Effects of Land-Use on Climate and Water Resources: Application of a Land Surface Model for Land-Use Management

The goal of this work is to use remote sensing land cover and leaf area index data to initialize a model of biogeophysical, biogeochemical, and hydrologic land-atmosphere interactions to assess the impact of natural land cover change and human land-use change (LCLUC) on climate and water resources. The work supports the development of the Community Land Model for the Community Climate System Model (CCSM). This model is being developed in coordination with the CCSM Land and Biogeochemistry Working Groups from the NCAR LSM, BATS, and other terrestrial models. The land model is being developed in four key areas: biogeophysical processes regulating the exchanges of energy, moisture, and momentum biogeochemical processes such as carbon and dust routing of runoff downstream into rivers and vegetation dynamics. Principal accomplishments during the first year are: 1. Development of a global 20-year atmospheric dataset at 3-hour resolution to allow model development uncoupled from an atmospheric model. This dataset allows us to develop and test new model parameterizations in a global context prior to coupling to a climate model. 2. Development of ˝° datasets of plant functional types and their individual monthly leaf area index. The land model was re-coded to represent vegetation as patches of co-existing plant functional types (PFTs) within a grid cell rather than as discrete biomes. This allows the model to interface better with dynamic global vegetation models (DVGMs), which represent vegetation as PFTs and change the abundance and geographic distribution of PFTs over time. 3. The surface biogeophysics were updated to include new parameterizations of soil temperature and water, snow processes, runoff generation, and surface energy exchange. These significantly improve the simulation when coupled to a climate model. Work during the second year includes: 1. Documenting the effects of the new surface biogeophysics on climate. 2. Implementing a dynamic global vegetation model to provide an integrated terrestrial model for climate studies. 3. Further development, testing, and application of the dust emission scheme.