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.

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.

This dataset provides values for AVERAGE TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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.

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.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part of the World Climate Research Programme (WCRP) to collect and analyze the global distribution of clouds, their properties, and their diurnal, seasonal, and interannual variations. The LAS provides data for Monthly Near-Surface Air Temperature Averages from 1994 to 2008.

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.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs 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, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.

Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the contiguous United States are ensemble mean values across 20 global climate models from the CMIP5 experiment (https://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-11-00094.1), downscaled to a 4 km grid. For more information on the downscaling method and to access the data, please see Abatzoglou and Brown, 2012 (https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312) and the Northwest Knowledge Network (https://climate.northwestknowledge.net/MACA/). We used the MACAv2- Metdata monthly dataset; average temperature values were calculated as the mean of monthly minimum and maximum air temperature values (degrees C), averaged over the season of interest (annual, winter, or summer). Absolute change was then calculated between the historical and future time periods.

Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).

Historical changes of annual temperature and precipitation indices at selected 210 U.S. cities

This dataset provide:

Annual average temperature, total precipitation, and temperature and precipitation extremes calculations for 210 U.S. cities.

Historical rates of changes in annual temperature, precipitation, and the selected temperature and precipitation extreme indices in the 210 U.S. cities.

Estimated thresholds (reference levels) for the calculations of annual extreme indices including warm and cold days, warm and cold nights, and precipitation amount from very wet days in the 210 cities.

Annual average of daily mean temperature, Tmax, and Tmin are included for annual average temperature calculations. Calculations were based on the compiled daily temperature and precipitation records at individual cities.

Temperature and precipitation extreme indices include: warmest daily Tmax and Tmin, coldest daily Tmax and Tmin , warm days and nights, cold days and nights, maximum 1-day precipitation, maximum consecutive 5-day precipitation, precipitation amounts from very wet days.

Number of missing daily Tmax, Tmin, and precipitation values are included for each city.

Rates of change were calculated using linear regression, with some climate indices applied with the Box-Cox transformation prior to the linear regression.

The historical observations from ACIS belong to Global Historical Climatological Network - daily (GHCN-D) datasets. The included stations were based on NRCC’s “ThreadEx” project, which combined daily temperature and precipitation extremes at 255 NOAA Local Climatological Locations, representing all large and medium size cities in U.S. (See Owen et al. (2006) Accessing NOAA Daily Temperature and Precipitation Extremes Based on Combined/Threaded Station Records).

Resources:

See included README file for more information.

Additional technical details and analyses can be found in: Lai, Y., & Dzombak, D. A. (2019). Use of historical data to assess regional climate change. Journal of climate, 32(14), 4299-4320. https://doi.org/10.1175/JCLI-D-18-0630.1

Other datasets from the same project can be accessed at: https://kilthub.cmu.edu/projects/Use_of_historical_data_to_assess_regional_climate_change/61538

ACIS database for historical observations: http://scacis.rcc-acis.org/

GHCN-D datasets can also be accessed at: https://www.ncei.noaa.gov/data/global-historical-climatology-network-daily/

Station information for each city can be accessed at: http://threadex.rcc-acis.org/

• 2024 August updated -

  Annual calculations for 2022 and 2023 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2022 and 2023 data.

  Note that future updates may be infrequent.

• 2022 January updated -

  Annual calculations for 2021 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2021 data.

• 2021 January updated -

  Annual calculations for 2020 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2020 data.

• 2020 January updated -

  Annual calculations for 2019 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2019 data.

  Thresholds for all 210 cities were combined into one single file – Thresholds.csv.

• 2019 June updated -

  Baltimore was updated with the 2018 data (previously version shows NA for 2018) and new ID to reflect the GCHN ID of Baltimore-Washington International AP. city_info file was updated accordingly.

  README file was updated to reflect the use of "wet days" index in this study. The 95% thresholds for calculation of wet days utilized all daily precipitation data from the reference period and can be different from the same index from some other studies, where only days with at least 1 mm of precipitation were utilized to calculate the thresholds. Thus the thresholds in this study can be lower than the ones that would've be calculated from the 95% percentiles from wet days (i.e., with at least 1 mm of precipitation).

