Data

See data for June 1 to Aug. 31, 2025, for people exposed to temperature anomalies, days at CSI level 2 or higher, and risky heat days in 240 countries, territories, and dependencies (referred to as “countries” in the rest of the report for simplicity) and 940 cities around the world.

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Methodology

This report documents how human-caused climate change influenced temperatures during this three-month period for people worldwide. We analyzed three measures of heat exposure:

1. Climate Shift Index (CSI) values: Developed by Climate Central’s scientists, this metric quantifies the local influence of climate change on daily temperatures. People primarily experience climate change through shifts in daily temperatures and weather patterns where they live. Positive CSI levels (1 to 5) indicate temperatures that are increasingly likely because of climate change. This analysis focuses on the average person’s experience of unusually warm conditions strongly influenced by climate change (CSI level 2 or higher).
2. Risky heat days: Risky heat days are days with temperatures hotter than 90% of those observed in a local area over the 1991-2020 period. Heat-related health risks rise when temperatures climb above this local threshold.
3. Temperature anomalies: Temperature anomalies show how much warmer or cooler conditions were than the 1991-2020 average. Note that the 1991-2020 baseline already includes about 0.9°C (1.6°F) of warming above pre-industrial levels. Temperature anomalies highlight conditions that people would recognize as unusual. We also refer to anomalies as “temperature differences from normal.”

Other data notes

• We calculated the country-level temperature anomalies and days at CSI 2 or higher as per capita averages, which allows us to more accurately represent the average person’s experience of extreme heat.
• For this analysis, the CSI value is based on daily average temperatures and ECMWF ERA5 data.
• See the frequently asked questions for details on computing the Climate Shift Index, including a summary of the multi-model approach described in Gilford et al. (2022).
• Values shown in maps and tables across this website have been rounded for clarity. For exact data values, please download the full dataset above.

A detailed methodology can be found in the full report.

Frequently Asked Questions

• What does "days above the 90th percentile" mean?

These are days with average temperatures that are warmer than 90% of temperatures observed at that site over the 1991-2020 period. These are temperatures that people would consider hot based on their local experience. Heat-related health risks rise when temperatures climb above this local threshold, hence why we refer to them as "risky heat days."



• What's a 30-year normal?

A 30-year normal is the average of weather data — in this case, temperature — over a recent 30-year period (the current standard one is 1991–2020). It’s used as a baseline to compare current conditions and identify changes and trends in the climate. It's a long enough period to smooth out natural year-to-year fluctuations.



• What's a per capita average?

A per capita average for the number of hot days tells us how many days the average person experienced. Instead of counting days in each place, it adds up all the hot days people lived through in a certain timeframe, and divides by the number of people. It's a population-weighted average, meaning the math gives more weight to places with more people. Instead of treating every location equally, it focuses on where people actually live. For example, if one city has 1 million people and another has 10,000, the bigger city’s temperature matters more on average — because far more people experience it. You'll see this in our reports as "the average person in the U.S. experienced x days". We take a similar approach to calculate a per capita average for days at or above CSI level 2.



• Do you provide the value of the temperature percentile for states and countries? For instance, what the 90th percentile temperature actually is in a specific state or country?

We do not. This is because we use a locally determined threshold for each location in the country rather than a single threshold countrywide. Because the climate varies across the country, it's more appropriate to use different thresholds for different locations rather than a single national temperature threshold.



• How did you choose to provide these variables?

The main data points in this analysis were selected to show (a) the strong influence of climate change on daily temperatures (days of temperatures reaching Climate Shift Index level 2 or higher) and (b) the extremely hot days people experience when heat-related health risks rise (risky heat days, or days of temperatures above the 90th percentile*).



• Why are some territories not included in the data for the country they belong to?

Our analysis is based on climatology. Some territories have distinct climate characteristics that align more closely with nearby regions than with the country they’re affiliated with. Grouping them by physical location ensures the data better represents local environmental conditions. This is true for territories like Puerto Rico, and French territories in the Caribbean, for instance.

• Does your analysis include climate change impacts in Antarctica?

No. While Antarctica is shown on our figures in gray, that shading does not represent data. Information from Antarctica was not part of the analysis.

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