Precipitation in the EURO-CORDEX 0.11∘ and 0.44∘ simulations: high resolution, high benefits? View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-06-25

AUTHORS

A. F. Prein, A. Gobiet, H. Truhetz, K. Keuler, K. Goergen, C. Teichmann, C. Fox Maule, E. van Meijgaard, M. Déqué, G. Nikulin, R. Vautard, A. Colette, E. Kjellström, D. Jacob

ABSTRACT

In the framework of the EURO-CORDEX initiative an ensemble of European-wide high-resolution regional climate simulations on a 0.11∘(∼12.5km)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.11^{\circ }\,({\sim}12.5\,\hbox {km})$$\end{document} grid has been generated. This study investigates whether the fine-gridded regional climate models are found to add value to the simulated mean and extreme daily and sub-daily precipitation compared to their coarser-gridded 0.44∘(∼50km)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.44^{\circ }\,({\sim}50\,\hbox {km})$$\end{document} counterparts. Therefore, pairs of fine- and coarse-gridded simulations of eight reanalysis-driven models are compared to fine-gridded observations in the Alps, Germany, Sweden, Norway, France, the Carpathians, and Spain. A clear result is that the 0.11∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.11^{\circ }$$\end{document} simulations are found to better reproduce mean and extreme precipitation for almost all regions and seasons, even on the scale of the coarser-gridded simulations (50 km). This is primarily caused by the improved representation of orography in the 0.11∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.11^{\circ }$$\end{document} simulations and therefore largest improvements can be found in regions with substantial orographic features. Improvements in reproducing precipitation in the summer season appear also due to the fact that in the fine-gridded simulations the larger scales of convection are captured by the resolved-scale dynamics . The 0.11∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.11^{\circ }$$\end{document} simulations reduce biases in large areas of the investigated regions, have an improved representation of spatial precipitation patterns, and precipitation distributions are improved for daily and in particular for 3 hourly precipitation sums in Switzerland. When the evaluation is conducted on the fine (12.5 km) grid, the added value of the 0.11∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.11^{\circ }$$\end{document} models becomes even more obvious. More... »

PAGES

383-412

References to SciGraph publications

  • 2014-06-01. Heavier summer downpours with climate change revealed by weather forecast resolution model in NATURE CLIMATE CHANGE
  • 2013-07-23. EURO-CORDEX: new high-resolution climate change projections for European impact research in REGIONAL ENVIRONMENTAL CHANGE
  • 2014-08-02. Benefit of convection permitting climate model simulations in the representation of convective precipitation in CLIMATE DYNAMICS
  • 1996-06. Design and performance of a new cloud microphysics scheme developed for the ECHAM general circulation model in CLIMATE DYNAMICS
  • 2007-03-17. Evaluating the performance and utility of regional climate models: the PRUDENCE project in CLIMATIC CHANGE
  • 2015-10-13. Daily precipitation statistics in a EURO-CORDEX RCM ensemble: added value of raw and bias-corrected high-resolution simulations in CLIMATE DYNAMICS
  • 2013-04-05. The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project in CLIMATE DYNAMICS
  • 2012-11-01. Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation? in CLIMATE DYNAMICS
  • 2006-10-27. The impact of lateral boundary data errors on the simulated climate of a nested regional climate model in CLIMATE DYNAMICS
  • 1993. Convective Parameterization for Mesoscale Models: The Kain-Fritsch Scheme in THE REPRESENTATION OF CUMULUS CONVECTION IN NUMERICAL MODELS
  • 2009-11-08. The influence of interpolation and station network density on the distributions and trends of climate variables in gridded daily data in CLIMATE DYNAMICS
  • 2008-04-28. Sensitivity of climate models to seasonal variability of snow-free land surface albedo in THEORETICAL AND APPLIED CLIMATOLOGY
  • 2013-04-02. Added value of convection permitting seasonal simulations in CLIMATE DYNAMICS
  • 1979-09. A parametric model of vertical eddy fluxes in the atmosphere in BOUNDARY-LAYER METEOROLOGY
  • 2007-03-17. An inter-comparison of regional climate models for Europe: model performance in present-day climate in CLIMATIC CHANGE
  • 2012-01-10. Changes in hail and flood risk in high-resolution simulations over Colorado's mountains in NATURE CLIMATE CHANGE
  • 2009-06-23. Resolution effects on regional climate model simulations of seasonal precipitation over Europe in CLIMATE DYNAMICS
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    URI

    http://scigraph.springernature.com/pub.10.1007/s00382-015-2589-y

    DOI

    http://dx.doi.org/10.1007/s00382-015-2589-y

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    https://app.dimensions.ai/details/publication/pub.1015079770


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