Directorate

• Contents
• EXECUTIVE SUMMARY
• 1. SCOPE OF THE PROGRAM
• 2. IMPROVING OUR UNDERSTANDING OF EARTH-SYSTEM PROCESSES
• 2.1 Scale Interactions Associated with Precipitating Convective Systems
• 2.2 Understanding the Dynamics and Predictability of Weather Systems on Time Scales of 0-48 h
• 2.3 Fundamental Research on Precipitation Processes, with an Emphasis on their Improved Representation in Numerical Models
• 2.4 Understanding the Dynamics, Physics and Chemistry of Multi-Scale Atmospheric Chemical Constituent and Particulate Transport, Dispersion and Transformations
• 2.5 Fundamental Research in Boundary Layers and their Interfacial Interactions
• 3. ADVANCING THE SCIENCE OF ATMOSPHERIC PREDICTION
• 3.1 Advancing Short-Range Weather Prediction
• 3.2Advancing Data Assimilation Research
• 3.3 Improving Forecasting of Pollutants and Hazardous Materials
• 4. ADVANCED COMMUNITY RESEARCH TOOLS
• 4.1 WRF Community Model
• 4.2 Community Data Assimilation Techniques
• 4.3 Nested Community Climate Model
• 5. SUMMARY
• Acronym List
• Print Version
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Mesoscale & Microscale Meteorology Division Science Plan:

4.3 Nested Community Climate Model

Objective: To develop a state-of-the-science nested climate model based in WRF and to provide this to the community.

Climate varies across a wide range of temporal and spatial scales. Yet, climate modeling has long been approached using global models that can resolve only the broader scales of atmospheric circulations and their interactions with convection, land, ocean surface, and sea ice. Clearly, large-scale climate determines the environment for mesoscale and microscale processes that govern the weather and local climate, but, likewise, processes that occur at the regional scale may have significant impacts on the large-scale circulation. This is an important issue for climate and weather scales, which we recognize in our emphasis on research in this area under Sections 2.2 and 3.1. Resolving such interactions will lead to much improved understanding of how climate both influences, and is influenced by, human activities.

We therefore see an urgent need for significant advancement in resolving upscaling and downscaling issues in climate modeling. Downscaling is the process of deriving regional climate information based on large-scale climate conditions. Both dynamical and statistical downscaling methods have been used extensively in the last decade to produce regional climate change scenarios; however, their resolution and physical fidelity are regarded as inadequate for the real issues. Upscaling encapsulates the aggregate effects of small-scale physical and dynamical processes on the large-scale climate conditions. One form of upscaling is the use of physical parameterizations such as that for deep convection that represent the gross properties of subgrid scale processes. These are also considered to be inadequate; much of the uncertainty in model sensitivity to greenhouse gas and aerosol forcing is now known to be associated with the treatments of clouds and aerosols in climate models.

Another form of upscaling is to explicitly include the effects of regional processes to the large-scale environment, both locally and remotely. One example is the complex process that occurs on the west coasts of continents in tropical and subtropical zones with prevalent oceanic upwelling and stratus clouds. Sensitivity experiments indicate that the interactions of the atmosphere and ocean in the highly localized coastal strip produce effects that propagate widely and strongly influence the large-scale climate system. A second example is the manner in which persistent tropical convection can produce extreme weather events in remote locations through persistent and transient responses. Thus, one might hypothesize that proper upscaling of tropical convection is necessary to accurately predict weather extremes in middle latitudes. Such upscaling studies would greatly benefit medium range predictions as described in THORPEX and efforts to evaluate how weather changes in response to climatic changes.

A 2-way Nested Regional Climate Model (NRCM) provides an integrating research tool that is essential to address these upscaling and downscaling issues. When applied at the appropriate spatial scales and locales such models can resolve climate processes across wide spectrum of scales and reduce the errors associated with physics parameterizations. They also can properly represent spatial variations of climate forcing, such as topography, lakes, and land-sea contrast; and human influence, such as air pollution and land/water use. To address the full requirements, the nested models must include both global and regional models with two-way interactions.

WRF and CCSM are ideal candidates for such coupling. NCAR’s lead in developing and providing these models as community resources within the MMM and CGD divisions, respectively, has already made significant contributions to weather and climate research in the community. Adapting the WRF model to a community NRCM that includes atmosphere, ocean, land, and other components (such as atmospheric chemistry, biogeochemistry, and sea ice) will provide an ideal tool for investigating earth system processes that cut across scales. The WRF-Chem and its development will be a critical component of this work. Recognizing that high resolution modeling does not automatically resolve all scaling issues, we will embark on mesoscale and microscale process studies and modeling to further advance capabilities in WRF and CCSM. This will occur through improvement and development of physical modules, model coupling, and methods to represent scale interactions.

Our goal is to provide a community NRCM that enables process study, downscaling, and upscaling research, and facilitates multidisciplinary research that promotes understanding of climate and societal impacts. The NRCM can be used to address a number of important regional climate problems, including:

• Subtropical and tropical eastern ocean boundary upwelling regimes;
• Effects of climate variations on extreme weather events (e.g., floods/droughts, hurricanes, heat waves);
• Climate control of mesoscale convective systems and warm season precipitation;
• Orographic effects on precipitation, winds, and snow distributions;
• Effects of land use change and urbanization on regional climate.

We consider that this will provide considerable benefits to university research and education, and we look forward to collaborating with CGD and the academic community in further development of this important community resource.

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