{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T06:04:16Z","timestamp":1775455456314,"version":"3.50.1"},"reference-count":95,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,22]],"date-time":"2021-04-22T00:00:00Z","timestamp":1619049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NASA ROSES","award":["NNH17CA04C"],"award-info":[{"award-number":["NNH17CA04C"]}]},{"name":"NASA ROSES","award":["80HQTR19C0003"],"award-info":[{"award-number":["80HQTR19C0003"]}]},{"name":"NASA ROSES","award":["NNH15CN50C"],"award-info":[{"award-number":["NNH15CN50C"]}]},{"name":"NASA ROSES","award":["80HQTR18C0035"],"award-info":[{"award-number":["80HQTR18C0035"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The measurement of ocean surface wind speeds in precipitation from satellite microwave radiometers is a challenging task. Rain attenuates the signal that is emitted from the ocean surface. Moreover, the rain and wind signals are very similar, which makes it difficult to distinguish wind from rain. The rain contamination can be mitigated for radiometers that operate simultaneously at C-band and X-band channels, such as WindSat, AMSR-E and AMSR2. The basic principle is to use combinations between C-band and X-band channels that are sensitive to wind speed but relatively insensitive to rain. Based on this principle, we have developed algorithms for retrieving wind speeds in rain from the WindSat and AMSR sensors. These algorithms are statistical regressions and are trained specifically under tropical cyclone conditions. We lay out the steps of the algorithm development, training, and testing. The major source for training the algorithm is provided by wind speeds from the SMAP L-band radiometer, which have been proven to provide reliable wind speeds in strong storms and are not affected by rain. We show that the WindSat and AMSR tropical cyclone wind algorithms perform well under precipitation where standard passive wind speed retrievals fail. We examine the possibility of extending the C\/X-band tropical cyclone wind algorithm to X\/K-band channels and discuss how it can be broadened from tropical cyclone conditions to global winds in rain retrievals.<\/jats:p>","DOI":"10.3390\/rs13091641","type":"journal-article","created":{"date-parts":[[2021,4,22]],"date-time":"2021-04-22T21:25:56Z","timestamp":1619126756000},"page":"1641","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Tropical Cyclone Wind Speeds from WindSat, AMSR and SMAP: Algorithm Development and Testing"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5488-1566","authenticated-orcid":false,"given":"Thomas","family":"Meissner","sequence":"first","affiliation":[{"name":"Remote Sensing Systems, 444 Tenth Street, Suite 200, Santa Rosa, CA 95401, USA"}]},{"given":"Lucrezia","family":"Ricciardulli","sequence":"additional","affiliation":[{"name":"Remote Sensing Systems, 444 Tenth Street, Suite 200, Santa Rosa, CA 95401, USA"}]},{"given":"Andrew","family":"Manaster","sequence":"additional","affiliation":[{"name":"Remote Sensing Systems, 444 Tenth Street, Suite 200, Santa Rosa, CA 95401, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8703","DOI":"10.1029\/96JC01751","article-title":"A well-calibrated ocean algorithm for special sensor microwave\/imager","volume":"102","author":"Wentz","year":"1997","journal-title":"J. Geophys. Res."},{"key":"ref_2","unstructured":"Wentz, F., and Meissner, T. (2021, February 14). Algorithm Theoretical Basis Document (ATBD), Version 2, AMSR Ocean Algorithm, RSS Tech. Report 121599A-1, Remote Sensing Systems, Santa Rosa, CA, 66 p. Available online: http:\/\/images.remss.com\/papers\/rsstech\/2000_121599A-1_Wentz_AMSR_Ocean_Algorithm_ATBD_Version2.pdf."},{"key":"ref_3","unstructured":"Wentz, F., and Meissner, T. (2021, February 14). Algorithm Theoretical Basis Document (ATBD), Supplement 1, AMSR Ocean Algorithm, RSS Tech. Report 1051707, Remote Sensing Systems, Santa Rosa, CA, 6 pp. Available online: http:\/\/images.remss.com\/papers\/rsstech\/2007_051707_Wentz_AMSR_Ocean_Algorithm_Version_2_Supplement1_ATBD.pdf."},{"key":"ref_4","unstructured":"Meissner, T., and Wentz, F. (March, January 28). Ocean Retrievals for WindSat. Proceedings of the IEEE MicroRad, San Juan, PR, USA. Available online: http:\/\/images.remss.com\/papers\/rssconf\/Meissner_microrad_2006_puertorico_windsat.pdf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1109\/TGRS.2005.862504","article-title":"A nonlinear optimization algorithm for WindSat wind vector retrievals","volume":"44","author":"Bettenhausen","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6882","DOI":"10.1175\/JCLI-D-15-0155.1","article-title":"A 17-Yr Climate Record of Environmental Parameters Derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager","volume":"28","author":"Wentz","year":"2015","journal-title":"J. Clim."