Multi-thousand-year simulations of December-February precipitation and zonal upper-level wind

• Main Authors: Emanuele Bevacqua, Peter Watson, Sarah Sparrow, David Wallom
• Format: Dataset
• Language: unknown
• Published: 2020
• Subjects: multi-thousand-year ensemble simulations; large ensemble; climate change; precipitation; simulations; zonal wind; climate model simulations; Sea ice
• Online Access: https://zenodo.org/record/4311221; https://doi.org/10.5281/zenodo.4311221

This dataset contains multi-thousand-year ensemble simulations of wintertime (December-February) precipitation total and average zonal winds at 250 hPa and 850 hPa. It includes data in a present-day scenario (2006-2015) and two future scenarios within which the world would be 1.5°C and 2.0°C warmer than pre-industrial conditions in 1850-1900. The simulations were run through the global model of the atmosphere and land surface HadAM4 (Williams et al., 2003) with a horizontal resolution of 5/6°x5/9° (approximately 60km in middle latitudes) and 38 vertical levels and a large ensemble. Following the HAPPI experiment design described by Mitchell et al. (2017), simulations were driven by prescribed fields of sea ice concentration, sea surface temperature, and atmospheric gas concentrations. The prescribed fields are observations for the present-day scenario. For future simulations, the prescribed fields were modified based on changes derived from CMIP5 multi-model means. The different realisations of the large ensemble were obtained through perturbing the initial conditions of each ensemble member on November 1st. For more details, see the description in Watson et al. (2020), who present the dataset, and in Bevacqua et al. (2021) where the dataset was used to study the spatial footprint of wintertime precipitation extremes. IMPORTANT: Note that a small fraction of the ensemble members is repeated in the dataset. Duplicates should be identified (for example, via the function duplicated() in the R software) and removed prior to any analysis. We thank JASMIN and CEDA for providing the facilities required to work with climateprediction.net. We thank the volunteers who have donated their computing time to climateprediction.net.