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.

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 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.

Q: Was the month cooler or warmer than usual? A: Colors show where and by how much the monthly average temperature differed from the month’s long-term average temperature from 1991-2020. Red areas were warmer than the 30-year average for the month, and blue areas were cooler. White and very light areas had temperatures close to the long-term average. 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). To calculate the difference-from-average temperatures shown on these maps—also called temperature anomalies—NCEI scientists take the average temperature in each 5x5 km grid box for a single month and year, and subtract its 1991-2020 average for the same month. If the result is a positive number, the region was warmer than average. A negative result means the region was cooler than usual. Q: What do the colors mean? A: Shades of blue show places where average monthly temperatures were below their long-term average for the month. Areas shown in shades of pink to red had average temperatures that were warmer than usual. The darker the shade of red or blue, the larger the difference from the long-term average temperature. White and very light areas show where average monthly temperature was the same as or very close to the long-term average. Q: Why do these data matter? A: Comparing an area’s recent temperature to its long-term average can tell how warm or how cool the area is compared to usual. Temperature anomalies also give us a frame of reference to better compare locations. For example, two areas might have each had recent temperatures near 70°F, but 70°F could be above average for one location while below average for another. Knowing an area is much warmer or much cooler than usual can encourage people to pay close attention to on-the-ground conditions that affect daily life and decisions. People check maps like this to judge crop progress, estimate energy use, consider snow and lake ice melt; and to understand impacts on wildfire regimes. 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. Q: Data Format Description A: NetCDF (Version: 4) 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 NClimGrid Temperature Normals 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 Cl

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.

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.

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.

A long-term timeseries of monthly averaged weather at Palmer Station, Antarctic, was created by combining calculated averages of daily weather from 1989-present with additional historical temperature measurements made between 1974-1989. The selected variables in this dataset include temperature, air pressure, precipitation, sea surface temperature, and wind speed. Monthly averages (means) are made for each calendar month, and dated with the month's start date. Historical monthly average temperatures (through March 1989) are from "Baker, K.S. (1996), Palmer LTER: Palmer Station air temperature 1974 to 1996." Monthly averages from April 1989 onwards are computed from the daily weather averages calculated at Palmer Station and made available by the Antarctic Meteorological Research Center (AMRC) archive at https://amrdcdata.ssec.wisc.edu/group/palmer-station/ The daily averages are available in aggregate form as PAL dataset #28 (knb-lter-pal.28.10), from which this dataset was generated.

This dataset contains monthly climate records for all states in Mexico from January 1985 to July 2025. It includes both temperature and precipitation data, with values provided in metric and imperial units. The dataset was compiled to support climate analysis, trend studies, and data visualization projects related to environmental conditions across Mexico.Temperature Data:Provided in both Celsius and Fahrenheit, with three key metrics:Minimum average temperature for the monthMaximum average temperature for the monthOverall mean temperature for the monthPrecipitation Data:Available in both millimeters and inches:Monthly total precipitation in millimetersMonthly total precipitation in inchesAdditional Components:A visualization script for generating temperature trend charts efficientlyA sample chart illustrating temperature evolution in Mexico CityA requirements.txt file listing dependencies for running the visualization scriptData Source:The temperature and precipitation data were sourced from the Mexican National Meteorological Service (SMN):https://smn.conagua.gob.mx/es/climatologia/temperaturas-y-lluvias/resumenes-mensuales-de-temperaturas-y-lluviasThis dataset is valuable for:Long-term climate change analysisRegional environmental studiesData-driven policy planningEducational and research purposes in meteorology and climatology

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.

This file contains additional resolutions of the same images as in https://www.datalumos.org/datalumos/project/233461/version/V2/view. 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.

Gridded files of average monthly maximum temperature in the Netherlands over the period 1981-2010 (normal period). Based on 28 automatic weather stations.

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 data updates monthly, usually around the 15th of the following month. For instance, the January data will become available on or about February 15th. 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 that summarizes the data is released each month (and end of the year) by NOAA NCEI is available here. GHCN monthly mean 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 month going back to 1880. Be sure to configure the time settings in your web map to view the time series 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. A version showing just the most recent month is available here.

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.

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.

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 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 and percent change were then calculated between the historical and future time periods.

Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the state of Alaska were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP) (https://snap.uaf.edu). These datasets have several important differences from the MACAv2-Metdata (https://climate.northwestknowledge.net/MACA/) products, used in the contiguous U.S. They were developed using different global circulation models and different downscaling methods, and were downscaled to a different scale (771 m instead of 4 km). While these cover the same time periods and use broadly similar approaches, caution should be used when directly comparing values between Alaska and the contiguous United States.

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).

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. The data updates monthly, usually around the 15th of the following month. For instance, the January data will become available on or about February 15th. 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 that summarizes the data is released each month (and end of the year) by NOAA NCEI is available here. GHCN monthly mean 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 the past month. Analysis: The full archive from 1880 – present is available here, and can be used as an input to a variety of geoprocessing tools, such as Space Time Cubes and other trend analyses.

This map is part of a series of global climate images produced by the Agrometeorology Group and based on data for mean monthly values of temperature, precipitation and cloudiness prepared in 1991 by R. Leemans and W. Cramer and published by the International Institute for Applied Systems Analysis (IIASA). For each of the weather stations used data have been assembled over a long time period - usually between 1961 and 1990 - and then averaged.

This dataset provides monthly average values of the TG variable, representing mean air temperature across European regions. It spans multiple years, supporting analysis of seasonal and interannual temperature variability. The data are suitable for climate research, trend detection, modeling efforts, and understanding temperature-related environmental impacts across Europe. Structured for compatibility with other Copernicus climate datasets, it can be integrated with variables such as precipitation, cloud cover, and wind speed to examine broader climate patterns.