to climate change. To investigate the effects of climate change on the ecosystem, the Normalized Difference Vegetation Index (NDVI) was employed as an indicator to reflect the vegetation dynamics in response to climate change. This study proposed a model based on Stepwise-cluster analysis to predict the temporal and spatial distributions of NDVI values for five future years according to Global Circulation Models (GCMs) climate projections under the RCP4.5 scenario. The obtained spatial results showed very good agreements between simulations and remote sensing observations of the NDVI value for both training and validation, and the developed model demonstrated its capability of predicting the monthly changes of NDVI through representing the relationships between it and various climatic factors, including remote sensed precipitation and temperature with no, 1 and 2-month lag period. The monthly average precipitation with one-month lag period was further found to be the most important climatic factor that drives the changes of NDVI in the THR. Compared with the values of NDVI in 2000 - 2013, the predicting results indicate the values of NDVI for the THR in growing season (May to October) will decrease by 15.74% in the next 100 years, suggesting that the THR is going to experience an environmental degradation. The results also show that precipitation is the primary driving factor relative to temperature, especially the one-month-lag precipitation. Findings from this study would help policy makers draw up effective water resource and eco-environmental management strategies for adapting to climate change in the THR.

Towards the impact of eddies on the response of the global ocean circulation to Southern Ocean gateway opening

NASA Astrophysics Data System (ADS)

Viebahn, Jan; von der Heydt, Anna S.; Dijkstra, Henk A.

2014-05-01

During the past 65 Million (Ma) years, Earth's climate has undergone a major change from warm 'greenhouse' to colder 'icehouse' conditions with extensive ice sheets in the polar regions of both hemispheres. The Eocene-Oligocene (~34 Ma) and Oligocene-Miocene (~23 Ma) boundaries reflect major transitions in Cenozoic global climate change. Proposed mechanisms of these transitions include reorganization of ocean circulation due to critical gateway opening/deepening, changes in atmospheric CO2-concentration, and feedback mechanisms related to land-ice formation. A long-standing hypothesis is that the formation of the Antarctic Circumpolar Current due to opening/deepening of Southern Ocean gateways led to glaciation of the Antarctic continent. However, while this hypothesis remains controversial, its assessment via coupled climate model simulations depends crucially on the spatial resolution in the ocean component. More precisely, only high-resolution modeling of the turbulent ocean circulation is capable of adequately describing reorganizations in the ocean flow field and related changes in turbulent heat transport. In this study, for the first time results of a high-resolution (0.1° horizontally) realistic global ocean model simulation with a closed Drake Passage are presented. Changes in global ocean temperatures, heat transport, and ocean circulation (e.g., Meridional Overturning Circulation and Antarctic Coastal Current) are established by comparison with an open Drake Passage high-resolution reference simulation. Finally, corresponding low-resolution simulations are also analyzed. The results highlight the essential impact of the ocean eddy field in palaeoclimatic change.

Glacial Inception in north-east Canada: The Role of Topography and Clouds

NASA Astrophysics Data System (ADS)

Birch, Leah; Tziperman, Eli; Cronin, Timothy

2016-04-01

Over the past 0.8 million years, ice ages have dominated Earth's climate on a 100 thousand year cycle. Interglacials were brief, sometimes lasting only a few thousand years, leading to the next inception. Currently, state-of-the-art global climate models (GCMs) are incapable of simulating the transition of Earth's climate from interglacial to glaciated. We hypothesize that this failure may be related to their coarse spatial resolution, which does not allow resolving the topography of inception areas, and their parameterized representation of clouds and atmospheric convection. To better understand the small scale topographic and cloud processes mis-represented by GCMs, we run the Weather Research and Forecasting model (WRF), which is a regional, cloud-resolving atmospheric model capable of a realistic simulation of the regional mountain climate and therefore of surface ice and snow mass balance. We focus our study on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred at 115kya. We examine the sensitivity of mountain glaciers to Milankovitch Forcing, topography, and meteorology, while observing impacts of a cloud resolving model. We first verify WRF's ability to simulate present day climate in the region surrounding the Penny Ice Cap, and then investigate how a GCM-like biased representation of topography affects sensitivity of this mountain glacier to Milankovitch forcing. Our results show the possibility of ice cap growth on an initially snow-free landscape with realistic topography and insolation values from the last glacial inception. Whereas, smoothed topography as seen in GCMs has a negative surface mass balance, even with the relevant orbital parameter configuration. We also explore the surface mass balance feedbacks from an initially ice-covered Baffin Island and discuss the role of clouds and convection.

Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2002-01-01

This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.

Performance optimization for space-based sensors: simulation and modelling at Fraunhofer IOSB

NASA Astrophysics Data System (ADS)

Schweitzer, Caroline; Stein, Karin

2014-10-01

The prediction of the effectiveness of a space-based sensor for its designated application in space (e.g. special earth surface observations or missile detection) can help to reduce the expenses, especially during the phases of mission planning and instrumentation. In order to optimize the performance of such systems we simulate and analyse the entire operational scenario, including: - optional waveband - various orbit heights and viewing angles - system design characteristics, e. g. pixel size and filter transmission - atmospheric effects, e. g. different cloud types, climate zones and seasons In the following, an evaluation of the appropriate infrared (IR) waveband for the designated sensor application is given. The simulation environment is also capable of simulating moving objects like aircraft or missiles. Therefore, the spectral signature of the object/missile as well as its track along a flight path is implemented. The resulting video sequence is then analysed by a tracking algorithm and an estimation of the effectiveness of the sensor system can be simulated. This paper summarizes the work carried out at Fraunhofer IOSB in the field of simulation and modelling for the performance optimization of space based sensors. The paper is structured as follows: First, an overview of the applied simulation and modelling software is given. Then, the capability of those tools is illustrated by means of a hypothetical threat scenario for space-based early warning (launch of a long-range ballistic missile (BM)).

The long-term effects of planting and harvesting on secondary forest dynamics under climate change in northeastern China

PubMed Central

Yao, Jing; He, Xingyuan; He, Hongshi; Chen, Wei; Dai, Limin; Lewis, Bernard J.; Yu, Lizhong

2016-01-01

Unlike the virgin forest in the Changbaishan Nature Reserve in northeastern China, little research on a landscape scale has been conducted on secondary forests in the region under conditions of a warming climate. This research was undertaken in the upper Hun River region where the vegetation is representative of the typical secondary forest of northeastern China. The spatially explicit forest landscape model LANDIS was utilized to simulate the responses of forest restoration dynamics to anthropogenic disturbance (planting and harvesting) and evaluate the difference of the restoration process under continuation of current climatic conditions and climate warming. The results showed that: (1) The interaction of planting and harvesting has organizational scale effects on the forest. The combination of planting and harvesting policies has significant effects on the overall forest but not on individual species. (2) The area expansion of the historically dominant species Pinus koraiensis is less under climate warming than under continuation of current climatic conditions. These suggests that we should carefully take historically dominant species as the main focus for forest restoration, especially when they are near their natural distribution boundary, because they are probably less capable of successfully adapting to climate change. PMID:26725308

The long-term effects of planting and harvesting on secondary forest dynamics under climate change in northeastern China.

PubMed

Yao, Jing; He, Xingyuan; He, Hongshi; Chen, Wei; Dai, Limin; Lewis, Bernard J; Yu, Lizhong

2016-01-04

Unlike the virgin forest in the Changbaishan Nature Reserve in northeastern China, little research on a landscape scale has been conducted on secondary forests in the region under conditions of a warming climate. This research was undertaken in the upper Hun River region where the vegetation is representative of the typical secondary forest of northeastern China. The spatially explicit forest landscape model LANDIS was utilized to simulate the responses of forest restoration dynamics to anthropogenic disturbance (planting and harvesting) and evaluate the difference of the restoration process under continuation of current climatic conditions and climate warming. The results showed that: (1) The interaction of planting and harvesting has organizational scale effects on the forest. The combination of planting and harvesting policies has significant effects on the overall forest but not on individual species. (2) The area expansion of the historically dominant species Pinus koraiensis is less under climate warming than under continuation of current climatic conditions. These suggests that we should carefully take historically dominant species as the main focus for forest restoration, especially when they are near their natural distribution boundary, because they are probably less capable of successfully adapting to climate change.

Prediction of car cabin environment by means of 1D and 3D cabin model

NASA Astrophysics Data System (ADS)

Fišer, J.; Pokorný, J.; Jícha, M.

2012-04-01

Thermal comfort and also reduction of energy requirements of air-conditioning system in vehicle cabins are currently very intensively investigated and up-to-date issues. The article deals with two approaches of modelling of car cabin environment; the first model was created in simulation language Modelica (typical 1D approach without cabin geometry) and the second one was created in specialized software Theseus-FE (3D approach with cabin geometry). Performance and capabilities of this tools are demonstrated on the example of the car cabin and the results from simulations are compared with the results from the real car cabin climate chamber measurements.

Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards

NASA Astrophysics Data System (ADS)

Bermudez, L. E.; Percivall, G.; Idol, T. A.

2015-12-01

Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues. Results of the testbeds will now be deployed in pilot applications. The testbed also identified areas of additional development needed to help identify scientific investments and cyberinfrastructure approaches needed to improve the application of climate science research results to urban climate resilence.

The influence of Cloud Longwave Scattering together with a state-of-the-art Ice Longwave Optical Parameterization in Climate Model Simulations

NASA Astrophysics Data System (ADS)

Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P.

2017-12-01

Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates.

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.

Scenarios of land use change for agriculture: the role of Land Evaluation in improving model simulation

NASA Astrophysics Data System (ADS)

Mereu, V.; Santini, M.; Dettori, G.; Muresu, P.; Spano, D.; Duce, P.

2009-12-01

Integrated scenarios of future climate and land use represent a useful input for impact studies about global changes. In particular, improving future land use simulations is essential for the agricultural sector, which is influenced by both biogeophysical constraints and human needs. Often land use change models are mainly based on statistical relationships between known land use distribution and biophysical or socio-economic factors, neglecting the necessary consideration of physical constraints that interact in making lands more or less capable for agriculture and suitable for supporting specific crops. In this study, a well developed land use change model (CLUE@CMCC) was suited for the Mediterranean basin case study, focusing on croplands. Several climate scenarios and future demands for croplands were combined to drive the model, while the same climate scenarios were used to more reliably allocate crops in the most suitable areas on the basis of Land Evaluation techniques. The probability for each map unit to sustain a specific crop, usually related to location characteristics, elasticity to conversion and competition among land use types, now includes specific crop-favoring location characteristics. Results, besides improving the consistency of the land use change model to allocate land for the future, can have the main feedback to suggest feasibility or reasonable thresholds to adjust land use demands during dynamic simulations.

Reduced ENSO Variability at the LGM Revealed by an Isotope-enabled Earth System Model

NASA Astrophysics Data System (ADS)

Zhu, J.; Liu, Z.; Otto-Bliesner, B. L.; Brady, E. C.; Noone, D.; Zhang, J.; Tomas, R. A.; Jahn, A.; Nusbaumer, J. M.; Wong, T. E.

2016-12-01

El Nino-Southern Oscillation (ENSO) is the most important climate variability at interannual timescale, greatly affecting the weather and climate worldwide. Studying the ENSO at the Last Glacial Maximum (LGM, 21 kyrs before present) can help us better understand its dynamics and improve its projections under anthropogenic global warming. However, both numerical simulations and paleoclimate reconstructions show contradicting results among themselves, e.g., using the Individual Foraminifera Analysis (IFA) approach, some paleo-records suggest an amplified ENSO at the LGM relative to present day; while others indicate a weakened ENSO. These contradictions are hard to explore using traditional climate models due to the indirect nature of model-data comparison: numerical models usually simulate variations in climate state variables (e.g., temperature); while reconstructions can only use proxies (e.g., water isotopes) to infer changes in these state variables. Here we employ the recently developed isotope-enabled Community Earth System Model (iCESM) to study the ENSO strength at the LGM and attempt to provide a consistent picture between climate model and different reconstructions. We find that ENSO at the LGM is about 30% weaker than that of the preindustrial in iCESM, primarily attributable to the weakened atmosphere-ocean coupled feedbacks in a colder climate with a deeper thermocline. With the capability of simulating water isotopes, our model demonstrates that total variance recorded by the IFA water-isotope records in the eastern equatorial Pacific (e.g., Core CD21-30) could actually increase because of an intensified annual cycle, instead of an amplified ENSO. Furthermore, our isotope-enabled simulations suggest that caution should be applied when interpreting the subsurface IFA water-isotope records (e.g., Cores CD38-17P and MD02-2529) due to the wide spread of habitat depth of thermocline-dwelling foraminifera and their possible migration with temporally varying thermocline, which could largely filter out the ENSO signal. Therefore, by realizing these complications, we argue that the weakened ENSO in our model is within the data uncertainty.

Modeling ecohydrological impacts of land management and water use in the Silver Creek basin, Idaho

NASA Astrophysics Data System (ADS)

Loinaz, Maria C.; Gross, Dayna; Unnasch, Robert; Butts, Michael; Bauer-Gottwein, Peter

2014-03-01

A number of anthropogenic stressors, including land use change and intensive water use, have caused stream habitat deterioration in arid and semiarid climates throughout the western U.S. These often contribute to high stream temperatures, a widespread water quality problem. Stream temperature is an important indicator of stream ecosystem health and is affected by catchment-scale climate and hydrological processes, morphology, and riparian vegetation. To properly manage affected systems and achieve ecosystem sustainability, it is important to understand the relative impact of these factors. In this study, we predict relative impacts of different stressors using an integrated catchment-scale ecohydrological model that simulates hydrological processes, stream temperature, and fish growth. This type of model offers a suitable measure of ecosystem services because it provides information about the reproductive capability of fish under different conditions. We applied the model to Silver Creek, Idaho, a stream highly valued for its world-renowned trout fishery. The simulations indicated that intensive water use by agriculture and climate change are both major contributors to habitat degradation in the study area. Agricultural practices that increase water use efficiency and mitigate drainage runoff are feasible and can have positive impacts on the ecosystem. All of the mitigation strategies simulated reduced stream temperatures to varying degrees; however, not all resulted in increases in fish growth. The results indicate that temperature dynamics, rather than point statistics, determine optimal growth conditions for fish. Temperature dynamics are influenced by surface water-groundwater interactions. Combined restoration strategies that can achieve ecosystem stability under climate change should be further explored.

A Novel Approach for Determining Source-Receptor Relationships of Aerosols in Model Simulations

NASA Astrophysics Data System (ADS)

Ma, P.; Gattiker, J.; Liu, X.; Rasch, P. J.

2013-12-01

The climate modeling community usually performs sensitivity studies in the 'one-factor-at-a-time' fashion. However, owing to the a-priori unknown complexity and nonlinearity of the climate system and simulation response, it is computationally expensive to systematically identify the cause-and-effect of multiple factors in climate models. In this study, we use a Gaussian Process emulator, based on a small number of Community Atmosphere Model Version 5.1 (CAM5) simulations (constrained by meteorological reanalyses) using a Latin Hypercube experimental design, to demonstrate that it is possible to characterize model behavior accurately and very efficiently without any modifications to the model itself. We use the emulator to characterize the source-receptor relationships of black carbon (BC), focusing specifically on describing the constituent burden and surface deposition rates from emissions in various regions. Our results show that the emulator is capable of quantifying the contribution of aerosol burden and surface deposition from different source regions, finding that most of current Arctic BC comes from remote sources. We also demonstrate that the sensitivity of the BC burdens to emission perturbations differs for various source regions. For example, the emission growth in Africa where dry convections are strong results in a moderate increase of BC burden over the globe while the same emission growth in the Arctic leads to a significant increase of local BC burdens and surface deposition rates. These results provide insights into the dynamical, physical, and chemical processes of the climate model, and the conclusions may have policy implications for making cost-effective global and regional pollution management strategies.

Space-borne profiling of atmospheric thermodynamic variables with Raman lidar: performance simulations.

PubMed

Di Girolamo, Paolo; Behrendt, Andreas; Wulfmeyer, Volker

2018-04-02

The performance of a space-borne water vapour and temperature lidar exploiting the vibrational and pure rotational Raman techniques in the ultraviolet is simulated. This paper discusses simulations under a variety of environmental and climate scenarios. Simulations demonstrate the capability of Raman lidars deployed on-board low-Earth-orbit satellites to provide global-scale water vapour mixing ratio and temperature measurements in the lower to middle troposphere, with accuracies exceeding most observational requirements for numerical weather prediction (NWP) and climate research applications. These performances are especially attractive for measurements in the low troposphere in order to close the most critical gaps in the current earth observation system. In all climate zones, considering vertical and horizontal resolutions of 200 m and 50 km, respectively, mean water vapour mixing ratio profiling precision from the surface up to an altitude of 4 km is simulated to be 10%, while temperature profiling precision is simulated to be 0.40-0.75 K in the altitude interval up to 15 km. Performances in the presence of clouds are also simulated. Measurements are found to be possible above and below cirrus clouds with an optical thickness of 0.3. This combination of accuracy and vertical resolution cannot be achieved with any other space borne remote sensing technique and will provide a breakthrough in our knowledge of global and regional water and energy cycles, as well as in the quality of short- to medium-range weather forecasts. Besides providing a comprehensive set of simulations, this paper also provides an insight into specific possible technological solutions that are proposed for the implementation of a space-borne Raman lidar system. These solutions refer to technological breakthroughs gained during the last decade in the design and development of specific lidar devices and sub-systems, primarily in high-power, high-efficiency solid-state laser sources, low-weight large aperture telescopes, and high-gain, high-quantum efficiency detectors.

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Model-Relevant Observations and the Beneficiary Modeling Efforts in the Realm of the EVS-2 Project ORACLES

NASA Technical Reports Server (NTRS)

Redemann, Jens

2018-01-01

Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.

Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: an important first step for assessing impact of future climate.

PubMed

Dixit, Prakash N; Telleria, Roberto

2015-04-01

Inter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region. Copyright © 2015 Elsevier B.V. All rights reserved.

Constructing a framework for risk analyses of climate change effects on the water budget of differently sloped vineyards with a numeric simulation using the Monte Carlo method coupled to a water balance model

PubMed Central

Hofmann, Marco; Lux, Robert; Schultz, Hans R.

2014-01-01

Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively, green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over 2 years. The results showed good agreement of modeled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity (SWC) and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in SWC. The improved model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes. PMID:25540646

Southern Ocean Bottom Water Characteristics in CMIP5 Models

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Heywood, Karen; Stevens, David; Ridley, Jeff

2013-04-01

The depiction of Southern Ocean deep water properties and formation processes in climate models is an indicator of their capability to simulate future climate, heat and carbon uptake, and sea level rise. Southern Ocean potential temperature and density averaged over 1986-2005 from fifteen CMIP5 climate models are compared with an observed climatology, focusing on bottom water properties. The mean bottom properties are reasonably accurate for half of the models, but the other half may not yet have approached an equilibrium state. Eleven models create dense water on the Antarctic shelf, but it does not spill off and propagate northwards, alternatively mixing rapidly with less dense water. Instead most models create deep water by open ocean deep convection. Models with large deep convection areas are those with a strong seasonal cycle in sea ice. The most accurate bottom properties occur in models hosting deep convection in the Weddell and Ross gyres.

Abrupt cooling over the North Atlantic in modern climate models

PubMed Central

Sgubin, Giovanni; Swingedouw, Didier; Drijfhout, Sybren; Mary, Yannick; Bennabi, Amine

2017-01-01

Observations over the 20th century evidence no long-term warming in the subpolar North Atlantic (SPG). This region even experienced a rapid cooling around 1970, raising a debate over its potential reoccurrence. Here we assess the risk of future abrupt SPG cooling in 40 climate models from the fifth Coupled Model Intercomparison Project (CMIP5). Contrary to the long-term SPG warming trend evidenced by most of the models, 17.5% of the models (7/40) project a rapid SPG cooling, consistent with a collapse of the local deep-ocean convection. Uncertainty in projections is associated with the models' varying capability in simulating the present-day SPG stratification, whose realistic reproduction appears a necessary condition for the onset of a convection collapse. This event occurs in 45.5% of the 11 models best able to simulate the observed SPG stratification. Thus, due to systematic model biases, the CMIP5 ensemble as a whole underestimates the chance of future abrupt SPG cooling, entailing crucial implications for observation and adaptation policy. PMID:28198383

Modelling the impacts of pests and diseases on agricultural systems.

PubMed

Donatelli, M; Magarey, R D; Bregaglio, S; Willocquet, L; Whish, J P M; Savary, S

2017-07-01

The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.

On requirements for a satellite mission to measure tropical rainfall

NASA Technical Reports Server (NTRS)

Thiele, Otto W. (Editor)

1987-01-01

Tropical rainfall data are crucial in determining the role of tropical latent heating in driving the circulation of the global atmosphere. Also, the data are particularly important for testing the realism of climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the effects of El Nino on climate could be addressed with a reliable, extended time series of tropical rainfall observations. A passive microwave sensor is planned to provide information on the integrated column precipitation content, its areal distribution, and its intensity. An active microwave sensor (radar) will define the layer depth of the precipitation and provide information about the intensity of rain reaching the surface, the key to determining the latent heat input to the atmosphere. A visible/infrared sensor will provide very high resolution information on cloud coverage, type, and top temperatures and also serve as the link between these data and the long and virtually continuous coverage by the geosynchronous meteorological satellites. The unique combination of sensor wavelengths, coverages, and resolving capabilities together with the low-altitude, non-Sun synchronous orbit provide a sampling capability that should yield monthly precipitation amounts to a reasonable accuracy over a 500- by 500-km grid.

On the climate model simulation of Indian monsoon low pressure systems and the effect of remote disturbances and systematic biases

NASA Astrophysics Data System (ADS)

Levine, Richard C.; Martin, Gill M.

2018-06-01

Monsoon low pressure systems (LPS) are synoptic-scale systems forming over the Indian monsoon trough region, contributing substantially to seasonal mean summer monsoon rainfall there. Many current global climate models (GCMs), including the Met Office Unified Model (MetUM), show deficient rainfall in this region, much of which has previously been attributed to remote systematic biases such as excessive equatorial Indian Ocean (EIO) convection, while also substantially under-representing LPS and associated rainfall as they travel westwards across India. Here the sources and sensitivities of LPS to local, remote and short-timescale forcing are examined, in order to understand the poor representation in GCMs. An LPS tracking method is presented using TRACK feature tracking software for comparison between re-analysis data-sets, MetUM GCM and regional climate model (RCM) simulations. RCM simulations, at similar horizontal resolution to the GCM and forced with re-analysis data at the lateral boundaries, are carried out with different domains to examine the effects of remote biases. The results suggest that remote biases contribute significantly to the poor simulation of LPS in the GCM. As these remote systematic biases are common amongst many current GCMs, it is likely that GCMs are intrinsically capable of representing LPS, even at relatively low resolution. The main problem areas are time-mean excessive EIO convection and poor representation of precursor disturbances transmitted from the Western Pacific. The important contribution of the latter is established using RCM simulations forced by climatological 6-hourly lateral boundary conditions, which also highlight the role of LPS in moving rainfall from steep orography towards Central India.

Assessing the capability of high resolution climatic model experiments to simulate Mediterranean cyclonic tracks

NASA Astrophysics Data System (ADS)

Hatzaki, M.; Flocas, H. A.; Giannakopoulos, C.; Kostopoulou, E.; Kouroutzoglou, I.; Keay, K.; Simmonds, I.

2010-09-01

In this study, a comparison of a reanalysis driven simulation to a GCM driven simulation of a regional climate model is performed in order to assess the model's ability to capture the climatic characteristics of cyclonic tracks in the Mediterranean in the present climate. The ultimate scope of the study will be to perform a future climate projection related to cyclonic tracks in order to better understand and assess climate change in the Mediterranean. The climatology of the cyclonic tracks includes inter-monthly variations, classification of tracks according to their origin domain, dynamic and kinematic characteristics, as well as trend analysis. For this purpose, the ENEA model is employed based on PROTHEUS system composed of the RegCM atmospheric regional model and the MITgcm ocean model, coupled through the OASIS3 flux coupler. These model data became available through the EU Project CIRCE which aims to perform, for the first time, climate change projections with a realistic representation of the Mediterranean Sea. Two experiments are employed; a) the ERA402 with lateral Boundary conditions from ERA40 for the 43-year period 1958-2000, and b) the EH5OM_20C3M where the lateral boundary conditions for the atmosphere (1951-2000) are taken from the ECHAM5-MPIOM 20c3m global simulation (run3) included in the IPCC-AR4. The identification and tracking of cyclones is performed with the aid of the Melbourne University algorithm (MS algorithm), according to the Lagrangian perspective. MS algorithm characterizes a cyclone only if a vorticity maximum could be connected with a local pressure minimum. This approach is considered to be crucial, since open lows are also incorporated into the storm life-cycle, preventing possible inappropriate time series breaks, if a temporary weakening to an open-low state occurs. The model experiments verify that considerable inter-monthly variations of track density occur in the Mediterranean region, consistent with previous studies. The classification of the tracks according to their origin domain show that the vast majority originate within the examined area itself. The study of the kinematic and dynamic parameters of tracks according to their origin demonstrate that deeper cyclones follow the SW track. ACKNOWLEDGMENTS: M. Hatzaki would like to thank the Greek State Scholarships Foundation for financial support through the program of postdoctoral research. The support of EU-FP6 project CIRCE Integrated Project-Climate Change and Impact Research: the Mediterranean Environment (http://www.circeproject.eu) for climate model data provision is also greatly acknowledged.

An iceberg model implementation in ACME.

NASA Astrophysics Data System (ADS)

Comeau, D.; Turner, A. K.; Hunke, E. C.

2017-12-01

Icebergs represent approximately half of the mass flux from the Antarctic ice sheet, transporting freshwater and nutrients away from the coast to the Southern Ocean. Icebergs impact the surrounding ocean and sea ice environment, and serve as nutrient sources for biogeochemical activity, yet these processes are typically not resolved in current climate models. We have implemented a parameterization for iceberg drift and decay into the Department of Energy's Accelerated Climate Model for Energy (ACME), where the ocean, sea ice, and land ice components are based on the unstructured grid modeling framework Multiple Prediction Across Scales (MPAS), to improve the representation of Antarctic mass flux to the Southern Ocean and its impacts on ocean stratification and circulation, sea ice, and biogeochemical processes in a fully coupled global climate model. The iceberg model is implemented in two frameworks: Lagrangian and Eulerian. The Lagrangian framework embeds individual icebergs into the ocean and sea ice grids, and will be useful in modeling `giant' (>10 nautical miles) iceberg events, which may have highly localized impacts on ocean and sea ice. The Eulerian framework allows us to model a realistic population of Antarctic icebergs without the computational expense of individual particle tracking to simulate the aggregate impact on the Southern Ocean climate system. This capability, together with under ice-shelf ocean cavities and dynamic ice-shelf fronts, will allow for extremely high fidelity simulation of the southern cryosphere within ACME.

Asphalt pavement aging and temperature dependent properties using functionally graded viscoelastic model

NASA Astrophysics Data System (ADS)

Dave, Eshan V.

Asphalt concrete pavements are inherently graded viscoelastic structures. Oxidative aging of asphalt binder and temperature cycling due to climatic conditions being the major cause of non-homogeneity. Current pavement analysis and simulation procedures dwell on the use of layered approach to account for these non-homogeneities. The conventional finite-element modeling (FEM) technique discretizes the problem domain into smaller elements, each with a unique constitutive property. However the assignment of unique material property description to an element in the FEM approach makes it an unattractive choice for simulation of problems with material non-homogeneities. Specialized elements such as "graded elements" allow for non-homogenous material property definitions within an element. This dissertation describes the development of graded viscoelastic finite element analysis method and its application for analysis of asphalt concrete pavements. Results show that the present research improves efficiency and accuracy of simulations for asphalt pavement systems. Some of the practical implications of this work include the new technique's capability for accurate analysis and design of asphalt pavements and overlay systems and for the determination of pavement performance with varying climatic conditions and amount of in-service age. Other application areas include simulation of functionally graded fiber-reinforced concrete, geotechnical materials, metal and metal composites at high temperatures, polymers, and several other naturally existing and engineered materials.

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.

Basic state lower-tropospheric humidity distribution: key to successful simulation and prediction of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Kim, D.; Ahn, M. S.; DeMott, C. A.; Jiang, X.; Klingaman, N. P.; Kim, H. M.; Lee, J. H.; Lim, Y.; Xavier, P. K.

2017-12-01

The Madden-Julian Oscillation (MJO) influences the global weather-climate system, thereby providing the source of predictability on the intraseasonal timescales worldwide. An accurate representation of the MJO, however, is still one of the most challenging tasks for many contemporary global climate models (GCMs). Identifying aspects of the GCMs that are tightly linked to GCMs' MJO simulation capability is a step toward improving the GCM representation of the MJO. This study surveys recent modeling work that collectively evidence that the horizontal distribution of the basic state low-tropospheric humidity is crucial to a successful simulation and prediction of the MJO. Specifically, the simulated horizontal and meridional gradients of the mean low-tropospheric humidity determine the magnitude of the moistening (drying) to the east (west) of the enhance MJO, thereby enabling or disabling the eastward propagation of the MJO. Supporting this argument, many MJO-incompetent GCMs also exhibit biases in the mean humidity that weaken the horizontal moisture gradient. Also, MJO prediction skill of the S2S models is tightly related to the biases in the mean moisture gradient. Implications of the robust relationship between the MJO and the mean state on MJO modeling and prediction will be discussed.

Simulating the convective precipitation diurnal cycle in a North American scale convection-permitting model

NASA Astrophysics Data System (ADS)

Scaff, L.; Li, Y.; Prein, A. F.; Liu, C.; Rasmussen, R.; Ikeda, K.

2017-12-01

A better representation of the diurnal cycle of convective precipitation is essential for the analysis of the energy balance and the water budget components such as runoff, evaporation and infiltration. Convection-permitting regional climate modeling (CPM) has been shown to improve the models' performance of summer precipitation, allowing to: (1) simulate the mesoscale processes in more detail and (2) to provide more insights in future changes in convective precipitation under climate change. In this work we investigate the skill of the Weather Research and Forecast model (WRF) in simulating the summer precipitation diurnal cycle over most of North America. We use 4 km horizontal grid spacing in a 13-years long current and future period. The future scenario is assuming no significant changes in large-scale weather patterns and aims to answer how the weather of the current climate would change if it would reoccur at the end of the century under a high-end emission scenario (Pseudo Global Warming). We emphasize on a region centered on the lee side of the Canadian Rocky Mountains, where the summer precipitation amount shows a regional maximum. The historical simulations are capable to correctly represent the diurnal cycle. At the lee-side of the Canadian Rockies the increase in the convective available potential energy as well as pronounced low-level moisture flux from the southeast Prairies explains the local maximum in summer precipitation. The PGW scenario shows an increase in summer precipitation amount and intensity in this region, consistently with a stronger source of moisture and convective energy.

Megadroughts in Southwestern North America in ECHO-G Millennial Simulations and Their Comparison to Proxy Drought Reconstructions

NASA Technical Reports Server (NTRS)

Coats, Sloan; Smerdon, Jason E.; Seager, Richard; Cook, Benjamin I.; Gozalez-Rouco, J. F.

2013-01-01

Simulated hydroclimate variability in millennium-length forced transient and control simulations from the ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G) coupled atmosphere-ocean general circulation model (AOGCM) is analyzed and compared to 1000 years of reconstructed Palmer drought severity index (PDSI) variability from the North American Drought Atlas (NADA). The ability of the model to simulate megadroughts in the North American southwest is evaluated. (NASW: 25deg42.5degN, 125deg-105degW). Megadroughts in the ECHO-G AOGCM are found to be similar in duration and magnitude to those estimated from the NADA. The droughts in the forced simulation are not, however, temporally synchronous with those in the paleoclimate record, nor are there significant differences between the drought features simulated in the forced and control runs. These results indicate that model-simulated megadroughts can result from internal variability of the modeled climate system rather than as a response to changes in exogenous forcings. Although the ECHO-G AOGCM is capable of simulating megadroughts through persistent La Nina-like conditions in the tropical Pacific, other mechanisms can produce similarly extreme NASW moisture anomalies in the model. In particular, the lack of low-frequency coherence between NASW soil moisture and simulated modes of climate variability like the El Nino-Southern Oscillation, Pacific decadal oscillation, and Atlantic multidecadal oscillation during identified drought periods suggests that stochastic atmospheric variability can contribute significantly to the occurrence of simulated megadroughts in the NASW. These findings indicate that either an expanded paradigm is needed to understand multidecadal hydroclimate variability in the NASW or AOGCMs may incorrectly simulate the strength and/or dynamics of the connection between NASW hydroclimate variability and the tropical Pacific.

Statistical Compression for Climate Model Output

NASA Astrophysics Data System (ADS)

Hammerling, D.; Guinness, J.; Soh, Y. J.

2017-12-01

Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset-one year of daily mean temperature data-particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers.

Upgrades, Current Capabilities and Near-Term Plans of the NASA ARC Mars Climate

NASA Technical Reports Server (NTRS)

Hollingsworth, J. L.; Kahre, Melinda April; Haberle, Robert M.; Schaeffer, James R.

2012-01-01

We describe and review recent upgrades to the ARC Mars climate modeling framework, in particular, with regards to physical parameterizations (i.e., testing, implementation, modularization and documentation); the current climate modeling capabilities; selected research topics regarding current/past climates; and then, our near-term plans related to the NASA ARC Mars general circulation modeling (GCM) project.

Cloud-Enabled Climate Analytics-as-a-Service using Reanalysis data: A case study.

NASA Astrophysics Data System (ADS)

Nadeau, D.; Duffy, D.; Schnase, J. L.; McInerney, M.; Tamkin, G.; Potter, G. L.; Thompson, J. H.

2014-12-01

The NASA Center for Climate Simulation (NCCS) maintains advanced data capabilities and facilities that allow researchers to access the enormous volume of data generated by weather and climate models. The NASA Climate Model Data Service (CDS) and the NCCS are merging their efforts to provide Climate Analytics-as-a-Service for the comparative study of the major reanalysis projects: ECMWF ERA-Interim, NASA/GMAO MERRA, NOAA/NCEP CFSR, NOAA/ESRL 20CR, JMA JRA25, and JRA55. These reanalyses have been repackaged to netCDF4 file format following the CMIP5 Climate and Forecast (CF) metadata convention prior to be sequenced into the Hadoop Distributed File System ( HDFS ). A small set of operations that represent a common starting point in many analysis workflows was then created: min, max, sum, count, variance and average. In this example, Reanalysis data exploration was performed with the use of Hadoop MapReduce and accessibility was achieved using the Climate Data Service(CDS) application programming interface (API) created at NCCS. This API provides a uniform treatment of large amount of data. In this case study, we have limited our exploration to 2 variables, temperature and precipitation, using 3 operations, min, max and avg and using 30-year of Reanalysis data for 3 regions of the world: global, polar, subtropical.

Land surface models systematically overestimate the intensity, duration and magnitude of seasonal-scale evaporative droughts

DOE PAGES

Ukkola, A. M.; De Kauwe, M. G.; Pitman, A. J.; ...

2016-10-13

Land surface models (LSMs) must accurately simulate observed energy and water fluxes during droughts in order to provide reliable estimates of future water resources. We evaluated 8 different LSMs (14 model versions) for simulating evapotranspiration (ET) during periods of evaporative drought (Edrought) across six flux tower sites. Using an empirically defined Edrought threshold (a decline in ET below the observed 15th percentile), we show that LSMs simulated 58 Edrought days per year, on average, across the six sites, ~3 times as many as the observed 20 d. The simulated Edrought magnitude was ~8 times greater than observed and twice asmore » intense. Our findings point to systematic biases across LSMs when simulating water and energy fluxes under water-stressed conditions. The overestimation of key Edrought characteristics undermines our confidence in the models' capability in simulating realistic drought responses to climate change and has wider implications for phenomena sensitive to soil moisture, including heat waves.« less

Group 1: Scenario design and development issues

NASA Technical Reports Server (NTRS)

Sherwin, P.

1981-01-01

All LOFT scenarios and flight segments should be designed on the basis of a detailed statement of specific objectives. These objectives must state what kind of situation is to be addressed and why. The origin, routing, and destination of a particular scenario should be dictated by the specific objectives for that scenario or leg. Other factors to be considered are the desired weather, climate, etc. Simulator visual system, as well as other capabilities and limitations must be considered at a very early stage of scenario design. The simulator navigation area must be apropriate and must coincide with current Jeppeson charts. Much of the realism of LOFT is destroyed if the crew is unable to use current manuals and other materials.

