Tool Overview

The Extreme Heat Mapper allows users to view modeled temperature maps for select hours of heat events. The maps show modeled outputs for a historical event at 30-meter neighborhood-level resolution and for a replay of the same event under a warmer future climate. To view more about the historical and future weather inputs, see About the Thermodynamic Global Warming (TGW) Dataset.

Simulations were conducted using the i-Tree Cool Air model, and the resulting modeled outputs were used to characterize spatial patterns of extreme heat. This spatial model resolves for water and energy balances utilizing raster inputs of land use, tree and impervious cover percentage, elevation, and anthropogenic heat. For more information on the i-Tree Cool Air model, see the i-Tree Cool Air Model Methods.

One long-duration heat event, spanning June 29–July 5, 2018, serves as the baseline for the Extreme Heat Mapper. The event brought high temperatures across the state and was selected for high-resolution simulation. To view temperatures across more heat events, use the Heat Trends Explorer.

The future modeled outputs show how the same heat event could become hotter, last longer, and affect more areas under a warmer climate. They are not intended to predict the number of heat events for a given year.

How to Use the Tool

For an interactive walkthrough of these steps, select Page Guide from the information card at the top of any tab.

Location

Select counties on the map to encompass your areas of interest. This will determine the area that the subsequent maps load in, and the color range for the temperature maps.

Use Identify to click on a boundary and view detailed statistics for the area. Box Select allows the user to click and drag to add selections.

If the user has a previously exported project file, they can import it using the Import Project (.uhim) button in the top-right corner of the Selection pane.

Once the user has selected areas of interest, they can click Continue to move to the Timeframe tab.

Timeframe

Use the Timeframe tab to review the selected heat event, compare historical and future conditions, and choose the hour that will be displayed on the temperature maps. The event information panel summarizes the historical event and its future recreation, presents observed statewide maximum temperatures, and provides links to supporting data. Select Back to Location Selection to revise the analysis area.

The temperature graph compares area-averaged modeled outputs for the historical event (2018), shown as a solid line, with the future replay (2058), shown as a dashed line. Use the checkboxes to show or hide either series. The adjacent controls change the displayed temperature type between Air Temp, Heat Index, and WBGT (Wet Bulb Globe Temperature).

Hover over a marked point on the graph to view its date, time, and historical and future average temperatures. Click a point to select that hour, or use the month, day, and hour controls below the graph to move through the available timeframe.

The Preset Hours provide three calculated selections:

  • Hottest hour: Selects the mappable hour with the highest historical area-average temperature.
  • Highest min: Identifies each day’s lowest mappable historical temperature, then selects the warmest of those daily lows. This is useful for examining periods when temperatures provide the least overnight or daily relief.
  • Greatest future heat increase: Selects the mappable hour with the largest modeled temperature increase between the historical event (2018) and future replay (2058).

The selected hour is used to create both historical and future temperature maps. Once an hour has been selected, choose Continue to Map to proceed to the Map tab.

Map

Once the map loads, several tools and settings are available:

Maps and Layers

Use the Maps tab to adjust temperature-map transparency and color scheme. Use the Layers tab to manage other visible layers. The Boundaries sub-tab supports selection, analysis, and map exports, while the Overlays sub-tab shows demographic, heat vulnerability, and land-use information.

Air Temperature: Heat Index: Wet Bulb Globe Temperature:
modeled Fahrenheit air temperature at a 6-foot height a measure of how hot it feels when relative humidity is combined with the air temperature a measure of heat stress in direct sunlight that accounts for temperature, humidity, wind speed, sun angle, and cloud cover.

Map Tools

Click a tool button above the map to turn it on. An active tool is highlighted in green. Click the button again to turn the tool off.

Navigate moves and zooms the map.

Select selects a boundary when it is clicked. Click the same area again to remove the selection. The map cannot be moved while Select is active.

Box-select selects multiple boundaries by clicking and dragging on the map. Hold Ctrl while clicking and dragging to remove areas. The map cannot be moved while Box-select is active.

Center moves and zooms the map to show all selected areas. If no areas are selected, it shows the full map area.

Clear selection removes all current selections.

Identify areas using the bottom-right map icon . With the tool active, click the map to view the data value at that point or statistics for the boundary.

Getting Started

Not sure where to start? Follow the steps below:

