2b:null 2c:["$","title",null,{"children":"Köppen-Geiger Climate Classification | Jesse Johnson's Workspace | Observable"}] 31:T408,## Hypothesis Changes in temperature and precipitation predicted to occur by 2100 will alter climate zones, or areas having broadly similar vegetation, in a way that lowers human energetic requirements. ### Rationale Some portion of human energy consumption is devoted to maintaining thermal *homeostasis*. More energy is consumed when the temperature of the environment is significantly differnt from human body temerature. ### Axioms * The per capita energy consumption in a country is normally distributed. * Koppen-Geiger climate zone classification is a fair representation of different ecoregions or bioregions on the planet. * The population weighted average of national per capita energy consumption is a reasonable approximation of a climate zone's per capita energy consumption. * [Primary energy consumption](https://en.wikipedia.org/wiki/Primary_energy) is a better metric to study than electricity consumption. * While large changes in population will occur by 2100, the relative distrubution will remain the same. 32:T4b7,climates = new Map([ [1, "Tropical, rainforest"], [2, "Tropical, monsoon"], [3, "Tropical, savannah"], [4, "Arid, desert, hot"], [5, "Arid, desert, cold"], [6, "Arid, steppe, hot"], [7, "Arid, steppe, cold"], [8, "Temperate, dry summer, hot summer"], [9, "Temperate, dry summer, warm summer"], [10, "Temperate, dry summer, cold summer"], [11, "Temperate, dry winter, hot summer"], [12, "Temperate, dry winter, warm summer"], [13, "Temperate, dry winter, cold summer"], [14, "Temperate, no dry season, hot summer"], [15, "Temperate, no dry season, warm summer"], [16, "Temperate, no dry season, cold summer"], [17, "Cold, dry summer, hot summer"], [18, "Cold, dry summer, warm summer"], [19, "Cold, dry summer, cold summer"], [20, "Cold, dry summer, very cold winter"], [21, "Cold, dry winter, hot summer"], [22, "Cold, dry winter, warm summer"], [23, "Cold, dry winter, cold summer"], [24, "Cold, dry winter, very cold winter"], [25, "Cold, no dry season, hot summer"], [26, "Cold, no dry season, warm summer"], [27, "Cold, no dry season, cold summer"], [28, "Cold, no dry season, very cold winter"], [29, "Polar, tundra"], [30, "Polar, frost"] 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types in 1884. Modifications were made in 1954 and 1961 by Rudolf Geiger. The system defines five major climates as *tropical, arid, temperate, continental, and polar*. Further subdivisions are based on seasonal variability. The system was designed to identify vegetation growing within each class.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":492,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":775,"value":"## Population density of the Earth\nPlot this first a reference and a demonstration of plotting rasters.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":501,"value":"viewof KoppenRes = Inputs.radio(\n new Map([\n [\"low\", koppen_raster_lowres],\n [\"high\", koppen_raster]\n ]),\n { label: \"Map Resolution\", value: koppen_raster_lowres }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":809,"value":"plotPopulation = Plot.plot({\n projection: \"equal-earth\",\n width: 1000,\n color: {\n type: \"log\",\n scheme: \"Cividis\",\n domain: [10, 1e7],\n legend: true,\n label: \"Population Density in 2020 (people per 1/12 degree squared)\"\n },\n\n marks: [\n Plot.raster(PopRes[0], {\n width: PopRes.width,\n height: PopRes.height,\n x1: bb[0],\n y1: bb[3],\n x2: bb[2],\n y2: bb[1],\n interpolate: \"nearest\",\n clip: \"sphere\"\n }),\n Plot.geo(countrymesh, {\n fill: \"none\",\n stroke: \"white\",\n strokeWidth: 0.4\n }),\n Plot.geo(d3.geoGraticule().step([30, 15])(), {\n stroke: \"gray\",\n strokeOpacity: 0.3\n })\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":672,"value":"\n \n \n \n

