edu.ucar.opensky::articles:25040 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T23:08:58.285408 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7057kfc https://doi.org/10.5067/CYGNN-22511 https Related Dataset #1 NOAA CYGNSS Level 2 Science Wind Speed 25-km Product Version 1.1 https://doi.org/10.5067/CYGNS-L1X20 https Related Dataset #2 CYGNSS Level 1 Science Data Record Version 2.0 https://doi.org/10.5067/CYGNS-L1X21 https Related Dataset #3 CYGNSS Level 1 Science Data Record Version 2.1 https://doi.org/10.5067/CYGNS-L1X30 https Related Dataset #4 CYGNSS Level 1 Science Data Record Version 3.0 The NOAA track-wise wind retrieval algorithm and product assessment for CYGNSS 2021-07-13T00:00:00Z publication https://n2t.org/ark:/85065/d7057kfc https://doi.org/10.1109/TGRS.2021.3087426 Said, F. author Jelenak, Zorana author Park, J. author Chang, P. S. author UCAR/NCAR - Library publisher A novel approach in addressing cyclone global navigation satellite system (CyGNSS) intersatellite and GPS-related calibration issues is proposed, based on a track-wise ﾏバ 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 ﾏバ bias correction maintains CyGNSS signal sensitivity. Both intersatellite and GPS-related calibration issues are removed after correction. Long-term ﾏバ downward trend, observed throughout the CyGNSS mission, is greatly reduced. Using the corrected ﾏバ 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. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation