4.6 Article

An intercomparison of multiple statistical downscaling methods for daily precipitation and temperature over China: future climate projections

期刊

CLIMATE DYNAMICS
卷 52, 期 11, 页码 6749-6771

出版社

SPRINGER
DOI: 10.1007/s00382-018-4543-2

关键词

Statistical downscaling; Climate change; Intercomparison; China; Extreme

资金

  1. National Key Research and Development Program of China [2017YFA0603803, 2016YFC0202000]
  2. National Natural Science Foundation of China [91425304, 41575099, 41275004]
  3. Chinese Jiangsu Collaborative Innovation Center for Climate Change
  4. World Climate Research Programme

向作者/读者索取更多资源

In this study, we use four statistical downscaling methods to statistically downscale seven Coupled Model Intercomparison Project (CMIP5) Global Climate Models (GCMs) and project the changes in precipitation and temperature over China under RCP4.5 and RCP8.5 emission scenarios. The four statistical downscaling methods are bias-correction and spatial downscaling (BCSD), bias-correction and climate imprint(BCCI), bias correction constructed analogues with quantile mapping reordering(BCCAQ), and cumulative distribution function transform(CDF-t). Though large inter-model variability exists in the distribution and magnitude of changes in projected precipitation, particularly for wet spell length (CWD), all downscaling methods generally project a consistent enhancement of precipitation in both summer and winter over most parts of China. For the arid and semiarid Northwest China, the shortened dry spell length (CDD) is accompanied by the pronouncedly intensified very wet days (R95p), as well as the increase in maximum 5-day precipitation amount (Rx5day). In contrast, southeastern regions may experience more consecutive dry days and more severe wet precipitation extremes. The projected changes from different downscaling techniques are fairly similar for temperature, apart from the diurnal temperature range for BCSD. Warming is projected across the whole domain with larger magnitude over the north and in winter under RCP8.5. More summer days and fewer frost days would appear in the future. The bias correction components of downscaling methods cause a higher degree of agreement among models, and the downscaled results generally retain the main climate change signal of the driving models.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据