  1. Get oriented. The Page Guide provides a guided overview of the map and tables. The tab contains background information about the data, temperature types, and map controls. Additional instructions, examples, and data references are available from About .
  2. Choose a temperature map. Open Maps tab and select Air Temperature, Heat Index, or Wet Bulb Globe Temperature (WBGT). Toggle the historical, future, or difference maps and adjust transparency to view the base map underneath. A transparency of 20–50% usually preserves heat details while keeping underlying features visible. Colorbar schemes can also be changed.
  3. Add boundaries and overlays. Open Layers tab and use the Boundaries sub-tab to select Census Block Groups, Census Tracts, City/Town boundaries, or Counties. These boundaries define the areas available for selection and table analysis. The Overlays sub-tab includes median temperature, land cover, community characteristics, heat vulnerability, and disadvantaged-community information.
  4. Navigate the map. Use Navigate to pan, Select to add or remove individual boundaries, Box Select to select several boundaries, Center to return to the analysis area, and Clear to remove all selections. The map can also be explored with the address search, zoom buttons, mouse wheel, and stacked or side-by-side layout controls.
  5. Identify map values. Expand Identify from the lower-right corner of the map. Select a visible temperature, overlay, or boundary layer and click Enable Identify before clicking the map. Results may include temperature-cell values, land-cover characteristics, or boundary statistics. Re-click the button or press ESC to disable Identify.
  6. Select areas for analysis. Activate a boundary layer before using Select or Box Select. Click a boundary to add it, click it again to remove it, or drag a box across multiple areas when using Box Select. Selected areas populate the tables adjacent to the map with temperature, climate, land-cover, census, and vulnerability information.
  7. Review and edit the tables. The Selections tab supports custom aliases and colors and allows the project to be saved for a later browser session. Additional tabs summarize hourly temperature, land characteristics, historical and future climate statistics, census populations, and Heat Vulnerability Index data. Sortable columns can help identify the highest- or lowest-ranking areas.
  8. Compare results and export. Compare selected areas by temperature, land cover, population vulnerability, modeled climate statistics, or heat-event frequency. Identify can support cell-level investigation within selected boundaries. Use Export tab to adjust the final map and download available maps, table images, CSV data, or viewport-based raster outputs.

View examples in About or try one of the following exercises:

  1. Compare block groups in a small area. Find representative school, park, hospital, downtown, and suburban census areas. Compare daytime and nighttime maximums, contrast population vulnerabilities, and study future changes in heat events or temperature to rank areas for vulnerability. This provides an overview of how temperature can change based on land use.
  2. Find the hottest areas and identify risk factors. Use Identify, Box Select, and table removal controls to narrow the selection to the hottest census block groups or tracts. For each area, identify a different high-risk characteristic such as elderly population, land use, HVI indicators, current temperature, or future climate temperature.
  3. Complete a cell-based analysis. Use a temperature or difference map to investigate the largest temperature values or changes. Identify individual cells and compare them with tree cover, impervious cover, and land-cover overlays to explore how landscape characteristics relate to heat exposure.

Export

Use the Export tab to create a custom map view and add tables for download. When more than one file is selected, the outputs are packaged together in a ZIP file.

  1. Choose the Map Export - under Map Type, select the desired map output:
    1. .PNG saves the image shown in Map Preview, including the selected map area, visible layers, legend, map details, and Map Layout settings.
    2. .TIF saves the visible Map Preview area as a geospatial raster for use in GIS software or further analysis.
    The temperature variable and map style originate from Map tab; return there to change the temperature map used in the export.
  2. Edit Map Options - when .PNG is enabled, use Map Area to control the map's extent, visible boundaries and overlays, legend content, north arrow, and scale bar. Hover over an information icon for additional details about an option. Use Map Layout to position the legend and map details and to select the page orientation. Changes are reflected in Map Preview. Review the preview before downloading to confirm that the map extent, layers, labels, metadata, and orientation are correct. If .PNG is not enabled, these image-layout options can be skipped.
  3. Add Tables and Download - under Table Formats, select the tables to include and choose whether they should be saved as images, CSV files, or both. Table images use a plain white background by default. Enable Use custom colors on table to apply the colors assigned to selected areas. When the tables have been configured and the map preview has been reviewed, select Download. If multiple outputs were selected, they will be packaged into a single ZIP file.

Examples

These examples show how municipalities and other local organizations can use Extreme Heat Mapper results in planning and project development. Each example connects the maps and tables to one practical decision: comparing neighborhoods for adaptation planning, identifying emerging risk for long-range planning, or screening areas for heat-mitigation projects. Results can support plans and project discussions when considered alongside local knowledge, community input, field conditions, and feasibility.

Example 1

Compare Neighborhoods for Heat Adaptation Planning

A municipality developing a heat adaptation plan may first need to understand how heat exposure and vulnerability differ among neighborhoods and important community locations. By comparing downtown, a hospital, an airport, a park, and suburbs with different tree-cover levels, this example shows where heat concerns overlap with population vulnerability, limited tree cover, or other local conditions.

Municipal staff can use the results to compare neighborhoods, identify where different heat strategies may be needed, and document priority areas in an adaptation or comprehensive plan. Reviewing hourly and 10-year heat metrics together also helps distinguish where green infrastructure may be feasible from places where other heat-reduction or preparedness measures may be needed.

Select the map bounds

In the Location tab, select the county containing the city of interest.
In the Timeframe tab, “Hottest hour” is selected by default. After areas are selected, the hour can be adjusted.

Location tab with Erie County selected.
Erie County is highlighted in orange after clicking on the map.

Set up the map view

After the map loads, open the Layers tab in the upper-right map pane. In the Boundaries sub-tab, select Census Block Groups or Census Tracts to show smaller boundaries.
Use Select at the top of the map to add areas by clicking them.
Increase the temperature-map transparency to see the basemap and more easily select areas near hospitals, parks, or other landmarks.

Temperature map with block groups selected and map select active.
Temperature map with transparency increased. Block Groups are selected from the Boundaries options, and the select tool is active from the top panel to click and select areas in cyan.

Select areas across a city

The selected areas include an airport, downtown, a hospital, a park, a high-tree-cover suburb, and a low-tree-cover suburb. Other useful comparison areas may include commercial zones, construction areas with outdoor workers, or agricultural land.

