{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:07:53Z","timestamp":1760234873687,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,19]],"date-time":"2021-06-19T00:00:00Z","timestamp":1624060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41971291"],"award-info":[{"award-number":["41971291"]}]},{"name":"National Key Research and Development Program of China","award":["No. 2016YFA0600101"],"award-info":[{"award-number":["No. 2016YFA0600101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A new satellite-based product containing daily sea surface net radiation (Rn) values at a spatial resolution of 0.25\u00b0 from 1988 to 2013, named the Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations, version 3 (J-OFURO3), was recently generated and released. In this letter, the performance of the J-OFURO3 sea-surface Rn product was fully evaluated by using observations from 55 global moored buoy sites. The overall accuracy was satisfactory, with root-mean-square difference (RMSD) of 24.05 and 10.76 Wm\u22122 at daily and monthly scales, respectively. However, an inconsistency issue was found in the long-term variations in the J-OFURO3 sea-surface Rn values in approximately 2000; this inconsistency may be due to the replacement of the input dataset. To address this issue, a simple but effective inconsistency correction method was developed and conducted in this study. The analysis results demonstrated that the variations in the corrected J-OFURO3 sea-surface Rn data were more reasonable and that its daily validation accuracy was significantly improved by decreasing the bias from 4.67 to 0.27 Wm\u22122 before the year 2000. Thereby, it is suggested that the inconsistency correction method should be applied before using the J-OFURO3 sea-surface Rn data. However, the data users still should be cautious about another discontinuity issues caused by the quality of the input dataset itself.<\/jats:p>","DOI":"10.3390\/rs13122403","type":"journal-article","created":{"date-parts":[[2021,6,20]],"date-time":"2021-06-20T21:50:15Z","timestamp":1624225815000},"page":"2403","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Evaluation of the J-OFURO3 Sea Surface Net Radiation and Inconsistency Correction"],"prefix":"10.3390","volume":"13","author":[{"given":"Hongkai","family":"Chen","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"China and Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5413-0247","authenticated-orcid":false,"given":"Bo","family":"Jiang","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"China and Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Xiuxia","family":"Li","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"China and Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Jianghai","family":"Peng","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"China and Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Hui","family":"Liang","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"China and Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Shaopeng","family":"Li","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China"},{"name":"China and Beijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,19]]},"reference":[{"key":"ref_1","unstructured":"Siegenthaler, U. 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