A New Code SORD for Simulation of Polarized Light Scattering in the Earth Atmosphere

NASA Technical Reports Server (NTRS)

Korkin, Sergey; Lyapustin, Alexei; Sinyuk, Aliaksandr; Holben, Brent

2016-01-01

We report a new publicly available radiative transfer (RT) code for numerical simulation of polarized light scattering in plane-parallel atmosphere of the Earth. Using 44 benchmark tests, we prove high accuracy of the new RT code, SORD (Successive ORDers of scattering). We describe capabilities of SORD and show run time for each test on two different machines. At present, SORD is supposed to work as part of the Aerosol Robotic NETwork (AERONET) inversion algorithm. For natural integration with the AERONET software, SORD is coded in Fortran 90/95. The code is available by email request from the corresponding (first) author or from ftp://climate1.gsfc.nasa.gov/skorkin/SORD/.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

Energy savings modelling of re-tuning energy conservation measures in large office buildings

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

Fernandez, Nick; Katipamula, Srinivas; Wang, Weimin

Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS’s capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This paper investigates the energy savings potential of several common HVAC system re-tuning measures on a typical large office building, using the Department of Energy’s building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy asmore » an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply-air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated – each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All the individual measures and combinations were simulated in 16 climate locations representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual total HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy savings for most cities for all measures). Combining many of the re-tuning measures revealed deep savings potential. Some of the more aggressive combinations revealed 35-75% reductions in annual HVAC energy consumption, depending on climate and building vintage.« less

Observations and simulations of the western United States' hydroclimate

NASA Astrophysics Data System (ADS)

Guirguis, Kristen

While very important from an economical and societal point of view, estimating precipitation in the western United States remains an unsolved and challenging problem. This is due to difficulties in observing and modeling precipitation in complex terrain. This research examines this issue by (i) providing a systematic evaluation of precipitation observations to quantify data uncertainty; and (ii) investigating the ability of the Ocean-Land-Atmosphere Model (OLAM) to simulate the winter hydroclimate in this region. This state-of-the-art, non-hydrostatic model has the capability of simulating simultaneously all scales of motions at various resolutions. This research intercompares nine precipitation datasets commonly used in hydrometeorological research in two ways. First, using principal component analysis, a precipitation climatology is conducted for the western U.S. from which five unique precipitation climates are identified. From this analysis, data uncertainty is shown to be primarily due to differences in (i) precipitation over the Rocky Mountains, (ii) the eastward wet-to-dry precipitation gradient during the cold season, (iii) the North American Monsoon signal, and (iv) precipitation in the desert southwest during spring and summer. The second intercomparison uses these five precipitation regions to provide location-specific assessments of uncertainty, which is shown to be dependent on season, location. Long-range weather forecasts on the order of a season are important for water-scarce regions such as the western U.S. The modeling component of this research looks at the ability of the OLAM to simulate the hydroclimate in the western U.S. during the winter of 1999. Six global simulations are run, each with a different spatial resolution over the western U.S. (360 km down to 11 km). For this study, OLAM is configured as for a long-range seasonal hindcast but with observed sea surface temperatures. OLAM precipitation compares well against observations, and is generally within the range of data uncertainty. Observed and simulated synoptic meteorological conditions are examined during the wettest and driest events. OLAM is shown to reproduce the appropriate anomaly fields, which is encouraging since it demonstrates the capability of a global climate model, driven only by SSTs and initial conditions, to represent meteorological features associated with daily precipitation variability.

Effects of Climate Change and Urban Development on Army Training Capabilities: Firing Ranges and Maneuver Areas

DTIC Science & Technology

2016-08-01

ER D C TR -1 6- 1 Integrated Climate Assessment for Army Enterprise Planning Effects of Climate Change and Urban Development on Army...ERDC TR-16-1 January 2016 Effects of Climate Change and Urban Development on Army Training Capabilities Firing Ranges and Maneuver Areas Michelle E... changes associated with climate and urban development might affect the ability of Army installa- tions to continue to conduct training on firing ranges

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.

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence; Govindaraju, Ravi C.; Atlas, Robert (Technical Monitor)

2002-01-01

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

Changes in climate variability with reference to land quality and agriculture in Scotland.

PubMed

Brown, Iain; Castellazzi, Marie

2015-06-01

Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west-east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.

The Finer Details: Climate Modeling

NASA Technical Reports Server (NTRS)

2000-01-01

If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.

Integrating a Detailed Agricultural Model in a Global Economic Framework: New methods for assessment of climate mitigation and adaptation opportunities

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Izaurralde, R. C.; Calvin, K.; Zhang, X.; Wise, M.; West, T. O.

2010-12-01

Climate change and food security are global issues increasingly linked through human decision making that takes place across all scales from on-farm management actions to international climate negotiations. Understanding how agricultural systems can respond to climate change, through mitigation or adaptation, while still supplying sufficient food to feed a growing global population, thus requires a multi-sector tool in a global economic framework. Integrated assessment models are one such tool, however they are typically driven by historical aggregate statistics of production in combination with exogenous assumptions of future trends in agricultural productivity; they are not yet capable of exploring agricultural management practices as climate adaptation or mitigation strategies. Yet there are agricultural models capable of detailed biophysical modeling of farm management and climate impacts on crop yield, soil erosion and C and greenhouse gas emissions, although these are typically applied at point scales that are incompatible with coarse resolution integrated assessment modeling. To combine the relative strengths of these modeling systems, we are using the agricultural model EPIC (Environmental Policy Integrated Climate), applied in a geographic data framework for regional analyses, to provide input to the global economic model GCAM (Global Change Assessment Model). The initial phase of our approach focuses on a pilot region of the Midwest United States, a highly productive agricultural area. We apply EPIC, a point based biophysical process model, at 60 m spatial resolution within this domain and aggregate the results to GCAM agriculture and land use subregions for the United States. GCAM is then initialized with multiple management options for key food and bioenergy crops. Using EPIC to distinguish these management options based on grain yield, residue yield, soil C change and cost differences, GCAM then simulates the optimum distribution of the available management options to meet demands for food and energy over the next century. The coupled models provide a new platform for evaluating future changes in agricultural management based on food demand, bioenergy demand, and changes in crop yield and soil C under a changing climate. This framework can be applied to evaluate the economically and biophysically optimal distribution of management under future climates.

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Clouds in GEOS-5

NASA Technical Reports Server (NTRS)

Bacmeister, Julio; Rienecker, Michele; Suarez, Max; Norris, Peter

2007-01-01

The GEOS-5 atmospheric model is being developed as a weather-and-climate capable model. It must perform well in assimilation mode as well as in weather and climate simulations and forecasts and in coupled chemistry-climate simulations. In developing GEOS-5, attention has focused on the representation of moist processes. The moist physics package uses a single phase prognostic condensate and a prognostic cloud fraction. Two separate cloud types are distinguished by their source: "anvil" cloud originates in detraining convection, and large-scale cloud originates in a PDF-based condensation calculation. Ice and liquid phases for each cloud type are considered. Once created, condensate and fraction from the anvil and statistical cloud types experience the same loss processes: evaporation of condensate and fraction, auto-conversion of liquid or mixed phase condensate, sedimentation of frozen condensate, and accretion of condensate by falling precipitation. The convective parameterization scheme is the Relaxed Arakawa-Schubert, or RAS, scheme. Satellite data are used to evaluate the performance of the moist physics packages and help in their tuning. In addition, analysis of and comparisons to cloud-resolving models such as the Goddard Cumulus Ensemble model are used to help improve the PDFs used in the moist physics. The presentation will show some of our evaluations including precipitation diagnostics.

Attribution of the Regional Patterns of North American Climate Trends

NASA Astrophysics Data System (ADS)

Hoerling, M.; Kumar, A.; Karoly, D.; Rind, D.; Hegerl, G.; Eischeid, J.

2007-12-01

North American trends in surface temperature and precipitation during 1951-2006 exhibit large spatial and seasonal variations. We seek to explain these by synthesizing new information based on existing model simulations of climate and its forcing, and based on modern reanalyses that describe past and current conditions within the free atmosphere. The presentation focuses on current capabilities to explain the spatial variations and seasonal differences in North American climate trends. It will address whether various heterogeneities in space and time can be accounted for by the climate system's sensitivity to time evolving anthropogenic forcing, and examines the influences of non-anthropogenic processes. New findings are presented that indicate anthropogenic forcing alone was unlikely the cause for key regional and seasonal patterns of change, including the absence of summertime warming over the Great Plains of the United States, and the absence of warming during both winter and summer over the southern United States. Key regional features are instead attributed to trends in the principal patterns of atmospheric flow that affect North American climate. It is demonstrated that observed variations in global sea surface temperatures have significantly influenced these patterns of atmospheric flow.

The Climatology of Extreme Surge-Producing Extratropical Cyclones in Observations and Models

NASA Astrophysics Data System (ADS)

Catalano, A. J.; Broccoli, A. J.; Kapnick, S. B.

2016-12-01

Extreme coastal storms devastate heavily populated areas around the world by producing powerful winds that can create a large storm surge. Both tropical and extratropical cyclones (ETCs) occur over the northwestern Atlantic Ocean, and the risks associated with ETCs can be just as severe as those associated with tropical storms (e.g. high winds, storm surge). At The Battery in New York City, 17 of the 20 largest storm surge events were a consequence of extratropical cyclones (ETCs), which are more prevalent than tropical cyclones in the northeast region of the United States. Therefore, we analyze the climatology of ETCs that are capable of producing a large storm surge along the northeastern coast of the United States. For a historical analysis, water level data was collected from National Oceanic and Atmospheric Administration (NOAA) tide gauges at three separate locations (Sewell's Pt., VA, The Battery, NY, and Boston, MA). We perform a k-means cluster analysis of sea level pressure from the ECMWF 20th Century Reanalysis dataset (ERA-20c) to explore the natural sets of observed storms with similar characteristics. We then composite cluster results with features of atmospheric circulation to observe the influence of interannual and multidecadal variability such as the North Atlantic Oscillation. Since observational records contain a small number of well-documented ETCs, the capability of a high-resolution coupled climate model to realistically simulate such extreme coastal storms will also be assessed. Global climate models provide a means of simulating a much larger sample of extreme events, allowing for better resolution of the tail of the distribution. We employ a tracking algorithm to identify ETCs in a multi-century simulation under present-day conditions. Quantitative comparisons of cyclolysis, cyclogenesis, and cyclone densities of simulated ETCs and storms from recent history (using reanalysis products) are conducted.

QBO Influence on Polar Stratospheric Variability in the GEOS Chemistry-Climate Model

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Oman, L. D.; Li, F.; Slong, I.-S.; Newman, P. A.; Nielsen, J. E.

2010-01-01

The quasi-biennial oscillation modulates the strength of both the Arctic and Antarctic stratospheric vortices. Model and observational studies have found that the phase and characteristics of the quasi-biennial oscillation (QBO) contribute to the high degree of variability in the Arctic stratosphere in winter. While the Antarctic stratosphere is less variable, recent work has shown that Southern Hemisphere planetary wave driving increases in response to "warm pool" El Nino events that are coincident with the easterly phase of the QBO. These events hasten the breakup of the Antarctic polar vortex. The Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) is now capable of generating a realistic QBO, due a new parameterization of gravity wave drag. In this presentation, we will use this new model capability to assess the influence of the QBO on polar stratospheric variability. Using simulations of the recent past, we will compare the modeled relationship between QBO phase and mid-winter vortex strength with the observed Holton-Tan relation, in both hemispheres. We will use simulations of the 21 St century to estimate future trends in the relationship between QBO phase and vortex strength. In addition, we will evaluate the combined influence of the QBO and El Nino/Southern Oscillation (ENSO) on the timing of the breakup of the polar stratospheric vortices in the GEOS CCM. We will compare the influence of these two natural phenomena with trends in the vortex breakup associated with ozone recovery and increasing greenhouse gas concentrations.

Challenge toward the prediction of typhoon behaviour and down pour

NASA Astrophysics Data System (ADS)

Takahashi, K.; Onishi, R.; Baba, Y.; Kida, S.; Matsuda, K.; Goto, K.; Fuchigami, H.

2013-08-01

Mechanisms of interactions among different scale phenomena play important roles for forecasting of weather and climate. Multi-scale Simulator for the Geoenvironment (MSSG), which deals with multi-scale multi-physics phenomena, is a coupled non-hydrostatic atmosphere-ocean model designed to be run efficiently on the Earth Simulator. We present simulation results with the world-highest 1.9km horizontal resolution for the entire globe and regional heavy rain with 1km horizontal resolution and 5m horizontal/vertical resolution for urban area simulation. To gain high performance by exploiting the system capabilities, we propose novel performance evaluation metrics introduced in previous studies that incorporate the effects of the data caching mechanism between CPU and memory. With a useful code optimization guideline based on such metrics, we demonstrate that MSSG can achieve an excellent peak performance ratio of 32.2% on the Earth Simulator with the single-core performance found to be a key to a reduced time-to-solution.

Impacts of Mt Pinatubo volcanic aerosol on the tropical stratosphere in chemistry-climate model simulations using CCMI and CMIP6 stratospheric aerosol data

NASA Astrophysics Data System (ADS)

Revell, Laura E.; Stenke, Andrea; Luo, Beiping; Kremser, Stefanie; Rozanov, Eugene; Sukhodolov, Timofei; Peter, Thomas

2017-11-01

To simulate the impacts of volcanic eruptions on the stratosphere, chemistry-climate models that do not include an online aerosol module require temporally and spatially resolved aerosol size parameters for heterogeneous chemistry and aerosol radiative properties as a function of wavelength. For phase 1 of the Chemistry-Climate Model Initiative (CCMI-1) and, later, for phase 6 of the Coupled Model Intercomparison Project (CMIP6) two such stratospheric aerosol data sets were compiled, whose functional capability and representativeness are compared here. For CCMI-1, the SAGE-4λ data set was compiled, which hinges on the measurements at four wavelengths of the SAGE (Stratospheric Aerosol and Gas Experiment) II satellite instrument and uses ground-based lidar measurements for gap-filling immediately after the 1991 Mt Pinatubo eruption, when the stratosphere was too optically opaque for SAGE II. For CMIP6, the new SAGE-3λ data set was compiled, which excludes the least reliable SAGE II wavelength and uses measurements from CLAES (Cryogenic Limb Array Etalon Spectrometer) on UARS, the Upper Atmosphere Research Satellite, for gap-filling following the Mt Pinatubo eruption instead of ground-based lidars. Here, we performed SOCOLv3 (Solar Climate Ozone Links version 3) chemistry-climate model simulations of the recent past (1986-2005) to investigate the impact of the Mt Pinatubo eruption in 1991 on stratospheric temperature and ozone and how this response differs depending on which aerosol data set is applied. The use of SAGE-4λ results in heating and ozone loss being overestimated in the tropical lower stratosphere compared to observations in the post-eruption period by approximately 3 K and 0.2 ppmv, respectively. However, less heating occurs in the model simulations based on SAGE-3λ, because the improved gap-filling procedures after the eruption lead to less aerosol loading in the tropical lower stratosphere. As a result, simulated tropical temperature anomalies in the model simulations based on SAGE-3λ for CMIP6 are in excellent agreement with MERRA and ERA-Interim reanalyses in the post-eruption period. Less heating in the simulations with SAGE-3λ means that the rate of tropical upwelling does not strengthen as much as it does in the simulations with SAGE-4λ, which limits dynamical uplift of ozone and therefore provides more time for ozone to accumulate in tropical mid-stratospheric air. Ozone loss following the Mt Pinatubo eruption is overestimated by up to 0.1 ppmv in the model simulations based on SAGE-3λ, which is a better agreement with observations than in the simulations based on SAGE-4λ. Overall, the CMIP6 stratospheric aerosol data set, SAGE-3λ, allows SOCOLv3 to more accurately simulate the post-Pinatubo eruption period.

East Asia winter climate changes under RCP scenarios in terms of East Asian winter monsoon indices

NASA Astrophysics Data System (ADS)

Ahn, J. B.; Hong, J. Y.

2016-12-01

The changes in the winter climatology and variability of the East Asian winter monsoon (EAWM) for the late 21st century (2070-2099) under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios are projected in terms of EAWM indices (EAWMIs). Firstly, the capability of the climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulating the boreal winter climatology and the interannual variability of the EAWM for the late 20th century (1971-2000) is examined. Nine of twenty-three climate models are selected based on the pattern correlations with observation and a multi-model ensemble is applied to the nine model data. Three of twelve EAWMIs that show the most significant temporal correlations between the observation and CMIP5 surface air temperatures are utilized. The ensemble CMIP5 is capable of reproducing the overall features of the EAWM in spite of some biases in the region. The negative correlations between the EAWMIs and boreal winter temperature are well reproduced and 3-5 years of the major interannual variation observed in this region are also well simulated according to power spectral analyses of the simulated indices. The regressed fields of sea level pressure, surface air temperature, 500-hPa geopotential height, and 300-hPa zonal wind are well established with pattern correlations above 0.83 between CMIP5 and observation data. The differences between RCPs and Historical indicate strong warming, which increases with latitude, ranging from 1°C to 5°C under RCP4.5 and from 3°C to 7°C under RCP8.5 in the East Asian region. The anomalous southerly winds generally become stronger, implying weaker EAWMs in both scenarios. These features are also identified with fields regressed onto the indices in RCPs. The future projections reveal that the interannual variability of the indices will be maintained with intensity similar to that of the present. AcknowledgmentsThis work was carried out with the support of "Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ012293)" Rural Development Administration, Republic of Korea.

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2015-04-01

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

The Simulated Impact of Dimethyl Sulfide Emissions on the Earth System

NASA Astrophysics Data System (ADS)

Cameron-Smith, P. J.; Elliott, S.; Shrivastava, M. B.; Burrows, S. M.; Maltrud, M. E.; Lucas, D. D.; Ghan, S.

2015-12-01

Dimethyl sulfide (DMS) is one of many biologically derived gases and particles emitted from the ocean that has the potential to affect climate. In the case of DMS it is oxidized to sulfate, which increases the aerosol loading in the atmosphere either through nucleation or condensation on other aerosols, which in turn changes the energy balance of the Earth by reflection of sunlight either through direct reflection by the aerosols or by modifying clouds. We have previously shown that the geographical distribution of DMS emission from the ocean may be quite sensitive to climate changes, especially in the Southern Ocean. Our state-of-the-art sulfur-cycle Earth system model (ESM), based on the Community Earth System Model (CESM) climate model, includes an ocean sulfur ecosystem model, the oxidation of DMS to sulfate by atmospheric chemistry, and the indirect effect of sulfate on radiation via clouds using the Modal Aerosol Model (MAM). Our multi-decadal simulations calculate the impact of DMS on the energy balance and climate of the Earth system, and its sensitivity/feedback to climate change. The estimate from our simulations is that DMS is responsible for ~6 W/m2 of reflected sunlight in the pre-industrial era (globally averaged), and ~4 W/m2 in the present era. The reduction is caused by increased competition with cloud condensation nuclei from anthropogenic aerosols in the present era, and therefore partially offsets the cooling from the anthropogenic aerosols. The distribution of these effects are not uniform, and doesn't necessarily follow the simulated DMS distribution, because some clouds are more sensitive to DMS derived sulfate than others, and there are surface feedbacks such as the ice-albedo feedback. Although our calculated impact of DMS is higher than some previous studies, it is not much higher than recent observational estimates (McCoy, et al., 2015). We are now porting these capabilities to the US Department of Energy's Accelerated Climate Modeling for Energy (ACME) model. This work was conducted by the ACME and SciDAC programs of the Office of Biological and Environmental Research and the Office of Advanced Scientific Computing Research of the U.S. Department of Energy. Prepared by LLNL under Contract DE-AC52-07NA27344.

Potential impact of global climate change on malaria risk

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

Martens, W.J.M.; Rotmans, J.; Niessen, L.W.

The biological activity and geographic distribution of the malarial parasite and its vector are sensitive to climatic influences, especially temperature and precipitation. We have incorporated General Circulation Model-based scenarios of anthropogenic global climate change in an integrated linked-system model for predicting changes in malaria epidemic potential in the next century. The concept of the disability-adjusted life years is included to arrive at a single measure of the effect of anthropogenic climate change on the health impact of malaria. Assessment of the potential impact of global climate change on the incidence of malaria suggests a widespread increase of risk due tomore » expansion of the areas suitable for malaria transmission. This predicted increase is most pronounced at the borders of endemic malaria areas and at higher altitudes within malarial areas. The incidence of infection is sensitive to climate changes in areas of Southeast Asia, South America, and parts of Africa where the disease is less endemic; in these regions the numbers of years of healthy life lost may increase significantly. However, the simulated changes in malaria risk must be interpreted on the basis of local environmental conditions, the effects of socioeconomic developments, and malaria control programs or capabilities. 33 refs., 5 figs., 1 tab.« less

A Novel Approach for Determining Source–Receptor Relationships in Model Simulations: A Case Study of Black Carbon Transport in Northern Hemisphere Winter

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

Ma, Po-Lun; Gattiker, J. R.; Liu, Xiaohong

2013-06-27

A Gaussian process (GP) emulator is applied to quantify the contribution of local and remote emissions of black carbon (BC) on the BC concentrations in different regions using a Latin Hypercube sampling strategy for emission perturbations in the offline version of the Community Atmosphere Model Version 5.1 (CAM5) simulations. The source-receptor relationships are computed based on simulations constrained by a standard free-running CAM5 simulation and the ERA-Interim reanalysis product. The analysis demonstrates that the emulator is capable of retrieving the source-receptor relationships based on a small number of CAM5 simulations. Most regions are found susceptible to their local emissions. Themore » emulator also finds that the source-receptor relationships retrieved from the model-driven and the reanalysis-driven simulations are very similar, suggesting that the simulated circulation in CAM5 resembles the assimilated meteorology in ERA-Interim. The robustness of the results provides confidence for applying the emulator to detect dose-response signals in the climate system.« less

Evolution of Software-Only-Simulation at NASA IV and V

NASA Technical Reports Server (NTRS)

McCarty, Justin; Morris, Justin; Zemerick, Scott

2014-01-01

Software-Only-Simulations have been an emerging but quickly developing field of study throughout NASA. The NASA Independent Verification Validation (IVV) Independent Test Capability (ITC) team has been rapidly building a collection of simulators for a wide range of NASA missions. ITC specializes in full end-to-end simulations that enable developers, VV personnel, and operators to test-as-you-fly. In four years, the team has delivered a wide variety of spacecraft simulations that have ranged from low complexity science missions such as the Global Precipitation Management (GPM) satellite and the Deep Space Climate Observatory (DSCOVR), to the extremely complex missions such as the James Webb Space Telescope (JWST) and Space Launch System (SLS).This paper describes the evolution of ITCs technologies and processes that have been utilized to design, implement, and deploy end-to-end simulation environments for various NASA missions. A comparison of mission simulators are discussed with focus on technology and lessons learned in complexity, hardware modeling, and continuous integration. The paper also describes the methods for executing the missions unmodified flight software binaries (not cross-compiled) for verification and validation activities.

Aerosol microphysics simulations of the Mt. Pinatubo eruption with the UKCA composition-climate model

NASA Astrophysics Data System (ADS)

Dhomse, S. S.; Emmerson, K. M.; Mann, G. W.; Bellouin, N.; Carslaw, K. S.; Chipperfield, M. P.; Hommel, R.; Abraham, N. L.; Telford, P.; Braesicke, P.; Dalvi, M.; Johnson, C. E.; O'Connor, F.; Morgenstern, O.; Pyle, J. A.; Deshler, T.; Zawodny, J. M.; Thomason, L. W.

2014-01-01

We have enhanced the capability of a microphysical aerosol-chemistry module to simulate the atmospheric aerosol and precursor gases for both tropospheric and stratospheric conditions. Using the Mount Pinatubo eruption (June 1991) as a test case, we evaluate simulated aerosol properties in a composition-climate model against a range of satellite and in-situ observations. Simulations are performed assuming an injection of 20 Tg SO2 at 19-27 km in tropical latitudes, without any radiative feedback from the simulated aerosol. In both quiescent and volcanically perturbed conditions, simulated aerosol properties in the lower stratosphere show reasonable agreement with the observations. The model captures the observed timing of the maximum aerosol optical depth (AOD) and its decay timescale in both tropics and Northern Hemisphere (NH) mid-latitudes. There is also good qualitative agreement with the observations in terms of spatial and temporal variation of the aerosol effective radius (Reff), which peaks 6-8 months after the eruption. However, the model shows significant biases against some observational data sets. Simulated AOD and Surface Area Density (SAD) in the tropics are substantially higher than the gap-filled satellite data products during the first 6 months after the eruption. The model shows consistently weaker enhancement in Reff compared to satellite and in-situ measurements. Simulated aerosol particle size distribution is also compared to NH mid-latitude in-situ balloon sounding measurements of size-resolved number concentrations. Before the eruption, the model captures the observed profiles of lower stratospheric particle number concentrations with radii larger than 5, 150 and 250 nm (N5, N150 and N250) very well. However, in the first 6 months after the eruption, the model shows high bias in N5 concentrations in the lower stratosphere, suggesting too strong nucleation. Following particle growth via condensation and coagulation, this bias in the finest particles propagates into a factor 2 high bias in N150. Our comparison suggests that new particle formation in the initial phase of large eruptions, and subsequent particle growth to optically-active sizes, might be playing an important role in determining the magnitude of the climate impacts from volcanoes like Pinatubo.

Dynamical malaria models reveal how immunity buffers effect of climate variability.

PubMed

Laneri, Karina; Paul, Richard E; Tall, Adama; Faye, Joseph; Diene-Sarr, Fatoumata; Sokhna, Cheikh; Trape, Jean-François; Rodó, Xavier

2015-07-14

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human-mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity.

Improvements in the Scalability of the NASA Goddard Multiscale Modeling Framework for Hurricane Climate Studies

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Chern, Jiun-Dar

2007-01-01

Improving our understanding of hurricane inter-annual variability and the impact of climate change (e.g., doubling CO2 and/or global warming) on hurricanes brings both scientific and computational challenges to researchers. As hurricane dynamics involves multiscale interactions among synoptic-scale flows, mesoscale vortices, and small-scale cloud motions, an ideal numerical model suitable for hurricane studies should demonstrate its capabilities in simulating these interactions. The newly-developed multiscale modeling framework (MMF, Tao et al., 2007) and the substantial computing power by the NASA Columbia supercomputer show promise in pursuing the related studies, as the MMF inherits the advantages of two NASA state-of-the-art modeling components: the GEOS4/fvGCM and 2D GCEs. This article focuses on the computational issues and proposes a revised methodology to improve the MMF's performance and scalability. It is shown that this prototype implementation enables 12-fold performance improvements with 364 CPUs, thereby making it more feasible to study hurricane climate.

European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling

PubMed Central

Bastos, Ana; Janssens, Ivan A.; Gouveia, Célia M.; Trigo, Ricardo M.; Ciais, Philippe; Chevallier, Frédéric; Peñuelas, Josep; Rödenbeck, Christian; Piao, Shilong; Friedlingstein, Pierre; Running, Steven W.

2016-01-01

Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO–EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models. PMID:26777730

European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling.

PubMed

Bastos, Ana; Janssens, Ivan A; Gouveia, Célia M; Trigo, Ricardo M; Ciais, Philippe; Chevallier, Frédéric; Peñuelas, Josep; Rödenbeck, Christian; Piao, Shilong; Friedlingstein, Pierre; Running, Steven W

2016-01-18

Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO-EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models.

Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Levermann, Anders

2017-07-01

Projections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300 % over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic-thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.

Impacts of Future Climate and Emission Changes on U.S. Air Quality

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

Penrod, Ashley; Zhang, Yang; Wang, K.

2014-06-01

Changes in climate and emissions will affect future air quality. In this work, simulations of present (2001-2005) and future (2026-2030) regional air quality are conducted with the newly released CMAQ version 5.0 to examine the individual and combined impacts of simulated future climate and anthropogenic emission projections on air quality over the U.S. Current (2001-2005) meteorological and chemical predictions are evaluated against observational data to assess the model’s capability in reproducing the seasonal differences. Overall, WRF and CMAQ perform reasonably well. Increased temperatures (up to 3.18 °C) and decreased ventilation (up to 157 m in planetary boundary layer height) aremore » found in both future winter and summer, with more prominent changes in winter. Increases in future temperatures result in increased isoprene and terpene emissions in winter and summer, driving the increase in maximum 8-h average O3 (up to 5.0 ppb) over the eastern U.S. in winter while decreases in NOx emissions drive the decrease in O3 over most of the U.S. in summer. Future concentrations of PM2.5 in winter and summer and many of its components including organic matter in winter, ammonium and nitrate in summer, and sulfate in winter and summer, decrease due to decreases in primary anthropogenic emissions and the concentrations of secondary anthropogenic pollutants and increased precipitation in winter. Future winter and summer dry and wet deposition fluxes are spatially variable and increase with increasing surface resistance and precipitation (e.g., NH4+ and NO3- dry and wet deposition fluxes increase in winter over much of the U.S.), respectively, and decrease with a decrease in ambient particulate concentrations (e.g., SO42- dry and wet deposition fluxes decrease over the eastern U.S. in summer and winter). Sensitivity simulations show that anthropogenic emission projections dominate over changes in climate in their impacts on the U.S. air quality in the near future. Changes in some regions/species, however, are dominated by climate and/or both climate and anthropogenic emissions, especially in future years that are marked by meteorological conditions conducive to poor air quality.« less

A new code SORD for simulation of polarized light scattering in the Earth atmosphere

NASA Astrophysics Data System (ADS)

Korkin, Sergey; Lyapustin, Alexei; Sinyuk, Aliaksandr; Holben, Brent

2016-05-01

We report a new publicly available radiative transfer (RT) code for numerical simulation of polarized light scattering in plane-parallel Earth atmosphere. Using 44 benchmark tests, we prove high accuracy of the new RT code, SORD (Successive ORDers of scattering1, 2). We describe capabilities of SORD and show run time for each test on two different machines. At present, SORD is supposed to work as part of the Aerosol Robotic NETwork3 (AERONET) inversion algorithm. For natural integration with the AERONET software, SORD is coded in Fortran 90/95. The code is available by email request from the corresponding (first) author or from ftp://climate1.gsfc.nasa.gov/skorkin/SORD/ or ftp://maiac.gsfc.nasa.gov/pub/SORD.zip

Abiotic/biotic coupling in the rhizosphere: a reactive transport modeling analysis

USGS Publications Warehouse

Lawrence, Corey R.; Steefel, Carl; Maher, Kate

2014-01-01

A new generation of models is needed to adequately simulate patterns of soil biogeochemical cycling in response changing global environmental drivers. For example, predicting the influence of climate change on soil organic matter storage and stability requires models capable of addressing complex biotic/abiotic interactions of rhizosphere and weathering processes. Reactive transport modeling provides a powerful framework simulating these interactions and the resulting influence on soil physical and chemical characteristics. Incorporation of organic reactions in an existing reactive transport model framework has yielded novel insights into soil weathering and development but much more work is required to adequately capture root and microbial dynamics in the rhizosphere. This endeavor provides many advantages over traditional soil biogeochemical models but also many challenges.

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Modeling Primary Atomization of Liquid Fuels using a Multiphase DNS/LES Approach

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

Arienti, Marco; Oefelein, Joe; Doisneau, Francois

2016-08-01

As part of a Laboratory Directed Research and Development project, we are developing a modeling-and-simulation capability to study fuel direct injection in automotive engines. Predicting mixing and combustion at realistic conditions remains a challenging objective of energy science. And it is a research priority in Sandia’s mission-critical area of energy security, being also relevant to many flows in defense and climate. High-performance computing applied to this non-linear multi-scale problem is key to engine calculations with increased scientific reliability.

Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099 *

USGS Publications Warehouse

Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.

2004-01-01

Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5??C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.

Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900-2099

NASA Astrophysics Data System (ADS)

Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.

2001-12-01

Sensitivities of river basins in the Sierra Nevada of California to historical and future climate variations and changes are analyzed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-year period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th Century until about 1975, when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st Century with an attendant +2.5ºC warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. In contrast, a control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995, yields climate and streamflow-timing conditions much like the 1980s and 1990s throughout its duration. Long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. The various projected trends in the business-as-usual simulations become readily visible above simulated natural climatic and hydrologic variability by about 2020.

Data Serving Climate Simulation Science at the NASA Center for Climate Simulation

NASA Technical Reports Server (NTRS)

Salmon, Ellen M.

2011-01-01

The NASA Center for Climate Simulation (NCCS) provides high performance computational resources, a multi-petabyte archive, and data services in support of climate simulation research and other NASA-sponsored science. This talk describes the NCCS's data-centric architecture and processing, which are evolving in anticipation of researchers' growing requirements for higher resolution simulations and increased data sharing among NCCS users and the external science community.

Evaluation of regional climate simulations over the Great Lakes region driven by three global data sets

Treesearch

Shiyuan Zhong; Xiuping Li; Xindi Bian; Warren E. Heilman; L. Ruby Leung; William I. Jr. Gustafson

2012-01-01

The performance of regional climate simulations is evaluated for the Great Lakes region. Three 10-year (1990-1999) current-climate simulations are performed using the MM5 regional climate model (RCM) with 36-km horizontal resolution. The simulations employed identical configuration and physical parameterizations, but different lateral boundary conditions and sea-...

Can quantile mapping improve precipitation extremes from regional climate models?

NASA Astrophysics Data System (ADS)

Tani, Satyanarayana; Gobiet, Andreas

2015-04-01

The ability of quantile mapping to accurately bias correct regard to precipitation extremes is investigated in this study. We developed new methods by extending standard quantile mapping (QMα) to improve the quality of bias corrected extreme precipitation events as simulated by regional climate model (RCM) output. The new QM version (QMβ) was developed by combining parametric and nonparametric bias correction methods. The new nonparametric method is tested with and without a controlling shape parameter (Qmβ1 and Qmβ0, respectively). Bias corrections are applied on hindcast simulations for a small ensemble of RCMs at six different locations over Europe. We examined the quality of the extremes through split sample and cross validation approaches of these three bias correction methods. This split-sample approach mimics the application to future climate scenarios. A cross validation framework with particular focus on new extremes was developed. Error characteristics, q-q plots and Mean Absolute Error (MAEx) skill scores are used for evaluation. We demonstrate the unstable behaviour of correction function at higher quantiles with QMα, whereas the correction functions with for QMβ0 and QMβ1 are smoother, with QMβ1 providing the most reasonable correction values. The result from q-q plots demonstrates that, all bias correction methods are capable of producing new extremes but QMβ1 reproduces new extremes with low biases in all seasons compared to QMα, QMβ0. Our results clearly demonstrate the inherent limitations of empirical bias correction methods employed for extremes, particularly new extremes, and our findings reveals that the new bias correction method (Qmß1) produces more reliable climate scenarios for new extremes. These findings present a methodology that can better capture future extreme precipitation events, which is necessary to improve regional climate change impact studies.

Land Use, climate change and BIOdiversity in cultural landscapes (LUBIO): Assessing feedbacks and promoting land-use strategies towards a viable future

NASA Astrophysics Data System (ADS)

Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander

2016-04-01

Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.

Continuously on-going hindcast simulations for impact applications

NASA Astrophysics Data System (ADS)

Anders, Ivonne; Geyer, Beate

2016-04-01

Observations for e.g. temperature, precipitation, radiation, or wind are often used as meteorological forcing for different impact models, like e.g. crop models, urban models, economic models and energy system models. To assess a climate signal, the time period covered by the observation is often too short, they have gaps in between, and are inhomogeneous over time, due to changes in the measurements itself or in the near surrounding. Thus output from global and regional climate models can close the gap and provide homogeneous and physically consistent time series of meteorological parameters. CORDEX evaluation runs performed for the IPCC-AR5 provide a good base for the regional scale. However, with respect to climate services, continuously on-going hindcast simulations are required for regularly updated applications. In this study two projects are presented where hindcast-simulations optimized for a region of interest are performed continuously. The hindcast simulation performed by HZG covering Europe includes the EURO-CORDEX domain with a wider extend to the north to cover the ice edge. The simulation under consideration of the coastDat-experiences is available for the period of 1979 - 2015, prolonged ongoing and fulfills the customer's needs with respect of output variables, levels, intervals and statistical measures. CoastDat - customers are dealing e.g. with naval architecture, renewable energies, offshore wind farming, shipping emissions, coastal flood risk and others. The evaluation of the hindcast is done for Europe by using the EVAL-tool of the CCLM community and by comparison with HYRAS - data for Germany and neighbouring countries. The Climate Research group at the national Austrian weather service, ZAMG, is focusing on high mountain regions and, especially on the Alps. The hindcast-simulation is forced by ERA-interim and optimized for the Alpine Region. One of the main tasks is to capture strong precipitation events which often occur during summer when low pressure systems develop over the Golf of Genoa, moving to the North-East. This leads to floods and landslide events in Austria, Czech Republic and Germany. Such events are not sufficiently represented in the CORDEX-evaluation runs. ZAMG use high quality gridded precipitation and temperature data for the Alpine Region (1-6km) to evaluate the model performance. Data is provided e.g. to hydrological modellers (high water, low water), but also to assess icing capability of infrastructure.

