{"id":2596152,"date":"2025-01-14T12:10:42","date_gmt":"2025-01-14T20:10:42","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2596152"},"modified":"2025-01-21T12:10:11","modified_gmt":"2025-01-21T20:10:11","slug":"color-schemes-for-the-global-wind-atlas","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas","title":{"rendered":"Color Schemes for the Global Wind Atlas"},"author":8492,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[22941],"tags":[26451,777872,774852,612611,777422],"industry":[],"product":[36581,36551,36561],"class_list":["post-2596152","blog","type-blog","status-publish","format-standard","hentry","category-mapping","tag-cartography","tag-color-scheme","tag-colors","tag-multidimensional","tag-wind","product-arcgis-living-atlas","product-arcgis-online","product-arcgis-pro"],"acf":{"short_description":"Mix colors to build a theme for the new multidimensional Global Wind Atlas that's now available in ArcGIS Living Atlas.","flexible_content":[{"acf_fc_layout":"content","content":"

The Global Wind Atlas is a series of maps that identify high-wind areas for wind power generation. There are three maps in the series (<\/span>Wind Speed<\/span><\/a>, <\/span>Wind Power Density<\/span><\/a>, and <\/span>Wind Capacity Factor<\/span><\/a>) and they are all available in <\/span>ArcGIS Living Atlas<\/span><\/a>. If you are interested to know more about the Global Wind Atlas layers and how they can be used to assess global wind potential to support green energy development, see the <\/span>Explore the Global Wind Atlas<\/span><\/a> StoryMap.<\/span>\u00a0<\/span><\/p>\n

Developing a set of informative color schemes\u00a0for dynamic layers\u00a0can be a cartographic challenge. This blog is about the methods we used for mixing colors along with some techniques to make it easy to repeat the process on your own series of maps. <\/span>\u00a0<\/span><\/p>\n

Here are the three layers with their final color schemes:<\/span>\u00a0<\/span><\/p>\n

Wind Speed 100 meters <\/span><\/span><\/a>around Chengdu and Chongquing, China.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2651142,"id":2651142,"title":"Blog_WindSpeed1-01","filename":"Blog_WindSpeed1-01.png","filesize":9469241,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/blog_windspeed1-01","alt":"Wind Speed\u00a0100 meters around Chengdu and Chongquing, China\u00a0","author":"8492","description":"","caption":"","name":"blog_windspeed1-01","status":"inherit","uploaded_to":2596152,"date":"2025-01-14 20:43:20","modified":"2025-01-14 20:45:17","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":10000,"height":5000,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01.png","medium-width":464,"medium-height":232,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01.png","medium_large-width":768,"medium_large-height":384,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01.png","large-width":1920,"large-height":960,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01-1536x768.png","1536x1536-width":1536,"1536x1536-height":768,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01-2048x1024.png","2048x2048-width":2048,"2048x2048-height":1024,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01-826x413.png","card_image-width":826,"card_image-height":413,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01-1920x960.png","wide_image-width":1920,"wide_image-height":960}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/Blog_WindSpeed1-01.png"},{"acf_fc_layout":"content","content":"

Wind P<\/span>ower Density 150 meters<\/span><\/span><\/a> in part of the\u00a0Appalachian Mountains\u00a0in southwest Virginia, USA.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2651192,"id":2651192,"title":"BlogPowerDensity2-01","filename":"BlogPowerDensity2-01.png","filesize":8194974,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/blogpowerdensity2-01","alt":"Wind Power Density 150 meters in part of the\u00a0Appalachian Mountains\u00a0in southwest Virginia, USA.","author":"8492","description":"","caption":"","name":"blogpowerdensity2-01","status":"inherit","uploaded_to":2596152,"date":"2025-01-14 20:53:49","modified":"2025-01-14 20:54:14","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":10000,"height":5000,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01.png","medium-width":464,"medium-height":232,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01.png","medium_large-width":768,"medium_large-height":384,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01.png","large-width":1920,"large-height":960,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01-1536x768.png","1536x1536-width":1536,"1536x1536-height":768,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01-2048x1024.png","2048x2048-width":2048,"2048x2048-height":1024,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01-826x413.png","card_image-width":826,"card_image-height":413,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01-1920x960.png","wide_image-width":1920,"wide_image-height":960}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/BlogPowerDensity2-01.png"},{"acf_fc_layout":"content","content":"

