EGU2020-20553, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-20553
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Influence of Assimilating CYGNSS Ocean Surface Wind Data on Tropical Cyclone Analyses and Predictions

Bachir Annane, Mark Leidner, Ross Hoffman, Feixiong Huang, and James Garrisson
Bachir Annane et al.
  • CIMAS/RSMAS, University of Miami, Miami, United States of America (bachir.annane@noaa.gov)
For the analysis and forecasting of tropical cyclones, the main benefits of data from the CYGNSS constellation of satellites are the increased revisit frequency compared with polar-orbiting satellites and the ability to provide ocean surface wind observations through convective precipitation. Consequently, CYGNSS delivers an improved capability to observe the structure and evolution of ocean surface winds in and around tropical cyclones. This study quantifies the impact of assimilating CYGNSS delay-Doppler maps, CYGNSS retrieved wind speeds and derived CYGNSS wind vectors on 6-hourly analyses and 5-day forecasts of developing tropical cyclones, using the 2019 version of NOAA's operational Hurricane Weather Research and Forecasting (HWRF) model.

How to cite: Annane, B., Leidner, M., Hoffman, R., Huang, F., and Garrisson, J.: Influence of Assimilating CYGNSS Ocean Surface Wind Data on Tropical Cyclone Analyses and Predictions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20553, https://doi.org/10.5194/egusphere-egu2020-20553, 2020