This dataset provides values for PRECIPITATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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 1-h precipitation accumulation in millimeters. For each grid cell, the availability for 1-h accumulations data is either no data or full availability, and can be determined from "dataset1/data1" through the "nodata" value (-9999000.0).

This statistic presents the number of days with precipitation in leading European countries between January 1 and March 31, 2018. According to data provided by LAL, the Netherlands had 56 days of rainfall during this period, the most of any country.

The dataset presents climate impact indicators related to extreme precipitation in Europe under current climate conditions. The suite of indicators include recent historic records, recurrence intervals, and other relevant statistical measures to evaluate the magnitude and frequency of extreme precipitation events. These are provided as gridded products, with one product covering the whole of Europe, and the other higher resolution product focused on 20 European cities that were identified as vulnerable to urban pluvial flooding based on stakeholder surveys. This dataset makes use of precipitation data available in the Climate Data Store (i.e. E-OBS gridded land-only observational dataset and ERA5 reanalysis) combined with additional datasets capable of improving the spatial and temporal resolution of the precipitation data, making it suitable for pluvial flood analysis at city scales. These are derived from i) the network of meteorological stations included in the European Climate Assessment & Dataset (ECA&D) programme and ii) dynamically downscaled ERA5 reanalysis at 2 km x 2 km (ERA5-2km) using the regional climate model COSMO-CLM and accounting for urban parameterization, specifically performed for the 20 European cities identified as vulnerable to urban pluvial flooding. At the European scale, E-OBS and ERA5 precipitation data are used to compute indicators at different temporal resolutions (i.e. daily, monthly, yearly, and 30-year) according to the type of indicator. The precipitation amounts at fixed return periods are also computed for point observations from meteorological stations using the ECA&D network and are then interpolated onto the E-OBS grid. At the city scale, a dynamically downscaled ERA5-2km precipitation data are instead used to derive daily indicators, allowing city stakeholders to detect and rank local extreme precipitation events and evaluate their magnitude. This dataset was produced on behalf of the Copernicus Climate Change Service.

NetCDF files containing estimated occurence frequency of the present day 10-year return levels of precipitation for different time periods and scenarios in the future climate. Additionally includes 10-year return levels of 3-hourly, 24 -hourly, 48-hourly and 72-hourly precipitation amounts for the simulated present day climate. The fields are multi model means of regional climate model simulations (EURO-CORDEX).

ERA5-Land daily: Total precipitation, daily time series for Europe at 30 arc seconds (ca. 1000 meter) resolution (2000 - 2020)

Source data:
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.

Processing steps:
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.
File naming:
era5_land_daily_prectot_YYYYMMDD_sum_30sec.tif
e.g.:era5_land_daily_prectot_20200418_sum_30sec.tif

The date within the filename is Year, Month and Day of timestamp.

Pixel values:
mm * 10
Scaled to Integer, example: value 218 = 21.8 mm

Projection + EPSG code:
Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:
north: 82:00:30N
south: 18:00:00N
west: 32:00:30W
east: 70:00:00E

Temporal extent:
01.01.2000 - 31.12.2020
NOTE: Due to file size, only 2020 data are available here. Data for other years are available on request.

Spatial resolution:
30 arc seconds (approx. 1000 m)

Temporal resolution:
daily

Lineage:
Dataset has been processed from Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used.

Software used:
GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)

Format: GeoTIFF

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

Representation type: Grid

Processed by:
mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

Contact:
mundialis GmbH & Co. KG, info@mundialis.de

Daily and monthly rainfall records for our station at Ring G.S. in Co. Waterford. This station is now closed.

