The average temperature in the contiguous United States reached 55.5 degrees Fahrenheit (13 degrees Celsius) in 2024, approximately 3.5 degrees Fahrenheit higher than the 20th-century average. These levels represented a record since measurements started in ****. Monthly average temperatures in the U.S. were also indicative of this trend. Temperatures and emissions are on the rise The rise in temperatures since 1975 is similar to the increase in carbon dioxide emissions in the U.S. Although CO₂ emissions in recent years were lower than when they peaked in 2007, they were still generally higher than levels recorded before 1990. Carbon dioxide is a greenhouse gas and is the main driver of climate change. Extreme weather Scientists worldwide have found links between the rise in temperatures and changing weather patterns. Extreme weather in the U.S. has resulted in natural disasters such as hurricanes and extreme heat waves becoming more likely. Economic damage caused by extreme temperatures in the U.S. has amounted to hundreds of billions of U.S. dollars over the past few decades.

Temperature in the United States increased to 10.73 celsius in 2024 from 10.25 celsius in 2023. This dataset includes a chart with historical data for the United States Average Temperature.

The monthly average temperature in the United States between 2020 and 2025 shows distinct seasonal variation, following similar patterns. For instance, in August 2025, the average temperature across the North American country stood at 22.98 degrees Celsius. Rising temperatures Globally, 2016, 2019, 2021 and 2024 were some of the warmest years ever recorded since 1880. Overall, there has been a dramatic increase in the annual temperature since 1895. Within the U.S. annual temperatures show a great deal of variation depending on region. For instance, Florida tends to record the highest maximum temperatures across the North American country, while Wyoming recorded the lowest minimum average temperature in recent years. Carbon dioxide emissions Carbon dioxide is a known driver of climate change, which impacts average temperatures. Global historical carbon dioxide emissions from fossil fuels have been on the rise since the industrial revolution. In recent years, carbon dioxide emissions from fossil fuel combustion and industrial processes reached over 37 billion metric tons. Among all countries globally, China was the largest emitter of carbon dioxide in 2023.

The average temperature in December 2024 was 38.25 degrees Fahrenheit in the United States, the fourth-largest country in the world. The country has extremely diverse climates across its expansive landmass. Temperatures in the United States On the continental U.S., the southern regions face warm to extremely hot temperatures all year round, the Pacific Northwest tends to deal with rainy weather, the Mid-Atlantic sees all four seasons, and New England experiences the coldest winters in the country. The North American country has experienced an increase in the daily minimum temperatures since 1970. Consequently, the average annual temperature in the United States has seen a spike in recent years. Climate Change The entire world has seen changes in its average temperature as a result of climate change. Climate change occurs due to increased levels of greenhouse gases which act to trap heat in the atmosphere, preventing it from leaving the Earth. Greenhouse gases are emitted from various sectors but most prominently from burning fossil fuels. Climate change has significantly affected the average temperature across countries worldwide. In the United States, an increasing number of people have stated that they have personally experienced the effects of climate change. Not only are there environmental consequences due to climate change, but also economic ones. In 2022, for instance, extreme temperatures in the United States caused over 5.5 million U.S. dollars in economic damage. These economic ramifications occur for several reasons, which include higher temperatures, changes in regional precipitation, and rising sea levels.

Temperature Over Time by State (Starts: 1895)

State and County Temperature Changes

By Environmental Data [source]

About this dataset

Do you want to know how rising temperatures are changing the contiguous United States? The Washington Post has used National Oceanic and Atmospheric Administration's Climate Divisional Database (nClimDiv) and Gridded 5km GHCN-Daily Temperature and Precipitation Dataset (nClimGrid) data sets to help analyze warming temperatures in all of the Lower 48 states from 1895-2019. To provide this analysis, we calculated annual mean temperature trends in each state and county in the Lower 48 states. Our results can be found within several datasets now available on this repository.

We are offering: Annual average temperatures for counties and states, temperature change estimates for each of the Lower 48-states, temperature change estimates for counties in the contiguous U.S., county temperature change data joined to a shapefile in GeoJSON format, gridded temperature change data for the contiguous U.S. in GeoTiff format - all contained with our dataset! We invite those curious about climate change to explore these data sets based on our analysis over multiple stories published by The Washington Post such as Extreme climate change has arrived in America, Fires, floods and free parking: California’s unending fight against climate change, In fast-warming Minnesota, scientists are trying to plant the forests of the future, This giant climate hot spot is robbing West of its water ,and more!

