Mapping Temperature Deviation and Elderly Vulnerability using Open Source Technology: A One-Week Analysis of Manhattan, New York City

Aurash Khawarzad

This paper outlines a research method for collecting, analyzing, and visualizing real-time temperature data for cities using open data and open source technology. The system collects temperature data for each census tract in Manhattan three times daily via the OpenWeather API and stores observations in a PostgreSQL/PostGIS database. A one-week pilot study (November 15-22, 2025) analyzed 8,990 temperature observations across Manhattan's 310 census tracts, revealing a borough-wide temperature range of 38.3°F to 55.2°F, including a mean of 45.4°F and standard deviation of 4.4°F. Census tract 263 (Washington Heights) recorded the coldest temperature (38.3°F), while tract 2.02 (Lower East Side) recorded the warmest (55.2°F). Tract 303 (Inwood) exhibited the highest internal temperature variability with a standard deviation of 4.6°F across the study period. A vulnerability index combining temperature deviation with elderly population density identified census tract 181 (Upper West Side) as having the highest risk during the study period. This approach establishes a scalable, replicable model for continuous climate monitoring to inform urban planning, design, and policy. Ongoing data collection and analysis are proposed in the paper. The active project is viewable at: https://terrestrialresearch.com/machinelearning/agetemp/tempage.html.