{"id":2946682,"date":"2025-11-04T09:00:19","date_gmt":"2025-11-04T17:00:19","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2946682"},"modified":"2025-11-14T08:38:23","modified_gmt":"2025-11-14T16:38:23","slug":"expanding-the-chelsa-bioclimate-projection-collection","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection","title":{"rendered":"Expanding the CHELSA Bioclimate Projection Collection"},"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":[23341,37101,430212],"tags":[572002,779892,779882,39271,410642],"industry":[],"product":[36581,36551],"class_list":["post-2946682","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-announcements","category-sustainable-development","tag-arcgis-living-atlas","tag-bioclimate","tag-chelsa","tag-climate-change","tag-environment","product-arcgis-living-atlas","product-arcgis-online"],"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":""},{"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":""}],"short_description":"Expanding the CHELSA Bioclimate Projection Collection","flexible_content":[{"acf_fc_layout":"image","image":{"ID":2946759,"id":2946759,"title":"chelsa_banner_card","filename":"chelsa_banner_card.png","filesize":2331219,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection\/chelsa_banner_card","alt":"This image shows the net primary productivity in the Amazon for 2011-2040 and SSP3-7.0.","author":"368302","description":"","caption":"Net primary productivity in the Amazon for 2011-2040 and SSP3-7.0.","name":"chelsa_banner_card","status":"inherit","uploaded_to":2946682,"date":"2025-11-03 18:58:13","modified":"2025-11-14 16:37:33","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":1920,"height":1080,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png","medium-width":464,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png","medium_large-width":768,"medium_large-height":432,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png","large-width":1920,"large-height":1080,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card-1536x864.png","1536x1536-width":1536,"1536x1536-height":864,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png","2048x2048-width":1920,"2048x2048-height":1080,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card-826x465.png","card_image-width":826,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png","wide_image-width":1920,"wide_image-height":1080}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_banner_card.png"},{"acf_fc_layout":"content","content":"

The CHELSA bioclimate projections<\/a><\/strong> in the Living Atlas have been incredibly popular with the GIS community, and now we have enhanced the collection to include <\/span><\/span>Growing Degree Days above 10<\/span> \u00b0C<\/span><\/strong><\/span><\/a>,\u202f<\/span><\/span>Net<\/span> Primary Productivity<\/span><\/strong><\/a><\/span>,\u202f<\/span><\/span>Snow Cover Days<\/span><\/strong><\/a><\/span>, and\u202f<\/span><\/span>Snow Water Equivalent<\/span><\/strong><\/a><\/span>. The new layers <\/span><\/span>provide<\/span> crucial<\/span> insights into <\/span>the<\/span> future<\/span> impact of <\/span>climate <\/span>change<\/span> on ecosystems<\/span> and <\/span>human wellbeing<\/span>.<\/span> The new layers include projections for <\/span>the early<\/span>, mid, and late 21<\/span><\/span>st<\/span><\/span> century under <\/span>several greenhouse gas scenarios (SSPs). <\/span>As we continue to expand <\/span>and refine <\/span>our data<\/span> collection<\/span>, we invite <\/span>everyon<\/span>e <\/span>to <\/span>lev<\/span>erage<\/span> this resource for their work in climate science and environmental management.<\/span><\/span><\/p>\n