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

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.

Virtual Earth System Laboratory (VESL): Effective Visualization of Earth System Data and Process Simulations

NASA Astrophysics Data System (ADS)

Quinn, J. D.; Larour, E. Y.; Cheng, D. L. C.; Halkides, D. J.

2016-12-01

The Virtual Earth System Laboratory (VESL) is a Web-based tool, under development at the Jet Propulsion Laboratory and UC Irvine, for the visualization of Earth System data and process simulations. It contains features geared toward a range of applications, spanning research and outreach. It offers an intuitive user interface, in which model inputs are changed using sliders and other interactive components. Current capabilities include simulation of polar ice sheet responses to climate forcing, based on NASA's Ice Sheet System Model (ISSM). We believe that the visualization of data is most effective when tailored to the target audience, and that many of the best practices for modern Web design/development can be applied directly to the visualization of data: use of negative space, color schemes, typography, accessibility standards, tooltips, etc cetera. We present our prototype website, and invite input from potential users, including researchers, educators, and students.

Extending the Community Multiscale Air Quality (CMAQ) Modeling System to Hemispheric Scales: Overview of Process Considerations and Initial Applications

PubMed Central

Mathur, Rohit; Xing, Jia; Gilliam, Robert; Sarwar, Golam; Hogrefe, Christian; Pleim, Jonathan; Pouliot, George; Roselle, Shawn; Spero, Tanya L.; Wong, David C.; Young, Jeffrey

2018-01-01

The Community Multiscale Air Quality (CMAQ) modeling system is extended to simulate ozone, particulate matter, and related precursor distributions throughout the Northern Hemisphere. Modelled processes were examined and enhanced to suitably represent the extended space and time scales for such applications. Hemispheric scale simulations with CMAQ and the Weather Research and Forecasting (WRF) model are performed for multiple years. Model capabilities for a range of applications including episodic long-range pollutant transport, long-term trends in air pollution across the Northern Hemisphere, and air pollution-climate interactions are evaluated through detailed comparison with available surface, aloft, and remotely sensed observations. The expansion of CMAQ to simulate the hemispheric scales provides a framework to examine interactions between atmospheric processes occurring at various spatial and temporal scales with physical, chemical, and dynamical consistency. PMID:29681922

Development of a system emulating the global carbon cycle in Earth system models

NASA Astrophysics Data System (ADS)

Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.

2010-08-01

Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).

Description of the LASSO Alpha 1 Release

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

Gustafson, William I.; Vogelmann, Andrew M.; Cheng, Xiaoping

The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility began a pilot project in May 2015 to design a routine, high-resolution modeling capability to complement ARM’s extensive suite of measurements. This modeling capability has been named the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project. The availability of LES simulations with concurrent observations will serve many purposes. LES helps bridge the scale gap between DOE ARM observations and models, and the use of routine LES adds value to observations. It provides a self-consistent representation of the atmosphere and a dynamical context for the observations. Further,more » it elucidates unobservable processes and properties. LASSO will generate a simulation library for researchers that enables statistical approaches beyond a single-case mentality. It will also provide tools necessary for modelers to reproduce the LES and conduct their own sensitivity experiments. Many different uses are envisioned for the combined LASSO LES and observational library. For an observationalist, LASSO can help inform instrument remote-sensing retrievals, conduct Observation System Simulation Experiments (OSSEs), and test implications of radar scan strategies or flight paths. For a theoretician, LASSO will help calculate estimates of fluxes and co-variability of values, and test relationships without having to run the model yourself. For a modeler, LASSO will help one know ahead of time which days have good forcing, have co-registered observations at high-resolution scales, and have simulation inputs and corresponding outputs to test parameterizations. Further details on the overall LASSO project are available at http://www.arm. gov/science/themes/lasso.« less

Modeling global vegetation in the late Quaternary: What progress have we made and what are the priorities for the future?

NASA Astrophysics Data System (ADS)

Kaplan, Jed

2017-04-01

More than two decades ago, the development of the first global biogeography models led to an interest in simulating global land cover in the past. These models promised the possibility of creating a coherent picture of the Earth's vegetation that went beyond qualitative extrapolation of site-based observations, e.g., from paleoecological archives, and was not limited to areas with a high density of sites. Then as now, the goal of much work simulating past vegetation was to explore and understand the role of biogeophysical and biogeochemical feedbacks between the Earth's land surface and the climate system. Paleovegetation modeling for the late Quaternary has also influenced debates on the character of natural vegetation, conservation and ecological restoration goals, and the co-evolution of humans, civilizations, and the landscapes in which they live. The first simulations of global land cover in the past used equilibrium vegetation models, e.g., BIOME1, BIOME3, and BIOME4, and focused on well-known timeslices of interest in paleoclimate research, including the Last Glacial Maximum (21,000 BP) and the mid-Holocene (6,000 BP). Questions addressed included: quantification of the importance of terrestrial vegetation in the glacial carbon cycle, the role of changing vegetation cover on glacial inception, and the influence of biogeophysical feedbacks on the amplitude and spatial pattern of the mid-Holocene African Monsoon. In the intervening years, as both vegetation and climate models evolved and improved, the spatial resolution, number of periods studied, and the type of research questions addressed expanded greatly. Studies covered the dynamics of Arctic vegetation, wetland area, wetland methane emissions, and paleo-atmospheric chemistry, dust emissions and effects on paleoclimate, among others. A major recent advance in paleovegetation modeling for the late Quaternary has come with the development of Dynamic Global Vegetation Models (DGVMs) that are capable of simulating changing vegetation cover over time, continuously. Several DGVMs have been directly incorporated into the land surface scheme of modern Earth System Models (ESMs), further allowing the exploration of land-atmosphere feedbacks, e.g., during abrupt climate change events, such as those that occurred during the last deglaciation. Recent increases in computer power have also allowed offline simulations, i.e., not directly coupled to an ESM, with DGVMs to simulate vegetation change over long time periods, e.g., continuously for the entire Holocene. Realizing that climate change alone was not the only driver of land cover change over the late Quaternary, the most recent developments in paleovegetation modeling for this period have incorporated human agency as an influence on vegetation. Incorporation of scenarios of Anthropogenic Land Cover Change into DGVMs has allowed a quantitative contribution to the ongoing, lively debate regarding the role of humans in influencing Holocene atmospheric greenhouse gas concentrations. With the further advances in ESMs and the availability of very long climate model simulations, e.g., TraCE-21ka, improvements to DGVMs such as the explicit representation of age structure and plant traits, and the increasing awareness of the importance of human-environment interactions, the future of paleovegetation modeling for the late Quaternary presents a variety of opportunities. One important focus for future modeling should be on simulating the dynamics of ecotones, e.g., forest-grassland boundaries, over time, particularly during abrupt transient climate change events. Accurate simulation of ecotone boundaries is traditionally a weakness in DGVMs, yet these environments are highly valued by humans for their ecosystem services both at present and in the past, paleoecological evidence suggests that ecotone boundaries were very sensitive to past climate change, and they are critical locations where land-atmosphere feedbacks could have amplified or attenuated ongoing, externally-forced climate change. Lessons drawn from paleovegetation simulations may shed new light on the behavior of the earth system that will be valuable for understanding the future.

BioSTAR, a New Biomass and Yield Modeling Software

NASA Astrophysics Data System (ADS)

Kappas, M.; Degener, J.; Bauboeck, R.

2013-12-01

BioSTAR (Biomass Simulation Tool for Agricultural Recourses) is a new crop model which has been developed at the University of Göttingen for the assessment of agricultural biomass potentials in Lower Saxony, Germany. Lower Saxony is a major agricultural producer in Germany and in the EU, and biogas facilities which either use agricultural crops or manure or both have seen a strong boom in the last decade. To be able to model the potentials of these agricultural bioenergy crops was the objective of developing the BioSTAR model. BioSTAR is kept simple enough to be usable even for non-scientific users, e.g. staff in planning offices or farmers. The software of the model is written in Java and uses a Microsoft Access database connection to read its input data and write its output data. In this sense the software architecture is something entirely new as far as existing crop models are concerned. The database connection enables very fast editing of the various data sources which are needed to run a crop simulation and fosters the organization of this data. Due to the software setup, the amount of individual sites which can be processed with a few clicks is only limited by the maximum size of an Access database (2 GB) and thus allows datasets of 105 sites or more to be stored and processed. Data can easily be copied or imported from Excel. Capabilities of the crop model are: simulation of single or multiple year crop growth with total biomass production, evapotranspiration, soil water budget of a 16 layered soil profile and, nitrogen budget. The original growth engine of the model was carbon based (Azam-Ali, et al., 1994), but a radiation use efficiency and two transpiration based growth engines were added at a later point. Before each simulation run, the user can choose between these four growth engines and four different ET0-methods, or use an ensemble of them. Up to date (07/2013), the model has been calibrated for several winter and spring cereals, canola, maize, sorghum, sunflower and, sugar beet. Calibrations for rye grass, cup plant, poplar and willow still need to be performed. A Comparison of simulated and observed biomass yields for sites in Lower Saxony has rendered good results with errors (RMSE) ranging from below 10% (winter wheat, n= 102) and 18.6 % (sunflower, n=8) (Bauböck, unpublished). Because simulations can be made with limited soil data (soil type or texture class) and a limited climate data set (smallest set can be either monthly means of precipitation, temperature and, radiation or precipitation, temperature and, humidity) and the software is capable of processing large datasets, the model appears to be a promising tool for mid or large scale biomass and yield predictions. Up to now the model has only been used for yield predictions with current state climate and climate change scenarios in Lower Saxony, but comparisons with output data of the model AquaCrop (Steduto, et al., 2009) have shown good performance in arid and semi-arid climates (Bauböck, 2013).

Simulation of Extreme Surface Winds by Regional Climate Models in the NARCCAP Archive

NASA Astrophysics Data System (ADS)

Hatteberg, R.; Takle, E. S.

2011-12-01

Surface winds play a significant role in many natural processes as well as providing a very important ecological service for many human activities. Surface winds ventilate pollutants and heat from our cities, contribute to pollination for our crops, and regulate the fluxes of heat, moisture, and carbon dioxide from the earth's surface. Many environmental models such as biogeochemical models, crop models, lake models, pollutant transport models, etc., use surface winds as a key variable. Studies of the impacts of climate change and climate variability on a wide range of natural systems and coupled human-natural systems frequently need information on how surface wind speeds will change as greenhouse gas concentrations in the earth's atmosphere change. We have studied the characteristics of extreme winds - both high winds and low winds - created by regional climate models (RCMs) in the NARCCAP archives. We evaluated the capabilities of five RCMs forced by NCEP reanalysis data as well as global climate model (GCM) data for contemporary and future scenario climates to capture the observed statistical distribution of surface winds, both high-wind events and low-wind conditions. Our domain is limited to the Midwest (37°N to 49°N, -82°W to -101°W) with the Great Lakes masked out, which eliminates orographic effects that may contribute to regional circulations. The majority of this study focuses on the warm seasonal in order to examine derechos on the extreme high end and air pollution and plant processes on the low wind speed end. To examine extreme high winds we focus on derechos, which are long-lasting convectively driven extreme wind events that frequently leave a swath of damage extending across multiple states. These events are unusual in that, despite their relatively small spatial scale, they can persist for hours or even days, drawing energy from well-organized larger mesoscale or synoptic scale processes. We examine the ability of NARCCAP RCMs to reproduce these isolated extreme events by assessing their existence, location, magnitude, synoptic linkage, initiation time and duration as compared to the record of observations of derechos in the Midwest and Northeast US. We find that RCMs do reproduce features with close resemblance to derechos although their magnitudes are considerably below those observed (which may be expected given the 50-km grid spacing of the RCM models). Extreme low wind speeds in summer are frequently associated with stagnation conditions leading to high air pollution events in major cities. Low winds also lead to reduced evapotranspiration by crops, which can impact phenological processes (e.g. pollination and seed fertilization, carbon uptake by plants). We evaluate whether RCMs can simulate climatic distributions of low-wind conditions in the northern US. Results show differences among models in their ability to reproduce observed characteristics of low summer-time winds. Only one model reproduces observed high frequency of calm night-time surface winds in summer, which suggests a need to improve model capabilities for simulating extreme stagnation events.

Weather and climate

NASA Technical Reports Server (NTRS)

1975-01-01

Recommendations for using space observations of weather and climate to aid in solving earth based problems are given. Special attention was given to: (1) extending useful forecasting capability of space systems, (2) reducing social, economic, and human losses caused by weather, (3) development of space system capability to manage and control air pollutant concentrations, and (4) establish mechanisms for the national examination of deliberate and inadvertent means for modifying weather and climate.

Development of a database-driven system for simulating water temperature in the lower Yakima River main stem, Washington, for various climate scenarios

USGS Publications Warehouse

Voss, Frank; Maule, Alec

2013-01-01

A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year. The difference between current conditions and measured monthly values for the two warmest months (July and August) were 0.5°C and 0.2°C, respectively. The model predicted that water temperature generally becomes less sensitive to air temperature increases as the distance from the mouth of the river decreases. As a consequence, the difference between climate warming scenarios also decreased. The pattern of decreasing sensitivity is most pronounced from August to October. Interactive graphing tools were developed to explore the relative sensitivity of average monthly and mean daily water temperature to increases in air temperature for model output locations along the lower Yakima River main stem.

Changes in Seasonal and Extreme Hydrologic Conditions of the Georgia Basin/Puget Sound in an Ensemble Regional Climate Simulation for the Mid-Century

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

Leung, Lai R.; Qian, Yun

This study examines an ensemble of climate change projections simulated by a global climate model (GCM) and downscaled with a region climate model (RCM) to 40 km spatial resolution for the western North America. One control and three ensemble future climate simulations were produced by the GCM following a business as usual scenario for greenhouse gases and aerosols emissions from 1995 to 2100. The RCM was used to downscale the GCM control simulation (1995-2015) and each ensemble future GCM climate (2040-2060) simulation. Analyses of the regional climate simulations for the Georgia Basin/Puget Sound showed a warming of 1.5-2oC and statisticallymore » insignificant changes in precipitation by the mid-century. Climate change has large impacts on snowpack (about 50% reduction) but relatively smaller impacts on the total runoff for the basin as a whole. However, climate change can strongly affect small watersheds such as those located in the transient snow zone, causing a higher likelihood of winter flooding as a higher percentage of precipitation falls in the form of rain rather than snow, and reduced streamflow in early summer. In addition, there are large changes in the monthly total runoff above the upper 1% threshold (or flood volume) from October through May, and the December flood volume of the future climate is 60% above the maximum monthly flood volume of the control climate. Uncertainty of the climate change projections, as characterized by the spread among the ensemble future climate simulations, is relatively small for the basin mean snowpack and runoff, but increases in smaller watersheds, especially in the transient snow zone, and associated with extreme events. This emphasizes the importance of characterizing uncertainty through ensemble simulations.« less

Using large-scale diagnostic quantities to investigate change in East Coast Lows

NASA Astrophysics Data System (ADS)

Ji, Fei; Evans, Jason P.; Argueso, Daniel; Fita, Lluis; Di Luca, Alejandro

2015-11-01

East Coast Lows (ECLs) are intense low-pressure systems that affect the eastern seaboard of Australia. They have attracted research interest for both their destructive nature and water supplying capability. Estimating the changes in ECLs in the future has a major impact on emergency response as well as water management strategies for the coastal communities on the east coast of Australia. In this study, ECLs were identified using two large-scale diagnostic quantities: isentropic potential vorticity (IPV) and geostrophic vorticity (GV), which were calculated from outputs of historical and future regional climate simulations from the NSW/ACT regional climate modelling (NARCliM) project. The diagnostic results for the historical period were evaluated against a subjective ECL event database. Future simulations using a high emission scenario were examined to estimate changes in frequency, duration, and intensity of ECLs. The use of a relatively high resolution regional climate model makes this the first study to examine future changes in ECLs while resolving the full range of ECL sizes which can be as small as 100-200 km in diameter. The results indicate that it is likely that there will be fewer ECLs, with weaker intensity in the future. There could also be a seasonal shift in ECLs from cool months to warm months. These changes have the potential to significantly impact the water security on the east coast of Australia.

Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales?

NASA Astrophysics Data System (ADS)

Hewitt, Helene T.; Bell, Michael J.; Chassignet, Eric P.; Czaja, Arnaud; Ferreira, David; Griffies, Stephen M.; Hyder, Pat; McClean, Julie L.; New, Adrian L.; Roberts, Malcolm J.

2017-12-01

As the importance of the ocean in the weather and climate system is increasingly recognised, operational systems are now moving towards coupled prediction not only for seasonal to climate timescales but also for short-range forecasts. A three-way tension exists between the allocation of computing resources to refine model resolution, the expansion of model complexity/capability, and the increase of ensemble size. Here we review evidence for the benefits of increased ocean resolution in global coupled models, where the ocean component explicitly represents transient mesoscale eddies and narrow boundary currents. We consider lessons learned from forced ocean/sea-ice simulations; from studies concerning the SST resolution required to impact atmospheric simulations; and from coupled predictions. Impacts of the mesoscale ocean in western boundary current regions on the large-scale atmospheric state have been identified. Understanding of air-sea feedback in western boundary currents is modifying our view of the dynamics in these key regions. It remains unclear whether variability associated with open ocean mesoscale eddies is equally important to the large-scale atmospheric state. We include a discussion of what processes can presently be parameterised in coupled models with coarse resolution non-eddying ocean models, and where parameterizations may fall short. We discuss the benefits of resolution and identify gaps in the current literature that leave important questions unanswered.

Addressing climate change in the Forest Vegetation Simulator to assess impacts on landscape forest dynamics

Treesearch

Nicholas L. Crookston; Gerald E. Rehfeldt; Gary E. Dixon; Aaron R. Weiskittel

2010-01-01

To simulate stand-level impacts of climate change, predictors in the widely used Forest Vegetation Simulator (FVS) were adjusted to account for expected climate effects. This was accomplished by: (1) adding functions that link mortality and regeneration of species to climate variables expressing climatic suitability, (2) constructing a function linking site index to...

Addressing climate change in the forest vegetation simulator to assess impacts on landscape forest dynamics

Treesearch

Nicholas L. Crookston; Gerald E. Rehfeldt; Gary E. Dixon; Aaron R. Weiskittel

2010-01-01

To simulate stand-level impacts of climate change, predictors in the widely used Forest Vegetation Simulator (FVS) were adjusted to account for expected climate effects. This was accomplished by: (1) adding functions that link mortality and regeneration of species to climate variables expressing climatic suitability, (2) constructing a function linking site index to...

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²

NASA Astrophysics Data System (ADS)

Goldenson, N. L.

2014-12-01

Exploration in an open-ended computer game is an engaging way to explore climate and climate change. Everyone can explore physical models with real-time visualization in the educational simulator Universe Sandbox ² (universesandbox.com/2), which includes basic climate simulations on planets. I have implemented a time-dependent, one-dimensional meridional heat transport energy balance model to run and be adjustable in real time in the midst of a larger simulated system. Universe Sandbox ² is based on the original game - at its core a gravity simulator - with other new physically-based content for stellar evolution, and handling collisions between bodies. Existing users are mostly science enthusiasts in informal settings. We believe that this is the first climate simulation to be implemented in a professionally developed computer game with modern 3D graphical output in real time. The type of simple climate model we've adopted helps us depict the seasonal cycle and the more drastic changes that come from changing the orbit or other external forcings. Users can alter the climate as the simulation is running by altering the star(s) in the simulation, dragging to change orbits and obliquity, adjusting the climate simulation parameters directly or changing other properties like CO2 concentration that affect the model parameters in representative ways. Ongoing visuals of the expansion and contraction of sea ice and snow-cover respond to the temperature calculations, and make it accessible to explore a variety of scenarios and intuitive to understand the output. Variables like temperature can also be graphed in real time. We balance computational constraints with the ability to capture the physical phenomena we wish to visualize, giving everyone access to a simple open-ended meridional energy balance climate simulation to explore and experiment with. The software lends itself to labs at a variety of levels about climate concepts including seasons, the Greenhouse effect, reservoirs and flows, albedo feedback, Snowball Earth, climate sensitivity, and model experiment design. Climate calculations are extended to Mars with some modifications to the Earth climate component, and could be used in lessons about the Mars atmosphere, and exploring scenarios of Mars climate history.

Trend analysis of watershed-scale precipitation over Northern California by means of dynamically-downscaled CMIP5 future climate projections.

PubMed

Ishida, K; Gorguner, M; Ercan, A; Trinh, T; Kavvas, M L

2017-08-15

The impacts of climate change on watershed-scale precipitation through the 21st century were investigated over eight study watersheds in Northern California based on dynamically downscaled CMIP5 future climate projections from three GCMs (CCSM4, HadGEM2-ES, and MIROC5) under the RCP4.5 and RCP8.5 future climate scenarios. After evaluating the modeling capability of the WRF model, the six future climate projections were dynamically downscaled by means of the WRF model over Northern California at 9km grid resolution and hourly temporal resolution during a 94-year period (2006-2100). The biases in the model simulations were corrected, and basin-average precipitation over the eight study watersheds was calculated from the dynamically downscaled precipitation data. Based on the dynamically downscaled basin-average precipitation, trends in annual depth and annual peaks of basin-average precipitation during the 21st century were analyzed over the eight study watersheds. The analyses in this study indicate that there may be differences between trends of annual depths and annual peaks of watershed-scale precipitation during the 21st century. Furthermore, trends in watershed-scale precipitation under future climate conditions may be different for different watersheds depending on their location and topography even if they are in the same region. Copyright © 2017 Elsevier B.V. All rights reserved.

2014 Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Conference Report

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

Williams, Dean N.

2015-01-27

The climate and weather data science community met December 9–11, 2014, in Livermore, California, for the fourth annual Earth System Grid Federation (ESGF) and Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Conference, hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UVCDATremain global collaborations committed to developing a new generation of open-source software infrastructure that provides distributed access and analysis to simulated and observed data from the climate and weather communities.more » The tools and infrastructure created under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change. In addition, the F2F conference fosters a stronger climate and weather data science community and facilitates a stronger federated software infrastructure. The 2014 F2F conference detailed the progress of ESGF, UV-CDAT, and other community efforts over the year and sets new priorities and requirements for existing and impending national and international community projects, such as the Coupled Model Intercomparison Project Phase Six. Specifically discussed at the conference were project capabilities and enhancements needs for data distribution, analysis, visualization, hardware and network infrastructure, standards, and resources.« less

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

NASA Technical Reports Server (NTRS)

Smith, James A.

2010-01-01

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

Present and future connection of Asian-Pacific Oscillation to large-scale atmospheric circulations and East Asian rainfall: results of CMIP5

NASA Astrophysics Data System (ADS)

Zhou, Botao; Xu, Ying; Shi, Ying

2018-01-01

The summer Asian-Pacific oscillation (APO), one of the major modes of climate variability over the Asian-Pacific sector, has a pronounced effect on variations of large-scale atmospheric circulations and climate. This study evaluated the capability of 30 state-of-the-art climate models among the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating its association with the atmospheric circulations over the Asian-Pacific region and the precipitation over East Asia. Furthermore, their future connections under the RCP8.5 scenario were examined. The evaluation results show that 5 out of 30 climate models can well capture the observed APO-related features in a comprehensive way, including the strengthened South Asian high (SAH), deepened North Pacific trough (NPT) and northward East Asian jet (EAJ) in the upper troposphere; an intensification of the Asian low and the North Pacific subtropical high (NPSH) as well as a northward shift of the western Pacific subtropical high (WPSH) in the lower troposphere; and a decrease in East Asian summer rainfall (EASR) under the positive APO phase. Based on the five CMIP5 models' simulations, the dynamic linkages of the APO to the SAH, NPT, AL, and NPSH are projected to maintain during the second half of the twenty-first century. However, its connection with the EASR tends to reduce significantly. Such a reduction might result from the weakening of the linkage of the APO to the meridional displacement of the EAJ and WPSH as a response to the warming scenario.

Dynamical malaria models reveal how immunity buffers effect of climate variability

PubMed Central

Laneri, Karina; Paul, Richard E.; Tall, Adama; Faye, Joseph; Diene-Sarr, Fatoumata; Sokhna, Cheikh; Trape, Jean-François; Rodó, Xavier

2015-01-01

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human–mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity. PMID:26124134

A Virtual Ocean Observatory for Climate and Ocean Science: Synergistic Applications for SWOT and XOVWM

NASA Astrophysics Data System (ADS)

Arabshahi, P.; Howe, B. M.; Chao, Y.; Businger, S.; Chien, S.

2010-12-01

We present a virtual ocean observatory (VOO) that supports climate and ocean science as addressed in the NRC decadal survey. The VOO is composed of an autonomous software system, in-situ and space-based sensing assets, data sets, and interfaces to ocean and atmosphere models. The purpose of this observatory and its output data products are: 1) to support SWOT mission planning, 2) to serve as a vanguard for fusing SWOT, XOVWM, and in-situ data sets through fusion of OSTM (SWOT proxy) and QuikSCAT (XOVWM proxy) data with in-situ data, and 3) to serve as a feed-forward platform for high-resolution measurements of ocean surface topography (OST) in island and coastal environments utilizing space-based and in-situ adaptive sampling. The VOO will enable models capable of simulating and estimating realistic oceanic processes and atmospheric forcing of the ocean in these environments. Such measurements are critical in understanding the oceans' effects on global climate. The information systems innovations of the VOO are: 1. Development of an autonomous software platform for automated mission planning and combining science data products of QuikSCAT and OSTM with complementary in-situ data sets to deliver new data products. This software will present first-step demonstrations of technology that, once matured, will offer increased operational capability to SWOT by providing automated planning, and new science data sets using automated workflows. The future data sets to be integrated include those from SWOT and XOVWM. 2. A capstone demonstration of the effort utilizes the elements developed in (1) above to achieve adaptive in-situ sampling through feedback from space-based-assets via the SWOT simulator. This effort will directly contribute to orbit design during the experimental phase (first 6-9 months) of the SWOT mission by high resolution regional atmospheric and ocean modeling and sampling. It will also contribute to SWOT science via integration of in-situ data, QuikSCAT, and OSTM data sets, and models, thus serving as technology pathfinder for SWOT and XOVWM data fusion; and will contribute to SWOT operations via data fusion and mission planning technology. The goals of our project are as follows: (a) Develop and test the VOO, including hardware, in-situ science platforms (Seagliders) and instruments, and two autonomous software modules: 1) automated data fusion/assimilation, and 2) automated planning technology; (b) Generate new data sets (OST data in the Hawaiian Islands region) from fusion of in-situ data with QuikSCAT and OSTM data; (c) Integrate data sets derived from the VOO into the SWOT simulator for improved SWOT mission planning; (d) Demonstrate via Hawaiian Islands region field experiments and simulation the operational capability of the VOO to generate improved hydrologic cycle/ocean science, in particular: mesoscale and submesoscale ocean circulation including velocities, vorticity, and stress measurements, that are important to the modeling of ocean currents, eddies and mixing.

A State-of-the-Art Experimental Laboratory for Cloud and Cloud-Aerosol Interaction Research

NASA Technical Reports Server (NTRS)

Fremaux, Charles M.; Bushnell, Dennis M.

2011-01-01

The state of the art for predicting climate changes due to increasing greenhouse gasses in the atmosphere with high accuracy is problematic. Confidence intervals on current long-term predictions (on the order of 100 years) are so large that the ability to make informed decisions with regard to optimum strategies for mitigating both the causes of climate change and its effects is in doubt. There is ample evidence in the literature that large sources of uncertainty in current climate models are various aerosol effects. One approach to furthering discovery as well as modeling, and verification and validation (V&V) for cloud-aerosol interactions is use of a large "cloud chamber" in a complimentary role to in-situ and remote sensing measurement approaches. Reproducing all of the complex interactions is not feasible, but it is suggested that the physics of certain key processes can be established in a laboratory setting so that relevant fluid-dynamic and cloud-aerosol phenomena can be experimentally simulated and studied in a controlled environment. This report presents a high-level argument for significantly improved laboratory capability, and is meant to serve as a starting point for stimulating discussion within the climate science and other interested communities.

Towards Cloud-Resolving European-Scale Climate Simulations using a fully GPU-enabled Prototype of the COSMO Regional Model

NASA Astrophysics Data System (ADS)

Leutwyler, David; Fuhrer, Oliver; Cumming, Benjamin; Lapillonne, Xavier; Gysi, Tobias; Lüthi, Daniel; Osuna, Carlos; Schär, Christoph

2014-05-01

The representation of moist convection is a major shortcoming of current global and regional climate models. State-of-the-art global models usually operate at grid spacings of 10-300 km, and therefore cannot fully resolve the relevant upscale and downscale energy cascades. Therefore parametrization of the relevant sub-grid scale processes is required. Several studies have shown that this approach entails major uncertainties for precipitation processes, which raises concerns about the model's ability to represent precipitation statistics and associated feedback processes, as well as their sensitivities to large-scale conditions. Further refining the model resolution to the kilometer scale allows representing these processes much closer to first principles and thus should yield an improved representation of the water cycle including the drivers of extreme events. Although cloud-resolving simulations are very useful tools for climate simulations and numerical weather prediction, their high horizontal resolution and consequently the small time steps needed, challenge current supercomputers to model large domains and long time scales. The recent innovations in the domain of hybrid supercomputers have led to mixed node designs with a conventional CPU and an accelerator such as a graphics processing unit (GPU). GPUs relax the necessity for cache coherency and complex memory hierarchies, but have a larger system memory-bandwidth. This is highly beneficial for low compute intensity codes such as atmospheric stencil-based models. However, to efficiently exploit these hybrid architectures, climate models need to be ported and/or redesigned. Within the framework of the Swiss High Performance High Productivity Computing initiative (HP2C) a project to port the COSMO model to hybrid architectures has recently come to and end. The product of these efforts is a version of COSMO with an improved performance on traditional x86-based clusters as well as hybrid architectures with GPUs. We present our redesign and porting approach as well as our experience and lessons learned. Furthermore, we discuss relevant performance benchmarks obtained on the new hybrid Cray XC30 system "Piz Daint" installed at the Swiss National Supercomputing Centre (CSCS), both in terms of time-to-solution as well as energy consumption. We will demonstrate a first set of short cloud-resolving climate simulations at the European-scale using the GPU-enabled COSMO prototype and elaborate our future plans on how to exploit this new model capability.

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.

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

Taylor, Mark A.; Zak, Bernard Daniel; Backus, George A.

The Arctic region is rapidly changing in a way that will affect the rest of the world. Parts of Alaska, western Canada, and Siberia are currently warming at twice the global rate. This warming trend is accelerating permafrost deterioration, coastal erosion, snow and ice loss, and other changes that are a direct consequence of climate change. Climatologists have long understood that changes in the Arctic would be faster and more intense than elsewhere on the planet, but the degree and speed of the changes were underestimated compared to recent observations. Policy makers have not yet had time to examine themore » latest evidence or appreciate the nature of the consequences. Thus, the abruptness and severity of an unfolding Arctic climate crisis has not been incorporated into long-range planning. The purpose of this report is to briefly review the physical basis for global climate change and Arctic amplification, summarize the ongoing observations, discuss the potential consequences, explain the need for an objective risk assessment, develop scenarios for future change, review existing modeling capabilities and the need for better regional models, and finally to make recommendations for Sandia's future role in preparing our leaders to deal with impacts of Arctic climate change on national security. Accurate and credible regional-scale climate models are still several years in the future, and those models are essential for estimating climate impacts around the globe. This study demonstrates how a scenario-based method may be used to give insights into climate impacts on a regional scale and possible mitigation. Because of our experience in the Arctic and widespread recognition of the Arctic's importance in the Earth climate system we chose the Arctic as a test case for an assessment of climate impacts on national security. Sandia can make a swift and significant contribution by applying modeling and simulation tools with internal collaborations as well as with outside organizations. Because changes in the Arctic environment are happening so rapidly, a successful program will be one that can adapt very quickly to new information as it becomes available, and can provide decision makers with projections on the 1-5 year time scale over which the most disruptive, high-consequence changes are likely to occur. The greatest short-term impact would be to initiate exploratory simulations to discover new emergent and robust phenomena associated with one or more of the following changing systems: Arctic hydrological cycle, sea ice extent, ocean and atmospheric circulation, permafrost deterioration, carbon mobilization, Greenland ice sheet stability, and coastal erosion. Sandia can also contribute to new technology solutions for improved observations in the Arctic, which is currently a data-sparse region. Sensitivity analyses have the potential to identify thresholds which would enable the collaborative development of 'early warning' sensor systems to seek predicted phenomena that might be precursory to major, high-consequence changes. Much of this work will require improved regional climate models and advanced computing capabilities. Socio-economic modeling tools can help define human and national security consequences. Formal uncertainty quantification must be an integral part of any results that emerge from this work.« less

Data management support for selected climate data sets using the climate data access system

NASA Technical Reports Server (NTRS)

Reph, M. G.

1983-01-01

The functional capabilities of the Goddard Space Flight Center (GSFC) Climate Data Access System (CDAS), an interactive data storage and retrieval system, and the archival data sets which this system manages are discussed. The CDAS manages several climate-related data sets, such as the First Global Atmospheric Research Program (GARP) Global Experiment (FGGE) Level 2-b and Level 3-a data tapes. CDAS data management support consists of three basic functions: (1) an inventory capability which allows users to search or update a disk-resident inventory describing the contents of each tape in a data set, (2) a capability to depict graphically the spatial coverage of a tape in a data set, and (3) a data set selection capability which allows users to extract portions of a data set using criteria such as time, location, and data source/parameter and output the data to tape, user terminal, or system printer. This report includes figures that illustrate menu displays and output listings for each CDAS function.

A method for modeling the effects of climate and land use changes on erosion and sustainability of soil in a Mediterranean watershed (Languedoc, France).

PubMed

Paroissien, Jean-Baptiste; Darboux, Frédéric; Couturier, Alain; Devillers, Benoît; Mouillot, Florent; Raclot, Damien; Le Bissonnais, Yves

2015-03-01

Global climate and land use changes could strongly affect soil erosion and the capability of soils to sustain agriculture and in turn impact regional or global food security. The objective of our study was to develop a method to assess soil sustainability to erosion under changes in land use and climate. The method was applied in a typical mixed Mediterranean landscape in a wine-growing watershed (75 km(2)) within the Languedoc region (La Peyne, France) for two periods: a first period with the current climate and land use and a second period with the climate and land use scenarios at the end of the twenty-first century. The Intergovernmental Panel on Climate Change A1B future rainfall scenarios from the Météo France General circulation model was coupled with four contrasting land use change scenarios that were designed using a spatially-explicit land use change model. Mean annual erosion rate was estimated with an expert-based soil erosion model. Soil life expectancy was assessed using soil depth. Soil erosion rate and soil life expectancy were combined into a sustainability index. The median simulated soil erosion rate for the current period was 3.5 t/ha/year and the soil life expectancy was 273 years, showing a low sustainability of soils. For the future period with the same land use distribution, the median simulated soil erosion rate was 4.2 t/ha/year and the soil life expectancy was 249 years. The results show that soil erosion rate and soil life expectancy are more sensitive to changes in land use than to changes in precipitation. Among the scenarios tested, institution of a mandatory grass cover in vineyards seems to be an efficient means of significantly improving soil sustainability, both in terms of decreased soil erosion rates and increased soil life expectancies. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Community Earth System Model-Polar Climate Working Group and the status of CESM2.

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Strategy for long-term 3D cloud-resolving simulations over the ARM SGP site and preliminary results

NASA Astrophysics Data System (ADS)

Lin, W.; Liu, Y.; Song, H.; Endo, S.

