{"id":2962039,"date":"2026-04-06T07:55:26","date_gmt":"2026-04-06T14:55:26","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2962039"},"modified":"2026-04-06T13:11:08","modified_gmt":"2026-04-06T20:11:08","slug":"clouds","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/analytics\/clouds","title":{"rendered":"Explore Cloud Cover Across the U.S."},"author":368302,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,37101,22931],"tags":[28261,781048,781049,115262,33981],"industry":[],"product":[36581,36551,36561],"class_list":["post-2962039","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-announcements","category-imagery","tag-agriculture","tag-clouds","tag-human-health","tag-imagery","tag-united-states","product-arcgis-living-atlas","product-arcgis-online","product-arcgis-pro"],"acf":{"authors":[{"ID":368302,"user_firstname":"Rafael","user_lastname":"Antwerpen","nickname":"Raf Antwerpen","user_nicename":"rantwerpen","display_name":"Raf Antwerpen","user_email":"rantwerpen@esri.com","user_url":"","user_registered":"2025-02-05 01:24:14","user_description":"Raf Antwerpen is a Senior GIS Engineer on the Living Atlas of the World team at Esri. He specializes in climate, agriculture, remote sensing, and data science and provides crucial subject matter expertise to climate resilience and adaptation projects. Raf holds a PhD in Earth and Environmental Sciences from Columbia University and is the curator for environmental content in the Living Atlas of the World.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/06\/RafAntwerpen_blog_profile-213x200.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"},{"ID":8492,"user_firstname":"Emily","user_lastname":"Meriam","nickname":"Emily Meriam","user_nicename":"emeriam","display_name":"Emily Meriam","user_email":"EMeriam@esri.com","user_url":"https:\/\/www.instagram.com\/emilymeriam\/","user_registered":"2018-10-26 16:33:49","user_description":"Emily Meriam has a diverse GIS background that spans more than two decades. Her portfolio includes mapping elephants in Thailand, wildlife poachers in the Republic of Palau, land-use issues around Yosemite National Park, and active wildfire incidents for the State of California. Since 2018, Emily has been with Esri's ArcGIS Living Atlas of the World. In this role she serves as lead Cartographer and Senior GIS Engineer for the Environment Team where she styles and designs layers, maps, and applications for the global GIS community. Outside of her professional endeavors, Emily is a passionate geographer who enjoys exploring the world with her family.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/EM-465x465.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"short_description":"USA Cloud Cover Days is now available in the ArcGIS Living Atlas of the World, making it easier than ever to integrate cloud cover information.","flexible_content":[{"acf_fc_layout":"content","content":"<p>Whether you\u2019re planning a move and you care about sunshine, planning renewable energy infrastructure or predicting agricultural yields, the presence \u2013 or absence \u2013 of clouds plays a starring role. To help you bridge this data gap, <a href=\"https:\/\/esri4.maps.arcgis.com\/home\/item.html?id=5819cc743d5d4036ab96250a69fa7720\"><strong>USA Cloud Cover Days<\/strong><\/a> is now available in the <a href=\"https:\/\/livingatlas.arcgis.com\/en\/home\/\"><strong>ArcGIS Living Atlas of the World<\/strong><\/a>, making it easier than ever to integrate cloud cover information into your GIS workflows.<\/p>\n<p>This new imagery layer provides the average number of days per year with cloud cover for the contiguous United States (CONUS) and portions of Mexico and Canada. With a 500-meter cell size, this data offers the spatial detail necessary for regional analyses in diverse environments.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2962040,"id":2962040,"title":"CONUS_CloudsLegend","filename":"CONUS_CloudsLegend-scaled.png","filesize":3579941,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-scaled.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/analytics\/clouds\/conus_cloudslegend","alt":"Average number of days per year with cloud cover over the US.","author":"368302","description":"Average number of days per year with cloud cover over the US.","caption":"Average number of days per year with cloud cover over the US.","name":"conus_cloudslegend","status":"inherit","uploaded_to":2962039,"date":"2026-04-03 16:11:31","modified":"2026-04-03 16:17:25","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":2560,"height":1440,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-scaled.png","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-scaled.png","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-scaled.png","large-width":1920,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-1536x864.png","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-2048x1152.png","2048x2048-width":2048,"2048x2048-height":1152,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-826x465.png","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-1920x1080.png","wide_image-width":1920,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/CONUS_CloudsLegend-scaled.png"},{"acf_fc_layout":"content","content":"<p><strong>Behind the data<\/strong><\/p>\n<p>The dataset is derived from NASA\u2019s <strong><a href=\"https:\/\/modis.gsfc.nasa.gov\/\">Moderate Resolution Imaging Spectroradiometer<\/a><\/strong> (MODIS)\u00a0data, collected by the <a href=\"https:\/\/aqua.nasa.gov\/content\/about-aqua\"><strong>Aqua satellite<\/strong><\/a>. Aqua passes over the equator at around 1:30 PM local solar time in an ascending (south to north) orbit. For the CONUS region, this means images are captured about 10 to 20 minutes later, providing a consistent snapshot of afternoon cloud cover patterns.