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.

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

The 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://res1journalsd-o-tametsocd-o-torg.vcapture.xyz/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://res1rmetsd-o-tonlinelibraryd-o-twileyd-o-tcom.vcapture.xyz/doi/full/10.1002/joc.2312) and the Northwest Knowledge Network (https://res1climated-o-tnorthwestknowledged-o-tnet.vcapture.xyz/MACA/). We used the MACAv2- Metdata monthly dataset; monthly precipitation values (mm) were summed 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://res1climated-o-tnorthwestknowledged-o-tnet.vcapture.xyz/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://res1wwwd-o-tfsd-o-tusdad-o-tgov.vcapture.xyz/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://res1wwwd-o-tfsd-o-tusdad-o-tgov.vcapture.xyz/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).

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 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. On an annual basis, approximately one year of "final" nClimGrid will be submitted to replace the initially supplied "preliminary" data for the same time period. Users should be sure to ascertain which level of data is required for their research.

This dataset replaces the previous Time Bias Corrected Divisional Temperature-Precipitation Drought Index. The new divisional data set (NClimDiv) is based on the Global Historical Climatological Network-Daily (GHCN-D) and makes use of several improvements to the previous data set. For the input data, improvements include additional station networks, quality assurance reviews and temperature bias adjustments. Perhaps the most extensive improvement is to the computational approach, which now employs climatologically aided interpolation. This 5km grid based calculation nCLIMGRID helps to address topographic and network variability. This data set is primarily used by the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC) to issue State of the Climate Reports on a monthly basis. These reports summarize recent temperature and precipitation conditions and long-term trends at a variety of spatial scales, the smallest being the climate division level. Data at the climate division level are aggregated to compute statewide, regional and national snapshots of climate conditions. For CONUS, the period of record is from 1895-present. Derived quantities such as Standardized precipitation Index (SPI), Palmer Drought Indices (PDSI, PHDI, PMDI, and ZNDX) and degree days are also available for the CONUS sites. In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. As of November 2018, NClimDiv includes county data and additional inventory files.

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

The U.S. Annual/Seasonal Climate Normals for 1991 to 2020 are 30-year averages of meteorological parameters that provide users the information needed to understand typical climate conditions for thousands of locations across the United States, as well as U.S. Territories and Commonwealths, and the Compact of Free Association nations. The stations used include those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the U.S. Climate Reference Network (USCRN) and other automated observation stations. In addition, precipitation normals for stations from the U.S. Snow Telemetry (SNOTEL) Network and the citizen-science Community Collaborative Rain, Hail and Snow (CoCoRaHS) Network are also available. The Annual/Seasonal Climate Normals dataset includes various derived products such as air temperature normals (including maximum and minimum temperature normals, heating and cooling degree day normals, and others), precipitation normals (including precipitation and snowfall totals, and percentiles, frequencies and other statistics of precipitation, snowfall, and snow depth), and agricultural normals (growing degree days (GDDs), lengths of growing seasons, probabilities of first or last temperature threshold exceedances. All data utilized in the computation of the 1991-2020 Climate Normals were taken from the Global Historical Climatology Network-Daily and -Monthly datasets. Temperatures were homogenized, adjusted for time-of-observation, and made serially complete where possible based on information from nearby stations. Precipitation totals were also made serially complete where possible based using nearby stations. The source datasets (including intermediate datasets used in the computation of products) are also archived at NOAA NCEI. A comparatively small number of station normals sets (~50) have been added as Version 1.0.1 to correct quality issues or because additional historical data during the 1991-2020 period has been ingested.

Comparative Climatic Data is a publication containing data tables of meteorological elements; the publication outlines the climatic conditions at major weather observing stations in all 50 states, Puerto Rico, and Pacific islands. The data are from observing sites presently in use or include data from former sites that are comparable in exposure. Stations having less than three years of data for the current operating site are omitted from the tables of observed data. Some elements will not be in the table for weather stations that do not regularly report that element. Major parameters are monthly and annual values: averages of cloudiness (clear, partly cloudy, cloudy), relative humidity (%), snowfall (in.), and wind speed (mph); mean number of days with minimum temperature 32 deg. F or less and precipitation 0.01 in. or more; average percent of possible sunshine and highest and lowest temperature (Deg F) and maximum wind speed (mph) of record. Monthly and annual normals of maximum, minimum and average temperatures (deg. F), precipitation (in.), and heating-degree days and cooling-degree days (base 65 deg. F).

