Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link



Ichii, K, White, MA, Votava, P, Michaelis, A, Nemani, RR (2008). Evaluation of snow models in terrestrial biosphere models using ground observation and satellite data: impact on terrestrial ecosystem processes. HYDROLOGICAL PROCESSES, 22(3), 347-355.

Snow is important for water management, and an important component of the terrestrial biosphere and climate system. In this study, the snow models included in the Biome-BGC and Terrestrial Observation and Prediction System (TOPS) terrestrial biosphere models are compared against ground and satellite observations over the Columbia River Basin in the US and Canada and the impacts of differences ill snow models oil simulated terrestrial ecosystem processes are analysed. First, a point-based comparison of ground observations against model and satellite estimates of snow dynamics are conducted. Next, model and satellite snow estimates for the entire Columbia River Basin are compared. Then, using two different TOPS simulations, the default TOPS model (TOPS with TOPS snow model) and the TOPS model with the Biome-BGC snow model, the impacts of snow model selection oil runoff and gross primary production (GPP) are investigated. TOPS snow model predictions were consistent with ground and satellite estimates of seasonal and interannual variations in snow cover, snow water equivalent, and snow season length; however, in the Biome-BGC snow model, the snow pack melted too early, leading to extensive Underpredictions of snow season length and snow covered area. These biases led to earlier simulated peak runoff and reductions ill summer GPP, underscoring the need for accurate snow models within terrestrial ecosystem models. Copyright (c) 2007 John Wiley & Sons, Ltd.



NASA Home Page Goddard Space Flight Center Home Page