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Ensemble of global climate simulations for temperature in historical, 1.5 °C and 2.0 °C scenarios from HadAM4.
Lizana, Jesús; Miranda, Nicole D; Sparrow, Sarah N; Watson, Peter A G; Zachau Walker, Miriam; Wallom, David C H; McCulloch, Malcolm D.
Affiliation
  • Lizana J; Future of Cooling Programme, Oxford Martin School, University of Oxford, Oxford, OX1 3BD, UK.
  • Miranda ND; Energy and Power Group, Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK.
  • Sparrow SN; Future of Cooling Programme, Oxford Martin School, University of Oxford, Oxford, OX1 3BD, UK. nicole.miranda@eng.ox.ac.uk.
  • Watson PAG; Energy and Power Group, Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK. nicole.miranda@eng.ox.ac.uk.
  • Zachau Walker M; Oxford e-Research Centre, University of Oxford, Oxford, OX1 3QG, UK.
  • Wallom DCH; School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK.
  • McCulloch MD; Energy and Power Group, Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK.
Sci Data ; 11(1): 578, 2024 Jun 04.
Article in En | MEDLINE | ID: mdl-38834583
ABSTRACT
Large ensembles of global temperature are provided for three climate scenarios historical (2006-16), 1.5 °C and 2.0 °C above pre-industrial levels. Each scenario has 700 members (70 simulations per year for ten years) of 6-hourly mean temperatures at a resolution of 0.833° ´ 0.556° (longitude ´ latitude) over the land surface. The data was generated using the climateprediction.net (CPDN) climate simulation environment, to run HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre. Biases in simulated temperature were identified and corrected using quantile mapping with reference temperature data from ERA5. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository as NetCDF V4 files.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Data Year: 2024 Document type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Data Year: 2024 Document type: Article Affiliation country: United kingdom