Wind Capacity Factor IEC1<\/span><\/span><\/a> in Europe around the Mediterranean Sea.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2651882,"id":2651882,"title":"CapFactorEurope-01","filename":"CapFactorEurope-01.png","filesize":5918376,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/capfactoreurope-01","alt":"Wind Capacity Factor IEC1 in Europe around the Mediterranean Sea.","author":"8492","description":"","caption":"","name":"capfactoreurope-01","status":"inherit","uploaded_to":2596152,"date":"2025-01-15 05:03:53","modified":"2025-01-15 05:04:50","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":10001,"height":5001,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01.png","medium-width":464,"medium-height":232,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01.png","medium_large-width":768,"medium_large-height":384,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01.png","large-width":1920,"large-height":960,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01-1536x768.png","1536x1536-width":1536,"1536x1536-height":768,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01-2048x1024.png","2048x2048-width":2048,"2048x2048-height":1024,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01-826x413.png","card_image-width":826,"card_image-height":413,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01-1920x960.png","wide_image-width":1920,"wide_image-height":960}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/CapFactorEurope-01.png"},{"acf_fc_layout":"content","content":"

Creating a Theme<\/span>\u00a0<\/span><\/h2>\n

Color selection unlocks the data\u2019s story and for scientific data it is necessary to display the full spectrum of information without bias. The colors chosen and where emphasis gets placed affects your viewers’ ability to interpret and make decisions about what is mapped.<\/span>\u00a0<\/span><\/p>\n

The wind layers are <\/span>image services<\/span><\/a> made from raster data, so we used an equal interval <\/span>continuous<\/span><\/a> color scheme to display minimum and maximum values. Equal intervals with definitive color stops allow viewers to understand things as a percentage of a whole, so there are color changes at 0, 25, 50, 75, and 100%. The goal was to look at the color scheme and quickly organize what the colors represent (for example, this color is twice as much as that one).<\/span>\u00a0<\/span><\/p>\n

To make them feel like a set, we chose colors where all three layers start with a variation of dark blue for the low values, the middle values for each layer have unique but similar color combinations, and the highest values all display in yellow.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2655052,"id":2655052,"title":"WindLegendExplained_wpp1b","filename":"WindLegendExplained_wpp1b-1.png","filesize":470037,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windlegendexplained_wpp1b-2","alt":"Graphic showing the three Wind Atlas color schemes and where the colors were placed.","author":"8492","description":"","caption":"The goal was an equal and seamless blend of colors.","name":"windlegendexplained_wpp1b-2","status":"inherit","uploaded_to":2596152,"date":"2025-01-21 19:50:07","modified":"2025-01-21 19:50:37","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":7022,"height":5605,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1.png","medium-width":327,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1.png","medium_large-width":768,"medium_large-height":613,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1.png","large-width":1353,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1-1536x1226.png","1536x1536-width":1536,"1536x1536-height":1226,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1-2048x1635.png","2048x2048-width":2048,"2048x2048-height":1635,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1-583x465.png","card_image-width":583,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1-1353x1080.png","wide_image-width":1353,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/WindLegendExplained_wpp1b-1.png"},{"acf_fc_layout":"content","content":"

