Published December 10, 2020 | Version 1.0.0
Dataset Open

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

  • 1. Department of Meteorology, University of Reading, Reading, United Kingdom
  • 2. School of Geographical Sciences, University of Bristol, Bristol, United Kingdom
  • 3. Oxford e-Reseach Centre, Engineering Science, University of Oxford, Oxford, United Kingdom

Description

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. 

Notes

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.

Files

Files (8.5 GB)

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md5:ef68fe65514a52555ffac6603b859806
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md5:c5f4664f33f1e19336a8e0fdff2f67c2
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md5:05e7f5428e1b28fff8242b2c807418bd
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Additional details

References

  • Bevacqua, E., Shepherd, T.G., Watson, P.A.G., Sparrow, S., Wallom, D., and Mitchell, D.: Larger spatial footprint of wintertime total precipitation extremes in a warmer climate, In review, 2021.
  • Mitchell, D., AchutaRao, K., Allen, M., Bethke, I., Beyerle, U., Ciavarella, A., Forster, P. M., Fuglestvedt, J., Gillett, N., Haustein, K., Ingram, W., Iversen, T., Kharin, V., Klingaman, N., Massey, N., Fischer, E., Schleussner, C.-F., Scinocca, J., Seland, Ø., Shiogama, H., Shuckburgh, E., Sparrow, S., Stone, D., Uhe, P., Wallom, D., Wehner, M., and Zaaboul, R.: Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design, Geosci. Model Dev., 10, 571–583, https://doi.org/10.5194/gmd-10-571-2017, 2017.
  • Watson, P., Sparrow, S., Ingram, W., Wilson, S., Marie, D., Zappa, G., Jones, R., Mitchell, D., Woollings, T., and Allen, M.: Multi-thousand member ensemble atmospheric simulations with global 60km resolution using climateprediction.net, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10895, https://doi.org/10.5194/egusphere-egu2020-10895, 2020.
  • Williams, K., Ringer, M., & Senior, C.: Evaluating the cloud response to climate change and current climate variability. Climate Dynamics, 20 (7-8), 705-721, 2003.