2011-12-01

Parametric representations of cloud/precipitation processes continue having to be adopted in climate simulations with increasingly higher spatial resolution or with emerging adaptive mesh framework; and it is only becoming more critical that such parameterizations have to be scale aware. Continuous cloud measurements at DOE's ARM sites have provided a strong observational basis for novel cloud parameterization research at various scales. Despite significant progress in our observational ability, there are important cloud-scale physical and dynamical quantities that are either not currently observable or insufficiently sampled. To complement the long-term ARM measurements, we have explored an optimal strategy to carry out long-term 3-D cloud-resolving simulations over the ARM SGP site using Weather Research and Forecasting (WRF) model with multi-domain nesting. The factors that are considered to have important influences on the simulated cloud fields include domain size, spatial resolution, model top, forcing data set, model physics and the growth of model errors. The hydrometeor advection that may play a significant role in hydrological process within the observational domain but is often lacking, and the limitations due to the constraint of domain-wide uniform forcing in conventional cloud system-resolving model simulations, are at least partly accounted for in our approach. Conventional and probabilistic verification approaches are employed first for selected cases to optimize the model's capability of faithfully reproducing the observed mean and statistical distributions of cloud-scale quantities. This then forms the basis of our setup for long-term cloud-resolving simulations over the ARM SGP site. The model results will facilitate parameterization research, as well as understanding and dissecting parameterization deficiencies in climate models.

Modeling Methods

USGS Publications Warehouse

Healy, Richard W.; Scanlon, Bridget R.

2010-01-01

Simulation models are widely used in all types of hydrologic studies, and many of these models can be used to estimate recharge. Models can provide important insight into the functioning of hydrologic systems by identifying factors that influence recharge. The predictive capability of models can be used to evaluate how changes in climate, water use, land use, and other factors may affect recharge rates. Most hydrological simulation models, including watershed models and groundwater-flow models, are based on some form of water-budget equation, so the material in this chapter is closely linked to that in Chapter 2. Empirical models that are not based on a water-budget equation have also been used for estimating recharge; these models generally take the form of simple estimation equations that define annual recharge as a function of precipitation and possibly other climatic data or watershed characteristics.Model complexity varies greatly. Some models are simple accounting models; others attempt to accurately represent the physics of water movement through each compartment of the hydrologic system. Some models provide estimates of recharge explicitly; for example, a model based on the Richards equation can simulate water movement from the soil surface through the unsaturated zone to the water table. Recharge estimates can be obtained indirectly from other models. For example, recharge is a parameter in groundwater-flow models that solve for hydraulic head (i.e. groundwater level). Recharge estimates can be obtained through a model calibration process in which recharge and other model parameter values are adjusted so that simulated water levels agree with measured water levels. The simulation that provides the closest agreement is called the best fit, and the recharge value used in that simulation is the model-generated estimate of recharge.

Detecting hydrological changes through conceptual model

NASA Astrophysics Data System (ADS)

Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

2015-04-01

Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.

Coupled ice sheet - climate simulations of the last glacial inception and last glacial maximum with a model of intermediate complexity that includes a dynamical downscaling of heat and moisture

NASA Astrophysics Data System (ADS)

Quiquet, Aurélien; Roche, Didier M.

2017-04-01

Comprehensive fully coupled ice sheet - climate models allowing for multi-millenia transient simulations are becoming available. They represent powerful tools to investigate ice sheet - climate interactions during the repeated retreats and advances of continental ice sheets of the Pleistocene. However, in such models, most of the time, the spatial resolution of the ice sheet model is one order of magnitude lower than the one of the atmospheric model. As such, orography-induced precipitation is only poorly represented. In this work, we briefly present the most recent improvements of the ice sheet - climate coupling within the model of intermediate complexity iLOVECLIM. On the one hand, from the native atmospheric resolution (T21), we have included a dynamical downscaling of heat and moisture at the ice sheet model resolution (40 km x 40 km). This downscaling accounts for feedbacks of sub-grid precipitation on large scale energy and water budgets. From the sub-grid atmospheric variables, we compute an ice sheet surface mass balance required by the ice sheet model. On the other hand, we also explicitly use oceanic temperatures to compute sub-shelf melting at a given depth. Based on palaeo evidences for rate of change of eustatic sea level, we discuss the capability of our new model to correctly simulate the last glacial inception ( 116 kaBP) and the ice volume of the last glacial maximum ( 21 kaBP). We show that the model performs well in certain areas (e.g. Canadian archipelago) but some model biases are consistent over time periods (e.g. Kara-Barents sector). We explore various model sensitivities (e.g. initial state, vegetation, albedo) and we discuss the importance of the downscaling of precipitation for ice nucleation over elevated area and for the surface mass balance of larger ice sheets.

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.

Scientific workflow and support for high resolution global climate modeling at the Oak Ridge Leadership Computing Facility

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mayer, B.; Wang, F.; Hack, J.; McKenna, D.; Hartman-Baker, R.

2012-04-01

The Oak Ridge Leadership Computing Facility (OLCF) facilitates the execution of computational experiments that require tens of millions of CPU hours (typically using thousands of processors simultaneously) while generating hundreds of terabytes of data. A set of ultra high resolution climate experiments in progress, using the Community Earth System Model (CESM), will produce over 35,000 files, ranging in sizes from 21 MB to 110 GB each. The execution of the experiments will require nearly 70 Million CPU hours on the Jaguar and Titan supercomputers at OLCF. The total volume of the output from these climate modeling experiments will be in excess of 300 TB. This model output must then be archived, analyzed, distributed to the project partners in a timely manner, and also made available more broadly. Meeting this challenge would require efficient movement of the data, staging the simulation output to a large and fast file system that provides high volume access to other computational systems used to analyze the data and synthesize results. This file system also needs to be accessible via high speed networks to an archival system that can provide long term reliable storage. Ideally this archival system is itself directly available to other systems that can be used to host services making the data and analysis available to the participants in the distributed research project and to the broader climate community. The various resources available at the OLCF now support this workflow. The available systems include the new Jaguar Cray XK6 2.63 petaflops (estimated) supercomputer, the 10 PB Spider center-wide parallel file system, the Lens/EVEREST analysis and visualization system, the HPSS archival storage system, the Earth System Grid (ESG), and the ORNL Climate Data Server (CDS). The ESG features federated services, search & discovery, extensive data handling capabilities, deep storage access, and Live Access Server (LAS) integration. The scientific workflow enabled on these systems, and developed as part of the Ultra-High Resolution Climate Modeling Project, allows users of OLCF resources to efficiently share simulated data, often multi-terabyte in volume, as well as the results from the modeling experiments and various synthesized products derived from these simulations. The final objective in the exercise is to ensure that the simulation results and the enhanced understanding will serve the needs of a diverse group of stakeholders across the world, including our research partners in U.S. Department of Energy laboratories & universities, domain scientists, students (K-12 as well as higher education), resource managers, decision makers, and the general public.

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

Untangling climate signals from autogenic changes in long-term peatland development

NASA Astrophysics Data System (ADS)

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

2015-12-01

Peatlands represent important archives of Holocene paleoclimatic information. However, autogenic processes may disconnect peatland hydrological behavior from climate and overwrite climatic signals in peat records. We use a simulation model of peatland development driven by a range of Holocene climate reconstructions to investigate climate signal preservation in peat records. Simulated water-table depths and peat decomposition profiles exhibit homeostatic recovery from prescribed changes in rainfall, whereas changes in temperature cause lasting alterations to peatland structure and function. Autogenic ecohydrological feedbacks provide both high- and low-pass filters for climatic information, particularly rainfall. Large-magnitude climatic changes of an intermediate temporal scale (i.e., multidecadal to centennial) are most readily preserved in our simulated peat records. Simulated decomposition signals are offset from the climatic changes that generate them due to a phenomenon known as secondary decomposition. Our study provides the mechanistic foundations for a framework to separate climatic and autogenic signals in peat records.

A Mixed-dimensional Model for Determining the Impact of Permafrost Polygonal Ground Degradation on Arctic Hydrology.

NASA Astrophysics Data System (ADS)

Coon, E.; Jan, A.; Painter, S. L.; Moulton, J. D.; Wilson, C. J.

2017-12-01

Many permafrost-affected regions in the Arctic manifest a polygonal patterned ground, which contains large carbon stores and is vulnerability to climate change as warming temperatures drive melting ice wedges, polygon degradation, and thawing of the underlying carbon-rich soils. Understanding the fate of this carbon is difficult. The system is controlled by complex, nonlinear physics coupling biogeochemistry, thermal-hydrology, and geomorphology, and there is a strong spatial scale separation between microtopograpy (at the scale of an individual polygon) and the scale of landscape change (at the scale of many thousands of polygons). Physics-based models have come a long way, and are now capable of representing the diverse set of processes, but only on individual polygons or a few polygons. Empirical models have been used to upscale across land types, including ecotypes evolving from low-centered (pristine) polygons to high-centered (degraded) polygon, and do so over large spatial extent, but are limited in their ability to discern causal process mechanisms. Here we present a novel strategy that looks to use physics-based models across scales, bringing together multiple capabilities to capture polygon degradation under a warming climate and its impacts on thermal-hydrology. We use fine-scale simulations on individual polygons to motivate a mixed-dimensional strategy that couples one-dimensional columns representing each individual polygon through two-dimensional surface flow. A subgrid model is used to incorporate the effects of surface microtopography on surface flow; this model is described and calibrated to fine-scale simulations. And critically, a subsidence model that tracks volume loss in bulk ice wedges is used to alter the subsurface structure and subgrid parameters, enabling the inclusion of the feedbacks associated with polygon degradation. This combined strategy results in a model that is able to capture the key features of polygon permafrost degradation, but in a simulation across a large spatial extent of polygonal tundra.

How accurately are climatological characteristics and surface water and energy balances represented for the Colombian Caribbean Catchment Basin?

NASA Astrophysics Data System (ADS)

Hoyos, Isabel; Baquero-Bernal, Astrid; Hagemann, Stefan

2013-09-01

In Colombia, the access to climate related observational data is restricted and their quantity is limited. But information about the current climate is fundamental for studies on present and future climate changes and their impacts. In this respect, this information is especially important over the Colombian Caribbean Catchment Basin (CCCB) that comprises over 80 % of the population of Colombia and produces about 85 % of its GDP. Consequently, an ensemble of several datasets has been evaluated and compared with respect to their capability to represent the climate over the CCCB. The comparison includes observations, reconstructed data (CPC, Delaware), reanalyses (ERA-40, NCEP/NCAR), and simulated data produced with the regional climate model REMO. The capabilities to represent the average annual state, the seasonal cycle, and the interannual variability are investigated. The analyses focus on surface air temperature and precipitation as well as on surface water and energy balances. On one hand the CCCB characteristics poses some difficulties to the datasets as the CCCB includes a mountainous region with three mountain ranges, where the dynamical core of models and model parameterizations can fail. On the other hand, it has the most dense network of stations, with the longest records, in the country. The results can be summarised as follows: all of the datasets demonstrate a cold bias in the average temperature of CCCB. However, the variability of the average temperature of CCCB is most poorly represented by the NCEP/NCAR dataset. The average precipitation in CCCB is overestimated by all datasets. For the ERA-40, NCEP/NCAR, and REMO datasets, the amplitude of the annual cycle is extremely high. The variability of the average precipitation in CCCB is better represented by the reconstructed data of CPC and Delaware, as well as by NCEP/NCAR. Regarding the capability to represent the spatial behaviour of CCCB, temperature is better represented by Delaware and REMO, while precipitation is better represented by Delaware. Among the three datasets that permit an analysis of surface water and energy balances (REMO, ERA-40, and NCEP/NCAR), REMO best demonstrates the closure property of the surface water balance within the basin, while NCEP/NCAR does not demonstrate this property well. The three datasets represent the energy balance fairly well, although some inconsistencies were found in the individual balance components for NCEP/NCAR.

Simulation of Asia Dust and Cloud Interaction Over Pacific Ocean During Pacdex

NASA Astrophysics Data System (ADS)

Long, X.; Huang, J.; Cheng, C.; Wang, W.

2007-12-01

The effect of dust plume on the Pacific cloud systems and the associated radiative forcing is an outstanding problem for understanding climate change. Many studies showing that dust aerosol might be a good absorber for solar radiation, at the same time dust aerosols could affect the cloud's formation and precipitation by its capability as cloud condensation nuclei (CCN) and ice forming nuclei (IFN). But the role of aerosols in clouds and precipitation is very complex. Simulation of interaction between cloud and dust aerosols requires recognition that the aerosol cloud system comprises coupled components of dynamics, aerosol and cloud microphysics, radiation processes. In this study, we investigated the interaction between dust aerosols and cloud with WRF which coupled with detailed cloud microphysics processes and dust process. The observed data of SACOL (Semi-Arid Climate and Environment Observatory of Lanzhou University) and PACDEX (Pacific Dust Experiment) is used as the initialization which include the vertical distributions and concentration of dust particles. Our results show that dust aerosol not only impacts cloud microphysical processes but also cloud microstructure; Dust aerosols can act as effective ice nuclei and intensify the ice-forming processes.

Assessing the performances of low impact development alternatives by long-term simulation for a semi-arid area in Tianjin, northern China.

PubMed

Huang, Jinhui Jeanne; Li, Yu; Niu, Shuai; Zhou, Shu H

2014-01-01

For areas that are urbanized rapidly, the practice of low impact development (LID) has gained an important place in stormwater management and urban planning due to its capability and beneficial effects in restoring the original hydrological cycle. The performances of LID alternatives can vary substantially due to different climate conditions. This study investigated the performances of five LID alternatives under a semi-arid climate in northern China on water balance and flood control. A numerical model, Storm Water Management Model version 5 (US Environmental Protection Agency), was employed to run 10 years' rainfall events for these objectives. Two evaluation methods were proposed in this study: the efficiency index for water balance and a performance radar chart. The investigation of the five LID alternatives revealed that these LID alternatives functioned differently in flood control and water balance, and porous pavement performed best in all indices except the lag time. The two evaluation methods, in conjunction with the long-term numerical simulation, can facilitate design and decision making by providing a clear picture of the performance and functions for these LID alternatives.

Development of Modal Aerosol Module in CAM5 for Biogeochemical Cycles

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

Liu, Xiaohong

2017-11-18

This project aims at developing new capabilities for the Modal Aerosol Module in the DOE’s E3SM model with the applications to the global biogeochemical cycle. The impacts of the new developments on model simulations of clouds and climate will be examined. There are thee objectives for this project study: Implementing primary marine organic aerosols into the modal aerosol module (MAM) and investigate effects of primary marine organic aerosols on climate in E3SM; Implementing dust speciation in MAM and investigate the effect of dust species on mixed-phase clouds through indirect effects in E3SM; Writing papers documenting the new MAM developments (e.g.,more » MAM4 documentation paper, marine organic aerosol paper, dust speciation); These objectives will be accomplished in collaborations with Drs. Phil Rasch, Steve Ghan, and Susannah Burrows at Pacific Northwest National Laboratory.« less

Overview of the United States Department of Energy's ARM (Atmospheric Radiation Measurement) Program

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

Stokes, G.M.; Tichler, J.L.

The Department of Energy (DOE) is initiating a major atmospheric research effort, the Atmospheric Radiation Measurement Program (ARM). The program is a key component of DOE's research strategy to address global climate change and is a direct continuation of DOE's decade-long effort to improve the ability of General Circulation Models (GCMs) to provide reliable simulations of regional, and long-term climate change in response to increasing greenhouse gases. The effort is multi-disciplinary and multi-agency, involving universities, private research organizations and more than a dozen government laboratories. The objective of the ARM Research is to provide an experimental testbed for the studymore » of important atmospheric effects, particularly cloud and radiative processes, and to test parameterizations of these processes for use in atmospheric models. This effort will support the continued and rapid improvement of GCM predictive capability. 2 refs.« less

Overview of Experimental Capabilities - Supersonics

NASA Technical Reports Server (NTRS)

Banks, Daniel W.

2007-01-01

This viewgraph presentation gives an overview of experimental capabilities applicable to the area of supersonic research. The contents include: 1) EC Objectives; 2) SUP.11: Elements; 3) NRA; 4) Advanced Flight Simulator Flexible Aircraft Simulation Studies; 5) Advanced Flight Simulator Flying Qualities Guideline Development for Flexible Supersonic Transport Aircraft; 6) Advanced Flight Simulator Rigid/Flex Flight Control; 7) Advanced Flight Simulator Rapid Sim Model Exchange; 8) Flight Test Capabilities Advanced In-Flight Infrared (IR) Thermography; 9) Flight Test Capabilities In-Flight Schlieren; 10) Flight Test Capabilities CLIP Flow Calibration; 11) Flight Test Capabilities PFTF Flowfield Survey; 12) Ground Test Capabilities Laser-Induced Thermal Acoustics (LITA); 13) Ground Test Capabilities Doppler Global Velocimetry (DGV); 14) Ground Test Capabilities Doppler Global Velocimetry (DGV); and 15) Ground Test Capabilities EDL Optical Measurement Capability (PIV) for Rigid/Flexible Decelerator Models.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

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.

Evaluation of the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

2016-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

Pacific-North American teleconnection and North Pacific Oscillation: historical simulation and future projection in CMIP5 models

NASA Astrophysics Data System (ADS)

Chen, Zheng; Gan, Bolan; Wu, Lixin; Jia, Fan

2017-09-01

Based on reanalysis datasets and as many as 35 CMIP5 models, this study evaluates the capability of climate models to simulate the spatiotemporal features of Pacific-North American teleconnection (PNA) and North Pacific Oscillation (NPO) in the twentieth century wintertime, and further investigates their responses to greenhouse warming in the twenty-first century. Analysis reveals that while the majority (80%) of models reasonably simulate either the geographical distribution or the amplitude of PNA/NPO pattern, only half of models can well capture both features in space. As for the temporal features, variabilities of PNA and NPO in most models are biased toward higher amplitude. Additionally, most models simulate the interannual variabilities of PNA and NPO, qualitatively consistent with the observation, whereas models generally lack the capability to reproduce the decadal (20-25 years) variability of PNA. As the climate warms under the strongest future warming scenario, the PNA intensity is found to be strengthened, whereas there is no consensus on the direction of change in the NPO intensity among models. The intensification of positive PNA is primarily manifested in the large deepening of the North Pacific trough, which is robust as it is 2.3 times the unforced internal variability. By focusing on the tropical Pacific Ocean, we find that the multidecadal evolution of the North Pacific trough intensity (dominating the PNA intensity evolution) is closely related to that of the analogous trough in the PNA-like teleconnection forced by sea surface temperature anomalies (SSTa) in the tropical central Pacific (CP) rather than the tropical eastern Pacific (EP). Such association is also found to act under greenhouse warming: that is, the strengthening of the PNA-like teleconnection induced by the CP SSTa rather than the EP SSTa is a driving force for the intensification of PNA. This is in part owing to the robust enhancement of the tropical precipitation response to the CP SST variation. Indeed, further inspection suggests that models with stronger intensification of the CP SST variability and its related tropical precipitation response tend to have larger deepening magnitude of the North Pacific trough associated with the PNA variability.

Pacific-North American teleconnection and North Pacific Oscillation: historical simulation and future projection in CMIP5 models

NASA Astrophysics Data System (ADS)

Chen, Zheng; Gan, Bolan; Wu, Lixin; Jia, Fan

2018-06-01

Based on reanalysis datasets and as many as 35 CMIP5 models, this study evaluates the capability of climate models to simulate the spatiotemporal features of Pacific-North American teleconnection (PNA) and North Pacific Oscillation (NPO) in the twentieth century wintertime, and further investigates their responses to greenhouse warming in the twenty-first century. Analysis reveals that while the majority (80%) of models reasonably simulate either the geographical distribution or the amplitude of PNA/NPO pattern, only half of models can well capture both features in space. As for the temporal features, variabilities of PNA and NPO in most models are biased toward higher amplitude. Additionally, most models simulate the interannual variabilities of PNA and NPO, qualitatively consistent with the observation, whereas models generally lack the capability to reproduce the decadal (20-25 years) variability of PNA. As the climate warms under the strongest future warming scenario, the PNA intensity is found to be strengthened, whereas there is no consensus on the direction of change in the NPO intensity among models. The intensification of positive PNA is primarily manifested in the large deepening of the North Pacific trough, which is robust as it is 2.3 times the unforced internal variability. By focusing on the tropical Pacific Ocean, we find that the multidecadal evolution of the North Pacific trough intensity (dominating the PNA intensity evolution) is closely related to that of the analogous trough in the PNA-like teleconnection forced by sea surface temperature anomalies (SSTa) in the tropical central Pacific (CP) rather than the tropical eastern Pacific (EP). Such association is also found to act under greenhouse warming: that is, the strengthening of the PNA-like teleconnection induced by the CP SSTa rather than the EP SSTa is a driving force for the intensification of PNA. This is in part owing to the robust enhancement of the tropical precipitation response to the CP SST variation. Indeed, further inspection suggests that models with stronger intensification of the CP SST variability and its related tropical precipitation response tend to have larger deepening magnitude of the North Pacific trough associated with the PNA variability.

Impact of lakes and wetlands on present and future boreal climate

NASA Astrophysics Data System (ADS)

Poutou, E.; Krinner, G.; Genthon, C.

2002-12-01

Impact of lakes and wetlands on present and future boreal climate The role of lakes and wetlands in present-day high latitude climate is quantified using a general circulation model of the atmosphere. The atmospheric model includes a lake module which is presented and validated. Seasonal and spatial wetland distribution is calculated as a function of the hydrological budget of the wetlands themselves and of continental soil whose runoff feeds them. Wetland extent is simulated and discussed both in simulations forced by observed climate and in general circulation model simulations. In off-line simulations, forced by ECMWF reanalyses, the lake model simulates correctly observed lake ice durations, while the wetland extent is somewhat underestimated in the boreal regions. Coupled to the general circulation model, the lake model yields satisfying ice durations, although the climate model biases have impacts on the modeled lake ice conditions. Boreal wetland extents are overestimated in the general circulation model as simulated precipitation is too high. The impact of inundated surfaces on the simulated climate is strongest in summer when these surfaces are ice-free. Wetlands seem to play a more important role than lakes in cooling the boreal regions in summer and in humidifying the atmosphere. The role of lakes and wetlands in future climate change is evaluated by analyzing simulations of present and future climate with and without prescribed inland water bodies.

Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-12-01

One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.

Processes governing the temperature structure of the tropical tropopause layer (Invited)

NASA Astrophysics Data System (ADS)

Birner, T.

2013-12-01

The tropical tropopause layer (TTL) is among the most important but least understood regions of the global climate system. The TTL sets the boundary condition for atmospheric tracers entering the stratosphere. Specifically, TTL temperatures control stratospheric water vapor concentrations, which play a key role in the radiative budget of the entire stratosphere with implications for tropospheric and surface climate. The TTL shows a curious stratification structure: temperature continues to decrease beyond the level of main convective outflow (~200 hPa) up to the cold point tropopause (~100 hPa), but TTL lapse rates are smaller than in the upper troposphere. A cold point tropopause well separated from the level of main convective outflow requires TTL cooling which may be the result of: 1) the detailed radiative balance in the TTL, 2) large-scale upwelling (forced by extratropical or tropical waves), 3) the large-scale hydrostatic response aloft deep convective heating, 4) overshooting convection, 5) breaking gravity waves. All of these processes may act in isolation or combine to produce the observed TTL temperature structure. Here, a critical discussion of these processes / mechanisms and their role in lifting the cold point tropopause above the level of main convective outflow is presented. Results are based on idealized radiative-convective equilibrium model simulations, contrasting single-column with cloud-resolving simulations, as well on simulations with chemistry-climate models and reanalysis data. While all of the above processes are capable of producing a TTL-like region in isolation, their combination is found to produce important feedbacks. In particular, both water vapor and ozone are found to have strong radiative effects on TTL temperatures, highlighting important feedbacks between transport circulations setting temperatures and tracer structures and the resulting tracer structures in turn affecting temperatures.

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.

Spatiotemporal Visualization of Time-Series Satellite-Derived CO2 Flux Data Using Volume Rendering and Gpu-Based Interpolation on a Cloud-Driven Digital Earth

NASA Astrophysics Data System (ADS)

Wu, S.; Yan, Y.; Du, Z.; Zhang, F.; Liu, R.

2017-10-01

The ocean carbon cycle has a significant influence on global climate, and is commonly evaluated using time-series satellite-derived CO2 flux data. Location-aware and globe-based visualization is an important technique for analyzing and presenting the evolution of climate change. To achieve realistic simulation of the spatiotemporal dynamics of ocean carbon, a cloud-driven digital earth platform is developed to support the interactive analysis and display of multi-geospatial data, and an original visualization method based on our digital earth is proposed to demonstrate the spatiotemporal variations of carbon sinks and sources using time-series satellite data. Specifically, a volume rendering technique using half-angle slicing and particle system is implemented to dynamically display the released or absorbed CO2 gas. To enable location-aware visualization within the virtual globe, we present a 3D particlemapping algorithm to render particle-slicing textures onto geospace. In addition, a GPU-based interpolation framework using CUDA during real-time rendering is designed to obtain smooth effects in both spatial and temporal dimensions. To demonstrate the capabilities of the proposed method, a series of satellite data is applied to simulate the air-sea carbon cycle in the China Sea. The results show that the suggested strategies provide realistic simulation effects and acceptable interactive performance on the digital earth.

Rapid Ice-Sheet Changes and Mechanical Coupling to Solid-Earth/Sea-Level and Space Geodetic Observation

NASA Astrophysics Data System (ADS)

Adhikari, S.; Ivins, E. R.; Larour, E. Y.

2015-12-01

Perturbations in gravitational and rotational potentials caused by climate driven mass redistribution on the earth's surface, such as ice sheet melting and terrestrial water storage, affect the spatiotemporal variability in global and regional sea level. Here we present a numerically accurate, computationally efficient, high-resolution model for sea level. Unlike contemporary models that are based on spherical-harmonic formulation, the model can operate efficiently in a flexible embedded finite-element mesh system, thus capturing the physics operating at km-scale yet capable of simulating geophysical quantities that are inherently of global scale with minimal computational cost. One obvious application is to compute evolution of sea level fingerprints and associated geodetic and astronomical observables (e.g., geoid height, gravity anomaly, solid-earth deformation, polar motion, and geocentric motion) as a companion to a numerical 3-D thermo-mechanical ice sheet simulation, thus capturing global signatures of climate driven mass redistribution. We evaluate some important time-varying signatures of GRACE inferred ice sheet mass balance and continental hydrological budget; for example, we identify dominant sources of ongoing sea-level change at the selected tide gauge stations, and explain the relative contribution of different sources to the observed polar drift. We also report our progress on ice-sheet/solid-earth/sea-level model coupling efforts toward realistic simulation of Pine Island Glacier over the past several hundred years.

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

LPJ-GUESS Simulated North America Vegetation for 21-0 ka Using the TraCE-21ka Climate Simulation

NASA Astrophysics Data System (ADS)

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

2016-12-01

Transient climate simulations that span multiple millennia (e.g., TraCE-21ka) have become more common as computing power has increased, allowing climate models to complete long simulations in relatively short periods of time (i.e., months). These climate simulations provide information on the potential rate, variability, and spatial expression of past climate changes. They also can be used as input data for other environmental models to simulate transient changes for different components of paleoenvironmental systems, such as vegetation. Long, transient paleovegetation simulations can provide information on a range of ecological processes, describe the spatial and temporal patterns of changes in species distributions, and identify the potential locations of past species refugia. Paleovegetation simulations also can be used to fill in spatial and temporal gaps in observed paleovegetation data (e.g., pollen records from lake sediments) and to test hypotheses of past vegetation change. We used the TraCE-21ka transient climate simulation for 21-0 ka from CCSM3, a coupled atmosphere-ocean general circulation model. The TraCE-21ka simulated temperature, precipitation, and cloud data were regridded onto a 10-minute grid of North America. These regridded climate data, along with soil data and atmospheric carbon dioxide concentrations, were used as input to LPJ-GUESS, a general ecosystem model, to simulate North America vegetation from 21-0 ka. LPJ-GUESS simulates many of the processes controlling the distribution of vegetation (e.g., competition), although some important processes (e.g., dispersal) are not simulated. We evaluate the LPJ-GUESS-simulated vegetation (in the form of plant functional types and biomes) for key time periods and compare the simulated vegetation with observed paleovegetation data, such as data archived in the Neotoma Paleoecology Database. In general, vegetation simulated by LPJ-GUESS reproduces the major North America vegetation patterns (e.g., forest, grassland) with regional areas of disagreement between simulated and observed vegetation. We describe the regions and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of both the simulated climate and simulated vegetation data.

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Assessment of CMIP5 historical simulations of rainfall over Southeast Asia

NASA Astrophysics Data System (ADS)

Raghavan, Srivatsan V.; Liu, Jiandong; Nguyen, Ngoc Son; Vu, Minh Tue; Liong, Shie-Yui

2018-05-01

We present preliminary analyses of the historical (1986-2005) climate simulations of a ten-member subset of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) global climate models over Southeast Asia. The objective of this study was to evaluate the general circulation models' performance in simulating the mean state of climate over this less-studied climate vulnerable region, with a focus on precipitation. Results indicate that most of the models are unable to reproduce the observed state of climate over Southeast Asia. Though the multi-model ensemble mean is a better representation of the observations, the uncertainties in the individual models are far high. There is no particular model that performed well in simulating the historical climate of Southeast Asia. There seems to be no significant influence of the spatial resolutions of the models on the quality of simulation, despite the view that higher resolution models fare better. The study results emphasize on careful consideration of models for impact studies and the need to improve the next generation of models in their ability to simulate regional climates better.

A Software Prototype For Accessing Large Climate Simulation Data Through Digital Globe Interface

NASA Astrophysics Data System (ADS)

Chaudhuri, A.; Sorokine, A.

2010-12-01

The IPCC suite of global Earth system models produced terabytes of data for the CMIP3/AR4 archive and is expected to reach the petabyte scale by CMIP5/AR5. Dynamic downscaling of global models based on regional climate models can potentially lead to even larger data volumes. The model simulations for global or regional climate models like CCSM3 or WRF are typically run on supercomputers like the ORNL/DOE Jaguar and the results are stored on high performance storage systems. Access to these results from a user workstation is impeded by a number of factors such as enormous data size, limited bandwidth of standard office networks, data formats which are not fully supported by applications. So, a user-friendly interface for accessing and visualizing these results over standard Internet connection is required to facilitate collaborative work among geographically dispersed groups of scientists. To address this problem, we have developed a virtual globe based application which enables the scientists to query, visualize and analyze the results without the need of large data transfers to desktops and department-level servers. We have used open-source NASA WorldWind as a virtual globe platform and extended it with modules capable of visualizing model outputs stored in NetCDF format, while the data resides on the high-performance system. Based on the query placed by the scientist, our system initiates data processing routines on the high performance storage system to subset the data and reduce its size and then transfer it back to scientist's workstation through secure shell tunnel. The whole operation is kept totally transparent to the scientist and for the most part is controlled from a point-and-click GUI. The virtual globe also serves as a common platform for geospatial data, allowing smooth integration of the model simulation results with geographic data from other sources such as various web services or user-specific data in local files, if required. Also the system has the capability of building and updating a metadata catalog on the high performance storage that presents a simplified summary of the stored variables, hiding the low-level details such as physical location, size or format of the files from the user. Since data are often contributed to the system from multiple sources, the metadata catalog provides the user with a bird's eye view of the recent status of the database. As a next step, we plan on parallelizing the metadata updating and query-driven data selection routines to reduce the query response time. At current stage, the system can be immediately useful in making climate model simulation results available to a greater number of researchers who need simple and intuitive visualization of the simulation data or want to perform some analysis on it. The system's utility can reach beyond this particular application since it is generic enough to be ported to other high performance systems and to enable easy access to other types of geographic data.

Simulation and Theory of Ions at Atmospherically Relevant Aqueous Liquid-Air Interfaces

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

Tobias, Douglas J.; Stern, Abraham C.; Baer, Marcel D.

2013-04-01

Chemistry occurring at or near the surfaces of aqueous droplets and thin films in the atmosphere influences air quality and climate. Molecular dynamics simulations are becoming increasingly useful for gaining atomic-scale insight into the structure and reactivity of aqueous interfaces in the atmosphere. Here we review simulation studies of atmospherically relevant aqueous liquid-air interfaces, with an emphasis on ions that play important roles in the chemistry of atmospheric aerosols. In addition to surveying results from simulation studies, we discuss challenges to the refinement and experimental validation of the methodology for simulating ion adsorption to the air-water interface, and recent advancesmore » in elucidating the driving forces for adsorption. We also review the recent development of a dielectric continuum theory that is capable of reproducing simulation and experimental data on ion behavior at aqueous interfaces. MDB and CJM acknowledge support from the US Department of Energy's Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Pacific Northwest National Laboratory (PNNL) is operated for the Department of Energy by Battelle. MDB is supported by the Linus Pauling Distinguished Postdoctoral Fellowship Program at PNNL.« less

Hydrological Modeling of the Jiaoyi Watershed (China) Using HSPF Model

PubMed Central

Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie

2014-01-01

A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R 2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory

NASA Astrophysics Data System (ADS)

Sundberg, R.; Moberg, A.; Hind, A.

2012-08-01

A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

BASINS Climate Assessment Tool Tutorials

EPA Pesticide Factsheets

The BASINS Climate Assessment Tool (CAT) provides a flexible set of capabilities for exploring the potential effects of climate change on streamflow and water quality using different watershed models in BASINS.

Analysis of climate change impact on runoff and sediment delivery in a Great Lake watershed using SWAT

NASA Astrophysics Data System (ADS)

Verma, S.; Bhattarai, R.; Cooke, R.

2011-12-01

The green house gas loading of the atmosphere has been increasing since the mid 19th century which threatens to dramatically change the earth's climate in the 21st Century. Scientific evidences show that earth's global average surface temperature has risen some 0.75°C (1.3°F) since 1850. Third Assessment Report (TAR) from the Intergovernmental Panel on Climate Change (IPCC) concluded that human activities have increased the atmospheric concentration of greenhouse gases (GHGs), which will result in a warming world and other changes in the climate. TAR has projected an increase in globally average surface temperature of 1.4 to 5.8 °C and an increase in precipitation of 5 to 20 % over the period of 1990 to 2100. Assuming a global temperature increase of between 2.8 and 5.2 °C, it was estimated a 7-15% increase in global evaporation and precipitation rates. Global warming and subsequent climate change could raise sea level by several tens of centimeters in the next fifty years. Such a rise may erode beaches, worsen coastal flooding and threaten water quality in estuaries and aquifers. With the climate already changing and further change in climate highly likely to happen, study of impact of climate and the adaptation is a necessary component of any response to climate change. The objective of this study is to analyze the impact of climate change on runoff and sediment delivery in a Great Lake watershed located in Northern Ohio. Maumee River watershed is predominantly an agricultural watershed with an area of 6330 sq mile and drains to Lake Erie. Agricultural area covers about 89.9% of the watershed while wooded area covers 7.3%, 1.2% is urban area and other land uses account for 1.6%. Water Quality Laboratory, Heidelberg College has monitored the watershed for last 25 years. The Soil and Water Assessment Tool (SWAT) model is used for both water quantity and water quality simulations for past and future scenarios. SWAT is a continuous, long-term watershed scale simulation model which operates on a daily time step. The model is physically based, computationally efficient, and capable of assessing the impact of climate and watershed management on water, sediment, and nutrient/chemical yields. SWAT model has been calibrated for flow and sediment yield from 1982 to 2002 for the watershed. The calibrated model will be used to predict future flow and sediment delivery scenarios due to climate change (increase in temperature).

Hybrid Electric Propulsion Technologies for Commercial Transports

NASA Technical Reports Server (NTRS)

Bowman, Cheryl; Jansen, Ralph; Jankovsky, Amy

2016-01-01

NASA Aeronautics Research Mission Directorate has set strategic research thrusts to address the major drivers of aviation such as growth in demand for high-speed mobility, addressing global climate and capitalizing in the convergence of technological advances. Transitioning aviation to low carbon propulsion is one of the key strategic research thrust and drives the search for alternative and greener propulsion system for advanced aircraft configurations. This work requires multidisciplinary skills coming from multiple entities. The Hybrid Gas-Electric Subproject in the Advanced Air Transportation Project is energizing the transport class landscape by accepting the technical challenge of identifying and validating a transport class aircraft with net benefit from hybrid propulsion. This highly integrated aircraft of the future will only happen if airframe expertise from NASA Langley, modeling and simulation expertise from NASA Ames, propulsion expertise from NASA Glenn, and the flight research capabilities from NASA Armstrong are brought together to leverage the rich capabilities of U.S. Industry and Academia.

