scholarly journals Numerical investigation of an extreme storm with the Canadian Regional Climate Model: the case study of windstorm VIVIAN , Switzerland, February 27, 1990

2001 ◽  
Vol 18 (1-2) ◽  
pp. 145-168 ◽  
Author(s):  
S. Goyette ◽  
M. Beniston ◽  
D. Caya ◽  
R. Laprise ◽  
P. Jungo
Keyword(s):  
Regional Climate Model ◽  
Numerical Investigation ◽  
Climate Model ◽  
Regional Climate ◽  
Canadian Regional Climate Model ◽  
Extreme Storm

Simulation of an extreme rainfall event over Mumbai using a regional climate model: a case study

2021 ◽  
Vol 134 (1) ◽  
Author(s):  
Manas Pant ◽  
Soumik Ghosh ◽  
Shruti Verma ◽  
Palash Sinha ◽  
R. K. Mall ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event

Quantifying internal variability in a regional climate model: a case study for Southern Africa

2011 ◽  
Vol 37 (7-8) ◽  
pp. 1335-1356 ◽  
Author(s):  
Julien Crétat ◽  
Clémence Macron ◽  
Benjamin Pohl ◽  
Yves Richard
Keyword(s):  
Regional Climate Model ◽  
Southern Africa ◽  
Climate Model ◽  
Regional Climate ◽  
Internal Variability

scholarly journals Brief Communication: An update of the article "Modeling flood damages under climate change conditions – a case study for Germany"

2015 ◽  
Vol 3 (12) ◽  
pp. 7231-7245
Author(s):  
F. F. Hattermann ◽  
S. Huang ◽  
O. Burghoff ◽  
P. Hoffmann ◽  
Z. W. Kundzewicz
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Large Scale ◽  
Considerable Increase ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Flood Damages

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood related losses can be expected in future, warmer, climate. However, the general significance of the study was limited by the fact that outcome of only one Global Climate Model (GCM) was used as large scale climate driver, while many studies report that GCM models are often the largest source of uncertainty in impact modeling. Here we show that a much broader set of global and regional climate model combinations as climate driver shows trends which are in line with the original results and even give a stronger increase of damages.

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