Impacts of Soil Moisture Initializations on WRF-Simulated North American Monsoon System

The North American Monsoon System (NAMS) displays greater spatial and temporal variability than other monsoon systems. Previous work has shown that local-scale interactions with land surface and topography are important for explaining North American monsoon rainfall patterns and the initialization of mesoscale features is critical for the modeling of NAMS. This study investigates how soil moisture conditions influence the NAMS. This study uses the Weather Research and Forecasting (WRF) Model with the Noah-MP land surface model. The study period spans 2015-2017 and the simulations are initialized at UTC 0:00 on May 1^st and end at UTC 0:00 October 1^st each year. North American Regional Reanalysis (NARR) 3-hourly product provides the atmospheric initial and lateral boundary conditions. For each year, three sensitivity experiments are conducted with WRF using soil moisture fields from: (1) NARR, (2) Noah/Global Land Data Assimilation System (GLDAS) and (3) Soil Moisture Active Passive (SMAP) L4 product. The NARR simulations serve as a control run. To evaluate model performance, diurnal and seasonal monsoon rainfall patterns are compared with observations from Tropical Rainfall Measuring Mission (TRMM) 3B42 product and Climatic Research Unit (CRU) TS4.0 dataset. The study will improve our understanding of the impacts of land-atmosphere interactions on monsoon system and predictions of NAMS.