A Dataset of Large Ensemble of CMIP6-based Transient Climate Scenarios for Impact Assessment in Great Britain.

Under the extant threat of climate change, impact assessment studies are essential to investigate and quantify the severity of the potential impacts, and support recommendations for mitigation strategies with foresight. Future climate change scenarios are therefore crucial for underpinning impact studies. Here, transient climate scenarios are important as they provide a more realistic and dynamic evolution of future climate conditions over time, rather than only static climate scenarios. It is also important to downscale climate projection of Global Climate Models (GCMs) from coarse spatial and temporal resolution to local scale site-specific daily climate scenarios which have a sufficiently large number of years or realisations for accounting for inter-annual variability and detecting rare extreme climatic events. In the new dataset presented herein, transient future climate scenarios were generated at 26 representative sites across Great Britain (GB) using the Long Ashton Research Station Weather Generator (LARS-WG 8.0), based on climate projections from a subset of five GCMs from the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble and two emission scenarios. For each site, 100 realisations of continuous transient time series of daily weather (minimum air temperature, maximum air temperature, rainfall and solar radiation) over the period 2020 to 2090 were generated. The use of a subset of five GCMs reduces computational requirements substantially for impact assessments, while allowing quantification of uncertainties in impacts related to uncertainty in future climate projections arising from GCMs. The dataset can be used to underpin assessments of future climate change risk and vulnerability, and their temporal patterns and progressive changes over time. Our data are designed to be used as a time series of climatic input to impact models for climate change assessments continuously over time related to various fields and disciplines, including land and water resources, agriculture and food production, soil carbon cycle, ecology and epidemiology, and human health and welfare. Various key stakeholders, such as researchers, breeders, farm managers, social and public sector advisers, policymakers and planners, may benefit from this new transient dataset for investigating, forecasting, designing and prioritising adaptive and mitigation strategies under changing climate.