2016
DOI: 10.1016/j.atmosres.2016.03.023
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Statistical downscaling of CMIP5 multi-model ensemble for projected changes of climate in the Indus River Basin

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Cited by 113 publications
(80 citation statements)
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References 49 publications
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“…For the purpose of Statistical inference in the future, the statistical relationship between observed and simulated historical data is established. As a bias correction method, the Equidistant Cumulative Distribution Functions (EDCDF) method is used in this study [35,36]. The Cumulative Distribution Function (CDF) of observed, simulated and predicted data is established to calculate to cumulative frequency of a certain value in the future.…”
Section: Bias Correction Methodsmentioning
confidence: 99%
“…For the purpose of Statistical inference in the future, the statistical relationship between observed and simulated historical data is established. As a bias correction method, the Equidistant Cumulative Distribution Functions (EDCDF) method is used in this study [35,36]. The Cumulative Distribution Function (CDF) of observed, simulated and predicted data is established to calculate to cumulative frequency of a certain value in the future.…”
Section: Bias Correction Methodsmentioning
confidence: 99%
“…The results of the hindcast analysis for the period 2006–2015 show a good representation of the trends, seasonality, and spatial correlations, while the absolute annual BIAS and temporal correlations differ quite strongly. Compared with the simulation results by Rajbhandari et al () and Su et al (), who used the RCM PRECIS driven by HadCM3 and the multi‐model ensemble of 21 CMIP5 GCMs over the IRB, respectively, CCLM performs better in reproducing the amounts and annual cycles of mean precipitation and annual precipitation, as well as the spatial patterns. Considering the biases and inaccuracies mentioned earlier, CCLM is a robust RCM and can be used to project the temperature and precipitation in the IRB.…”
Section: Conclusion and Discussionmentioning
confidence: 79%
“…strong increase over the Indus Delta and in the northern mountainous areas. Similar results of warming in the upper IRB are also projected by other RCMs and downscaled GCMs (Kazmi et al , ; Rajbhandari et al , ; Su et al , ). Based on the results by Ali et al () the GCM CCAM and the RCM RegCM also project a consistent increase in temperature over the northwestern mountainous part of the IRB under RCP8.5.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…Scenarios are the key tools used to describe possible climatic, societal, and environmental changes in the future (Moss et al, ; O'Neill et al, ). The current parallel scenario development process began with representative concentration pathways, which reflect the atmospheric concentration targets of greenhouse gases and have been widely used to understand potential changes to the future climate (Huang et al, ; Su et al, ; Taylor et al, ; Van Vuuren et al, ). Future socioeconomic conditions that connect the impact of, adaptation to, and mitigation of climate change are generating increasing concern among multiple stakeholders regarding mitigation targets and liability (Kriegler et al, ).…”
Section: Introductionmentioning
confidence: 99%