Regional & Global Model Analysis

The goal of the Regional & Global Model Analysis (RGMA) program area is to advance the predictive understanding of Earth’s climate by focusing on scientific analysis of the dominant sets of governing processes that describe climate change on regional scales; evaluating robust methods to obtain higher spatial resolution for projections of climate and earth system change; and diagnosing model systems that are cause for uncertainty in regional climate projections. The program area's goal is accomplished through sensitivity studies and applications of regional and global earth system models that focus on various aspects of the climate system, including but not limited to, the understanding of feedbacks within the climate system, detection and attribution studies, developing capabilities for decadal predictability, and uncertainty characterization. RGMA investments are also dedicated to the development of metrics for model validation, that in turn may be used to inform the model development strategies of Earth System Model Development (ESMD), and to inform the process research priorities of the Terrestrial Ecosystem Sciences (TES) and the Atmospheric System Research (ASR) program areas. RGMA also coordinates with the Multisector Dynamics (MD) program area on understanding individual and select coupled systems, such as water resources, critical for the energy mission.

RGMA Priorities:

1. Development of robust analytical frameworks and model hierarchies to advance Earth system projections, predictions, and hindcasts, and to understand climate evolution at multiple scales. This priority also includes decadal predictions for specific regions, using high-resolution and variable scale climate modeling, and applying a combination of dynamical and statistical downscaling methodologies. Metrics are developed and assessed depending on measurement availability and quality, and depending on temporal and spatial scales.

2. Focused investigation of regions that are climatically sensitive or vital to climate assessments.

  • Arctic focus: Analyze the complex interactions between sea ice, ice sheets, cold oceans, regional climate, and permafrost stability in the context of both high-resolution regional and global models. This links closely with the vegetation and biogeochemical focus of the Next Generation Ecosystem Experiment (NGEE) Arctic and informs ESMD.
  • Tropical focus: Includes an emphasis on understanding and identifying tropical biases, such as cloud-precipitation biases, in collaboration with ASR, and in the carbon cycle, in collaboration with TES and NGEE tropics.
  • Regional focus: Analysis of the integrated water cycle as climate changes will be done in collaboration with MD.

3. The assessment and delineation of natural and forced climate variability. Understanding the relative importance of anthropogenic versus natural climate change, i.e., taking into account natural variability, requires a combination of modeling and observational research to extend this understanding. This also includes resolving different long- and short-term modes of climate variability (e.g., El Niño Southern Oscillation, Madden-Julian Oscillation) and describing how these change in a changing climate.

4. The analysis and understanding of climate extreme events, including floods and droughts, potential abrupt system changes, and tipping points, and how these are affected in a changing climate. Further emphasis is placed on multivariate and multi-stressor extremes, such as simultaneous combinations of hot, dry, and windy conditions and hot, moist, and stagnant conditions, and characterizing the number and amount of exceedances above given thresholds and quantifying uncertainties. Climate system resilience, reversibility, and tipping points are investigated.

5. The characterization of climate feedbacks and their uncertainties to quantify the cloud-climate, carbon-cycle climate, high-latitude feedback processes and address the fidelity of the models that capture these processes at regional and global scales.

6. Model evaluation, analysis, uncertainty characterization, diagnostics, and visualization tools to improve and facilitate comparison among models and between models and measurements in order to challenge and inform model development. Metrics to evaluate components of the Earth system, such as the carbon cycle, ocean eddies, and cloud-aerosol interactions, represent a practical approach to help guide the planning process for observational and process research.

7. Dissemination of data through the Earth System Grid Federation (ESGF). The ESGF is an interagency and international effort led by DOE and co-funded by national and international agencies for the management and dissemination of CMIP5 model output and observational data. Efforts will soon be placed on developing a roadmap to upgrade the ESGF to handle data emerging post-CMIP5.

Why the Program Area's Research is Important

Achieving greater detail about uncertainty and future variability of the earth climate system is critical for decision makers. There is a need to ascertain shifts in major modes of climate variability and climate extremes, to detect and attribute regional manifestations of climate change. This program area also provides support for national and international climate modeling research and assessments. An understanding of the model biases seamlessly feeds back to the model development needs of the Earth System Model Development (ESMD) program area, the process research needs of the Atmospheric System Research (ASR) and Terrestrial Ecosystem Science (TES) program areas.

RGMA also contributes to elements of the Interagency Group on Integrated Modeling (IGIM) of the U.S. Global Change Research Program (USGCRP), and coordinates its activities with the climate modeling programs at other federal agencies, particularly the National Science Foundation (NSF), the National Oceanic and Atmospheric Administration (NOAA), and the National Aeronautics and Space Administration (NASA).

Solicitations

Funding opportunity announcements are posted on the DOE Office of Science Grants and Contracts Website and at grants.gov. Information about preparing and submitting applications, as well as the DOE Office of Science merit review process, is at the DOE Office of Science Grants and Contracts Web Site.

Data Sharing Policy

Funding of projects by the program area is contingent on adherence to the BER data sharing policy.

Recent Content

Recent Highlights

A specialized spatial extreme value analysis is used to characterize the climatology of extreme precipitation over the contiguous United States. The essence of the method is to first estimate the climatology of extreme precipitation based on station data and then use a data-driven statistical...
As mass loss from the Greenland and Antarctic ice sheets accelerates, climate modelers recognize the importance of dynamic ice sheet models for predicting future mass loss and sea level rise. The Community Ice Sheet Model (CISM) version 2.1 has been significantly improved and, as a result of these...
Ocean wave climate is an important area of research, particularly in the context of extremes driven by tropical cyclones (TC). We can now simulate global cli­mate at resolutions sufficient to resolve TCs and for durations long enough to explore climatological changes. We present two simulated 50-...
Summer monsoon rainfall provides the lifeline for agriculture in many tropical and subtropical countries. How monsoon precipitation and hydrological extremes could respond to climate warming is of great social and societal importance. Working with university collaborators, researchers from the U.S...
As global temperatures increase, melting Arctic sea ice is enabling greater maritime access to the Arctic Ocean. Emissions from shipping are believed to have the potential to warm the Earth further by darkening snow and ice surfaces, or they may cool the climate by promoting cloud formation....

Publications

Gridded data products, for example, interpolated daily measurements of precipitation from weather stations, are commonly used as a convenient substitute for direct observations because these products provide a spatially and temporally continuous and complete source of data. However, when the goal...
We describe and evaluate version 2.1 of the Community Ice Sheet Model (CISM). CISM is a parallel, 3-D thermomechanical model, written mainly in Fortran, that solves equations for the momentum balance and the thickness and temperature evolution of ice sheets. CISM's velocity solver incorporates a...
Ocean wave climate is an important area of research, particularly in the context of extremes driven by tropical cyclones (TC). We can now simulate global climate at resolutions sufficient to resolve TCs and for durations long enough to explore climatological changes. Both the devastating 2017 North...
The column integrated water vapor (CWV)‐based local wave activity (LWA) is adapted to examine the response of the hydrological cycle and extremes of the Asian summer monsoon in CMIP5 simulations under the RCP8.5 forcing scenario. A tight linear relationship between CWV LWA ( urn:x-wiley:00948276:...
As global temperatures increase, sea ice loss will increasingly enable commercial shipping traffic to cross the Arctic Ocean, where the ships' gas and particulate emissions may have strong regional effects. Here we investigate impacts of shipping emissions on Arctic climate using a fully coupled...