However,<\/span> an added <\/span>challenge <\/span>is<\/span> t<\/span>hese<\/span> layers are <\/span>multidimensional image services<\/span>,<\/span> which<\/span> mean<\/span>s <\/span>the entire<\/span> r<\/span>ange <\/span>of the data need<\/span>s<\/span> to be <\/span>accounted<\/span> for<\/span>, <\/span>not just <\/span>what<\/span>\u2019<\/span>s<\/span> presented <\/span>in<\/span> one<\/span> selected <\/span>dimension<\/span>. <\/span>Here’s<\/span> an example <\/span>showing <\/span>Wind Power Density <\/span>around the Horn of Africa.<\/span> You can see <\/span>when you <\/span>chang<\/span>e<\/span> the <\/span>height<\/span>,<\/span> it <\/span>first <\/span>starts with dark blue <\/span>all over the map<\/span> but<\/span> then <\/span>the<\/span> orange and y<\/span>ellow<\/span> values <\/span>increase<\/span> and the map looks completely different.<\/span><\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2605532,"id":2605532,"title":"WindAtlas_15framecrop_wpp","filename":"WindAtlas_15framecrop_wpp.gif","filesize":9410721,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windatlas_15framecrop_wpp","alt":"Animated gif showing the multidimensions for Wind Power Density around the Horn of Africa.","author":"8492","description":"","caption":"Color schemes developed for multidimensional image services must accommodate dramatic changes across the landscape.","name":"windatlas_15framecrop_wpp","status":"inherit","uploaded_to":2596152,"date":"2024-11-30 02:36:06","modified":"2025-01-13 20:47:17","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1787,"height":859,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif","medium-width":464,"medium-height":223,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif","medium_large-width":768,"medium_large-height":369,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif","large-width":1787,"large-height":859,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp-1536x738.gif","1536x1536-width":1536,"1536x1536-height":738,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif","2048x2048-width":1787,"2048x2048-height":859,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp-826x397.gif","card_image-width":826,"card_image-height":397,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif","wide_image-width":1787,"wide_image-height":859}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/11\/WindAtlas_15framecrop_wpp.gif"},{"acf_fc_layout":"content","content":"

Selecting Colors<\/span>\u00a0<\/span><\/h2>\n

The schemes were developed in ArcGIS Pro using the HSV Color Mode. HSV is an additive color mode made up of hue (H), saturation (S), and value (V) or brightness. You can finesse colors with precision using HSV and this is the mode I develop colors in the most.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2639142,"id":2639142,"title":"WindYellows","filename":"WindYellows.png","filesize":718120,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windyellows","alt":"Graphic showing the HSV yellow color settings for all three themes.","author":"8492","description":"","caption":"To activate the Color Editor, open Symbology and click on the color scheme. Select the color you want and then open Color Properties. You might need to switch the Color Mode dropdown to change to HSV.","name":"windyellows","status":"inherit","uploaded_to":2596152,"date":"2024-12-23 05:28:48","modified":"2025-01-13 20:49:35","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":8724,"height":3032,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows.png","medium-width":464,"medium-height":161,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows.png","medium_large-width":768,"medium_large-height":267,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows.png","large-width":1920,"large-height":667,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows-1536x534.png","1536x1536-width":1536,"1536x1536-height":534,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows-2048x712.png","2048x2048-width":2048,"2048x2048-height":712,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows-826x287.png","card_image-width":826,"card_image-height":287,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows-1920x667.png","wide_image-width":1920,"wide_image-height":667}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindYellows.png"},{"acf_fc_layout":"content","content":"

When developing the color schemes, we were careful selecting the yellow color for maximum values so they didn\u2019t dominate the map. Perfect yellow has a hue of 60\u00b0 and can have a strong presence, so all three yellows are slightly moving towards orange in the 40-50\u00b0 range.<\/span><\/p>\n

Additionally, we kept the <\/span>s<\/span><\/i>aturation low between 19-38% for all the schemes so the yellows stayed closer to white but with just a hint of color. For value we wanted real illumination against the opposite dark blue, so the colors are fully bright at 98-100%. <\/span>\u00a0<\/span><\/p>\n

What was tricky was making sure the windy poles didn\u2019t get over emphasized. Both Greenland in the north and the southernmost tip of South America naturally have more wind but don\u2019t have a large network of transmission infrastructure. \u00a0In addition, fewer people live there and there is less demand for wind energy. We didn\u2019t want these locations to be overemphasized.<\/span>\u00a0<\/span><\/p>\n