Q: Where was the monthly temperature warmer or cooler than usual? A: Colors show where average monthly temperature was above or below its 1991-2020 average. Blue areas experienced cooler-than-usual temperatures while areas shown in red were warmer than usual. The darker the color, the larger the difference from the long-term average temperature. Q: Where do these measurements come from? A: Weather stations on every continent record temperatures over land, and ocean surface temperatures come from measurements made by ships and buoys. NOAA scientists merge the readings from land and ocean into a single dataset. To calculate difference-from-average temperatures—also called temperature anomalies—scientists calculate the average monthly temperature across hundreds of small regions, and then subtract each region’s 1991-2020 average for the same month. If the result is a positive number, the region was warmer than the long-term average. A negative result from the subtraction means the region was cooler than usual. To generate the source images, visualizers apply a mathematical filter to the results to produce a map that has smooth color transitions and no gaps. Q: What do the colors mean? A: Shades of red show where average monthly temperature was warmer than the 1991-2020 average for the same month. Shades of blue show where the monthly average was cooler than the long-term average. The darker the color, the larger the difference from average temperature. White and very light areas were close to their long-term average temperature. Gray areas near the North and South Poles show where no data are available. Q: Why do these data matter? A: Over time, these data give us a planet-wide picture of how climate varies over months and years and changes over decades. Each month, some areas are cooler than the long-term average and some areas are warmer. Though we don’t see an increase in temperature at every location every month, the long-term trend shows a growing portion of Earth’s surface is warmer than it was during the base period. 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. NOAA's Environmental Visualization Laboratory (NNVL) produces the source images for the Difference from Average Temperature – Monthly maps. To produce our images, we run a set of scripts that access the source images, re-project them into desired projections at various sizes, and output them with a custom color bar. Additional information Source images available through NOAA's Environmental Visualization Lab (NNVL) are interpolated from data originally provided by the National Center for Environmental Information (NCEI) - Weather and Climate. NNVL images are based on NOAA Merged Land Ocean Global Surface Temperature Analysis data (NOAAGlobalTemp, formerly known as MLOST). References NCEI Monthly Global Analysis NOAA View Temperature Anomaly Merged Land Ocean Global Surface Temperature Analysis Global Surface Temperature Anomalies Climate at a Glance - Data Information Source: https://www.climate.gov/maps-data/data-snapshots/data-source/temperature-global-monthly-difference-a...This upload includes two additional files:* Temperature - Global Monthly, Difference from Average _NOAA Climate.gov.pdf is a screenshot of the main Climate.gov site for these snapshots (https://www.climate.gov/maps-data/data-snapshots/data-source/temperature-global-monthly-difference-a...)* Cimate_gov_ Data Snapshots.pdf is a screenshot of the data download page for the full-resolution files.

Temperature in Iran decreased to 19.18 celsius in 2024 from 19.61 celsius in 2023. This dataset includes a chart with historical data for Iran Average Temperature.

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.

Based on current monthly figures, on average, German climate has gotten a bit warmer. The average temperature for January 2025 was recorded at around 2 degrees Celsius, compared to 1.5 degrees a year before. In the broader context of climate change, average monthly temperatures are indicative of where the national climate is headed and whether attempts to control global warming are successful. Summer and winter Average summer temperature in Germany fluctuated in recent years, generally between 18 to 19 degrees Celsius. The season remains generally warm, and while there may not be as many hot and sunny days as in other parts of Europe, heat waves have occurred. In fact, 2023 saw 11.5 days with a temperature of at least 30 degrees, though this was a decrease compared to the year before. Meanwhile, average winter temperatures also fluctuated, but were higher in recent years, rising over four degrees on average in 2024. Figures remained in the above zero range since 2011. Numbers therefore suggest that German winters are becoming warmer, even if individual regions experiencing colder sub-zero snaps or even more snowfall may disagree. Rain, rain, go away Average monthly precipitation varied depending on the season, though sometimes figures from different times of the year were comparable. In 2024, the average monthly precipitation was highest in May and September, although rainfalls might increase in October and November with the beginning of the cold season. In the past, torrential rains have led to catastrophic flooding in Germany, with one of the most devastating being the flood of July 2021. Germany is not immune to the weather changing between two extremes, e.g. very warm spring months mostly without rain, when rain might be wished for, and then increased precipitation in other months where dry weather might be better, for example during planting and harvest seasons. Climate change remains on the agenda in all its far-reaching ways.

