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王晓欣, 姜大膀, 郎咸梅. CMIP5多模式预估的1.5℃升温背景下中国气温和降水变化[J]. 大气科学, 2019, 43(5): 1158-1170. DOI: 10.3878/j.issn.1006-9895.1810.18225
引用本文: 王晓欣, 姜大膀, 郎咸梅. CMIP5多模式预估的1.5℃升温背景下中国气温和降水变化[J]. 大气科学, 2019, 43(5): 1158-1170. DOI: 10.3878/j.issn.1006-9895.1810.18225
Temperature and Precipitation Changes over China under a 1.5℃ Global Warming Scenario Based on CMIP5 Models[J]. Chinese Journal of Atmospheric Sciences, 2019, 43(5): 1158-1170. DOI: 10.3878/j.issn.1006-9895.1810.18225
Citation: Temperature and Precipitation Changes over China under a 1.5℃ Global Warming Scenario Based on CMIP5 Models[J]. Chinese Journal of Atmospheric Sciences, 2019, 43(5): 1158-1170. DOI: 10.3878/j.issn.1006-9895.1810.18225

CMIP5多模式预估的1.5℃升温背景下中国气温和降水变化

Temperature and Precipitation Changes over China under a 1.5℃ Global Warming Scenario Based on CMIP5 Models

  • 摘要: 本文使用国际耦合模式比较计划第五阶段(CMIP5)中39个全球气候模式的试验数据,预估了相对于工业革命前期全球1.5℃升温背景下中国气温和降水变化。根据多模式中位数预估结果,在不同典型浓度路径(RCPs)情景下,相对于工业革命前期全球1.5℃升温分别发生在2034年(RCP2.6)、2033年(RCP4.5)和2029年(RCP8.5)。全球升温1.5℃时,中国年和季节气温平均上升1.8℃和1.6~2.1℃,其中冬季最强。增温总体上由南向北加强,青藏高原为高值中心。年和各季节增温均超过其自然内部变率,区域平均的信噪比分别为3.4和1.6~2.7。年和季节降水整体上在中国北方增加、华南减少;区域平均的年降水增加1.4%,季节降水增加0.1%~5.1%,冬季增幅最大。年和季节降水变化要远小于其自然内部变率,区域平均的信噪比仅为0.1和0.01~0.2。总体上,模式对气温预估的不确定性较小,对降水的偏大,其中对季节尺度预估的不确定性要高于年平均结果。

     

    Abstract: To better understand the climate changes over China associated with a 1.5℃ global warming world relative to the pre-industrial levels, the authors present an analysis based on numerical experiments undertaken using 39 Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. The results indicate that a global warming of 1.5℃ will occur in the median year 2034 for the representative concentration pathway (RCP) 2.6, 2033 for RCP4.5, and 2029 for RCP8.5. Under a 1.5℃ global warming world, annual and seasonal temperatures are projected to increase by an average of 1.8℃ and 1.6-2.1℃, respectively, with the strongest warming occurring in winter. Generally, the warming strengthens from south to north, and an amplification occurs in the Tibetan Plateau. Change signals of annual and seasonal temperatures exceed the local natural internal variability over the entire country, and the corresponding signal-to-noise ratios average 3.4 and 1.6-2.7, respectively. Annual and seasonal precipitation is expected to increase in northern China and decrease in southern China. Annual and seasonal precipitation averaged over the country increases by 1.4% and 0.1%-5.1%, respectively, with the greatest increase occurring in winter. On the whole, changes in annual and seasonal precipitation do not fall outside the local natural internal variability, and the signal-to-noise ratios averaged over the country are 0.1 and 0.01-0.2, respectively. Greater inter-model uncertainty occurs in the projection of changes in precipitation than that of changes in temperature, and the same holds for the seasonal projections.

     

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