气候变化研究进展 ›› 2019, Vol. 15 ›› Issue (2): 140-149.doi: 10.12006/j.issn.1673-1719.2018.153

• 气候系统变化 • 上一篇    下一篇

6.25 km高分辨率降尺度数据对雄安新区及整个京津冀地区未来极端气候事件的预估

石英,韩振宇(),徐影,周波涛,吴佳   

  1. 中国气象局国家气候中心,北京100081
  • 收稿日期:2018-11-02 修回日期:2018-12-07 出版日期:2019-03-30 发布日期:2019-03-30
  • 作者简介:石英,女,副研究员, shiying@cma.cn
  • 基金资助:
    国家重点研发计划(2018YFA0606301,2017YFA0605002);国家自然科学基金项目(41805063,41375104)

Future changes of climate extremes in Xiongan New Area and Jing-Jin-Ji district based on high resolution (6.25 km) combined statistical and dynamical downscaling datasets

Ying SHI,Zhen-Yu HAN(),Ying XU,Bo-Tao ZHOU,Jia WU   

  1. National Climate Center, China Meteorological Administration, Beijing 100081, China
  • Received:2018-11-02 Revised:2018-12-07 Online:2019-03-30 Published:2019-03-30

摘要:

基于RCP4.5情景下6.25 km高分辨率统计降尺度数据,使用国际上通用的极端气候事件指数,分析雄安新区及整个京津冀地区未来极端气候事件的可能变化。首先对当代模拟结果进行评估,结果表明,集合平均模拟可以较好地再现大部分极端气候事件指数的分布,且对与气温有关的极端气候事件指数模拟效果较好。但也存在一定偏差,特别是对连续干旱日数(CDD)的模拟效果相对较差。集合平均的预估结果表明,未来在全球变暖背景下,雄安新区及整个京津冀地区均表现为极端暖事件增多,极端冷事件减少,连续干旱日数减少,极端强降水事件增多。具体来看,到21世纪末期,日最高气温最高值(TXx)和日最低气温最低值(TNn)在整个区域上都是增加的,大部分地区增加值分别超过2.4℃和3.2℃;夏季日数(SU)和热带夜数(TR)也都表现为增加,但两者的变化分布基本相反,其中SU在山区增加幅度较大,平原地区增加幅度较小,而TR在平原地区的增加值较山区更显著,两个指数未来增加值分别为20~40 d和5~40 d;霜冻日数(FD)和冰冻日数(ID)都表现为减少,减少值分别超过10 d和5 d;与降水有关的极端气候事件指数,CDD、降雨日数(R1mm)和中雨日数(R10mm)的变化均以减少为主,但数值较小,一般都在?10%~0之间;最大5 d降水量(RX5day)、降水强度(SDII)和大雨日数(R20mm)主要表现为增加,增加值一般在0~25%之间。从区域平均的变化来看,与气温有关的极端气候事件指数的变化趋势较为显著,与降水有关的极端气候事件指数变化趋势较小。两个区域对比来看,雄安新区模式间的不确定性更大,反映出模式对较小区域模拟的不足。

关键词: 区域气候模式, 雄安新区, 京津冀地区, 极端事件

Abstract:

Future changes of climate extremes in the 21st century over Xiongan New Area and Jing-Jin-Ji district were investigated based on high resolution (6.25 km) combined statistical and dynamical downscaling datasets, which were produced using the observation of CLDAS, five sets of regional climate change simulations by RegCM4.4, and statistical downscaling with quantile mapping. Of that, the RegCM4.4 simulations were conducted over East Asia under RCP4.5 scenario driven by five different CMIP5 global climate models of CSIRO-Mk3-6-0, EC-EARTH, HadGEM2-ES, MPI-ESM-MR and NorESM1-M. Validations of the present climate show that the multi-model ensemble mean can well reproduce the spatial distribution of most climate extremes, and better performance can be found in the temperature-related climate extremes. However, some biases can also be observed, especially for the consecutive drought days (CDD). In the context of global warming, increased extreme warm events, decreased extreme cold events and consecutive drought days and increased extreme heavy precipitation events are projected in Xiongan New Area and the whole Jing-Jin-Ji district. In specific, increased TXx (Maximum value of daily maximum temperature) and TNn (Minimum value of daily minimum temperature) can be found, with the value exceeding 2.4℃ and 3.2℃, respectively. More pronounced increase of SU (Number of summer days) over the mountainous areas compared with the plain is observed, while greater increase of TR (Number of tropical nights) is found over the plain. The increase of SU and TR are in the range of 20 ? 40 d and5 ? 40 d, respectively. Both the FD (Number of frost days) and ID (Number of icing days) will decrease, with the decline above 10 d and 5 d, respectively. Precipitation-related climate extremes including CDD, R1mm (Annual count of days when daily precipitation≥1mm) and R10mm (Annual count of days when daily precipitation≥10 mm) are mainly on decrease with small values of ?10% ? 0 while increase of RX5day (Maximum consecutive 5-day precipitation), SDII (Simple precipitation intensity index) and R20mm (Annual count of days when daily precipitation≥20 mm) are found in most areas with the values in the range of 0 ? 25%. Regional mean changes show that the linear trends are more significantly in temperature-related climate extremes compared with those in precipitation-related climate extremes. Comparing the two regions, greater uncertainty of the simulations in Xiongan New Area can be found, which indicates the deficiency of the model in local scale areas.

Key words: Regional climate model, Xiongan New Area, Jing-Jin-Ji district, Climate extremes

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