We tested these areas over and over until we had the right colors for yellow, as described above, with our goal being you might see them at first, because they are the brightest, but they prompt you to explore the rest of the map instead of focusing your attention on one place.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2650082,"id":2650082,"title":"wind_poles_wp","filename":"wind_poles_wp.gif","filesize":2523671,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/wind_poles_wp","alt":"Animated gif showing a global view of all three layers.","author":"8492","description":"","caption":"There is naturally more wind at the poles and we wanted the maximum values shown in yellow to not be too bright and take over the map. ","name":"wind_poles_wp","status":"inherit","uploaded_to":2596152,"date":"2025-01-13 19:43:17","modified":"2025-01-13 20:51:58","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1837,"height":1134,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp.gif","medium-width":423,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp.gif","medium_large-width":768,"medium_large-height":474,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp.gif","large-width":1750,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp-1536x948.gif","1536x1536-width":1536,"1536x1536-height":948,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp.gif","2048x2048-width":1837,"2048x2048-height":1134,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp-753x465.gif","card_image-width":753,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp-1750x1080.gif","wide_image-width":1750,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/wind_poles_wp.gif"},{"acf_fc_layout":"content","content":"

What <\/span>makes these schemes <\/span>u<\/span>nique from <\/span>each other<\/span> a<\/span>r<\/span>e<\/span> the<\/span> colors <\/span>from<\/span> 50<\/span>–<\/span>75%<\/span>.<\/span> We wanted an element of <\/span>intensity,<\/span> so we went with <\/span>colors like <\/span>purple, re<\/span>d, <\/span>orange, and gold<\/span>. <\/span>We <\/span>optimized<\/span> these colors <\/span>so<\/span> the<\/span> multidimensions <\/span>within the data <\/span>c<\/span>ould<\/span>\u00a0<\/span>accentuate <\/span>a<\/span> variety <\/span>of <\/span>geographies.<\/span> \u00a0<\/span>Using <\/span>Wind <\/span>Capacity<\/span> Factor<\/span> IEC 1<\/span> as an example<\/span>,<\/span> here <\/span>in Brazil <\/span>you can see the <\/span>red and gold hues <\/span>really stand out from the blue<\/span> and <\/span>purple<\/span>.<\/span> At<\/span>\u00a0<\/span>25% and 50% all <\/span>of<\/span> the schemes have colors that <\/span>are <\/span>high in saturation and<\/span> are complimentary <\/span>on the color wheel <\/span>(<\/span>for example<\/span> here <\/span>it’s<\/span> not a <\/span>h<\/span>uge<\/span> leap<\/span> to go from periwinkle <\/span>to <\/span>a<\/span>n<\/span> orang<\/span>e<\/span>-re<\/span>d<\/span>)<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2639562,"id":2639562,"title":"CapFactorMedHigh4","filename":"CapFactorMedHigh4.png","filesize":7447571,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/capfactormedhigh4","alt":"Image showing part of Brazil and the color stops for Wind Capacity Factor.","author":"8492","description":"","caption":"We optimized these colors so the multidimensions within the data could accentuate a variety of geographies. Notice there\u2019s more saturation and value placed from 50-100%.","name":"capfactormedhigh4","status":"inherit","uploaded_to":2596152,"date":"2024-12-23 19:17:38","modified":"2025-01-13 20:52:41","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":16439,"height":8407,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4.png","medium-width":464,"medium-height":237,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4.png","medium_large-width":768,"medium_large-height":393,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4.png","large-width":1920,"large-height":982,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4-1536x786.png","1536x1536-width":1536,"1536x1536-height":786,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4-2048x1047.png","2048x2048-width":2048,"2048x2048-height":1047,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4-826x422.png","card_image-width":826,"card_image-height":422,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4-1920x982.png","wide_image-width":1920,"wide_image-height":982}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/CapFactorMedHigh4.png"},{"acf_fc_layout":"content","content":"