Dynamical Core in Atmospheric Model Does Matter in the Simulation of Arctic Climate

NASA Astrophysics Data System (ADS)

Jun, Sang-Yoon; Choi, Suk-Jin; Kim, Baek-Min

2018-03-01

Climate models using different dynamical cores can simulate significantly different winter Arctic climates even if equipped with virtually the same physics schemes. Current climate simulated by the global climate model using cubed-sphere grid with spectral element method (SE core) exhibited significantly warmer Arctic surface air temperature compared to that using latitude-longitude grid with finite volume method core. Compared to the finite volume method core, SE core simulated additional adiabatic warming in the Arctic lower atmosphere, and this was consistent with the eddy-forced secondary circulation. Downward longwave radiation further enhanced Arctic near-surface warming with a higher surface air temperature of about 1.9 K. Furthermore, in the atmospheric response to the reduced sea ice conditions with the same physical settings, only the SE core showed a robust cooling response over North America. We emphasize that special attention is needed in selecting the dynamical core of climate models in the simulation of the Arctic climate and associated teleconnection patterns.

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/

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Spatial Heterodyne Observations of Water (SHOW) vapour in the upper troposphere and lower stratosphere from a high altitude aircraft: Modelling and sensitivity analysis

NASA Astrophysics Data System (ADS)

Langille, J. A.; Letros, D.; Zawada, D.; Bourassa, A.; Degenstein, D.; Solheim, B.

2018-04-01

A spatial heterodyne spectrometer (SHS) has been developed to measure the vertical distribution of water vapour in the upper troposphere and the lower stratosphere with a high vertical resolution (∼500 m). The Spatial Heterodyne Observations of Water (SHOW) instrument combines an imaging system with a monolithic field-widened SHS to observe limb scattered sunlight in a vibrational band of water (1363 nm-1366 nm). The instrument has been optimized for observations from NASA's ER-2 aircraft as a proof-of-concept for a future low earth orbit satellite deployment. A robust model has been developed to simulate SHOW ER-2 limb measurements and retrievals. This paper presents the simulation of the SHOW ER-2 limb measurements along a hypothetical flight track and examines the sensitivity of the measurement and retrieval approach. Water vapour fields from an Environment and Climate Change Canada forecast model are used to represent realistic spatial variability along the flight path. High spectral resolution limb scattered radiances are simulated using the SASKTRAN radiative transfer model. It is shown that the SHOW instrument onboard the ER-2 is capable of resolving the water vapour variability in the UTLS from approximately 12 km - 18 km with ±1 ppm accuracy. Vertical resolutions between 500 m and 1 km are feasible. The along track sampling capability of the instrument is also discussed.

Performance of MODIS satellite and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir

2015-04-01

Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by MODIS or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from MODIS and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and MODIS LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with MODIS LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from MODIS and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, MODIS satellite, Soil Moisture Deficit, Neural Network

Improving Undergraduate Climate Change Literacy through Writing: A Pilot Study

ERIC Educational Resources Information Center

Small Griswold, Jennifer D.

2017-01-01

A climate-literate population, capable of making informed decisions related to climate change, is of critical importance as society faces ever-increasing global temperatures and changes in the climate system. This project evaluates the effectiveness of a novel instructional approach that incorporates climate change science into a first-year…

High Altitude Long Endurance UAV Analysis Model Development and Application Study Comparing Solar Powered Airplane and Airship Station-Keeping Capabilities

NASA Technical Reports Server (NTRS)

Ozoroski, Thomas A.; Nickol, Craig L.; Guynn, Mark D.

2015-01-01

There have been ongoing efforts in the Aeronautics Systems Analysis Branch at NASA Langley Research Center to develop a suite of integrated physics-based computational utilities suitable for modeling and analyzing extended-duration missions carried out using solar powered aircraft. From these efforts, SolFlyte has emerged as a state-of-the-art vehicle analysis and mission simulation tool capable of modeling both heavier-than-air (HTA) and lighter-than-air (LTA) vehicle concepts. This study compares solar powered airplane and airship station-keeping capability during a variety of high altitude missions, using SolFlyte as the primary analysis component. Three Unmanned Aerial Vehicle (UAV) concepts were designed for this study: an airplane (Operating Empty Weight (OEW) = 3285 kilograms, span = 127 meters, array area = 450 square meters), a small airship (OEW = 3790 kilograms, length = 115 meters, array area = 570 square meters), and a large airship (OEW = 6250 kilograms, length = 135 meters, array area = 1080 square meters). All the vehicles were sized for payload weight and power requirements of 454 kilograms and 5 kilowatts, respectively. Seven mission sites distributed throughout the United States were selected to provide a basis for assessing the vehicle energy budgets and site-persistent operational availability. Seasonal, 30-day duration missions were simulated at each of the sites during March, June, September, and December; one-year duration missions were simulated at three of the sites. Atmospheric conditions during the simulated missions were correlated to National Climatic Data Center (NCDC) historical data measurements at each mission site, at four flight levels. Unique features of the SolFlyte model are described, including methods for calculating recoverable and energy-optimal flight trajectories and the effects of shadows on solar energy collection. Results of this study indicate that: 1) the airplane concept attained longer periods of on-site capability than either airship concept, and 2) the airship concepts can attain higher levels of energy collection and storage than the airplane concept; however, attaining these energy benefits requires adverse design trades of reduced performance (small airship) or excessive solar array area (large airship).

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

Influence and predictive capacity of climate anomalies on daily to decadal extremes in canopy photosynthesis.

PubMed

Desai, Ankur R

2014-02-01

Significant advances have been made over the past decades in capabilities to simulate diurnal and seasonal variation of leaf-level and canopy-scale photosynthesis in temperate and boreal forests. However, long-term prediction of future forest productivity in a changing climate may be more dependent on how climate and biological anomalies influence extremes in interannual to decadal variability of canopy ecosystem carbon exchanges. These exchanges can differ markedly from leaf level responses, especially owing to the prevalence of long lags in nutrient and water cycling. Until recently, multiple long-term (10+ year) high temporal frequency (daily) observations of canopy exchange were not available to reliably assess this claim. An analysis of one of the longest running North American eddy covariance flux towers reveals that single climate variables do not adequately explain carbon exchange anomalies beyond the seasonal timescale. Daily to weekly lagged anomalies of photosynthesis positively autocorrelate with daily photosynthesis. This effect suggests a negative feedback in photosynthetic response to climate extremes, such as anomalies in evapotranspiration and maximum temperature. Moisture stress in the prior season did inhibit photosynthesis, but mechanisms are difficult to assess. A complex interplay of integrated and lagged productivity and moisture-limiting factors indicate a critical role of seasonal thresholds that limit growing season length and peak productivity. These results lead toward a new conceptual framework for improving earth system models with long-term flux tower observations.

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

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

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.« less

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

DOE PAGES

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; ...

2017-06-19

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.« less

Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

NASA Astrophysics Data System (ADS)

Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; Wyant, Matthew C.; Khairoutdinov, Marat

2017-07-01

Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called "ultraparameterization" (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (˜14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.

Towards a high resolution, integrated hydrology model of North America: Diagnosis of feedbacks between groundwater and land energy fluxes at continental scales.

NASA Astrophysics Data System (ADS)

Maxwell, Reed; Condon, Laura

2016-04-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Model results suggest that partitioning of plant transpiration to bare soil evaporation is a function of water table depth and later groundwater flow. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Climate change impacts on crop yield and quality with CO2 fertilization in China

PubMed Central

Erda, Lin; Wei, Xiong; Hui, Ju; Yinlong, Xu; Yue, Li; Liping, Bai; Liyong, Xie

2005-01-01

A regional climate change model (PRECIS) for China, developed by the UK's Hadley Centre, was used to simulate China's climate and to develop climate change scenarios for the country. Results from this project suggest that, depending on the level of future emissions, the average annual temperature increase in China by the end of the twenty-first century may be between 3 and 4 °C. Regional crop models were driven by PRECIS output to predict changes in yields of key Chinese food crops: rice, maize and wheat. Modelling suggests that climate change without carbon dioxide (CO2) fertilization could reduce the rice, maize and wheat yields by up to 37% in the next 20–80 years. Interactions of CO2 with limiting factors, especially water and nitrogen, are increasingly well understood and capable of strongly modulating observed growth responses in crops. More complete reporting of free-air carbon enrichment experiments than was possible in the Intergovernmental Panel on Climate Change's Third Assessment Report confirms that CO2 enrichment under field conditions consistently increases biomass and yields in the range of 5–15%, with CO2 concentration elevated to 550 ppm Levels of CO2 that are elevated to more than 450 ppm will probably cause some deleterious effects in grain quality. It seems likely that the extent of the CO2 fertilization effect will depend upon other factors such as optimum breeding, irrigation and nutrient applications. PMID:16433100

Projected timing of perceivable changes in climate extremes for terrestrial and marine ecosystems.

PubMed

Tan, Xuezhi; Gan, Thian Yew; Horton, Daniel E

2018-05-26

Human and natural systems have adapted to and evolved within historical climatic conditions. Anthropogenic climate change has the potential to alter these conditions such that onset of unprecedented climatic extremes will outpace evolutionary and adaptive capabilities. To assess whether and when future climate extremes exceed their historical windows of variability within impact-relevant socioeconomic, geopolitical, and ecological domains, we investigate the timing of perceivable changes (time of emergence; TOE) for 18 magnitude-, frequency-, and severity-based extreme temperature (10) and precipitation (8) indices using both multimodel and single-model multirealization ensembles. Under a high-emission scenario, we find that the signal of frequency- and severity-based temperature extremes is projected to rise above historical noise earliest in midlatitudes, whereas magnitude-based temperature extremes emerge first in low and high latitudes. Precipitation extremes demonstrate different emergence patterns, with severity-based indices first emerging over midlatitudes, and magnitude- and frequency-based indices emerging earliest in low and high latitudes. Applied to impact-relevant domains, simulated TOE patterns suggest (a) unprecedented consecutive dry day occurrence in >50% of 14 terrestrial biomes and 12 marine realms prior to 2100, (b) earlier perceivable changes in climate extremes in countries with lower per capita GDP, and (c) emergence of severe and frequent heat extremes well-before 2030 for the 590 most populous urban centers. Elucidating extreme-metric and domain-type TOE heterogeneities highlights the challenges adaptation planners face in confronting the consequences of elevated twenty-first century radiative forcing. © 2018 John Wiley & Sons Ltd.

The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

PubMed

Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

2013-10-28

Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

The pilot climate data system

NASA Technical Reports Server (NTRS)

Reph, M. G.; Treinish, L. A.; Smith, P. H.

1984-01-01

The Pilot Climate Data System (PCDS) is an interactive scientific information management system for locating, obtaining, manipulating, and displaying climate-research data. The PCDS was developed to manage a large collection of data of interest to the National Aeronautics and Space Administration's (NASA) research community and currently provides such support for approximately twenty data sets. In order to provide the PCDS capabilities, NASA's Goddard Space Flight Center (NASA/GSFC) has integrated the capabilities of several general-purpose software packages with specialized software for reading and reformatting the supported data sets. These capabilities were integrated in a manner which allows the PCDS to be easily expanded, either to provide support for additional data sets or to provide additional functional capabilities. This also allows the PCDS to take advantage of new technology as it becomes available, since parts of the system can be replaced with more powerful components without significantly affecting the user interface.

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.

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).

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.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

A dynamic simulation based water resources education tool.

PubMed

Williams, Alison; Lansey, Kevin; Washburne, James

2009-01-01

Educational tools to assist the public in recognizing impacts of water policy in a realistic context are not generally available. This project developed systems with modeling-based educational decision support simulation tools to satisfy this need. The goal of this model is to teach undergraduate students and the general public about the implications of common water management alternatives so that they can better understand or become involved in water policy and make more knowledgeable personal or community decisions. The model is based on Powersim, a dynamic simulation software package capable of producing web-accessible, intuitive, graphic, user-friendly interfaces. Modules are included to represent residential, agricultural, industrial, and turf uses, as well as non-market values, water quality, reservoir, flow, and climate conditions. Supplementary materials emphasize important concepts and lead learners through the model, culminating in an open-ended water management project. The model is used in a University of Arizona undergraduate class and within the Arizona Master Watershed Stewards Program. Evaluation results demonstrated improved understanding of concepts and system interactions, fulfilling the project's objectives.

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

Treesearch

John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole

2016-01-01

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...

Simulation of Climate Change Impacts on Wheat-Fallow Cropping Systems

USDA-ARS?s Scientific Manuscript database

Agricultural system simulation models are predictive tools for assessing climate change impacts on crop production. In this study, RZWQM2 that contains the DSSAT 4.0-CERES model was evaluated for simulating climate change impacts on wheat growth. The model was calibrated and validated using data fro...

Climate simulations and projections with a super-parameterized climate model

DOE PAGES

Stan, Cristiana; Xu, Li

2014-07-01

The mean climate and its variability are analyzed in a suite of numerical experiments with a fully coupled general circulation model in which subgrid-scale moist convection is explicitly represented through embedded 2D cloud-system resolving models. Control simulations forced by the present day, fixed atmospheric carbon dioxide concentration are conducted using two horizontal resolutions and validated against observations and reanalyses. The mean state simulated by the higher resolution configuration has smaller biases. Climate variability also shows some sensitivity to resolution but not as uniform as in the case of mean state. The interannual and seasonal variability are better represented in themore » simulation at lower resolution whereas the subseasonal variability is more accurate in the higher resolution simulation. The equilibrium climate sensitivity of the model is estimated from a simulation forced by an abrupt quadrupling of the atmospheric carbon dioxide concentration. The equilibrium climate sensitivity temperature of the model is 2.77 °C, and this value is slightly smaller than the mean value (3.37 °C) of contemporary models using conventional representation of cloud processes. As a result, the climate change simulation forced by the representative concentration pathway 8.5 scenario projects an increase in the frequency of severe droughts over most of the North America.« less

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.

Ground-water/surface-water responses to global climate simulations, Santa Clara-Calleguas basin, Ventura County, California, 1950-93

USGS Publications Warehouse

Hanson, Randall T.; Dettinger, Michael D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa Clara-Calleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/°C, compared to 0.9 m/°C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and — when the GCM forecast skills are adequate — for near term predictions.

Ground water/surface water responses to global climate simulations, Santa Clara-Calleguas Basin, Ventura, California

USGS Publications Warehouse

Hanson, R.T.; Dettinger, M.D.

2005-01-01

Climate variations can play an important, if not always crucial, role in successful conjunctive management of ground water and surface water resources. This will require accurate accounting of the links between variations in climate, recharge, and withdrawal from the resource systems, accurate projection or predictions of the climate variations, and accurate simulation of the responses of the resource systems. To assess linkages and predictability of climate influences on conjunctive management, global climate model (GCM) simulated precipitation rates were used to estimate inflows and outflows from a regional ground water model (RGWM) of the coastal aquifers of the Santa ClaraCalleguas Basin at Ventura, California, for 1950 to 1993. Interannual to interdecadal time scales of the El Nin??o Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) climate variations are imparted to simulated precipitation variations in the Southern California area and are realistically imparted to the simulated ground water level variations through the climate-driven recharge (and discharge) variations. For example, the simulated average ground water level response at a key observation well in the basin to ENSO variations of tropical Pacific sea surface temperatures is 1.2 m/??C, compared to 0.9 m/??C in observations. This close agreement shows that the GCM-RGWM combination can translate global scale climate variations into realistic local ground water responses. Probability distributions of simulated ground water level excursions above a local water level threshold for potential seawater intrusion compare well to the corresponding distributions from observations and historical RGWM simulations, demonstrating the combination's potential usefulness for water management and planning. Thus the GCM-RGWM combination could be used for planning purposes and - when the GCM forecast skills are adequate - for near term predictions.

Considerations in Managing the Fill Rate of the Grand Ethiopian Renaissance Dam Reservoir Using a System Dynamics Approach.

NASA Technical Reports Server (NTRS)

Keith, Bruce; Ford, David N.; Horton, Radley M.

2016-01-01

The purpose of this study is to evaluate simulated fill rate scenarios for the Grand Ethiopian Renaissance Dam while taking into account plausible climate change outcomes for the Nile River Basin. The region lacks a comprehensive equitable water resource management strategy, which creates regional security concerns and future possible conflicts. We employ climate estimates from 33 general circulation models within a system dynamics model as a step in moving toward a feasible regional water resource management strategy. We find that annual reservoir fill rates of 8-15% are capable of building hydroelectric capacity in Ethiopia while concurrently ensuring a minimum level of stream flow disruption into Egypt before 2039. Insofar as climate change estimates suggest a modest average increase in stream flow into the Aswan, climate changes through 2039 are unlikely to affect the fill rate policies. However, larger fill rates will have a more detrimental effect on stream flow into the Aswan, particularly beyond a policy of 15%. While this study demonstrates that a technical solution for reservoir fill rates is feasible, the corresponding policy challenge is political. Implementation of water resource management strategies in the Nile River Basin specifically and Africa generally will necessitate a national and regional willingness to cooperate.

Assessing Impact of Aerosol Intercontinental Transport on Regional Air Quality and Climate: What Satellites Can Help

NASA Technical Reports Server (NTRS)

Yu, Hongbin

2011-01-01

Mounting evidence for intercontinental transport of aerosols suggests that aerosols from a region could significantly affect climate and air quality in downwind regions and continents. Current assessment of these impacts for the most part has been based on global model simulations that show large variability. The aerosol intercontinental transport and its influence on air quality and climate involve many processes at local, regional, and intercontinental scales. There is a pressing need to establish modeling systems that bridge the wide range of scales. The modeling systems need to be evaluated and constrained by observations, including satellite measurements. Columnar loadings of dust and combustion aerosols can be derived from the MODIS and MISR measurements of total aerosol optical depth and particle size and shape information. Characteristic transport heights of dust and combustion aerosols can be determined from the CALIPSO lidar and AIRS measurements. CALIPSO liar and OMI UV technique also have a unique capability of detecting aerosols above clouds, which could offer some insights into aerosol lofting processes and the importance of above-cloud transport pathway. In this presentation, I will discuss our efforts of integrating these satellite measurements and models to assess the significance of intercontinental transport of dust and combustion aerosols on regional air quality and climate.

Biogenic organic emissions, air quality and climate

NASA Astrophysics Data System (ADS)

Guenther, A. B.

2015-12-01

Living organisms produce copious amounts of a diverse array of metabolites including many volatile organic compounds that are released into the atmosphere. These compounds participate in numerous chemical reactions that influence the atmospheric abundance of important air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. The production and release of these organics are strongly influenced by environmental conditions including air pollution, temperature, solar radiation, and water availability and they are highly sensitive to stress and extreme events. As a result, releases of biogenic organics to the atmosphere have an impact on, and are sensitive to, air quality and climate leading to potential feedback couplings. Their role in linking air quality and climate is conceptually clear but an accurate quantitative representation is needed for predictive models. Progress towards this goal will be presented including numerical model development and assessments of the predictive capability of the Model of Emission of Gases and Aerosols from Nature (MEGAN). Recent studies of processes controlling the magnitude and variations in biogenic organic emissions will be described and observations of their impact on atmospheric composition will be shown. Recent advances and priorities for future research will be discussed including laboratory process studies, long-term measurements, multi-scale regional studies, global satellite observations, and the development of a next generation model for simulating land-atmosphere chemical exchange.

An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models

USGS Publications Warehouse

David E. Rupp,

2016-05-05

The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

NASA Technical Reports Server (NTRS)

Arneson, Heather; Evans, Antony D.; Li, Jinhua; Wei, Mei Yueh

2017-01-01

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a collaboration between the Center for Ocean-Land-Atmosphere studies (COLA); the Geophysical Fluid Dynamics Laboratory (GFDL); the George Mason University (GMU); the National Center for Atmospheric Research (NCAR); the NCDC; NCEP; the Pacific Marine Environmental Laboratory (PMEL); and the University of Washington. The objective of the NOMADS is to preserve and provide retrospective access to GCM's and reference quality long-term observational and high volume three dimensional data as well as NCEP NWP models and re-start and re-analysis information. The creation of the NOMADS features a data distribution, format independent, methodology enabling scientific collaboration between researchers. The NOMADS configuration will allow a researcher to transparently browse, extract and intercompare retrospective observational and model data products from any of the participating centers. NOMADS will provide the ability to easily initialize and compare the results of ongoing climate model assessments and NWP output. Beyond the ingest and access capability soon to be implemented with NOMADS is the challenge of algorithm development for the inter-comparison of large-array data (e.g., satellite and radar) with surface, upper-air, and sub-surface ocean observational data. The implementation of NOMADS should foster the development of new quality control processes by taking advantage of distributed data access.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

NASA Astrophysics Data System (ADS)

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-05-01

climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

USGS Publications Warehouse

Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

2013-01-01

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

Climate change negotiation simulations for students: responses across gender and age.A case study: San Francisco State University World Climate Exercises

NASA Astrophysics Data System (ADS)

Rasheva, E. A.

2015-12-01

For decades, role-play and simulation exercises have been utilized for learning and policy decision making. While the power of Model UN simulations in building first-person experience and understanding of complex international issues is well known, the effectiveness of simulations for inspiring citizen engagement in scientific public-policy issues is little studied. My work hypothesizes that climate-change negotiation simulations can enhance students' scientific literacy and policy advocacy. It aims to determine how age and gender influence the responsiveness of students to such simulations. During the 2015 fall semester, I am conducting World Climate exercises for fellow graduate and undergraduate students at San Francisco State University. At the end of the exercise, I will have collected the responses to an anonymous questionnaire in which the participants indicate age and gender. The questionnaire asks participants to describe their hopes and fears for the future and to propose public and personal actions for achieving a strong climate change agreement. I am tracking differences to determine whether participants' age and gender correlate with particular patterns of feeling and thinking. My future research will aim to determine whether and how strongly the World Climate Exercise has affected participants' actual policy engagement. This work will also reflect on my experiences as a World Climate facilitator. I will describe the facilitation process and then discuss some of my observations from the sessions. I will specify the challenges I have encountered and suggest strategies that can strengthen the learning process. World Climate is a computer-simulation-based climate change negotiations role-playing exercise developed by Climate Interactive in partnership with the System Dynamics Group at the MIT Sloan School of Management.

Simulating Climate Change in Ireland

NASA Astrophysics Data System (ADS)

Nolan, P.; Lynch, P.

2012-04-01

At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

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

76 FR 71341 - BASINS and WEPP Climate Assessment Tools: Case Study Guide to Potential Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-17

... report presents a series of short case studies designed to illustrate the capabilities of these tools for... change impacts on water. This report presents a series of short case studies using the BASINS and WEPP climate assessment tools. The case studies are designed to illustrate the capabilities of these tools for...

The Nonlinear Response of the Equatorial Pacific Ocean-Atmosphere System to Periodic Variations in Insolation and its Association with the Abrupt Climate Transitions during the Quaternary.

NASA Astrophysics Data System (ADS)

Lopes, P. G.

2015-12-01

The evidences of climate changes during the Quaternary are abundant but the physical mechanisms behind the climate transitions are controversial. The theory of Milankovitch takes into account the periodic orbital variations and the solar radiation received by the Earth as the main explanation for the glacial-interglacial cycles. However, some gaps in the theory still remain. In this study, we propose elucidating some of these gaps by approaching the Equatorial Pacific Ocean as a large oscillator, capable of triggering climate changes in different temporal scales. A mathematical model representing El Ninõ-like phenomena, based on Duffing equation and modulated by the astronomical cycle of 100 ka, was used to simulate the variability of the equatorial Pacific climate system over the last 2 Ma. The physical configuration of the Pacific Ocean, expressed in the equation, explains the temporal limit of the glacial-interglacial cycles. According to the simulation results, consistent with paleoclimate records, the amplification of the effects of the gradual variation of the Earth's orbit eccentricity - another unclear question - is due to the feedback mechanism of the Pacific ocean-atmosphere system, which responds non-linearly to small variations in insolation forcing and determines the ENSO-like phase (warm or cold) at different time scales and different intensities. The approach proposed here takes into account that the abrupt transitions between the ENSO-like phases, and the consequent changes in the sea surface temperature (SST) along the Equatorial Pacific Ocean, produce reactions that act as secondary causes of the temperature fluctuations that result in a glaciation (or deglaciation) - as the drastic change on the rate of evaporation/precipitation around the globe, and the increase (or decrease) of the atmospheric CO2 absorption by the phytoplankton. The transitional behavior between the warm and the cold phases, according to the presented model, is enhanced as the rate of SST variation increases.

iRODS-Based Climate Data Services and Virtualization-as-a-Service in the NASA Center for Climate Simulation

NASA Astrophysics Data System (ADS)

Schnase, J. L.; Duffy, D. Q.; Tamkin, G. S.; Strong, S.; Ripley, D.; Gill, R.; Sinno, S. S.; Shen, Y.; Carriere, L. E.; Brieger, L.; Moore, R.; Rajasekar, A.; Schroeder, W.; Wan, M.

2011-12-01

Scientific data services are becoming an important part of the NASA Center for Climate Simulation's mission. Our technological response to this expanding role is built around the concept of specialized virtual climate data servers, repetitive cloud provisioning, image-based deployment and distribution, and virtualization-as-a-service. A virtual climate data server is an OAIS-compliant, iRODS-based data server designed to support a particular type of scientific data collection. iRODS is data grid middleware that provides policy-based control over collection-building, managing, querying, accessing, and preserving large scientific data sets. We have developed prototype vCDSs to manage NetCDF, HDF, and GeoTIF data products. We use RPM scripts to build vCDS images in our local computing environment, our local Virtual Machine Environment, NASA's Nebula Cloud Services, and Amazon's Elastic Compute Cloud. Once provisioned into these virtualized resources, multiple vCDSs can use iRODS's federation and realized object capabilities to create an integrated ecosystem of data servers that can scale and adapt to changing requirements. This approach enables platform- or software-as-a-service deployment of the vCDSs and allows the NCCS to offer virtualization-as-a-service, a capacity to respond in an agile way to new customer requests for data services, and a path for migrating existing services into the cloud. We have registered MODIS Atmosphere data products in a vCDS that contains 54 million registered files, 630TB of data, and over 300 million metadata values. We are now assembling IPCC AR5 data into a production vCDS that will provide the platform upon which NCCS's Earth System Grid (ESG) node publishes to the extended science community. In this talk, we describe our approach, experiences, lessons learned, and plans for the future.

Paleoclimate diagnostics: consistent large-scale temperature responses in warm and cold climates

NASA Astrophysics Data System (ADS)

Izumi, Kenji; Bartlein, Patrick; Harrison, Sandy

2015-04-01

The CMIP5 model simulations of the large-scale temperature responses to increased raditative forcing include enhanced land-ocean contrast, stronger response at higher latitudes than in the tropics, and differential responses in warm and cool season climates to uniform forcing. Here we show that these patterns are also characteristic of CMIP5 model simulations of past climates. The differences in the responses over land as opposed to over the ocean, between high and low latitudes, and between summer and winter are remarkably consistent (proportional and nearly linear) across simulations of both cold and warm climates. Similar patterns also appear in historical observations and paleoclimatic reconstructions, implying that such responses are characteristic features of the climate system and not simple model artifacts, thereby increasing our confidence in the ability of climate models to correctly simulate different climatic states. We also show the possibility that a small set of common mechanisms control these large-scale responses of the climate system across multiple states.

The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Simulating post-wildfire forest trajectories under alternative climate and management scenarios

Treesearch

Alicia Azpeleta Tarancon; Peter Z. Fule; Kristen L. Shive; Carolyn H. Sieg; Andrew Sanchez Meador; Barbara Strom

2014-01-01

Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned...

Using multiple climate projections for assessing hydrological response to climate change in the Thukela River Basin, South Africa

NASA Astrophysics Data System (ADS)

Graham, L. Phil; Andersson, Lotta; Horan, Mark; Kunz, Richard; Lumsden, Trevor; Schulze, Roland; Warburton, Michele; Wilk, Julie; Yang, Wei

This study used climate change projections from different regional approaches to assess hydrological effects on the Thukela River Basin in KwaZulu-Natal, South Africa. Projecting impacts of future climate change onto hydrological systems can be undertaken in different ways and a variety of effects can be expected. Although simulation results from global climate models (GCMs) are typically used to project future climate, different outcomes from these projections may be obtained depending on the GCMs themselves and how they are applied, including different ways of downscaling from global to regional scales. Projections of climate change from different downscaling methods, different global climate models and different future emissions scenarios were used as input to simulations in a hydrological model to assess climate change impacts on hydrology. A total of 10 hydrological change simulations were made, resulting in a matrix of hydrological response results. This matrix included results from dynamically downscaled climate change projections from the same regional climate model (RCM) using an ensemble of three GCMs and three global emissions scenarios, and from statistically downscaled projections using results from five GCMs with the same emissions scenario. Although the matrix of results does not provide complete and consistent coverage of potential uncertainties from the different methods, some robust results were identified. In some regards, the results were in agreement and consistent for the different simulations. For others, particularly rainfall, the simulations showed divergence. For example, all of the statistically downscaled simulations showed an annual increase in precipitation and corresponding increase in river runoff, while the RCM downscaled simulations showed both increases and decreases in runoff. According to the two projections that best represent runoff for the observed climate, increased runoff would generally be expected for this basin in the future. Dealing with such variability in results is not atypical for assessing climate change impacts in Africa and practitioners are faced with how to interpret them. This work highlights the need for additional, well-coordinated regional climate downscaling for the region to further define the range of uncertainties involved.

Sensitivity of tropical convection in cloud-resolving WRF simulations to model physics and forcing procedures

NASA Astrophysics Data System (ADS)

Endo, S.; Lin, W.; Jackson, R. C.; Collis, S. M.; Vogelmann, A. M.; Wang, D.; Oue, M.; Kollias, P.

2017-12-01

Tropical convection is one of the main drivers of the climate system and recognized as a major source of uncertainty in climate models. High-resolution modeling is performed with a focus on the deep convection cases during the active monsoon period of the TWP-ICE field campaign to explore ways to improve the fidelity of convection permitting tropical simulations. Cloud resolving model (CRM) simulations are performed with WRF modified to apply flexible configurations for LES/CRM simulations. We have enhanced the capability of the forcing module to test different implementations of large-scale vertical advective forcing, including a function for optional use of large-scale thermodynamic profiles and a function for the condensate advection. The baseline 3D CRM configurations are, following Fridlind et al. (2012), driven by observationally-constrained ARM forcing and tested with diagnosed surface fluxes and fixed sea-surface temperature and prescribed aerosol size distributions. After the spin-up period, the simulations follow the observed precipitation peaks associated with the passages of precipitation systems. Preliminary analysis shows that the simulation is generally not sensitive to the treatment of the large-scale vertical advection of heat and moisture, while more noticeable changes in the peak precipitation rate are produced when thermodynamic profiles above the boundary layer were nudged to the reference profiles from the forcing dataset. The presentation will explore comparisons with observationally-based metrics associated with convective characteristics and examine the model performance with a focus on model physics, doubly-periodic vs. nested configurations, and different forcing procedures/sources. A radar simulator will be used to understand possible uncertainties in radar-based retrievals of convection properties. Fridlind, A. M., et al. (2012), A comparison of TWP-ICE observational data with cloud-resolving model results, J. Geophys. Res., 117, D05204, doi:10.1029/2011JD016595.

Building an ensemble of climate scenarios for decision-making in hydrology: benefits, pitfalls and uncertainties

NASA Astrophysics Data System (ADS)

Braun, Marco; Chaumont, Diane

2013-04-01

Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an ensemble comprising 87 climate simulations. The climate data ensemble is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for downscaling and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this submission focuses on the production of climatic scenarios for application in hydrology, the submission « The (cQ)2 project: assessing watershed scale hydrological changes for the province of Québec at the 2050 horizon, a collaborative framework » by Catherine Guay describes how Hydro-Québec and CEHQ put the data into use.

Modeling the Climatic Consequences of Geoengineering

NASA Astrophysics Data System (ADS)

Somerville, R. C.

2005-12-01

The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert opinion is that this evidence is now sufficient to establish the human cause of much recent climate change. Nevertheless, no model can provide detailed and fully trustworthy answers to every possible question of interest. As an example, how will the climatology of Atlantic hurricanes change as the greenhouse effect becomes stronger? Can models reliably forecast changes in the length of the hurricane season or changes in the geographical regions affected by hurricanes? The answer is no, or at least, not yet. Additionally, climate models are not based entirely on first principles, such as Newtonian physics. Instead, they have been developed primarily to simulate the present climate and relatively small departures from it. To achieve this goal, a certain amount of empiricism has been built into the models. The result has sometimes been to increase the apparent realism of models at the cost of limiting their generality. Thus, the available climate models may well be less capable of simulating a geoengineering experiment that might lead to a radically different climate. New model development may be required for this new application. The challenge is to distinguish between what models can and cannot do well. It would be irresponsible and unethical, either to undertake geoengineering projects without modeling their consequences, or to place blind faith in the models. To decide how best to model a proposed geoengineering technique requires a deep understanding of the strengths and weaknesses of climate models. The history of modeling successes and failures is a valuable guide to the wise interpretation of model results.

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

NASA Astrophysics Data System (ADS)

Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

2017-04-01

Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

An effective online data monitoring and saving strategy for large-scale climate simulations

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

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

An effective online data monitoring and saving strategy for large-scale climate simulations

DOE PAGES

Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin; ...

2018-01-22

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

Impacts of Irrigation on Daily Extremes in the Coupled Climate System

NASA Technical Reports Server (NTRS)

Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide

2014-01-01

Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

Advancing coupled human-earth system models: The integrated Earth System Model Project

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems. While these initial experiments have relied on offline coupling methodologies, current and future experiments are utilizing a single model code developed to integrate GCAM into CESM as a component of the land model. This unique capability facilitates many new applications to scientific questions arising from human and biogeophysical systems interaction. Future developments will further integrate the energy system decisions and greenhouse gas emissions as simulated in GCAM with the appropriate climate and land system components of CESM.

Multi-millennia simulation of Greenland deglaciation from the Max-Plank-Institute Model (MPI-ISM) 2xCO2 simulation

NASA Astrophysics Data System (ADS)

Cabot, Vincent; Vizcaino, Miren; Mikolajewicz, Uwe

2016-04-01

Long-term ice sheet and climate coupled simulations are of great interest since they assess how the Greenland Ice Sheet (GrIS) will respond to global warming and how GrIS changes will impact on the climate system. We have run the Max-Plank-Institute Earth System Model coupled with an Ice Sheet Model (SICOPOLIS) over a time period of 10500 years under two times CO2 forcing. This is a coupled atmosphere (ECHAM5T31), ocean (MPI-OM), dynamic vegetation (LPJ), and ice sheet (SICOPOLIS, 10 km horizontal resolution) model. Given the multi-millennia simulation, the horizontal spatial resolution of the atmospheric component is relatively coarse (3.75°). A time-saving technique (asynchronous coupling) is used once the global climate reaches quasi-equilibrium. In our doubling-CO2 simulation, the GrIS is expected to break up into two pieces (one ice cap in the far north on one ice sheet in the south and east) after 3000 years. During the first 500 simulation years, the GrIS climate and surface mass balance (SMB) are mainly affected by the greenhouse effect-forced climate change. After the simulated year 500, the global climate reaches quasi-equilibrium. Henceforth Greenland climate change is mainly due to ice sheet decay. GrIS albedo reduction enhances melt and acts as a powerful feedback for deglaciation. Due to increased cloudiness in the Arctic region as a result of global climate change, summer incoming shortwave radiation is substantially reduced over Greenland, reducing deglaciation rates. At the end of the simulation, Greenland becomes green with forest growing over the newly deglaciated regions. References: Helsen, M. M., van de Berg, W. J., van de Wal, R. S. W., van den Broeke, M. R., and Oerlemans, J. (2013), Coupled regional climate-ice-sheet simulation shows limited Greenland ice loss during the Eemian, Climate of the Past, 9, 1773-1788, doi: 10.5194/cp-9-1773-2013 Helsen, M. M., van de Wal, R. S. W., van den Broeke, M. R., van de Berg, W. J., and Oerlemans, J. (2015), Coupling of climate models and ice sheet models by the surface mass balance gradients: application to the Greenland Ice Sheet, The Cryosphere, 6, 255-272, doi: 10.5194/tc-6-255-2012 Robinson, A., Calov, R., and Ganopolski, A. (2011), Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial, Climate of the Past, 7, 381-396, doi: 10.5194/cp-7-381-2011 Vizcaino, M., Mikolajewicz, U., Ziemen, F., Rodehacke, C. B., Greve, R., and van den Broeke, M. R. (2015), Coupled simulations of Greenland Ice Sheet and climate change up to A.D. 2300, Geophysical Research Letters, 42, doi: 10.1002/2014GL061142

Simulated Tree Growth across the Northern Hemisphere and the Seasonality of Climate Signals Encoded within Tree-ring Widths

NASA Astrophysics Data System (ADS)

Li, X.; St George, S.

