{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:27:37Z","timestamp":1772252857322,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T00:00:00Z","timestamp":1662076800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["41925024"],"award-info":[{"award-number":["41925024"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["41906178"],"award-info":[{"award-number":["41906178"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["41925024"],"award-info":[{"award-number":["41925024"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["41906178"],"award-info":[{"award-number":["41906178"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}]},{"name":"National Natural Science Foundation of China","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}]},{"name":"National Natural Science Foundation of China","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}]},{"name":"National Natural Science Foundation of China","award":["41925024"],"award-info":[{"award-number":["41925024"]}]},{"name":"National Natural Science Foundation of China","award":["41906178"],"award-info":[{"award-number":["41906178"]}]},{"name":"National Natural Science Foundation of China","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}]},{"name":"National Natural Science Foundation of China","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}]},{"name":"National Natural Science Foundation of China","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["41925024"],"award-info":[{"award-number":["41925024"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["41906178"],"award-info":[{"award-number":["41906178"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}]},{"name":"Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["41925024"],"award-info":[{"award-number":["41925024"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["41906178"],"award-info":[{"award-number":["41906178"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}]},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, the Chinese Academy of Sciences","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["41925024"],"award-info":[{"award-number":["41925024"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["41906178"],"award-info":[{"award-number":["41906178"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}]},{"name":"China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["2017YFA0603200"],"award-info":[{"award-number":["2017YFA0603200"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["XDB42000000"],"award-info":[{"award-number":["XDB42000000"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["41925024"],"award-info":[{"award-number":["41925024"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["41906178"],"award-info":[{"award-number":["41906178"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["GML2019ZD0306"],"award-info":[{"award-number":["GML2019ZD0306"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["ISEE2021ZD01"],"award-info":[{"award-number":["ISEE2021ZD01"]}]},{"name":"Independent Research Project Program of State Key Laboratory of Tropical Oceanography","award":["LTOZZ2004"],"award-info":[{"award-number":["LTOZZ2004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Near-surface humidity (Qa) is a key parameter that modulates oceanic evaporation and influences the global water cycle. Remote sensing observations act as feasible sources for long-term and large-scale Qa monitoring. However, existing satellite Qa retrieval models are subject to apparent uncertainties due to model errors and insufficient training data. Based on in situ observations collected over the China Seas over the last two decades, a deep learning approach named Ensemble Mean of Target deep neural networks (EMTnet) is proposed to improve the satellite Qa retrieval over the China Seas for the first time. The EMTnet model outperforms five representative existing models by nearly eliminating the mean bias and significantly reducing the root-mean-square error in satellite Qa retrieval. According to its target deep neural network selection process, the EMTnet model can obtain more objective learning results when the observational data are divergent. The EMTnet model was subsequently applied to produce 30-year monthly gridded Qa data over the China Seas. It indicates that the climbing rate of Qa over the China Seas under the background of global warming is probably underestimated by current products.<\/jats:p>","DOI":"10.3390\/rs14174353","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"4353","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deep Learning to Near-Surface Humidity Retrieval from Multi-Sensor Remote Sensing Data over the China Seas"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6870-474X","authenticated-orcid":false,"given":"Rongwang","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China"},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences, Guangzhou 511458, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weihao","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China"},{"name":"Innovation Academy of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences, Guangzhou 511458, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,2]]},"reference":[{"key":"ref_1","unstructured":"Baumgartner, A., and Reichel, E. (1975). The World Water Balance, Elsevier."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1038\/359373a0","article-title":"The hydrological cycle and its influence on climate","volume":"359","author":"Chahine","year":"1992","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1175\/JHM600.1","article-title":"Estimates of the global water budget and its annual cycle using observational and model data","volume":"8","author":"Trenberth","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"5376","DOI":"10.1175\/2007JCLI1714.1","article-title":"Global variations in oceanic evaporation (1958\u20132005): The role of the changing wind Speed","volume":"20","author":"Yu","year":"2007","journal-title":"J. Clim."