TY - JOUR
T1 - The NOAA Track-Wise Wind Retrieval Algorithm and Product Assessment for CyGNSS
AU - Said, Faozi
AU - Jelenak, Zorana
AU - Park, Jeonghwan
AU - Chang, Paul S.
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2022
Y1 - 2022
N2 - A novel approach in addressing cyclone global navigation satellite system (CyGNSS) intersatellite and GPS-related calibration issues is proposed, based on a track-wise $\sigma ^{o}$ bias correction method. This method makes use of both ancillary data from numerical weather prediction models and a semiempirical geophysical model function. Care is taken, so the track-wise $\sigma ^{o}$ bias correction maintains CyGNSS signal sensitivity. Both intersatellite and GPS-related calibration issues are removed after correction. Long-term $\sigma ^{o}$ downward trend, observed throughout the CyGNSS mission, is greatly reduced. Using the corrected $\sigma ^{o}$ measurements, a wind retrieval method is also presented and its product thoroughly assessed for a three-year period against European Centre for Medium-Range Weather Forecasts (ECMWFs), Advanced Scatterometer (ASCAT) A/B, Advanced Microwave Scanning Radiometer (AMSR)-2, GMI, WindSat, hurricane weather research and forecasting (HWRF) model, and the stepped frequency microwave radiometer (SFMR) winds. The overall wind speed bias and standard deviation of the error (stde) against ECMWF are 0.16 and 1.19 m/s, while these are -0.11 and 1.12 m/s against ASCAT A/B, respectively. The same metrics against AMSR-2/GMI/WindSat (combined) are -0.19 and 1.11 m/s, respectively. The bias and stde against soil moisture active passive (SMAP) are -0.38 and 1.90 m/s, respectively. In the tropical cyclone environment, the bias and stde against HWRF are -0.54 and 2.90 m/s, and -4.71 and 5.88 m/s with SFMR. Finally, CyGNSS wind performance is gauged in the presence of rain. Below 10 m/s, the bias between CyGNSS and ECMWF increases as the rain rate increases. Between 10 and 15 m/s, biases are mostly absent. Above 15 m/s, results are inconclusive due to the low number of collocated rain samples. Overall, the presented CyGNSS wind speed product both exhibits consistency and reliability, showing promise of using GNSS-R derived winds for operational purposes.
AB - A novel approach in addressing cyclone global navigation satellite system (CyGNSS) intersatellite and GPS-related calibration issues is proposed, based on a track-wise $\sigma ^{o}$ bias correction method. This method makes use of both ancillary data from numerical weather prediction models and a semiempirical geophysical model function. Care is taken, so the track-wise $\sigma ^{o}$ bias correction maintains CyGNSS signal sensitivity. Both intersatellite and GPS-related calibration issues are removed after correction. Long-term $\sigma ^{o}$ downward trend, observed throughout the CyGNSS mission, is greatly reduced. Using the corrected $\sigma ^{o}$ measurements, a wind retrieval method is also presented and its product thoroughly assessed for a three-year period against European Centre for Medium-Range Weather Forecasts (ECMWFs), Advanced Scatterometer (ASCAT) A/B, Advanced Microwave Scanning Radiometer (AMSR)-2, GMI, WindSat, hurricane weather research and forecasting (HWRF) model, and the stepped frequency microwave radiometer (SFMR) winds. The overall wind speed bias and standard deviation of the error (stde) against ECMWF are 0.16 and 1.19 m/s, while these are -0.11 and 1.12 m/s against ASCAT A/B, respectively. The same metrics against AMSR-2/GMI/WindSat (combined) are -0.19 and 1.11 m/s, respectively. The bias and stde against soil moisture active passive (SMAP) are -0.38 and 1.90 m/s, respectively. In the tropical cyclone environment, the bias and stde against HWRF are -0.54 and 2.90 m/s, and -4.71 and 5.88 m/s with SFMR. Finally, CyGNSS wind performance is gauged in the presence of rain. Below 10 m/s, the bias between CyGNSS and ECMWF increases as the rain rate increases. Between 10 and 15 m/s, biases are mostly absent. Above 15 m/s, results are inconclusive due to the low number of collocated rain samples. Overall, the presented CyGNSS wind speed product both exhibits consistency and reliability, showing promise of using GNSS-R derived winds for operational purposes.
KW - Geophysical measurements
KW - global positioning system
KW - microwave reflectometry
KW - radar measurements
KW - remote sensing
KW - scattering
KW - sea surface
KW - wind
UR - https://www.scopus.com/pages/publications/85110817696
U2 - 10.1109/TGRS.2021.3087426
DO - 10.1109/TGRS.2021.3087426
M3 - Article
AN - SCOPUS:85110817696
SN - 0196-2892
VL - 60
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
ER -