University of Reading Research Data Archive

A new multi-variable benchmark for Last Glacial Maximum climate simulations

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Description

Reconstruction of climate anomalies for the Last Glacial Maximum (LGM, ca 21,000 years ago), made by combining pollen based reconstructions (from Bartlein et al. 2011) and averaged outputs of LGM simulations from the 3rd round of the Palaeoclimate Model Intercomparison Project (PMIP, Braconnot et al. 2011), under a variational data assimilation technique. This reconstruction is designed to be used for data-model comparison, specifically against the results of PMIP4. The dataset consists of 6 variables: moisture index (the ratio precipitation and equilibrium evapotranspiration), mean annual precipitation (mm), mean annual temperature (degrees C), mean temperature of the coldest month (degrees C), mean temperature of the warmest month (degrees C), growing degree days above 5 degrees C (day degrees C). The standard deviation of these variables is also given.

This dataset supersedes the version published at http://dx.doi.org/10.17864/1947.206, where the spatial and temporal correlations used with the PMIP data were based on a Gaussian function, instead of a Bessel function.

Resource Type: Dataset
Creators: Cleator, Sean, Harrison, Sandy, Nichols, Nancy, Prentice, Iain Colin, Roulstone, Ian
Rights-holders: Sean F. Cleator, University of Surrey, University of Reading, Imperial College London
Data Publisher: University of Reading
Publication Date: 2019
Data last accessed: 17 November 2019
DOI: http://dx.doi.org/10.17864/1947.229
Metadata Record URL: https://researchdata.reading.ac.uk/id/eprint/229
Organisational units: Faculty of Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Faculty of Science > School of Mathematical, Computational and Physical Sciences > Department of Mathematics and Statistics
Participating Organisations: University of Surrey, University of Reading, Imperial College London
Keywords: Last Glacial Maximum, reconstruction, pollen, PMIP3, 3D-Var
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