Added value in regional climate modeling

被引:217
作者
Rummukainen, Markku [1 ]
机构
[1] Lund Univ, Ctr Environm & Climate Res, Lund, Sweden
关键词
BIAS CORRECTION; GREAT-LAKES; PROJECTIONS; IMPACT; SIMULATIONS; RESOLUTION; REPRESENTATION; PRECIPITATION; VARIABILITY; EXTREMES;
D O I
10.1002/wcc.378
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Regional climate modeling is a dynamical downscaling technique applied to the results of global climate models (GCMs) in order to acquire more information on climate simulations and climate change projections. GCMs and regional climate models (RCMs) have undergone considerable development over the past few decades, and both have increased in resolution. The higher-resolution edge of RCMs compared to GCMs still remains, however. This has been demonstrated in a number of specific studies. As GCMs operate on relatively coarse resolutions, they do not resolve more variable land forms and similar features that shape regional-scale climates. RCMs operate on higher resolutions than GCMs, by a factor of 2-10. Some RCMs now explore resolutions down to 1-5 km. This adds value in regions with variable orography, land-sea and other contrasts, as well as in capturing sharp, short-duration and extreme events. In contrast, large-scale and time-averaged fields, not least over smooth terrain and on scales that have been already skillfully resolved in GCMs, are not much affected. RCMs also generate additional detail compared to GCMs when in climate projection mode. Compared to the present-day climate for which observations exist, here the added value aspect is more complex to evaluate. Nevertheless, added value is meaningfully underlined when there is a clear physical context for it to appear in. In addition to climate modeling and model evaluation-related added value considerations, a significant relevant aspect of added value is the provision of regional scale information, including climate change projections, for climate impact, adaptation, and vulnerability research. (C) 2015 Wiley Periodicals, Inc.
引用
收藏
页码:145 / 159
页数:15
相关论文
共 75 条
[1]  
[Anonymous], 2007, General Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment
[2]  
[Anonymous], 2009, WORLD METEOROLOGICAL
[3]   An atmosphere-ocean regional climate model for the Mediterranean area: assessment of a present climate simulation [J].
Artale, Vincenzo ;
Calmanti, Sandro ;
Carillo, Adriana ;
Dell'Aquila, Alessandro ;
Herrmann, Marine ;
Pisacane, Giovanna ;
Ruti, Paolo M. ;
Sannino, Gianmaria ;
Struglia, Maria Vittoria ;
Giorgi, Filippo ;
Bi, Xunqiang ;
Pal, Jeremy S. ;
Rauscher, Sara .
CLIMATE DYNAMICS, 2010, 35 (05) :721-740
[4]   Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations [J].
Ban, Nikolina ;
Schmidli, Juerg ;
Schaer, Christoph .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2014, 119 (13) :7889-7907
[5]   Overestimation of Mediterranean summer temperature projections due to model deficiencies [J].
Boberg, Fredrik ;
Christensen, Jens H. .
NATURE CLIMATE CHANGE, 2012, 2 (06) :433-436
[6]   Bayesian multi-model projection of climate: bias assumptions and interannual variability [J].
Buser, Christoph M. ;
Kuensch, H. R. ;
Luethi, D. ;
Wild, M. ;
Schaer, C. .
CLIMATE DYNAMICS, 2009, 33 (06) :849-868
[7]   Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation? [J].
Chan, Steven C. ;
Kendon, Elizabeth J. ;
Fowler, Hayley J. ;
Blenkinsop, Stephen ;
Ferro, Christopher A. T. ;
Stephenson, David B. .
CLIMATE DYNAMICS, 2013, 41 (5-6) :1475-1495
[8]   Finding appropriate bias correction methods in downscaling precipitation for hydrologic impact studies over North America [J].
Chen, Jie ;
Brissette, Francois P. ;
Chaumont, Diane ;
Braun, Marco .
WATER RESOURCES RESEARCH, 2013, 49 (07) :4187-4205
[9]   Uncertainty of downscaling method in quantifying the impact of climate change on hydrology [J].
Chen, Jie ;
Brissette, Francois P. ;
Leconte, Robert .
JOURNAL OF HYDROLOGY, 2011, 401 (3-4) :190-202
[10]   Weight assignment in regional climate models [J].
Christensen, Jens Hesselbjerg ;
Kjellstrom, Erik ;
Giorgi, Filippo ;
Lenderink, Geert ;
Rummukainen, Markku .
CLIMATE RESEARCH, 2010, 44 (2-3) :179-194