32:T574,viewof plot4 = Plot.plot({ style: { color: "black", fontSize: 14 }, height: 600, width: width, projection: proj2, marks: [ Plot.sphere({fill:"#8aa6cb", opacity:0.75}), Plot.geo(countries, {fill:"#c7c8ca", opacity: 0.75}), Plot.geo(asiaMap, {fill: "#c7c8ca", stroke: "black", strokeWidth: 0.5}), Plot.dot(asiaCities, {x: "lng", y: "lat", fill: (d) => vari(radioSelect, d), stroke:"black", strokeWidth:0.5, r:8, opacity:0.85, channels: { city: { value: "city", label: "City" }, population: { value: "population", label: "Population" }, "mean temperature anomaly (¬∞C) during 3-month period": { value: "mean temperature anomaly (¬∞C) during 3-month period", label: "Anomaly" }, CSI2 : { value: "days_at_or_above_CSI2", label: "Days of CSI 2+" }, RiskyAdded : { value: "days above 90th percentile added by climate change", label: "Risky days added" } }, tip: { format: { city: true, population: true, x: false, y: false, "mean temperature anomaly (¬∞C) during 3-month period": (d)=> +d > 0 ? "+" +d.toFixed(1) + "°C" : +d.toFixed(1) + "°C" , CSI2: (d) => +d.toFixed(0), RiskyAdded: (d) => +d.toFixed(0) } }}), ] }) 33:[{"id":"e69b5679c2818b2c5c965a72a2f9770b6399f04dd9850e6da557517207bb51924c5149c7143976e023ce9b687e4c9b8db302b44c9b64117d3e61a4ab4d6b632f","href":"https://static.observableusercontent.com/files/e69b5679c2818b2c5c965a72a2f9770b6399f04dd9850e6da557517207bb51924c5149c7143976e023ce9b687e4c9b8db302b44c9b64117d3e61a4ab4d6b632f","name":"asia-data-final.csv","type":"text/csv","lastModified":1742480889005.434,"size":2582},{"id":"5a9fadd5c85c0c14f9849886a66dbd03ed67662ead98114cbe633072026e41eec8c0d8ee22bd3c3b0bffb441bf8e8b1964c6861973c9dc3f5f160324feead694","href":"https://static.observableusercontent.com/files/5a9fadd5c85c0c14f9849886a66dbd03ed67662ead98114cbe633072026e41eec8c0d8ee22bd3c3b0bffb441bf8e8b1964c6861973c9dc3f5f160324feead694","name":"CC_LongLogo-3.png","type":"image/png","lastModified":1742480946899.508,"size":199924},{"id":"8ba6f608ee78289013915741d84a155f7c41f98e9d301f7152bdef084c4a625e215b29bb386db06e7232e48302b4d58ad4de4fdc9b7d031dcdfc26e869438120","href":"https://static.observableusercontent.com/files/8ba6f608ee78289013915741d84a155f7c41f98e9d301f7152bdef084c4a625e215b29bb386db06e7232e48302b4d58ad4de4fdc9b7d031dcdfc26e869438120","name":"asia-cities-final.csv","type":"text/csv","lastModified":1742482347803.806,"size":28485},{"id":"7c6167b65013c12f3978b4d8e85dd28a27e3b5eb580d1e76696ce5b0d399c196de2b02c45e734462931e1af823698e36bb072722253d5e03e7fb61222755bc0c","href":"https://static.observableusercontent.com/files/7c6167b65013c12f3978b4d8e85dd28a27e3b5eb580d1e76696ce5b0d399c196de2b02c45e734462931e1af823698e36bb072722253d5e03e7fb61222755bc0c","name":"countries-110m.json","type":"application/json","lastModified":1742482654236.4,"size":107761},{"id":"06f4b18cd080b941a861ed7da3e6991039a700fc585d0ae039735d47e63610abcf4eccc7644decbb21c46570cb24350b7b92f6d7d3e8ec1e8f882a7a10a3d175","href":"https://static.observableusercontent.com/files/06f4b18cd080b941a861ed7da3e6991039a700fc585d0ae039735d47e63610abcf4eccc7644decbb21c46570cb24350b7b92f6d7d3e8ec1e8f882a7a10a3d175","name":"asia-data-final.geojson","type":"application/geo+json","lastModified":1742482230737.518,"size":4694363}] 30:{"title":"People Exposed to Climate Change: December 2024-February 2025","cells":[{"id":0,"value":"

