Impact of Aircraft Observations on the Prediction of 2017 Atlantic Tropical Cyclones

NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) has developed a new testbed for model and data assimilation development, ensemble forecasting, observing system design, and satellite data assimilation research. The testbed adopts a research-based version of the Hurricane Weather Research and Forecasting (HWRF) model reconfigured to a fixed domain for tropical cyclone forecasts. The fully-cycled ensemble data assimilation enables this version of HWRF to support uninterrupted assimilation of conventional and satellite observations for entire hurricane seasons. The resulting strategy allows for a systematic season-long evaluation of the HWRF model and data assimilation procedures to guide future developments and applications aimed at tropical cyclone prediction. AOML's advanced regional Observing System Simulation Experiment (OSSE) system, relies on this testbed to improve hurricane prediction by investigating the potential impact of various observing systems including space-borne, land-based, and aircraft reconnaissance observations.

Research aircraft observations remain an important aspect of hurricane forecasting, particularly because they provide direct measurements in crucial, data-sparse regions over the ocean. As a way to optimize aircraft resources, OSSEs can quantify the impact of current observing strategies and alterations in design. The ability for these OSSEs to replicate reality requires a thorough calibration where realistic error statistics are calculated using analog Observing System Experiments (OSEs) that describe the impact of real aircraft observations in this framework. Many hurricane cases are required to obtain robust error statistics for OSSE system calibration. Thus, the cases selected to perform these experiments encompass a wide range of scenarios from the 2017 Atlantic hurricane season, including several intense, long-lived storms and multiple landfalls. This presentation focuses on the impact of research aircraft data on the forecasts of tropical cyclones during this time.