The Heat Event Characteristics tab summarizes four heat event types across the 10-year historical simulation and 10-year 2050s replay. The thresholds use heat index, which combines air temperature and humidity to estimate how hot conditions feel to the human body:

Below the Intensity/Duration/Frequency summary, the tool shows heat events by year. By default, the graph displays the maximum heat index reached by any event in the selected timeframe. The controls can switch to average heat index, or to total and average duration and frequency metrics.

Duration shows how much longer heat events become in the 2050s replay. Increases can come from the same historical event lasting longer, or from events that were not extreme in the historical simulation crossing advisory or warning thresholds when replayed under the hotter climate.

Frequency shows how many additional events cross a heat threshold. In some years, Niagara Falls has up to 10 times as many events in the 2050s replay; years with no historical events can also gain multiple heat event days.

Clicking any year shows the monthly breakdown. In this example, 2016 is selected because it has the greatest number of historical events.

The daily table shows that:

1. The historical heat wave had 8 hours above 95°F heat index in Niagara Falls, affecting 20 of the city’s 58 block groups. The highest heat index across any block group was 96.5°F, indicating that roughly half of the city experienced high afternoon heat-index values.

The 2050s replay varies across the city:

1. 30 block groups experienced a multi-day National Heat Advisory, with a maximum heat index of 110.8°F. Although this value is above the National Heat Warning threshold, the Warning requires every day in the event to exceed 105°F heat index; at least one day in this grouping was above 100°F but below 105°F.
2. 24 block groups experienced a NYS Heat Advisory, defined as 2 or more hours above 95°F heat index. The highest labeled heat-index value was 105.9°F, meaning at least one block group briefly exceeded the NYS Heat Warning threshold but did not remain above it long enough to qualify as a Warning.
3. The remaining four block groups were under a NYS Heat Warning, defined as 2 or more hours above 105°F heat index, with event duration measured from the period above 95°F heat index. These block groups experienced at least 2 hours above 105°F and sustained heat-index exposure above 95°F from 9 AM to 9 PM.

These results show three spatial heat patterns. The urban core reaches heat-index values up to 110.8°F and has limited nighttime cooling between two high-heat days. A transition zone also reaches high daytime heat index but can cool below 75°F overnight, providing some physiological relief. The remaining block groups still experience moderately high daytime heat, but at lower intensity than the 34 block groups in the higher-risk zones.

This section shows how the Heat Event Characteristics tab can move from a broad decade-level comparison into a specific event-day interpretation. For Niagara Falls, the August 10 comparison shows that the 2050s replay is not just hotter; it also changes the type, duration, and spatial extent of heat risk. A historical afternoon heat event affecting part of the city becomes a future event where all block groups meet some heat event threshold, with the urban core differentiated as experiencing the highest heat index values and limited nighttime cooling. This aids in understanding whether future heat risk is driven by higher intensity, longer duration, more frequent events, broader exposure across the city, or a combination of all four.

The tool tracks air temperature, heat index, and wet bulb globe temperature (WBGT). WBGT combines air temperature, humidity, wind, and solar radiation to estimate heat stress. For each temperature type, the tool summarizes the daily maximum using three statistics:

1. Minimum: the daily maximum temperature reached at the coolest pixel within the selected area. This often represents high tree cover and low impervious cover, and helps identify whether any outdoor relief from high temperatures exists within the area.
2. Mean: the area-averaged value across all block groups for the maximum-temperature hour. This is best for understanding average heat exposure across the selected area.
3. Maximum: the daily maximum temperature reached at the hottest pixel within the selected area. This often represents low tree cover and high impervious cover, and helps identify the highest potential heat exposure in the area.

The default graph shows a notable increase between the historical simulation and the 2050s replay. It counts days when the citywide average heat index is above 85°F at the hottest hour of the day, including forested areas within the city boundary.

The threshold graphs show the following patterns:

To analyze seasonal timing, move year by year to identify early-season (May) and late-season (September) high temperatures, which can be important because people may be less acclimated at the beginning and end of the warm season.

The Heat Event Characteristics tab summarizes four event types across the 10-year historical simulation and 10-year 2050s replay. The thresholds use heat index, which combines air temperature and humidity to estimate how hot conditions feel to the human body:

The Intensity/Duration/Frequency summary card focuses on three metrics:

Below the summary card, the tool shows heat events by year. By default, the graph displays the maximum heat index from any event in the selected timeframe. The top controls can change the metric, metric type (average or sum), and graph view.

For this use case, switch to Difference view. This replaces the side-by-side 2010s/2050s view with one 10-year graph showing the difference between decades, which is easier to read when many areas are selected. To compare absolute values, such as the location with the highest heat index, switch back to Values view. Use this section to examine intensity, duration, and frequency in more detail.

Maximum intensity shows where the highest heat-index values increase the most, based on the highest heat index from any event in the timeframe. Newburgh, Albany, Syracuse, Rochester, and Crown Heights in New York City each have high outliers in at least one year. Differences are not shown for selections that did not have historical data.

Average intensity shows how much the average event’s maximum heat index increased. Areas with many historical heat events often show consistently high increases because they have a larger sample of events that intensify in the 2050s replay, plus new events that did not meet a heat threshold historically. New York City and Yonkers are examples of areas with positive values in all years.

This statistic can be negative when the historical sample size is small. For example, Binghamton rarely reached 95°F heat index historically, but when it did, some events were multiple degrees hotter. In July 2019, Binghamton had two events with an average maximum heat index above 105°F. In the 2050s replay, the same month has fourteen events.

Use the Values view and Select All | Select None to isolate Binghamton. This shows how the average intensity can decline even when heat risk increases: the frequency rises sharply because many additional, somewhat less intense events enter the dataset.

