Ocean Wave Data Assimilation Impact on Land Falling Tropical Cyclone Forecast

Improvements of the tropical cyclone (TC) model initial condition and physics parameterizations in recent years have yielded a substantial skill increase in TC track and intensity forecasts. However, correcting the coupled TC model initial condition errors in the atmosphere, ocean, and wave field remains a non-trivial goal to achieve. Especially, it is not known whether assimilating routinely available and emerging targeted ocean and wave observations without correcting the wind errors have any longer lasting effect to improve the coupled TC models’ forecasting skill. This presentation will describe recent efforts at the Naval Research Laboratory, Scripps Institution of Oceanography, and (U.S. Naval Academy) University of Washington, APL to assimilate both the tropical cyclone targeted Airborne EXpendable BathyThermograph (AXBT) temperature and wave spectra observations in the coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC). The discussion will highlight innovative new wave assimilation technology developed in the Navy Coupled Ocean Data Assimilation system (NCODA) to assimilate these tropical cyclone wave data using the maximum likelihood method. The land falling Hurricanes Harvey (2017) and Isaias (2020) coupled model cycling sensitivity runs clearly show a positive beneficial impact on the COAMPS-TC track, intensity, and significant wave height forecast. For the Category 4 Harvey case, NCODA assimilated the 1D directional wave spectra from the NDBC buoys. For the Isaias case study, NCODA assimilated three of Scripps Institution of Oceanography’s Lagrangian Drifter Laboratory (LDL) Directional Wave Spectra Drifter (DWSD) 2D directional wave spectra. These two TC case studies investigated the impact of ocean and wave assimilation on the coastal landfall TC atmosphere, ocean, and wave prediction.