Using Novel Observations at the Air-Sea Interface to Evaluate the Coupled Ocean-Atmosphere Background Ensemble Covariances from the Self-Cycled Hurricane Analysis and Forecast System (HAFS)

A field campaign during Hurricane Fiona (2022) collected unique observations at the air-sea interface using instruments such as saildrone, paired dropsondes and AXBT (Airborne EXpendable BathyThermograph), gliders, and the SFMR (WP-3D Stepped Frequency Microwave Radiometer). These observation platforms measured key atmospheric and oceanic parameters, including wind, temperature, and salinity, and also provided vertical profiles of the atmospheric boundary layer and ocean thermal structure down to 400 meters, which enabled the derivation of 3D thermal fluxes at the air-sea interface.

These novel observations were leveraged to evaluate the coupled ocean-atmosphere background ensemble from the self-cycled HAFS data assimilation system. Verification of background ensemble against saildrone, gliders, and SFMR data indicated good agreement, although some biases were identified. The thermal flux verification demonstrated consistency in storm shape and size. Notably, background ensemble forecast verification revealed the largest spread near the TC center, with the innovation variance and ensemble variance of near sea-surface air temperature, moisture, and wind speed showing a positive correlation. However, the SST ensemble variance was too low and showed incorrect, anti-correlation with the SST innovation variances. This study provides insights to improve the coupled atmosphere-ocean background ensemble covariances, paving the way for strongly coupled ocean-atmosphere DA for hurricanes.