Improving the Understanding and Modeling of Land Processes in the Community Climate System Model (CCSM4.0)

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Land processes play a key role in the earth system, and their treatment is crucial for climate system modeling. The overall goal of this project is to improve the understanding and modeling of land processes in the new version of the Community Climate System Model (CCSM4.0) whose land component is the Community Land Model (CLM4.0). The investigators build on their significant progress under prior NSF support in addressing various interdisciplinary issues related to the land-atmosphere-ocean interface processes, as evidenced by the implementation in CLM4.0 of their improved parameterizations related to five different aspects of land processes, the implementation in the European Centre for Medium-Range Weather Forecasts (ECMWF) of their ocean skin temperature scheme, and the testing and implementation of their new formulations of land surface roughness lengths for momentum and heat in the National Centers for Environmental Prediction (NCEP) regional and global forecasting models.This project will address four questions through extensive in situ and satellite data analysis, process studies, and global modeling: a) How realistic are the land surface energy/water/carbon cycles and dynamic vegetation from CCSM4.0? b) How does CNDV (carbon and nitrogen cycling with dynamic vegetation) affect the energy/water/carbon cycles in CLM4.0 and how can its treatment be further improved? c) How does groundwater affect other land processes in CLM4.0 and how can its treatment be further improved? and d) How to use the insights gained from these efforts to better understand the uncertainties in the future climate projections of land processes from CCSM4.0?The broader impacts of the proposed work include: a) improving the understanding of energy/water/carbon cycles, improving the treatment of two important processes (i.e., groundwater and dynamic vegetation with carbon and nitrogen cycling), training students, and incorporating research results in teaching; b) upgrading and maintaining a computer cluster for interdisciplinary research; and c) broadly disseminating results through peer-reviewed publications, presentations at conferences and workshops, web page, and lectures to the general public.