People Exposed to Climate Change: December 2024-February 2025

Asia Regional Summary Maps

","pinned":false,"hidden":false,"mode":"md"},{"id":1069,"value":"This page is meant to serve as a resource for anyone who may want to embed one of the maps featured in Climate Central's People Exposed to Climate Change data explorer. More about the data underlying these maps, along with data for the rest of the world, can be found in the full report, released in March 2025. For any questions, issues, or requests for other regional or country-specific maps, feel free to reach out to Kaitlyn Trudeau at ktrudeau@climatecentral.org.","pinned":false,"hidden":false,"mode":"html"},{"id":450,"value":"#### Map 1: Average temperature anomalies by country","pinned":false,"hidden":false,"mode":"md"},{"id":507,"value":"map1 = embed(\"https://observablehq.com/embed/7a369ddca96516cd@1044?cells=embedMap1&banner=false\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":559,"value":"

Want to embed Map 1 on another website?

${Object.assign(html`

","pinned":false,"hidden":false,"mode":"html"},{"id":571,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":567,"value":"#### Map 2: Days at/above CSI 2 by country ","pinned":false,"hidden":false,"mode":"md"},{"id":581,"value":"map2 = embed(\"https://observablehq.com/embed/7a369ddca96516cd@latest?cells=embedMap2&banner=false\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":611,"value":"

Want to embed Map 2 on another website?

${Object.assign(html`

","pinned":false,"hidden":false,"mode":"html"},{"id":575,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":576,"value":"#### Map 3: Risky heat days added by climate change by country","pinned":false,"hidden":false,"mode":"md"},{"id":599,"value":"map3 = embed(\"https://observablehq.com/embed/7a369ddca96516cd@latest?cells=embedMap3&banner=false\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":640,"value":"

Want to embed Map 3 on another website?

${Object.assign(html`

","pinned":false,"hidden":false,"mode":"html"},{"id":139,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":621,"value":"#### Map 4: Asian cities map","pinned":false,"hidden":false,"mode":"md"},{"id":626,"value":"map4 = embed(\"https://observablehq.com/embed/7a369ddca96516cd@latest?cells=embedMap4&banner=false\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":522,"value":"embedButton = htl.html`

Want to embed Map 4 on another website?