After selecting the areas, assign each area a color and alias so the table and map are easier to read. Save the changes, then export the selections as a .uhim file so the same areas and custom appearances can be imported later. Turn on tinted table rows to distinguish area types more easily.

Selections table with custom colors and nicknames.
Tables from the Selections tab showing the selected layer ID, nickname assigned to each layer, and updated colors. This view is from after the button is triggered. To save changes, the hovered-over Save button must be clicked. To revisit the project later, Export .uhim is highlighted. It is highly recommended to tint table rows with selection colors for easy differentiation of selected areas.

Compare Area Characteristics

The Land, Census, and Heat Vulnerability Index (HVI) tabs summarize each area’s population, land cover, and heat vulnerability.

Land Cover

The Land tab summarizes land-cover data for each selected area. Key patterns include:

  1. Tree cover is highest in the high-tree-cover suburb, followed by the park.
  2. Impervious cover is the highest downtown, followed by the hospital and the low-tree-cover suburb.
  3. Plantable space is estimated by subtracting tree cover and impervious cover from the total land area. It is highest in the park, airport, and high-tree-cover suburb, where grass and other open land are more common.

Areas with low tree cover and high plantable space may be good candidates for green infrastructure or other heat interventions, depending on their heat exposure and population characteristics. These differences can help a municipality screen where tree planting or green infrastructure may be feasible and where limited available space may require other heat-reduction strategies.

Land cover table sorted by plantable space.
Land cover table, sorted by plantable space.
Census Data

The Census tab shows population characteristics for each selection and helps identify where people, especially vulnerable groups, are concentrated. This context helps target interventions to high-impact areas. In this example:

  1. Disadvantaged communities are concentrated downtown and near the hospital.
  2. The park and airport areas have lower incomes and higher percentages of people of color (POC), which may be associated with greater outdoor heat exposure. However, these areas have smaller older adult and disabled populations, two groups with higher susceptibility to heat stress.
  3. The largest population concentrations are downtown, in the low-tree-cover suburb, and in the airport block group.

These population and demographic indicators show who may be affected by an extreme heat event and how many people are exposed. Combined with the heat and land-cover results, they can help prioritize neighborhoods in an adaptation or comprehensive planning process.

Census table sorted by percent people of color.
Census table, sorted by % POC.
Heat Vulnerability Index

The HVI tab combines statewide heat, population, and health-outcome indicators into a broader heat-risk profile. In this example:

The HVI ranks the suburbs highest for heat exposure, largely because of the increase in days above 85°F heat index from 2000 to 2021. Heat index combines air temperature and humidity to estimate how hot conditions feel to the human body.

Sociodemographic vulnerability is highest near the hospital and downtown, largely because of heat risk among the Black/African American population.

HVI heat exposure table sorted by days above 85 degrees Fahrenheit heat index percentile.
HVI Heat Exposure table sorted by Days >85°F Heat Index percentile; measured from 2000–2021.

Health-outcome susceptibility is highest near the hospital, driven in part by the highest acute kidney failure emergency department visit rate in the statewide non-NYC dataset.

Together, these indicators give the hospital area the highest overall Heat Vulnerability Index ranking, followed by the downtown and suburban areas. For municipal planning, this ranking helps explain why a priority area may not be the hottest place: heat exposure and susceptibility are considered together.

Health outcomes table with emergency department visits and hospitalizations.
ED = emergency department visits; HP = hospitalizations.
Main HVI table ranking selected areas.

Compare Heat

With the population and land-cover context in place, compare model-estimated urban heat patterns for an extreme heat event and examine how those patterns change in the 2050s replay. In the Extreme Heat Mapper, “historical” means a calibrated climate-model recreation of a past weather event, not direct observations. “Future” means that same recreated event is replayed under a hotter 2050s climate, with climate-forced changes in temperature, moisture, and related weather fields. It is not an independent climate projection that creates its own weather sequence. Simulations were conducted using i-Tree Cool Air for both the historical recreation and the 2050s replay. The model accounts for tree canopy, impervious surface, other land cover, elevation, anthropogenic heat, and related local factors; the resulting modeled outputs are the spatial temperature maps and tables shown in the tool. Modeled outputs can be explored as hourly values for a single event and as 10-year average summaries.

The Temperature tab reports statistics for the hour shown on the map: the maximum value within the selected area (the hottest pixel), the mean across all pixels in the area, and the minimum value.

Temperature table for selected areas.

Sorting by air temperature shows that the highest maximum values occur downtown, at the airport, and near the hospital. These same areas remain among the hottest in the 2050s replay. For this hour, however, the largest increases occur downtown for maximum and mean temperature and in the low-tree-cover suburb for minimum temperature.

Although maximum temperatures in the hottest areas are close to one another, about 0.5°F apart, mean temperature better summarizes conditions across each full area. Downtown’s mean temperature is more than 1°F higher than the suburban areas.

High minimum temperatures indicate areas with little green space and mostly residential or urban development. Because downtown includes a park, the highest minimum temperatures occur in the low-tree-cover suburb and near the hospital. Tonawanda, the low-tree-cover suburb, also has the largest increase in minimum temperature.

