4.4 A hybrid land surface model approach to improving near-surface forecasts

Wilson, Travis, and Robert Fovell, University of California Los Angeles

In recent years, WRF-ARW has gained a large number of physics options, including land surface models (LSMs), many of which have become increasingly complex. Despite this, some daunting problems have persisted, including the simulation of near-surface temperature and moisture through the diurnal cycle. Through deconstruction of the popular Noah LSM and detailed comparison with all available data (including surface fluxes), we have identified the sources of many of the worst errors and biases common in near-surface WRF forecasts. This led to the creation of a substantially simpler land surface model, called the Hybrid LSM, which convolves the complexity of Noah’s soil moisture treatment with the simplicity of the Thermal Diffusion (slab) heat transfer model. When compared to the newly revised Noah-MP and Noah options in WRFV3.5, the Hybrid has yielded the most accurate forecasts in terms of errors and bias-corrected errors of surface temperature and dew point across the continental United States, during both summer and winter. By making things ‘as simple as possible, but not simpler’, a model improvement of more general use and applicability has been accomplished.