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 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).

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).

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.

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).

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 monthly average temperature in the United States between 2020 and 2025 shows distinct seasonal variation, following similar patterns. For instance, in April 2025, the average temperature across the North American country stood at 12.02 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 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).

The average temperature in Spain stood at 15 degrees Celsius in 2024. This represented a slight decrease from the previous year, but an anomaly of 1.1 degrees Celsius above the annual mean from 1991 to 2020. During the period in consideration, average temperatures in the Mediterranean country reached a record high in 2017, at some 16.2 degrees Celsius.

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.

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

The North America climate data were derived from WorldClim, a set of global climate layers developed by the Museum of Vertebrate Zoology at the University of California, Berkeley, USA, in collaboration with The International Center for Tropical Agriculture and Rainforest CRC with support from NatureServe.The global climate data layers were generated through interpolation of average monthly climate data from weather stations across North America. The result is a 30-arc-second-resolution (1-Km) grid of mean temperature values. The North American data were clipped from the global data and reprojected to the standard Lambert Azimuthal Equal Area projection used for the North American Environmental Atlas. Background information on the WorldClim database is available in: Very High-Resolution Interpolated Climate Surfaces for Global Land Areas; Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis; International Journal of Climatology 25: 1965-1978; 2005.Files Download

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.

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).

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.

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).

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 dataset provide:a) annual average temperature, total precipitation, and temperature and precipitation extremes calculations for 210 U.S. cities.b) historical rates of annual temperature, precipitation, and extremes change in the 210 U.S. cities.c) 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 Box-Cox transformation prior to linear regression.See included README file for more information.

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.

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 state of Alaska were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP) (https://snap.uaf.edu). 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). 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).