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 US Global Change Research Program sponsors the semi-annual National Climate Assessment, which is the authoritative analysis of climate change and its potential impacts in the United States. The 4th National Climate Assessment (NCA4), issued in 2018, used high resolution, downscaled LOCA climate data for many of its national and regional analyses. The LOCA downscaling was applied to multi-model mean weighted averages, using the following 32 CMIP5 model ensemble:ACCESS1-0, ACCESS1-3, bcc-csm1-1, bcc-csm1-1-m, CanESM2, CCSM4, CESM1-BGC, CESM1-CAM5, CMCC-CM, CMCC-CMS, CNRM-CM5, CSIRO-Mk3-6-0, EC EARTH, FGOALS-g2, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, GISS-E2-H-p1, GISS-E2-R-p1, HadGEM2-AO, HadGEM2-CC, HadGEM2-ES, inmcm4, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM, MIROC-ESM, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, NorESM1-M.All of the LOCA variables used in NCA4 are presented here. Many are thresholded to provide 47 actionable statistics, like days with precipitation greater than 3", length of the growing season, or days above 90 degrees F. Time RangesStatistics for each variables were calculated over a 30-year period. Four different time ranges are provided:Historical: 1976-2005Early-Century: 2016-2045Mid-Century: 2036-2065Late-Century: 2070-2099Climate ScenariosClimate models use estimates of greenhouse gas concentrations to predict overall change. These difference scenarios are called the Relative Concentration Pathways. Two different RCPs are presented here: RCP 4.5 and RCP 8.5. The number indicates the amount of radiative forcing(watts per meter square) associated with the greenhouse gas concentration scenario in the year 2100 (higher forcing = greater warming). It is unclear which scenario will be the most likely, but RCP 4.5 aligns with the international targets of the COP-26 agreement, while RCP 8.5 is aligns with a more "business as usual" approach. Detailed documentation and the original data from USGCRP, processed by NOAA's National Climate Assessment Technical Support Unit at the North Carolina Institute for Climate Studies, can be accessed from the NCA Atlas. Variable DefinitionsCooling Degree Days: Cooling degree days (annual cumulative number of degrees by which the daily average temperature is greater than 65°F) [degree days (degF)]Consecutive Dry Days: Annual maximum number of consecutive dry days (days with total precipitation less than 0.01 inches)Consecutive Dry Days Jan Jul Aug: Summer maximum number of consecutive dry days (days with total precipitation less than 0.01 inches in June, July, and August)Consecutive Wet Days: Annual maximum number of consecutive wet days (days with total precipitation greater than or equal to 0.01 inches)First Freeze Day: Date of the first fall freeze (annual first occurrence of a minimum temperature at or below 32degF in the fall)Growing Degree Days: Growing degree days, base 50 (annual cumulative number of degrees by which the daily average temperature is greater than 50°F) [degree days (degF)]Growing Degree Days Modified: Modified growing degree days, base 50 (annual cumulative number of degrees by which the daily average temperature is greater than 50°F; before calculating the daily average temperatures, daily maximum temperatures above 86°F and daily minimum temperatures below 50°F are set to those values) [degree days (degF)]growing-season: Length of the growing (frost-free) season (the number of days between the last occurrence of a minimum temperature at or below 32degF in the spring and the first occurrence of a minimum temperature at or below 32degF in the fall)Growing Season 28F: Length of the growing season, 28°F threshold (the number of days between the last occurrence of a minimum temperature at or below 28°F in the spring and the first occurrence of a minimum temperature at or below 28°F in the fall)Growing Season 41F: Length of the growing season, 41°F threshold (the number of days between the last occurrence of a minimum temperature at or below 41°F in the spring and the first occurrence of a minimum temperature at or below 41°F in the fall)Heating Degree Days: Heating degree days (annual cumulative number of degrees by which the daily average temperature is less than 65°F) [degree days (degF)]Last Freeze Day: Date of the last spring freeze (annual last occurrence of a minimum temperature at or below 32degF in the spring)Precip Above 99th pctl: Annual total precipitation for all days exceeding the 99th percentile, calculated with reference to 1976-2005 [inches]Precip Annual Total: Annual total precipitation [inches]Precip Days Above 99th pctl: Annual number of days with precipitation exceeding the 99th percentile, calculated with reference to 1976-2005 [inches]Precip 1in: Annual number of days with total precipitation greater than 1 inchPrecip 2in: Annual number of days with total precipitation greater than 2 inchesPrecip 3in: Annual number of days with total precipitation greater than 3 inchesPrecip 4in: Annual number of days with total precipitation greater than 4 inchesPrecip Max 1 Day: Annual highest precipitation total for a single day [inches]Precip Max 5 Day: Annual highest precipitation total over a 5-day period [inches]Daily Avg Temperature: Daily average temperature [degF]Daily Max Temperature: Daily maximum temperature [degF]Temp Max Days Above 99th pctl: Annual number of days with maximum temperature greater than the 99th percentile, calculated with reference to 1976-2005Temp Max Days Below 1st pctl: Annual number of days with maximum temperature lower than the 1st percentile, calculated with reference to 1976-2005Days Above 100F: Annual number of days with a maximum temperature greater than 100degFDays Above 105F: Annual number of days with a maximum temperature greater than 105degFDays Above 110F: Annual number of days with a maximum temperature greater than 110degFDays Above 115F: Annual number of days with a maximum temperature greater than 115degFTemp Max 1 Day: Annual single highest maximum temperature [degF]Days Above 32F: Annual number of icing days (days with a maximum temperature less than 32degF)Temp Max 5 Day: Annual highest maximum temperature averaged over a 5-day period [degF]Days Above 86F: Annual number of days with a maximum temperature greater than 86degFDays Above 90F: Annual number of days with a maximum temperature greater than 90degFDays Above 95F: Annual number of days with a maximum temperature greater than 95degFTemp Min: Daily minimum temperature [degF]Temp Min Days Above 75F: Annual number of days with a minimum temperature greater than 75degFTemp Min Days Above 80F: Annual number of days with a minimum temperature greater than 80degFTemp Min Days Above 85F: Annual number of days with a minimum temperature greater than 85degFTemp Min Days Above 90F: Annual number of days with a minimum temperature greater than 90degFTemp Min Days Above 99th pctl: Annual number of days with minimum temperature greater than the 99th percentile, calculated with reference to 1976-2005Temp Min Days Below 1st pctl: Annual number of days with minimum temperature lower than the 1st percentile, calculated with reference to 1976-2005Temp Min Days Below 28F: Annual number of days with a minimum temperature less than 28degFTemp Min Max 5 Day: Annual highest minimum temperature averaged over a 5-day period [degF]Temp Min 1 Day: Annual single lowest minimum temperature [degF]Temp Min 32F: Annual number of frost days (days with a minimum temperature less than 32degF)Temp Min 5 Day: Annual lowest minimum temperature averaged over a 5-day period [degF]For For freeze-related variables:The first fall freeze is defined as the date of the first occurrence of 32degF or lower in the nine months starting midnight August 1. Grid points with more than 10 of the 30 years not experiencing an occurrence of 32degF or lower are excluded from the analysis.No freeze occurrence, value = 999The last spring freeze is defined as the date of the last occurrence of 32degF or lower in the nine months prior to midnight August 1. Grid points with more than 10 of the 30 years not experiencing an occurrence of 32degF or lower are excluded from the analysis.No freeze occurrence, value = 999The growing season is defined as the number of days between the last occurrence of 28degF/32degF/41degF or lower in the nine months prior to midnight August 1 and the first occurrence of 28degF/32degF/41degF or lower in the nine months starting August 1. Grid points with more than 10 of the 30 years not experiencing an occurrence of 28degF/32degF/41degF or lower are excluded from the analysis.No freeze occurrence, value = 999

