Report•July 2, 2024
Monthly Attribution Overview - June 2024
An analysis of how climate change boosted United States temperatures in June 2024
Using Climate Central’s Climate Shift Index (CSI) tool to measure the impact of climate change on daily temperatures across the United States, as well as NOAA’s Applied Climate Information System (ACIS) to find daily temperature information, we have compiled a high-level overview of how climate change has affected temperature trends in June across the United States. This will be a monthly release, put out early in the days following the end of a month. In months with exceptional heat, such as this one, an additional section, titled “Special alert: Exceptional Heat” will cover more in depth statistics for the month.
1. High level findings
Temperature anomalies were elevated across the country (Figure 1) this June
Temperatures were exceptionally high in the Southwest where a number of cities experienced average temperature anomalies greater than 5°F. 179 out of 191 ACIS stations analyzed had positive temperature anomalies, indicating that these cities experienced a warmer June than usual.
Out of 191 ACIS stations, 12 experienced their hottest monthly temperatures on record. 45 experienced heat that ranked in their top 5 hottest Junes on record, while another 36 experienced heat that ranked in their top 6-10.
The average person in the Southwest experienced 4.2 more days above 90 degrees as a result of climate change this June.
Climate Shift Index (CSI) signal was elevated in the southwest and the Gulf Coast, with many cities in these regions experiencing more than 14 days with CSI values at or above 2 (Figure 2).
Elevated and sustained CSI signals were not only restricted to these locations. 168 out of 191 ACIS stations analyzed experienced at least one day with a CSI value greater than or equal to 2, indicating that temperatures on at least one day were made at least twice as likely due to climate change. 34 cities had 14 or more days with CSI values of 2 or more.
Figure 1. Threaded ACIS temperature anomalies for June 2024 relative to the 1991-2020 standard normal period. Analysis based on ACIS data.
Figure 2. Days with a CSI of 2 or higher for June 2024 for ACIS threaded stations. Analysis based on ERA5 data (June 1-27) and GFS data (June 28-30).
2. Special alert: Exceptional heat in June 2024
Analysis for this section uses three sets of data: city-specific ACIS station data (available at https://scacis.rcc-acis.org/), gridded ERA5 and GFS temperature data aggregated at state and country levels, and CSI values based on ERA5 and GFS temperature data.
2.1 June 2024 was historically hot
Temperatures were among the hottest on record for June: out of 191 ACIS stations, 12 experienced their hottest Junes on record. 45 experienced heat that ranked in their top 5 hottest Junes on record, while another 36 experienced heat that ranked in their top 6-10.
The average U.S. resident experienced temperatures at least 1.0°F hotter than typical Junes, while specific hot spots across the country stood out: In the Southwest, people in Nevada experienced a June that was 5.7°F hotter than normal (In Colorado and Utah, this value was 5.0°F, Table 1). Out of 10 ACIS stations in the Southwest (those stations in Nevada, Arizona, Colorado, Utah, and New Mexico), 7 experienced monthly temperature anomalies greater than 5°F, this being the hottest ever June for 4 stations in the region, and in the top 10 for 9 stations.
State | Average Temperature Anomaly (average person,°F ) | Increase in Likelihood Of June Temperatures Occurring As a Result of climate change (average person) | Number of Days with CSI Values Greater than or Equal to 3 (average person) | Number of days above 80°F added by climate change (average person) | Number of days above 90°F added by climate change (average person) |
|---|---|---|---|---|---|
Nevada | 5.7 | 8.2 | 13 | 4 | 7 |
Utah | 5.0 | 5.4 | 11 | 3 | 0 |
Colorado | 5.0 | 4.2 | 8 | 1 | 0 |
Wyoming | 3.4 | 1.7 | 1 | 0 | 0 |
Arizona | 3.3 | 7.1 | 10 | 3 | 9 |
New Hampshire | 3.1 | 2.0 | 0 | 1 | 0 |
New Jersey | 2.7 | 3.4 | 2 | 4 | 0 |
New Mexico | 2.7 | 6.3 | 12 | 4 | 1 |
Idaho | 2.6 | 1.5 | 0 | 1 | 0 |
Massachusetts | 2.6 | 2.3 | 0 | 1 | 0 |
Table 1. Top 10 state stations with the highest June 2024 Temperature Anomalies.
2.2 Climate change drove June temperatures
This extreme heat was driven by climate change. On average, the June temperatures that a person in the U.S. experienced were 2.3 times more likely due to climate change. However, these numbers increase drastically when focusing on specific regions: the average person in Nevada experienced June temperatures that were made 8.2 times more likely. While over the entire Southwest, the average person experienced temperatures that were made 6.0 times more likely. Every state in the Southwest experienced some of the most extreme June temperature anomalies and associated climate-driven heat on record, ranking in the top 10 for both of these metrics (Table 1, 2).
