[{"data":1,"prerenderedAt":87},["ShallowReactive",2],{"page-\u002Flibrary":3,"data-library":46},{"id":4,"title":5,"body":6,"description":38,"extension":39,"meta":40,"navigation":41,"path":42,"seo":43,"stem":44,"__hash__":45},"content\u002Flibrary.md","Agricultural Open Data Library: Free Global Datasets",{"type":7,"value":8,"toc":35},"minimark",[9,28,31],[10,11,16],"hero-module",{":centered":12,":serif":12,"eyebrow":13,"headline":14,"data-editable-base":15},"true","Open data","Open agricultural data library","c:content\u002Flibrary.md#hero-module@0",[17,18,20],"template",{"v-slot:subhead":19},"",[21,22,23,24,27],"p",{},"Free, open global datasets on climate, soil and growing conditions.",[25,26],"br",{},"\nExplore them by country and region, or download the data.",[29,30],"common-divider",{},[32,33],"data-library-module",{"data-editable-base":34},"c:content\u002Flibrary.md#data-library-module@0",{"title":19,"searchDepth":36,"depth":36,"links":37},2,[],"Free global datasets on climate type, rainfall, humidity, wind, solar radiation, soil, frost risk, winter chill and growing degree days, by country and region.","md",{},true,"\u002Flibrary",{"title":5,"description":38},"library","TG0MpyJ13lWHc4ZHYr47drtTYpMGmne_VW3hIXSXroI",[47,52,57,61,65,70,74,78,82],{"slug":48,"title":49,"description":50,"coverage":51},"climate_type","Climate Type","The Köppen–Geiger climate classification divides climates into five main climate groups, with each group being divided based on patterns of seasonal precipitation and temperature. The five main groups are A (tropical), B (arid), C (temperate), D (continental), and E (polar). Each group and subgroup is represented by a letter. All climates are assigned a main group (the first letter). All climates except for those in the E group are assigned a seasonal precipitation subgroup (the second letter). For example, Af indicates a tropical rainforest climate. The system assigns a temperature subgroup for all groups other than those in the A group, indicated by the third letter for climates in B, C, D, and the second letter for climates in E. For example, Cfb indicates an oceanic climate with warm summers as indicated by the ending b. Climates are classified based on specific criteria unique to each climate type.\n\nThis particular form of the Köppen-Geiger Climate Classification is a new 1x1km resolution analysis from GloH20, based on high-resolution, observation-based climatologies. Whereas most maps of the Köppen-Geiger Climate Classification are low resolution, this 1x1 km resolution map provides a more accurate representation of the climate distributions across the globe.","Global",{"slug":53,"title":54,"description":55,"coverage":56},"frost_risk","Frost Risk","This datasource includes a map of the day of last frost event in both hemispheres. Days are counted from 0 in both cases, to make comparison easier between layers. Data were taken from 'ERA5 hourly data on single levels from 1940 to present', which has a 0.25 x 0.25 degree (~25km x 25km) resolution. Data were then resampled to a 10x10km resolution using a Nearest Neighbour resampling method in order to preserve accuracy of the original data, while increasing usability and granularity.\n\nThe day of last frost event in a year is defined as: The last day in the period starting at any point before the beginning of spring, ending just before the beginning of the next winter period, where a temperature of -2C was recorded at any point in the day.\n\nFor each hemisphere, nominal 'years' were defined as:\nNorthern Hemisphere: Jan-01 -> Jul-31\nSouthern Hemisphere: Jul-31 -> Jan-01 (next year)","Global · 2015–2024",{"slug":58,"title":59,"description":60,"coverage":56},"growing_degree_days","Growing Degree Days","This datasource includes a map of accumulated growing degree days over the entire year, globally. Growing degree days are calculated as the number of hours during a period of time where the temperature is above 10C and below 30C. Data were taken from 'ERA5 hourly data on single levels from 1940 to present', which has a 0.25 x 0.25 degree (~25km x 25km) resolution. Data were then resampled to a 10x10km resolution using a Bilinear resampling method to increase usability and granularity. \n\nGrowing degree days is calculated by taking the mean daily temperature, and subtracting a base temperature. This dataset uses a base temperature of 5C.",{"slug":62,"title":63,"description":64,"coverage":56},"humidity","Humidity","This datasource includes a map of global relative humidity at a 10km resolution (resampled from 25km) at daytime. Data were taken from 'ERA5 hourly data on single levels from 1940 to present'. Relative humidity can be approximated as the ratio of water vapor pressure to saturation water vapour pressure. We utilise the August-Roche-Magnus formula to calculate these vapour pressures using temperature and dewpoint temperature, where dewpoint temperature is the temperature at which saturation water vapour pressure is reached. For daytime hours, we take the hours from 6am to 6pm.",{"slug":66,"title":67,"description":68,"coverage":69},"precipitation","Precipitation","This datasource includes a map of annual total precipitation at a 0.25 x 0.25 degree (~28km x 28km) resolution at the equator, global, for 2024. Daily precipitation data were taken from 'Agrometeorological indicators from 1979 to present derived from reanalysis (AgEra5)' and summed over the year for each grid point to produce this map. Any areas with total annual rainfall above 10,000mm were truncated to 10,000mm.","Global · 2020–2024",{"slug":71,"title":72,"description":73,"coverage":51},"soil","Soil","A map of global soil composition using the USDA texture class system of topsoil predicted using the global compilation of soil ground observations. The map has a 250x250m resolution, and the soil data used were taken between 1950 - 2016.",{"slug":75,"title":76,"description":77,"coverage":69},"sunlight","Sunlight","This datasource includes a map of annual total Solar Radiation at a 0.1 x 0.1 degree (~9km x 9km) resolution, global. Daily Solar Radiation Flux data were taken from 'Agrometeorological indicators from 1979 to present derived from reanalysis (AgEra5)' and summed over the year for each grid point to produce these maps. Units are in kWh\u002Fm2, i.e. how many kilowatt-hours of energy the sun irradiates for every square meter of area.",{"slug":79,"title":80,"description":81,"coverage":69},"wind","Wind","This datasource includes a map of annual mean Wind Speed at a 0.1 x 0.1 degree (~9km x 9km) resolution, global. Daily Mean Wind Speed data were taken from 'Agrometeorological indicators from 1979 to present derived from reanalysis (AgEra5)' and summed over the year for each grid point to produce this map.",{"slug":83,"title":84,"description":85,"coverage":86},"winter_chill","Winter Chill","This datasource includes a map of the 90th percentile accumulated chill hours at a 0.25 x 0.25 degree (~25km x 25km) resolution, global, for each hemisphere's \"winter\" months, resampled to a resolution of 10km x 10km. This map was created by performing chill hours calculations on gridded hourly temperature data from 'ERA5 hourly data on single levels from 1940 to present'. A 'chill hour' was assumed to be an hour where the temperature was between 0°C and 7.2°C. Northern hemisphere winter months were assumed as: December, January, February inclusive. Southern hemisphere winter months were assumed as: June, July, August inclusive.","Global · 2015–2023",1793108547002]