The last part of the color schemes <\/span>are the<\/span> dark <\/span>blue <\/span>values. <\/span>Dark maps do a good job of <\/span>being the backdrop for data that has a <\/span>diverse <\/span>geograph<\/span>y<\/span> and<\/span>\u00a0<\/span>a <\/span>massive <\/span>range<\/span>.<\/span> Unlike a light background which can dominate<\/span> by being bright<\/span>, <\/span>a<\/span> dark background <\/span>disappears and allows <\/span>even the <\/span>most minimum<\/span> values of wind dynamics to be seen.<\/span><\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2650222,"id":2650222,"title":"tehran2wp-01","filename":"tehran2wp-01.png","filesize":6902408,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/tehran2wp-01","alt":"Image near Tehran showing the color scheme for Wind Power Density","author":"8492","description":"","caption":"The dark minimum value colors show the shape of the desert terrain around Tehran using Wind Power Density 150 meters.","name":"tehran2wp-01","status":"inherit","uploaded_to":2596152,"date":"2025-01-13 21:10:59","modified":"2025-01-13 21:12:58","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":15005,"height":7431,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01.png","medium-width":464,"medium-height":230,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01.png","medium_large-width":768,"medium_large-height":380,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01.png","large-width":1920,"large-height":951,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01-1536x761.png","1536x1536-width":1536,"1536x1536-height":761,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01-2048x1014.png","2048x2048-width":2048,"2048x2048-height":1014,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01-826x409.png","card_image-width":826,"card_image-height":409,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01-1920x951.png","wide_image-width":1920,"wide_image-height":951}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/tehran2wp-01.png"},{"acf_fc_layout":"content","content":"

We did adjust the Maximum Values<\/span>\u00a0<\/span><\/h2>\n

One last note, the raw multidimensional image services come symbolized with the minimum and maximum value by default. Using Wind Speed as an example, that meant the range was 0-84.66 meters per second. Having it set that high meant we weren\u2019t able to see the full spectrum of information because the outliers were skewing the color scheme. You can change this in ArcGIS Pro and Online so we modified the maximum value to 12 meters per second which is considered the speed at which most turbines can produce their maximum power.\u00a0 Here along the border of Nepal and Tibet watch how to modify that in ArcGIS Online.<\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2640902,"id":2640902,"title":"EditMinMax_Wind_wp","filename":"EditMinMax_Wind_wp.gif","filesize":1441727,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/editminmax_wind_wp","alt":"Animated gif showing how to change the maximum values in ArcGIS Online for Wind Speed and how that changes the map.","author":"8492","description":"","caption":"You might need to change your maximum values so your color scheme can accommodate all the data. Here we change the maximum value of 84.66 to 12 meters per second for Wind Speed 200 meters.","name":"editminmax_wind_wp","status":"inherit","uploaded_to":2596152,"date":"2024-12-24 01:32:39","modified":"2025-01-13 20:54:09","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1537,"height":738,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","medium-width":464,"medium-height":223,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","medium_large-width":768,"medium_large-height":369,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","large-width":1537,"large-height":738,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","1536x1536-width":1536,"1536x1536-height":738,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","2048x2048-width":1537,"2048x2048-height":738,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp-826x397.gif","card_image-width":826,"card_image-height":397,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif","wide_image-width":1537,"wide_image-height":738}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/EditMinMax_Wind_wp.gif"},{"acf_fc_layout":"content","content":"

Interesting Geography<\/span>\u00a0<\/span><\/h2>\n

These layers are a valuable addition to the <\/span>Living Atlas<\/span><\/a>. They can be used globally for renewable energy planning, climate research, or environmental impact assessments.\u00a0 They also are fascinating to explore. There are so many unique wind patterns across the earth to discover.<\/span>\u00a0<\/span><\/p>\n

