The accumulated rainfall chart with wide intervals will be updated for download starting from September 15, 2023. Please update before December 31, 2023 as the old links will expire after that. If you need to download a large amount of data, please apply for membership at the Meteorological Data Open Platform https://opendata.cwa.gov.tw/index.

Hourly Precipitation Data (HPD) is digital data set DSI-3240, archived at the National Climatic Data Center (NCDC). The primary source of data for this file is approximately 5,500 US National Weather Service (NWS), Federal Aviation Administration (FAA), and cooperative observer stations in the United States of America, Puerto Rico, the US Virgin Islands, and various Pacific Islands. The earliest data dates vary considerably by state and region: Maine, Pennsylvania, and Texas have data since 1900. The western Pacific region that includes Guam, American Samoa, Marshall Islands, Micronesia, and Palau have data since 1978. Other states and regions have earliest dates between those extremes. The latest data in all states and regions is from the present day. The major parameter in DSI-3240 is precipitation amounts, which are measurements of hourly or daily precipitation accumulation. Accumulation was for longer periods of time if for any reason the rain gauge was out of service or no observer was present. DSI 3240_01 contains data grouped by state; DSI 3240_02 contains data grouped by year.

The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal accumulated amounts for various stations around the world. These charts are created for different scales of time (30, 90, 365 days). Each station has a graphic that contains two charts. The first chart in the graphic is a time series in the format of a line graph, representing accumulated precipitation for each day in the time series compared to the accumulated normal amount of precipitation. The second chart is a bar graph displaying actual daily precipitation. The total accumulation and surplus or deficit amounts are displayed as text on the charts representing the entire time scale, in both inches and millimeters. The graphics are updated daily and the graphics reflect the updated observations and accumulated precipitation amounts including the latest daily data available. The available graphics are rotated, meaning that only the most recently created graphics are available. Previously made graphics are not archived.

Overview: ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. Total precipitation: Accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable is accumulated from the beginning of the forecast time to the end of the forecast step. The units of precipitation are depth in metres. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model variables with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step. The original ERA5-Land dataset (period: 2000 - 2020) has been reprocessed to: - aggregate ERA5-Land hourly data to daily data (minimum, mean, maximum) - while increasing the resolution from the native ERA5-Land resolution of 0.1 degree (~ 9 km) to 30 arc-sec (~ 1 km) by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically: 1. spatially aggregate CHELSA to the resolution of ERA5-Land 2. calculate proportion of ERA5-Land / aggregated CHELSA 3. interpolate proportion with a Gaussian filter to 30 arc seconds 4. multiply the interpolated proportions with CHELSA Using proportions ensures that areas without precipitation remain areas without precipitation. Only if there was actual precipitation in a given area, precipitation was redistributed according to the spatial detail of CHELSA. Data available is the daily sum of precipitation. Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief) Original ERA5-Land dataset license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf CHELSA climatologies (V1.2): Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. http://dx.doi.org/doi:10.5061/dryad.kd1d4 Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122

The accumulated rainfall distribution status, including the background small spacing daily cumulative rainfall map, and the daily cumulative rainfall observation analysis grid data *Changes in the download URL since September 15, 112, please switch it before December 31, 112, and the old version link will expire after the deadline. If you need to download a large amount of data, please apply for membership on the Meteorological Data Open Platform. https://opendata.cwa.gov.tw/index

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.

This polygon layer represents accumulated precipitation forecasts from the Regional Ensemble Prediction System (REPS), a regional probabilistic model. It delivers ensemble‑based, short‑range precipitation forecasts—typically a 72‑hour accumulation—that aid in assessing the risk and spatial distribution of rainfall events, supporting hydrological analysis, flood forecasting, and water resource management. This polygon layer is produced by processing REPS GRIB2 files. The workflow involves extracting the precipitation field, converting it to a TIF raster, and then applying resampling, smoothing, and classification to create polygon features. These features represent forecasted rainfall totals over a 72‑hour period and are updated with each model run to maintain current predictive information. Source: Environment & Climate Change Canada

Monthly accumulated precipitation for Mexico at a resolution of 20 arc-seconds for the 1951-2020 period. The data are distributed as GeoTiffs in geographical coordinates at a 20 arcsec resolution, with each file containing the twelve months of each year. These data were computed from the gridded daily precipitation values of the MexHiResClimDB.