By accessing our dataset containing columns such as fips code, year range from 1895-2019, three season temperatures (Fall/Spring/Summer/Winter), max warming season temps plus temp recorded total yearly - you can become an active citizen scientist! If publishing a story or graphic work based off this data set please credit The Washington Post with a link back to this repository while sending us an email so that we can track its usage as well - 2cdatawashpost.com.

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How to use the dataset

The main files provided by this dataset are climdiv_state_year, climdiv_county_year, model_state, model_county , climdiv_national_year ,and model county .geojson . Each file contains different information capturing climate change across different geographies of the United States over time spans from 1895.

Research Ideas

• Investigating and mapping the temperatures for all US states over the past 120 years, to observe long-term changes in temperature patterns.
• Examining regional biases in warming trends across different US counties and states to help inform resource allocation decisions for climate change mitigation and adaption initiatives.
• Utilizing the ClimDiv National Dataset to understand continental-level average annual temperature changes, allowing comparison of global average temperatures with US averages over a long period of time

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: climdiv_state_year.csv | Column name | Description | |:--------------|:------------------------------------------------------------------------| | fips | Federal Information Processing Standard code for each county. (Integer) | | year | Year of the temperature data. (Integer) | | tempc | Temperature change from the previous year. (Float) |

File: climdiv_county_year.csv | Column name | Description | |:--------------|:------------------------------------------------------------------------| | fips | Federal Information Processing Standard code for each county. (Integer) | | year | Year of the temperature data. (Integer) | | tempc | Temperature change from the previous year. (Float) |

File: model_state.csv | Column name | Description | |:------------------...

In 2024, the average annual temperature in the United States was ***** degrees Celsius, the warmest year recorded in the period in consideration. In 1895, this figure stood at ***** degrees Celsius. Recent years have been some of the warmest years recorded in the country.

This dataset provides weekly average temperature data for all U.S. counties from 2013 to 2023. Each row in the dataset represents a specific county, and the columns correspond to the weekly average temperatures over the ten-year period. The dataset is structured to facilitate time series analysis, climate trend studies, and machine learning applications related to environmental and climate change research.

Key Features: - County-Level Data: Temperature data is provided for each county in the United States, allowing for detailed, localized climate analysis. - Weekly Time Intervals: The data is aggregated on a weekly basis, offering a finer temporal resolution that captures seasonal and short-term temperature fluctuations.

• 10-Year Span: Covers a significant period from 2013 to 2023, enabling long-term trend analysis and comparison across different periods.

• Temperature Units: All temperature values are presented in Kelvin (K).

Potential Uses:

• Climate Research: Investigate climate change impacts at the county level, identify trends, and assess regional climate variability. Geospatial Analysis: Integrate with other spatial datasets for comprehensive environmental and geographical studies.

• Machine Learning: Suitable for training models on temporal climate data, predictive analytics, and anomaly detection.

• Public Policy and Planning: Useful for policymakers to study historical climate trends and support decision-making in areas such as agriculture, disaster management, and urban planning.

This dataset is ideal for researchers, data scientists, and analysts interested in exploring U.S. climate data at a granular level.

This indicator shows how the average air temperature from 2000 to 2023 has differed from the long-term average (1895 - 2023). To provide more detailed information, each state has been divided into climate divisions, which are zones that share similar climate features. For more information: https://www.epa.gov/climate-indicators.

