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).
Typical annual rainfall data were summarized from monthly precipitation data and provided in millimeters (mm). The monthly climate data for global land areas were generated from a large network of weather stations by the WorldClim project. Precipitation and temperature data were collected from the weather stations and aggregated across a target temporal range of 1970-2000.
Weather station data (between 9,000 and 60,000 stations) were interpolated using thin-plate splines with covariates including elevation, distance to the coast, and MODIS-derived minimum and maximum land surface temperature. Spatial interpolation was first done in 23 regions of varying size depending on station density, instead of the common approach to use a single model for the entire world. The satellite imagery data were most useful in areas with low station density. The interpolation technique allowed WorldClim to produce high spatial resolution (approximately 1 km2) raster data sets.
In 2024, the United States saw some **** inches of precipitation. The main forms of precipitation include hail, drizzle, rain, sleet, and snow. Since the turn of the century, 2012 was the driest year on record with an annual precipitation of **** inches. Regional disparities in rainfall Louisiana emerged as the wettest state in the U.S. in 2024, recording a staggering ***** inches (*** meters) of precipitation—nearly **** inches (ca. ** centimeters) above its historical average. In stark contrast, Nevada received only **** inches (ca. ** centimeters), underscoring the vast differences in rainfall across the nation. These extremes illustrate the uneven distribution of precipitation, with the southwestern states experiencing increasingly dry conditions that experts predict will worsen in the coming years. Drought concerns persist Drought remains a significant concern in many parts of the country. The Palmer Drought Severity Index (PDSI) for the contiguous United States stood at ***** in December 2024, indicating moderate to severe drought conditions. This reading follows three years of generally negative PDSI values, with the most extreme drought recorded in December 2023 at *****.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
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30-year Average precipitation represents the average amount (mm) of precipitation received in a month across a 30 year period (1961-1991, 1971-2000, 1981-2010, 1991-2020). These values are calculated across Canada in 10x10 km cells.
In 2024, Louisiana recorded ***** inches of precipitation. This was the highest precipitation within the 48 contiguous U.S. states that year. On the other hand, Nevada was the driest state, with only **** inches of precipitation recorded. Precipitation across the United States Not only did Louisiana record the largest precipitation volume in 2024, but it also registered the highest precipitation anomaly that year, around 14.36 inches above the 1901-2000 annual average. In fact, over the last decade, rainfall across the United States was generally higher than the average recorded for the 20th century. Meanwhile, the driest states were located in the country's southwestern region, an area which – according to experts – will become even drier and warmer in the future. How does global warming affect precipitation patterns? Rising temperatures on Earth lead to increased evaporation which – ultimately – results in more precipitation. Since 1900, the volume of precipitation in the United States has increased at an average rate of **** inches per decade. Nevertheless, the effects of climate change on precipitation can vary depending on the location. For instance, climate change can alter wind patterns and ocean currents, causing certain areas to experience reduced precipitation. Furthermore, even if precipitation increases, it does not necessarily increase the water availability for human consumption, which might eventually lead to drought conditions.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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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).
In 2020, the annual precipitation in Indonesia amounted to around *** thousand millimeters. The fundamental determinant of Indonesia's climate is rainfall, not temperature or air pressure. Indonesia has a variety of climates, the most common of which being tropical rainforest, which receives the most precipitation, followed by tropical monsoon and tropical savanna (lowest precipitation). The variations in rainfall are related to the monsoons, and the western and northern parts of Indonesia experience the most precipitation.
These data represent mean annual precipitation in the Louisiana StreamStats study area for the period of 1971-2000.
This metadata record describes the 30-year annual average of precipitation in millimeters (mm) and temperature (Celsius) during the period 1990–2019 for North America. The source data were produced by and acquired from DAYMET daily climate data (2020) and presented here as a series of two 1-kilometer resolution GeoTIFF files. An open source python code file used to process the data is also included.
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). Monthly precipitation values (mm) were summed 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).
U.S. Government Workshttps://www.usa.gov/government-works
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The California Department of Water Resources (DWR), Northern Region Office (NRO), maintains 33 precipitation stations that were installed starting in 1944. Stations record total annual precipitation. This information can help inform annual water budgets or track climate-related trends in annual precipitation. The CSV file contains total annual precipitation data in inches. The PDF file contains a description of stations and methods for data collection.
https://geocatalog-uidaho.hub.arcgis.com/datasets/c72fb71c196944b7879b59122c675b3e_0/license.jsonhttps://geocatalog-uidaho.hub.arcgis.com/datasets/c72fb71c196944b7879b59122c675b3e_0/license.json
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows two maps for the annual total precipitation. Annual precipitation is defined as the sum of rainfall and the assumed water equivalent of snowfall for a given year. A specific gravity of 0.1 for freshly fallen snow is used, which means that ten inches (25.4 cm) of freshly fallen snow is assumed to be equal to one inch (2.54 cm) of rain. The mean annual total precipitation and snowfall maps on this plate are primarily based on thirty-year data during the period 1921 to 1950 inclusive.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Precipitation in Turkey decreased to 569.47 mm in 2024 from 658.17 mm in 2023. This dataset includes a chart with historical data for Turkey Average Precipitation.
Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
License information was derived automatically
1km gridded Rainfall map - interpolation over DEM. Rainfall data scattered well except Western and Southern Highlands Provinces. With the Digicel Towers (mounted with rainfall instruments) network nation-wide. The Rainfall Map can be improved.
Total annual precipitation is shown along with elevation hillshade using the NAGI method. Hillshade is from Esri Elevation Service, and precipitation data is taken from WMO and FAO rain gages in addition to a number of national datasets. The annual and monthly averages for the period 1950-2000 was calculated and interpolated by WorldClim.org, a collaboration between the University of California, Berkeley, the International Cetner for Tropical Agrilculture, and the Cooperative Research Centre for Tropical Rainforest Ecology and Management.
https://data.mfe.govt.nz/license/attribution-3-0-new-zealand/https://data.mfe.govt.nz/license/attribution-3-0-new-zealand/
"Annual rainfall is the total accumulated rain over one year. Rain is vital for life, including plant growth, drinking water, river ecosystem health, and sanitation. Floods and droughts affect our environment, economy, and recreational opportunities.
This dataset shows annual average rainfall across New Zealand for 1987 as part of the data series for years 1972 to 2013. Annual rainfall is estimated from the daily rainfall estimates of the Virtual Climate Station Network (NIWA).
This dataset relates to the "Annual average rainfall" measure on the Environmental Indicators, Te taiao Aotearoa website.
Geometry: grid Unit: mm/yr"
This is a dataset download, not a document. The Open button will start the download.This data layer is an element of the Oregon GIS Framework. Monthly 30-year "normal" dataset covering Oregon, averaged over the climatological period 1991-2020. Contains spatially gridded average annual total precipitation at 800m (30 arc-second) grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. This dataset is available free-of-charge on the PRISM website.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Precipitation in the United States increased to 777.25 mm in 2024 from 738.01 mm in 2023. This dataset includes a chart with historical data for the United States Average Precipitation.
In 2020, approximately **** percent of the United States' land area recorded unusually high annual precipitation. The previous year had recorded the largest area affected in the indicated period, with roughly ** percent of the country's land area registering much higher annual rainfall than expected based on historical data.
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).