The average U.S. resident experienced an additional 3.6 days above 80°F this June due to climate change. In the Southwest, this value was 2.5 days, while there were 4.2 additional days above 90°F for the average person, due to climate change.
State | Increase in likelihood of June temperatures occurring as a result of climate change (average person) | Average temperature anomaly (average person,°F ) | Number of days with CSI values greater than or equal to 3 (average person) | Number of days above 80°F added by climate change (average person) | Number of days above 90°F added by climate change (average person) |
|---|---|---|---|---|---|
Nevada | 8.2 | 5.7 | 13 | 4 | 7 |
Arizona | 7.1 | 3.3 | 10 | 3 | 9 |
New Mexico | 6.3 | 2.7 | 12 | 4 | 1 |
Utah | 5.4 | 5.0 | 11 | 3 | 0 |
Florida | 5.2 | 1.3 | 12 | 11 | 0 |
Hawaii | 4.6 | 0.3 | 16 | 0 | 0 |
Colorado | 4.2 | 5.0 | 8 | 1 | 0 |
Delaware | 3.4 | 2.4 | 4 | 4 | 0 |
New Jersey | 3.4 | 2.7 | 2 | 4 | 0 |
New York | 3.3 | 2.4 | 2 | 2 | 0 |
Table 2. Top 10 States stations with the highest influence of climate change influence on June temperatures.
2.3 Climate change-influenced extreme heat will only get worse
Per a 2022 Climate Central analysis projecting how ACIS stations are expected to warm in the next 80 years, summers in cities across the country are expected to get much hotter. In the southwest, where heat has been exceptionally notable this June, temperatures are expected to soar in the coming years. By 2100, summers in Las Vegas are expected to feel like summers in Kuwait City today (an 8°F increase on average, Figure 4). Salt Lake City is expected to feel like Los Mochis, Mexico (an 8.6°F increase). Denver is expected to feel like Monclova, Mexico (an 8.7°F increase), while Phoenix is expected to feel like Al Mubarraz, Saudi Arabia(a 7.2° F increase). View the release to explore other cities and find equivalent figures to Figure 3.
Figure 3. Projected temperature increases for Las Vegas, Arizona, drawn from our Shifting Cities Analysis.
3. Temperature anomaly station analysis
179 out of 191 ACIS stations analyzed had positive temperature anomalies, indicating that these cities experienced a warmer June than usual. The Southwest in particular stood out as an exceptionally warm region.
11 cities had a monthly temperature anomaly greater than 5°F. 7 out of 10 stations in the Southwest experienced monthly temperature anomalies greater than 5°F.
Of the cities examined, seven out of the ten most anomalously warm were in the Southwest (Las Vegas, Reno, Salt Lake City, Flagstaff, Phoenix, Grand Junction, and Denver).
The average temperature anomaly across all stations was 2.43°F. In the southwest, this value rose to 5.22°F.
187 out of 191 ACIS stations analyzed had positive temperature trends for June, indicating that these cities have been on average warming since 1970.
Reno, NV had an exceptionally hot June (with an average daily temperature anomaly of 6.58°F making it the most anomalously hot ACIS station), and the fastest warming ACIS station in June, warming 10.1°F since 1970.
The second fastest warming ACIS station was El Paso, TX. The average June temperature in El Paso has warmed by 7.1 degrees since 1970. This June, it was 5.45°F hotter than normal.
City | State | Temperature Anomaly (°F) | Average Temperature (°F) | Warming Since 1970 (°F) |
|---|---|---|---|---|
Las Vegas | NV | 6.99 | 94.58 | 6.3 |
Reno | NV | 6.58 | 75.78 | 10.1 |
Salt Lake City | UT | 5.97 | 77.57 | 5.3 |
Flagstaff | AZ | 5.93 | 66.73 | 2.8 |
Phoenix | AZ | 5.62 | 97.02 | 5.3 |
Grand Junction | CO | 5.58 | 78.58 | 2.1 |
Denver | CO | 5.56 | 73.77 | 2.5 |
El Paso | TX | 5.45 | 89.28 | 7.1 |
Hartford | CT | 5.21 | 74.07 | 1.4 |
Springfield | MA | 5.21 | 74.07 | 1.4 |
Table 3. Top 10 ACIS stations with the highest June 2024 Temperature Anomaly.
4. CSI station analysis
168 out of 191 ACIS stations analyzed had at least one day with a CSI value greater than or equal to 2, indicating that temperatures on at least one day were made at least twice as likely due to climate change in those cities.
