Impact of Ensemble-Based Targeting for Coyote UAS Observations in an OSSE

Impact of ensemble-based targeting for Coyote UAS observations in an OSSE

The Coyote is an Uncrewed Aircraft System (UAS) with an endurance of up to 1 hour that is deployed from the NOAA P-3 during hurricane reconnaissance missions. It collects continuous observations at low altitudes that are too hazardous for the P-3, proving useful for filling gaps in data collection. During missions into both Hurricane Edouard (2014) and Hurricane Maria (2017), the Coyote targeted the inflow layer of each storm and performed a circumnavigation through the eyewall. Data assimilation experiments that used data from the two missions through Hurricane Edouard showed that Coyote observations yielded a slightly better analysis with some decrease in forecast error when assimilated into NOAA/HRD’s HWRF Ensemble Data Assimilation System (HEDAS). However, the impact of the observations may be increased with changes to the Coyote's sampling strategy.

In this study, the Ensemble Transform Sensitivity (ETS) method (Zhang et al. 2016) is used to identify regions of the hurricane that exhibit strong error growth sensitivity and where targeted Coyote observations may have the most impact. Observations are simulated from the Nolan et al (2013) hurricane nature run and assimilated into HWRF with HEDAS. The impact of assimilating ETS-targeted Coyote observations versus observations simulated along a typical eyewall circumnavigation path will be discussed, along with implications for future flight planning.