{"id":1814,"date":"2016-01-01T11:17:49","date_gmt":"2016-01-01T10:17:49","guid":{"rendered":"http:\/\/zoz.cbk.waw.pl\/en\/?p=1814"},"modified":"2018-05-15T11:14:56","modified_gmt":"2018-05-15T09:14:56","slug":"kotarba-z-regional-high-resolution-cloud-climatology-based-modis-cloud-detection-data-volume-36-issue-8-30-june-2016-pages-3105-3115-2016","status":"publish","type":"post","link":"https:\/\/zoz.cbk.waw.pl\/en\/kotarba-z-regional-high-resolution-cloud-climatology-based-modis-cloud-detection-data-volume-36-issue-8-30-june-2016-pages-3105-3115-2016\/","title":{"rendered":"Kotarba A.Z. (2016) Regional high-resolution cloud climatology based on MODIS cloud detection data, Volume 36, Issue 8 30 June 2016  Pages 3105\u20133115, doi: 10.1002\/joc.4539"},"content":{"rendered":"<section id=\"abstract\" class=\"article-section article-section--abstract\">\n<div class=\"article-section__content mainAbstract\">\n<p>Most satellite cloud climatologies come in the form of global, low-resolution datasets: so- called \u2018gridded\u2019 Level 3 products, resulting from the reprojection and spatio-temporal aggregation of swath (Level 2) data. Their coarse resolution means that global datasets are of limited usefulness in regional studies. In this paper we develop and evaluate a new, regional cloud climatology over Poland and its neighbouring countries (\u223c10% of the area covered by Europe), based on observations performed with the state-of-the-art cloud imager, the moderate resolution imaging spectroradiometer (MODIS). In contrast to the operational, global MODIS cloud climatology, which is delivered as a Level 3 product at a spatial resolution of 1\u00b0\u2009\u00d7\u20091\u00b0, this regional climatology maintains the MODIS nadir spatial resolution of 1\u2009km\/pixel. The resulting high-spatial-resolution climatology is compared with AVHRR and SEVIRI datasets, and surface-based (SYNOP) observations at the level of monthly and annual means. The results shows that the standard MODIS Level 2 cloud mask product MOD35\/MYD35 can be successfully used to develop a regional, high-resolution cloud climatology. MODIS provides reliable estimates of cloud amount at the national scale (annual mean: 64.0% or 70.8%, depending on the MODIS data interpretation scheme), and correctly reproduces the annual cloud amount cycle (correlation between monthly means with SEVIRI\/AVHRR &gt;0.98). A comparison with monthly mean surface observations reveals a bias ranging from \u22121.1% up to 5.9%, and a root mean square error of 4.2%\u2009\u2212\u20096.6%. MODIS data also correctly indicates the spatial distribution of clouds. However, local anomalies were detected that were identified as artifacts of the MODIS cloud detection algorithm. Those artifacts covered 9% of the study area, but had no impact on spatially-averaged metrics.<\/p>\n<\/div>\n<\/section>\n<p>Kotarba A.Z. (2016) Regional high-resolution cloud climatology based on MODIS cloud detection data, Volume 36, Issue 8 30 June 2016  Pages 3105\u20133115,<br \/>\nKotarba A.Z., Vertical profile of cloud amount over Poland: variability and uncertainty based on CloudSat-CALIPSO observations. International Journal of Climatology,<br \/>\n<a href=\"http:\/\/dx.doi.org\/10.1002\/joc.4539\" target=\"_blank\">doi:10.1002\/joc.4539<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Most satellite cloud climatologies come in the form of global, low-resolution datasets: so- called \u2018gridded\u2019 Level 3 products, resulting from the reprojection and spatio-temporal aggregation of swath (Level 2) data. Their coarse resolution means that global datasets are of limited usefulness in regional studies. In this paper we develop and evaluate a new, regional cloud [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":2110,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[111,113],"tags":[],"coauthors":[80],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/posts\/1814"}],"collection":[{"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/comments?post=1814"}],"version-history":[{"count":4,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/posts\/1814\/revisions"}],"predecessor-version":[{"id":2113,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/posts\/1814\/revisions\/2113"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/media\/2110"}],"wp:attachment":[{"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/media?parent=1814"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/categories?post=1814"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/tags?post=1814"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/zoz.cbk.waw.pl\/en\/wp-json\/wp\/v2\/coauthors?post=1814"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}