Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes

2009 ◽  
Vol 29 (3) ◽  
pp. 385-416 ◽  
Author(s):  
H. J. Fowler ◽  
M. Ekström
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Precipitation Extremes ◽  
Seasonal Precipitation ◽  
Model Ensemble

Strengthening forecasts of climate change impacts with multi-model ensemble averaged projections using MAGICC/SCENGEN 5.3

Ecography ◽  
2012 ◽  
Vol 35 (1) ◽  
pp. 4-8 ◽  
Author(s):  
Damien A. Fordham ◽  
Tom M. L. Wigley ◽  
Michael J. Watts ◽  
Barry W. Brook
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Model Ensemble

scholarly journals Climate change impacts on Great Lakes Basin precipitation extremes

2014 ◽  
Vol 119 (18) ◽  
pp. 10,799-10,812 ◽  
Author(s):  
Marc d'Orgeville ◽  
W. Richard Peltier ◽  
Andre R. Erler ◽  
Jonathan Gula
Keyword(s):  
Climate Change ◽  
Great Lakes ◽  
Climate Change Impacts ◽  
Precipitation Extremes ◽  
Great Lakes Basin

scholarly journals A Projection of Extreme Precipitation Based on a Selection of CMIP5 GCMs over North Korea

2019 ◽  
Vol 11 (7) ◽  
pp. 1976 ◽  
Author(s):  
Jang Sung ◽  
Minsung Kwon ◽  
Jong-June Jeon ◽  
Seung Seo
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Daily Maximum ◽  
Climate Change Scenarios ◽  
Model Ensemble ◽  
Model Variability ◽  
Cmip5 Gcms ◽  
Selection Of

The numerous choices between climate change scenarios makes decision-making difficult for the assessment of climate change impacts. Previous studies have used climate models to compare performance in terms of simulating observed climates or preserving model variability among scenarios. In this study, the Katsavounidis-Kuo-Zhang algorithm was applied to select representative climate change scenarios (RCCS) that preserve the variability among all climate change scenarios (CCS). The performance of multi-model ensemble of RCCS was evaluated for reference and future climates. It was found that RCCS was well suited for observations and multi model ensemble of all CCS. Using the RCCS under RCP (Representative Concentration Pathway) 8.5, the future extreme precipitation was projected. As a result, the magnitude and frequency of extreme precipitation increased towards the farther future. Especially, extreme precipitation (daily maximum precipitation of 20-year return-period) during 2070-2099, was projected to occur once every 8.3-year. The RCCS employed in this study is able to successfully represent the performance of all CCS, therefore, this approach can give opportunities managing water resources efficiently for assessment of climate change impacts.

Climate change impacts on crop yields in Ethiopia

2019 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)
Keyword(s):  
Climate Change ◽  
Crop Yields ◽  
Climate Change Impacts
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