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Select variables and click Build Composite Risk Map
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click tracts to explore
EP_NOINT, shututility_prev); <stem>_data_dictionary.csv gives each one a plain-English label, its units, whether a higher value means more or less risk, and a link to the original source. It also records the heat mode, scenario and switched-on variables the index columns were built from. GeoJSON downloads carry the same information at metadata. Watch the direction: adaptive_score is stored capacity-side (100 = most capacity, least risk), the opposite of exposure_score and sensitivity_score.in_download = no and a note on where to request them. Percentile ranks (0–100) are always computed against all San Diego County tracts, even when you export a single jurisdiction. Every row carries citation, license (CC BY 4.0) and sources_url columns; the full source table is in the User Guide.Only heat exposure responds to the climate scenario. Who is vulnerable and their ability to cope stay at today's levels, so the right map isolates the warming signal. The scale is percentile points — a tract's countywide exposure rank, 0 to 100.
Quick start
Or use the left panel to customize your map. Here’s what each section does:
© 2026 Southern California Extreme Heat Research Hub & San Diego Regional Climate Collaborative. Code MIT; data & content CC BY 4.0, each source under its own terms.