资源环境科技发展态势分析平台

The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016, providing an unprecedented opportunity to obtain ocean surface wind speeds including wind estimates over the hurricane inner-core region. This study demonstrates the influence of assimilating an early version of CYGNSS observations of ocean surface wind speeds on numerical simulations of two notable landfalling hurricanes, Harvey and Irma (2017). A research version of the National Centers for Environmental Prediction operational Hurricane Weather Research and Forecasting model and the Gridpoint Statistical Interpolation-based hybrid ensemble three-dimensional variational data assimilation system are used. It is found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for both hurricane cases, especially for the weak phase of a hurricane, implying potential benefits of using such data for future research and operational applications.

Plain Language Summary The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016. It provides an unprecedented opportunity to obtain ocean surface wind speeds over a hurricane inner-core region. In this study, we combined the early version of CYGNSS data with all other observations that are currently available for operational forecasts to form initial conditions (inputs data) for a numerical weather prediction model. A research version of the National Oceanic and Atmospheric Administration operational hurricane forecast model named the Hurricane Weather Research and Forecast (HWRF) model is used. Results show that adding CYGNSS data into HWRF model results in improved track, intensity, and structure forecasts for two notable landfalling hurricanes, Harvey and Irma (2017), demonstrating the potential benefits of using CYGNSS data for future research and operational applications.