{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T15:28:42Z","timestamp":1760369322990,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2016,6,18]],"date-time":"2016-06-18T00:00:00Z","timestamp":1466208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An important component of the AVHRR PATMOS-x climate date record (CDR)\u2014or any satellite cloud climatology\u2014is the performance of its cloud detection scheme and the subsequent quality of its cloud fraction CDR. PATMOS-x employs the NOAA Enterprise Cloud Mask for this, which is based on a na\u00efve Bayesian approach. The goal of this paper is to generate analysis of the PATMOS-x cloud fraction CDR to facilitate its use in climate studies. Performance of PATMOS-x cloud detection is compared to that of the well-established MYD35 and CALIPSO products from the EOS A-Train. Results show the AVHRR PATMOS-x CDR compares well against CALIPSO with most regions showing proportional correct values of 0.90 without any spatial filtering and 0.95 when a spatial filter is applied. Values are similar for the NASA MODIS MYD35 mask. A direct comparison of PATMOS-x and MYD35 from 2003 to 2014 also shows agreement over most regions in terms of mean cloud amount, inter-annual variability, and linear trends. Regional and seasonal differences are discussed. The analysis demonstrates that PATMOS-x cloud amount uncertainty could effectively screen regions where PATMOS-x differs from MYD35.<\/jats:p>","DOI":"10.3390\/rs8060511","type":"journal-article","created":{"date-parts":[[2016,6,20]],"date-time":"2016-06-20T12:51:28Z","timestamp":1466427088000},"page":"511","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Using the NASA EOS A-Train to Probe the Performance of the NOAA PATMOS-x Cloud Fraction CDR"],"prefix":"10.3390","volume":"8","author":[{"given":"Andrew","family":"Heidinger","sequence":"first","affiliation":[{"name":"NOAA NESDIS Center for Satellite Applications and Research, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Foster","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center (SSEC), University of Wisconsin, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Denis","family":"Botambekov","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center (SSEC), University of Wisconsin, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Hiley","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center (SSEC), University of Wisconsin, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andi","family":"Walther","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center (SSEC), University of Wisconsin, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Li","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center (SSEC), University of Wisconsin, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,6,18]]},"reference":[{"key":"ref_1","unstructured":"National Research Council (2004). 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