Total duration increases substantially across the selected locations. Outliers appear in Plattsburgh, Newburgh, Brookhaven, and New York City. In Difference view, large outliers such as Plattsburgh should be inspected before assuming a simple increase in heat event severity.

The large 2053 Plattsburgh duration increase is largely traced to July. In July, Plattsburgh increases from five single-day NYS Heat events in 2013 to twelve events in 2053.

Average duration shows how the typical event length changes. This statistic can be exaggerated in areas with few historical events, especially when those events were multi-day events or long single-day events. Newburgh shows a negative average difference in total hours for 2051 and 2059; after filtering to single-day events, most areas show an increase in average hours above 95°F heat index.

This example shows how to compare many locations without relying on a single metric. Statewide comparisons identify where intensity, duration, and frequency increase, but the details matter: New York City and Yonkers may have high baseline heat exposure and high absolute values, while places such as Buffalo, Rochester, Brookhaven, and Plattsburgh show larger percent increases in future heat event frequency or duration. The example also shows why large changes should be inspected carefully: a high total-duration increase may reflect overlapping event types within a tract, while a negative average-intensity difference may occur when many new, lower-intensity events are added to a small historical sample. The Difference view, event filters, year/month/day drilldowns, and hourly graphs help separate real risk patterns.

The threshold graphs can be viewed for air temperature, heat index, and wet bulb globe temperature (WBGT). WBGT combines air temperature, humidity, wind, and solar radiation to estimate heat stress. For each temperature type, the tool summarizes the daily maximum using three statistics:

1. Minimum: the daily maximum temperature reached at the coolest pixel within the selected area. This helps identify whether any outdoor heat relief exists in the area.
2. Mean: the area-averaged value across the selected tract for the maximum-temperature hour. This is best for understanding average exposure across the tract.
3. Maximum: the daily maximum temperature reached at the hottest pixel in the selected area. This is best for identifying the highest potential heat exposure.

The tool loads with 85°F mean heat index by default, which provides a broad overview of heat occurrences in each area. Adjusting the statistic reveals different patterns:

Changing the temperature type and threshold can reveal additional high- and low-temperature patterns. Heat index and WBGT also include Human Health Considerations that help interpret the danger of different thresholds. Examples include:

The same comparison can be repeated across temperature types and statistics to compare the hottest, coolest, and area-average conditions within each tract.

Because this example focuses on WBGT, open the Temperature Thresholds tab and select Wet Bulb Globe Temperature. Brooklyn is in Region 2 in the Human Health Considerations graphic, so use the following WBGT flag categories:

The threshold values in the tool increase in 5°F increments, such as 75°F, 80°F, and 85°F. These values do not align exactly with the flag thresholds, but they provide a practical way to assess the level of precaution needed. After switching the temperature type to WBGT, the statistics default to mean values above 85°F.

The mean temperature statistic represents the average temperature across the full area for the maximum heat hour. The gray bar represents the East New York neighborhood selection, which averages temperatures in proportion to total area across all encompassed tracts. The highest-ranked dark-red tract has the most historical and 2050s days when the entire tract has WBGT above 85°F.

As we increase the temperature threshold, it can become easier to separate out the hottest years and areas with the most extreme heat.

Increasing the maximum WBGT threshold to 90°F makes the #1 tract more similar to other high-WBGT tracts. Although tracts #3 and #7 can have more Red Flag days, tract #1 has the highest incidence of Extreme, or Black Flag, WBGT. This indicates that tract #1 is most vulnerable to the most extreme WBGT values, while parts of other tracts can equal or exceed it on Red Flag days.

Minimum WBGT shows the coolest point in each area. This helps identify whether an area has outdoor heat relief, often associated with high tree canopy. Because the East New York neighborhood contains all selected census tracts, its minimum value will match or be lower than the lowest individual tract.

Tracts ranked #4-6 (orange/yellow) have notably higher minimum WBGT than tract #1 in historical and 2050s years. Cross-comparing minimum, mean, and maximum values shows that tract #6 has similar counts across all three statistics for most years, indicating highly uniform WBGT stress across the tract. Several lower-ranked tracts, such as #10, also have minimum values equal to or higher than the top three WBGT tracts.

These threshold results show that tract #1 ranks highest mainly because of its high mean WBGT and its highest maximum WBGT above 90°F, or Black Flag days. Tracts #2 and #3 can contain hotspots that are hotter than tract #1 on Red Flag days, but their mean values are lower because higher tree cover creates lower minimum WBGT within the tracts. Tracts #4-6 show more uniform heat stress: when one part of the tract is above 90°F WBGT, much of the tract is likely above that threshold as well.

Lower-ranked tracts have lower mean WBGT, but can still experience maximums or minimums that are similar to or higher than the #1 tract. Use the Hourly Temperature Graphs tab to explore these WBGT patterns over time. To view spatial maps of Wet Bulb Globe Temperature, use the Extreme Heat Mapper.

Hourly temperature graphs work best with one or only a few selections shown. Local events represent periods when all selected tracts have a heat event, and event length is determined by the longest overlapping heat event. Sorting by Max Heat Index (highest to lowest) places the most extreme events at the top. Among the top six events, the fifth-highest event has the highest future WBGT, surpassing 99°F, even though it ranks fifth by future maximum heat index at 122.92°F.

For the remaining graphs, four selections are isolated to study the area temperatures: the #1 ranked WBGT tract (dark red), the #5 WBGT tract (yellow) with very close minimum, mean, and maximum threshold counts, the lowest rank WBGT tract (purple), and the full East New York neighborhood (gray).