In 2024, the maximum average temperature in Florida stood at 83 degrees Fahrenheit. The 'sunshine' state is hardly touched by low temperatures and even sees temperatures rise above 100 degrees statewide in the summer. For many of these hot states, maximum temperatures were above normal in 2024.

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

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

The U.S. Annual Climate Normals for 1981 to 2010 are 30-year averages of meteorological parameters for thousands of U.S. stations located across the 50 states, as well as U.S. territories, commonwealths, the Compact of Free Association nations, and one station in Canada. NOAA Climate Normals are a large suite of data products that provide users with many tools to understand typical climate conditions for thousands of locations across the United States. As many NWS stations as possible are used, including those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the Climate Reference Network (CRN). The comprehensive U.S. Climate Normals dataset includes various derived products including daily air temperature normals (including maximum and minimum temperature normal, heating and cooling degree day normal, and others), precipitation normals (including snowfall and snow depth, percentiles, frequencies and other), and hourly normals (all normal derived from hourly data including temperature, dew point, heat index, wind chill, wind, cloudiness, heating and cooling degree hours, pressure normals). In addition to the standard set of normals, users also can find "agricultural normals", which are used in many industries including but not limited to construction, architecture, pest control, etc. These supplemental "agricultural normals" include frost-freeze date probabilities, growing degree day normals, probabilities of reaching minimum temperature thresholds, and growing season length normals. Users can access the data either by product or by station. Included in the dataset is extensive documentation to describe station metadata, filename descriptions, and methodology of producing the data. All data utilized in the computation of the 1981-2010 Climate Normals were taken from the ISD Lite (a subset of derived Integrated Surface Data), the Global Historical Climatology Network-Daily dataset, and standardized monthly temperature data (COOP). These source datasets (including intermediate datasets used in the computation of products) are also archived at the NOAA NCDC.

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

Annual Climatological Summary contains historical monthly and annual summaries for over 8000 U.S. locations. Observing stations are located in the United States of America, U.S. Virgin Islands, Puerto Rico, and Pacific islands of the U.S. and associated nations. The major parameters are: monthly mean maximum, mean minimum and mean temperatures; monthly total precipitation and snowfall; departure from normal of the mean temperature and total precipitation; monthly heating and cooling degree days; number of days that temperatures and precipitation are above or below certain thresholds; and extreme daily temperature and precipitation amounts. Annual Climatological Summary is derived from the NCDC Summary of the Month dataset (DSI-3220).

The U.S. Daily Climate Normals (DSI-9641D) are based on monthly maximum, minimum, and mean temperature and monthly total precipitation records for each year in the 30-year period 1971-2000, inclusive (as well as separately computed monthly degree day totals). The monthly values are available in data set DSI-9641C or publication online (Climatography of the United States, No. 81 Monthly Station Normals of Temperature, Precipitation, and Heating and Cooling Degree Days, 1971-2000). In order to be included in the normals, a station had to have at least 10 years of monthly temperature data or 10 years of monthly precipitation data for each month in the period 1971-2000. In addition, a station had to be active since January 1, 1999, or had to be included as a normals station in the 1961-1990 normals.