This dataset provides precipitation and near surface air temperature for Europe as Essential Climate Variables (ECVs) and as a set of Climate Impact Indicators (CIIs) based on the ECVs. ECV datasets provide the empirical evidence needed to understand the current climate and predict future changes. CIIs contain condensed climate information which facilitate relatively quick and efficient subsequent analysis. Therefore, CIIs make climate information accessible to application focussed users within a sector. The ECVs and CIIs provided here were derived within the water management sectoral information service to address questions specific to the water sector. However, the products are provided in a generic form and are relevant for a range of sectors, for example agriculture and energy. The data represent the current state-of-the-art in Europe for regional climate modelling and indicator production. Data from eight model simulations included in the Coordinated Regional Climate Downscaling Experiment (CORDEX) were used to calculate a total of two ECVs and five CIIs at a spatial resolution of 0.11° x 0.11° and 5km x 5km. The ECV data meet the technical specification set by the Global Climate Observing System (GCOS), as such they are provided on a daily time step. They are bias adjusted using the EFAS gridded observations as a reference dataset. Note these are model output data, not observation data as is the general case for ECVs. The CIIs are provided as mean values over a 30-year time period. For the reference period (1971-2000) data is provided as absolute values, for the future periods the data is provided as absolute values and as the relative or absolute change from the reference period. The future periods cover 3 fixed time periods (2011-2040, 2041-2070 and 2071-2100) and 3 "degree scenario" periods defined by when global warming exceeds a given threshold (1.5 °C, 2.0 °C or 3.0 °C). The global warming is calculated from the global climate model (GCM) used, therefore the actual time period of the degree scenarios will be different for each GCM. This dataset is produced and quality assured by the Swedish Meteorological and Hydrological Institute on behalf of the Copernicus Climate Change Service.

Regardless of whether the rain in Spain stays mainly in the plain, the truth is annual precipitations in the Mediterranean country experienced a downward trend in recent years, with around 536 millimeters of rainfall recorded in 2023. For instance, March – one of Spain's wettest months – registered just over 21 millimeters of rain in 2023, down from a record high of 163 millimeters in March 2018. Spain: Europe’s suntrapMany picture Spain as a dream summer holiday destination – Mediterranean cuisine in the form of tapas, great beaches, and what many visit the country for – its warm climate and sweet sunshine. This enthusiasm for the European country is then not too surprising, since most of its sunniest areas exceeded 3,000 hours of sunshine according to data provided by the Spanish Statistics Institute. Tourism constitutes an essential industry for the Spanish economic systemTravel and tourism have become one of the leading engines of growth for the Spanish economy, featuring an ongoing increase in the GDP contribution over the last years – despite a drop due to the COVID-19 pandemic – and is projected to reach nearly 165 billion euros in 2023.

Past, present and future rainfall erosivity in Northwestern Europe calculated from convection-permitting climate simulations in CNRM-AROME (Lucas-Picher et al., 2022; https://doi.org/10.1007/s00382-022-06637-y) using emission scenario RCP 8.5. A description of the methodology is given in the article "Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations" by Magdalena Uber et al. (2024) in Hydrology and Earth System Sciences (https://doi.org/10.5194/hess-28-87-2024).

The data contains observations measured with weather surveys of the Finnish Meteorological Institute. The following quantities are available as a composite image containing all weather radars: radar reflectivity factor, rain intensity and one hour and day rainfall accumulation. A radar reflectivity factor, rain intensity and wind radial velocity are available as images of individual weather radars.

The datafile contains gridded data on a 0.25 degree regular grid of daily precipitation sums in mm.

We acknowledge the E-OBS dataset from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu)

This historical weather dataset provides hourly weather data for a number of major European Cities between 2003-01-01 and 2022-12-31. You can use this data to analyze and understand how weather has impacted your business, enrich your website with weather-related information, or enhance your data science projects with weather data. In addition to standard weather measurements such as air pressure, temperature, precipitation, and wind speed, this dataset includes solar radiation and UV index data as well. The full list of fields is provided in the documentation.

