Integrated evaluation of land surface models (Invited Presentation)

This paper reviews traditional methods of evaluating land-surface models used in numerous land-model comparison projects, and attempts to answer the following questions: 1) what type of evaluation metrics can be used to assess the integrity of models? 2) what type of evaluation would provide insights into improving models? and 3) how could we evaluate model performance in the context of physics ensemble prediction/simulation? We will use two examples to address the above questions. In one example, we evaluated the ability of six widely used land-surface/snow models (Noah, Noah-MP, VIC, CLM, SAST, and LEAF-2) in simulating the seasonal evolution of snowpacks in central Rockies. For this, we developed an integrated data set including one-year (2007-2008) snow water equivalent (SWE) observations from 112 SNOTEL sites in the Colorado Headwaters region, and surface-flux data (surface heat fluxes, radiation budgets, soil temperature and moisture) from two AmeriFlux sites (Niwot Ridge, Colorado and GLEES, Wyoming). While those six models captured fairly well the seasonality of SWE evolution, they exhibited large disparities in simulating the surface energy partitioning. That resulted in too little outgoing long-wave radiation and sensible heating returned to the atmosphere, which could be a crucial deficiency in coupled weather and climate models. Complex models produced similar SWE through different pathways. In the other example, we applied the Noah-MP land model in physics-ensemble simulations with the Weather Research and Forecasting model to assess how the treatment of canopy processes and interactions with deep ground water affect seasonal regional climate simulations.