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. Full details about this application can be found at https://doi.org/10.5285/44c577d3-665f-40de-adce-74ecad7b304a

[This application is embargoed until January 1, 2025]. A collection of python and bash scripts to implement, train and deploy a generative adversarial network for population genetic inferences. The networks have been tuned to be deployed to genomic data from Anopheles mosquitoes. However, the general framework can be applied to other species. It requires the input data to be in Variant Call Format (VCF) format and the simulations need to be in msprime format. Full details about this application can be found at https://doi.org/10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54

This dataset contains the material required to reproduce 3D volumetric data describing the energy density of photons within a simulated environment and heatmaps and journey lengths for ensembles of weighted walkers experiencing specific simulated environments. The dataset includes source code for snapshots of the Monte Carlo Radiative Transfer (MCRT) code used to run simulations, the weighted random walking code used to emulate the behaviour of animals experiencing the simulated environment, as well as inputs and configuration files for both codes. The MCRT software outputs 3D volumetric data describing the energy density of photons within the simulated environment. Then, the weighted random walk code takes 2D planes from this data and produces heatmaps and journey lengths for ensembles of weighted walkers experiencing these simulated environments. Full details about this application can be found at https://doi.org/10.5285/1b64b008-8c20-4dd4-bf54-bf1894767a56