Temperature in Russia increased to -2.63 celsius in 2024 from -2.82 celsius in 2023. This dataset includes a chart with historical data for Russia Average Temperature.

The highest average temperature recorded in 2024 until November was in August, at 16.8 degrees Celsius. Since 2015, the highest average daily temperature in the UK was registered in July 2018, at 18.7 degrees Celsius. The summer of 2018 was the joint hottest since institutions began recording temperatures in 1910. One noticeable anomaly during this period was in December 2015, when the average daily temperature reached 9.5 degrees Celsius. This month also experienced the highest monthly rainfall in the UK since before 2014, with England, Wales, and Scotland suffering widespread flooding. Daily hours of sunshine Unsurprisingly, the heat wave that spread across the British Isles in 2018 was the result of particularly sunny weather. July 2018 saw an average of 8.7 daily sun hours in the United Kingdom. This was more hours of sun than was recorded in July 2024, which only saw 5.8 hours of sun. Temperatures are on the rise Since the 1960s, there has been an increase in regional temperatures across the UK. Between 1961 and 1990, temperatures in England averaged nine degrees Celsius, and from 2013 to 2022, average temperatures in the country had increased to 10.3 degrees Celsius. Due to its relatively southern location, England continues to rank as the warmest country in the UK.

Some say climate change is the biggest threat of our age while others say it’s a myth based on dodgy science. We are turning some of the data over to you so you can form your own view.

Even more than with other data sets that Kaggle has featured, there’s a huge amount of data cleaning and preparation that goes into putting together a long-time study of climate trends. Early data was collected by technicians using mercury thermometers, where any variation in the visit time impacted measurements. In the 1940s, the construction of airports caused many weather stations to be moved. In the 1980s, there was a move to electronic thermometers that are said to have a cooling bias.

Given this complexity, there are a range of organizations that collate climate trends data. The three most cited land and ocean temperature data sets are NOAA’s MLOST, NASA’s GISTEMP and the UK’s HadCrut.

We have repackaged the data from a newer compilation put together by the Berkeley Earth, which is affiliated with Lawrence Berkeley National Laboratory. The Berkeley Earth Surface Temperature Study combines 1.6 billion temperature reports from 16 pre-existing archives. It is nicely packaged and allows for slicing into interesting subsets (for example by country). They publish the source data and the code for the transformations they applied. They also use methods that allow weather observations from shorter time series to be included, meaning fewer observations need to be thrown away.

In this dataset, we have include several files:

Global Land and Ocean-and-Land Temperatures (GlobalTemperatures.csv):

• Date: starts in 1750 for average land temperature and 1850 for max and min land temperatures and global ocean and land temperatures
• LandAverageTemperature: global average land temperature in celsius
• LandAverageTemperatureUncertainty: the 95% confidence interval around the average
• LandMaxTemperature: global average maximum land temperature in celsius
• LandMaxTemperatureUncertainty: the 95% confidence interval around the maximum land temperature
• LandMinTemperature: global average minimum land temperature in celsius
• LandMinTemperatureUncertainty: the 95% confidence interval around the minimum land temperature
• LandAndOceanAverageTemperature: global average land and ocean temperature in celsius
• LandAndOceanAverageTemperatureUncertainty: the 95% confidence interval around the global average land and ocean temperature

Other files include:

• Global Average Land Temperature by Country (GlobalLandTemperaturesByCountry.csv)
• Global Average Land Temperature by State (GlobalLandTemperaturesByState.csv)
• Global Land Temperatures By Major City (GlobalLandTemperaturesByMajorCity.csv)
• Global Land Temperatures By City (GlobalLandTemperaturesByCity.csv)

The raw data comes from the Berkeley Earth data page.