What’s New in the CHELSA Collection?<\/strong><\/h3>\n

Growing Degree Days above 10<\/span> \u00b0C<\/span><\/strong><\/a><\/span>\u202f(GDD)<\/strong> is a measure of heat accumulation<\/span> and <\/span>can be<\/span> used to predict plant<\/span> and animal<\/span> development rates<\/span>.<\/span> The GDD<\/span> represents<\/span> the total number of degrees Celsius by which each day\u2019s mean temperature <\/span>is warmer than <\/span>10<\/span> \u00b0C<\/span>, <\/span>added up<\/span> over a year.<\/span> In other words, if it is 20 <\/span>\u00b0C<\/span> today, 10 <\/span>\u00b0C<\/span> will be <\/span>added to the total. If it is 5 <\/span>\u00b0C<\/span> tomorrow, 0 <\/span>\u00b0C<\/span> will be <\/span>added to the total.<\/span> A higher GDD <\/span>generally indicates<\/span> the potential for increased agricultural yields<\/span>. B<\/span>ut keep in mind that GDD is not the only factor <\/span>that<\/span> determines<\/span> this<\/span>.<\/span> Precipitation, s<\/span>unshine hours, soil quality,<\/span> and plant diseases are just some of the <\/span>variables that need to be taken into <\/span>account<\/span>.<\/span> In the image below, <\/span>the GDD <\/span>ove<\/span>r <\/span><\/span>the<\/span> Middle East<\/span><\/span> is shown<\/span>.<\/span> While the Fertile Crescent <\/span>in the northern part of the <\/span>Arabian Peninsula is not as fertile as it once was due to climate change and human activities, remnants of the <\/span>agricultural viability (in darker green) are still visible in eastern Iraq between Baghdad and Basra<\/span>.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2946687,"id":2946687,"title":"Growing Degree Days Above 10C","filename":"GrowingDegreeDays_crop.png","filesize":3691645,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection\/growingdegreedays_crop","alt":"This image shows the growing degree days above 10C in the Middle East for 2041-2070 and SSP3-7.0.","author":"368302","description":"","caption":"Growing degree days above 10C in the Middle East for 2041-2070 and SSP3-7.0.","name":"growingdegreedays_crop","status":"inherit","uploaded_to":2946682,"date":"2025-11-03 16:31:24","modified":"2025-11-03 16:42:39","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":2407,"height":1233,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop.png","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop.png","medium_large-width":768,"medium_large-height":393,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop.png","large-width":1920,"large-height":984,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop-1536x787.png","1536x1536-width":1536,"1536x1536-height":787,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop-2048x1049.png","2048x2048-width":2048,"2048x2048-height":1049,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop-826x423.png","card_image-width":826,"card_image-height":423,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop-1920x984.png","wide_image-width":1920,"wide_image-height":984}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/GrowingDegreeDays_crop.png"},{"acf_fc_layout":"content","content":"

Net Primary Productivity<\/a> (NPP)<\/span><\/span><\/strong>\u202f<\/span>is<\/span> the rate at which plants<\/span> and other autotrophs <\/span>(like algae and cyanobacteria) <\/span>store<\/span> carb<\/span>on<\/span> as biomass<\/span> as they photosynthesize<\/span>. The NPP is <\/span>measured in grams of carbon per square meter per year (g<\/span> C\/m\u00b2\/yr)<\/span>.<\/span> This metric<\/span> is crucial for assessing the health of ecosystems and their ability to support biodiversity<\/span> and agriculture<\/span>.<\/span> The image below shows NPP levels across <\/span>central Africa<\/span>, revealing areas of high productivity in green<\/span>, like the Congo Basin and the Choke Mountains in Ethiopia. These areas<\/span> are vital for sustaining both wildlife and human populations.<\/span> Understanding<\/span> the future<\/span> of<\/span> NPP<\/span> can inform conservation efforts and agricultural practices in these <\/span>biodiverse landscapes.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2946688,"id":2946688,"title":"Net Primary Productivity","filename":"NetPrimaryProductivity_crop.png","filesize":3305005,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection\/netprimaryproductivity_crop","alt":"This image shows the net primary productivity in Central Africa for 2041-2070 and SSP3-7.0.","author":"368302","description":"","caption":"Net primary productivity in Central Africa for 2041-2070 and SSP3-7.0.","name":"netprimaryproductivity_crop","status":"inherit","uploaded_to":2946682,"date":"2025-11-03 16:31:43","modified":"2025-11-03 16:42:41","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":2412,"height":1237,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop.png","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop.png","medium_large-width":768,"medium_large-height":394,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop.png","large-width":1920,"large-height":985,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop-1536x788.png","1536x1536-width":1536,"1536x1536-height":788,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop-2048x1050.png","2048x2048-width":2048,"2048x2048-height":1050,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop-826x424.png","card_image-width":826,"card_image-height":424,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop-1920x985.png","wide_image-width":1920,"wide_image-height":985}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/NetPrimaryProductivity_crop.png"},{"acf_fc_layout":"content","content":"