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"D20118","DOI":"10.1029\/2010JD013949","article-title":"Evaporation change and global warming: The role of net radiation and relative humidity","volume":"115","author":"Lorenz","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1175\/JTECH-D-14-00080.1","article-title":"An improved near-surface specific humidity and air temperature climatology for the SSM\/I satellite period","volume":"32","author":"Jin","year":"2015","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"C03018","DOI":"10.1029\/2009JC005545","article-title":"An assessment of surface heat fluxes from J-OFURO2 at the KEO and JKEO sites","volume":"115","author":"Tomita","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1175\/JTECH-D-15-0122.1","article-title":"Decomposition of random errors inherent to HOAPS-3.2 near-surface humidity estimates using multiple triple collocation analysis","volume":"33","author":"Kinzel","year":"2016","journal-title":"J. Atmos. Ocean. Tech."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5469","DOI":"10.1175\/2011JCLI4223.1","article-title":"An assessment of the uncertainties in ocean surface turbulent fluxes in 11 reanalysis, satellite-derived, and combined global datasets","volume":"24","author":"Brunke","year":"2011","journal-title":"J. Clim."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1002\/joc.3691","article-title":"A comparison of global marine surface-specific humidity datasets from in situ observations and atmospheric reanalysis","volume":"34","author":"Kent","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6135","DOI":"10.1175\/JCLI-D-13-00384.1","article-title":"Consistency of estimated global water cycle variations over the satellite era","volume":"27","author":"Robertson","year":"2014","journal-title":"J. Clim."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8289","DOI":"10.1175\/JCLI-D-14-00555.1","article-title":"The observed state of the water cycle in the early twenty-first century","volume":"28","author":"Rodell","year":"2015","journal-title":"J. Clim."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1793","DOI":"10.5194\/amt-11-1793-2018","article-title":"Uncertainty characterization of HOAPS 3.3 latent heat-flux-related parameters","volume":"11","author":"Liman","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1220","DOI":"10.1029\/2018EA000436","article-title":"Improving near-surface retrievals of surface humidity over the global open oceans from passive microwave observations","volume":"6","author":"Roberts","year":"2019","journal-title":"Earth Space Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"7111","DOI":"10.1175\/JCLI-D-17-0713.1","article-title":"On the simulations of global oceanic latent heat flux in the CMIP5 multimodel ensemble","volume":"31","author":"Zhang","year":"2018","journal-title":"J. Clim."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1002\/2017GL076384","article-title":"Improved satellite estimation of near-surface humidity using vertical water vapor profile information","volume":"45","author":"Tomita","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.1175\/1520-0485(1984)014<1451:DOMMHI>2.0.CO;2","article-title":"Determination of monthly mean humidity in the atmospheric surface layer over oceans from satellite data","volume":"14","author":"Liu","year":"1984","journal-title":"J. Phys. Oceanogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1591","DOI":"10.1175\/1520-0493(1986)114<1591:SRBMMP>2.0.CO;2","article-title":"Statistical relation between monthly precipitable water and surface-level humidity over global oceans","volume":"114","author":"Liu","year":"1986","journal-title":"Mon. Weather Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"14539","DOI":"10.1029\/JC094iC10p14539","article-title":"The relationship between total precipitable water and surface-level humidity over the sea surface: A further evaluation","volume":"94","author":"Hsu","year":"1989","journal-title":"J. Geophys. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2773","DOI":"10.1080\/01431169308904308","article-title":"Water vapour in the atmospheric boundary layer over oceans from SSM\/I measurements","volume":"14","author":"Schulz","year":"1993","journal-title":"Int. J. Remote Sens"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/0273-1177(95)00389-V","article-title":"Retrieval of latent heat flux and longwave irradiance at the sea surface from SSM\/I and AVHRR measurements","volume":"16","author":"Schanz","year":"1995","journal-title":"Adv. Space Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1175\/1520-0493(1995)123<2405:EOSHAL>2.0.CO;2","article-title":"Estimates of surface humidity and latent heat fluxes over oceans from SSM\/I Data","volume":"123","author":"Chou","year":"1995","journal-title":"Mon. Weather Rev."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1175\/1520-0450(1999)038<1229:ANMFDO>2.0.CO;2","article-title":"A new method for deriving ocean surface specific humidity and air temperature: An artificial neural network approach","volume":"38","author":"Jones","year":"1999","journal-title":"J. Appl. Meteorol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1175\/1520-0442(2003)016<0637:SEOWSA>2.0.CO;2","article-title":"Satellite estimates of wind speed and latent heat flux over the global oceans","volume":"16","author":"Bentamy","year":"2003","journal-title":"J. Clim."