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2165","DOI":"10.1109\/JSTARS.2016.2643641","article-title":"Evaluating and extending the ocean winds data climate record","volume":"99","author":"Wentz","year":"2017","journal-title":"J. Select. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_8","unstructured":"Wentz, F., Meissner, T., Gentemann, C., and Brewer, M. (2021, February 14). Remote Sensing Systems AQUA AMSR-E Daily Environmental Suite on 0.25 deg grid, Version 7.0, Wind Speed, Water Vapor, Cloud Liquid Water and Rain Rate. Remote Sensing Systems, Santa Rosa, CA. Available online: www.remss.com\/missions\/amsr."},{"key":"ref_9","unstructured":"Wentz, F., Meissner, T., Gentemann, C., Hilburn, K., and Scott, J. (2021, February 14). Remote Sensing Systems GCOM-W1 AMSR2 Daily Environmental Suite on 0.25 deg grid, Version 8.0, Wind Speed, Water Vapor, Cloud Liquid Water and Rain Rate. Remote Sensing Systems, Santa Rosa, CA. Available online: www.remss.com\/missions\/amsr."},{"key":"ref_10","unstructured":"Wentz, F., Ricciardulli, L., Gentemann, C., Meissner, T., Hilburn, K., and Scott, J. (2021, February 14). Remote Sensing Systems Coriolis WindSat Daily Environmental Suite on 0.25 deg grid, Version 7.0.1, Wind Speed and Rain Rate. Remote Sensing Systems, Santa Rosa, CA. Available online: www.remss.com\/missions\/windsat."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1109\/TGRS.2002.808331","article-title":"The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), NASDA\u2019s contribution to the EOS for global energy and water cycle studies","volume":"41","author":"Kawanishi","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","first-page":"13","article-title":"Instrument performance and calibration of AMSR-E and AMSR2","volume":"Volume 38","author":"Imaoka","year":"2010","journal-title":"International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Oki, T., Imaoka, K., and Kachi, M. (2010, January 25\u201330). AMSR instruments on GCOM-W1\/2: Concepts and applications. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, HI, USA.","DOI":"10.1109\/IGARSS.2010.5650001"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1109\/TGRS.2004.836867","article-title":"The WindSat spaceborne polarimetric microwave radiometer: Sensor description and early orbit performance","volume":"42","author":"Gaiser","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","unstructured":"Liou, K. (2002). An Introduction to Atmospheric Radiation, Elsevier Science. [2nd ed.]."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1126\/science.214.4518.274","article-title":"Airborne Microwave Remote-Sensing Measurements of Hurricane Allen","volume":"214","author":"Jones","year":"1981","journal-title":"Science"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1175\/1520-0426(2003)020<0099:VORSSS>2.0.CO;2","article-title":"Verification of Remotely Sensed Sea Surface Winds in Hurricanes","volume":"20","author":"Uhlhorn","year":"2003","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3070","DOI":"10.1175\/MWR3454.1","article-title":"Hurricane surface wind measurements from an operational stepped frequency microwave radiometer","volume":"135","author":"Uhlhorn","year":"2007","journal-title":"Mon. Wea. Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/LGRS.2010.2043814","article-title":"An improved C-band ocean surface emissivity model at hurricane-force wind speeds over a wide range of Earth incidence angles","volume":"7","author":"Jones","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2392","DOI":"10.1175\/JTECH-D-14-00028.1","article-title":"Improved Stepped Frequency Microwave Radiometer tropical cyclone surface winds in heavy precipitation","volume":"31","author":"Klotz","year":"2014","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1175\/JTECH-D-18-0005.1","article-title":"Off-Nadir SFMR Brightness Temperature Measurements in High-Wind Conditions","volume":"35","author":"Holbach","year":"2018","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Sapp, J., Alsweiss, S., Jelenak, Z., Chang, P., and Carswell, J. (2019). Stepped Frequency Microwave Radiometer wind-speed retrieval improvements. Remote Sens., 11.","DOI":"10.3390\/rs11030214"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3065","DOI":"10.1109\/TGRS.2009.2027012","article-title":"Wind vector retrievals under rain with passive satellite microwave radiometers","volume":"47","author":"Meissner","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Meissner, T., Ricciardulli, L., and Wentz, F. (2011, January 24\u201329). All-weather