Regional & Global Climate Modeling

The goal of the RGCM program 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 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. RGCM investments are also dedicated to development of metrics for model validation, that in turn may be used to inform the model development strategies of Earth System Modeling (ESM), and to inform the process research priorities of the Terrestrial Ecosystem Sciences (TES) and the Atmospheric System Research (ASR) programs. RGCM also coordinates with the Integrated Assessment Research (IAR) program on understanding individual and select coupled systems, such as water resources, critical for the energy mission.

RGCM 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 ESM model development.
  • 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 IAR.

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 exceedences 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'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 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 Modeling program, the process research needs of the Atmospheric System Research and Terrestrial Ecosystem Science programs.

RGCM 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).


Funding opportunity announcements are posted on the DOE Office of Science Grants and Contracts Website and at 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 is contingent on adherence to the BER data sharing policy.

Recent Content

Recent Highlights

Water vapor controls how clouds and precipitation form, but its vertical distribution in the atmosphere can vary significantly under different conditions in the Earth’s lowest atmospheric layer, called the troposphere. Researchers compared satellite-derived data of vertical atmospheric moisture...
Polynyas, areas of open water amidst the winter ice pack, are characterized by strong heat exchange between the ocean and atmosphere. The impact of this heat exchange on the atmosphere is studied and quantified by comparing years with and without polynyas in a high-resolution climate model.
Limited by computing resources, global climate models are designed to simulate atmospheric processes at relatively coarse spatial resolution using a hydrostatic approximation that allows the models to run efficiently. A study, led by researchers at Pacific Northwest National Laboratory,...
Simulating tropical rainfall is one of the most stubborn challenges in climate science. Scientists organized the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP) to study the dynamics (winds) of tropical rain belts using multi-model simulations to...
Robust projections and predictions of regional climate variability and change rely on a climate model’s ability to represent the driving processes with fidelity. For the first time, the High Resolution Model Intercomparison Project (HighResMIP) uses a multi-model approach to systematically...


This paper examines the performance of satellite sounder atmospheric vertical moisture profiles under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs), tropical Hadley cells, and...
The nonhydrostatic Model for Prediction Across Scales (NH-MPAS) provides a global framework to achieve high resolution using regional mesh refinement. Previous studies using the hydrostatic version of MPAS (H-MPAS) with the physics parameterizations of Community Atmosphere Model version 4 (CAM4)...
In this paper we study the atmospheric response to an open-ocean polynya in the Southern Ocean by analyzing the results from an atmospheric and oceanic synoptic-scale resolving Community Earth System Model (CESM) simulation. While coarser-resolution versions of CESM generally do not produce open-...
This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified...
Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate...