A Comparison Study of the Noah and Noah-MP Land Surface Models

The anomalies in land heat and water storage can affect climate and weather predictability through their effects on surface energy and water fluxes.  For example, anomalous snow accumulation in winter can affect the warming in spring or early summer through melting.  In order to better represent multiple physics in a single land surface model (LSM), Noah-MP uses a variety of parameters to represent key land-atmosphere interaction processes.  It was coupled with the Weather Research and Forecasting (WRF) model and released in 2012.

The purpose of the present work is to evaluate the performance of both the classic Noah and Noah-MP LSMs, running online with WRF v3.7.1.  Prior comparisons at METAR locations over the New York (NY) metropolitan region, using daily (00Z) 72-hour forecasts at 2-km resolution for a winter and spring month of 2015, showed that classic Noah generally had lower-magnitude bias and RMSE scores for temperature and wind speed, relative to Noah-MP.  However, when compared against a high-quality AMERIFLX FLXNET station, Noah-MP was better correlated with the observed values of soil temperature, soil moisture, latent and sensible heat fluxes, and albedo. 

The continuation of this work, in part, focuses on verification to further address the biases in Noah-MP, and includes the roles of land-use, terrain height, and albedo and their relation to (influence on) these biases.  We also perform comparisons with other datasets/products and against additional FLXNET observations, where applicable.