Matched Filter Cyclone Maximum Wind Retrievals Using CYGNSS: Progress Update and Error Analysis.

Area of Science:

• Earth and Space Sciences
• Remote Sensing
• Atmospheric Science

Background:

• Hurricane maximum wind speed estimation is crucial for tropical cyclone forecasting and impact assessment.
• Spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) offers a novel approach for oceanic wind measurements.
• The Cyclone Global Navigation Satellite System (CYGNSS) mission provides Delay Doppler Map (DDM) measurements for this purpose.

Purpose of the Study:

• To advance a matched filter retrieval approach for estimating hurricane maximum wind speeds using CYGNSS DDM measurements.
• To analyze the impact of synthetic storm models on retrieval performance.
• To investigate the relationship between retrieval error and measurement delay extent.

Main Methods:

• Utilized a matched filter retrieval approach comparing measured and simulated CYGNSS DDMs.
• Employed multiple parametric storm models for forward modeling.
• Analyzed CYGNSS full DDM and Raw I/F downlinks from 2017-2020 (68 tracks, 18 storms).

Main Results:

• Retrieved hurricane maximum wind speed estimates achieved a 92% correlation with reference data.
• Root-mean-square error (RMSE) was 6.05 m/s, with a mean difference of 4.83 m/s.
• Retrieval errors decreased significantly with increased measurement delay extent.

Conclusions:

• The matched filter retrieval methodology shows significant potential for accurate cyclone wind speed estimation using GNSS-R.
• Optimizing storm models and utilizing extended measurement delay extents can further enhance retrieval accuracy.
• This approach contributes to improved spaceborne remote sensing capabilities for tropical cyclone monitoring.