Comparison of spatial downscaling methods of general circulation model results to study climate variability during the Last Glacial Maximum

Latombe, Guillaume; Burke, Ariane; Vrac, Mathieu; Levavasseur, Guillaume; Dumas, Christophe; Kageyama, Masa; Ramstein, Gilles

doi:https://doi.org/10.5194/gmd-11-2563-2018

Articles | Volume 11, issue 7

https://doi.org/10.5194/gmd-11-2563-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-11-2563-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 7

Model description paper

|

03 Jul 2018

Model description paper |

| 03 Jul 2018

Comparison of spatial downscaling methods of general circulation model results to study climate variability during the Last Glacial Maximum

Guillaume Latombe, Ariane Burke, Mathieu Vrac, Guillaume Levavasseur, Christophe Dumas, Masa Kageyama, and Gilles Ramstein

Supplement

https://doi.org/10.5194/gmd-11-2563-2018-supplement

Model code and software

Latombe et al. scripts and data G. Latombe, A. Burke, M. Vrac, G. Levavasseur, C. Dumas, M. Kageyama, and G. Ramstein https://doi.org/10.6084/m9.figshare.5487145

Short summary

It is still unclear how climate conditions, and especially climate variability, influenced the spatial distribution of past human populations. Global climate models (GCMs) cannot simulate climate at sufficiently fine scale for this purpose. We propose a statistical method to obtain fine-scale climate projections for 15 000 years ago from coarse-scale GCM outputs. Our method agrees with local reconstructions from fossil and pollen data, and generates sensible climate variability maps over Europe.