Case Study of Satellite Data Assimilation Latency Impacts on Numerically Simulated Severe Weather

Quantifying the impacts of satellite data latency on data assimilation for numerical forecasts is vital to understanding the importance of satellites in weather prediction. As a result, this study strives to address the significance of Joint Polar Satellite System (JPSS) data in operational weather forecasting by focusing on assimilation of the Advanced Technology Microwave Sounder (ATMS) into the Weather Research and Forecasting (WRF) Nonhydrostatic Mesoscale Model (NMM). The study highlights five frontally forced convective events which occurred in fall 2012, emphasizing the short-term effects of ATMS latency on the validity of the resultant thunderstorm forecasts. To ensure similarity to operational output, the model was built in coordination with the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) to mimic their operational NMM, running at high resolution with 4-km output. ATMS data is assimilated at 15 minute timesteps after satellite observation, demonstrating a forced latency of satellite data in the NMM. Simulations are then compared to the National Environmental Prediction Center (NCEP) Stage IV analysis to validate forecast accuracy and identify departures from ground truth. Results will be shown to demonstrate basic latency-driven relationships.