Snow Cover Days<\/span><\/strong><\/a><\/span>\u202f<\/span>represents<\/span> the number of days per year that snow <\/span>can be found<\/span> on the ground. This <\/span>metric<\/span> is essential for <\/span>analyzing<\/span> hydrological <\/span>processes<\/span> and <\/span>understanding how snow influences <\/span>ecosystem dynamics in <\/span>high-altitude and cold regions.<\/span> The image <\/span>below <\/span>shows<\/span> the<\/span> snow cover<\/span> pattern in<\/span> <\/span>the Himalayas and the Tibetan Plateau<\/span><\/span>,<\/span> highlighting<\/span> areas with significant snow accumulation.<\/span> Th<\/span>ese insights<\/span> provide <\/span>support<\/span> for <\/span>communities in <\/span>preparing for<\/span> future changes in snow accumulation<\/span> patterns<\/span> for<\/span> agriculture<\/span> and snow-related tourism.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2946689,"id":2946689,"title":"Snow Covered Days","filename":"SnowCoveredDays_crop.png","filesize":3934615,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection\/snowcovereddays_crop","alt":"This image shows the snow cover days for the Himalayas and the Tibetan Plateau for 2041-2070 and SSP3-7.0.","author":"368302","description":"","caption":"Snow cover days for the Himalayas and the Tibetan Plateau for 2041-2070 and SSP3-7.0.","name":"snowcovereddays_crop","status":"inherit","uploaded_to":2946682,"date":"2025-11-03 16:32:01","modified":"2025-11-03 16:42:41","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":2418,"height":1194,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop.png","medium-width":464,"medium-height":229,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop.png","medium_large-width":768,"medium_large-height":379,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop.png","large-width":1920,"large-height":948,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop-1536x758.png","1536x1536-width":1536,"1536x1536-height":758,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop-2048x1011.png","2048x2048-width":2048,"2048x2048-height":1011,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop-826x408.png","card_image-width":826,"card_image-height":408,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop-1920x948.png","wide_image-width":1920,"wide_image-height":948}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowCoveredDays_crop.png"},{"acf_fc_layout":"content","content":"

Snow Water Equivalent<\/a> (SWE)<\/span><\/strong><\/span>\u202fmeasures the amount of water contained in <\/span>the <\/span>snowpack<\/span>, if all the snow <\/span>is melted. SWE is <\/span>expressed in <\/span>kilograms per square meter per year (kg<\/span>\/m\u00b2\/yr<\/span>)<\/span> and<\/span> is crucial for understanding water availability in regions that experience seasonal snow.<\/span> I<\/span><\/span>n the<\/span>\u202f<\/span>E<\/span>uropean Alps<\/span>,<\/span> t<\/span>he<\/span><\/span> snowpack serves as a natural reservoir, releasing fresh meltwater that sustains millions of people downstream<\/span>.<\/span> The image provid<\/span>es<\/span> essential<\/span> insights for<\/span> effective water resource management and predicting water <\/span>supply for agriculture, hydropower, and urban use.<\/span><\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2946690,"id":2946690,"title":"Snow Water Equivalent","filename":"SnowWaterEquivalent_crop.png","filesize":4764798,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection\/snowwaterequivalent_crop","alt":"This image shows the snow water equivalent over the European Alps for 2041-2070 and SSP3-7.0.","author":"368302","description":"","caption":"Snow water equivalent over the European Alps for 2041-2070 and SSP3-7.0.","name":"snowwaterequivalent_crop","status":"inherit","uploaded_to":2946682,"date":"2025-11-03 16:32:20","modified":"2025-11-03 16:42:41","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":2413,"height":1239,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop.png","medium-width":464,"medium-height":238,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop.png","medium_large-width":768,"medium_large-height":394,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop.png","large-width":1920,"large-height":986,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop-1536x789.png","1536x1536-width":1536,"1536x1536-height":789,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop-2048x1052.png","2048x2048-width":2048,"2048x2048-height":1052,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop-826x424.png","card_image-width":826,"card_image-height":424,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop-1920x986.png","wide_image-width":1920,"wide_image-height":986}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/SnowWaterEquivalent_crop.png"},{"acf_fc_layout":"content","content":"

