The map shows the mean total precipitation in the month of January. January precipitation across Canada is mainly in the form of snow. Throughout much of the interior and the north, precipitation amounts are generally less than 20 mm and, in the high Arctic, as little as a few millimetres. The west coast receives heavy precipitation in the form of rain at low elevations and mainly snow at higher elevations. For coastal British Columbia, this is the rainy season. On Canada’s east coast, where cold continental air masses clash with the warmer air masses from the Atlantic, there is a mixture of rain and snow, with rain dominating close to the Atlantic and snow becoming more prevalent to the northwest, in southern Quebec and Labrador. The snow belt east of Lake Superior and Lake Huron is clearly visible, especially around Georgian Bay.

Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt. Dataset SummaryThe GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available.This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

What does the data show?

The data shows monthly averages of rainfall amount (mm) for 1991-2020 from HadUK gridded data. It is provided on a 2km British National Grid (BNG).

What are the naming conventions and how do I explore the data?

This data contains a field for each month’s average over the period. They are named 'pr' (precipitation) and the month. E.g. 'pr March' is the average rainfall amount for March in the period 1991-2020.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr January’ values

Data source:

HadUK-Grid v1.1.0.0 (downloaded 11/03/2022)

Useful links

Further information on HadUK-Grid Further information on understanding climate data within the Met Office Climate Data Portal

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

The wettest months in the United Kingdom tend to be at the start and end of the year. In the period of consideration, the greatest measurement of rainfall was nearly 217 millimeters, recorded in December 2015. The lowest level of rainfall was recorded in April 2021, at 20.6 millimeters. Rainy days The British Isles are known for their wet weather, and in 2024 there were approximately 164 rain days in the United Kingdom. A rainday is when more than one millimeter of rain falls within a day. Over the past 30 years, the greatest number of rain days was recorded in the year 2000. In that year, the average annual rainfall in the UK amounted to 1,242.1 millimeters. Climate change According to the Met Office, climate change in the United Kingdom has resulted in the weather getting warmer and wetter. In 2022, the annual average temperature in the country reached a new record high, surpassing 10 degrees Celsius for the first time. This represented an increase of nearly two degrees Celsius when compared to the annual average temperature recorded in 1910. In a recent survey conducted amongst UK residents, almost 80 percent of respondents had concerns about climate change.

This ongoing dataset contains monthly precipitation measurements from a network of standard can rain gauges at the Jornada Experimental Range in Dona Ana County, New Mexico, USA. Precipitation physically collects within gauges during the month and is manually measured with a graduated cylinder at the end of each month. This network is maintained by USDA Agricultural Research Service personnel. This dataset includes 39 different locations but only 29 of them are current. Other precipitation data exist for this area, including event-based tipping bucket data with timestamps, but do not go as far back in time as this dataset. Resources in this dataset:Resource Title: Website Pointer to html file. File Name: Web Page, url: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-jrn&identifier=210380001 Webpage with information and links to data files for download

Of the various climate zones the world is divided into, tropical rainforest areas generally experience the highest levels of rainfall, while deserts experience the lowest. Of the examples given, Manaus in the Amazon rainforest experienced the highest average rainfall in 11 months of the year, with a range between 68mm in August to 310mm in April. However, the example with the largest relative variation between seasons is the shrubland, which ranged from an average of 4mm in July to 156mm in January. In Cairo, in Egypt's Western Desert, monthly rainfall in all summer months was less than one millimeter.

Contained within the 4th Edition (1974) of the Atlas of Canada is a collection of six maps. Each map shows the average monthly precipitation for April, May, June, July, August and September.

Historical Past (1895-1980) - Time series datasets prior to 1981 are modeled using climatologically-aided interpolation (CAI), which uses the long-term average pattern (i.e., the 30-year normals) as first-guess of the spatial pattern of climatic conditions for a given month or day. CAI is robust to wide variations in station data density, which is necessary when modeling long time series. Data is based on Monthly and Annual dataset covering the conterminous U.S. from 1981 to now. Contains spatially gridded monthly and annual total precipitation at 4km 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.

Using observation data from various agencies in Taiwan, including the Central Weather Bureau, Water Resources Agency, Irrigation Agency and Taiwan Power Company, supplementary, homogenization, and gridization operations were carried out to establish grid data with a resolution of 5 kilometers throughout Taiwan. This data was produced by the "Taiwan Climate Change Projection Information and Adaptation Knowledge Platform Project" of the National Science Council.

The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the Daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average monthly precipitation between 1981 and 2000 to be used for display and/or analyses requiring spatially distributed monthly or annual precipitation. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperatures) or summing (precipitation) the monthly grids.

Seney NWR monthly precipitation totals, 1939-2015.

This data set contains monthly precipitation data from Costa Rica. Data are from 14 sites within Costa Rica covering the time period January 1950 to December 1997.

The Winter of Water Year (WY) 2024 brought almost as many Atmospheric Rivers (AR) to the California-Nevada River Forecast Center domain by the end of January as in all of WY 2023. However many of these did not deliver large amounts of precipitation. This layer evaluates the active period from January 31-February 3 using gridded precipitation data from the PRISM Group.