For example, we saw interesting wind arrangements around islands areas like here where the wind patterns cast shadows, much in the same way light does.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2640932,"id":2640932,"title":"WindAtlasIslands_wp2a","filename":"WindAtlasIslands_wp2a.png","filesize":7097120,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windatlasislands_wp2a","alt":"","author":"8492","description":"","caption":"","name":"windatlasislands_wp2a","status":"inherit","uploaded_to":2596152,"date":"2024-12-24 05:36:23","modified":"2024-12-24 05:36:23","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":5703,"height":3058,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a.png","medium-width":464,"medium-height":249,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a.png","medium_large-width":768,"medium_large-height":412,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a.png","large-width":1920,"large-height":1030,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a-1536x824.png","1536x1536-width":1536,"1536x1536-height":824,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a-2048x1098.png","2048x2048-width":2048,"2048x2048-height":1098,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a-826x443.png","card_image-width":826,"card_image-height":443,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a-1920x1030.png","wide_image-width":1920,"wide_image-height":1030}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasIslands_wp2a.png"},{"acf_fc_layout":"content","content":"

T<\/span>he <\/span>Sierra Crest <\/span>is the spine of California<\/span>.\u00a0 <\/span>It<\/span> runs <\/span>roughly north-to-south<\/span> and demarcates the western and eastern slopes of the Sierra Nevada. <\/span>Th<\/span>is example shows Wind Speed<\/span>s up to<\/span> 100 <\/span>meters<\/span>. The <\/span>hi<\/span>gh<\/span>est<\/span> granite peaks <\/span>are easily<\/span> d<\/span>iscerned<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2609132,"id":2609132,"title":"WindAtlasSierraCrest2","filename":"WindAtlasSierraCrest2.png","filesize":5182225,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windatlassierracrest2","alt":"","author":"8492","description":"","caption":"","name":"windatlassierracrest2","status":"inherit","uploaded_to":2596152,"date":"2024-12-03 18:18:23","modified":"2024-12-03 18:18:23","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":2421,"height":1241,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2.png","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2.png","medium_large-width":768,"medium_large-height":394,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2.png","large-width":1920,"large-height":984,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2-1536x787.png","1536x1536-width":1536,"1536x1536-height":787,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2-2048x1050.png","2048x2048-width":2048,"2048x2048-height":1050,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2-826x423.png","card_image-width":826,"card_image-height":423,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2-1920x984.png","wide_image-width":1920,"wide_image-height":984}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasSierraCrest2.png"},{"acf_fc_layout":"content","content":"

In Iceland <\/span>in the center and southern part of the country <\/span>you can see <\/span>k<\/span>atabatic <\/span>w<\/span>inds coming off <\/span>Sn\u00e6fellsj\u00f6kull<\/span>,<\/span> Langj\u00f6kull, <\/span>Hoffellsj\u00f6kull<\/span>, <\/span>Vatnajokull<\/span>, and <\/span>M\u00fdrdalsj\u00f6kull<\/span> glaciers<\/span> with the Wind Power Density <\/span>10 meters<\/span> layer<\/span>.<\/span><\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2607402,"id":2607402,"title":"WindAtlas_Iceland","filename":"WindAtlas_Iceland.png","filesize":2917084,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windatlas_iceland","alt":"","author":"8492","description":"","caption":"","name":"windatlas_iceland","status":"inherit","uploaded_to":2596152,"date":"2024-12-03 01:29:37","modified":"2024-12-03 01:29:37","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":2404,"height":1239,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland.png","medium-width":464,"medium-height":239,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland.png","medium_large-width":768,"medium_large-height":396,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland.png","large-width":1920,"large-height":990,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland-1536x792.png","1536x1536-width":1536,"1536x1536-height":792,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland-2048x1056.png","2048x2048-width":2048,"2048x2048-height":1056,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland-826x426.png","card_image-width":826,"card_image-height":426,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland-1920x990.png","wide_image-width":1920,"wide_image-height":990}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlas_Iceland.png"},{"acf_fc_layout":"content","content":"

