Benefits of Assimilating DAWN and HALO Observations for Numerical Simulations of Tropical Convective Systems Associated with African Easterly Waves during NASA’s CPEX-AW and CPEX-CV

Abstract One objective of NASA’s Convective Processes Experiments—Aerosols and Winds (CPEX-AW, 2021) and Cabo Verde (CPEX-CV, 2022)—was to assess the impact of high-spatiotemporal-resolution airborne observations on the understanding and prediction of tropical Atlantic convective systems. This study investigates the effects of assimilating observations simultaneously from two airborne lidar systems, Doppler Aerosol Wind (DAWN) lidar winds and High Altitude Lidar Observatory (HALO) water vapor profiles, as well as dropsonde profiles on short-range precipitation forecasts associated with four African easterly waves (AEWs) during CPEX-AW and CPEX-CV. Observations are assimilated into the Weather Research and Forecasting (WRF) Model using the NCEP Gridpoint Statistical Interpolation analysis system (GSI)-based three-dimensional ensemble–variational hybrid data assimilation (3DEnVAR) system. Forecasts are evaluated against Airborne Precipitation Radar (APR)-3 observations and satellite-derived precipitation datasets. Results show that assimilating DAWN winds improves forecasts of the African easterly jet (AEJ) and AEW steering flow, refining precipitation placement. DAWN assimilation also weakens low-level convergence and upper-level divergence, thereby reducing moisture convergence and suppressing spurious simulated precipitation under observed clear skies. HALO water vapor assimilation achieves similar improvements by reducing low-level moisture and total precipitable water. Additionally, DAWN wind assimilation adjusts divergence near cloud tops and enhances precipitation forecasts in observed cloudy skies. The joint assimilation of DAWN winds and HALO water vapor combines these benefits. Dropsonde profiles provide valuable in-cloud data that enhance convective system forecasts but can introduce uncertainties due to their sparse and drifting nature. These drawbacks are effectively mitigated when dropsonde data are jointly assimilated with DAWN winds and HALO water vapor, underscoring the advantages of integrated airborne data assimilation.