${Object.assign(html`

`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":859,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":862,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":866,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":870,"value":"---","pinned":false,"hidden":false,"mode":"md"},{"id":520,"value":"embedCode1 = {\n return``\n }","pinned":false,"hidden":false,"mode":"ojs"},{"id":539,"value":"embedCode2 = {\n return``\n }","pinned":false,"hidden":false,"mode":"ojs"},{"id":606,"value":"embedCode3 = {\n return``\n }","pinned":false,"hidden":false,"mode":"ojs"},{"id":631,"value":"embedCode4 = {\n return``\n }","pinned":false,"hidden":false,"mode":"ojs"},{"id":126,"value":"viewof plot2 = Plot.plot({\nstyle: {\n\t\tcolor: \"black\",\n\t\tfontSize: 14\n\t},\n\twidth,\n\theight: 600,\n\tprojection: proj2,\n marks: [\n \t\tPlot.sphere({fill:\"#8aa6cb\", opacity:0.75}),\n \t\tPlot.geo(countries, {fill:\"#c7c8ca\", opacity: 0.75}),\n \tPlot.geo(asiaMap, {fill: (d) => getCSIColor(d.properties[\"per-capi_1\"]), stroke:\"black\", strokeWidth:0.5, \n \t channels: { \n\t\t\t Country: {\n\t\t\t \tvalue: \"country/te\",\n\t\t\t \tlabel: \"Country\"\n\t\t\t },\n\t\t\t Population: {\n\t\t\t \tvalue: \"population\",\n\t\t\t \tlabel: \"Population\"\n\t\t\t },\n\t\t\t CSI2: {\n\t\t\t \tvalue: \"per-capi_1\",\n\t\t\t \tlabel: \"Days of CSI 2+\"\n\t\t\t }\n\t\t\t },\n\t\t\t tip: {\n\t\t\t format: {\n\t\t\t \tCountry: true,\n\t\t\t \tPopulation: true,\n\t\t\t \t\tCSI2: (d) => d.toFixed(0)\n\t\t\t }\n\t\t\t\t}})\n ]\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":122,"value":"function getCSIColor(y) {\n\tlet x = +y;\n\tif (x < 1) {\n\t\treturn csiColors[0];\n\t} else if(x >= 1 & x < 5) {\n\t\treturn csiColors[1];\n\t} else if (x >=5 & x < 10) {\n\t\treturn csiColors[2];\n\t} else if (x >= 10 & x < 20) {\n\t\treturn csiColors[3];\n\t} else if (x >= 20 & x < 30) {\n\t\treturn csiColors[4];\n\t} else if (x >= 30 & x < 40) {\n\t\treturn csiColors[5]\n\t} else if (x >= 40 & x < 60) {\n\t\treturn csiColors[6];\n\t} else {\n\t\treturn csiColors[7];\n\t} \n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":113,"value":"csiColors = [\n\t\t\t\"#c7c8ca\",\n\t\t\t\"#fef6f0\",\n\t\t\t\"#fed2c1\",\n\t\t\t\"#fda284\",\n\t\t\t\"#fc8969\",\n\t\t\t\"#f54331\",\n\t\t\t\"#b91419\",\n\t\t\t\"#6b0011\"];\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":115,"value":"viewof legend2 = Legend(d3.scaleThreshold([1,5,10,20,30,40,60,90], csiColors), {\n\ttextColor: \"black\",\n title: \"Average days at or above CSI 2 per-capita\",\n tickSize: 0\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":17,"value":"viewof logo = await(FileAttachment(\"CC_LongLogo-3.png\")).image({width: 250, height:18})","pinned":false,"hidden":false,"mode":"ojs"},{"id":483,"value":"viewof logo2 = await(FileAttachment(\"CC_LongLogo-3.png\")).image({width: 250, height:18})","pinned":false,"hidden":false,"mode":"ojs"},{"id":484,"value":"viewof logo3 = await(FileAttachment(\"CC_LongLogo-3.png\")).image({width: 250, height:18})","pinned":false,"hidden":false,"mode":"ojs"},{"id":486,"value":"viewof logo4 = await(FileAttachment(\"CC_LongLogo-3.png\")).image({width: 250, height:18})","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"value":"asiaData = FileAttachment(\"asia-data-final.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"asiaMap = FileAttachment(\"asia-data-final.geojson\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":153,"value":"riskyColors = [\n\t\t\"#c7c8ca\",\n\t\t\"#fef6f0\",\n\t\t\"#fed2c1\",\n\t\t\"#fda284\",\n\t\t\"#fc8969\",\n\t\t\"#f54331\"\n];","pinned":false,"hidden":false,"mode":"ojs"},{"id":154,"value":"viewof legend3 = Legend(d3.scaleThreshold([1,5,10,15,20,25], riskyColors), {\n\ttextColor: \"black\",\n title: \"Average risky heat days days added by climate change per-capita\",\n tickSize: 0\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":36,"value":"asiaCities = FileAttachment(\"asia-cities-final.csv\").csv({typed:true})","pinned":false,"hidden":false,"mode":"ojs"},{"id":164,"value":"viewof plot3 = Plot.plot({\n\tstyle: {\n\t\tcolor: \"black\",\n\t\tfontSize: 14\n\t},\n\twidth,\n\theight: 600,\n\tprojection: proj2,\n marks: [\n \tPlot.sphere({fill:\"#8aa6cb\", opacity: 0.75}),\n \tPlot.geo(countries, {fill:\"#c7c8ca\", opacity: 0.75}),\n Plot.geo(asiaMap, {fill: (d) => getRiskyColor(d.properties[\"per-capi_3\"]), stroke:\"black\", strokeWidth: 0.5, \n \t channels: { \n\t\t\t Country: {\n\t\t\t \tvalue: \"country/te\",\n\t\t\t \tlabel: \"Country\"\n\t\t\t },\n\t\t\t Population: {\n\t\t\t \tvalue: \"population\",\n\t\t\t \tlabel: \"Population\"\n\t\t\t },\n\t\t\t Risky: {\n\t\t\t \tvalue: \"per-capi_2\",\n\t\t\t \tlabel: \"Risky heat days\" \n\t\t\t },\n\t\t\t Risky2: {\n\t\t\t \tvalue: \"per-capi_3\",\n\t\t\t \tlabel: \"Risky days added by climate change\" \n\t\t\t }\n\t\t\t },\n\t\t\t tip: {\n\t\t\t format: {\n\t\t\t \tCountry: true,\n\t\t\t \tPopulation: true,\n\t\t\t \t\tRisky: (d) => d.toFixed(0),\n\t\t\t \t\tRisky2: (d) => d.toFixed(0)\n\t\t\t }\n\t\t\t\t}\n\t\t\t})\n ]\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":177,"value":"anomColors2 = [\n\t\"#ccdfeb\",\n\t\"#e9f0f4\",\n\t\"#fef6f0\",\n\t\"#fed2c1\",\n\t\"#fc8969\",\n\t\"#f54331\",\n\t\"#b91419\"\n];","pinned":false,"hidden":false,"mode":"ojs"},{"id":323,"value":"variable = {\n if(radioSelect === \"Anomalies\") {\n return \"mean temperature anomaly (¬∞C) during 3-month period\";\n } else if (radioSelect === \"Days of CSI 2+\") {\n return \"days_at_or_above_CSI2\"\n } else {\n return \"days above 90th percentile added by climate change\"\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":179,"value":"function vari(x, y) {\n if(x === \"Anomalies\") {\n return getAnomColor2(+y[variable]);\n } else if (x === \"Days of CSI 2+\") {\n return getCSIColor(+y[variable]);\n } else {\n return getRiskyColor(+y[variable]);\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":195,"value":"function getAnomColor2(y) {\n const x = +(y.toFixed(2))\n\tif (x <= -0.5) {\n\t\treturn anomColors2[0];\n\t} else if (x > -0.5 & x < 0) {\n\t\treturn anomColors2[1];\n\t} else if (x > 0 & x < 0.5) {\n\t\treturn anomColors2[2];\n\t} else if (x >= 0.5 & x < 1) {\n\t\treturn anomColors2[3];\n\t} else if (x >= 1 & x < 2) {\n\t\treturn anomColors2[4];\n\t} else if (x >= 2 & x < 3) {\n\t\treturn anomColors2[5]\n\t} else {\n\t\treturn anomColors2[6];\n\t}\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":200,"value":"legVals = radioSelect === \"Anomalies\" ? [-0.5,0,0.5,1,2,3,4] : (radioSelect === \"Days of CSI 2+\" ? [1,5,10,20,30,40,60,90] : [1,5,10,20,30,40]);","pinned":false,"hidden":false,"mode":"ojs"},{"id":212,"value":"legTitle = radioSelect === \"Anomalies\" ? \"Average temperature anomaly (°C) per-capita\" : (radioSelect === \"Days of CSI 2+\" ? \"Average days at or above CSI 2 per-capita\" : \"Average risky heat days days added by climate change per-capita\");","pinned":false,"hidden":false,"mode":"ojs"},{"id":214,"value":"viewof legend4 = Legend(d3.scaleThreshold(legVals, legCols), {\n title: legTitle,\n textColor: \"black\",\n tickSize: 0\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":173,"value":"viewof radioSelect = Inputs.radio([\"Anomalies\", \"Days of CSI 2+\", \"Risky heat days added by climate change\"], {label:\"Select a variable:\", value:\"Anomalies\"});","pinned":false,"hidden":false,"mode":"ojs"},{"id":240,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":201,"value":"legCols = radioSelect === \"Anomalies\" ? anomColors2 : (radioSelect === \"Days of CSI 2+\" ? csiColors : riskyColors);","pinned":false,"hidden":false,"mode":"ojs"},{"id":160,"value":"function getRiskyColor(x) {\n\tif (x === 0) {\n\t\treturn riskyColors[0]\n\t} else if(x > 0 & x < 5) {\n\t\treturn riskyColors[1];\n\t} else if (x >=5 & x < 10) {\n\t\treturn