Assimilating Ocean Observations from Autonomous Drones into a Regional Weather Model

Weather observations in the ocean are sparse due to the difficulties in maintaining observing stations in such remote locations. Saildrone provides autonomous drones (saildrones), powered by the wind and sun, that collect surface observations. Saildrones are able to enter even the most remote oceanic region; Saildrone completed the first autonomous circumnavigation of Antarctica in August 2019. Saildrones are mobile and are able to be moved into desired regions where observations are desired. Ocean observation systems and buoys are known to improve forecast skill when assimilated into regional weather models. A case study is performed assimilating Saildrone observations of temperature, humidity, pressure, and wind into a GFS forecast, downscaling with the Advanced Research Weather Research and Forecast model (WRF-ARW) and assimilation done using the Gridpoint Statistical Interpolation (GSI) system and observation nudging. Saildrones were situated at various points in the Pacific Ocean for a domain that included northern California. The results of this study show improvements for an operational regional model; indicating Saildrone observations will be an important contribution for improving forecasting skill of severe mesoscale weather events, especially in coastal regions.