2013-12-01

Both dendrochronological theory and regional and global networks of tree-ring width measurements indicate that trees can respond to climate variations quite differently from one location to another. To explain these geographical differences at hemispheric scale, we used a process-based model of tree-ring formation (the Vaganov-Shashkin model) to simulate tree growth at over 6000 locations across the Northern Hemisphere. We compared the seasonality and strength of climate signals in the simulated tree-ring records against parallel analysis conducted on a hemispheric network of real tree-ring observations, tested the ability of the model to reproduce behaviors that emerge from large networks of tree-ring widths and used the model outputs to explain why the network exhibits these behaviors. The simulated tree-ring records are consistent with observations with respect to the seasonality and relative strength of the encoded climate signals, and time-related changes in these climate signals can be predicted using the modeled relative growth rate due to temperature or soil moisture. The positive imprint of winter (DJF) precipitation is strongest in simulations from the American Southwest and northern Mexico as well as selected locations in the Mediterranean and central Asia. Summer (JJA) precipitation has higher positive correlations with simulations in the mid-latitudes, but some high-latitude coastal sites exhibit a negative association. The influence of summer temperature is mainly positive at high-latitude or high-altitude sites and negative in the mid-latitudes. The absolute magnitude of climate correlations are generally higher in simulations than in observations, but the pattern and geographical differences remain the same, demonstrating that the model has skill in reproducing tree-ring growth response to climate variability in the Northern Hemisphere. Because the model uses only temperature, precipitation and latitude as input and is not adjusted for species or other biological factors, the fact that the climate response of the simulations largely agrees with the observations may imply that climate, rather than biology, is the main factor that influences large-scale patterns of the climate information recorded by tree rings. Our results also suggest that the Vaganov-Shashkin model could be used to estimate the likely climate response of trees in ';frontier' areas that have not been sampled extensively. Seasonal Climate Correlations of Simulated Tree-ring Records

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Identifying the most hazardous synoptic meteorological conditions for Winter UK PM10 exceedences

NASA Astrophysics Data System (ADS)

Webber, Chris; Dacre, Helen; Collins, Bill; Masato, Giacomo

2016-04-01

Summary We investigate the relationship between synoptic scale meteorological variability and local scale pollution concentrations within the UK. Synoptic conditions representative of atmospheric blocking highlighted significant increases in UK PM10 concentration ([PM10]), with the probability of exceeding harmful [PM10] limits also increased. Once relationships had been diagnosed, The Met Office Unified Model (UM) was used to replicate these relationships, using idealised source regions of PM10. This helped to determine the PM10 source regions most influential throughout UK PM10 exceedance events and to test whether the model was capable of capturing the relationships between UK PM10 and atmospheric blocking. Finally, a time slice simulation for 2050-2060 helped to answer the question whether PM10 exceedance events are more likely to occur within a changing climate. Introduction Atmospheric blocking events are well understood to lead to conditions, conducive to pollution events within the UK. Literature shows that synoptic conditions with the ability to deflect the Northwest Atlantic storm track from the UK, often lead to the highest UK pollution concentrations. Rossby wave breaking (RWB) has been identified as a mechanism, which results in atmospheric blocking and its relationship with UK [PM10] is explored using metrics designed in Masato, et al., 2013. Climate simulations facilitated by the Met Office UM, enable these relationships between RWB and PM10 to be found within the model. Subsequently the frequency of events that lead to hazardous PM10 concentrations ([PM10]) in a future climate, can be determined, within a climate simulation. An understanding of the impact, meteorology has on UK [PM10] within a changing climate, will help inform policy makers, regarding the importance of limiting PM10 emissions, ensuring safe air quality in the future. Methodology and Results Three Blocking metrics were used to subset RWB into four categories. These RWB categories were all shown to increase UK [PM10] and to increase the probability of exceeding a UK [PM10] threshold, when they occurred within constrained regions. Further analysis highlighted that Omega Block events lead to the greatest probability of exceeding hazardous UK [PM10] limits. These events facilitated the advection of European PM10, while also providing stagnant conditions over the UK, facilitating PM10 accumulation. The Met Office UM was used and nudged to ERA-Interim Reanalysis wind and temperature fields, to replicate the relationships found using observed UK [PM10]. Inert tracers were implemented into the model to replicate UK PM10 source regions throughout Europe. The modelled tracers were seen to correlate well with observed [PM10] and Figure 1 highlights the correlations between a RWB metric and observed (a) and modelled (b) [PM10]. A further free running model simulation highlighted the deficiency of the Met Office UM in capturing RWB frequency, with a reduction over the Northwest Atlantic/ European region. A final time slice simulation was undertaken for the period 2050-2060, using Representative Concentration Pathway 8.5, which attempted to determine the change in frequency of UK PM10 exceedance events, due to changing meteorology, in a future climate. Conclusions RWB has been shown to increase UK [PM10] and to lead to greater probabilities of exceeding a harmful [PM10] threshold. Omega block events have been determined the most hazardous RWB subset and this is due to a combination of European advection and UK stagnation. Simulations within the Met Office UM were undertaken and the relationships seen between observed UK [PM10] and RWB were replicated within the model, using inert tracers. Finally, time slice simulations were undertaken, determining the change in frequency of UK [PM10] exceedance events within a changing climate. References Masato, G., Hoskins, B. J., Woolings, T., 2013; Wave-breaking Characteristics of Northern Hemisphere Winter Blocking: A Two-Dimensional Approach. J. Climate, 26, 4535-4549.

Evaluating meteo marine climatic model inputs for the investigation of coastal hydrodynamics

NASA Astrophysics Data System (ADS)

Bellafiore, D.; Bucchignani, E.; Umgiesser, G.

2010-09-01

One of the major aspects discussed in the recent works on climate change is how to provide information from the global scale to the local one. In fact the influence of sea level rise and changes in the meteorological conditions due to climate change in strategic areas like the coastal zone is at the base of the well known mitigation and risk assessment plans. The investigation of the coastal zone hydrodynamics, from a modeling point of view, has been the field for the connection between hydraulic models and ocean models and, in terms of process studies, finite element models have demonstrated their suitability in the reproduction of complex coastal morphology and in the capability to reproduce different spatial scale hydrodynamic processes. In this work the connection between two different model families, the climate models and the hydrodynamic models usually implemented for process studies, is tested. Together, they can be the most suitable tool for the investigation of climate change on coastal systems. A finite element model, SHYFEM (Shallow water Hydrodynamic Finite Element Model), is implemented on the Adriatic Sea, to investigate the effect of wind forcing datasets produced by different downscaling from global climate models in terms of surge and its coastal effects. The wind datasets are produced by the regional climate model COSMO-CLM (CIRA), and by EBU-POM model (Belgrade University), both downscaling from ECHAM4. As a first step the downscaled wind datasets, that have different spatial resolutions, has been analyzed for the period 1960-1990 to compare what is their capability to reproduce the measured wind statistics in the coastal zone in front of the Venice Lagoon. The particularity of the Adriatic Sea meteo climate is connected with the influence of the orography in the strengthening of winds like Bora, from North-East. The increase in spatial resolution permits the more resolved wind dataset to better reproduce meteorology and to provide a more realistic forcing for hydrodynamic simulations. After this analysis, effects on water level variations, under different wind forcing, has been analyzed to define what is the local effect on sea level changes in the coastal area of the North Adriatic. Surge statistics produced from different climate model forcings for the IPCC A1B scenario have been studied to provide local information on climate change effects on coastal hydrodynamics due to meteorological effect. This typology of application has been considered a suitable tool for coastal management and can be considered a study field that will increase its importance in the more general investigation on scale interaction processes as the effects of global scale climate phenomena on local areas.

The New England Climate Adaptation Project: Enhancing Local Readiness to Adapt to Climate Change through Role-Play Simulations

NASA Astrophysics Data System (ADS)

Rumore, D.; Kirshen, P. H.; Susskind, L.

2014-12-01

Despite scientific consensus that the climate is changing, local efforts to prepare for and manage climate change risks remain limited. How we can raise concern about climate change risks and enhance local readiness to adapt to climate change's effects? In this presentation, we will share the lessons learned from the New England Climate Adaptation Project (NECAP), a participatory action research project that tested science-based role-play simulations as a tool for educating the public about climate change risks and simulating collective risk management efforts. NECAP was a 2-year effort involving the Massachusetts Institute of Technology, the Consensus Building Institute, the National Estuarine Research Reserve System, and four coastal New England municipalities. During 2012-2013, the NECAP team produced downscaled climate change projections, a summary risk assessment, and a stakeholder assessment for each partner community. Working with local partners, we used these assessments to create a tailored, science-based role-play simulation for each site. Through a series of workshops in 2013, NECAP engaged between 115-170 diverse stakeholders and members of the public in each partner municipality in playing the simulation and a follow up conversation about local climate change risks and possible adaptation strategies. Data were collected through before-and-after surveys administered to all workshop participants, follow-up interviews with 25 percent of workshop participants, public opinion polls conducted before and after our intervention, and meetings with public officials. This presentation will report our research findings and explain how science-based role-play simulations can be used to help communicate local climate change risks and enhance local readiness to adapt.

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

NASA Astrophysics Data System (ADS)

Erickson, T. A.; Koziol, B. W.; Rood, R. B.

2011-12-01

The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

Risk assessment of climate systems for national security.

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

Backus, George A.; Boslough, Mark Bruce Elrick; Brown, Theresa Jean

2012-10-01

Climate change, through drought, flooding, storms, heat waves, and melting Arctic ice, affects the production and flow of resource within and among geographical regions. The interactions among governments, populations, and sectors of the economy require integrated assessment based on risk, through uncertainty quantification (UQ). This project evaluated the capabilities with Sandia National Laboratories to perform such integrated analyses, as they relate to (inter)national security. The combining of the UQ results from climate models with hydrological and economic/infrastructure impact modeling appears to offer the best capability for national security risk assessments.

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0)contribution to CMIP6

DOE PAGES

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; ...

2016-10-18

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of futuremore » climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.« less

The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; Hegerl, Gabriele; Knutti, Reto; Matthes, Katja; Santer, Benjamin D.; Stone, Daithi; Tebaldi, Claudia

2016-10-01

Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

Toward Surface Mass Balance Modeling over Antarctic Peninsula with Improved Snow/Ice Physics within WRF

NASA Astrophysics Data System (ADS)

Villamil-Otero, G.; Zhang, J.; Yao, Y.

2017-12-01

The Antarctic Peninsula (AP) has long been the focus of climate change studies due to its rapid environmental changes such as significantly increased glacier melt and retreat, and ice-shelf break-up. Progress has been continuously made in the use of regional modeling to simulate surface mass changes over ice sheets. Most efforts, however, focus on the ice sheets of Greenland with considerable fewer studies in Antarctica. In this study the Weather Research and Forecasting (WRF) model, which has been applied to the Antarctic region for weather modeling, is adopted to capture the past and future surface mass balance changes over AP. In order to enhance the capabilities of WRF model simulating surface mass balance over the ice surface, we implement various ice and snow processes within the WRF and develop a new WRF suite (WRF-Ice). The WRF-Ice includes a thermodynamic ice sheet model that improves the representation of internal melting and refreezing processes and the thermodynamic effects over ice sheet. WRF-Ice also couples a thermodynamic sea ice model to improve the simulation of surface temperature and fluxes over sea ice. Lastly, complex snow processes are also taken into consideration including the implementation of a snowdrift model that takes into account the redistribution of blowing snow as well as the thermodynamic impact of drifting snow sublimation on the lower atmospheric boundary layer. Intensive testing of these ice and snow processes are performed to assess the capability of WRF-Ice in simulating the surface mass balance changes over AP.

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

Effects of Climate Change, Urban Development, and Threatened and Endangered Species Management on Army Training Capabilities: Firing Ranges

DTIC Science & Technology

2016-01-01

Climate Assessment for Army Enterprise Planning Effects of Climate Change , Urban Development, and... Climate Assessment for Army Enterprise Planning ERDC/CERL TR-16-29 January 2016 Effects of Climate Change , Urban Development, and Threatened and...due to climate change factors. The effects of climate change on DoD in- stallations is increasing in significance and has the potential to impact

Equilibrium and Effective Climate Sensitivity

NASA Astrophysics Data System (ADS)

Rugenstein, M.; Bloch-Johnson, J.

2016-12-01

Atmosphere-ocean general circulation models, as well as the real world, take thousands of years to equilibrate to CO2 induced radiative perturbations. Equilibrium climate sensitivity - a fully equilibrated 2xCO2 perturbation - has been used for decades as a benchmark in model intercomparisons, as a test of our understanding of the climate system and paleo proxies, and to predict or project future climate change. Computational costs and limited time lead to the widespread practice of extrapolating equilibrium conditions from just a few decades of coupled simulations. The most common workaround is the "effective climate sensitivity" - defined through an extrapolation of a 150 year abrupt2xCO2 simulation, including the assumption of linear climate feedbacks. The definitions of effective and equilibrium climate sensitivity are often mixed up and used equivalently, and it is argued that "transient climate sensitivity" is the more relevant measure for predicting the next decades. We present an ongoing model intercomparison, the "LongRunMIP", to study century and millennia time scales of AOGCM equilibration and the linearity assumptions around feedback analysis. As a true ensemble of opportunity, there is no protocol and the only condition to participate is a coupled model simulation of any stabilizing scenario simulating more than 1000 years. Many of the submitted simulations took several years to conduct. As of July 2016 the contribution comprises 27 scenario simulations of 13 different models originating from 7 modeling centers, each between 1000 and 6000 years. To contribute, please contact the authors as soon as possible We present preliminary results, discussing differences between effective and equilibrium climate sensitivity, the usefulness of transient climate sensitivity, extrapolation methods, and the state of the coupled climate system close to equilibrium. Caption for the Figure below: Evolution of temperature anomaly and radiative imbalance of 22 simulations with 12 models (color indicates the model). 20 year moving average.

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.

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

A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.

Forward modeling of tree-ring data: a case study with a global network

NASA Astrophysics Data System (ADS)

Breitenmoser, P. D.; Frank, D.; Brönnimann, S.

2012-04-01

Information derived from tree-rings is one of the most powerful tools presently available for studying past climatic variability as well as identifying fundamental relationships between tree-growth and climate. Climate reconstructions are typically performed by extending linear relationships, established during the overlapping period of instrumental and climate proxy archives into the past. Such analyses, however, are limited by methodological assumptions, including stationarity and linearity of the climate-proxy relationship. We investigate climate and tree-ring data using the Vaganov-Shashkin-Lite (VS-Lite) forward model of tree-ring width formation to examine the relations among actual tree growth and climate (as inferred from the simulated chronologies) to reconstruct past climate variability. The VS-lite model has been shown to produce skill comparable to that achieved using classical dendrochronological statistical modeling techniques when applied on simulations of a network of North American tree-ring chronologies. Although the detailed mechanistic processes such as photosynthesis, storage, or cell processes are not modeled directly, the net effect of the dominating nonlinear climatic controls on tree-growth are implemented into the model by the principle of limiting factors and threshold growth response functions. The VS-lite model requires as inputs only latitude, monthly mean temperature and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the 20th century reanalysis project back to 1871. These simulated tree-ring chronologies are compared to the climate-driven variability in worldwide observed tree-ring chronologies from the International Tree Ring Database. Results point toward the suitability of the relationship among actual tree growth and climate (as inferred from the simulated chronologies) for use in global palaeoclimate reconstructions.

Climate resources for field ornithologists: what is climate, what do we know, and why should you care?

Treesearch

Daphne Gemmill

2005-01-01

As the ornithological community has become more aware of natural climate variability (as opposed to weather) impacts on the life histories of birds, especially seabirds, the meteorological community has been advancing our knowledge and predictive capabilities. The latest climate information, however, is slow to transfer to the ornithological community. Climate...

Comparison of Solar and Other Influences on Long-term Climate

NASA Technical Reports Server (NTRS)

Hansen, James E.; Lacis, Andrew A.; Ruedy, Reto A.

1990-01-01

Examples are shown of climate variability, and unforced climate fluctuations are discussed, as evidenced in both model simulations and observations. Then the author compares different global climate forcings, a comparison which by itself has significant implications. Finally, the author discusses a new climate simulation for the 1980s and 1990s which incorporates the principal known global climate forcings. The results indicate a likelihood of rapid global warming in the early 1990s.

Seasonal prediction and predictability of Eurasian spring snow water equivalent in NCEP Climate Forecast System version 2 reforecasts

NASA Astrophysics Data System (ADS)

He, Qiong; Zuo, Zhiyan; Zhang, Renhe; Zhang, Ruonan

2018-01-01

The spring snow water equivalent (SWE) over Eurasia plays an important role in East Asian and Indian monsoon rainfall. This study evaluates the seasonal prediction capability of NCEP Climate Forecast System version 2 (CFSv2) retrospective forecasts (1983-2010) for the Eurasian spring SWE. The results demonstrate that CFSv2 is able to represent the climatological distribution of the observed Eurasian spring SWE with a lead time of 1-3 months, with the maximum SWE occurring over western Siberia and Northeastern Europe. For a longer lead time, the SWE is exaggerated in CFSv2 because the start of snow ablation in CFSv2 lags behind that of the observation, and the simulated snowmelt rate is less than that in the observation. Generally, CFSv2 can simulate the interannual variations of the Eurasian spring SWE 1-5 months ahead of time but with an exaggerated magnitude. Additionally, the downtrend in CFSv2 is also overestimated. Because the initial conditions (ICs) are related to the corresponding simulation results significantly, the robust interannual variability and the downtrend in the ICs are most likely the causes for these biases. Moreover, CFSv2 exhibits a high potential predictability for the Eurasian spring SWE, especially the spring SWE over Siberia, with a lead time of 1-5 months. For forecasts with lead times longer than 5 months, the model predictability gradually decreases mainly due to the rapid decrease in the model signal.

Fostering Hope in Climate Change Educators

ERIC Educational Resources Information Center

Swim, Janet K.; Fraser, John

2013-01-01

Climate Change is a complex set of issues with large social and ecological risks. Addressing it requires an attentive and climate literate population capable of making informed decisions. Informal science educators are well-positioned to teach climate science and motivate engagement, but many have resisted the topic because of self-doubt about…

Development of a dynamic coupled hydro-geomechanical code and its application to induced seismicity

NASA Astrophysics Data System (ADS)

Miah, Md Mamun

This research describes the importance of a hydro-geomechanical coupling in the geologic sub-surface environment from fluid injection at geothermal plants, large-scale geological CO2 sequestration for climate mitigation, enhanced oil recovery, and hydraulic fracturing during wells construction in the oil and gas industries. A sequential computational code is developed to capture the multiphysics interaction behavior by linking a flow simulation code TOUGH2 and a geomechanics modeling code PyLith. Numerical formulation of each code is discussed to demonstrate their modeling capabilities. The computational framework involves sequential coupling, and solution of two sub-problems- fluid flow through fractured and porous media and reservoir geomechanics. For each time step of flow calculation, pressure field is passed to the geomechanics code to compute effective stress field and fault slips. A simplified permeability model is implemented in the code that accounts for the permeability of porous and saturated rocks subject to confining stresses. The accuracy of the TOUGH-PyLith coupled simulator is tested by simulating Terzaghi's 1D consolidation problem. The modeling capability of coupled poroelasticity is validated by benchmarking it against Mandel's problem. The code is used to simulate both quasi-static and dynamic earthquake nucleation and slip distribution on a fault from the combined effect of far field tectonic loading and fluid injection by using an appropriate fault constitutive friction model. Results from the quasi-static induced earthquake simulations show a delayed response in earthquake nucleation. This is attributed to the increased total stress in the domain and not accounting for pressure on the fault. However, this issue is resolved in the final chapter in simulating a single event earthquake dynamic rupture. Simulation results show that fluid pressure has a positive effect on slip nucleation and subsequent crack propagation. This is confirmed by running a sensitivity analysis that shows an increase in injection well distance results in delayed slip nucleation and rupture propagation on the fault.

Simulations of the Montréal urban heat island

NASA Astrophysics Data System (ADS)

Roberge, François; Sushama, Laxmi; Fanta, Gemechu

2017-04-01

The current population of Montreal is around 3.8 million and this number is projected to go up in the coming years to decades, which will lead to vast expansion of urban areas. It is well known that urban morphology impacts weather and climate, and therefore should be taken into consideration in urban planning. This is particularly important in the context of a changing climate, as the intensity and frequency of temperature extremes such as hot spells are projected to increase in future climate, and Urban Heat Island (UHI) can potentially raise already stressful temperatures during such events, which can have significant effects on human health and energy consumption. High-resolution regional climate model simulations can be utilized to understand better urban-weather/climate interactions in current and future climates, particularly the spatio-temporal characteristics of the Urban Heat Island and its impact on other weather/climate characteristics such as urban flows, precipitation etc. This paper will focus on two high-resolution (250 m) simulations performed with (1) the Canadian Land Surface Scheme (CLASS) and (2) CLASS and TEB (Town Energy Balance) model; TEB is a single layer urban canopy model and is used to model the urban fractions. The two simulations are performed over a domain covering Montreal for the 1960-2015 period, driven by atmospheric forcing data coming from a high-resolution Canadian Regional Climate Model (CRCM5) simulation, driven by ERA-Interim. The two simulations are compared to assess the impact of urban regions on selected surface fields and the simulation with both CLASS and TEB is then used to study the spatio-temporal characteristics of the UHI over the study domain. Some preliminary results from a coupled simulation, i.e. CRCM5+CLASS+TEB, for selected years, including extreme warm years, will also be presented.

Increasing the relevance of GCM simulations for Climate Services

NASA Astrophysics Data System (ADS)

Smith, L. A.; Suckling, E.

2012-12-01

The design and interpretation of model simulations for climate services differ significantly from experimental design for the advancement of the fundamental research on predictability that underpins it. Climate services consider the sources of best information available today; this calls for a frank evaluation of model skill in the face of statistical benchmarks defined by empirical models. The fact that Physical simulation models are thought to provide the only reliable method for extrapolating into conditions not previously observed has no bearing on whether or not today's simulation models outperform empirical models. Evidence on the length scales on which today's simulation models fail to outperform empirical benchmarks is presented; it is illustrated that this occurs even on global scales in decadal prediction. At all timescales considered thus far (as of July 2012), predictions based on simulation models are improved by blending with the output of statistical models. Blending is shown to be more interesting in the climate context than it is in the weather context, where blending with a history-based climatology is straightforward. As GCMs improve and as the Earth's climate moves further from that of the last century, the skill from simulation models and their relevance to climate services is expected to increase. Examples from both seasonal and decadal forecasting will be used to discuss a third approach that may increase the role of current GCMs more quickly. Specifically, aspects of the experimental design in previous hind cast experiments are shown to hinder the use of GCM simulations for climate services. Alternative designs are proposed. The value in revisiting Thompson's classic approach to improving weather forecasting in the fifties in the context of climate services is discussed.

Community-based benchmarking of the CMIP DECK experiments

NASA Astrophysics Data System (ADS)

Gleckler, P. J.

2015-12-01

A diversity of community-based efforts are independently developing "diagnostic packages" with little or no coordination between them. A short list of examples include NCAR's Climate Variability Diagnostics Package (CVDP), ORNL's International Land Model Benchmarking (ILAMB), LBNL's Toolkit for Extreme Climate Analysis (TECA), PCMDI's Metrics Package (PMP), the EU EMBRACE ESMValTool, the WGNE MJO diagnostics package, and CFMIP diagnostics. The full value of these efforts cannot be realized without some coordination. As a first step, a WCRP effort has initiated a catalog to document candidate packages that could potentially be applied in a "repeat-use" fashion to all simulations contributed to the CMIP DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. Some coordination of community-based diagnostics has the additional potential to improve how CMIP modeling groups analyze their simulations during model-development. The fact that most modeling groups now maintain a "CMIP compliant" data stream means that in principal without much effort they could readily adopt a set of well organized diagnostic capabilities specifically designed to operate on CMIP DECK experiments. Ultimately, a detailed listing of and access to analysis codes that are demonstrated to work "out of the box" with CMIP data could enable model developers (and others) to select those codes they wish to implement in-house, potentially enabling more systematic evaluation during the model development process.

Projected hydrologic changes in monsoon-dominated Himalaya Mountain basins with changing climate and deforestation

NASA Astrophysics Data System (ADS)

Neupane, Ram P.; White, Joseph D.; Alexander, Sara E.

2015-06-01

In mountain headwaters, climate and land use changes affect short and long term site water budgets with resultant impacts on landslide risk, hydropower generation, and sustainable agriculture. To project hydrologic change associated with climate and land use changes in the Himalaya Mountains, we used the Soil and Water Assessment Tool (SWAT) calibrated for the Tamor and Seti River basins located at eastern and western margins of Nepal. Future climate change was modeled using averaged temperature and precipitation for 2080 derived from Special Report on Emission Scenarios (SRES) (B1, A1B and A2) of 16 global circulation models (GCMs). Land use change was modeled spatially and included expansion of (1) agricultural land, (2) grassland, and (3) human settlement area that were produced by considering existing land use with projected changes associated with viability of elevation and slope characteristics of the basins capable of supporting different land use type. From these simulations, higher annual stream discharge was found for all GCM-derived scenarios compared to a baseline simulation with maximum increases of 13 and 8% in SRES-A2 and SRES-A1B for the Tamor and Seti basins, respectively. On seasonal basis, we assessed higher precipitation during monsoon season in all scenarios that corresponded with higher stream discharge of 72 and 68% for Tamor and Seti basins, respectively. This effect appears to be geographically important with higher influence in the eastern Tamor basin potentially due to longer and stronger monsoonal period of that region. However, we projected minimal changes in stream discharge for the land use scenarios potentially due to higher water transmission to groundwater reservoirs associated with fractures of the Himalaya Mountains rather than changes in surface runoff. However, when combined the effects of climate and land use changes, discharge was moderately increased indicating counteracting mechanisms of hydrologic yield in these mountains. Better understanding of potential hydrologic response to climate and land use changes in these basins might be crucial for national and transnational water management.

Regional climate and vegetation response to orbital forcing within the mid-Pliocene Warm Period: A study using HadCM3

NASA Astrophysics Data System (ADS)

Prescott, C. L.; Dolan, A. M.; Haywood, A. M.; Hunter, S. J.; Tindall, J. C.

2018-02-01

Regional climate and environmental variability in response to orbital forcing during interglacial events within the mid-Piacenzian (Pliocene) Warm Period (mPWP; 3.264-3.025 Ma) has been rarely studied using climate and vegetation models. Here we use climate and vegetation model simulations to predict changes in regional vegetation patterns in response to orbital forcing for four different interglacial events within the mPWP (Marine Isotope Stages (MIS) G17, K1, KM3 and KM5c). The efficacy of model-predicted changes in regional vegetation is assessed by reference to selected high temporal resolution palaeobotanical studies that are theoretically capable of discerning vegetation patterns for the selected interglacial stages. Annual mean surface air temperatures for the studied interglacials are between 0.4 °C to 0.7 °C higher than a comparable Pliocene experiment using modern orbital parameters. Increased spring/summer and reduced autumn/winter insolation in the Northern Hemisphere during MIS G17, K1 and KM3 enhances seasonality in surface air temperature. The two most robust and notable regional responses to this in vegetation cover occur in North America and continental Eurasia, where forests are replaced by more open-types of vegetation (grasslands and shrubland). In these regions our model results appear to be inconsistent with local palaeobotanical data. The orbitally driven changes in seasonal temperature and precipitation lead to a 30% annual reduction in available deep soil moisture (2.0 m from surface), a critical parameter for forest growth, and subsequent reduction in the geographical coverage of forest-type vegetation; a phenomenon not seen in comparable simulations of Pliocene climate and vegetation run with a modern orbital configuration. Our results demonstrate the importance of examining model performance under a range of realistic orbital forcing scenarios within any defined time interval (e.g. mPWP). Additional orbitally resolved records of regional vegetation are needed to further examine the validity of model-predicted regional climate and vegetation responses in greater detail.

A Petascale Non-Hydrostatic Atmospheric Dynamical Core in the HOMME Framework

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

Tufo, Henry

The High-Order Method Modeling Environment (HOMME) is a framework for building scalable, conserva- tive atmospheric models for climate simulation and general atmospheric-modeling applications. Its spatial discretizations are based on Spectral-Element (SE) and Discontinuous Galerkin (DG) methods. These are local methods employing high-order accurate spectral basis-functions that have been shown to perform well on massively parallel supercomputers at any resolution and scale particularly well at high resolutions. HOMME provides the framework upon which the CAM-SE community atmosphere model dynamical-core is constructed. In its current incarnation, CAM-SE employs the hydrostatic primitive-equations (PE) of motion, which limits its resolution to simulations coarser thanmore » 0.1 per grid cell. The primary objective of this project is to remove this resolution limitation by providing HOMME with the capabilities needed to build nonhydrostatic models that solve the compressible Euler/Navier-Stokes equations.« less

High-order hydrodynamic algorithms for exascale computing

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

Morgan, Nathaniel Ray

Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broadmore » range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.« less

Urban-Climate Adaptation Tool: Optimizing Green Infrastructure

NASA Astrophysics Data System (ADS)

Fellows, J. D.; Bhaduri, B. L.

2016-12-01

Cities have an opportunity to become more resilient to future climate change and green through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection and other environmental information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). The initial focus of Urban-CAT is to optimize the placement of green infrastructure (e.g., green roofs, porous pavements, retention basins, etc.) to be better control stormwater runoff and lower the ambient urban temperature. Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic and other environmental data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. This presentation will highlight the methods that drive each of the modules, demo some of the capabilities using Knoxville Tennessee as a case study, and discuss the challenges of working with communities to incorporate climate change into their planning. Next steps on Urban-CAT is to additional capabilities to create a comprehensive climate adaptation tool, including energy, transportation, health, and other key urban services.

Climate downscaling over South America for 1971-2000: application in SMAP rainfall-runoff model for Grande River Basin

NASA Astrophysics Data System (ADS)

da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio

2018-03-01

This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate model and that data from regional models must be bias-corrected so as to improve their results.

The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

NASA Astrophysics Data System (ADS)

Betts, R. A.; Cox, P. M.; Collins, M.; Harris, P. P.; Huntingford, C.; Jones, C. D.

A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO2 is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO2 was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO2 contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO2 and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.

Local control on precipitation in a fully coupled climate-hydrology model.

PubMed

Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

2016-03-10

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

Local control on precipitation in a fully coupled climate-hydrology model

PubMed Central

Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

2016-01-01

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

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.

Simulation of the present-day climate with the climate model INMCM5

NASA Astrophysics Data System (ADS)

Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykossov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Iakovlev, N. G.

2017-12-01

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

Spatial distirbution of Antarctic mass flux due to iceberg transport

NASA Astrophysics Data System (ADS)

Comeau, Darin; Hunke, Elizabeth; Turner, Adrian

Under a changing climate that sees amplified warming in the polar regions, the stability of the West Antarctic ice sheet and its impact on sea level rise is of great importance. Icebergs are at the interface of the land-ice, ocean, and sea ice systems, and represent approximately half of the mass flux from the Antarctic ice sheet to the ocean. Calved icebergs transport freshwater away from the coast and exchange heat with the ocean, thereby affecting stratification and circulation, with subsequent indirect thermodynamic effects to the sea ice system. Icebergs also dynamically interact with surrounding sea ice pack, as well as serving as nutrient sources for biogeochemical activity. The spatial pattern of these fluxes transported from the continent to the ocean is generally poorly represented in current global climate models. We are implementing an iceberg model into the new Accelerated Climate Model for Energy (ACME) within the MPAS-Seaice model, which uses a variable resolution, unstructured grid framework. This capability will allow for full coupling with the land ice model to inform calving fluxes, and the ocean model for freshwater and heat exchange, giving a complete representation of the iceberg lifecycle and increasing the fidelity of ACME southern cryosphere simulations.

Integrating SPOT-VEGETATION 13-yr time series and land-surface modelling to forecast the terrestrial carbon dynamics in a changing climate - The VEGECLIM project: achievements and lessons learned

NASA Astrophysics Data System (ADS)

Defourny, Pierre; Verbeeck, Hans; Moreau, Inès; De Weirdt, Marjolein; Verhegghen, Astrid; Kibambe-Lubamba, Jean-Paul; Jungers, Quentin; Maignan, Fabienne; Najdovski, Nicolas; Poulter, Benjamin; MacBean, Natasha; Peylin, Philippe

2014-05-01

Vegetation is a major carbon sink and is as such a key component of the international response to climate change caused by the build-up of greenhouse gases in the atmosphere. However, anthropogenic disturbances like deforestation are the primary mechanism that changes ecosystems from carbon sinks to sources, and are hardly included in the current carbon modelling approaches. Moreover, in tropical regions, the seasonal/interannual variability of carbon fluxes is still uncertain and a weak or even no seasonality is taken into account in global vegetation models. In the context of climate change and mitigation policies like "Reducing Emissions from Deforestation and Forest Degradation in Developing Countries" (REDD), it is particularly important to be able to quantify and forecast the vegetation dynamics and carbon fluxes in these regions. The overall objective of the VEGECLIM project is to increase our knowledge on the terrestrial carbon cycle in tropical regions and to improve the forecast of the vegetation dynamics and carbon stocks and fluxes under different climate-change and deforestation scenarios. Such an approach aims to determine whether the African terrestrial carbon balance will remain a net sink or could become a carbon source by the end of the century, according to different climate-change and deforestation scenarios. The research strategy is to integrate the information of the land surface characterizations obtained from 13 years of consistent SPOT-VEGETATION time series (land cover, vegetation phenology through vegetation indices such as the Enhanced Vegetation Index (EVI)) as well as in-situ carbon flux data into the process based ORCHIDEE global vegetation model, capable of simulating vegetation dynamics and carbon balance. Key challenge of this project was to bridge the gap between the land cover and the land surface model teams. Several improvements of the ORCHIDEE model have been realized such as a new seasonal leaf dynamics for tropical evergreen forests, the introduction of spatial soil phosphorus to improve the spatial distribution of simulated woody biomass and an assimilation of smoothed seasonal pattern of satellite-based EVI used as a proxy to vegetation productivity. The outputs of the ORCHIDEE simulations over both Amazon and Congo Basins are discussed with regards to the observed phenology by remote sensing.

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

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

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less

Current and future patterns of fire-induced forest degradation in Amazonia

NASA Astrophysics Data System (ADS)

De Faria, Bruno L.; Brando, Paulo M.; Macedo, Marcia N.; Panday, Prajjwal K.; Soares-Filho, Britaldo S.; Coe, Michael T.

2017-09-01

Amazon droughts directly increase forest flammability by reducing forest understory air and fuel moisture. Droughts also increase forest flammability indirectly by decreasing soil moisture, triggering leaf shedding, branch loss, and tree mortality—all of which contribute to increased fuel loads. These direct and indirect effects can cause widespread forest fires that reduce forest carbon stocks in the Amazon, with potentially important consequences for the global carbon cycle. These processes are expected to become more widespread, common, and intense as global climate changes, yet the mechanisms linking droughts, wildfires, and associated changes in carbon stocks remain poorly understood. Here, we expanded the capabilities of a dynamic forest carbon model to better represent (1) drought effects on carbon and fuel dynamics and (2) understory fire behavior and severity. We used the refined model to quantify changes in Pan-Amazon live carbon stocks as a function of the maximum climatological water deficit (MCWD) and fire intensity, under both historical and future climate conditions. We found that the 2005 and 2010 droughts increased potential fire intensity by 226 kW m-1 and 494 kW m-1, respectively. These increases were due primarily to increased understory dryness (109 kW m-1 in 2005; 124 kW m-1 in 2010) and altered forest structure (117 kW m-1 in 2005; 370 kW m-1 in 2010) effects. Combined, these historic droughts drove total simulated reductions in live carbon stocks of 0.016 (2005) and 0.027 (2010) PgC across the Amazon Basin. Projected increases in future fire intensity increased simulated carbon losses by up to 90% per unit area burned, compared with modern climate. Increased air temperature was the primary driver of changes in simulated future fire intensity, while reduced precipitation was secondary, particularly in the eastern portion of the Basin. Our results show that fire-drought interactions strongly affect live carbon stocks and that future climate change, combined with the synergistic effects of drought on forest flammability, may strongly influence the stability of tropical forests in the future.

Final Technical Report for DE-SC0005467

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

Broccoli, Anthony J.

