Code and UK observation-based historical climate input data for the Rainfall and Weather GENerator (RWGEN) stochastic model
https://doi.org/10.5285/44c577d3-665f-40de-adce-74ecad7b304a
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This dataset contains the stochastic Rainfall and Weather GENerator (RWGEN) model and observational historical climate inputs for UK applications. The model simulates one or more stochastic realisations of any length for rainfall (mm), temperature (°C) and potential evapotranspiration (mm) at hourly or longer timesteps.
RWGEN can be used for single site or spatial simulations of historical/reference or perturbed/future climate. The model version in this dataset is a snapshot of the RWGEN Github repository, which contains new releases and developments: https://github.com/rwgen1/rwgen.
The observational climate inputs consist of historical hourly rainfall and daily weather time series for selected UK Met Office (UKMO) station locations. The historical time series are derived from the UKMO Met Office Integrated Data Archive System (MIDAS) Open datasets for the period 1853 to 2020. These time series can be used to train the RWGEN model for UK locations or catchments. Note that the data coverage is not consistent throughout the 1853-2020 period, with lower data availability prior to the mid-twentieth century. A user may also choose to use alternative data for model input.
RWGEN can be used for single site or spatial simulations of historical/reference or perturbed/future climate. The model version in this dataset is a snapshot of the RWGEN Github repository, which contains new releases and developments: https://github.com/rwgen1/rwgen.
The observational climate inputs consist of historical hourly rainfall and daily weather time series for selected UK Met Office (UKMO) station locations. The historical time series are derived from the UKMO Met Office Integrated Data Archive System (MIDAS) Open datasets for the period 1853 to 2020. These time series can be used to train the RWGEN model for UK locations or catchments. Note that the data coverage is not consistent throughout the 1853-2020 period, with lower data availability prior to the mid-twentieth century. A user may also choose to use alternative data for model input.
Publication date: 2024-06-17
Formats
Python, yaml, Comma-separated values (CSV)
Spatial information
Study area
Spatial representation type
Tabular (text)
Spatial reference system
WGS 84
Temporal information
Temporal extent
1853-01-01 to 2020-12-31
Temporal resolution
1 day, 1 hour
Provenance & quality
The model was developed within the UK Research and Innovation (UKRI)/UKMO UK Climate Resilience Programme as part of project NE/W007037/1. The model is provided as a Python package, with installation instructions, examples and documentation. The rainfall component of the model is based on the Neyman-Scott Rectangular Pulse process. The weather and potential evapotranspiration component is based on a regression model. It has been tested against other software (RainSim V3) and against observations (although like all models it has limitations and prospective users should ensure that the model is fit-for-purpose in their applications).
The historical climate time series were obtained by extracting data from the quality-controlled version (qc1) of the UKMO MIDAS-Open data collection. Further spot checks were undertaken to confirm that the extraction, processing and reformatting appear to have worked satisfactorily.
The historical climate time series were obtained by extracting data from the quality-controlled version (qc1) of the UKMO MIDAS-Open data collection. Further spot checks were undertaken to confirm that the extraction, processing and reformatting appear to have worked satisfactorily.
Licensing and constraints
This model is available under the terms of the Open Government Licence 
Cite this model as:
Pritchard, D. (2024). Code and UK observation-based historical climate input data for the Rainfall and Weather GENerator (RWGEN) stochastic model. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/44c577d3-665f-40de-adce-74ecad7b304a
Citations
Environment Agency (2025) Review of stochastic and other approaches in water resources planning. The UK Government. https://www.gov.uk/government/publications/review-of-stochastic-and-other-approaches-in-water-resources-planning
Correspondence/contact details
Other contacts
Publisher
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Rights holder
Newcastle University
david.pritchard@newcastle.ac.uk