wind vector measurements from intercalibrated active and passive microwave satellite sensors. Proceedings of the 2011 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6049354"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhang, L., Yin, X., Shi, H., and Wang, Z. (2016). Hurricane Wind Speed Estimation Using WindSat 6 and 10 GHz Brightness Temperatures. Remote Sens., 8.","DOI":"10.3390\/rs8090721"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1007\/s10872-006-0060-8","article-title":"A wind speed retrieval algorithm by combining 6 and 10 GHz data from Advanced Microwave Scanning Radiometer: Wind speed inside hurricanes","volume":"62","author":"Shibata","year":"2006","journal-title":"J. Oceanogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3347","DOI":"10.1002\/grl.50664","article-title":"New approach for severe marine weather study using satellite passive microwave sensing, Geophys","volume":"40","author":"Zabolotskikh","year":"2013","journal-title":"Res. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.rse.2014.02.016","article-title":"GCOM-W1 AMSR2 and MetOp-A ASCAT wind speeds for the extratropical cyclones over the North Atlantic","volume":"147","author":"Zabolotskikh","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"4248","DOI":"10.1109\/JSTARS.2015.2416514","article-title":"New possibilities for geophysical parameter retrievals opened by GCOM-W1 AMSR2","volume":"8","author":"Zabolotskikh","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4501","DOI":"10.1109\/TGRS.2016.2543502","article-title":"Application of AMSR-E and AMSR2 low-frequency channel brightness temperature data for hurricane wind retrievals","volume":"54","author":"Mai","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/S0167-6105(98)00131-7","article-title":"The HRD real time hurricane wind analysis system","volume":"77\u201378","author":"Powell","year":"1998","journal-title":"J. Wind Eng. Ind. Aerodyn."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"822","DOI":"10.1175\/JTECH-D-11-00165.1","article-title":"Uncertainty and intercalibration analysis of H*Wind","volume":"29","author":"DiNapoli","year":"2012","journal-title":"J. Atmos. Oceanic Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1660","DOI":"10.1175\/BAMS-D-16-0052.1","article-title":"Capability of the SMAP Mission to measure ocean surface winds in storms","volume":"98","author":"Meissner","year":"2017","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_34","unstructured":"Meissner, T., Ricciardulli, L., and Wentz, F. (2021, February 14). Remote Sensing Systems SMAP daily Sea Surface Winds Speeds on 0.25 deg grid, Version 01.0. FINAL. Remote Sensing Systems, Santa Rosa, CA. Available online: www.remss.com\/missions\/smap\/."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1109\/JPROC.2010.2043918","article-title":"The Soil Moisture Active Passive (SMAP) mission","volume":"98","author":"Entekhabi","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_36","unstructured":"Entekhabi, D., Yueh, S., O\u2019Neill, P., Kellogg, K., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., and Crow, W. (2021, February 14). SMAP Handbook. National Aeronautics and Space Administration, Available online: https:\/\/smap.jpl.nasa.gov\/mission\/description\/."},{"key":"ref_37","unstructured":"Wentz, F. (2021, February 14). The effect of clouds and rain on the Aquarius salinity retrieval. RSS Tech. Report 3031805, Remote Sensing Systems, Santa Rosa, CA, 14 p. Available online: http:\/\/images.remss.com\/papers\/aquarius\/rain_effect_on_salinity.pdf."},{"key":"ref_38","first-page":"C02006","article-title":"SMOS satellite L-band radiometer: A new capability for ocean surface remote sensing in hurricanes","volume":"117","author":"Reul","year":"2012","journal-title":"J. Geophys. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.rse.2016.03.011","article-title":"A revised L-band radio-brightness sensitivity to extreme winds under tropical cyclones: The five year SMOS-storm data-base","volume":"180","author":"Reul","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"7339","DOI":"10.1109\/TGRS.2016.2600239","article-title":"SMAP L-band passive microwave observations of ocean surface wind during severe storms","volume":"54","author":"Yueh","year":"2016","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1175\/BAMS-D-15-00291.1","article-title":"A new generation of tropical cyclone size measurements from space","volume":"98","author":"Reul","year":"2017","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1109\/LGRS.2018.2849649","article-title":"SMAP radiometer-only tropical cyclone intensity and size validation","volume":"15","author":"Fore","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1175\/JTECH-D-18-0116.1","article-title":"Validation of high ocean surface winds from satellites using oil platform anemometers","volume":"36","author":"Manaster","year":"2019","journal-title":"J. Atmos. Oceanic Technol."