Q: What was the average temperature for the month? A: Colors show the average monthly temperature across the contiguous United States. White and very light areas had average temperatures near 50°F. Blue areas on the map were cooler than 50°F; the darker the blue, the cooler the average temperature. Orange to red areas were warmer than 50°F; the darker the shade, the warmer the monthly average temperature. Q: Where do these measurements come from? A: Daily temperature readings come from weather stations in the Global Historical Climatology Network (GHCN-D). Volunteer observers or automated instruments collect the highest and lowest temperature of the day at each station over the entire month, and submit them to the National Centers for Environmental Information (NCEI). After scientists check the quality of the data to omit any systematic errors, they calculate each station’s monthly average of daily mean temperatures, then plot it on a 5x5 km gridded map. To fill in the grid at locations without stations, a computer program interpolates (or estimates) values, accounting for the distribution of stations and various physical relationships, such as the way temperature changes with elevation. The resulting product is the NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid). Q: What do the colors mean? A: Shades of blue show areas that had monthly average temperatures below 50°F. The darker the shade of blue, the lower the average temperature. Areas shown in shades of orange and red had average temperatures above 50°F. The darker the shade of orange or red, the higher the average temperature. White or very light colors show areas where the average temperature was near 50°F. Q: Why do these data matter? A: The 5x5km NClimGrid data allow scientists to report on recent temperature conditions and track long-term trends at a variety of spatial scales. The gridded cells are used to create statewide, regional and national snapshots of climate conditions. Energy companies use this information to estimate demand for heating and air conditioning. Agricultural businesses also use these data to optimize timing of planting, harvesting, and putting livestock to pasture. Q: How did you produce these snapshots? A: Data Snapshots are derivatives of existing data products; to meet the needs of a broad audience, we present the source data in a simplified visual style. This set of snapshots is based on NClimGrid climate data produced by and available from the National Centers for Environmental Information (NCEI). To produce our images, we invoke a set of scripts that access the source data and represent them according to our selected color ramps on our base maps. Additional information The data used in these snapshots can be downloaded from different places and in different formats. We used these specific data sources: NClimGrid Average Temperature References NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) NOAA Monthly U.S. Climate Divisional Database (NClimDiv) Improved Historical Temperature and Precipitation Time Series for U.S. Climate Divisions) NCEI Monthly National Analysis) Climate at a Glance - Data Information) NCEI Climate Monitoring - All Products Source: https://www.climate.gov/maps-data/data-snapshots/data-source/temperature-us-monthly-averageThis upload includes two additional files:* Temperature - US Monthly Average _NOAA Climate.gov.pdf is a screenshot of the main Climate.gov site for these snapshots.* Cimate_gov_ Data Snapshots.pdf is a screenshot of the data download page for the full-resolution files.

This statistic shows cities in the United States with the highest average annual temperatures. Data is based on recordings from 1981 to 2010. In San Antonio, Texas the average temperature is 80.7 degrees Fahrenheit. Some cities that have the hottest maximum summer temperatures will not be included in this list due to their extreme temperature variance.

The NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature, minimum temperature, average temperature and precipitation. Each file provides monthly values in a 5x5 lat/lon grid for the Continental United States. Data is available from 1895 to the present. In March 2015, new Alaska data was included in the nClimDiv dataset. The Alaska nClimDiv data were created and updated using similar methodology as that for the CONUS. It includes maximum temperature, minimum temperature, average temperature and precipitation. In January 2025, the National Centers for Environmental Information (NCEI) began summarizing the State of the Climate for Hawaii. This was made possible through a collaboration between NCEI and the University of Hawaii/Hawaii Climate Data Portal and completes a long-standing gap in NCEI's ability to characterize the State of the Climate for all 50 states. NCEI maintains monthly statewide, divisional, and gridded average temperature, maximum temperatures (highs), minimum temperature (lows) and precipitation data for Hawaii over the period 1991-2025.

The National Forest Climate Change Maps project was developed to meet the need of National Forest managers for information on projected climate changes at a scale relevant to decision making processes, including Forest Plans. The maps use state-of-the-art science and are available for every National Forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation and air temperature, including both Alaskan and lower 48 datasets. Data from the lower 48 were downloaded from here: https://www.fs.usda.gov/rm/boise/AWAE/projects/national-forest-climate-change-maps.html, and Alaskan data came from here: https://www.snap.uaf.edu/tools/data-downloads. Historical data are compared with RCP 8.5 projections from the 2080s.A Raster Function Template is available in this service that will classify the data as originally intended by OSC. The RFT currently works in AGOL but not in ArcGIS Pro.