\n ${KoppenPlot}\n

\n ${legend}\n

\n \n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":768,"value":"## Analysis of population and energy use per climate zone\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":394,"value":"\n \n \n \n

\n ${popChart}\n

\n ${energyChart}\n

\n \n","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":516,"value":"legend = Plot.plot({\n title: \"Legend\",\n marginLeft: 60,\n width: 255,\n color: { range: colors_marked.values(), legend: false },\n x: { grid: false, label: \"\", ticks: \"\" },\n y: {\n grid: false,\n label: \"\",\n tickPadding: -10,\n tickSize: 0\n },\n marks: [\n Plot.barX(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(1),\n fill: \"Climate Zone\"\n }),\n Plot.text(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(0),\n text: (d) => climate_detail.get(d[\"Climate Zone\"]),\n textAnchor: \"start\",\n dx: 10,\n fill: \"black\",\n stroke: \"white\",\n fontSize: 12\n }),\n Plot.text(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(0),\n text: (d) => text_crude.get(d[\"Climate Zone\"]),\n textAnchor: \"end\",\n dx: -8,\n fontWeight: \"bold\"\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":20,"value":"KoppenPlot = Plot.plot({\n title: \"Köppen-Geiger Climate Zones\",\n projection: \"equal-earth\",\n width: 1200,\n caption: \"\",\n color: {\n type: \"categorical\",\n range: colors.values(),\n legend: false,\n label: \"Köppen Climate Classification\"\n },\n\n marks: [\n Plot.raster(KoppenRes[0], {\n width: KoppenRes.width,\n height: KoppenRes.height,\n x1: bb[0],\n y1: bb[3],\n x2: bb[2],\n y2: bb[1],\n clip: \"sphere\",\n interpolate: \"nearest\"\n }),\n Plot.geo(countrymesh, {\n fill: \"none\",\n stroke: \"white\",\n strokeWidth: 0.6\n }),\n Plot.geo(d3.geoGraticule().step([30, 15])(), {\n stroke: \"gray\",\n strokeOpacity: 0.3\n }),\n Plot.geo(d3.geoGraticule().step([-1, 90])(), {\n stroke: \"gold\",\n strokeWidth: 3.0,\n strokeOpacity: 0.5\n }),\n Plot.geo(d3.geoGraticule().step([-1, 90])(), {\n stroke: \"red\",\n strokeWidth: 1.0\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":773,"value":"## Analysis of land area fraction per climate zone","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":740,"value":"landAreaChart = Plot.plot({\n marginLeft: 60,\n marginRight: -10,\n width: 400,\n color: { range: colors_marked.values(), legend: false },\n x: { grid: true, domain: [0, 5], label: \"Percentage of total land area\" },\n y: { axis: null },\n marks: [\n Plot.barX(zonepopfrac, {\n y: \"Climate Zone\",\n x: \"Fraction of Land\",\n fill: \"Climate Zone\"\n }),\n ,\n Plot.text(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(0),\n text: (d) => climate_detail.get(d[\"Climate Zone\"]),\n textAnchor: \"start\",\n dx: 10,\n fill: \"black\",\n stroke: \"white\"\n }),\n Plot.text(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(0),\n text: (d) => text_crude.get(d[\"Climate Zone\"]),\n textAnchor: \"end\",\n dx: -8,\n fontWeight: \"bold\"\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":300,"value":"popChart = Plot.plot({\n marginLeft: 100,\n marginRight: -10,\n width: 400,\n color: { range: colors_marked.values(), legend: false },\n x: { grid: true, label: \"Population (millions)\" },\n y: { axis: null },\n marks: [\n Plot.barX(zonepopfrac, {\n y: \"Climate Zone\",\n x: \"Population\",\n fill: \"Climate Zone\"\n }),\n ,\n