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Manaster, A., Ricciardulli, L., and Meissner, T. (2021). Tropical Cyclone Wind Speeds from AMSR, WindSat and SMAP: Comparison with the HWRF Model. Remote Sens., submitted.","DOI":"10.3390\/rs13122347"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1109\/36.58966","article-title":"Optimum interpolation of imaging microwave radiometer data","volume":"28","author":"Poe","year":"1990","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Meissner, T., Wentz, F., and Draper, D. (2021, February 14). GMI Calibration Algorithm and Analysis Theoretical Basis Document, Version G, RSS Tech. Report 041912, Remote Sensing Systems, Santa Rosa, CA, 124 p. Available online: http:\/\/images.remss.com\/papers\/rsstech\/2012_041912_Meissner_GMI_ATBD_vG.pdf.","DOI":"10.56236\/RSS-au"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"6499","DOI":"10.1002\/2014JC009837","article-title":"The emission and scattering of L-band microwave radiation from rough ocean surfaces and wind speed measurements from Aquarius","volume":"119","author":"Meissner","year":"2014","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"5473","DOI":"10.1175\/2007JCLI1824.1","article-title":"Daily high-resolution blended analyses for sea surface temperature","volume":"20","author":"Reynolds","year":"2007","journal-title":"J. Climate"},{"key":"ref_49","unstructured":"(2021, February 14). NOAA Optimum Interpolation Sea Surface Temperature (OISST) v2.1, Available online: https:\/\/www.ncdc.noaa.gov\/oisst\/optimum-interpolation-sea-surface-temperature-oisst-v21."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1175\/1520-0469(1998)055<1613:SIRRWA>2.0.CO;2","article-title":"SSM\/I rain retrievals within a unified All-weather ocean algorithm","volume":"55","author":"Wentz","year":"1998","journal-title":"J. Atmos. Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1175\/2007JAMC1635.1","article-title":"Intercalibrated passive microwave rain products from the Unified Microwave Ocean Retrieval Algorithm (UMORA)","volume":"47","author":"Hilburn","year":"2008","journal-title":"J. Appl. Meteor. Climatol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"3004","DOI":"10.1109\/TGRS.2011.2179662","article-title":"The emissivity of the ocean surface between 6 and 90 GHz over a large range of wind speeds and Earth incidence angles","volume":"50","author":"Meissner","year":"2012","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"ref_53","unstructured":"Ashcroft, P., and Wentz, F. (2021, February 14). AMSR Level 2A Algorithm Theoretical Basis Document, RSS Tech. Report 121599B-1, Remote Sensing Systems, Santa Rosa, CA, p. 29. Available online: http:\/\/images.remss.com\/papers\/rsstech\/2000_121599B-1_Wentz_AMSR_Level2A_Algorithm_ATBD.pdf."},{"key":"ref_54","unstructured":"Wentz, F., Gentemann, C., and Ashcroft, P. (2021, February 14). On-orbit calibration of AMSR-E and the retrieval of ocean products, presented at 83rd AMS Annual Meeting, Long Beach, CA. 2003. Available online: http:\/\/images.remss.com\/papers\/rssconf\/Wentz_AMS_2003_LongBeach_AMSRE_calibration.pdf."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Wentz, F. (2021, February 14). Updates to the AMSR-E Level-2A Version B07 Algorithm, RSS Tech. Report 013006, Remote Sensing Systems, Santa Rosa, CA, p. 29. Available online: http:\/\/images.remss.com\/papers\/rsstech\/2006_013006_Wentz_AMSRE_L2A_Version_B07_Updates.pdf.","DOI":"10.56236\/RSS-al"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1836","DOI":"10.1109\/TGRS.2004.831888","article-title":"The complex dielectric constant of pure and sea water from microwave satellite observations","volume":"42","author":"Meissner","year":"2004","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Wentz, F., and Meissner, T. (2016). Atmospheric absorption model for dry air and water vapor at microwave frequencies below 100 GHz derived from spaceborne radiometer observations. Radio Sci., 51.","DOI":"10.56236\/RSS-ba"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1175\/1520-0493(1975)103<0420:TCIAAF>2.0.CO;2","article-title":"Tropical cyclone intensity analysis and forecasting from satellite imagery","volume":"103","author":"Dvorak","year":"1975","journal-title":"Mon. Wea. Rev."