Assimilation of NASA CPEX-AW and CPEX-CV Field Observations and Satellite Data for Improved Numerical Simulations of Tropical Cyclone and Tropical Convection

One of the scientific objectives of the National Aeronautics and Space Administration (NASA)’s Convective Process Experiments, including CPEX-AW (2021) and CPEX-CV (2022) is to examine the influence of satellite data and observations onboard the NASA DC-8 medium-altitude aircraft on the understanding and predictions of tropical Atlantic weather systems.This presentation summarizes our results that contribute to this important objective. Specifically, we assessed the impacts of assimilating Doppler Aerosol WiNd lidar (DAWN) wind profiles and High-Altitude Lidar Observatory (HALO) water vapor profiles on numerical simulations of tropical convective systems. Data collected from Research Flights during both CPEX-CV and CPEX-AW were assimilated into the mesoscale community Weather Research and Forecasting (WRF) model using the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI)-based three-dimensional ensemble-variational hybrid data assimilation (3DEnVAR) system. The convective processes embedded in an African easterly wave (AEW) over the tropical East Atlantic were evaluated with a series of numerical experiments. Results show that the experiment assimilating both DAWN and HALO produces the best numerical simulations of convective system evolution among all experiments, mainly due to better-reproducing precipitation and the dissipation of the conventions associated with the AEW. More experiments with NASA CPEX-CV and CPEX-AW cases and the sensitivity of the analyses and simulations to the error characteristics of the data were also examined. Dropsounding data from NASA DC-8 were also assimilated for comparison. In addition, we assimilated GOES-R satellite radiances and Aeolus wind data for the selected cases. The talk will summarize data assimilation results from all mentioned studies. Further discussion will be made to demonstrate the role of data assimilation in facilitating the process studies that lead to an improved understanding of tropical convective processes.