Repeat this process for the heat index and wet bulb globe temperature tables. WBGT combines air temperature, humidity, wind, and solar radiation to estimate heat stress. Sorting each statistic and decade helps compare extreme and average heat conditions during the event.

The Climate tab summarizes modeled outputs from the 300-meter, 10-year i-Tree Cool Air simulations for 2010–2019 and 2050–2059 using the thermodynamic global warming dataset. These 10-year summaries are separate from the 30-meter maps, which show modeled outputs for a single heat event.

The first table reports the average maximum heat metric from June through September over each 10-year period. It loads with Heat Index selected by default. The largest average heat-index increases occur in the suburbs, where lawns and limited shade can compound heat stress. However, these suburbs still have lower absolute heat-index values than the other compared areas.

Climate table comparing median maximum air temperature for 2010s and 2050s.
Median Maximum Air Temperature for 2010–2019 and 2050–2059.

The Heat Advisories & Warnings section summarizes modeled heat event days using the tool's NYS and National categories. NYS heat event days meet a heat index threshold above 95°F for at least two hours. The displayed historical averages are two NYS heat event days per year for downtown, the hospital, and the park, compared with one for the airport block group. These modeled outputs compare estimates for the selected locations; they are not airport weather-station observations or records of official National Weather Service advisories and warnings. For emergency and public-health planning, this comparison can help staff evaluate whether the modeled value for a single airport block group adequately represents potential heat exposure across nearby communities.

Climate event table showing annual average of days above 95 degrees Fahrenheit heat index for two or more hours.
Annual Average of Days >95°F Heat Index for 2+ hours.

Export Map

The table review suggests three main findings:

  1. The hospital and downtown areas have the highest heat vulnerability and are also disadvantaged communities, making them high priorities for heat interventions. Lower plantable space, however, may limit some green-infrastructure options.
  2. The suburbs have lower overall heat vulnerability, but heat increases faster there in the 2050s replay. Their larger older adult and disabled populations may also increase heat risk.
  3. Some urban areas have more modeled NYS heat event days than the airport block group. The modeled output for one airport block group does not fully represent heat exposure across nearby urban areas.

The selected areas and tables can be exported together to share findings. Center the selected areas in the frame as much as possible and leave room in one corner for the legend before moving to the Export tab. In the Export tab, add a legend that includes the title, temperature scale, and selected areas in the bottom-left corner. Then export the map as a PNG file. The exported map can be included in planning documents or community meetings to communicate why neighborhoods were selected for further evaluation.

Exported map with selected areas labeled.
Exported map with labels shown for each area selection.

Conclusion

This example demonstrates that the hottest places are not always the same as the most vulnerable places. Downtown and hospital areas may have higher heat vulnerability and more disadvantaged communities, while suburban areas may show larger future increases in heat during the 2050s replay. Suburban populations may sometimes have higher rates of disabled or elderly individuals; living alone further increases risk. The example also shows that the airport block group's modeled NYS heat event frequency does not fully represent nearby urban conditions. A municipality could use this combined analysis to compare neighborhoods for an adaptation or comprehensive plan, flag potential gaps in emergency and public-health planning, and identify places that need more detailed local evaluation.

Data

Simulations

Simulations were conducted using the i-Tree Cool Air model (revision 1946) for June 30 through July 5, 2018 and the corresponding 2058 future scenario at 30-meter resolution. The simulations used 2019 land cover, tree canopy, and impervious cover inputs from the National Land Cover Database (NLCD). Elevation, in centimeters, was retrieved from the National Hydrography Dataset Plus V2 (NHDPlusV2). Each simulation was divided by HUC10 watershed to calibrate initial soil moisture and watershed discharge for each period.

Anthropogenic heat, or thermal energy released into the atmosphere from human activities, is represented using a 1-kilometer hourly anthropogenic heat flux dataset. Link The dataset provides anthropogenic heat emissions in W/m2 for each hour of the day across each month. The anthropogenic heat grids are separated into commercial+residential emissions and transportation emissions. These components are resampled from 1-kilometer to 30-meter grid cells using impervious cover and urban land use distribution.

The resulting modeled outputs include modeled air temperature, heat index, and wet bulb globe temperature as ASCII files. Watershed-level modeled outputs are merged into statewide maps. Water cells are excluded from the temperature maps and subsequent census-level analysis.

Map

Boundaries

Census Block Group: Administrative boundary data displaying the 2020 block group boundaries. Block groups are clusters of blocks within the same census tract and generally contain between 600 and 3,000 people. Link

Census Tract: Administrative boundary data displaying the 2020 census tract boundaries. Census tracts are subdivisions of United States counties and generally contain between 1,200 and 8,000 people, with an optimum size of about 4,000 people. Link

City/Town:

  • Non-NYC: Administrative boundary data displaying the 2020 county subdivision boundaries clipped to the shorelines of major hydrographic features. Census county subdivisions are divisions of counties, including Minor Civil Divisions (MCDs) and Census County Divisions (CCDs). Link
  • NYC: Administrative boundary data displaying the 2020 Neighborhood Tabulation Areas (NTAs). NTAs are created by aggregating census tracts within Community District Tabulation Areas (CDTAs). Link

