UK Input Data

Open gauge/station data have been collated to support stochastic rainfall and weather modelling in the UK. The data are formatted ready for use with the RWGEN modelling package. Details of the data available so far are given below.

Note

Please consider the data to be preliminary at present. Changes may be made if any issues are found in the data processing (none so far) and following further quality checks.

Available Data

Currently available data are gauge/station time series data processed from the UKMO MIDAS-Open collection:

• Hourly rainfall time series for 331 gauges

• Daily weather time series for 1000 stations

The data have been compiled and reformatted using the qc-version-1 data in the MIDAS-Open datasets. No further quality control has been applied so far.

Note that the periods of record and completeness vary notably.

The daily weather time series include precipitation, temperature, vapour pressure, wind speed and sunshine duration. Not all variables are available at all stations or throughout the entire record periods. The data have been compiled from different datasets within the MIDAS-Open collection - a mixture of daily and (aggregated) hourly time series.

A metadata file summarises basic information (location, UKMO identifier etc) for the gauges/stations.

Downloads

The formatted MIDAS-Open data are now available for download from the UKCEH Environmental Information Data Centre (EIDC). Click on the “download data” button on the dataset landing page or see the following direct links:

• Hourly rainfall data

• Daily weather data

• Gauge/station metadata

Bulk download tools can be used to obtain all files or alternatively a small script, such as the following Python example:

import os
import requests

import pandas as pd


metadata_url = 'https://catalogue.ceh.ac.uk/datastore/eidchub/44c577d3-665f-40de-adce-74ecad7b304a/station_metadata.csv'
weather_base_url = 'https://catalogue.ceh.ac.uk/datastore/eidchub/44c577d3-665f-40de-adce-74ecad7b304a/historical_daily-weather/'
output_folder = ...  # TODO: Insert path to output folder

df = pd.read_csv(metadata_url)

for file_name in df['File_Name']:
    print(file_name)
    with requests.get(f'{weather_base_url}{file_name}') as r:
        with open(os.path.join(output_folder, file_name), 'wb') as fh:
            fh.write(r.content)

Note

The EIDC dataset entry contains an archived version of the model code, but this has been superseded. Instead, please refer to the GitHub repository, which contains the most recent code.

Future Data

Additional data to be added in the future include:

• Updated gauge/station time series supplemented by point extractions from HadUK-Grid to supplement missing precipitation and temperature data

• Change factors based on UKCP18-Local to facilitate climate change scenarios

Once the above are available and stable, the data will be moved to a data repository and a DOI assigned.

Licence Information

Contains public sector information licensed under the Open Government Licence v3.0.