{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T12:43:10Z","timestamp":1763988190325,"version":"build-2065373602"},"reference-count":76,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T00:00:00Z","timestamp":1620345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 41774028 and No. 41676167"],"award-info":[{"award-number":["No. 41774028 and No. 41676167"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Plan","award":["2017YFB050802"],"award-info":[{"award-number":["2017YFB050802"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LR21D060002"],"award-info":[{"award-number":["LR21D060002"]}]},{"name":"Key R$\\&amp;$D Project of Shandong Province","award":["2019JZZY010102"],"award-info":[{"award-number":["2019JZZY010102"]}]},{"name":"Project of State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography","award":["SOEDZZ2003"],"award-info":[{"award-number":["SOEDZZ2003"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19090103"],"award-info":[{"award-number":["XDA19090103"]}]},{"name":"Spanish Ministry of Economy and Competitiveness and EU\/FEDER","award":["ESP2015-70014-C2-2-R"],"award-info":[{"award-number":["ESP2015-70014-C2-2-R"]}]},{"name":"Ram\u00f3n y Cajal Program","award":["RYC2019-027000-I"],"award-info":[{"award-number":["RYC2019-027000-I"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CyGNSS) mission was launched in December 2016, which can remotely sense sea surface wind with a relatively high spatio-temporal resolution for tracking tropical cyclones. In recent years, with the gradual development of the geophysical model function (GMF) for CyGNSS wind retrieval, different versions of CyGNSS Level 2 products have been released and their performance has gradually improved. This paper presents a comprehensive evaluation of CyGNSS wind product v1.1 produced by the National Oceanic and Atmospheric Administration (NOAA). The Cross-Calibrated Multi-Platform (CCMP) analysis wind (v02.0 and v02.1 near real time) products produced by Remote Sensing Systems (RSS) were used as the reference. Data pairs between the NOAA CyGNSS and RSS CCMP products were processed and evaluated by the bias and standard deviation SD. The CyGNSS dataset covers the period between May 2017 and December 2020. The statistical comparisons show that the bias and SD of CyGNSS relative to CCMP-nonzero collocations when the flag of CCMP winds is nonzero are \u20130.05 m\/s and 1.19 m\/s, respectively. The probability density function (PDF) of the CyGNSS winds coincides with that of CCMP-nonzero. Furthermore, the average monthly bias and SD show that CyGNSS wind is consistent and reliable generally. We found that negative deviation mainly appears at high latitudes in both hemispheres. Positive deviation appears in the China Sea, the Arabian Sea, and the west of Africa and South America. Spatial\u2013temporal analysis demonstrates the geographical anomalies in the bias and SD of the CyGNSS winds, confirming that the wind speed bias shows a temporal dependency. The verification and comparison show that the remotely sensed wind speed measurements from NOAA CyGNSS wind product v1.1 are in good agreement with CCMP winds.<\/jats:p>","DOI":"10.3390\/rs13091832","type":"journal-article","created":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T22:36:24Z","timestamp":1620426984000},"page":"1832","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Validation of NOAA CyGNSS Wind Speed Product with the CCMP Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0426-3628","authenticated-orcid":false,"given":"Xiaohui","family":"Li","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, Beihang University, Beijing 100191, China"},{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongkai","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7514-3212","authenticated-orcid":false,"given":"Jingsong","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4883-0578","authenticated-orcid":false,"given":"Guoqi","family":"Han","sequence":"additional","affiliation":[{"name":"Fisheries and Oceans Canada, Institute of Ocean Sciences, Sidney, BC V8L 4B2, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8507-7880","authenticated-orcid":false,"given":"Gang","family":"Zheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6215-7607","authenticated-orcid":false,"given":"Weiqiang","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Space Sciences (ICE, CSIC), 08193 Barcelona, Spain"},{"name":"Institut d\u2019Estudis Espacials de Catalunya (IEEC), 08034 Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2469","DOI":"10.1109\/36.789643","article-title":"Ocean surface wind fields estimated from satellite active and passive microwave instruments","volume":"37","author":"Bentamy","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1175\/1520-0485(1985)015<1043:TEFFTW>2.0.CO;2","article-title":"The Energy Flux from the Wind to Near-Inertial Motions in the Surface Mixed Layer","volume":"15","year":"1985","journal-title":"J. Phys.Oceanogr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.rse.2006.06.005","article-title":"Wind resource assessment from C-band SAR","volume":"105","author":"Christiansen","year":"2006","journal-title":"Remote. Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2898","DOI":"10.3390\/rs6042898","article-title":"Reconstructed Wind Fields from Multi-Satellite Observations","volume":"6","author":"Tang","year":"2014","journal-title":"Remote. Sens."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Hu, T., Li, Y., Li, Y., Wu, Y., and Zhang, D. (2020). Retrieval of Sea Surface Wind Fields Using Multi-Source Remote Sensing Data. Remote. Sens., 12.","DOI":"10.3390\/rs12091482"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1175\/1520-0477(2001)082<1965:TEOMWF>2.3.CO;2","article-title":"The Effects of Marine Winds from Scatterometer Data on Weather Analysis and Forecasting","volume":"82","author":"Atlas","year":"2010","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xing, J., Shi, J., Lei, Y., Huang, X.Y., and Liu, Z. (2016). Evaluation of HY-2A scatterometer wind vectors using data from buoys, ERA-interim and ASCAT during 2012\u20132014. Remote. Sens., 8.","DOI":"10.3390\/rs8050390"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhou, L., Zheng, G., Li, X., Yang, J., and Lou, X. (2017). An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery. Remote Sens., 9.","DOI":"10.3390\/rs9070671"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1016\/S1352-2310(97)00184-2","article-title":"Numerical simulation of daytime mesoscale flow over highly complex terrain: Alps case","volume":"32","author":"Varvayanni","year":"1998","journal-title":"Atmos. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2273","DOI":"10.1029\/JC091iC02p02273","article-title":"The necessity for a new parametrisation of an empirical model for wind\/ocean scatterometry","volume":"91","author":"Woiceshyn","year":"1986","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"14250","DOI":"10.1029\/JC091iC12p14250","article-title":"Further Development of an Improved Altimeter Wind Speed Algorithm","volume":"91","author":"Chelton","year":"1987","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"14547","DOI":"10.1029\/JC094iC10p14547","article-title":"Remote sensing of ocean surface winds with the special sensor microwave\/imager","volume":"94","author":"Goodberlet","year":"1989","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_13","unstructured":"Quilfen, Y., and Cavanie, A. (1991). A High Precision Wind Algorithm For The Ers1 Scatterometer Furthermore, Its Validation. Proceedings of the 11th Annual International Geoscience and Remote Sensing Symposium, Espoo, Finland, 3\u20136 June 1991, IEEE."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"490","DOI":"10.5589\/m02-028","article-title":"Wind information for marine weather forecasting from RADARSAT-1 synthetic aperture radar data: Initial results from the \u201cMarine winds from SAR\u201d demonstration project","volume":"28","author":"Flett","year":"2002","journal-title":"Can. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"524","DOI":"10.5589\/m02-043","article-title":"Ocean winds from RADARSAT-1 ScanSAR","volume":"28","author":"Jochen","year":"2002","journal-title":"Can. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"498","DOI":"10.5589\/m02-029","article-title":"Wind direction estimation from SAR images of the ocean using wavelet analysis","volume":"28","author":"Du","year":"2002","journal-title":"Can. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"462","DOI":"10.5589\/m03-075","article-title":"Comparison of C-band wind retrieval model functions with airborne multipolarization SAR data","volume":"30","author":"Vachon","year":"2004","journal-title":"Can. J. Remote Sens."},{"key":"ref_18","unstructured":"Montuori, A., Ricchi, A., Benassai, G., and Migliaccio, M. (December, January 29). Sea Wave Numerical Simulations and Verification in Tyrrhenian Coastal Area with X-Band Cosmo-Skymed SAR Data. Proceedings of the ESA, SOLAS & EGU Joint Conference Earth Observation for Ocean-Atmosphere Interactions Science, Frascati, Italy."},{"key":"ref_19","unstructured":"Benassai, G., Migliaccio, M., Montuori, A., and Ricchi, A. (2012, January 22\u201327). SWAN wave simulations in the Southern Thyrrenian Sea with COSMO SKY-MED SAR data. Proceedings of the EGU General Assembly, Vienna, Austria."