County: Administrative boundary displaying the 2020 county boundaries clipped to the shorelines of major hydrographic features. Counties are the primary legal, administrative, and statistical subdivisions of a state. Link

Disadvantaged Communities: Administrative census tract-level boundary displaying disadvantaged communities (DACs) defined by the New York State Energy Research and Development Authority (NYSERDA). DACs are underserved communities identified as priority areas in planning and programs for state climate initiatives. Link

Economic Development Regions: Administrative boundary delineating New York into 10 separate regions based on shared economic interests, geography, and labor market. The Regional Economic Development Councils (REDCs) drive local, bottom-up economic growth and direct state investments. Link

State: Administrative boundary displaying the 2020 New York State boundaries clipped to the shorelines of major hydrographic features. Link

Overlays

Land Cover

Tree Canopy: Tree canopy raster from the 2019 National Land Cover Database (NLCD) at 30-meter resolution, produced by the Forest Service as a partner in the Multi-Resolution Land Characteristics Consortium (MRLC). This layer represents the percentage of each cell occupied by the tree canopy. Link

Plantable Space: Estimated percentage of each cell that is not occupied by tree canopy or impervious cover. It is calculated as 100% minus tree canopy cover minus impervious cover. Because NLCD tree canopy cover can underestimate the existing canopy, this value may overestimate available planting space. Plantable space should therefore be interpreted as a screening-level indicator of potential planting opportunity rather than a field-verified estimate of plantable land. Supporting references: Nowak and Greenfield 2010 Link; Greenfield and Schleeweis 2019 Link

Impervious Cover: Impervious cover raster from the 2019 National Land Cover Database (NLCD) at 30-meter resolution, produced by the U.S. Geological Survey (USGS) Land Cover program. Link

Land Cover: Land cover raster from the 2019 National Land Cover Database (NLCD) at 30-meter resolution, produced by the U.S. Geological Survey (USGS) Land Cover program. It classifies land into categories including urbanization, forest, agriculture, grasslands, and wetlands. Link

Community

% POC: Percentage of the total population that is Hispanic or non-white, calculated at the block group level. Link

% Low Income: Percentage of the total population below 200% of the 2022 poverty level. Poverty threshold source: Link ACS table source: Link

% Disabled: Percentage of the total population with one or more disabilities, calculated at the census tract level. Link

% Elderly: Percentage of the total population over age 64, calculated at the block group level. Link

Heat Vulnerability Index (NY): Percentile score from 0–100 defined on a statewide, non-NYC census tract scale. The census tract HVI scores reflect how temperatures in the tract compare to temperatures in other areas of the state, how emergency department visits and hospitalizations for select heat-related health outcomes in the tract compare to other areas of the state, and characteristics of the population in the tract that may be linked with increased vulnerability to heat. Link

Heat Vulnerability Index (NYC): Score from 1–5 defined for Neighborhood Tabulation Areas (NTAs) in New York City. The index weighs air conditioning and green space access, median income, and Black/African American population. Link

Base Map

Map data copyrighted OpenStreetMap contributors and available from OpenStreetMap. Link

Tables

Temperature

Temperature statistics describe modeled minimum, mean, maximum, and change values for the selected hour.

Minimum: Lowest pixel value among all temperature cells in the boundary.

Mean: Average of all temperature pixel values in the boundary.

Maximum: Highest pixel value among all temperature cells in the boundary.

Change: Temperature difference between the 2050s and 2010s modeled outputs.

Land

Average values of land use characteristics from the 2019 National Land Cover Database (NLCD) used in model simulations.

Tree Cover %: Average tree cover percentage from 2019 NLCD Tree Canopy Cover. Link

Impervious Cover %: Average impervious cover percentage from 2019 NLCD Impervious Cover. Link

Plantable Space %: Estimated space remaining after subtracting tree canopy cover and impervious cover from total land area. This value is best interpreted as a screening-level estimate of potential planting opportunity. Tree canopy source: Link Impervious cover source: Link

Climate

Statistics derived from modeled outputs of the 300-meter 2010–2019 and 2050–2059 simulations, examining differences in heat between decades.

Average Maximum Temperature
Air Temperature Heat Index Wet Bulb Globe Temperature
50th percentile of modeled daily maximum air temperature from June through September for the modeled 10-year period. 50th percentile of modeled the daily maximum heat index from June through September for the modeled 10-year period. 50th percentile of modeled daily maximum wet bulb globe temperature from June through September for the modeled 10-year period.
Heat Advisories and Warnings

The NYS and National Heat Advisory and Warning categories are used in this tool to classify and compare modeled heat events. Their definitions are not intended to represent official advisories or warnings issued by National Weather Service (NWS) Weather Forecast Offices, or the criteria those offices use. They support analysis of two broad patterns: shorter-duration, primarily daytime heat events (NYS) and multi-day heat events with limited nighttime cooling (National). Within each group, Advisory and Warning categories distinguish different heat-index thresholds.

Annual NYS Heat Event Days Total National Heat Event Days
Average yearly number of days in the modeled 10-year period where the modeled maximum heat index is greater than 95°F for two or more hours. To read more about event calculations, see the Heat Trends About page.
Because this value is calculated from maximum heat index, a tract, city, or county inherits an event any time one or more block groups within it meet the threshold. 		Decadal sum of events where the daily maximum heat index is greater than 100°F and daily minimum air temperature is greater than 75°F for at least two consecutive days. To read more about event calculations, see the Heat Trends About page.
Because this value is calculated from maximum heat index and warm overnight air temperature, a tract, city, or county inherits an event any time one or more block groups within it meet the thresholds.