riskyColors[2];\n\t} else if (x >= 10 & x < 15) {\n\t\treturn riskyColors[3];\n\t} else if (x >= 15 & x < 20) {\n\t\treturn riskyColors[4];\n\t} else {\n\t\treturn riskyColors[5];\n\t}\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"anomColors = [\n\t\"#74a9cf\",\n\t\"#bdc9e1\",\n\t\"#f1eef6\",\n\t\"#fef6f0\",\n\t\"#fed2c1\",\n\t\"#fda284\",\n\t\"#fc8969\",\n\t\"#f54331\",\n\t\"#b91419\"\n];","pinned":false,"hidden":false,"mode":"ojs"},{"id":71,"value":"viewof plot1 = Plot.plot({\n\tstyle: {\n\t\tcolor: \"black\",\n\t\tfontSize: 14\n\t},\n\theight: 600,\n\twidth,\n\tprojection: proj2,\n marks: [\n \tPlot.sphere({fill:\"#8aa6cb\", opacity:0.75}),\n \tPlot.geo(countries, {fill:\"#c7c8ca\", opacity: 0.75}),\n Plot.geo(asiaMap, {fill: (d) => getAnomColor(d.properties[\"per-capita\"]), stroke:\"black\", strokeWidth: 0.5, \n \t channels: {\n\t\t\t Country: {\n\t\t\t \tvalue: \"country/te\",\n\t\t\t \tlabel: \"Country\"\n\t\t\t },\n\t\t\t Population: {\n\t\t\t \tvalue: \"population\",\n\t\t\t \tlabel: \"Population\"\n\t\t\t },\n\t\t\t Anomaly: {\n\t\t\t \tvalue: \"per-capita\",\n\t\t\t \tlabel: \"Anomaly\"\n\t\t\t }\n\t\t\t },\n\t\t\t tip: {\n\t\t\t format: {\n\t\t\t \tCountry: true,\n\t\t\t \tPopulation: true,\n\t\t\t \t\tAnomaly: (d)=> d > 0 ? \"+\" +d.toFixed(1) + \"°C\" : +d.toFixed(1) + \"°C\" \n\t\t\t }\n\t\t\t\t}})\n ]\n}); // <- the semicolon is important!","pinned":false,"hidden":false,"mode":"ojs"},{"id":75,"value":"world = FileAttachment(\"countries-110m.json\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":90,"value":"countries = topojson.feature(world, world.objects.countries)","pinned":false,"hidden":false,"mode":"ojs"},{"id":48,"value":"height = 625","pinned":false,"hidden":false,"mode":"ojs"},{"id":56,"value":"viewof legend1 = Legend(d3.scaleThreshold([-0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.5, 2], anomColors), {\n\ttextColor: \"black\",\n title: \"Average temperature anomaly (°C) per-capita\",\n tickSize: 0\n});","pinned":false,"hidden":false,"mode":"ojs"},{"id":60,"value":"function getAnomColor(x) {\n\tif (x <= -0.5) {\n\t\treturn anomColors[0];\n\t} else if (x > -0.5 & x < -0.25) {\n\t\treturn anomColors[1];\n\t} else if (x >= -0.25 & x <=0) {\n\t\treturn anomColors[2];\n\t} else if (x > 0 & x < 0.25) {\n\t\treturn anomColors[3];\n\t} else if (x >= 0.25 & x < 0.5) {\n\t\treturn anomColors[4];\n\t} else if (x >= 0.5 & x < 0.75) {\n\t\treturn anomColors[5]\n\t} else if (x >= 0.75 & x < 1) {\n\t\treturn anomColors[6]\n\t} else if (x >= 1 & x < 1.5) {\n\t\treturn anomColors[7]\n\t} else {\n\t\treturn anomColors[8];\n\t}\n};","pinned":false,"hidden":false,"mode":"ojs"},{"id":58,"value":"import {Legend} from \"@d3/color-legend\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":500,"value":"import {embed} from \"@observablehq/auto-resizing-embed\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":529,"value":"import {copy} from \"@mbostock/copy-to-clipboard\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"embedMap1 = htl.html`\n

\n\n

${viewof logo}

${viewof legend1}

${viewof plot1}

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":112,"value":"embedMap2 = htl.html`\n

\n\n

${viewof logo2}

${viewof legend2}

${viewof plot2}

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":303,"value":"embedMap3 = htl.html`\n

\n\n\n

${viewof logo3}

${viewof legend3}

${viewof plot3}

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":422,"value":"embedMap4 = htl.html`\n

\n\n\n

${viewof logo4}

${viewof radioSelect}

${viewof legend4}

${viewof plot4}

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":805,"value":"proj2 = d3.geoMercator()\n .fitExtent([[30, 40], [width - 30, height - 40]], asiaMap)\n\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"proj1 = d3.geoMercator()\n .center([86, 14]) // Rough center of India\n .fitSize([width, height], asiaMap)","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}