MODIS Consistent Vegetation Parameter Specifications and Their Impacts on Regional Climate Simulations

Abstract

consistent set of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation parameters, including leaf and stem area index (LAI and SAI, respectively), land-cover category (LCC), fractional vegetation cover (FVC), and albedo parameterization are developed, and their impacts on North American regional climate are evaluated based on 10-yr Climate?Weather and Research Forecasting Model (CWRF) simulations. As compared with the previous Advanced Very High Resolution Radiometer (AVHRR) set, MODIS LCC increases grassland and cropland fractions in the central Great Plains and Midwest, respectively. Evergreen needleleaf forest converts to mixed forest in the Southeast, and mixed forest converts to evergreen needleleaf in Canada. FVC decreases by 0.05?0.3 over the central Great Plains but increases by 0.1?0.35 over the northern Rocky Mountains, Canada, and the U.S. Southeast. MODIS LAI is less than AVHRR by 2?6, except in the central Great Plains, eastern Rocky Mountains, and central Mexico. LCC and FVC changes over the central Great Plains reduce CWRF warm biases by 0.71°C and wet biases by 0.36 mm day?1. Large LAI reductions cause latent and sensible heat fluxes to decrease by 0.78?5.81 and 0.91?6.54 W m?2, respectively. They also lessen cold biases over the Gulf States and Southeast and wet biases over the North American monsoon region and Canada during summer. In densely vegetated regions including eastern Canada, the Ohio Valley, and the mid-Atlantic region, spring and summer precipitation decreases and temperature increases result from LAI reductions that cause positive evapotranspiration?precipitation?soil moisture feedbacks. Conversely, precipitation and temperature decreases in sparely vegetated regions, such as the Great Plains, result from FVC reductions that cause negative albedo?evapotranspiration?precipitation?soil moisture feedbacks.