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"443","DOI":"10.3389\/fmars.2019.00443","article-title":"Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling","volume":"6","author":"Bourassa","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Hasager, C., and Sj\u00f6holm, M. (2019). Remote Sensing of Atmospheric Conditions for Wind Energy Applications, MDPI. Remote Sensing, MDPI Books.","DOI":"10.3390\/rs11070781"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"8382","DOI":"10.1029\/2001JD001512","article-title":"Next generation of NOAA\/NESDIS TMI, SSM\/I, and AMSR-E microwave land rainfall algorithms","volume":"108","author":"McCollum","year":"2003","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Surussavadee, C., Staelin, D.H., Chadarong, V., Mclaughlin, D., and Entekhabi, D. (2008). Comparison of NOWRAD, AMSU, AMSR-E, TMI, and SSM\/I surface precipitation rate Retrievals over the united states great plains. Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain, 23\u201327 July 2007, IEEE.","DOI":"10.1109\/IGARSS.2007.4423702"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1002\/qj.828","article-title":"The ERA-Interim reanalysis: Configuration and performance of the data assimilation system","volume":"137","author":"Dee","year":"2011","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.1175\/JCLI-D-12-00823.1","article-title":"The NCEP Climate Forecast System Version 2","volume":"27","author":"Saha","year":"2012","journal-title":"J. Clim."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1175\/2010BAMS2946.1","article-title":"A Cross-calibrated, Multiplatform Ocean Surface Wind Velocity Product for Meteorological and Oceanographic Applications","volume":"92","author":"Atlas","year":"2011","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"33","DOI":"10.4031\/MTSJ.52.3.6","article-title":"The Tampa Bay Coastal Ocean Model Performance for Hurricane Irma","volume":"52","author":"Chen","year":"2018","journal-title":"Mar. Technol. Soc. J."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1002\/2016JC012112","article-title":"Winds on the West Florida Shelf: Regional comparisons between observations and model estimates","volume":"122","author":"Mayer","year":"2017","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_29","first-page":"331","article-title":"A Passive Reflectometry and Interferometry System (PARIS): Application to ocean altimetry","volume":"17","year":"1993","journal-title":"ESA J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4419","DOI":"10.1109\/TGRS.2016.2541343","article-title":"Wind Speed Retrieval Algorithm for the Cyclone Global Navigation Satellite System (CYGNSS) Mission","volume":"54","author":"Clarizia","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/JSTARS.2018.2833075","article-title":"Development of the CYGNSS Geophysical Model Function for Wind Speed","volume":"12","author":"Ruf","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1029\/2004GL020680","article-title":"Sea state monitoring using coastal GNSS-R","volume":"31","author":"Soulat","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Roggenbuck, O., Reinking, J., and Lambertus, T. (2019). Determination of Significant Wave Heights Using Damping Coefficients of Attenuated GNSS SNR Data from Static and Kinematic Observations. Remote Sens., 11.","DOI":"10.3390\/rs11040409"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4989","DOI":"10.1109\/TGRS.2017.2699122","article-title":"Sea Ice Detection Using U.K. TDS-1 GNSS-R Data","volume":"55","author":"Zavorotny","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1510","DOI":"10.1109\/LGRS.2018.2852143","article-title":"Sea Ice Sensing From GNSS-R Data Using Convolutional Neural Networks","volume":"15","author":"Yan","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"8369","DOI":"10.1002\/2017GL074513","article-title":"First spaceborne phase altimetry over sea ice using TechDemoSat-1 GNSS-R signals","volume":"44","author":"Li","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"6243","DOI":"10.1109\/TGRS.2020.2975817","article-title":"The Validation of the Weight Function in the Leading-Edge-Derivative Path Delay Estimator for Space-Based GNSS-R Altimetry","volume":"58","author":"Hu","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"111959","DOI":"10.1016\/j.rse.2020.111959","article-title":"Tidal analysis of GNSS reflectometry applied for coastal sea level sensing in Antarctica and Greenland","volume":"248","author":"Tabibi","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/BF01030061","article-title":"Mapping surface soil moisture with microwave radiometers","volume":"54","author":"Schmugge","year":"1994","journal-title":"Meteorol. Atmos. Phys."