This metadata record describes the 30-year annual average of precipitation in millimeters (mm) and temperature (Celsius) during the period 1990–2019 for North America. The source data were produced by and acquired from DAYMET daily climate data (2020) and presented here as a series of two 1-kilometer resolution GeoTIFF files. An open source python code file used to process the data is also included.

US Average, Maximum, and Minimum Temperatures

Analyzing Daily Temperatures Across the USA

By Matthew Winter [source]

About this dataset

This dataset features the daily temperature summaries from various weather stations across the United States. It includes information such as location, average temperature, maximum temperature, minimum temperature, state name, state code, and zip code. All the data contained in this dataset has been filtered so that any values equaling -999 were removed. With this powerful set of data you to explore how climate conditions changed throughout the year and how they varied across different regions of the country. Dive into your own research today to uncover fascinating climate trends or use it to further narrow your studies specific to a region or city

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This dataset offers a detailed look at daily average, minimum, and maximum temperatures across the United States. It contains information from 1120 weather stations throughout the year to provide a comprehensive look at temperature trends for the year.

The data contains a variety of columns including station, station name, location (latitude and longitude), state name zip code and date. The primary focus of this dataset is on the AvgTemp, MaxTemp and MinTemp columns which provide daily average, maximum and minimum temperature records respectively in degrees Fahrenheit.

To use this dataset effectively it is useful to consider multiple views before undertaking any analysis or making conclusions:
- Plot each individual record versus time by creating a line graph with stations as labels on different lines indicating changes over time. Doing so can help identify outliers that may need further examination; much like viewing data on a scatterplot looking for confidence bands or examining variance between points that are otherwise hard to see when all points are plotted on one graph only.
- A comparison of states can be made through creating grouped bar charts where states are grouped together with Avg/Max/Min temperatures included within each chart - thereby showing any variance that may exist between states during a specific period about which it's possible to make observations about themselves (rather than comparing them). For example - you could observe if there was an abnormally high temperature increase in California during July compared with other US states since all measurements would be represented visually providing opportunity for insights quickly compared with having to manually calculate figures from raw data sets only.

With these two initial approaches there will also be further visualizations possible regarding correlations between particular geographical areas versus different climatic conditions or through population analysis such as correlating areas warmer/colder than median observances verses relative population densities etc.. providing additional opportunities for investigation particularly when combined with key metrics collected over multiple years versus one single year's results exclusively allowing wider inferences to be made depending upon what is being requested in terms of outcomes desired from those who may explore this data set further down the line beyond its original compilation starter point here today!

Research Ideas

• Using the Latitude and Longitude values, this dataset can be used to create a map of average temperatures across the USA. This would be useful for seeing which areas were consistently hotter or colder than others throughout the year.
• Using the AvgTemp and StateName columns, predictors could use regression modeling to predict what temperature an area will have in a given month based on it's average temperature.
• By using the Date column and plotting it alongside MaxTemp or MinTemp values, visualization methods such as timelines could be utilized to show how temperatures changed during different times of year across various states in the US

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: 2015 USA Weather Data FINAL.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Matthew Winter.

Annual mean temperature is mean of the average temperatures for each month in degrees Celsius for the period of January 1971 through December 2009.The relationships established between species demographics and distributions with bioclimatic predictors can inform land managers of climatic effects on species during decision making processes.Dataset SummaryAnnual mean temperature was developed by the U.S. Geological Survey (USGS) as part of a collection Bioclimatic Predictors for Supporting Ecological Applications in the Conterminous United States. These predictors highlight climate conditions best related to species physiology. The Parameter-elevation Regression on Independent Slopes Model (PRISM) and down-scaled PRISM data, which included both averaged multi-year and averaged monthly climate summaries, were used to develop these multi-scale bioclimatic predictors.Link to source metadataWhat can you do with this layer?The layer is restricted to an 24,000 x 24,000 pixel limit for these services, which represents an area roughly 1,200 miles on a side.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

Includes Average Temperature of US States from Jan 1950 - Aug 2022

Source: https://www.ncei.noaa.gov/cag/statewide/mapping/110/tavg/202208/1/value

References: NOAA National Centers for Environmental information, Climate at a Glance: Statewide Mapping, Average Temperature, published September 2022, retrieved on October 8, 2022 from https://www.ncdc.noaa.gov/cag/

The monthly mean temperature data presented in this dataset was obtained from the Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis, which was loaded into Python using xarray. The data was then filtered to include only the latitude and longitude coordinates corresponding to each city in the dataset. In order to select the nearest location to each city, the 'select' method with the nearest point was used, resulting in temperature data that may not be exactly at the city location. The data is presented on a 0.5x0.5 degree grid across the globe.