Census

Statistics for the population from the 2018–2022 American Community Survey. The selected statistics represent populations that may be more vulnerable or exposed to extreme heat.

All variables except disadvantaged communities (DACs) are calculated at the census block group level and summed to all other geographies. City/town populations across the state have boundaries that do not align with tracts or block groups. Each block group is assigned to the city/town boundary with which it has the largest area overlap; therefore, population statistics for these areas are estimates.

Additionally, cities such as Syracuse, Rochester, Schenectady, and Plattsburgh have small geometries that do not encompass a full census block group boundary. If the additional geometry encompasses more than 50% of the area, it is included in the city population count.

Population: Total population from ACS 2018–2022. Table DP05. Link

% Disadvantaged Community: Percentage of the population identified as living in a disadvantaged community by NYSERDA. DACs are underserved communities identified as priority areas in planning and programs for state climate initiatives. This variable is calculated at the census tract scale. Link

% POC: Percentage of the total population that is Hispanic or non-white.

% Low Income: Percentage of the total population with household earnings below 200% of the 2022 poverty level.

% Disabled: Percentage of the total population with one or more disabilities.

% Elderly: Percentage of the total population over age 64.

% No HS (25+): Percentage of the total population over age 25 with no high school diploma.

Heat Vulnerability Index (non-NYC)

The New York State Heat Vulnerability Index (HVI) is a percentile score from 0-100 defined on a statewide, non-NYC census tract scale. The census tract HVI scores reflect how temperatures in the tract compare to temperatures in other areas of the state, how emergency department visits and hospitalizations for select heat-related health outcomes in the tract compare to other areas of the state, and characteristics of the population in the tract that may be linked with increased vulnerability to heat. Link

The methodology for calculating the HVI can be found on the NYS Department of Health Website.

Heat Vulnerability Index and exposure, sociodemographics, and health outcome values are displayed as a median and min-max range for larger geographies with multiple census tracts, and as a single value for census tracts and block groups. All individual attributes for each category are visible as either a statewide percentile from 0–100 or as a raw value.

City/town populations across the state have boundaries that do not align with tracts. Each tract is assigned to the city/town boundary with which it has the largest area overlap; therefore, statistics for these areas are estimates and marked with a warning.

Heat Exposure Percentile: Percentile for summed heat exposure variables.

Exposure Variable Description
Days >85°F Heat Index (HI) Trend Yearly linear trend in the number of days the heat index reaches 85°F or greater since 2000.
Avg. Max Heat Index (HI) Average daily maximum heat index for all landmass census tracts in New York State, excluding New York City, between May and September for years 2012–2021.

Sociodemographic Percentile: Percentile for summed sociodemographic variables.

Sociodemographic Variable Description
% Black/AA Percentage of the census tract population who are Black or African American Alone or in Combination with Some Other Race.
% Disabled Percentage of census tract population with a disability.
% Elderly Live Alone Percentage of census tract population age 65 years and older who live alone.
% Low Income The percentage of the census tract population living below 200% of the poverty line.
% Limited English Percentage of the census tract population age 5 and over who speak English less than very well.
% Outdoor Workers Percentage of the employed civilian workforce in agriculture, forestry, fishing and hunting, mining, or construction industries.
% Uninsured Percentage of the civilian non-institutionalized population without health insurance.

Health Outcome Percentile: Percentile for summed health outcome variables.

Values are rates per 100,000 people for aggregated subcounty areas. Percentiles are a statewide ranking for subcounty areas in New York State excluding NYC.

Health Outcome Variable Description
Asthma Emergency Department (ED) Rate Rate of asthma ED visits per 100,000 people.
Chronic Obstructive Pulmonary Disease
Emergency Department Rate (COPD ED)		 Rate of COPD ED visits per 100,000 people.
Heart Attack Emergency Department (ED) Rate Rate of hospitalizations for heart attacks per 100,000 people.
Diabetes Hospitalization (HP) Rate Rate of hospitalizations for diabetes per 100,000 people.
Acute Kidney Failure Emergency Department (ED) Rate Rate of acute kidney failure ED visits per 100,000 people.

Heat Vulnerability Index: Heat Vulnerability Index from 0–100. This is the percentile of summed scores for heat exposure, sociodemographic, and health outcome factors, used to measure a census tract population's susceptibility to injury or harm during periods of hot weather.

Heat Vulnerability Index (NYC)

The New York City Heat Vulnerability Index is calculated at the Neighborhood Tabulation Area (NTA) scale and ranks neighborhoods from 1–5 based on environmental and social factors associated with increased heat risk. Since the HVI variables are calculated at the neighborhood scale, variables such as green space are not shown in this tool to avoid confusion with census block group or tract estimates such as tree cover percentage. View all HVI variables from the source. Link

Air Conditioning: Percentage of adults reporting that they have an air conditioner. The citywide median is 91%.

Median Income: Median household income at the neighborhood scale. The citywide median is $67,046.