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1175\/1520-0477(2000)081<1231:TATCFS>2.3.CO;2","article-title":"The Automated Tropical Cyclone Forecasting System (version 3.2)","volume":"81","author":"Sampson","year":"2000","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1175\/BAMS-87-9-1195","article-title":"The Dvorak tropical cyclone intensity estimation technique: A satellite-based method that has endured for over 30 years","volume":"87","author":"Velden","year":"2006","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1175\/2009BAMS2755.1","article-title":"The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone best track data","volume":"91","author":"Knapp","year":"2010","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1175\/2010WAF2222375.1","article-title":"An evaluation of Dvorak Technique-based tropical cyclone intensity estimates","volume":"25","author":"Knaff","year":"2010","journal-title":"Wea. Forecast."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2149","DOI":"10.1175\/2011JAMC2673.1","article-title":"An automated, objective, multi-satellite platform tropical cyclone surface wind analysis","volume":"50","author":"Knaff","year":"2011","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"3576","DOI":"10.1175\/MWR-D-12-00254.1","article-title":"Atlantic hurricane database uncertainty and presentation of a new database format","volume":"141","author":"Landsea","year":"2013","journal-title":"Mon. Wea. Rev."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1175\/WAF-D-14-00149.1","article-title":"After a decade are Atlantic tropical cyclone gale force wind radii forecasts now skillful?","volume":"30","author":"Knaff","year":"2015","journal-title":"Wea. Forecast."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1175\/WAF-D-15-0009.1","article-title":"A consensus forecast for tropical cyclone gale wind radii","volume":"30","author":"Sampson","year":"2015","journal-title":"Wea. Forecast."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1175\/MWR-D-15-0267.1","article-title":"Using routinely available information to es-timate tropical cyclone wind structure","volume":"144","author":"Knaff","year":"2016","journal-title":"Mon. Wea. Rev."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1175\/WAF-D-16-0196.1","article-title":"Tropical cyclone gale wind radii estimates for the western North Pacific","volume":"32","author":"Sampson","year":"2017","journal-title":"Wea. Forecast."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1175\/WAF-D-17-0153.1","article-title":"Tropical cyclone gale wind radii estimates, forecasts and error forecast for the western North Pacific","volume":"33","author":"Sampson","year":"2018","journal-title":"Wea. Forecast."},{"key":"ref_70","unstructured":"(2021, February 14). National Hurricane Center Data Archive, Available online: https:\/\/www.nhc.noaa.gov\/data\/."},{"key":"ref_71","unstructured":"(2021, February 14). Joint Typhoon Warning Center Best Track Archive, Naval Oceanography Archive. Available online: https:\/\/www.metoc.navy.mil\/jtwc\/jtwc.html?best-tracks."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1109\/TGRS.2009.2027896","article-title":"Validation and calibration of ASCAT using CMOD5.n","volume":"48","author":"Verspeek","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1175\/WAF-D-19-0007.1","article-title":"The Advanced Dvorak Technique (ADT) for estimating tropical cyclone intensity: Update and new capabilities","volume":"34","author":"Olander","year":"2019","journal-title":"Wea. Forecast."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1175\/WAF-D-20-0015.1","article-title":"A consensus approach for estimating tropical cyclone intensity from meteoro-logical satellites: SATCON","volume":"35","author":"Velden","year":"2020","journal-title":"Wea. Forecast."},{"key":"ref_75","unstructured":"Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center\/University of Wisconsin-Madison (2021, February 14). TC Webpage Product Archive: SATCON. Available online: http:\/\/tropic.ssec.wisc.edu."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1175\/JAMC-D-19-0177.1","article-title":"Estimating the true maximum sustained wind speed of a tropical cyclone from spatially averaged observations","volume":"59","author":"Mayers","year":"2020","journal-title":"J. Appl. Meteorol. Clim."},{"key":"ref_77","unstructured":"Harper, B., Kepert, J., and Ginger, J. (2021, February 14). Guidelines for Converting between Various Wind Averaging Periods in Tropical Cyclone Conditions. World Metrological Organization WMO\/TD 1555, 2010; p. 64. Available online: https:\/\/library.wmo.int\/doc_num.php?explnum_id=290."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1175\/2009WAF2222280.1","article-title":"A Revised Tropical Cyclone Rapid Intensification Index for the Atlantic and Eastern North Pacific Basins","volume":"25","author":"Kaplan","year":"2010","journal-title":"Weather Forecast."