Key features:

• Hourly historical weather data between 2003 and 2022
• Includes solar radiation data
• Provides information on standard weather measurements such as air pressure, temperature, precipitation, and wind speed
• Offers insights into how weather has impacted your business

This Historical Weather Data is crucial for businesses needing detailed Climate Data, including Precipitation Data and Wind Data, to make informed decisions

Generated using Copernicus Climate Change Service information 2023 Contains modified Copernicus Climate Change Service information 2023

Daily and monthly rainfall records for our station at Cloontuskert in Co. Roscommon. This station is now closed.

NetCDF files containing data related to annual probability of freezing rain in Europe under present and projected future climates. Probabilities are shown as multi-model means based on the simulations performed with 6 regional climate models (CORDEX): SMHI-RCA4-CanESM2, SMHI-RCA4-NorESM1, SMHI-RCA4-IPSL-CM5A-MR, KNMI-RACMO22E-EC-EARTH, KNMI-RACMO22E-HadGEM2-ES and MPI-CSC-REMO2009-MPI-ESM-LR. For the period 1981-2010, the probabilities are also derived from the ERA-Interim reanalysis.

We propose a formal classification scheme for streamflow droughts in humid-temperature climate regions. The classification scheme relies on an existing drought typology and assigns events to one of eight drought types - each characterized by a set of compounding drivers - using information about seasonality, precipitation deficits and snow availability. To ensure generalizability, the classification scheme uses globally available data i.e. observed streamflow from the Global Runoff Database and hydro-meteorological time series from the ERA5-Land reanalysis including temperature, precipitation, and snow-water-equivalent (SWE). Hydrological drought types include rainfall deficit droughts, which are exclusively caused by a prolonged lack of rainfall and possibly aggravated by high evapotranspiration; rain-to-snow-season droughts, caused by a rainfall deficit in the rain season continuing into the snow season; wet-to-dry season droughts caused by a rainfall deficit in the rain season that continues into the dry season; cold-snow-season droughts, caused by abnormally low temperatures in the snow season; warm-snow-season droughts, caused by abnormally high temperatures in the snow season; snowmelt droughts, caused by a lack of snowmelt discharge in snow-influenced basins; glaciermelt droughts, caused by a lack of glaciermelt; and composite droughts, caused by a number of drought generation mechanisms.

Daily and monthly rainfall records for our station at Meanus in Co. Limerick. This station is now closed.

Climate Index: Very heavy precipitation days

Definition: Average number of very heavy precipitation days (daily precipitation ≥ 20mm).

Additional information: The dataset is based on an ensemble of EURO-CORDEX model simulations of daily near-surface maximum temperature. All ensemble members are bias-corrected against the gridded daily observational dataset E-OBS.

Results (ensemble mean and standard deviation) are available for historical (1971-2000) and future (2011-2040, 2041-2070, 2071-2100) climate periods and for the representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.

The bias-corrected EURO-CORDEX climate model simulations used are:

CLMcom-CCLM4-8-17/ICHEC-EC-EARTH, CLMcom-CCLM4-8-17/MOHC-HadGEM2-ES

DMI-HIRHAM5/ICHEC-EC-EARTH

KNMI-RACMO22E/ICHEC-EC-EARTH, KNMI-RACMO22E/MOHC-HadGEM2-ES

SMHI-RCA4/ICHEC-EC-EARTH, SMHI-RCA4/MOHC-HadGEM2-ES

Daily and monthly rainfall records for our station at Monaghan (St.Patrick,S Coll.) in Co. Monaghan. This station is now closed.

This data set contains two animations showing the spatial evolution of precipitation over the whole of Europe: One 3-hourly over 7 days based on the deterministic precipitation forecast of the DWD and the other one 6-hourly over 10 days based on the ECMWF forecast. The update frequency of this data set is twice a day (00:00 and 12:00 UTC); and the spatial coverage is the extended geographic Europe; while the horizontal resolution is xx km.

This information is produced by the operational suit of EFAS (www.efas.eu) in order to provide the EFAS partners with an European overview on the expected tempo-spatial evolution of precipitation over the forecast range of 7 i.e. 10 days.