Black Population %: Percentage of population identifying as Black or African American Alone or in Combination with Some Other Race.

Heat Vulnerability Index (HVI 1–5): Heat Vulnerability Index from 1–5, ranking NYC neighborhoods based on temperature, air conditioning, green space, median income, and racial inequalities.

Select counties on the map to define the boundaries to load temperature maps within.
Enable Identify to view basic information about an area, or enable Box Select to select several areas.
Launch the Page Guide or view the About tab in a new window for help using the tool and to view examples.
Loading map...
Layers
Disadvantaged Communities (DACs)
Selected counties will define the boundaries for temperature maps. Smaller boundaries for analysis will be selectable in a later step.
Select an hour to load temperature maps by clicking a point on the temperature graph below or choosing a preset hour. Use the time and temperature controls to edit the graph view.
Event 5 historical heat index map 2018
Event 5 future heat index map 2050s

Heat Event Summary

June 29 - July 5, 2018

The week-long heat event was simulated at a 30-meter resolution with the i-Tree Cool Air model because of its prevalence of heat across the state. The adjacent graph shows the simulated temperature in selected areas for the historical and future temperature model outputs. The following text provides context to the event with temperature observations.

Temperature anomalies up to 14°F were observed in Albany, Plattsburgh, and Long Island. Most of the state was under excessive heat warnings during the weeklong heat event, including the Fourth of July holiday.

When the same event is simulated under a hotter SSP245 climate scenario, the modeled outputs show statewide temperatures averaging 4°F higher. During select hours, the modeled heat index increases by more than 15°F and air temperature by as much as 10°F across the state. Along the I-95 corridor and into New York City, the modeled outputs show up to five days with heat index above 100°F.

Observed NCEI NOAA Temperatures (2018)

Station Location Max Air Temp. Date
Albany Intl. Airport 97°F July 2
Greater Binghamton Airport 90°F July 2
Buffalo Niagara Intl. Airport 93°F July 4
Long Island MacArthur Airport (Islip) 95°F July 1
Ithaca-Tompkins Regional Airport 96°F July 1
Central Park 93°F July 2
Plattsburgh International Airport 92°F July 2
Adirondack Regional Airport (Saranac Lake) 92°F July 1
Syracuse Hancock Intl. Airport 95°F July 2
June 29 - July 5, 2018 & 2058 Area Air Temperature modeled Fahrenheit air temperature at a 6-foot height.
Hour Selection:
Preset Hours:
Month
Day
Hour
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Action
Customize temperature maps and add layers, then select areas of interest using the map controls. The tables adjacent to the map will populate when boundaries are selected.
Select areas using the map controls to populate the table.
About the Data

Simulations were conducted using i-Tree Cool Air at 30-meter resolution for June 29 – July 5, 2018, using weather from the thermodynamic global warming (TGW) dataset. The same event is replayed for 2058 under hotter future conditions. The resulting modeled outputs characterize spatial patterns of extreme heat and provide a perspective on increases in event intensity, geographic scope, and duration. This approach is not intended to estimate future changes in extreme event frequency that might result from changes in large-scale atmospheric dynamics.

Maps and Layers

Interact with visible map layers using the top-right map pane. All layers can be adjusted for transparency, and colorbar appearance can be adjusted for the temperature map. Boundaries can be overlaid to select layers for further analysis or map export, and overlays can be used to identify areas by demographics, heat vulnerability, or land use info.

Air Temperature: Heat Index: Wet Bulb Globe Temperature:
modeled Fahrenheit air temperature at a 6-foot height a measure of how hot it feels when relative humidity is combined with the air temperature a measure of heat stress in direct sunlight that accounts for temperature, humidity, wind speed, sun angle, and cloud cover.
Map Tools

Click on a tool button above the map to activate it. An enabled tool will be highlighted in green, and the user must click the tool button again to disable it.

Use the buttons below to change the position of tables.

Not sure where to start? Launch the or follow the steps below:

  1. Get oriented. The Page Guide provides a guided overview of the map and tables. The tab contains background information about the data, temperature types, and map controls. Additional instructions, examples, and data references are available from About.
  2. Choose a temperature map. Open Maps tab and select Air Temperature, Heat Index, or Wet Bulb Globe Temperature (WBGT). Toggle the historical, future, or difference maps and adjust transparency to view the base map underneath. A transparency of 20–50% usually preserves heat details while keeping underlying features visible. Colorbar schemes can also be changed.
  3. Add boundaries and overlays. Open Layers tab and use the Boundaries sub-tab to select Census Block Groups, Census Tracts, City/Town boundaries, or Counties. These boundaries define the areas available for selection and table analysis. The Overlays sub-tab includes median temperature, land cover, community characteristics, heat vulnerability, and disadvantaged-community information.
  4. Navigate the map. Use Navigate to pan, Select to add or remove individual boundaries, Box Select to select several boundaries, Center to return to the analysis area, and Clear to remove all selections. The map can also be explored with the address search, zoom buttons, mouse wheel, and stacked or side-by-side layout controls.
  5. Identify map values. Expand Identify from the lower-right corner of the map. Select a visible temperature, overlay, or boundary layer and click Enable Identify before clicking the map. Results may include temperature-cell values, land-cover characteristics, or boundary statistics. Re-click the button or press ESC to disable Identify.
  6. Select areas for analysis. Activate a boundary layer before using Select or Box Select. Click a boundary to add it, click it again to remove it, or drag a box across multiple areas when using Box Select. Selected areas populate the tables adjacent to the map with temperature, climate, land-cover, census, and vulnerability information.
  7. Review and edit the tables. The Selections tab supports custom aliases and colors and allows the project to be saved for a later browser session. Additional tabs summarize hourly temperature, land characteristics, historical and future climate statistics, census populations, and Heat Vulnerability Index data. Sortable columns can help identify the highest- or lowest-ranking areas.
  8. Compare results and export. Compare selected areas by temperature, land cover, population vulnerability, modeled climate statistics, or heat-event frequency. Identify can support cell-level investigation within selected boundaries. Use the Export tab to adjust the final map and download available maps, table images, CSV data, or viewport-based raster outputs.