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Mayers, D., and Ruf, C. (2020). MTrack: Improved Center Fix of Tropical Cyclones from SMAP Wind Observations. Bull. Amer. Meteor. Soc.","DOI":"10.1175\/BAMS-D-20-0068.1"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2","article-title":"The Tropical Rainfall Measuring Mission (TRMM) sensor package","volume":"15","author":"Kummerow","year":"1998","journal-title":"J. Atmos. Oceanic Technol."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"3452","DOI":"10.1109\/JSTARS.2015.2403303","article-title":"The Global Precipitation Meas-urement (GPM) Microwave Imager (GMI): Instrument overview and early on-orbit performance","volume":"8","author":"Draper","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_82","unstructured":"(2021, February 14). Weather System Follow-on, Ball Aerospace. Available online: https:\/\/www.ball.com\/aerospace\/getmedia\/d2ba7f42-c3dc-41e6-9114-016acb1906c5\/D3395_WSF_1.pdf.aspx?ext=.pdf."},{"key":"ref_83","unstructured":"(2021, February 14). Weather System Follow-on, eoPortal: Satellite Missions. Available online: https:\/\/directory.eoportal.org\/web\/eoportal\/satellite-missions\/content\/-\/article\/wsf-m."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1175\/BAMS-D-15-00032.1","article-title":"Satellite and in situ salinity: Understanding near-surface stratification and subfootprint variability","volume":"97","author":"Boutin","year":"2016","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_85","unstructured":"(2021, February 14). National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) Model 10-m Winds (at 0.25\u00b0 Resolution), Available online: www.nco.ncep.noaa.gov\/pmb\/products\/gfs\/."},{"key":"ref_86","unstructured":"Portmann, H. (2021, February 14). Handbook of Automated Data Quality Control Checks and Procedures. National Data Buoy Center Tech. Doc. 09\u201302, Available online: http:\/\/www.ndbc.noaa.gov\/NDBCHandbookofAutomatedDataQualityControl2009.pdf."},{"key":"ref_87","unstructured":"(2021, February 14). National Data Buoy Center: Data Access, Available online: https:\/\/www.ndbc.noaa.gov\/."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"14169","DOI":"10.1029\/97JC02906","article-title":"The Tropical Ocean\u2013Global Atmosphere (TOGA) observing system: A decade of progress","volume":"103","author":"McPhaden","year":"1998","journal-title":"J. Geophys. Res."},{"key":"ref_89","unstructured":"(2021, February 14). Pacific Marine Environmental Laboratory: Data Access, Available online: https:\/\/www.pmel.noaa.gov\/."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1175\/2008BAMS2462.1","article-title":"The PIRATA program: History, accomplishments, and future directions","volume":"89","author":"Bourles","year":"2008","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1175\/2008BAMS2608.1","article-title":"RAMA: The Research Moored Array for African\u2013Asian\u2013Australian Monsoon Analysis and Prediction","volume":"90","author":"McPhaden","year":"2009","journal-title":"Bull. Amer. Meteor. Soc."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"3709","DOI":"10.1175\/1520-0442(2002)015<3709:TWAWCA>2.0.CO;2","article-title":"Temperature, wind, and wave climatologies, and trends from marine meteorological buoys in the northeast Pacific","volume":"15","author":"Gower","year":"2002","journal-title":"J. Clim."},{"key":"ref_93","unstructured":"(2021, February 14). Fisheries and Oceans Canada: Marine Environmental Data Section. Available online: http:\/\/www.meds-sdmm.dfo-mpo.gc.ca\/isdm-gdsi\/waves-vagues\/index-eng.htm."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"11719","DOI":"10.1029\/1999JC000097","article-title":"Comparison of Special Sensor Microwave Imager and buoy-measured wind speeds from 1987 to 1997","volume":"106","author":"Mears","year":"2001","journal-title":"J. Geophys. Res."},{"key":"ref_95","unstructured":"Ricciardulli, L., and Wentz, F. (2021, February 14). Remote Sensing Systems ASCAT Daily Ocean Vector Winds on 0.25 deg grid, Version 02.1, Wind Speed. Remote Sensing Systems, Santa Rosa, CA. 2016. Remote Sensing Systems. Available online: www.remss.com\/missions\/ascat."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1641\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:51:29Z","timestamp":1760161889000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1641"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,22]]},"references-count":95,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091641"],"URL":"https:\/\/doi.org\/10.3390\/rs13091641","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,22]]}}}