2014-09-14

The objective of this project is to gain a comprehensive understanding of the key atmospheric mechanisms and physical processes associated with temperature extremes in order to better interpret and constrain uncertainty in climate model simulations of future extreme temperatures. To achieve this objective, we first used climate observations and a reanalysis product to identify the key atmospheric circulation patterns associated with extreme temperature days over North America during the late twentieth century. We found that temperature extremes were associated with distinctive signatures in near-surface and mid-tropospheric circulation. The orientations and spatial scales of these circulation anomalies vary with latitude, season,more » and proximity to important geographic features such as mountains and coastlines. We next examined the associations between daily and monthly temperature extremes and large-scale, recurrent modes of climate variability, including the Pacific-North American (PNA) pattern, the northern annular mode (NAM), and the El Niño-Southern Oscillation (ENSO). The strength of the associations are strongest with the PNA and NAM and weaker for ENSO, and also depend upon season, time scale, and location. The associations are stronger in winter than summer, stronger for monthly than daily extremes, and stronger in the vicinity of the centers of action of the PNA and NAM patterns. In the final stage of this project, we compared climate model simulations of the circulation patterns associated with extreme temperature days over North America with those obtained from observations. Using a variety of metrics and self-organizing maps, we found the multi-model ensemble and the majority of individual models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) generally capture the observed patterns well, including their strength and as well as variations with latitude and season. The results from this project indicate that current models are capable of simulating the large-scale meteorological patterns associated with daily temperature extremes and they suggest that such models can be used to evaluate the extent to which changes in atmospheric circulation will influence future changes in temperature extremes.« less

Simulated crop yield in response to changes in climate and agricultural practices: results from a simple process based model

NASA Astrophysics Data System (ADS)

Caldararu, S.; Smith, M. J.; Purves, D.; Emmott, S.

2013-12-01

Global agriculture will, in the future, be faced with two main challenges: climate change and an increase in global food demand driven by an increase in population and changes in consumption habits. To be able to predict both the impacts of changes in climate on crop yields and the changes in agricultural practices necessary to respond to such impacts we currently need to improve our understanding of crop responses to climate and the predictive capability of our models. Ideally, what we would have at our disposal is a modelling tool which, given certain climatic conditions and agricultural practices, can predict the growth pattern and final yield of any of the major crops across the globe. We present a simple, process-based crop growth model based on the assumption that plants allocate above- and below-ground biomass to maintain overall carbon optimality and that, to maintain this optimality, the reproductive stage begins at peak nitrogen uptake. The model includes responses to available light, water, temperature and carbon dioxide concentration as well as nitrogen fertilisation and irrigation. The model is data constrained at two sites, the Yaqui Valley, Mexico for wheat and the Southern Great Plains flux site for maize and soybean, using a robust combination of space-based vegetation data (including data from the MODIS and Landsat TM and ETM+ instruments), as well as ground-based biomass and yield measurements. We show a number of climate response scenarios, including increases in temperature and carbon dioxide concentrations as well as responses to irrigation and fertiliser application.

Earth System Grid II (ESG): Turning Climate Model Datasets Into Community Resources

NASA Astrophysics Data System (ADS)

Williams, D.; Middleton, D.; Foster, I.; Nevedova, V.; Kesselman, C.; Chervenak, A.; Bharathi, S.; Drach, B.; Cinquni, L.; Brown, D.; Strand, G.; Fox, P.; Garcia, J.; Bernholdte, D.; Chanchio, K.; Pouchard, L.; Chen, M.; Shoshani, A.; Sim, A.

2003-12-01

High-resolution, long-duration simulations performed with advanced DOE SciDAC/NCAR climate models will produce tens of petabytes of output. To be useful, this output must be made available to global change impacts researchers nationwide, both at national laboratories and at universities, other research laboratories, and other institutions. To this end, we propose to create a new Earth System Grid, ESG-II - a virtual collaborative environment that links distributed centers, users, models, and data. ESG-II will provide scientists with virtual proximity to the distributed data and resources that they require to perform their research. The creation of this environment will significantly increase the scientific productivity of U.S. climate researchers by turning climate datasets into community resources. In creating ESG-II, we will integrate and extend a range of Grid and collaboratory technologies, including the DODS remote access protocols for environmental data, Globus Toolkit technologies for authentication, resource discovery, and resource access, and Data Grid technologies developed in other projects. We will develop new technologies for (1) creating and operating "filtering servers" capable of performing sophisticated analyses, and (2) delivering results to users. In so doing, we will simultaneously contribute to climate science and advance the state of the art in collaboratory technology. We expect our results to be useful to numerous other DOE projects. The three-year R&D program will be undertaken by a talented and experienced team of computer scientists at five laboratories (ANL, LBNL, LLNL, NCAR, ORNL) and one university (ISI), working in close collaboration with climate scientists at several sites.

Projected Changes on the Global Surface Wave Drift Climate towards the END of the Twenty-First Century

NASA Astrophysics Data System (ADS)

Carrasco, Ana; Semedo, Alvaro; Behrens, Arno; Weisse, Ralf; Breivik, Øyvind; Saetra, Øyvind; Håkon Christensen, Kai

2016-04-01

The global wave-induced current (the Stokes Drift - SD) is an important feature of the ocean surface, with mean values close to 10 cm/s along the extra-tropical storm tracks in both hemispheres. Besides the horizontal displacement of large volumes of water the SD also plays an important role in the ocean mix-layer turbulence structure, particularly in stormy or high wind speed areas. The role of the wave-induced currents in the ocean mix-layer and in the sea surface temperature (SST) is currently a hot topic of air-sea interaction research, from forecast to climate ranges. The SD is mostly driven by wind sea waves and highly sensitive to changes in the overlaying wind speed and direction. The impact of climate change in the global wave-induced current climate will be presented. The wave model WAM has been forced by the global climate model (GCM) ECHAM5 wind speed (at 10 m height) and ice, for present-day and potential future climate conditions towards the end of the end of the twenty-first century, represented by the Intergovernmental Panel for Climate Change (IPCC) CMIP3 (Coupled Model Inter-comparison Project phase 3) A1B greenhouse gas emission scenario (usually referred to as a ''medium-high emissions'' scenario). Several wave parameters were stored as output in the WAM model simulations, including the wave spectra. The 6 hourly and 0.5°×0.5°, temporal and space resolution, wave spectra were used to compute the SD global climate of two 32-yr periods, representative of the end of the twentieth (1959-1990) and twenty-first (1969-2100) centuries. Comparisons of the present climate run with the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-40 reanalysis are used to assess the capability of the WAM-ECHAM5 runs to produce realistic SD results. This study is part of the WRCP-JCOMM COWCLIP (Coordinated Ocean Wave Climate Project) effort.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

The Agriculture Model Intercomparison and Improvement Project (AgMIP) (Invited)

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2010-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and world agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Historical period results will spur model improvement and interaction among major modeling groups, while future period results will lead directly to tests of adaptation and mitigation strategies across a range of scales. AgMIP will consist of a multi-scale impact assessment utilizing the latest methods for climate and agricultural scenario generation. Scenarios and modeling protocols will be distributed on the web, and multi-model results will be collated and analyzed to ensure the widest possible coverage of agricultural crops and regions. AgMIP will place regional changes in agricultural production in a global context that reflects new trading opportunities, imbalances, and shortages in world markets resulting from climate change and other driving forces for food supply. Such projections are essential inputs from the Vulnerability, Impacts, and Adaptation (VIA) research community to the Intergovernmental Panel on Climate Change Fifth Assessment (AR5), now underway, and the UN Framework Convention on Climate Change. They will set the context for local-scale vulnerability and adaptation studies, supply test scenarios for national-scale development of trade policy instruments, provide critical information on changing supply and demand for water resources, and elucidate interactive effects of climate change and land use change. AgMIP will not only provide crucially-needed new global estimates of how climate change will affect food supply and hunger in the agricultural regions of the world, but it will also build the capabilities of developing countries to estimate how climate change will affect their supply and demand for food.

Emergent properties of climate-vegetation feedbacks in the North American Monsoon Macrosystem

NASA Astrophysics Data System (ADS)

Mathias, A.; Niu, G.; Zeng, X.

2012-12-01

The ability of ecosystems to adapt naturally to climate change and associated disturbances (e.g. wildfires, spread of invasive species) is greatly affected by the stability of feedback interactions between climate and vegetation. In order to study climate-vegetation interactions, such as CO2 and H2O exchange in the North American Monsoon System (NAMS), we plan to couple a community land surface model (NoahMP or CLM) used in regional climate models (WRF) with an individual based, spatially explicit vegetation model (ECOTONE). Individual based modeling makes it possible to link individual plant traits with properties of plant communities. Community properties, such as species composition and species distribution arise from dynamic interactions of individual plants with each other, and with their environment. Plants interact with each other through intra- and interspecific competition for resources (H2O, nitrogen), and the outcome of these interactions depends on the properties of the plant community and the environment itself. In turn, the environment is affected by the resulting change in community structure, which may have an impact on the drivers of climate change. First, we performed sensitivity tests of ECOTONE to assess its ability to reproduce vegetation distribution in the NAMS. We compared the land surface model and ECOTONE with regard to their capability to accurately simulate soil moisture, CO2 flux and above ground biomass. For evaluating the models we used the eddy-correlation sensible and latent heat fluxes, CO2 flux and observations of other climate and environmental variables (e.g. soil temperature and moisture) from the Santa Rita experimental range. The model intercomparison helped us understand the advantages and disadvantages of each model, providing us guidance for coupling the community land surface model (NoahMP or CLM) with ECOTONE.

Validation of Multibody Program to Optimize Simulated Trajectories II Parachute Simulation with Interacting Forces

NASA Technical Reports Server (NTRS)

Raiszadeh, Behzad; Queen, Eric M.; Hotchko, Nathaniel J.

2009-01-01

A capability to simulate trajectories of multiple interacting rigid bodies has been developed, tested and validated. This capability uses the Program to Optimize Simulated Trajectories II (POST 2). The standard version of POST 2 allows trajectory simulation of multiple bodies without force interaction. In the current implementation, the force interaction between the parachute and the suspended bodies has been modeled using flexible lines, allowing accurate trajectory simulation of the individual bodies in flight. The POST 2 multibody capability is intended to be general purpose and applicable to any parachute entry trajectory simulation. This research paper explains the motivation for multibody parachute simulation, discusses implementation methods, and presents validation of this capability.

Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

NASA Astrophysics Data System (ADS)

Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

2015-04-01

At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

Simulated Extreme Prepitation Indices over Northeast Brasil in Current Climate and Future Scenarios RCP4.5 and RCP8.5

NASA Astrophysics Data System (ADS)

Wender Santiago Marinho, Marcos; Araújo Costa, Alexandre; Cassain Sales, Domingo; Oliveira Guimarães, Sullyandro; Mariano da Silva, Emerson; das Chagas Vasconcelos Júnior, Francisco

2013-04-01

In this study, we analyzed extreme precipitation indices, for present and future modeled climates over Northeast of Brazil (NEB), from CORDEX simulations over the domain of Tropical Americas. The period for the model validation was from 1989-2007, using data from the European Center (ECWMF) Reanalysis, ERA-INTERIM, as input to drive the regional model (RAMS 6.0). Reanalysis data were assimilated via both lateral boundaries and the entire domain (a much weaker "central nudging"). Six indices of extreme precipitation were calculated over NEB: the average number of days above 10, 20 and 30 mm in one year (R10, R20, R30), the number of consecutive dry days (CDD), the number of consecutive wet days (CWD) and the maximum rainfall in five consecutive days (RX5). Those indices were compared against two independent databases: MERRA (Modern Era Retrospective analysis for Research and Applications) and TRMM (Tropical Rainfall Measuring Mission). After validation, climate simulations were performed for the present climate (1985-2005) and short-term (2015-2035), mid-term (2045-2065) and long-term (2079 to 2099) future climates for two scenarios: RCP 4.5 and RCP 8.5, nesting RAMS into HadGEM2-ES global model (a participant of CMIP5). Along with the indices, we also calculated Probability Distribution Functions (PDFs) to study the behavior of daily precipitation in the present and by the end of the 21st century (2079 to 2099) to assess possible changes under RCPs 4.5 and 8.5. The regional model is capable of representing relatively well the extreme precipitation indices for current climate, but there is some difficulties in performing a proper validation since the observed databases disagree significantly. Future projections show significant changes in most extreme indices. Rnn generally tend to increase, especially under RCP8.5. More significant changes are projected for the long-term period, under RCP8.5, which shows a pronounced R30 enhancement over northern states. CDD tends to decrease over most of NEB in the short but this trend is reverted toward the end of the century in both scenarios with a significant increase in the duration of the dry season over Northwestern and Eastern NEB (exceeding 50 days over certain areas), whereas projected CWD changes are smaller. Rx5 shows a general increasing trend especially in the long term period,under RCP8.5.

NASA Tools for Climate Impacts on Water Resources

NASA Technical Reports Server (NTRS)

Toll, David; Doorn, Brad

2010-01-01

Climate and environmental change are expected to fundamentally alter the nation's hydrological cycle and water availability. Satellites provide global or near-global coverage using instruments, allowing for consistent, well-calibrated, and equivalent-quality data of the Earth system. A major goal for NASA climate and environmental change research is to create multi-instrument data sets to span the multi-decadal time scales of climate change and to combine these data with those from modeling and surface-based observing systems to improve process understanding and predictions. NASA and Earth science data and analyses will ultimately enable more accurate climate prediction, and characterization of uncertainties. NASA's Applied Sciences Program works with other groups, including other federal agencies, to transition demonstrated observational capabilities to operational capabilities. A summary of some of NASA tools for improved water resources management will be presented.

System and Method for Providing a Climate Data Analytic Services Application Programming Interface Distribution Package

NASA Technical Reports Server (NTRS)

Tamkin, Glenn S. (Inventor); Duffy, Daniel Q. (Inventor); Schnase, John L. (Inventor)

2016-01-01

A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface distribution package. The example system can provide various components. The system provides a climate data analytic services application programming interface library that enables software applications running on a client device to invoke the capabilities of a climate data analytic service. The system provides a command-line interface that provides a means of interacting with a climate data analytic service by issuing commands directly to the system's server interface. The system provides sample programs that call on the capabilities of the application programming interface library and can be used as templates for the construction of new client applications. The system can also provide test utilities, build utilities, service integration utilities, and documentation.

Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.; Supit, I.

2012-06-01

Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.

Climate impacts on palm oil yields in the Nigerian Niger Delta

NASA Astrophysics Data System (ADS)

Okoro, Stanley U.; Schickhoff, Udo; Boehner, Juergen; Schneider, Uwe A.; Huth, Neil

2016-04-01

Palm oil production has increased in recent decades and is estimated to increase further. The optimal role of palm oil production, however, is controversial because of resource conflicts with alternative land uses. Local conditions and climate change affect resource competition and the desirability of palm oil production. Based on this, crop yield simulations using different climate model output under different climate scenarios could be important tool in addressing the problem of uncertainty quantification among different climate model outputs. Previous studies on this region have focused mostly on single experimental fields, not considering variations in Agro-Ecological Zones, climatic conditions, varieties and management practices and, in most cases not extending to various IPCC climate scenarios and were mostly based on single climate model output. Furthermore, the uncertainty quantification of the climate- impact model has rarely been investigated on this region. To this end we use the biophysical simulation model APSIM (Agricultural Production Systems Simulator) to simulate the regional climate impact on oil palm yield over the Nigerian Niger Delta. We also examine whether the use of crop yield model output ensemble reduces the uncertainty rather than the use of climate model output ensemble. The results could serve as a baseline for policy makers in this region in understanding the interaction between potentials of energy crop production of the region as well as its food security and other negative feedbacks that could be associated with bioenergy from oil palm. Keywords: Climate Change, Climate impacts, Land use and Crop yields.

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.

Losing the Lake: Simulations to Promote Gains in Student Knowledge and Interest about Climate Change

ERIC Educational Resources Information Center

Nussbaum, E. Michael; Owens, Marissa C.; Sinatra, Gale M.; Rehmat, Abeera P.; Cordova, Jacqueline R.; Ahmad, Sajjad; Harris, Fred C., Jr.; Dascalu, Sergiu M.

2015-01-01

Climate change literacy plays a key role in promoting sound political decisions and promoting sustainable consumption patterns. Based on evidence suggesting that student understanding and interest in climate change is best accomplished through studying local effects, we developed a simulation/game exploring the impact of climate change on the…

Pilot climate data system: A state-of-the-art capability in scientific data management

NASA Technical Reports Server (NTRS)

Smith, P. H.; Treinish, L. A.; Novak, L. V.

1983-01-01

The Pilot Climate Data System (PCDS) was developed by the Information Management Branch of NASA's Goddard Space Flight Center to manage a large collection of climate-related data of interest to the research community. The PCDS now provides uniform data catalogs, inventories, access methods, graphical displays and statistical calculations for selected NASA and non-NASA data sets. Data manipulation capabilities were developed to permit researchers to easily combine or compare data. The current capabilities of the PCDS include many tools for the statistical survey of climate data. A climate researcher can examine any data set of interest via flexible utilities to create a variety of two- and three-dimensional displays, including vector plots, scatter diagrams, histograms, contour plots, surface diagrams and pseudo-color images. The graphics and statistics subsystems employ an intermediate data storage format which is data-set independent. Outside of the graphics system there exist other utilities to select, filter, list, compress, and calculate time-averages and variances for any data of interest. The PCDS now fully supports approximately twenty different data sets and is being used on a trial basis by several different in-house research grounds.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

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

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Status and Plans for Reanalysis at NASA/GMAO

NASA Technical Reports Server (NTRS)

Gelaro, Ron

2017-01-01

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

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.

Assessing the spatial impact of climate on wheat productivity and the potential value of climate forecasts at a regional level

NASA Astrophysics Data System (ADS)

Wang, Enli; Xu, J.; Jiang, Q.; Austin, J.

2009-03-01

Quantification of the spatial impact of climate on crop productivity and the potential value of seasonal climate forecasts can effectively assist the strategic planning of crop layout and help to understand to what extent climate risk can be managed through responsive management strategies at a regional level. A simulation study was carried out to assess the climate impact on the performance of a dryland wheat-fallow system and the potential value of seasonal climate forecasts in nitrogen management in the Murray-Darling Basin (MDB) of Australia. Daily climate data (1889-2002) from 57 stations were used with the agricultural systems simulator (APSIM) to simulate wheat productivity and nitrogen requirement as affected by climate. On a good soil, simulated grain yield ranged from <2 t/ha in west inland to >7 t/ha in the east border regions. Optimal nitrogen rates ranged from <60 kgN/ha/yr to >200 kgN/ha/yr. Simulated gross margin was in the range of -20/ha to 700/ha, increasing eastwards. Wheat yield was closely related to rainfall in the growing season and the stored soil moisture at sowing time. The impact of stored soil moisture increased from southwest to northeast. Simulated annual deep drainage ranged from zero in western inland to >200 mm in the east. Nitrogen management, optimised based on ‘perfect’ knowledge of daily weather in the coming season, could add value of 26˜79/ha compared to management optimised based on historical climate, with the maximum occurring in central to western part of MDB. It would also reduce the nitrogen application by 5˜25 kgN/ha in the main cropping areas. Comparison of simulation results with the current land use mapping in MDB revealed that the western boundary of the current cropping zone approximated the isolines of 160 mm of growing season rainfall, 2.5t/ha of wheat grain yield, and 150/ha of gross margin in QLD and NSW. In VIC and SA, the 160-mm isohyets corresponded relatively lower simulated yield due to less stored soil water. Impacts of other factors like soil types were also discussed.

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

NASA Technical Reports Server (NTRS)

Arneson, Heather; Evans, Antony D.; Li, Jinhua; Wei, Mei Yueh

2017-01-01

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, while automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies to be carried out that can inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. The paper describes the initial validation of the automated simulation capability against results from previous IDM HITL experiments, quantifying the differences. The simulator is then used to explore the performance of the IDM concept under the simple scenario of a capacity constrained airport under a wide range of wind conditions.

Using WNTR to Model Water Distribution System Resilience ...

EPA Pesticide Factsheets

The Water Network Tool for Resilience (WNTR) is a new open source Python package developed by the U.S. Environmental Protection Agency and Sandia National Laboratories to model and evaluate resilience of water distribution systems. WNTR can be used to simulate a wide range of disruptive events, including earthquakes, contamination incidents, floods, climate change, and fires. The software includes the EPANET solver as well as a WNTR solver with the ability to model pressure-driven demand hydraulics, pipe breaks, component degradation and failure, changes to supply and demand, and cascading failure. Damage to individual components in the network (i.e. pipes, tanks) can be selected probabilistically using fragility curves. WNTR can also simulate different types of resilience-enhancing actions, including scheduled pipe repair or replacement, water conservation efforts, addition of back-up power, and use of contamination warning systems. The software can be used to estimate potential damage in a network, evaluate preparedness, prioritize repair strategies, and identify worse case scenarios. As a Python package, WNTR takes advantage of many existing python capabilities, including parallel processing of scenarios and graphics capabilities. This presentation will outline the modeling components in WNTR, demonstrate their use, give the audience information on how to get started using the code, and invite others to participate in this open source project. This pres

Computational Science: A Research Methodology for the 21st Century

NASA Astrophysics Data System (ADS)

Orbach, Raymond L.

2004-03-01

Computational simulation - a means of scientific discovery that employs computer systems to simulate a physical system according to laws derived from theory and experiment - has attained peer status with theory and experiment. Important advances in basic science are accomplished by a new "sociology" for ultrascale scientific computing capability (USSCC), a fusion of sustained advances in scientific models, mathematical algorithms, computer architecture, and scientific software engineering. Expansion of current capabilities by factors of 100 - 1000 open up new vistas for scientific discovery: long term climatic variability and change, macroscopic material design from correlated behavior at the nanoscale, design and optimization of magnetic confinement fusion reactors, strong interactions on a computational lattice through quantum chromodynamics, and stellar explosions and element production. The "virtual prototype," made possible by this expansion, can markedly reduce time-to-market for industrial applications such as jet engines and safer, more fuel efficient cleaner cars. In order to develop USSCC, the National Energy Research Scientific Computing Center (NERSC) announced the competition "Innovative and Novel Computational Impact on Theory and Experiment" (INCITE), with no requirement for current DOE sponsorship. Fifty nine proposals for grand challenge scientific problems were submitted for a small number of awards. The successful grants, and their preliminary progress, will be described.

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.

Quantitative Assessment on Anthropogenic Contributions to the Rainfall Extremes Associated with Typhoon Morakot (2009)

NASA Astrophysics Data System (ADS)

Chen, C. T.; Lo, S. H.; Wang, C. C.; Tsuboki, K.

2017-12-01

More than 2000 mm rainfall occurred over southern Taiwan when a category 1 Typhoon Morakot pass through Taiwan in early August 2009. Entire village and hundred of people were buried by massive mudslides induced by record-breaking precipitation. Whether the past anthropogenic warming played a significant role in such extreme event remained very controversial. On one hand, people argue it's nearly impossible to attribute an individual extreme event to global warming. On the other hand, the increase of heavy rainfall is consistent with the expected effects of climate change on tropical cyclone. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall associated with Typhoon Morakot, we adapt an existing probabilistic event attribution framework to simulate a `world that was' and compare it with an alternative condition, 'world that might have been' that removed the historical anthropogenic drivers of climate. One limitation for applying such approach to high-impact weather system is that it will require models capable of capturing the essential processes lead to the studied extremes. Using a cloud system resolving model that can properly simulate the complicated interactions between tropical cyclone, large-scale background, topography, we first perform the ensemble `world that was' simulations using high resolution ECMWF YOTC analysis. We then re-simulate, having adjusted the analysis to `world that might have been conditions' by removing the regional atmospheric and oceanic forcing due to human influences estimated from the CMIP5 model ensemble mean conditions between all forcing and natural forcing only historical runs. Thus our findings are highly conditional on the driving analysis and adjustments therein, but the setup allows us to elucidate possible contribution of anthropogenic forcing to changes in the likelihood of heavy rainfall associated Typhoon Morakot in early August 2009.

Evaluation of the WRF model for precipitation downscaling on orographic complex islands

NASA Astrophysics Data System (ADS)

Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

2010-05-01

General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong precipitation events.

Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate

NASA Astrophysics Data System (ADS)

Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.

2013-08-01

This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.

[Simulating the effects of climate change and fire disturbance on aboveground biomass of boreal forests in the Great Xing'an Mountains, Northeast China].

PubMed

Luo, Xu; Wang, Yu Li; Zhang, Jin Quan

2018-03-01

Predicting the effects of climate warming and fire disturbance on forest aboveground biomass is a central task of studies in terrestrial ecosystem carbon cycle. The alteration of temperature, precipitation, and disturbance regimes induced by climate warming will affect the carbon dynamics of forest ecosystem. Boreal forest is an important forest type in China, the responses of which to climate warming and fire disturbance are increasingly obvious. In this study, we used a forest landscape model LANDIS PRO to simulate the effects of climate change on aboveground biomass of boreal forests in the Great Xing'an Mountains, and compared direct effects of climate warming and the effects of climate warming-induced fires on forest aboveground biomass. The results showed that the aboveground biomass in this area increased under climate warming scenarios and fire disturbance scenarios with increased intensity. Under the current climate and fire regime scenario, the aboveground biomass in this area was (97.14±5.78) t·hm -2 , and the value would increase up to (97.93±5.83) t·hm -2 under the B1F2 scenario. Under the A2F3 scenario, aboveground biomass at landscape scale was relatively higher at the simulated periods of year 100-150 and year 150-200, and the value were (100.02±3.76) t·hm -2 and (110.56±4.08) t·hm -2 , respectively. Compared to the current fire regime scenario, the predicted biomass at landscape scale was increased by (0.56±1.45) t·hm -2 under the CF2 scenario (fire intensity increased by 30%) at some simulated periods, and the aboveground biomass was reduced by (7.39±1.79) t·hm -2 in CF3 scenario (fire intensity increased by 230%) at the entire simulation period. There were significantly different responses between coniferous and broadleaved species under future climate warming scenarios, in that the simulated biomass for both Larix gmelinii and Betula platyphylla showed decreasing trend with climate change, whereas the simulated biomass for Pinus sylvestris var. mongolica, Picea koraiensis and Populus davidiana showed increasing trend at different degrees during the entire simulation period. There was a time lag for the direct effect of climate warming on biomass for coniferous and broadleaved species. The response time of coniferous species to climate warming was 25-30 years, which was longer than that for broadleaf species. The forest landscape in the Great Xing'an Mountains was sensitive to the interactive effect of climate warming (high CO 2 emissions) and high intensity fire disturbance. Future climate warming and high intensity forest fire disturbance would significantly change the composition and structure of forest ecosystem.

Effects of different representations of transport in the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Kreyling, Daniel; Rex, Markus

2017-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Interactively coupled chemistry climate models (CCMs) provide a means to realistically simulate the interaction between atmospheric chemistry and dynamics. The calculation of chemistry in CCMs, however, is computationally expensive which renders the use of complex chemistry models not suitable for ensemble simulations or simulations with multiple climate change scenarios. In these simulations ozone is therefore usually prescribed as a climatological field or included by incorporating a fast linear ozone scheme into the model. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. An alternative approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. When using SWIFT in EMAC, there are several possibilities to represent the effect of transport inside the polar vortex: the semi-Lagrangian transport scheme of EMAC and a transport parameterisation that can be useful when using SWIFT in models not having transport of their own. Here, we present results of equivalent simulations with different handling of transport, compare with EMAC simulations with full interactive chemistry and evaluate the results with observations.

Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies

NASA Astrophysics Data System (ADS)

Williams, Paul; Howe, Nicola; Gregory, Jonathan; Smith, Robin; Joshi, Manoj

2016-04-01

In climate simulations, the impacts of the sub-grid scales on the resolved scales are conventionally represented using deterministic closure schemes, which assume that the impacts are uniquely determined by the resolved scales. Stochastic parameterization relaxes this assumption, by sampling the sub-grid variability in a computationally inexpensive manner. This presentation shows that the simulated climatological state of the ocean is improved in many respects by implementing a simple stochastic parameterization of ocean eddies into a coupled atmosphere-ocean general circulation model. Simulations from a high-resolution, eddy-permitting ocean model are used to calculate the eddy statistics needed to inject realistic stochastic noise into a low-resolution, non-eddy-permitting version of the same model. A suite of four stochastic experiments is then run to test the sensitivity of the simulated climate to the noise definition, by varying the noise amplitude and decorrelation time within reasonable limits. The addition of zero-mean noise to the ocean temperature tendency is found to have a non-zero effect on the mean climate. Specifically, in terms of the ocean temperature and salinity fields both at the surface and at depth, the noise reduces many of the biases in the low-resolution model and causes it to more closely resemble the high-resolution model. The variability of the strength of the global ocean thermohaline circulation is also improved. It is concluded that stochastic ocean perturbations can yield reductions in climate model error that are comparable to those obtained by refining the resolution, but without the increased computational cost. Therefore, stochastic parameterizations of ocean eddies have the potential to significantly improve climate simulations. Reference PD Williams, NJ Howe, JM Gregory, RS Smith, and MM Joshi (2016) Improved Climate Simulations through a Stochastic Parameterization of Ocean Eddies. Journal of Climate, under revision.

Can role-play with interactive simulations enhance climate change knowledge, affect and intent to act?

NASA Astrophysics Data System (ADS)

Rooney-varga, J. N.; Sterman, J.; Fracassi, E. P.; Franck, T.; Kapmeier, F.; Kurker, V.; Jones, A.; Rath, K.

2017-12-01

The strong scientific consensus about the reality and risks of anthropogenic climate change stands in stark contrast to widespread confusion and complacency among the public. Many efforts to close that gap, grounded in the information deficit model of risk communication, provide scientific information on climate change through reports and presentations. However, research shows that showing people research does not work: the gap between scientific and public understanding of climate change remains wide. Tools that are rigorously grounded in the science and motivate action on climate change are urgently needed. Here we assess the impact of one such tool, an interactive, role-play simulation, World Climate. Participants take the roles of delegates to the UN climate negotiations and are challenged to create an agreement limiting warming to no more than 2°C. The C-ROADS climate simulation model then provides participants with immediate feedback about the expected impacts of their decisions. Participants use C-ROADS to explore the climate system and use the results to refine their negotiating positions, learning about climate change while experiencing the social dynamics of negotiations and decision-making. Pre- and post-survey results from 21 sessions in eight nations showed significant gains in participants' climate change knowledge, affective engagement, intent to take action, and desire to learn. Contrary to the deficit model, gains in participants' desire to learn more and intention to act were associated with gains in affective engagement, particularly feelings of urgency and hope, but not climate knowledge. Gains were just as strong among participants who oppose government regulation, suggesting the simulation's potential to reach across political divides. Results indicate that simulations like World Climate offer a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science.

Obliquity Driven Climate Change in Mars' Recent Past

NASA Technical Reports Server (NTRS)

Haberle, R. M.; Montmessin, F.; Forget, F.; Spiga, A.; Colaprete, A.

2003-01-01

Mars has a natural mechanism for experiencing significant climate change and redistributing surface ice. Obliquity changes alone are quite capable of moving ice into low latitudes and may provide an explanation for the many geological landforms that strongly indicate recent climate change.

Improved National Response to Climate Change: Aligning USGCRP reports and the U.S. Climate Resilience Toolkit

NASA Astrophysics Data System (ADS)

Lipschultz, F.; Dahlman, L. E.; Herring, D.; Fox, J. F.

2017-12-01

As part of an effort to coordinate production and distribution of scientific climate information across the U.S. Government, and to spur adaptation actions across the nation, the U.S. Global Change Research Program (USGCRP) has worked to better integrate the U.S. Climate Resilience Toolkit (CRT) and its Climate Explorer (CE) tool into USGCRP activities and products. Much of the initial CRT content was based on the Third National Climate Assessment (NCA3). The opportunity to integrate current development of NCA4—scheduled for release in late 2018—with CRT and CE can enhance all three projects and result in a useable and "living" NCA that is part of USGCRP's approach to sustained climate assessment. To coordinate this work, a USGCRP-led science team worked with CRT staff and CE developers to update the set of climate projections displayed in the CE tool. In concert with the USGCRP scenarios effort, the combined team selected the Localized Constructed Analogs (LOCA) dataset for the updated version of CE, based on its capabilities for capturing climate extremes and local climate variations. The team identified 28 variables from the LOCA dataset for display in the CE; many of these variables will also be used in USGCRP reports. In CRT engagements, communities with vulnerable assets have expressed a high value for the ability to integrate climate data available through the CE with data related to non-climate stressors in their locations. Moving forward, the teams intend to serve climate information needs at additional spatial scales by making NCA4 content available via CE's capability for dynamic interaction with climate-relevant datasets. This will permit users to customize the extent of data they access for decision-making, starting with the static NCA4 report. Additionally, NCA4 case studies and other content can be linked to more in-depth content within the CRT site. This capability will enable more frequent content updates than can be managed with quadrennial NCA reports. Overall, enhanced integration between USGCRP and CRT will provide consistent information for communities that are assessing their climate vulnerabilities or considering adaptation options.

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2015-01-01

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Advances in Cross-Cutting Ideas for Computational Climate Science

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

Ng, Esmond; Evans, Katherine J.; Caldwell, Peter

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less

Advances in Cross-Cutting Ideas for Computational Climate Science

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

Ng, E.; Evans, K.; Caldwell, P.

This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« 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.

The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

DOE PAGES

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.; ...

2017-08-11

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less

The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models

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

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less

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

Bland, Arthur S Buddy; Hack, James J; Baker, Ann E

Oak Ridge National Laboratory's (ORNL's) Cray XT5 supercomputer, Jaguar, kicked off the era of petascale scientific computing in 2008 with applications that sustained more than a thousand trillion floating point calculations per second - or 1 petaflop. Jaguar continues to grow even more powerful as it helps researchers broaden the boundaries of knowledge in virtually every domain of computational science, including weather and climate, nuclear energy, geosciences, combustion, bioenergy, fusion, and materials science. Their insights promise to broaden our knowledge in areas that are vitally important to the Department of Energy (DOE) and the nation as a whole, particularly energymore » assurance and climate change. The science of the 21st century, however, will demand further revolutions in computing, supercomputers capable of a million trillion calculations a second - 1 exaflop - and beyond. These systems will allow investigators to continue attacking global challenges through modeling and simulation and to unravel longstanding scientific questions. Creating such systems will also require new approaches to daunting challenges. High-performance systems of the future will need to be codesigned for scientific and engineering applications with best-in-class communications networks and data-management infrastructures and teams of skilled researchers able to take full advantage of these new resources. The Oak Ridge Leadership Computing Facility (OLCF) provides the nation's most powerful open resource for capability computing, with a sustainable path that will maintain and extend national leadership for DOE's Office of Science (SC). The OLCF has engaged a world-class team to support petascale science and to take a dramatic step forward, fielding new capabilities for high-end science. This report highlights the successful delivery and operation of a petascale system and shows how the OLCF fosters application development teams, developing cutting-edge tools and resources for next-generation systems.« less

Addressing capability computing challenges of high-resolution global climate modelling at the Oak Ridge Leadership Computing Facility

NASA Astrophysics Data System (ADS)

Anantharaj, Valentine; Norman, Matthew; Evans, Katherine; Taylor, Mark; Worley, Patrick; Hack, James; Mayer, Benjamin

2014-05-01

During 2013, high-resolution climate model simulations accounted for over 100 million "core hours" using Titan at the Oak Ridge Leadership Computing Facility (OLCF). The suite of climate modeling experiments, primarily using the Community Earth System Model (CESM) at nearly 0.25 degree horizontal resolution, generated over a petabyte of data and nearly 100,000 files, ranging in sizes from 20 MB to over 100 GB. Effective utilization of leadership class resources requires careful planning and preparation. The application software, such as CESM, need to be ported, optimized and benchmarked for the target platform in order to meet the computational readiness requirements. The model configuration needs to be "tuned and balanced" for the experiments. This can be a complicated and resource intensive process, especially for high-resolution configurations using complex physics. The volume of I/O also increases with resolution; and new strategies may be required to manage I/O especially for large checkpoint and restart files that may require more frequent output for resiliency. It is also essential to monitor the application performance during the course of the simulation exercises. Finally, the large volume of data needs to be analyzed to derive the scientific results; and appropriate data and information delivered to the stakeholders. Titan is currently the largest supercomputer available for open science. The computational resources, in terms of "titan core hours" are allocated primarily via the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) and ASCR Leadership Computing Challenge (ALCC) programs, both sponsored by the U.S. Department of Energy (DOE) Office of Science. Titan is a Cray XK7 system, capable of a theoretical peak performance of over 27 PFlop/s, consists of 18,688 compute nodes, with a NVIDIA Kepler K20 GPU and a 16-core AMD Opteron CPU in every node, for a total of 299,008 Opteron cores and 18,688 GPUs offering a cumulative 560,640 equivalent cores. Scientific applications, such as CESM, are also required to demonstrate a "computational readiness capability" to efficiently scale across and utilize 20% of the entire system. The 0,25 deg configuration of the spectral element dynamical core of the Community Atmosphere Model (CAM-SE), the atmospheric component of CESM, has been demonstrated to scale efficiently across more than 5,000 nodes (80,000 CPU cores) on Titan. The tracer transport routines of CAM-SE have also been ported to take advantage of the hybrid many-core architecture of Titan using GPUs [see EGU2014-4233], yielding over 2X speedup when transporting over 100 tracers. The high throughput I/O in CESM, based on the Parallel IO Library (PIO), is being further augmented to support even higher resolutions and enhance resiliency. The application performance of the individual runs are archived in a database and routinely analyzed to identify and rectify performance degradation during the course of the experiments. The various resources available at the OLCF now support a scientific workflow to facilitate high-resolution climate modelling. A high-speed center-wide parallel file system, called ATLAS, capable of 1 TB/s, is available on Titan as well as on the clusters used for analysis (Rhea) and visualization (Lens/EVEREST). Long-term archive is facilitated by the HPSS storage system. The Earth System Grid (ESG), featuring search & discovery, is also used to deliver data. The end-to-end workflow allows OLCF users to efficiently share data and publish results in a timely manner.