Plot.text(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(0),\n text: (d) => climate_detail.get(d[\"Climate Zone\"]),\n textAnchor: \"start\",\n dx: 10,\n fill: \"black\",\n stroke: \"white\"\n }),\n Plot.text(zoneenergy, {\n y: \"Climate Zone\",\n x: new Array(30).fill(0),\n text: (d) => text_crude.get(d[\"Climate Zone\"]),\n textAnchor: \"end\",\n dx: -8,\n fontWeight: \"bold\"\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":390,"value":"energyChart = Plot.plot({\n //title: \"\",\n marginLeft: 0,\n width: 400,\n color: { range: colors_marked.values(), legend: false },\n x: { grid: true, label: \"per Capita Energy Use (kWh)\" },\n y: { grid: false, axis: null },\n marks: [\n Plot.barX(zoneenergy, {\n y: \"Climate Zone\",\n x: \"Energy Use (per capita kWh)\",\n fill: \"Climate Zone\"\n }),\n Plot.ruleX([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":555,"value":"viewof PopRes = Inputs.radio(\n new Map([\n [\"low\", populationDensity_raster_lowres],\n [\"high\", populationDensity_raster]\n ]),\n { label: \"Map Resolution\", value: populationDensity_raster_lowres }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":264,"value":"Plot.plot({\n width: 800,\n height: 800,\n grid: true,\n title: \"Primary Energy Consumption vs. GNP per capita\",\n color: { legend: true },\n x: { type: \"log\" },\n y: { type: \"log\" },\n marks: [\n Plot.dot(energygnp, {\n x: \"GNP per capita\",\n y: \"Consumption 2021 (kWh)\",\n channels: {\n Country: { value: \"Country\", label: \"\" }\n },\n tip: {\n format: {\n Country: (d) => `${d}`,\n x: (d) => `\\$${d.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g, \",\")}`,\n y: (d) => `${d.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g, \",\")}`\n }\n }\n }),\n Plot.linearRegressionY(energygnp, {\n x: \"GNP per capita\",\n y: \"Consumption 2021 (kWh)\"\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":805,"value":"## Overview of Raster Reading\nThe following three code blocks break down how to import a geotiff raster data type into the observable environment.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"// The first step to download a raster is to import a supporting library, in this case it is geotiff\nGeoTIFF = require(\"geotiff@2.0.7\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"// Now the file can be brought in with the following command\n// Observe that this doesn't actually do much, it just sets up the file to be read.\nkoppen= FileAttachment(\"Beck_KG_V1_present_0p083.tif\").arrayBuffer()\n .then((buffer) => GeoTIFF.fromArrayBuffer(buffer))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":803,"value":"// The final step or the raster reading process is to bring in the raster by 'reading' it. Strange, I know, but this \n// forces Javascript to do what it has been delaying for performance reasons.\n// Not that the raster will now be refered to as koppen_raster[0], meaning the data is in the first element of a list.\nkoppen_raster = koppen.readRasters()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":822,"value":"// For plotting purposes it is helpful to know the bounding box for the data\nbb = koppen.getImage().then((d) => d.getBoundingBox())","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":828,"value":"// For plotting purposes it is helpful to know the bounding box for the data\nres = koppen.getImage().then((d) => d.getResolution())","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":75,"value":"koppen_lowres = FileAttachment(\"Beck_KG_V1_present_0p5.tif\")\n .arrayBuffer()\n .then((buffer) => GeoTIFF.fromArrayBuffer(buffer))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":63,"value":"koppen_raster_lowres = koppen_lowres.readRasters()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":706,"value":"populationDensity = FileAttachment(\n \"gpw_v4_population_density_rev11_2020_15_min.tif\"\n)\n .arrayBuffer()\n .then((buffer) => GeoTIFF.fromArrayBuffer(buffer))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":709,"value":"populationDensity_raster = populationDensity.readRasters()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":222,"value":"populationDensity_lr = FileAttachment(\n \"gpw_v4_population_count_adjusted_to_2015_unwpp_country_totals_rev11_2020_30_min@1.tif\"\n)\n .arrayBuffer()\n .then((buffer) => GeoTIFF.fromArrayBuffer(buffer))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":228,"value":"populationDensity_raster_lowres = populationDensity_lr.readRasters()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":35,"value":"colors = new Map([\n [0, \"#f0f8ff\"],\n [1, \"#0000ff\"],\n [2, \"#0078ff\"],\n [3, \"#46aafa\"],\n [4, \"#ff0000\"],\n [5, \"#ff9696\"],\n [6, \"#f5a500\"],\n [7, \"#ffdc64\"],\n [8, \"#ffff00\"],\n [9, \"#c8c800\"],\n [10, \"#969600\"],\n [11, \"#96ff96\"],\n [12, \"#64c864\"],\n [13, \"#329632\"],\n [14, \"#c8ff50\"],\n [15, \"#64ff50\"],\n [16, \"#32c800\"],\n [17, \"#ff00ff\"],\n [18, \"#c800c8\"],\n [19, \"#963296\"],\n [20, \"#966496\"],\n [21, \"#aaafff\"],\n [22, \"#5a78dc\"],\n [23, \"#4b50b4\"],\n [24, \"#320087\"],\n [25, \"#00ffff\"],\n [26, \"#37c8ff\"],\n [27, \"#007d7d\"],\n [28, \"#00465f\"],\n [29, \"#b2b2b2\"],\n [30, \"#666666\"]\n])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"altcolors = new Map([\n [0, \"#f0f8ff\"],\n [1, \"#18476d\"],\n [2, \"#3f6f9e\"],\n [3, \"#659ad2\"],\n [4, \"#c30000\"],\n [5, \"#cb543b\"],\n [6, \"#cc8371\"],\n [7, \"#ffd5c2\"],\n [8, \"#e3e436\"],\n [9, \"#d3d250\"],\n [10, \"#c3c063\"],\n [11, \"#b2ae72\"],\n [12, \"#3a7e19\"],\n [13, \"#609a42\"],\n [14, \"#85b769\"],\n [15, \"#aad590\"],\n [17, \"#cff3b8\"],\n [18, \"#520052\"],\n [19, \"#320032\"],\n [20, \"#323232\"],\n [21, \"#3e3e7f\"],\n [22, \"#2a327f\"],\n [23, \"#1e207f\"],\n [24, \"#00197f\"],\n [25, \"#007f7f\"],\n [26, \"#297f7f\"],\n [27, \"#003b3b\"],\n [28, \"#001e1e\"],\n [29, \"#535353\"],\n [30, \"#2b2b2b\"]\n])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":604,"value":"altcolors_marked = new Map([\n [1, \"#18476d\"],\n [2, \"#3f6f9e\"],\n [3, \"#659ad2\"],\n [4, \"#c30000\"],\n [5, \"#cb543b\"],\n [6, \"#cc8371\"],\n [7, \"#ffd5c2\"],\n [8, \"#e3e436\"],\n [9, \"#d3d250\"],\n [10, \"#c3c063\"],\n [11, \"#b2ae72\"],\n [12, \"#3a7e19\"],\n [13, \"#609a42\"],\n [14, \"#85b769\"],\n [15, \"#aad590\"],\n [17, \"#cff3b8\"],\n [18, \"#520052\"],\n [19, \"#320032\"],\n [20, \"#323232\"],\n [21, \"#3e3e7f\"],\n [22, \"#2a327f\"],\n [23, \"#1e207f\"],\n [24, \"#00197f\"],\n [25, \"#007f7f\"],\n [26, \"#297f7f\"],\n [27, \"#003b3b\"],\n [28, \"#001e1e\"],\n [29, \"#535353\"],\n [30, \"#2b2b2b\"]\n])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":378,"value":"colors_marked = new Map([\n [1, \"#0000ff\"],\n [2, \"#0078ff\"],\n [3, \"#46aafa\"],\n [4, \"#ff0000\"],\n [5, \"#ff9696\"],\n [6, \"#f5a500\"],\n [7, \"#ffdc64\"],\n [8, \"#ffff00\"],\n [9, \"#c8c800\"],\n [10, \"#969600\"],\n [11, \"#96ff96\"],\n [12, \"#64c864\"],\n [13, \"#329632\"],\n [14, \"#c8ff50\"],\n [15, \"#64ff50\"],\n [16, \"#32c800\"],\n [17, \"#ff00ff\"],\n [18, \"#c800c8\"],\n [19, \"#963296\"],\n [20, \"#966496\"],\n [21, \"#aaafff\"],\n [22, \"#5a78dc\"],\n [23, \"#4b50b4\"],\n [24, \"#320087\"],\n [25, \"#00ffff\"],\n [26, \"#37c8ff\"],\n [27, \"#007d7d\"],\n [28, \"#00465f\"],\n [29, \"#b2b2b2\"],\n [30, \"#666666\"]\n])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":52,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":607,"value":"climates_crude = new Map([\n [1, \"Tropical\"],\n [2, \"Tropical\"],\n [3, \"Tropical\"],\n [4, \"Arid\"],\n [5, \"Arid\"],\n [6, \"Arid\"],\n [7, \"Arid\"],\n [8, \"Temperate\"],\n [9, \"Temperate\"],\n [10, \"Temperate\"],\n [11, \"Temperate\"],\n [12, \"Temperate\"],\n [13, \"Temperate\"],\n [14, \"Temperate\"],\n [15, \"Temperate\"],\n [16, \"Temperate\"],\n [17, \"Cold\"],\n [18, \"Cold\"],\n [19, \"Cold\"],\n [20, \"Cold\"],\n [21, \"Cold\"],\n [22, \"Cold\"],\n [23, \"Cold\"],\n [24, \"Cold\"],\n [25, \"Cold\"],\n [26, \"Cold\"],\n [27, \"Cold\"],\n [28, \"Cold\"],\n [29, \"Polar\"],\n [30, \"Polar\"]\n])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":621,"value":"text_crude = new Map([\n [1, \"Tropical\"],\n [2, \"\"],\n [3, \"\"],\n [4, \"Arid\"],\n [5, \"\"],\n [6, \"\"],\n [7, \"\"],\n [8, \"Temperate\"],\n [9, \"\"],\n [10, \"\"],\n [11, \"\"],\n [12, \"\"],\n [13, \"\"],\n [14, \"\"],\n [15, \"\"],\n [16, \"\"],\n [17, \"Cold\"],\n [18, \"\"],\n [19, \"\"],\n [20, \"\"],\n [21, \"\"],\n [22, \"\"],\n [23, \"\"],\n [24, \"\"],\n [25, \"\"],\n [26, \"\"],\n [27, \"\"],\n [28, \"\"],\n [29, \"Polar\"],\n [30, \"\"]\n])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":624,"value":"climate_detail = new Map([\n [1, \"rainforest\"],\n [2, \"monsoon\"],\n [3, \"savannah\"],\n [4, \"desert, hot\"],\n [5, \"desert, cold\"],\n [6, \"steppe, hot\"],\n [7, \"steppe, cold\"],\n [8, \"dry summer, hot summer\"],\n [9, \"dry summer, warm summer\"],\n [10, \"dry summer, cold summer\"],\n [11, \"dry winter, hot summer\"],\n [12, \"dry winter, warm summer\"],\n [13, \"dry winter, cold summer\"],\n [14, \"no dry season, hot summer\"],\n [15, \"no dry season, warm summer\"],\n [16, \"no dry season, cold summer\"],\n [17, \"dry summer, hot summer\"],\n [18, \"dry summer, warm summer\"],\n [19, \"dry summer, cold summer\"],\n [20, \"dry summer, very cold winter\"],\n [21, \"dry winter, hot summer\"],\n [22, \"dry winter, warm summer\"],\n [23, \"dry winter, cold summer\"],\n [24, \"dry winter, very cold winter\"],\n [25, \"no dry season, hot summer\"],\n [26, \"no dry season, warm summer\"],\n [27, \"no dry season, cold summer\"],\n [28, \"no dry season, very cold winter\"],\n [29, \"tundra\"],\n [30, \"frost\"]\n])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":651,"value":"legend_text_colors = new Array(30).fill(\"white\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":655,"value":"(legend_text_colors[7] = \"black\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":668,"value":"legend_text_colors","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":91,"value":"world = FileAttachment(\"countries_50m.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":93,"value":"countries = topojson.feature(world, world.objects.countries).features","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":97,"value":"countrymesh = topojson.mesh(world, world.objects.countries, (a, b) => a !== b)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":268,"value":"energygnp = await FileAttachment(\"EnergyGNP@1.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"energygnp","database":"$undefined"},{"id":299,"value":"zonepopfrac = await FileAttachment(\"zonePopFrac.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"zonepopfrac","database":"$undefined"},{"id":450,"value":"zoneenergy = await FileAttachment(\"zoneEnergy.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"zoneenergy","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 30:"$2f:body"