Regional Climate Change Scenarios over the United States Produced with a Nested Regional Climate Model

1994 ◽  
Vol 7 (3) ◽  
pp. 375-399 ◽  
Author(s):  
Filippo Giorgi ◽  
Christine Shields Brodeur ◽  
Gary T. Bates
Keyword(s):  
Climate Change ◽  
United States ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Change ◽  
The United States ◽  
Climate Change Scenarios

The Potential Impact of Regional Climate Change on Fire Weather in the United States

2014 ◽  
Vol 105 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ying Tang ◽  
Shiyuan Zhong ◽  
Lifeng Luo ◽  
Xindi Bian ◽  
Warren E. Heilman ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Regional Climate ◽  
Regional Climate Change ◽  
The United States ◽  
Fire Weather ◽  
Potential Impact

Evaluation of the Surface Climatology over the Conterminous United States in the North American Regional Climate Change Assessment Program Hindcast Experiment Using a Regional Climate Model Evaluation System

2013 ◽  
Vol 26 (15) ◽  
pp. 5698-5715 ◽  
Author(s):  
Jinwon Kim ◽  
Duane E. Waliser ◽  
Chris A. Mattmann ◽  
Linda O. Mearns ◽  
Cameron E. Goodale ◽  
...  
Keyword(s):  
United States ◽  
Regional Climate Model ◽  
Great Plains ◽  
Model Evaluation ◽  
Evaluation System ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Change ◽  
The North ◽  
Climate Change Assessment

Abstract Surface air temperature, precipitation, and insolation over the conterminous United States region from the North American Regional Climate Change Assessment Program (NARCCAP) regional climate model (RCM) hindcast study are evaluated using the Jet Propulsion Laboratory (JPL) Regional Climate Model Evaluation System (RCMES). All RCMs reasonably simulate the observed climatology of these variables. RCM skill varies more widely for the magnitude of spatial variability than the pattern. The multimodel ensemble is among the best performers for all these variables. Systematic biases occur across these RCMs for the annual means, with warm biases over the Great Plains (GP) and cold biases in the Atlantic and the Gulf of Mexico (GM) coastal regions. Wet biases in the Pacific Northwest and dry biases in the GM/southern Great Plains also occur in most RCMs. All RCMs suffer problems in simulating summer rainfall in the Arizona–New Mexico region. RCMs generally overestimate surface insolation, especially in the eastern United States. Negative correlation between the biases in insolation and precipitation suggest that these two fields are related, likely via clouds. Systematic variations in biases for regions, seasons, variables, and metrics suggest that the bias correction in applying climate model data to assess the climate impact on various sectors must be performed accordingly. Precipitation evaluation with multiple observations reveals that observational data can be an important source of uncertainties in model evaluation; thus, cross examination of observational data is important for model evaluation.

scholarly journals Impact of climate changes on water resources of Kuialnyk Liman catchment in scenario climate conditions

2017 ◽  
pp. 189-195
Author(s):  
N.S. Loboda ◽  
Y.V. Bozhok
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Regional Climate Model ◽  
Climate Model ◽  
Climatic Factors ◽  
Global Climate ◽  
Regional Climate ◽  
Climate Change Scenarios ◽  
Climate Conditions ◽  
Surrounding Areas

The actuality of research is conditioned by necessity of water regime determination under climate change for substantiate management its water resources in future. The purpose of investigation is evaluation of changes in water resources of Kuyalnyk Liman catchment under climate change. The main method of research is model "climate- runoff ", developed at the Odessa State Environmental University. Database of global climate change scenarios A1B (realized in regional climate model REMO) and A2 (developed under the regional climate model RCA) was used. The analysis of fluctuation regularity of climatic factors of the flow formation on the Kuyalnyk  Liman catchment and surrounding areas according to selected scenarios using  difference-integral curves are done. Changes in precipitation and the maximum possible evaporation for the 30-year intervals up to the year 2100 (scenario A1D) or up to the year 2050 (scenario A2) are analyzed. The main tendencies in water resources of Kuyalnyk Liman using the model "climate- runoff" in the future are established. It is shown that according to the scenario A1B by the middle of XXI century possible reduction of water resources in the Kuyalnyk Liman catchment is 40%. According to the scenario A2 water resources in northern part of the basin can grow on average by 20-30%, and in the southern part runoff can be reduced on average by 10%.

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