This polygon layer showcases ultra-fine (2.5 km) short-range precipitation forecasts from the High Resolution Deterministic Prediction System (HRDPS), a convection-permitting model by Environment and Climate Change Canada. It identifies local-scale rainfall or snowfall patterns up to 48 hours, supporting urban flood forecasting, severe weather response, and detailed water resource planning. Convection-Permitting: The HRDPS can explicitly resolve thunderstorms and other small-scale weather events by running at ~2.5 km. Short-Range Focus: Typically provides forecasts out to 36–48 hours, updated several times daily. Local Impact: Valuable for pinpointing high-impact precipitation in complex terrain or urban environments, aiding emergency managers and hydrologists in short-lead-time decisions. Nested Model: Receives lateral boundary conditions from RDPS, maintaining consistency with regional forecasts while refining detail in local domains.

This polygon layer provides medium-range (up to 10 days) accumulated precipitation forecasts from the Global Deterministic Prediction System (GDPS), a worldwide numerical weather model run by Environment and Climate Change Canada. It addresses broad-scale weather systems and supplies boundary conditions for nested regional models. Global Scope: The GDPS covers the entire planet at ~15 km resolution, projecting large-scale atmospheric developments over a 240-hour window. Coupled Model: Integrates atmospheric and oceanic interactions, improving forecast accuracy for cyclones, frontal systems, and long-traveling storm patterns. Operational Backbone: Frequently used as a reference for regional or local models (e.g., RDPS) and for medium-range planning in water resource management or agriculture. Forecast Frequency: Runs twice daily, producing deterministic outputs that guide meteorologists, hydrologists, and emergency preparedness teams.

The European climatological gauge-adjusted radar precipitation dataset, EURADCLIM, addresses the need for an accurate (sub-)daily precipitation product covering 8000000 square kilometers of Europe at high spatial resolution. It consists of 1-h and 24-h precipitation accumulations (every clock-hour) at a 2-km grid for the period 2013 through 2022. It is based on the European Meteorological Network (EUMETNET) Operational Program on the Exchange of weather RAdar Information (OPERA) gridded radar dataset of 15-min instantaneous surface rain rates. For EURADCLIM, first methods have been applied to further remove non-meteorological echoes from these images by applying two statistical methods and a satellite-based cloud type mask. Second, the radar composites are merged with the rain gauge data from the European Climate Assessment & Dataset (ECA&D) in order to substantially improve its quality. We expect to rerun EURADCLIM once a year over the entire period, using all available ECA&D rain gauge data, and extend it with one year of data. This will result in a new version of this dataset. Project EURADCLIM was financed by KNMI’s multi-annual strategic research programme (project number 2017.02). The EURADCLIM dataset is based on the OPERA surface radar rain rate and daily precipitation sums of the rain gauge networks provided by the European national weather services and other data holding institutes, through ECA&D. With respect to version 1, the changes include slightly improved removal of non-meteorological echoes, somewhat better rain gauge coverage over the years 2013 to 2020, and years 2021 and 2022 have been added to the dataset. Usage: For each month a zip file is provided. The data are in UTC, where the time in the unzipped filenames is the end time of observation in UTC. Object "dataset1/data1" contains the 24-h precipitation accumulation in millimeters. For a given grid cell, it is equal to the "nodata" value (-9999000.0) in case data availability of the underlying 1-h accumulations is < 83.3%. Object "dataset2/dataset1" contains the number of valid values for each radar grid cell (count), i.e., the number of underlying 1-h accumulations that have been used.

U.S. 15 Minute Precipitation Data is digital data set DSI-3260, archived at the National Climatic Data Center (NCDC). This is precipitation data. The primary source of data for this file is approximately 2,000 mostly U.S. weather stations operated or managed by the U.S. National Weather Service. Stations are primary, secondary, or cooperative observer sites that have the capability to measure precipitation at 15 minute intervals. This dataset contains 15-minute precipitation data (reported 4 times per hour, if precip occurs) for U.S. stations along with selected non-U.S. stations in U.S. territories and associated nations. It includes major city locations and many small town locations. Daily total precipitation is also included as part of the data record. NCDC has in archive data from most states as far back as 1970 or 1971, and continuing to the present day. The major parameter is precipitation amounts at 15 minute intervals, when precipitation actually occurs.

Accumulated Precipitation represents the amount of total precipitation in mm (solid and/or liquid) which has been recorded over a given period of time. Products are produced for the following timeframes: Agricultural Year, Growing Season, Winter Season, as well as rolling products for 7, 14, 30, 60, 90, 180, 270, 365, 730, 1095, 1460 and 1825 days.