The temperature data provides a valuable resource for time series analysis, and if you are interested in obtaining temperature data for additional cities, please let me know. I will also be sharing the source code on GitHub for anyone who would like to reproduce the data or analysis.

US Weather History

Actual and Average Temperatures and Precipitation

By FiveThirtyEight [source]

About this dataset

This dataset contains a collection of weather data from twelve major cities across the United States, including Los Angeles (KCTQ), Charlotte (KCLT), Houston (KHOU), Indianapolis (KIND), Jacksonville (KJAX), Chicago (KMDW), New York City (KNYC), Philadelphia(KPHL ), Phoenix( KPHX) and Seattle( KSEA). These datasets offer an exciting insight into the changing temperatures and climate in these key locations over a period of 12 months. Whether you are an experienced researcher in climate science or just interested in understanding more about world weather trends, this dataset provides an invaluable source.

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This dataset contains 12 weather records from various cities across the US, from Los Angeles to New York City. Each record includes information about average and actual temperatures, as well as precipitation and related records.

Research Ideas

• Using the data to map out a timeline of high temperature records throughout the US and compare it to predictions of climate scientists on how climate change will affect regional temperatures in a given area.
• Tracking average and actual precipitation levels over the course of an entire year in various cities around the US in order to develop city-specific estimates for water resource availability in future years.
• Comparing record temperatures across cities in different regions, determining if there are any correlations between geographical location and temperature extremes, and then extrapolating these findings to better understand local weather patterns on both short-term or long-term scales

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: KPHL.csv | Column name | Description | |:--------------------------|:--------------------------------------------------------------------| | date | The date of the weather record. (Date) | | actual_mean_temp | The actual mean temperature for the day. (Float) | | actual_min_temp | The actual minimum temperature for the day. (Float) | | actual_max_temp | The actual maximum temperature for the day. (Float) | | average_min_temp | The average minimum temperature for the day. (Float) | | average_max_temp | The average maximum temperature for the day. (Float) | | record_min_temp | The record minimum temperature for the day. (Float) | | record_max_temp | The record maximum temperature for the day. (Float) | | record_min_temp_year | The year in which the record minimum temperature was set. (Integer) | | record_max_temp_year | The year in which the record maximum temperature was set. (Integer) | | actual_precipitation | The actual precipitation for the day. (Float) | | average_precipitation | The average precipitation for the day. (Float) | | record_precipitation | The record precipitation for the day. (Float) |

File: KPHX.csv | Column name | Description | |:--------------------------|:--------------------------------------------------------------------| | date | The date of the weather record. (Date) | | actual_mean_temp | The actual mean temperature for the day. (Float) | | actual_min_temp | The actual minimum temperature for the day. (Float) | | actual_max_temp | The actual maximum temperature for the day. (Float) | | average_min_temp | The average minimum temperature for the day. (Float) | | average_max_temp | The average maximum temperature for the day. (Float) | | **record_min_...

In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. In January 2025, the National Centers for Environmental Information (NCEI) began summarizing the State of the Climate for Hawaii. This was made possible through a collaboration between NCEI and the University of Hawaii/Hawaii Climate Data Portal and completes a long-standing gap in NCEI's ability to characterize the State of the Climate for all 50 states. NCEI maintains monthly statewide, divisional, and gridded average temperature, maximum temperatures (highs), minimum temperature (lows) and precipitation data for Hawaii over the period 1991-2025. As of November 2018, NClimDiv includes county data and additional inventory files In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set.

As of November 2018, NClimDiv includes county data and additional inventory files.

In 2024, the minimum average temperature in the contiguous United States reached around 6.45 degrees Celsius. Several of the hottest years on record have all been recorded within the last decade. Just one-degree of warming is significant, as it takes a vast amount of heat to warm up the oceans, atmosphere, and land to this degree.