<\/p>\n<p>To ensure a reliable product, we extracted daily cloud flags from the <strong><a href=\"https:\/\/planetarycomputer.microsoft.com\/dataset\/modis-10A1-061\">Daily Snow Cover Product<\/a><\/strong> (MYD10A1) Collection 6.1 for the period 2020-2024. If you are interested in learning more about how clouds are identified by the MODIS team, we recommend checking out the <a href=\"https:\/\/cimss.ssec.wisc.edu\/modis\/CMUSERSGUIDE.PDF\"><strong>Cloud Mask User\u2019s Guide<\/strong><\/a>.<\/p>\n<p>Because satellite missions occasionally face technical outages, we didn\u2019t just calculate a simple average over the 2020-2024 period. Instead, we calculated the 5-year average by weighting each year based on the total number of valid observations, providing a more accurate long-term representation of cloud cover.<\/p>\n<p>We processed the data using the new computing capabilities within our ArcGIS software. It is now possible to access and process the petabytes worth of high-quality data available on the Microsoft Planetary Computer, all from within our ArcGIS environment. This means you don\u2019t have to download and process large volumes of data on your laptop anymore! Learn more about what you can do with <a href=\"https:\/\/doc.arcgis.com\/en\/microsoft-planetary-computer\/latest\/get-started\/configure-arcgis-for-microsoft-planetary-computer.htm\"><strong>ArcGIS and Microsoft Planetary Computer<\/strong><\/a>\u00a0here.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2962041,"id":2962041,"title":"Cascades","filename":"Cascades-scaled.png","filesize":5993474,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-scaled.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/analytics\/clouds\/cascades","alt":"Average number of days per year with cloud cover over the Pacific Northwest.","author":"368302","description":"Average number of days per year with cloud cover over the Pacific Northwest.","caption":"Average number of days per year with cloud cover over the Pacific Northwest.","name":"cascades","status":"inherit","uploaded_to":2962039,"date":"2026-04-03 16:12:31","modified":"2026-04-03 16:18:07","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":2560,"height":1440,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-scaled.png","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-scaled.png","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-scaled.png","large-width":1920,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-1536x864.png","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-2048x1152.png","2048x2048-width":2048,"2048x2048-height":1152,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-826x465.png","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-1920x1080.png","wide_image-width":1920,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Cascades-scaled.png"},{"acf_fc_layout":"content","content":"<p><strong>What can you do with this layer?<\/strong><\/p>\n<p>Cloud cover is more than just a weather forecast; it is a critical variable for a wide range of industries and scientific studies:<\/p>\n<ul>\n<li><strong>Site selection for solar power farms<\/strong>: identify regions with the highest number of cloud-free days to maximize solar power farm yield.<\/li>\n<li><strong>Agricultural planning<\/strong>: analyze cloud patterns to understand solar radiation availability for different crop types.<\/li>\n<li><strong>Urban heat island effects<\/strong>: study how consistent cloud cover (or the lack thereof) influences heat stress and temperature retention in urban areas.<\/li>\n<li><strong>Climate trends<\/strong>: use the data as a baseline of studying shifting climate patterns through the rest of the 21<sup>st<\/sup><\/li>\n<\/ul>\n"},{"acf_fc_layout":"image","image":{"ID":2962042,"id":2962042,"title":"DenverRockies","filename":"DenverRockies-scaled.png","filesize":6013600,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-scaled.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/analytics\/clouds\/denverrockies","alt":"Average number of days per year with cloud cover over Denver and the Rockies.","author":"368302","description":"Average number of days per year with cloud cover over Denver and the Rockies.","caption":"Average number of days per year with cloud cover over Denver and the Rockies.","name":"denverrockies","status":"inherit","uploaded_to":2962039,"date":"2026-04-03 16:13:25","modified":"2026-04-03 16:18:09","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":2560,"height":1440,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-scaled.png","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-scaled.png","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-scaled.png","large-width":1920,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-1536x864.png","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-2048x1152.png","2048x2048-width":2048,"2048x2048-height":1152,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-826x465.png","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-1920x1080.png","wide_image-width":1920,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/DenverRockies-scaled.png"},{"acf_fc_layout":"content","content":"<p><strong>Put the Science of Where to work<\/strong><\/p>\n<p>USA Cloud Cover Days is optimized for fast visualization and analysis in ArcGIS Online and Pro. You can easily determine the cloud cover for your area of interest by clicking on the map to reveal the pre-configured pop-up.