This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

Data on daily total rainfall (Please visit the reference link for other climate information). The multiple file formats are available for datasets download in API.

The NOAA Cooperative Observer Program (COOP) 15-Minute Precipitation Data consists of quality controlled precipitation amounts, which are measurements of 15 minute accumulation of precipitation, including rain and snow for approximately 2,000 observing stations around the country, and several U.S. territories in the Caribbean and Pacific operated or managed by the NOAA National Weather Service (NWS). Stations are primary, secondary, or cooperative observer sites that have the capability to measure precipitation at 15 minute intervals. This dataset contains 15-minute precipitation data (reported 4 times per hour, if precipitation occurred) for U.S. stations along with selected non-U.S. stations in U.S. territories and associated nations. It includes major city locations and many small town locations. Daily total precipitation is also included as part of the data record. The dataset period of record is from May 1970 to December 2013. The dataset is archived by the NOAA National Centers for Environmental Information (NCEI).

The AdjDlyRS dataset contains adjusted daily rainfall (R) and snowfall (S) data from all Canadian stations reporting rainfall and snowfall for which we have metadata to do the adjustments (Wang et al. 2017). The processing includes inspection and adjustments using quality control procedures customized for producing gridded datasets (Wang et al. 2017), including: (1) conversion of snowfall ruler measurements to their water equivalents; (2) corrections for gauge undercatch and evaporation due to wind effect, for gauge specific wetting loss, and for trace precipitation amount; and (3) treatment of flags (e.g. accumulation flags). Version 2020 or later versions of this dataset also includes identification and correction of random erroneous values, including false zeros, which usually arose from missing values being misrecorded as 0 precipitation in the climate Archive (Cheng et al. 2022). All the identified erroneous daily values are set to missing. A total of 3346 stations were processed, but the data series are not homogenized. Most of the stations are located in southern Canada and have short and/or seasonal data records. The number of stations changes over time: there are 512-958 stations in the period 1948-1964, 1012-2038 stations in the period 1965-2008, and only around 300 stations in the recent years. Note that the unadjusted/raw total precipitation data in Environment and Climate Change Canada's digital Archive underestimate more than 25% of the total precipitation in northern Canada, and about 10-15% in most of southern Canada (Wang et al. 2017). References: (1) Wang, X. L., Xu, B. Qian, Y. Feng, E. Mekis, 2017: Adjusted daily rainfall and snowfall data for Canada, Atmosphere-Ocean, 55:3, 155-168, DOI:10.1080/07055900.2017.1342163. (2) Cheng, V. Y.S., X. L. Wang, Y. Feng, 2022: A quality control system for historical in situ precipitation data. Atmosphere-Ocean (submitted)

Ensemble Approach: GEPS runs multiple perturbed members of ECCC’s GEM model, capturing a range of atmospheric evolutions and yielding probability distributions for precipitation.Global Domain: Similar coverage to the GDPS but focuses on ensemble mean, spreads, and probabilities rather than a single deterministic outcome.Longer-Range Outlook: Extends up to 16 days, supporting risk-based planning for potential floods, extended rainfall events, or dryness.Data Utility: Allows decision-makers to weigh confidence levels in precipitation scenarios, vital for water management, agriculture, and emergency contingency strategies.

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.

Predicted amounts of precipitation are shown in this imagery from the NOAA Global Forecast System weather model. Each time step is an accumulation of the predicted precipitation amounts over a 3-hour period. Light blue areas are low precipitation amounts; bright green/white areas are heavy amounts. The amount of precipitation is shown as the accumulated amount over the three hours in between each time increment of the model. The values are displayed in inches or mm of liquid water (rain), though depending on the temperatures, it may precipitate as snow. In those cases a general rule of thumb is that 1 inch of liquid water equals 10 inches of snow. The model updates every six hours and provides forecasts for 10 days (240 hours) out from the start time.Meteorologists use many tools to predict the weather. They use past data such as temperature observations, real-time data such as radar and satellite images, and models that look into the future. Many different parameters are plotted using the numerical forecast models, which are generated using computers. The models consist of numerical equations which use current conditions as the inputs. The resulting outputs are forecasts for what is likely to happen in the future, based on those initial conditions. There are many different models that all attempt to do the same thing. The Global Forecast System model is used in this visualization.