Regional & Global Model Analysis

The overarching goal of the Regional & Global Model Analysis (RGMA) program area is to enhance predictive and process- and system-level understanding of the modes of variability and change within the earth system by advancing capabilities to design, evaluate, diagnose, and analyze global and regional earth system model (ESM) simulations informed by observations.  

The rapidly increasing complexity of ESMs necessitates a rigorous and comprehensive understanding and evaluation of their skill and behavior. Multifaceted, multisystem approaches are required to probe and understand the various feedbacks within and among individual systems, including the atmosphere, ocean, land surface, and cryosphere. The use of model simulations, in combination with observations, enables a deeper understanding of the earth system and models that emulate it.

The RGMA program area focuses on analyzing regions critical to understanding the dynamics of climate variability and change; evaluating robust methods for higher spatial resolution simulations; and diagnosing and analyzing state-of-the-science coupled climate and ESMs across a wide range of scales. These analyses often take the form of modeling experiments that target various aspects of the climate system, including detection and attribution of changes, analysis of climate response to perturbations, exploration of predictability on subseasonal-to-decadal scales, and analysis of feedbacks within the earth system. Understanding and reducing biases of earth system models, as well as uncertainty characterization, are also important elements of the RGMA program area.

To enhance understanding of processes and feedbacks, and to reduce uncertainties and biases in ESMs, the RGMA program area has six major thrusts, each with unique priorities. These are enabled through a combination of university projects, science focus areas (SFA), and cooperative agreements (CA), as indicated in parentheses:

  • Cloud processes and Feedbacks focuses on improving simulation accuracy through better cloud representations in ESMs and on determining the cloud feedbacks that influence climate sensitivity and change. (PCMDI SFA)
  • Biogeochemical Processes and Feedbacks focuses on identifying and quantifying feedbacks between biogeochemical cycles and the earth system and on quantifying and reducing the uncertainties in ESMs associated with these feedback processes. (RUBISCO SFA)
  • High-Latitude Processes and Feedbacks aims at a better understanding of the processes driving rapid system change at high latitudes and the subsequent effects on the Earth’s environment. (HiLAT SFA)
  • Modes of Variability and Change provides insight on the interplay between internally generated climate variability and externally forced response for improved understanding of near-term decadal predictability and projections in the context of longer-term projections. (PCMDI SFA and CATALYST CA)
  • Extreme Event Drivers, Statistics, and Uncertainties targets actionable understanding of multi-sectoral impacts of extreme weather events, especially droughts, floods, and tropical cyclones, and the physical mechanisms that drive variability and change in extremes. (CASCADE SFA & HyperFACETS CA)
  • Water Cycle focuses on advancing the understanding of multiscale water cycle processes and hydrologic extremes and their response to perturbations in the context of the whole earth system and implications for water availability. (WACCEM SFA & HyperFACETS CA)

Some of the cross-cutting capabilities that are the strength of the RGMA program area include:

  • Development of frameworks using a hierarchy of models, ranging from the most complex, very high-resolution climate models like the Department of Energy’s Energy Exascale Earth System Model (E3SM), non-hydrostatic atmospheric models, variable resolution models, and super parametrized models to less complex system models or idealized configurations of complex models for hypothesis testing and addressing scientific questions. (WACCEM SFA, HiLAT SFA, CASCADE SFA, CATALYST CA, HyperFACETS CA)
  • Holistic uncertainty characterization is enabled by a suite of tools, ranging from cutting-edge computational capabilities to complementary empirical models enabled by the latest statistical techniques. This enables us to understand and evaluate the need for improved observations and models. (CASCADE SFA, HiLAT SFA, CATALYST CA)
  • Diagnosing the complex behavior of model simulations and evaluating the capability of models through systematic comparison with available observations and quantifiable metrics, novel diagnostics, and robust extreme event identification methods are some of the core activities of the RGMA program area. These provide pathways for advancing an understanding of the earth system, improving models, and reducing uncertainties that exist in current ESMs. (RUBISCO SFA, WACCEM SFA, PCMDI SFA, CASCADE SFA, CATALYST CA)

The RGMA program area also actively contributes to and coordinates its activities with the U.S. Global Change Research Program (USGCRP), the U.S. Climate Variability and Predictability Program (US CLIVAR), and Interagency Arctic Research Policy Committee (IARPC).