Q: What average temperatures are projected for future decades if global emissions of heat-trapping gases continue increasing through 2100? A: Colors show projected average daily temperature for each month from the 2020s through the 2090s, based on a high-emissions future. In this case, the high-emissions future represents a specific Representative Concentration Pathway (RCP) called RCP 8.5. Learn more about RCPs » « Go back to the Data Snapshots interface Q: Where do these measurements come from? A: Temperature projections in these images represent output from 32 global climate models that are all part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Projections labeled as “High emissions” represent a potential future in which global emissions continue increasing through the 21st century. By 2100, the result of this pathway is climate forcing of 8.5 Watts per square meter at the top of the atmosphere. Based on the energy imbalance along this pathway, global climate models calculate temperature across Earth’s surface for future periods. The RCP 8.5 scenario represents a future in which no climate policies are enacted. To produce regionally relevant projections, results from the global models were statistically downscaled using a method called Localized Constructed Analogs (LOCA). This technique uses observed local-scale weather and climate information to increase the spatial resolution of global-scale projections, and corrects for bias in the model simulations. Images of long-term averages from 1981 to 2010 (PRISM normals) show recent conditions; these maps provide a baseline for comparison with future projections. To produce the normals data, the PRISM group at Oregon State University gathered temperature and precipitation records from a range of federal, state, and international weather station networks, and then mapped them to a grid. To fill map areas between observation stations, the group used a digital elevation model as a predictor grid, and refined the model to account for local effects of mountains, distance from coasts, and other factors that affect climate in complex terrains. Q: What do the colors mean? A: Shades of blue show where average temperature for the month was, or is projected to be, below 60°F during the period indicated. The darker the shade of blue, the lower the temperature. Areas shown in shades of orange and red had, or are projected to have, average temperatures over 60°F. The darker the shade of orange or red, the higher the temperature. White or very light colors show where the average temperature was, or is projected to be, near 60°F. Q: Why do these data matter? A: In order to meet future needs for energy, food, and public health, planners and other decision makers need to understand how temperatures are projected to change over the coming decades. As the climate system continues responding to the heat-trapping gases we have added to the atmosphere, temperatures will change at different rates in different regions. These images can help people get a sense of how much warming their region will experience each decade so they can plan ahead for new conditions. These data also provide people with a way to compare conditions projected for stabilized emissions with conditions projected for high emissions. Comparing the two potential futures may encourage people to take actions to reduce emissions. Q: How did you produce these snapshots? A: We used a suite of Python scripts to process and visualize LOCA (Localized Constructed Analogs) data. The processing scripts averaged the daily values for each month in a given decade from all 32 global climate models that comprise the LOCA dataset. We then calculated the median of all models in each month of the decade. The visualization scripts produced maps of the results within the contiguous United States. For further information, see the README file or access the scripts on GitHub ». Add

Measurements of surface air and ocean temperature are compiled from around the world each month by NOAA’s National Centers for Environmental Information and are analyzed and compared to the 1971-2000 average temperature for each location. The resulting temperature anomaly (or difference from the average) is shown in this feature service, which includes an archive going back to 1880. The mean of the 12 months each year is displayed here. Each annual update is available around the 15th of the following January (e.g., 2020 is available Jan 15th, 2021). The NOAAGlobalTemp dataset is the official U.S. long-term record of global temperature data and is often used to show trends in temperature change around the world. It combines thousands of land-based station measurements from the Global Historical Climatology Network (GHCN) along with surface ocean temperature from the Extended Reconstructed Sea Surface Temperature (ERSST) analysis. These two datasets are merged into a 5-degree resolution product. A report summary report by NOAA NCEI is available here. GHCN monthly mean station averages for temperature and precipitation for the 1981-2010 period are also available in Living Atlas here.What can you do with this layer? Visualization: This layer can be used to plot areas where temperature was higher or lower than the historical average for each year since 1880. Be sure to configure the time settings in your web map to view the timeseries correctly. Analysis: This layer can be used as an input to a variety of geoprocessing tools, such as Space Time Cubes and other trend analyses. For a more detailed temporal analysis, a monthly mean is available here.

This dataset shows the averaged current average temperature presented to sites across the UK from temperatures degrees per day, based on data collected from a 1981-2010 baseline period. The dataset shows the likelihood of a temperature hazard event distributed across 5km hexagonal grids.