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"D10306","DOI":"10.1029\/2005JD006431","article-title":"Near-surface retrieval of air temperature and specific humidity using multi-sensor microwave satellite observations","volume":"111","author":"Jackson","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"8016","DOI":"10.3390\/s8128016","article-title":"Retrieval of surface air specifific humidity over the ocean using AMSR-E measurements","volume":"8","author":"Kubota","year":"2008","journal-title":"Sensors"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"D16303","DOI":"10.1029\/2008JD011341","article-title":"Improved multisensor approach to satellite-retrieved near-surface specific humidity observations","volume":"114","author":"Jackson","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.rse.2018.06.001","article-title":"A regime-dependent retrieval algorithm for near-surface air temperature and specific humidity from multi-microwave sensors","volume":"215","author":"Yu","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gao, Q., Wang, S., and Yang, X. (2019). Estimation of surface air specific humidity and air\u2013sea latent heat flux using FY-3C microwave observations. Remote Sens., 11.","DOI":"10.3390\/rs11040466"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1820","DOI":"10.1175\/JTECH-D-12-00153.1","article-title":"Validation of satellite-derived daily latent heat flux over the South China Sea, compared with observations and five products","volume":"30","author":"Wang","year":"2013","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"5088","DOI":"10.1002\/2016JC012332","article-title":"Biases of five latent heat flux products and their impacts on mixed-layer temperature estimates in the South China Sea","volume":"122","author":"Wang","year":"2017","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"D19113","DOI":"10.1029\/2009JD013099","article-title":"Predicting near-surface atmospheric variables from Special Sensor Microwave\/Imager using neural networks with a first-guess approach","volume":"115","author":"Roberts","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1038\/s41586-019-0912-1","article-title":"Prabhat Deep learning and process understanding for data-driven earth system science","volume":"566","author":"Reichstein","year":"2019","journal-title":"Nature"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"9101","DOI":"10.1029\/2019JC015577","article-title":"Coastal inundation mapping from bitemporal and dual-polarization SAR imagery based on deep convolutional neural networks","volume":"124","author":"Liu","year":"2019","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1093\/nsr\/nwaa047","article-title":"Deep-learning-based information mining from ocean remote-sensing imagery","volume":"7","author":"Li","year":"2020","journal-title":"Nat. Sci. Rev."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3495","DOI":"10.1109\/JSTARS.2021.3066552","article-title":"Carbon sinks and variations of pCO2 in the Southern Ocean from 1998 to 2018 based on a deep learning approach","volume":"14","author":"Wang","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1007\/s11802-016-2804-4","article-title":"Effects of precipitation on sonic anemometer measurements of turbulent Fluxes in the atmospheric surface layer","volume":"15","author":"Zhang","year":"2016","journal-title":"J. Ocean Univ. China"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"6091","DOI":"10.5194\/amt-11-6091-2018","article-title":"Evaluation of OAFlux datasets based on in situ air\u2013sea flux tower observations over the Yongxing Islands in 2016","volume":"11","author":"Zhou","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1175\/1520-0442(2003)016<0571:BPOASF>2.0.CO;2","article-title":"Bulk parameterization of air-sea fluxes: Updates and verification for the COARE algorithm","volume":"16","author":"Fairall","year":"2003","journal-title":"J. Clim."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Wentz, F.J. (2013). SSM\/I Version-7 Calibration Report (Report Number 011012), Remote Sensing Systems.","DOI":"10.56236\/RSS-av"},{"key":"ref_41","unstructured":"Zou, C.-Z., and Wang, W. (2013). Climate Algorithm Theoretical Basis Document (C-ATBD)\u2014AMSU Radiance Fundamental Climate Data Record Derived From Integrated Microwave Inter-calibration Approach, NOAA. Technical Report."},{"key":"ref_42","unstructured":"Zou, C.-Z., and Hao, X. (2022, June 30). AMSU-A Brightness Temperature FCDR\u2014Climate Algorithm Theoretical Basis Document. NOAA Climate Data Record Program CDRP-ATBD-0345, Rev. 2.0, Available online: http:\/\/www.ncdc.noaa.gov\/cdr\/operationalcdrs.html."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1002\/qj.3803","article-title":"The ERA5 global reanalysis","volume":"146","author":"Hersbach","year":"2020","journal-title":"Quart. J. R. Meteor. Soc."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1631","DOI":"10.1175\/BAMS-83-11-1631","article-title":"NCEP\u2013DOE AMIP-II reanalysis (R-2)","volume":"83","author":"Kanamitsu","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/B978-1-4832-1446-7.50035-2","article-title":"Learning internal representations by error propagation","volume":"323","author":"Rumelhart","year":"1988","journal-title":"Read. Cogn. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"5686","DOI":"10.1175\/JCLI3990.1","article-title":"Robust responses of the hydrological cycle to global warming","volume":"19","author":"Held","year":"2006","journal-title":"J. Clim."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4353\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:22:16Z","timestamp":1760142136000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4353"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,2]]},"references-count":46,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["rs14174353"],"URL":"https:\/\/doi.org\/10.3390\/rs14174353","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints202207.0077.v1","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,2]]}}}