Abstract
By using observational daily precipitation data over the Yangtze–Huaihe River basin, ERA-40 data, and the data from eight CMIP5 climate models, statistical downscaling models are constructed based on BP-CCA (combination of empirical orthogonal function and canonical correlation analysis) to project future changes of precipitation. The results show that the absolute values of domain-averaged precipitation relative errors of most models are reduced from 8%–46% to 1%–7% after statistical downscaling. The spatial correlations are all improved from less than 0.40 to more than 0.60. As a result of the statistical downscaling multimodel ensemble (SDMME), the relative error is improved from–15.8% to–1.3%, and the spatial correlation increases significantly from 0.46 to 0.88. These results demonstrate that the simulation skill of SDMME is relatively better than that of the multimodel ensemble (MME) and the downscaling of most individual models. The projections of SDMME reveal that under the RCP (Representative Concentration Pathway) 4.5 scenario, the projected domain-averaged precipitation changes for the early (2016–2035), middle (2046–2065), and late (2081–2100) 21st century are–1.8%, 6.1%, and 9.9%, respectively. For the early period, the increasing trends of precipitation in the western region are relatively weak, while the precipitation in the east shows a decreasing trend. Furthermore, the reliability of the projected changes over the area east of 115 ◦ E is higher than that in the west. The stations with significant increasing trends are primarily located over the western region in both the middle and late periods, with larger magnitude for the latter. Stations with high reliability mainly appear in the region north of 28.5 ◦ N for both periods.
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Acknowledgments
We acknowledge the modeling groups listed in Table 1 of this paper for making their simulations available for analysis, the PCMDI for collecting and archiving the CMIP5 model output, and the World Climate Research Programme’s Working Group on Coupled Modelling.
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Supported by the National Natural Science Foundation of China (41230528), Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions, and National Key Pesearch and Development Program of China (2016YFA0600402).
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Wu, D., Jiang, Z. & Ma, T. Projection of summer precipitation over the Yangtze–Huaihe River basin using multimodel statistical downscaling based on canonical correlation analysis. J Meteorol Res 30, 867–880 (2016). https://doi.org/10.1007/s13351-016-6030-1
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DOI: https://doi.org/10.1007/s13351-016-6030-1