View examples in About or try one of the following exercises:

  1. Compare block groups in a small area. Find representative school, park, hospital, downtown, and suburban census areas. Compare daytime and nighttime maximums, contrast population vulnerabilities, and study future changes in heat events or temperature to rank areas for vulnerability. This provides an overview of how temperature can change based on land use.
  2. Find the hottest areas and identify risk factors. Use Identify, Box Select, and table removal controls to narrow the selection to the hottest census block groups or tracts. For each area, identify a different high-risk characteristic such as elderly population, land use, HVI indicators, current temperature, or future climate temperature.
  3. Complete a cell-based analysis. Use a temperature or difference map to investigate the largest temperature values or changes. Identify individual cells and compare them with tree cover, impervious cover, and land-cover overlays to explore how landscape characteristics relate to heat exposure.
ID Alias Color Clear
Hourly Temperature
Temperature statistics at 30-meter resolution for the minimum pixel temperature, mean of all temperature values, and maximum pixel temperature for the mapped hour.
Placeholder: mapped-hour temperature details will render here.
Land Characteristics
Average value of land use characteristics from the 2019 National Land Cover Database (NLCD) used in model simulations.
ID Tree Cover % Impervious Cover % Plantable Space %
Climate Statistics
Statistics derived from modeled outputs of the 300-meter 2010-2019 & 2050-2059 simulations, examining differences in heat between decades.
Average Maximum Temperature (June–September)
Table Temperatures:
ID Air Temperature
(Percentile) 		Heat Index
(Percentile) 		Wet Bulb Globe Temperature (WBGT)
(Percentile)
2010s 2050s Change 2010s 2050s Change 2010s 2050s Change
Heat Advisories & Warnings
NYS Heat Events are days when the heat index is above 95°F for two or more hours. National Heat Events are multi-day events with a maximum heat index >100°F and a daily minimum air temperature >75°F. These definitions are for comparing modeled heat events and do not represent official National Weather Service alerts or local alert criteria. View the Heat Trends tool to view more about heat events across the 10-year simulation periods.
ID Annual NYS Heat Event Days
(Percentile) 		Total National Heat Event Days
(Percentile)
2010s 2050s Change 2010s 2050s Change
Census Data (ACS 2022)
Statistics for the population from the 2018-2022 American Community Survey. Statistics chosen are meant to represent populations more vulnerable or exposed to extreme heat.
ID Population % DAC % POC % Low-Income % Disabled % Elderly % No HS (25+)
HVI (non-NYC)
Heat Vulnerability Index from 0–100. This is the percentile of summed scores for heat exposure, sociodemographic, and health outcome factors, used to measure a census tract population's susceptibility to injury or harm during periods of hot weather.
ID Heat Exposure
Percentile
Sociodemographic
Percentile
Health Outcome
Percentile
Heat Vulnerability
Index (HVI)
Expanded HVI Table View
HVI Heat Exposure Indexes
Exposure is measured by the days >85°F heat index and the average maximum heat index (2012–2021) to rank areas by the number of days when negative effects of heat are elevated.
ID Days >85°F
HI Trend 		Avg. Max
HI
HVI Sociodemographic Indexes
The sociodemographic index measures the ability of the population to adapt to instances of high temperature.
ID % Black/AA
% Disabled
% Elderly
Live Alone
% Low Income
% Limited
English
% Outdoor Work
% Uninsured
HVI Health Outcome Indexes
Health outcomes seek to track physiological vulnerability to health outcomes known to be exacerbated by high temperatures. Data is from aggregated subcounty areas. Values are rates per 100,000 people for aggregated subcounty areas. Percentiles are a statewide ranking for subcounty areas in New York State excluding NYC.
ID Asthma ED
Rate
COPD ED
Rate
Heart Attack
ED Rate
Diabetes
HP Rate
Acute Kidney
Failure ED Rate
Key: ED = Emergency Department Visit / HP = Hospitalizations
Create a custom map view and add tables to download. Multiple files will come in ZIP format.
Map Options
Map Area
Map Extents
Map Type
Boundaries
Overlays
Legend
Map Details
Map Layout
Legend Placement
Map Details Placement
Orientation
Map Preview
July 6, 2010 @ 3PM
Extreme Heat Mapper
Map output preview area
Funding for this project provided by the Environmental Protection Fund as administered by the New York State Department of Environmental Conservation
Table Options
Tables
Table Format
Table Color