This collection is no longer being updated. See IMERG monthly This dataset algorithmically merges microwave data from multiple satellites, including SSMI, SSMIS, MHS, AMSU-B and AMSR-E, each inter-calibrated to the TRMM Combined Instrument. Algorithm 3B43 is executed once per calendar month to produce the single, best-estimate precipitation rate and RMS precipitation-error estimate field (3B43) by combining the 3-hourly merged high-quality/IR estimates (3B42) with the monthly accumulated Global Precipitation Climatology Centre (GPCC) rain gauge analysis. All of the global precipitation datasets have some calibrating data source, which is necessary to control bias differences between contributing satellites. The multi-satellite data are averaged to the monthly scale and combined with the Global Precipitation Climatology Centre's (GPCC) monthly surface precipitation gauge analysis. In each case the multi-satellite data are adjusted to the large-area mean of the gauge analysis, where available (mostly over land), and then combined with the gauge analysis using a simple inverse estimated-random-error variance weighting. Regions with poor gauge coverage, like central Africa and the oceans, have a higher weighting on the satellite input. See the algorithm description and the file specification for details.

Dataset consists of twelve monthly images for 1991-2020, available in small, large, broadcast media, full size zip, and KML archive formats. These images were derived from NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid).Description from Climate.gov:Q:How much rain and snow usually fall this month?A:Based on daily observations from 1991-2020, colors on the map show long-term average precipitation totals in 5x5 km grid cells for the month displayed. The darker the color, the higher the total precipitation.Q:Where do these measurements come from?A:Daily totals of rain and snow come from weather stations in the Global Historical Climatology Network (GHCN-D). Volunteer observers or automated instruments gathered the data from 1991 to 2020 and submitted them to the National Centers for Environmental Information (NCEI). After scientists checked the quality of the data to omit any systematic errors, they calculated each station’s monthly total and plotted 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:White areas on the map received an average of zero measurable precipitation during the month from 1991-2020. Areas shown in the lightest green received a monthly average of less than one inch of water from rain or snow over the 30-year period. The darker the color on the map, the higher the average precipitation total for the month. Areas shown in dark blue received an average of eight or more inches of water that fell as either rain or snow. Note that snowfall totals are reported as the amount of liquid water they produce upon melting. Thus, a 10-inch snowfall that melts to produce one inch of liquid water would be counted as one inch of precipitation.Q:Why do these data matter?A:Understanding these values provides insight into the “normal” conditions for a month. This type of information is widely used across an array of planning activities, from designing energy distribution networks, to the timing of crop and plant emergence, to choosing the right place and time for recreational activities.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 climate data (NClimGrid) 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 informationThe data used in these snapshots can be downloaded from different places and in different formats. We used these specific data sources:NClimGrid Precipitation Normals ReferencesNOAA 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

Total monthly precipitation modeled globally by NASA . The map shows monthly precipitation for the period of 2000 to the present, focused on the Caribbean.Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt. Dataset SummaryThe GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available.This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

The Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group works on a range of projects, some of which support the development of spatial climate datasets. These PRISM datasets provide estimates of the basic climate element of precipitation (ppt), or the Daily total precipitation averaged over a month for both rain and melted snow. These datasets are modeled with PRISM using a digital elevation model (DEM) as the predictor grid and provide baselines describing average monthly precipitation between 1981 and 2000 to be used for display and/or analyses requiring spatially distributed monthly or annual precipitation. Grids were modeled on a monthly basis. Annual grids were produced by averaging (temperatures) or summing (precipitation) the monthly grids.

[THIS DATASET HAS BEEN WITHDRAWN]. 1 km gridded estimates of daily and monthly rainfall for Great-Britain and Northern Ireland (together with approximately 3000 km2 of catchment in the Republic of Ireland) from 1890 to 2017. The rainfall estimates are derived from the Met Office national database of observed precipitation. To derive the estimates, monthly and daily (when complete month available) precipitation totals from the UK rain gauge network are used. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly estimates. The estimated rainfall on a given day refers to the rainfall amount precipitated in 24 hours between 9am on that day until 9am on the following day. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012. Full details about this dataset can be found at https://doi.org/10.5285/ee9ab43d-a4fe-4e73-afd5-cd4fc4c82556

What does the data show?

The data shows monthly averages of precipitation amount (mm) for 1991-2020 from HadUK gridded data. It is provided on a 12km British National Grid (BNG).

Limitations of the dataWe recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.What are the naming conventions and how do I explore the data?

This data contains a field for each month’s average over the period. They are named 'pr' (precipitation) and the month. E.g. 'pr March' is the rainfall amount for March in the period 1991-2020.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr January’ values.

Data source: 

·
Version: HadUK-Grid v1.1.0.0 (downloaded 26/08/2022)

·
Source: https://catalogue.ceda.ac.uk/uuid/652cea3b8b4446f7bff73be0ce99ba0f

·
Filename: rainfall_hadukgrid_uk_12km_mon-30y_199101-202012.nc

Useful links

·
Further information on HadUK-Grid

·
Further information on understanding climate data within the Met Office Climate Data Portal