Of the cities examined, San Juan, Puerto Rico had the highest number of days at or above a CSI of 2, with 30. Victoria, Texas, had the second highest, with 26.
87 out of 191 ACIS stations analyzed had at least 7 days with a CSI value greater than or equal to 2, with Texas having 12 such stations, and Florida having 10.
In San Juan, temperatures every day in June reached a CSI of 5, meaning that temperatures were made at least 5 times more likely due to climate change.
The Climate Shift Index (CSI) |
|---|
Humans have caused global average temperatures to increase by 1.1°C (2°F) since 1850. But people do not experience global average temperatures. Instead, we mainly experience climate change through shifts in the daily temperatures and weather patterns where we live.
Climate Central’s Climate Shift Index (CSI) system quantifies the local influence of climate change on daily temperatures around the world. The CSI quantifies how much human-caused climate change has shifted the odds of daily temperatures that people experience locally. The CSI is grounded in peer-reviewed attribution science and was launched by Climate Central in 2022. The data is accessible via our free map tool. The CSI scale is centered on zero. A CSI level of zero means that there is no detectable influence of human-caused climate change. In other words, that day’s temperature is equally likely in both the modern climate and one without global warming. Positive CSI levels 1 to 5 indicate conditions that are increasingly likely in today’s climate. A CSI level of 1 means that climate change is detectable (technically, the temperature is at least 1.5x more likely). CSI levels 2 and higher correspond with the multipliers (2 = at least 2x more likely, 3 = at least 3x more likely, etc.). The CSI scale is currently capped at level 5 which means that a CSI of 5 includes higher values and thus should be read as at least 5. CSI level 5 events would be very difficult to encounter in a world without climate change—not impossible, but extremely unlikely. The CSI can also be applied to temperatures that are unusually cool. For instance, a CSI level -2 means that the temperature in question is two times less likely (equivalently 1/2 as likely) due to human-caused climate change. Climate Central’s Climate Shift Index map tool shows which parts of the world are experiencing high CSI levels, every day. Explore the global CSI map for today, tomorrow, and any day this past year. |
METHODS
Calculating the Climate Shift Index
All Climate Shift Index (CSI) levels reported in this brief are based on daily average temperatures and ERA5 data from June 1 to June 30, 2024. 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).
City Analysis
We analyzed 191 Applied Climate Information System (ACIS) stations associated with U.S. cities. For each city, we found the CSI time series from the nearest 0.25° grid cell. We the number of days at CSI levels 2, 3, 4, and 5. We used ACIS data to find the average monthly temperatures, temperature anomalies, and precipitation information, and to derive average monthly warming trends for each city.
State Analysis
For each national or State statistic, we used population density maps to find the population-weighted average over the desired region.
Calculating Days Above 80 or 90 Degrees Added by Climate Change
To calculate the number of days with temperatures above 80 (or 90) degrees added by climate change, we first found the days that were greater than 80 (or 90) degrees in June according to ERA5 (June 1-27) and GFS (June 28-30) nationally and state by state.
We then calculated those days that were below 80 (or 90) degrees in the counterfactual climate (the climate in a world where climate change hasn’t occurred): First, we calculated the likelihood as a percentile of daily average temperatures occurring from May 15, 2023 to May 15, 2024 in the modern climate. Next, we applied that percentile to the counterfactual climate to compute what the equivalent temperature would have been in the counterfactual climate. We found those days where counterfactual temperatures were below 80 (or 90) degrees.
We then counted those days where both observed temperatures were above 80 (or 90) degrees and the associated counterfactual temperatures were below 80 (or 90) degrees, to find the number of days at or above 80 (or 90) degrees added by climate change.
Calculating probability ratios for triggered heat events
To calculate the increase in likelihood of June temperatures occurring as a result of climate change (also called the Probability Ratio, or PR, of temperatures), we found the daily climate factors (a value derived to generate the Climate Shift Index that is a measurement of the increase in likelihood due to climate change of a temperature occurring) for each ERA5 or GFS grid cell for June. To find the climate factor of the month as a whole, we found the variance associated with the daily temperatures in each location for June from 1991-2020. We then calculated the yearly means for those same daily temperatures from 1991-2020, before calculating the variance of these yearly means. By multiplying the ratio of the two (the daily temperature variance to the yearly temperature variance) by the mean climate factor, we calculated variance-scaled climate factors. This translates a sequence of changes in likelihoods to a single comprehensive value. Finally, we converted climate factors to Probability Ratios.
Major funding provided by the Bezos Earth Fund and The Schmidt Family Foundation.