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

 

Current RGMA Science Focus Areas

Current RGMA University Projects

Current RGMA Cooperative Agreements

Recent Content

Recent Highlights

This study connected the amplified climate variability to increasingly fluctuating natural gas supply and demand, providing information useful for understanding the role of a changing climate on a crucial economic and energy resource for the United States.
Predicting environmental conditions several weeks to months in advance has significant socioeconomic value. However, a gap exists between current short-term weather forecasts and subseasonal forecasts made two weeks to three months in advance, respectively. Further complicating the latter challenge...
The climate in the western United States is characterized by temperate, wet winters; warm, dry summers; and a pronounced wet season from October to April. Understanding potential future changes in seasonal precipitation due to warming in the western U.S. can help in predicting wildfires, droughts,...
Atmospheric rivers (ARs) are long, narrow bands of intense moisture that originate in the tropics and travel long distances through the sky. Scientists have confirmed a link between ARs and extreme precipitation events on the U.S. West Coast. However, the likelihood and the characteristics of ARs...
A lower-resolution grid is implemented into the Community Atmosphere Model with spectral element dynamics and conservative semi-Lagrangian tracer transport (CAM-SE-CSLAM) for evaluating the physical parameterizations. Building on previous work, the physics grid is effective at reducing spurious...
Although the occurrence of positive correlations between SST and near-surface wind speed over oceanic mesoscale ranges is well-known, the intrinsic spatial and temporal scales over which this air–sea coupling regime takes place are not well established. The contribution of the near-ubiquitous...
Our preliminary survey showed that most of the recent flood-related studies did not formally explain the physical mechanisms of long-duration flood events that can evoke substantial damages to properties and infrastructure systems. We have shown in this investigation that long-duration floods can...
This comprehensive study is the very first global study of actual flood events, which identifies temporal changes in the frequencies, and characteristics of probability distribution of flood durations to understand the changing organization of the local to global dynamical systems. Using the global...
It is important to have confidence in seasonal climate predictions of precipitation, particularly related to drought, as implications can be far-reaching and costly—this is particularly true for Florida. Precipitation can vary on fine spatial resolutions, and high-resolution coupled models may be...
By synthesizing recent studies employing a wide range of approaches (modern observations, paleo reconstructions, and climate model simulations), this study provides a comprehensive review of the linkage between multidecadal Atlantic Meridional Overturning Circulation (AMOC) variability and Atlantic...

Recent Publications

Anomalously cold winters with extreme storms strain natural gas (NG) markets due to heightened demand for heating and electricity generation. While extended weather forecasting has become an indicator for NG management, seasonal (2–3 month) prediction could mitigate the impact of extreme winters on...
Long-duration floods cause substantial damages and prolonged interruptions to water resource facilities and critical infrastructure. We present a novel generalized statistical and physical-based model for flood duration with a deeper understanding of dynamically coupled nexus of the land surface...
We introduce the idea of simultaneous heavy precipitation events (SHPEs) to understand whether extreme precipitation has a spatial organization that is manifest as specified tracks or contiguous fields with inherent scaling relationships. For this purpose, we created a database of SHPEs from 1242...
An accurate assessment of flood inundation and damages on residential and industrial properties requires a comprehensive modeling of simultaneous flood duration, peak, and volumeand identifying their regional hydrologic drivers. The purpose of this study is to advance our understanding from...
Arctic regions are changing rapidly as permafrost thaws and sea ice retreats. These changes directly affect Arctic river deltas, but how permafrost and ice alter delta hydrology and sediment transport are not well researched. This knowledge gap limits our ability to forecast how these systems will...
Changes in subseasonal precipitation variability have important implications for predictability of weather and climate extreme. Here we explore the mechanisms that lead to future changes in subseasonal precipitation variability in North America during winter based on 20 state‐of‐the‐art climate...
The mean precipitation along the U.S. West Coast exhibits a pronounced seasonality change under warming. Here we explore the characteristics of the seasonality change and investigate the underlying mechanisms, with a focus on quantifying the roles of moisture (thermodynamic) versus circulation (...
We quantified the relationship between atmospheric rivers (ARs) and occurrence and magnitude of extreme precipitation in western U.S. watersheds, using ARs identified by the Atmospheric River Tracking Method Intercomparison Project and precipitation from a high‐resolution regional climate...
This paper describes the implementation of a coarser‐resolution physics grid into the Community Atmosphere Model (CAM), containing urn:x-wiley:jame:media:jame20916:jame20916-math-0001 fewer grid columns than the dynamics grid. The dry dynamics is represented by the spectral element dynamical core...
This study aims to determine the spatial-temporal scales where the SST forcing of the near-surface winds takes places and its relationship with the action of coherent ocean eddies. Here, cross-spectral statistics are used to examine the relationship between satellite-based SST and 10-m wind speed (...