Improving the Representation of Soil Knowledge in the Noah-MP Land Surface Model.

Successful simulation of weather, climate conditions, and pollutant trajectory requires realistic representation of soil parameters and consideration of spatial variability of these parameters in the land surface models (LSMs). However, currently, the NOAH LSM is using a default parameter table which is not representative for Texas, and a vertically homogenous soil that is uniformly deep to 2 meters. This research examines the effect of modifications made on the default soil parameter table and consideration of vertical soil heterogeneity on the water and energy flux outputs of the Noah-MP model. These outputs are an important lower boundary inputs for climate models.  We used the multi-parametric version of the NOAH (Noah-MP) to examine the effect of improving the representation of soil knowledge on the overall water balance, soil moisture dynamics, and partitioning of latent and sensible heat fluxes.  Hourly soil moisture simulation results were compared with the soil moisture measurement obtained from the U.S. Climate Reference Network. In addition, the output from a biophysical model (RZWQM2) was used for comparison with water and energy flux outputs from Noah-MP. Our result showed an improvement in Noah-MP model performance in simulating soil water content when using the revised parameter table and heterogeneous soil profile. Likewise, Noah-MP and RZWQM2 models behave comparable when using improved soil information. These results suggest the need for a better accounting of soil knowledge in the LSMs for modeling exchange of energy and mass at the land-atmosphere boundaries.