4.7 Article

weather@ home 2: validation of an improved global-regional climate modelling system

Journal

GEOSCIENTIFIC MODEL DEVELOPMENT
Volume 10, Issue 5, Pages 1849-1872

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/gmd-10-1849-2017

Keywords

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Funding

  1. Natural Environment Research Council (NERC)
  2. University of Oxford [NE/L010364/1]
  3. University of Bristol [NE/L010399/1]
  4. Cranfield University [NE/L010186/1]
  5. Met Office
  6. Centre for Ecology and Hydrology [NE/L010208/1]
  7. USDA National Institute of Food and Agriculture [2013-67003-20652]
  8. Natural Environment Research Council [NE/L010364/1] Funding Source: researchfish
  9. NERC [NE/L010364/1] Funding Source: UKRI

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Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home sys-tem, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

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