Analysis-Ready Layers for Planning\u00a0<\/strong><\/h3>\n

Load the new CHELSA bioclimate projections in ArcGIS Pro for all your projects on climate, ecology, and more. For example, quickly analyze future trends in Net Primary Productivity in India with only a few mouse clicks.<\/span><\/p>\n

First, we need a feature for India\u2019s borders. Import the World Countries Generalized<\/a>\u00a0Feature Layer and apply a Definition Query<\/a> with \u201cWhere Country Name is equal to India.\u201d<\/span><\/p>\n

Then, select your Net Primary Productivity layer in Contents and head over to the Multidimensional tab. Under Analysis, select Temporal Profile<\/a> and under Time Series select \u201cOne location with multiple variables.\u201d Define an area of interest by selecting India with Feature Selector and add your desired SSPs under Select Variables. Note: it may take several minutes for Pro to process your chart request. You have now calculated how the Net Primary Productivity in India may change throughout the rest of the century.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2946691,"id":2946691,"title":"Net Primary Productivity Projections for India","filename":"pro_chelsa_timeseries-scaled.png","filesize":1125658,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-scaled.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/announcements\/expanding-the-chelsa-bioclimate-projection-collection\/pro_chelsa_timeseries","alt":"This image shows the projections for net productivity for India under the greenhouse gas emissions scenarios SSP1-2.6, SSP3-7.0, and SSP5-8.5.","author":"368302","description":"","caption":"Net productivity projections for India for SSP1-2.6, SSP3-7.0, and SSP5-8.5.","name":"pro_chelsa_timeseries","status":"inherit","uploaded_to":2946682,"date":"2025-11-03 16:32:41","modified":"2025-11-03 16:42:41","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":2560,"height":1366,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-scaled.png","medium-width":464,"medium-height":248,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-scaled.png","medium_large-width":768,"medium_large-height":410,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-scaled.png","large-width":1920,"large-height":1025,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-1536x820.png","1536x1536-width":1536,"1536x1536-height":820,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-2048x1093.png","2048x2048-width":2048,"2048x2048-height":1093,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-826x441.png","card_image-width":826,"card_image-height":441,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-1920x1025.png","wide_image-width":1920,"wide_image-height":1025}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/pro_chelsa_timeseries-scaled.png"},{"acf_fc_layout":"content","content":"

Limitations and Known Issues<\/strong>\u00a0<\/span><\/h3>\n

To create these layers, we combined five climate models into a multi-model ensemble. This method may introduce artifacts in the resulting maps. For instance, in Snow Cover Days, faint lines may be visible in Eastern Europe and elsewhere indicating the edges of the snow-covered areas in each model. These artifacts could affect your analysis, so be mindful of these limitations when interpreting your results.<\/span><\/p>\n

More Information<\/strong><\/h3>\n

Join the Esri Community<\/a> of experts and get inspired by others or get answers to your questions.<\/p>\n"}],"related_articles":"","show_article_image":true,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/11\/chelsa_card.png","wide_image":false},"yoast_head":"\nExpanding the CHELSA Bioclimate Projection Collection<\/title>\n<meta name=\"description\" content=\"The CHELSA bioclimate projections in the Living Atlas have been incredibly popular with the GIS community, and now we have enhanced the collection to include Growing Degree Days above 10 \u00b0C,\u202fNet Primary Productivity,\u202fSnow Cover Days, and\u202fSnow Water Equivalent. The new layers provide crucial insights into the future impact of climate change on ecosystems and human wellbeing. The new layers include projections for the early, mid, and late 21st century under several greenhouse gas scenarios (SSPs). 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