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

Extending Climate Analytics-As to the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Tamkin, G.; Schnase, J. L.; Duffy, D.; McInerney, M.; Nadeau, D.; Li, J.; Strong, S.; Thompson, J. H.

2015-12-01

We are building three extensions to prior-funded work on climate analytics-as-a-service that will benefit the Earth System Grid Federation (ESGF) as it addresses the Big Data challenges of future climate research: (1) We are creating a cloud-based, high-performance Virtual Real-Time Analytics Testbed supporting a select set of climate variables from six major reanalysis data sets. This near real-time capability will enable advanced technologies like the Cloudera Impala-based Structured Query Language (SQL) query capabilities and Hadoop-based MapReduce analytics over native NetCDF files while providing a platform for community experimentation with emerging analytic technologies. (2) We are building a full-featured Reanalysis Ensemble Service comprising monthly means data from six reanalysis data sets. The service will provide a basic set of commonly used operations over the reanalysis collections. The operations will be made accessible through NASA's climate data analytics Web services and our client-side Climate Data Services (CDS) API. (3) We are establishing an Open Geospatial Consortium (OGC) WPS-compliant Web service interface to our climate data analytics service that will enable greater interoperability with next-generation ESGF capabilities. The CDS API will be extended to accommodate the new WPS Web service endpoints as well as ESGF's Web service endpoints. These activities address some of the most important technical challenges for server-side analytics and support the research community's requirements for improved interoperability and improved access to reanalysis data.

Simulated Climate Impacts of Mexico City's Historical Urban Expansion

NASA Astrophysics Data System (ADS)

Benson-Lira, Valeria

Urbanization, a direct consequence of land use and land cover change, is responsible for significant modification of local to regional scale climates. It is projected that the greatest urban growth of this century will occur in urban areas in the developing world. In addition, there is a significant research gap in emerging nations concerning this topic. Thus, this research focuses on the assessment of climate impacts related to urbanization on the largest metropolitan area in Latin America: Mexico City. Numerical simulations using a state-of-the-science regional climate model are utilized to address a trio of scientifically relevant questions with wide global applicability. The importance of an accurate representation of land use and land cover is first demonstrated through comparison of numerical simulations against observations. Second, the simulated effect of anthropogenic heating is quantified. Lastly, numerical simulations are performed using pre-historic scenarios of land use and land cover to examine and quantify the impact of Mexico City's urban expansion and changes in surface water features on its regional climate.

Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

NASA Astrophysics Data System (ADS)

Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. We reveal that LAI-driven evapotranspiration feedback may reduced rainfall in parts of Africa, vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa. Keywords: vegetation-climate feedback, regional climate model, evapotranspiration, CORDEX. References: Betts, R.A., Cox, P.M., Collins, M., Harris, P.P., Huntingford, C. & Jones, C.D. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology 78: 157-175. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408: 184-187. Samuelsson, P., Jones, C., Wilĺen, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3:Model description and performance. Tellus 63A, 4-23. Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637 Smith, B., Samuelsson, P., Wramneby, A. & Rummukainen, M. 2011. A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus 63A: 87-106.

Simulating the response of natural ecosystems and their fire regimes to climatic variability in Alaska.

Treesearch

D. Bachelet; J. Lenihan; R. Neilson; R. Drapek; T. Kittel

2005-01-01

The dynamic global vegetation model MC1 was used to examine climate, fire, and ecosystems interactions in Alaska under historical (1922-1996) and future (1997-2100) climate conditions. Projections show that by the end of the 21st century, 75%-90% of the area simulated as tundra in 1922 is replaced by boreal and temperate forest. From 1922 to 1996, simulation results...

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).

Predicting forest attributes from climate data using a recursive partitioning and regression tree algorithm

Treesearch

Greg C. Liknes; Christopher W. Woodall; Charles H. Perry

2009-01-01

Climate information frequently is included in geospatial modeling efforts to improve the predictive capability of other data sources. The selection of an appropriate climate data source requires consideration given the number of choices available. With regard to climate data, there are a variety of parameters (e.g., temperature, humidity, precipitation), time intervals...

A climate model diagnostic metric for the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Gonzalez, A. O.; Jiang, X.

2016-12-01

Despite its significant impacts on global weather and climate, the Madden-Julian oscillation (MJO) remains a grand challenge for state-of-the-art general circulation models (GCMs). The eastward propagation of the MJO is often poorly simulated in GCMs, represented by a stationary or even westward propagating mode. Recent analyses based on moist static energy processes suggest the horizontal advection of the winter mean moist static energy by the MJO circulation plays a critical role in the observed eastward propagation of the MJO. In this study, we explore relationships between model fidelity in representing the eastward propagation of the MJO and the winter mean lower-tropospheric moisture pattern by analyzing a suite of GCMs from a recent multi-model MJO comparison project. Model capability of reproducing the observed spatial pattern of the 650-900 hPa winter mean specific humidity is a robust indicator of how well they reproduce the MJO's eastward propagation. In particular, model skill in simulating the low-level winter mean specific humidity over the Maritime Continent region (20°S-20°N, 90°-135°E) is highly correlated with model skill of MJO propagation across the 23 GCMs analyzed, with a correlation of about 0.8. Winter mean lower-tropospheric moisture patterns over two other regions, including the western Indian Ocean and an off-equatorial region in the central Indian Ocean, also exhibit high correlations with MJO propagation skill in the model simulations. This study supports recent studies in highlighting the importance of the mean low-level moisture for MJO propagation and it points out a direction for model improvement of the MJO. Meanwhile, it is also suggested that the winter mean low-level moisture pattern over the Indo-Pacific region, particularly over the Maritime Continent region, can serve as a diagnostic metric for the eastward propagation of the MJO in climate model assessments.

Soil organic carbon dynamics following afforestation in the Loess Plateau of China

NASA Astrophysics Data System (ADS)

Lu, N.; Liski, J.; Chang, R. Y.; Akujärvi, A.; Wu, X.; Jin, T. T.; Wang, Y. F.; Fu, B. J.

2013-07-01

Soil organic carbon (SOC) is the largest terrestrial carbon pool and sensitive to land use and cover change; its dynamics is critical for carbon cycling in terrestrial ecosystems and the atmosphere. In this study, we combined a modeling approach and field measurements to examine the temporal dynamics of SOC following afforestation of former arable land at six sites under different climatic conditions in the Loess Plateau during 1980-2010. The results showed that the measured mean SOC increased to levels higher than before afforestation when taking the last measurements (i.e., at age 25 to 30 yr), although it decreased in the first few years at the wetter sites. The accumulation rates of SOC were 1.58 to 6.22% yr-1 in the upper 20 cm and 1.62 to 5.15% yr-1 in the upper 40 cm of soil. The simulations reproduced the basic characteristics of measured SOC dynamics, suggesting that litter input and climatic factors (temperature and precipitation) were the major causes for SOC dynamics and the differences among the sites. They explained 88-96, 48-86 and 57-74% of the variations in annual SOC changes at the soil depths of 0-20, 0-40, and 0-100 cm, respectively. Notably, the simulated SOC decreased during the first few years at all the sites, although the magnitudes of decreases were small at the drier sites. This suggested that the modeling may be advantageous in capturing SOC changes at finer time scale. The discrepancy between the simulation and measurement was a result of uncertainties in model structure, data input, and sampling design. Our findings indicated that afforestation promoted soil carbon sequestration at the study sites, which is favorable for further restoration of the vegetation and environment. Afforestation activities should decrease soil disturbances to reduce carbon release in the early stage. The long-term strategy for carbon fixation capability of the plantations should also consider the climate and site conditions, species adaptability, and successional stage of recovery.

The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations

NASA Astrophysics Data System (ADS)

Zhang, K.; O'Donnell, D.; Kazil, J.; Stier, P.; Kinne, S.; Lohmann, U.; Ferrachat, S.; Croft, B.; Quaas, J.; Wan, H.; Rast, S.; Feichter, J.

2012-03-01

This paper introduces and evaluates the second version of the global aerosol-climate model ECHAM-HAM. Major changes have been brought into the model, including new parameterizations for aerosol nucleation and water uptake, an explicit treatment of secondary organic aerosols, modified emission calculations for sea salt and mineral dust, the coupling of aerosol microphysics to a two-moment stratiform cloud microphysics scheme, and alternative wet scavenging parameterizations. These revisions extend the model's capability to represent details of the aerosol lifecycle and its interaction with climate. Sensitivity experiments are carried out to analyse the effects of these improvements in the process representation on the simulated aerosol properties and global distribution. The new parameterizations that have largest impact on the global mean aerosol optical depth and radiative effects turn out to be the water uptake scheme and cloud microphysics. The former leads to a significant decrease of aerosol water contents in the lower troposphere, and consequently smaller optical depth; the latter results in higher aerosol loading and longer lifetime due to weaker in-cloud scavenging. The combined effects of the new/updated parameterizations are demonstrated by comparing the new model results with those from the earlier version, and against observations. Model simulations are evaluated in terms of aerosol number concentrations against measurements collected from twenty field campaigns as well as from fixed measurement sites, and in terms of optical properties against the AERONET measurements. Results indicate a general improvement with respect to the earlier version. The aerosol size distribution and spatial-temporal variance simulated by HAM2 are in better agreement with the observations. Biases in the earlier model version in aerosol optical depth and in the Ångström parameter have been reduced. The paper also points out the remaining model deficiencies that need to be addressed in the future.

Quantifying the effect of mixing on the mean age of air in CCMVal-2 and CCMI-1 models

NASA Astrophysics Data System (ADS)

Dietmüller, Simone; Eichinger, Roland; Garny, Hella; Birner, Thomas; Boenisch, Harald; Pitari, Giovanni; Mancini, Eva; Visioni, Daniele; Stenke, Andrea; Revell, Laura; Rozanov, Eugene; Plummer, David A.; Scinocca, John; Jöckel, Patrick; Oman, Luke; Deushi, Makoto; Kiyotaka, Shibata; Kinnison, Douglas E.; Garcia, Rolando; Morgenstern, Olaf; Zeng, Guang; Stone, Kane Adam; Schofield, Robyn

2018-05-01

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry-climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry-Climate Model Validation Activity 2) and CCMI-1 (Chemistry-Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Uncertainty in simulating wheat yields under climate change

USDA-ARS?s Scientific Manuscript database

Anticipating the impacts of climate change on crop yields is critical for assessing future food security. Process-based crop simulation models are the most commonly used tools in such assessments. Analysis of uncertainties in future greenhouse gas emissions and their impacts on future climate change...

"The Effect of Alternative Representations of Lake Temperatures and Ice on WRF Regional Climate Simulations"

EPA Science Inventory

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 Weathe...

A blueprint for using climate change predictions in an eco-hydrological study

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2009-12-01

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.

Global Simulation of Bioenergy Crop Productivity: Analytical Framework and Case Study for Switchgrass

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

Kang, Shujiang; Kline, Keith L; Nair, S. Surendran

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high-performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC-Environmental Policy Integrated Climate (HPC-EPIC) model simulatedmore » a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field-trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.« less

Collaborative Proposal. Development of an Isotope-Enabled CESM for Testing Abrupt Climate Changes

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

Otto-Bliesner, Bette

2015-12-10

We have made significant landmarks in our proposed work in the last 4 years (3 years plus 1 year of no cost extension). We have developed the simulation capability of the major isotopes in CESM. In particular, we have completed the implementation of the stable water isotopes (δ 18O, δD) into the components for the atmosphere, ocean, land surface, runoff transport, sea ice, and coupler. In addition, the carbon isotopes (abiotic and biotic radiocarbon, δ 13 C) have been implemented into the CESM ocean and land models, and long spinup simulations have been completed (Jahn et al., 2015). Furthermore, wemore » have added abiotic Neodymium to the CESM ocean model as a tracer of ocean circulation, also measured by the proxy data community. Fullycoupled simulations with the stable water isotopes and ocean radiocarbon are currently being run for the preindustrial and also the Last Glacial Maximum. We have secured 19 million core-hours on the NWSC Yellowstone supercomputer for 12 months. Together with some CESM Paleoclimate Working Group CSL Yellowstone core hours, we are guaranteed sufficient computing for the spin-up experiments and deglaciation simulations for 21 to 15ka.« less

pyBadlands: A framework to simulate sediment transport, landscape dynamics and basin stratigraphic evolution through space and time

PubMed Central

2018-01-01

Understanding Earth surface responses in terms of sediment dynamics to climatic variability and tectonics forcing is hindered by limited ability of current models to simulate long-term evolution of sediment transfer and associated morphological changes. This paper presents pyBadlands, an open-source python-based framework which computes over geological time (1) sediment transport from landmasses to coasts, (2) reworking of marine sediments by longshore currents and (3) development of coral reef systems. pyBadlands is cross-platform, distributed under the GPLv3 license and available on GitHub (http://github.com/badlands-model). Here, we describe the underlying physical assumptions behind the simulated processes and the main options already available in the numerical framework. Along with the source code, a list of hands-on examples is provided that illustrates the model capabilities. In addition, pre and post-processing classes have been built and are accessible as a companion toolbox which comprises a series of workflows to efficiently build, quantify and explore simulation input and output files. While the framework has been primarily designed for research, its simplicity of use and portability makes it a great tool for teaching purposes. PMID:29649301

Simulator for concurrent processing data flow architectures

NASA Technical Reports Server (NTRS)

Malekpour, Mahyar R.; Stoughton, John W.; Mielke, Roland R.

1992-01-01

A software simulator capability of simulating execution of an algorithm graph on a given system under the Algorithm to Architecture Mapping Model (ATAMM) rules is presented. ATAMM is capable of modeling the execution of large-grained algorithms on distributed data flow architectures. Investigating the behavior and determining the performance of an ATAMM based system requires the aid of software tools. The ATAMM Simulator presented is capable of determining the performance of a system without having to build a hardware prototype. Case studies are performed on four algorithms to demonstrate the capabilities of the ATAMM Simulator. Simulated results are shown to be comparable to the experimental results of the Advanced Development Model System.

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.

Introducing the Met Office 2.2-km Europe-wide convection-permitting regional climate simulations

NASA Astrophysics Data System (ADS)

Kendon, Elizabeth J.; Chan, Steven C.; Berthou, Segolene; Fosser, Giorgia; Roberts, Malcolm J.; Fowler, Hayley J.

2017-04-01

The Met Office is currently conducting Europe-wide 2.2-km convection-permitting model (CPM) simulations driven by ERA-Interim reanalysis and present/future-climate GCM simulations. Here, we present the preliminary results of these new European simulations examining daily and sub-daily precipitation outputs in comparison with observations across Europe, 12-km European and 1.5-km UK climate model simulations. As the simulations are not yet complete, we focus on diagnostics that are relatively robust with a limited amount of data; for instance, the diurnal cycle and the probability distribution of daily and sub-daily precipitation intensities. We will also present specific case studies that showcase the benefits of using continental-scale CPM simulations over previously-available small-domain CPM simulations.

Atmospheric Constituents in GEOS-5: Components for an Earth System Model

NASA Technical Reports Server (NTRS)

Pawson, Steven; Douglass, Anne; Duncan, Bryan; Nielsen, Eric; Ott, Leslie; Strode, Sarah

2011-01-01

The GEOS-S model is being developed for weather and climate processes, including the implementation of "Earth System" components. While the stratospheric chemistry capabilities are mature, we are presently extending this to include predictions of the tropospheric composition and chemistry - this includes CO2, CH4, CO, nitrogen species, etc. (Aerosols are also implemented, but are beyond the scope of this paper.) This work will give an overview of our chemistry modules, the approaches taken to represent surface emissions and uptake of chemical species, and some studies of the sensitivity of the atmospheric circulation to changes in atmospheric composition. Results are obtained through focused experiments and multi-decadal simulations.

Common Methodology for Efficient Airspace Operations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar

2012-01-01

Topics include: a) Developing a common methodology to model and avoid disturbances affecting airspace. b) Integrated contrails and emission models to a national level airspace simulation. c) Developed capability to visualize, evaluate technology and alternate operational concepts and provide inputs for policy-analysis tools to reduce the impact of aviation on the environment. d) Collaborating with Volpe Research Center, NOAA and DLR to leverage expertise and tools in aircraft emissions and weather/climate modeling. Airspace operations is a trade-off balancing safety, capacity, efficiency and environmental considerations. Ideal flight: Unimpeded wind optimal route with optimal climb and descent. Operations degraded due to reduction in airport and airspace capacity caused by inefficient procedures and disturbances.

Case study applications of the BASINS climate assessment tool (CAT)

EPA Science Inventory

This EPA report will illustrate the application of different climate assessment capabilities within EPA’s BASINS modeling system for assessing a range of potential questions about the effects of climate change on streamflow and water quality in different watershed settings and us...

Estimated migration rates under scenarios of global climate change.

Treesearch

Jay R. Malcolm; Adam Markham; Ronald P. Neilson; Michael Oaraci

2002-01-01

Greefihouse-induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO2 doubled climatic forcing.

Comparison of Global Cloud Fraction and TOA Radiation Budgets between the NASA GISS AR5 GCM Simulations and CERES-MODIS Observations

NASA Astrophysics Data System (ADS)

Stanfield, R. E.; Dong, X.; Xi, B.; Del Genio, A. D.; Minnis, P.; Doelling, D.; Loeb, N. G.

2011-12-01

To better advise policymakers, it is necessary for climate models to provide credible predictions of future climates. Meeting this goal requires climate models to successfully simulate the present and past climates. The past, current and future Earth climate has been simulated by the NASA GISS ModelE climate model and has been summarized by the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, AR4, 2007). New simulations from the updated AR5 version of the NASA GISS ModelE GCM have been released to the public community and will be included in the IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, however, they have yet to be extensively validated against observations. To evaluate the GISS AR5 simulated global clouds and TOA radiation budgets, we have collected and processed the NASA CERES and MODIS observations during the period 2000-2005. In detail, the 1ox1o resolution monthly averaged SYN1 product has been used with combined observations from both Terra and Aqua satellites, and degraded to a 2ox2.5o grid box to match the GCM spatial resolution. These observations are temporally interpolated and fit to data from geostationary satellites to provide time continuity. The GISS AR5 products were downloaded from the CMIP5 (Coupled Model Intercomparison Project Phase 5) for the IPCC-AR5. Preliminary comparisons between GISS AR5 simulations and CERES-MODIS observations have shown that although their annual and seasonal mean CFs agree within a few percent, there are significant differences in several climatic regions. For example, the modeled CFs have positive biases in the Arctic, Antarctic, Tropics, and Sahara Desert, but negative biases over the southern middle latitudes (30-65 oS). The OLR, albedo and NET radiation comparisons are similar to the CF comparison.

Pollen-proxies say cooler, climate models say warmer: resolving conflicting views of the Holocene climate of the Mediterranean region

NASA Astrophysics Data System (ADS)

Russo, E.; Mauri, A.; Davis, B. A. S.; Cubasch, U.

2017-12-01

The evolution of the Mediterranean region's climate during the Holocene has been the subject of long-standing debate within the paleoclimate community. Conflicting hypotheses have emerged from the analysis of different climate reconstructions based on proxy records and climate models outputs.In particular, pollen-based reconstructions of cooler summer temperatures during the Holocene have been criticized based on a hypothesis that the Mediterranean vegetation is mainly limited by effective precipitation and not summer temperature. This criticism is important because climate models show warmer summer temperatures during the Holocene over the Mediterranean region, in direct contradiction of the pollen-based evidence. Here we investigate this problem using a high resolution model simulation of the climate of the Mediterranean region during the mid-to-late Holocene, which we compare against pollen-based reconstructions using two different approaches.In the first, we compare the simulated climate from the model directly with the climate derived from the pollen data. In the second, we compare the simulated vegetation from the model directly with the vegetation from the pollen data.Results show that the climate model is unable to simulate neither the climate nor the vegetation shown by the pollen-data. The pollen data indicates an expansion in cool temperate vegetation in the mid-Holocene while the model suggests an expansion in warm arid vegetation. This suggests that the data-model discrepancy is more likely the result of bias in climate models, and not bias in the pollen-climate calibration transfer-function.

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.

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

On the Value of Climate Elasticity Indices to Assess the Impact of Climate Change on Streamflow Projection using an ensemble of bias corrected CMIP5 dataset

NASA Astrophysics Data System (ADS)

Demirel, Mehmet; Moradkhani, Hamid

2015-04-01

Changes in two climate elasticity indices, i.e. temperature and precipitation elasticity of streamflow, were investigated using an ensemble of bias corrected CMIP5 dataset as forcing to two hydrologic models. The Variable Infiltration Capacity (VIC) and the Sacramento Soil Moisture Accounting (SAC-SMA) hydrologic models, were calibrated at 1/16 degree resolution and the simulated streamflow was routed to the basin outlet of interest. We estimated precipitation and temperature elasticity of streamflow from: (1) observed streamflow; (2) simulated streamflow by VIC and SAC-SMA models using observed climate for the current climate (1963-2003); (3) simulated streamflow using simulated climate from 10 GCM - CMIP5 dataset for the future climate (2010-2099) including two concentration pathways (RCP4.5 and RCP8.5) and two downscaled climate products (BCSD and MACA). The streamflow sensitivity to long-term (e.g., 30-year) average annual changes in temperature and precipitation is estimated for three periods i.e. 2010-40, 2040-70 and 2070-99. We compared the results of the three cases to reflect on the value of precipitation and temperature indices to assess the climate change impacts on Columbia River streamflow. Moreover, these three cases for two models are used to assess the effects of different uncertainty sources (model forcing, model structure and different pathways) on the two climate elasticity indices.

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

Modeling the influence of climate change on watershed systems: Adaptation through targeted practices

NASA Astrophysics Data System (ADS)

Dudula, John; Randhir, Timothy O.

2016-10-01

Climate change may influence hydrologic processes of watersheds (IPCC, 2013) and increased runoff may cause flooding, eroded stream banks, widening of stream channels, increased pollutant loading, and consequently impairment of aquatic life. The goal of this study was to quantify the potential impacts of climate change on watershed hydrologic processes and to evaluate scale and effectiveness of management practices for adaptation. We simulate baseline watershed conditions using the Hydrological Simulation Program Fortran (HSPF) simulation model to examine the possible effects of changing climate on watershed processes. We also simulate the effects of adaptation and mitigation through specific best management strategies for various climatic scenarios. With continuing low-flow conditions and vulnerability to climate change, the Ipswich watershed is the focus of this study. We quantify fluxes in runoff, evapotranspiration, infiltration, sediment load, and nutrient concentrations under baseline and climate change scenarios (near and far future). We model adaptation options for mitigating climate effects on watershed processes using bioretention/raingarden Best Management Practices (BMPs). It was observed that climate change has a significant impact on watershed runoff and carefully designed and maintained BMPs at subwatershed scale can be effective in mitigating some of the problems related to stormwater runoff. Policy options include implementation of BMPs through education and incentives for scale-dependent and site specific bioretention units/raingardens to increase the resilience of the watershed system to current and future climate change.

UNSAT-H Version 2. 0: Unsaturated soil water and heat flow model

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

Fayer, M.J.; Jones, T.L.

1990-04-01

This report documents UNSAT-H Version 2.0, a model for calculating water and heat flow in unsaturated media. The documentation includes the bases for the conceptual model and its numerical implementation, benchmark test cases, example simulations involving layered soils and plant transpiration, and the code listing. Waste management practices at the Hanford Site have included disposal of low-level wastes by near-surface burial. Predicting the future long-term performance of any such burial site in terms of migration of contaminants requires a model capable of simulating water flow in the unsaturated soils above the buried waste. The model currently used to meet thismore » need is UNSAT-H. This model was developed at Pacific Northwest Laboratory to assess water dynamics of near-surface, waste-disposal sites at the Hanford Site. The code is primarily used to predict deep drainage as a function of such environmental conditions as climate, soil type, and vegetation. UNSAT-H is also used to simulate the effects of various practices to enhance isolation of wastes. 66 refs., 29 figs., 7 tabs.« less

SIMULATING REGIONAL-SCALE AIR QUALITY WITH DYNAMIC CHANGES IN REGIONAL CLIMATE AND CHEMICAL BOUNDARY CONDITIONS

EPA Science Inventory

This poster compares air quality modeling simulations under current climate and a future (approximately 2050) climate scenario. Differences in predicted ozone episodes and daily average PM_2.5 concentrations are presented, along with vertical ozone profiles. Modeling ...

Integrated Framework for an Urban Climate Adaptation Tool

NASA Astrophysics Data System (ADS)

Omitaomu, O.; Parish, E. S.; Nugent, P.; Mei, R.; Sylvester, L.; Ernst, K.; Absar, M.

2015-12-01

Cities have an opportunity to become more resilient to future climate change through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. In this paper, we present some of the methods that drive each of the modules and demo some of the capabilities available to-date using the City of Knoxville in Tennessee as a case study.

Implementation of local grid refinement (LGR) for the Lake Michigan Basin regional groundwater-flow model

USGS Publications Warehouse

Hoard, C.J.

2010-01-01

The U.S. Geological Survey is evaluating water availability and use within the Great Lakes Basin. This is a pilot effort to develop new techniques and methods to aid in the assessment of water availability. As part of the pilot program, a regional groundwater-flow model for the Lake Michigan Basin was developed using SEAWAT-2000. The regional model was used as a framework for assessing local-scale water availability through grid-refinement techniques. Two grid-refinement techniques, telescopic mesh refinement and local grid refinement, were used to illustrate the capability of the regional model to evaluate local-scale problems. An intermediate model was developed in central Michigan spanning an area of 454 square miles (mi2) using telescopic mesh refinement. Within the intermediate model, a smaller local model covering an area of 21.7 mi2 was developed and simulated using local grid refinement. Recharge was distributed in space and time using a daily output from a modified Thornthwaite-Mather soil-water-balance method. The soil-water-balance method derived recharge estimates from temperature and precipitation data output from an atmosphere-ocean coupled general-circulation model. The particular atmosphere-ocean coupled general-circulation model used, simulated climate change caused by high global greenhouse-gas emissions to the atmosphere. The surface-water network simulated in the regional model was refined and simulated using a streamflow-routing package for MODFLOW. The refined models were used to demonstrate streamflow depletion and potential climate change using five scenarios. The streamflow-depletion scenarios include (1) natural conditions (no pumping), (2) a pumping well near a stream; the well is screened in surficial glacial deposits, (3) a pumping well near a stream; the well is screened in deeper glacial deposits, and (4) a pumping well near a stream; the well is open to a deep bedrock aquifer. Results indicated that a range of 59 to 50 percent of the water pumped originated from the stream for the shallow glacial and deep bedrock pumping scenarios, respectively. The difference in streamflow reduction between the shallow and deep pumping scenarios was compensated for in the deep well by deriving more water from regional sources. The climate-change scenario only simulated natural conditions from 1991-2044, so there was no pumping stress simulated. Streamflows were calculated for the simulated period and indicated that recharge over the period generally increased from the start of the simulation until approximately 2017, and decreased from then to the end of the simulation. Streamflow was highly correlated with recharge so that the lowest streamflows occurred in the later stress periods of the model when recharge was lowest.

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.

Vegetation-climate feedback causes reduced precipitation and tropical rainforest cover in CMIP5 regional Earth system model simulation over Africa

NASA Astrophysics Data System (ADS)

Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

2012-12-01

We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. Our study, the first application of a coupled Earth system model at regional scale and resolution over Africa, reveals that vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa.

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)

Possible climate change over Eurasia under different emission scenarios

NASA Astrophysics Data System (ADS)

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

2011-12-01

In an attempt to evaluate possible climate change over EURASIA, we analyze results of six AMIP type simulations with CAM version 3 (CAM3) at 2x2.5 degree resolution. CAM3 is driven by time series of sea surface temperatures (SSTs) and sea ice obtained by running the MIT IGSM2.3, which consists of a 3D ocean GCM coupled to a zonally-averaged atmospheric climate-chemistry model. In addition to changes in SSTs, CAM3 is forced by changes in greenhouse gases and ozone concentrations, sulfate aerosol forcing and black carbon loading calculated by the IGSM2.3. An essential feature of the IGSM is the possibility to vary its climate sensitivity (using a cloud adjustment technique) and the strength of the aerosol forcing. For consistency, new modules were developed in CAM3 to modify its climate sensitivity and aerosol forcing to match those used in the simulations with the IGSM2.3. The simulations presented in this paper were carried out for two emission scenarios, a "Business as usual" scenario and a 660 ppm of CO2-EQ stabilization, which are similar to the RCP8.5 and RCP4.5 scenarios, respectively. Values of climate sensitivity used in the simulations within the IGSM-CAM framework are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the 20th century climate simulated by different versions of the IGSM with observations. The associated strength of the aerosol forcing was chosen to ensure a good agreement with the observed climate change over the 20th century. Because the concentration of sulfate aerosol significantly decreases over the 21st century in both emissions scenarios, climate changes obtained in these simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Possible climate change over Eurasia under different emission scenarios

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Monier, E.; Gao, X.

2012-12-01

In an attempt to evaluate possible climate change over EURASIA, we analyze results of six AMIP type simulations with CAM version 3 (CAM3) at 2x2.5 degree resolution. CAM3 is driven by time series of sea surface temperatures (SSTs) and sea ice obtained by running the MIT IGSM2.3, which consists of a 3D ocean GCM coupled to a zonally-averaged atmospheric climate-chemistry model. In addition to changes in SSTs, CAM3 is forced by changes in greenhouse gases and ozone concentrations, sulfate aerosol forcing and black carbon loading calculated by the IGSM2.3. An essential feature of the IGSM is the possibility to vary its climate sensitivity (using a cloud adjustment technique) and the strength of the aerosol forcing. For consistency, new modules were developed in CAM3 to modify its climate sensitivity and aerosol forcing to match those used in the simulations with the IGSM2.3. The simulations presented in this paper were carried out for two emission scenarios, a "Business as usual" scenario and a 660 ppm of CO2-EQ stabilization, which are similar to the RCP8.5 and RCP4.5 scenarios, respectively. Values of climate sensitivity used in the simulations within the IGSM-CAM framework are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the 20th century climate simulated by different versions of the IGSM with observations. The associated strength of the aerosol forcing was chosen to ensure a good agreement with the observed climate change over the 20th century. Because the concentration of sulfate aerosol significantly decreases over the 21st century in both emissions scenarios, climate changes obtained in these simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Simulations and Evaluation of Mesoscale Convective Systems in a Multi-scale Modeling Framework (MMF)

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.

2017-12-01

It is well known that the mesoscale convective systems (MCS) produce more than 50% of rainfall in most tropical regions and play important roles in regional and global water cycles. Simulation of MCSs in global and climate models is a very challenging problem. Typical MCSs have horizontal scale of a few hundred kilometers. Models with a domain of several hundred kilometers and fine enough resolution to properly simulate individual clouds are required to realistically simulate MCSs. The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has shown some capabilities of simulating organized MCS-like storm signals and propagations. However, its embedded CRMs typically have small domain (less than 128 km) and coarse resolution ( 4 km) that cannot realistically simulate MCSs and individual clouds. In this study, a series of simulations were performed using the Goddard MMF. The impacts of the domain size and model grid resolution of the embedded CRMs on simulating MCSs are examined. The changes of cloud structure, occurrence, and properties such as cloud types, updraft and downdraft, latent heating profile, and cold pool strength in the embedded CRMs are examined in details. The simulated MCS characteristics are evaluated against satellite measurements using the Goddard Satellite Data Simulator Unit. The results indicate that embedded CRMs with large domain and fine resolution tend to produce better simulations compared to those simulations with typical MMF configuration (128 km domain size and 4 km model grid spacing).

Threat radar system simulations

NASA Astrophysics Data System (ADS)

Miller, L.

The capabilities, requirements, and goals of radar emitter simulators are discussed. Simulators are used to evaluate competing receiver designs, to quantify the performance envelope of a radar system, and to model the characteristics of a transmitted signal waveform. A database of candidate threat systems is developed and, in concert with intelligence data on a given weapons system, permits upgrading simulators to new projected threat capabilities. Four currently available simulation techniques are summarized, noting the usefulness of developing modular software for fast controlled-cost upgrades of simulation capabilities.

The sensitivity of the Arctic sea ice to orbitally induced insolation changes: a study of the mid-Holocene Paleoclimate Modelling Intercomparison Project 2 and 3 simulations

NASA Astrophysics Data System (ADS)

Berger, M.; Brandefelt, J.; Nilsson, J.

2013-04-01

In the present work the Arctic sea ice in the mid-Holocene and the pre-industrial climates are analysed and compared on the basis of climate-model results from the Paleoclimate Modelling Intercomparison Project phase 2 (PMIP2) and phase 3 (PMIP3). The PMIP3 models generally simulate smaller and thinner sea-ice extents than the PMIP2 models both for the pre-industrial and the mid-Holocene climate. Further, the PMIP2 and PMIP3 models all simulate a smaller and thinner Arctic summer sea-ice cover in the mid-Holocene than in the pre-industrial control climate. The PMIP3 models also simulate thinner winter sea ice than the PMIP2 models. The winter sea-ice extent response, i.e. the difference between the mid-Holocene and the pre-industrial climate, varies among both PMIP2 and PMIP3 models. Approximately one half of the models simulate a decrease in winter sea-ice extent and one half simulates an increase. The model-mean summer sea-ice extent is 11 % (21 %) smaller in the mid-Holocene than in the pre-industrial climate simulations in the PMIP2 (PMIP3). In accordance with the simple model of Thorndike (1992), the sea-ice thickness response to the insolation change from the pre-industrial to the mid-Holocene is stronger in models with thicker ice in the pre-industrial climate simulation. Further, the analyses show that climate models for which the Arctic sea-ice responses to increasing atmospheric CO2 concentrations are similar may simulate rather different sea-ice responses to the change in solar forcing between the mid-Holocene and the pre-industrial. For two specific models, which are analysed in detail, this difference is found to be associated with differences in the simulated cloud fractions in the summer Arctic; in the model with a larger cloud fraction the effect of insolation change is muted. A sub-set of the mid-Holocene simulations in the PMIP ensemble exhibit open water off the north-eastern coast of Greenland in summer, which can provide a fetch for surface waves. This is in broad agreement with recent analyses of sea-ice proxies, indicating that beach-ridges formed on the north-eastern coast of Greenland during the early- to mid-Holocene.

SimilarityExplorer: A visual inter-comparison tool for multifaceted climate data

Treesearch

J. Poco; A. Dasgupta; Y. Wei; W. Hargrove; C. Schwalm; R. Cook; E. Bertini; C. Silva

2014-01-01

Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, for example, simulations of photosynthesis and respiration, using algorithms...

Sensitivity of WRF Regional Climate Simulations to Choice of Land Use Dataset

EPA Science Inventory

The goal of this study is to assess the sensitivity of regional climate simulations run with the Weather Research and Forecasting (WRF) model to the choice of datasets representing land use and land cover (LULC). Within a regional climate modeling application, an accurate repres...

Global Responses to Potential Climate Change: A Simulation.

ERIC Educational Resources Information Center

Williams, Mary Louise; Mowry, George

This interdisciplinary five-day unit provides students with an understanding of the issues in the debate on global climate change. Introductory lessons enhance understanding of the "greenhouse gases" and their sources with possible global effects of climate change. Students then roleplay negotiators from 10 nations in a simulation of the…