17:15 〜 19:15
[AOS12-P06] A comparative analysis and validation of satellite techniques for retrieving sea surface wind speeds
キーワード：ASCAT, GNSS-R, ERA5, mean square slope, significant wave height, geophysical model function
Establishing and maintaining fixed ocean observation stations, such as buoys, is both costly and technologically challenging. The density of observation points at sea is significantly lower than that on land, and the harsh marine environment—characterized by strong winds, large waves, and corrosive seawater—further complicates the installation and maintenance of equipment. As a result, satellite remote sensing technology has become a critical tool to address the scarcity of ocean observation data. By providing extensive, high-resolution, and real-time observations of the ocean surface, satellite remote sensing technology has significantly improved the understanding and predictive capabilities of various meteorological phenomena.
This study explores the performance of various meteorological satellite missions, including the Advanced Scatterometer (ASCAT), Global Navigation Satellite System Reflectometry (GNSS-R) aboard the Meteorological Operational satellite (MetOp), the Cyclone Global Navigation Satellite System (CYGNSS), and the TRITON satellite, in retrieving sea surface wind speeds under different weather conditions. The study examined two representative cases: the first case selected Typhoon Saola in August 2023, comparing sea surface wind speed data from CYGNSS and MetOp with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) to assess the performance of these two satellite technologies under typhoon conditions. The second case analyzed sea surface wind speed data in the waters around Taiwan from November 2023 to March 2024, influenced by the northeast monsoon. It incorporated data from TRITON, Taiwan's first domestically developed meteorological satellite launched in October 2023, and compared it with data from CYGNSS and MetOp.
The results indicated that under the extreme weather conditions of a typhoon, both ASCAT and GNSS-R demonstrate commendable performance in wind speed retrieval. However, the data quality of ASCAT diminished due to the interference of precipitation and cloud cover, while for GNSS-R, the deviation of the retrieved wind speed from ERA5 increased concurrently as wind speeds intensified (exceeding 15 m/s). The analysis of the northeast monsoon case revealed that under conditions of sustained strong winds, which increased the roughness of the sea surface (mean square slope exceeding 0.01 and significant wave height exceeding 2 m), the reliability of GNSS-R data significantly diminished. Although the research findings indicate that TRITON has room for improvement in data stability, the analysis demonstrates that it already possesses commendable technical potential (with both the average wind speed bias and the maximum wind speed discrepancy being the lowest among the three satellites). Future research will focus on developing innovative empirical formulas for wind speed retrieval using GNSS-R technology, specifically aimed at correcting data errors caused by increased sea surface roughness. Additionally, a geophysical model function (GMF) will be established to relate different wind speed ranges to sea surface roughness, with the expectation of enhancing the stability and accuracy of TRITON's retrieval techniques under high wind speeds and severe weather conditions.
This study explores the performance of various meteorological satellite missions, including the Advanced Scatterometer (ASCAT), Global Navigation Satellite System Reflectometry (GNSS-R) aboard the Meteorological Operational satellite (MetOp), the Cyclone Global Navigation Satellite System (CYGNSS), and the TRITON satellite, in retrieving sea surface wind speeds under different weather conditions. The study examined two representative cases: the first case selected Typhoon Saola in August 2023, comparing sea surface wind speed data from CYGNSS and MetOp with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) to assess the performance of these two satellite technologies under typhoon conditions. The second case analyzed sea surface wind speed data in the waters around Taiwan from November 2023 to March 2024, influenced by the northeast monsoon. It incorporated data from TRITON, Taiwan's first domestically developed meteorological satellite launched in October 2023, and compared it with data from CYGNSS and MetOp.
The results indicated that under the extreme weather conditions of a typhoon, both ASCAT and GNSS-R demonstrate commendable performance in wind speed retrieval. However, the data quality of ASCAT diminished due to the interference of precipitation and cloud cover, while for GNSS-R, the deviation of the retrieved wind speed from ERA5 increased concurrently as wind speeds intensified (exceeding 15 m/s). The analysis of the northeast monsoon case revealed that under conditions of sustained strong winds, which increased the roughness of the sea surface (mean square slope exceeding 0.01 and significant wave height exceeding 2 m), the reliability of GNSS-R data significantly diminished. Although the research findings indicate that TRITON has room for improvement in data stability, the analysis demonstrates that it already possesses commendable technical potential (with both the average wind speed bias and the maximum wind speed discrepancy being the lowest among the three satellites). Future research will focus on developing innovative empirical formulas for wind speed retrieval using GNSS-R technology, specifically aimed at correcting data errors caused by increased sea surface roughness. Additionally, a geophysical model function (GMF) will be established to relate different wind speed ranges to sea surface roughness, with the expectation of enhancing the stability and accuracy of TRITON's retrieval techniques under high wind speeds and severe weather conditions.