<\/p>\n<p>For a more advanced workflow, we\u2019ll show how to use the <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/big-data-analytics\/find-similar-locations.htm\"><strong>Find Similar Locations<\/strong><\/a> tool to find counties with a similar cloudiness and precipitation feel to Denver County. First, find the layer in ArcGIS Pro by pasting the item ID (5819cc743d5d4036ab96250a69fa7720) in Catalog &gt; Portal &gt; Living Atlas and add it to your map.<\/p>\n<p>Then, add \u201c<a href=\"https:\/\/esri4.maps.arcgis.com\/home\/item.html?id=59ffddea52ac4875afa8605b1a9e7568\"><strong>CHELSA Bioclimate Projections \u2013 Annual Precipitation (Bio12)<\/strong><\/a>\u201d and \u201c<a href=\"https:\/\/esri.maps.arcgis.com\/home\/item.html?id=c643ea4555e248e39ad163fee6e3b4b4\"><strong>CHELSA Bioclimate Projections \u2013 Precipitation Seasonality (Bio15)<\/strong><\/a>\u201d to your map. These are our rainy conditions. Also add <a href=\"https:\/\/esri4.maps.arcgis.com\/home\/item.html?id=14c5450526a8430298b2fa74da12c2f4\"><strong>USA Census Counties<\/strong><\/a> to your map and use <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/3.4\/tool-reference\/data-management\/copy-features.htm\"><strong>Copy Features<\/strong><\/a> to get a copy on your local machine.<\/p>\n<p>Run <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/spatial-analyst\/zonal-statistics-as-table.htm\"><strong>Zonal Statistics as Table<\/strong><\/a> on your local copy of the USA counties three times, once for each cloud and rain layer. Set the Statistics Type to Mean. Make sure the CHELSA layers\u2019 multidimensional settings are set to Variable: SSP370 and StdTime: 2025-12-01T00:00:00, these settings most closely match the cloud cover data period. Leave \u201cProcess as Multidimensional\u201d unchecked, this ensures that zonal statistics are calculated for the current visible slice. The result will be three new tables, each containing a column with the mean values for cloud cover and precipitation for every county.<\/p>\n<p>Run <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/3.4\/tool-reference\/data-management\/join-field.htm\"><strong>Join Field<\/strong><\/a> three times to add the \u201cMEAN\u201d columns of each table back to the local version of the USA counties. Make sure to use the county name for the Input Fields for both the Input Table and the Join Table.<\/p>\n<p>We need two separate layers as input for the Find Similar Locations tool. So, create a copy of the USA Counties layer to which you\u2019ve just added the zonal statistics tables with Copy Features. Set a <a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/help\/mapping\/layer-properties\/definition-query.htm\"><strong>Definition Query<\/strong><\/a> on the copied layer with \u201cWhere NAME = \u2018Denver County\u2019\u201d. This is your Input Layer. Use the other copy of USA Counties with the zonal statistics as the Search Layer. The tool will search for locations similar to Denver County in this layer. Add all three zonal statistics columns to the Analysis Fields and search for Most Similar using Attribute Values. Run the tool.<\/p>\n<p>Congratulations! The output dataset now shows the counties most similar to Denver County in terms of cloudiness and precipitation. Change the Symbology to Graduated Colors and the Field to \u201csimindex\u201d to show the degree to which each county is similar to Denver County (see the image below).<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2962043,"id":2962043,"title":"find_similar_locations","filename":"find_similar_locations-scaled.jpg","filesize":545171,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-scaled.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/analytics\/clouds\/find_similar_locations","alt":"Results for Denver County from the Find Similar Locations tool.","author":"368302","description":"Results for Denver County from the Find Similar Locations tool.","caption":"Results for Denver County from the Find Similar Locations tool.","name":"find_similar_locations","status":"inherit","uploaded_to":2962039,"date":"2026-04-03 16:13:56","modified":"2026-04-03 16:18:09","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":2560,"height":1398,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-scaled.jpg","medium-width":464,"medium-height":253,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-scaled.jpg","medium_large-width":768,"medium_large-height":419,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-scaled.jpg","large-width":1920,"large-height":1049,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-1536x839.jpg","1536x1536-width":1536,"1536x1536-height":839,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-2048x1119.jpg","2048x2048-width":2048,"2048x2048-height":1119,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-826x451.jpg","card_image-width":826,"card_image-height":451,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-1920x1049.jpg","wide_image-width":1920,"wide_image-height":1049}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/find_similar_locations-scaled.jpg"},{"acf_fc_layout":"content","content":"<p>Explore <a href=\"https:\/\/esri4.maps.arcgis.com\/home\/item.html?id=5819cc743d5d4036ab96250a69fa7720\"><strong>USA Cloud Cover Days<\/strong><\/a> today and let us know how you&#8217;re using it to power your maps and apps!<\/p>\n"}],"related_articles":"","show_article_image":true,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/04\/Clouds_Card.png","wide_image":false},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Explore Cloud Cover Across the U.S.<\/title>\n<meta name=\"description\" content=\"Whether you\u2019re planning a move and you care about sunshine, planning renewable energy infrastructure or predicting agricultural yields, the presence \u2013 or absence \u2013 of clouds plays a starring role. 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