In Central America there are two distinct wind<\/span> patterns<\/span> you can see on this map<\/span> of Wind <\/span>Capacity<\/span> Factor<\/span> IEC<\/span> 1<\/span>. In <\/span>Mexico<\/span> the <\/span>T<\/span>ehuan<\/span>o<\/span> W<\/span>ind<\/span> travels through the <\/span>Chivel<\/span>a<\/span> Pass <\/span>across the Isthmus of Tehuantepec.<\/span> In <\/span>Nicara<\/span>gua<\/span>,<\/span> the <\/span><\/span>P<\/span>apagayo Wind<\/span> travels from the Caribbean Sea through the low elevation<\/span> areas<\/span> of Lake Nicaragua.<\/span><\/span>\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2607172,"id":2607172,"title":"WindAtlasTehuanoPapagayo_crop","filename":"WindAtlasTehuanoPapagayo_crop.png","filesize":2511144,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\/windatlastehuanopapagayo_crop","alt":"","author":"8492","description":"","caption":"","name":"windatlastehuanopapagayo_crop","status":"inherit","uploaded_to":2596152,"date":"2024-12-02 23:40:33","modified":"2024-12-02 23:40:33","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":2071,"height":1255,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop.png","medium-width":431,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop.png","medium_large-width":768,"medium_large-height":465,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop.png","large-width":1782,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop-1536x931.png","1536x1536-width":1536,"1536x1536-height":931,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop-2048x1241.png","2048x2048-width":2048,"2048x2048-height":1241,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop-767x465.png","card_image-width":767,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop-1782x1080.png","wide_image-width":1782,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/12\/WindAtlasTehuanoPapagayo_crop.png"},{"acf_fc_layout":"content","content":"

Explore the Maps<\/span>\u00a0<\/span><\/h2>\n

There are so many discoveries to be made about the dynamic relationship between land and wind and how it can be used to generate clean energy.<\/span>\u00a0<\/span><\/p>\n

To go directly to the three layers visit the <\/span>ArcGIS Living Atlas<\/span><\/a>.\u00a0 Also check out the <\/span>Explore the Global Wind Atlas StoryMap<\/span><\/a>.<\/span>\u00a0<\/span><\/p>\n

If you would like the webmaps used in this blog along with a custom basemap they can be found here:<\/span>\u00a0<\/span><\/p>\n

Global Wind Atlas \u2013 Wind Speed<\/span><\/a>\u00a0<\/span><\/p>\n

Global Wind Atlas \u2013 Power Density<\/span><\/a>\u00a0<\/span><\/p>\n

Global Wind Atlas \u2013 Capacity Factor<\/span><\/a>\u00a0<\/span><\/p>\n

Please reach out with comments or questions.<\/span>\u00a0<\/span><\/p>\n"}],"authors":[{"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\/meriamaps\/","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":""}],"show_article_image":false,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/FinalCardWindPalette.png","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/01\/FinalBannerWindPalette.png","related_articles":[{"ID":2635302,"post_author":"8492","post_date":"2024-12-20 11:55:26","post_date_gmt":"2024-12-20 19:55:26","post_content":"","post_title":"Explore the Global Wind Atlas","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"global-wind-atlas","to_ping":"","pinged":"","post_modified":"2024-12-20 13:43:11","post_modified_gmt":"2024-12-20 21:43:11","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2635302","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":2615632,"post_author":"4941","post_date":"2024-12-30 04:25:32","post_date_gmt":"2024-12-30 12:25:32","post_content":"","post_title":"Making Negative Positive - How to create a cartographic mask to cover areas of NoData","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"making-negative-positive-how-to-create-a-cartographic-mask-to-cover-areas-of-nodata","to_ping":"","pinged":"","post_modified":"2024-12-20 14:04:48","post_modified_gmt":"2024-12-20 22:04:48","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2615632","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"}]},"yoast_head":"\nColor Schemes for the Global Wind Atlas<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Color Schemes for the Global Wind Atlas\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/mapping\/color-schemes-for-the-global-wind-atlas\" \/>\n<meta property=\"og:site_name\" content=\"ArcGIS Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/esrigis\/\" \/>\n<meta property=\"article:modified_time\" content=\"2025-01-21T20:10:11+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@ESRI\" 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