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3616","DOI":"10.1109\/TGRS.2009.2030672","article-title":"Soil Moisture Retrieval Using GNSS-R Techniques: Experimental Results Over a Bare Soil Field","volume":"47","author":"Camps","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1109\/36.898676","article-title":"The PARIS Concept: An Experimental Demonstration of Sea Surface Altimetry Using GPS Reflected Signals","volume":"39","author":"Caparrini","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Mart\u00edn-Neira, F., Camps, A., Martin-Neira, M., D\u2019Addio, S., and Park, H. (2015). Significant wave height retrieval based on the effective number of incoherent averages. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 26\u201331 July 2015, IEEE.","DOI":"10.1109\/IGARSS.2015.7326609"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1109\/36.841977","article-title":"Scattering of GPS signals from the ocean with wind remote sensing application","volume":"38","author":"Zavorotny","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/S0034-4257(00)00091-2","article-title":"GPS Signal Scattering from Sea Surface: Wind Speed Retrieval Using Experimental Data and Theoretical Model","volume":"73","author":"Komjathy","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Cardellach, E., Fabra, F., Nogu\u00e9s-Correig, O., Oliveras, S., Rib\u00f3, S., and Rius, A. (2011). GNSS-R ground-based and airborne campaigns for ocean, land, ice, and snow techniques: Application to the GOLD-RTR data sets. Radio Sci., 46.","DOI":"10.1029\/2011RS004683"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1375","DOI":"10.1029\/2002GL014759","article-title":"5-cm-Precision aircraft ocean altimetry using GPS reflections","volume":"29","author":"Lowe","year":"2002","journal-title":"Geophys. Res. Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4992","DOI":"10.1109\/TGRS.2013.2286257","article-title":"Consolidating the Precision of Interferometric GNSS-R Ocean Altimetry Using Airborne Experimental Data","volume":"52","author":"Cardellach","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1522","DOI":"10.1109\/JSTARS.2014.2322854","article-title":"Airborne GNSS-R Polarimetric Measurements for Soil Moisture and Above-Ground Biomass Estimation","volume":"7","author":"Egido","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Lowe, S.T., Labrecque, J.L., Zuffada, C., Romans, L.J., Young, L.E., and Hajj, G.A. (2016). First spaceborne observation of an Earth-reflected GPS signal. Radio Sci., 37.","DOI":"10.1029\/2000RS002539"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1109\/TGRS.2005.845643","article-title":"Detection and Processing of bistatically reflected GPS signals from low Earth orbit for the purpose of ocean remote sensing","volume":"43","author":"Gleason","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"5435","DOI":"10.1002\/2015GL064204","article-title":"Spaceborne GNSS reflectometry for ocean winds: First results from the UK TechDemoSat-1 mission","volume":"42","author":"Foti","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"4534","DOI":"10.1109\/JSTARS.2018.2873241","article-title":"TDS-1 GNSS Reflectometry: Development and Validation of Forward Scattering Winds","volume":"11","author":"Asgarimehr","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"4678","DOI":"10.1109\/JSTARS.2016.2602703","article-title":"The GNSS Reflectometry Response to the Ocean Surface Winds and Waves","volume":"9","author":"Soisuvarn","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3418","DOI":"10.1109\/JSTARS.2017.2674305","article-title":"An Assessment of Non-geophysical Effects in Spaceborne GNSS Reflectometry Data From the UK TechDemoSat-1 Mission","volume":"10","author":"Foti","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"111744","DOI":"10.1016\/j.rse.2020.111744","article-title":"Temporal variability of GNSS-Reflectometry ocean wind speed retrieval performance during the UK TechDemoSat-1 mission","volume":"242","author":"Hammond","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_56","unstructured":"Ruf, C., and Twigg, D. (2021, February 02). Level 1 and 2 Trackwise Corrected Climate Data Record Algorithm Theoretical Basis Document. Available online: https:\/\/clasp-research.engin.umich.edu\/missions\/cygnss\/reference\/148-0389."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Jing, C., Niu, X., Duan, C., Lu, F., and Yang, X. (2019). Sea Surface Wind Speed Retrieval from the First Chinese GNSS-R Mission: Technique and Preliminary Results. Remote Sens., 11.","DOI":"10.3390\/rs11243013"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"6829","DOI":"10.1109\/TGRS.2014.2303831","article-title":"Spaceborne GNSS-R Minimum Variance Wind Speed Estimator","volume":"52","author":"Clarizia","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Clarizia, M.P., Ruf, C.S., Gleason, S., Balasubramaniam, R., and Mckague, D. (2017). Generation of CYGNSS level 2 wind speed data products. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), FortWorth, TX, USA, 23\u201328 July 2017, IEEE.","DOI":"10.1109\/IGARSS.2017.8127539"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1109\/JSTARS.2018.2825948","article-title":"Assessment of CYGNSS Wind Speed Retrieval Uncertainty","volume":"12","author":"Ruf","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1175\/JTECH-D-20-0079.1","article-title":"CYGNSS Ocean Surface Wind Validation in the Tropics","volume":"38","author":"Asharaf","year":"2020","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_62","unstructured":"Said, F., Jelenak, Z., Park, J., Chang, P.S., and Soisuvarn, S. (2019, January 6). NOAA CyGNSSWind Product-Ver 1.0; Presentations. Proceedings of the CyGNSS Science TeamWebex Telecon, online."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"6997","DOI":"10.1029\/2019JC015367","article-title":"A Near-Real-Time Version of the Cross-Calibrated Multiplatform (CCMP) Ocean Surface Wind Velocity Data Set","volume":"124","author":"Mears","year":"2019","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"638","DOI":"10.1109\/TGRS.2005.855997","article-title":"Evaluation of WindSat wind vector performance with respect to QuikSCAT estimates","volume":"44","author":"Monaldo","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1842","DOI":"10.1175\/JTECH-D-12-00240.1","article-title":"Assessment of Sea Surface Wind from NWP Reanalyses and Satellites in the Southern Ocean","volume":"30","author":"Li","year":"2013","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_66","unstructured":"Wang, X., Shum, C.K., and Johnson, J. (2014, January 1\u20134). Analysis of Surface Wind Diurnal Cycles in Tropical Regions using Mooring Observations and the CCMP Product. Proceedings of the Conference on Hurricanes and Tropical Meteorology American Meteorological Society, Washington, DC, USA."},{"key":"ref_67","first-page":"150626133330005","article-title":"New Ocean Winds Satellite Mission to Probe Hurricanes and Tropical Convection","volume":"97","author":"Ruf","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_68","unstructured":"Said, F., Jelenak, Z., Park, J., and Chang, P.S. (2020, January 6). An Introduction to v1.1 NOAA CyGNSS Wind Product and a Look at v3.0 Level 1 Data. Proceedings of the CyGNSS Science Team Webex Telecon, online. Technical Report."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2009","DOI":"10.1175\/BAMS-D-18-0337.1","article-title":"In-Orbit Performance of the Constellation of CYGNSS Hurricane Satellites","volume":"100","author":"Ruf","year":"2019","journal-title":"Bull. Amer. Meteorol. Soc."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Said, F., Jelenak, Z., Park, J., Soisuvarn, S., and Chang, P.S. (2019). A \u2018Track-Wise\u2019 Wind Retrieval Algorithm for the CYGNSS Mission. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July\u20132 August 2019, IEEE.","DOI":"10.1109\/IGARSS.2019.8898099"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Chang, P.S., Jelenak, Z., Said, F., and Soisuvarn, S. (2018). CYGNSS Observations of Ocean Winds and Waves. Proceedings of the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22\u201327 July 2018, IEEE.","DOI":"10.1109\/IGARSS.2018.8517846"},{"key":"ref_72","unstructured":"Said, F., Jelenak, Z., and Chang, P.S. (2020). V1.1 NOAA Level 2 CyGNSS Winds Basic User Guide, Compiled by the OSWT at NOAA-NESDIS-STAR. September 2020."},{"key":"ref_73","unstructured":"Ruf, C., Atlas, R., Majumdar, S., Ettammal, S., and Waliser, D. (2017, January 23\u201328). NASA CYGNSS Tropical Cyclone Mission. Proceedings of the EGU, General Assembly Conference, Vienna, Austria."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1109\/LGRS.2018.2872354","article-title":"On the Estimation of Wind Speed Diurnal Cycles Using Simulated Measurements of CYGNSS and ASCAT","volume":"16","author":"Yi","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"8741","DOI":"10.1029\/96JB00104","article-title":"A global, self-consistent, hierarchical, high-resolution shoreline database","volume":"101","author":"Wessel","year":"1996","journal-title":"J. Geophys. Res."},{"key":"ref_76","unstructured":"Said, F., Jelenak, Z., Park, J., Soisuvarn, S., and Chang, P.S. (2019, January 14). Latest Cal\/Val Assessment of v2.1 L1\/L2 Data. Proceedings of the CyGNSS Science Team Meeting on JPL, Pasadena, CA, USA. 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