Climate Change Projection over Xiong'an District and Its Adjacent Areas: An Ensemble of RegCM4 Simulations
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摘要: 基于CSIRO-Mk3-6-0、EC-EARTH、HadGEM2-ES和MPI-ESM-MR共4个全球气候模式,分别驱动区域气候模式RegCM4,所进行的RCP4.5(典型浓度路径)中等排放情景下25 km较高水平分辨率东亚区域21世纪气候变化模拟结果,针对雄安新区及周边区域,在对当代(1986~2005)气候进行检验的基础上,进行了该区域未来气候变化的多模拟集合预估,并给出了模拟间的差别。结果表明:RegCM4可以较好地模拟出分析区域当代平均气温和降水的分布及年内月循环变化特征;对与气温相关的极端气候事件指数,日最高气温最高值(TXx)和日最低气温最低值(TNn),以及和降水相关的指数日最大降水量(RX1day)也有较好的模拟能力。雄安及周边区域未来平均气温、TXx和TNn将不断上升,高温热浪事件在增加的同时,低温事件将减少。未来分析区域平均降水量有所增加;而RX1day的增加更明显,且模拟间的一致性较好,不确定性相对较低,暴雨和洪涝事件的频率和强度均将增大。同时由于气温升高导致的潜在蒸发量相对于降水更大的增加,将使得区域水资源相对不足的现象加重。Abstract: We investigate the future climate changes in the 21st century in the Xiong'an District, recently established by the Chinese government, and its surrounding areas in North China based on 4 sets of RegCM4 climate change simulations over East Asia under the mid-range RCP4.5 (Representative Concentration Pathway) scenario. The model is run at a grid spacing of 25 km, and driven by the global model simulations of CSIRO-Mk3-6-0, EC-EARTH, HadGEM2-ES and MPI-ESM-MR, respectively. Validation of the present day (1986-2005) climate simulations is conducted first, followed by the ensemble projection of future changes along with the inter-simulation spread. Results show that the model can well capture both the spatial distributions of mean temperature and precipitation and their annual cycles. The model also shows a good performance in reproducing the temperature extreme indices of annual maximum value of daily maximum temperature (TXx) and annual minimum value of daily minimum temperature (TNn), and the precipitation extreme index of annual maximum 1-day precipitation (RX1day). Continuous warming and increases of TXx and TNn are found over Xiong'an District and its adjacent areas in the 21st century, indicating a warmer climate condition and more frequent hot spells in the future. With slight increases in mean precipitation, significant increases in RX1day with small inter-simulation spread are projected, indicating the intensification of precipitation extremes and more floods over the region. In the meantime, the greater increase in potential evapotranspiration compared to precipitation following the warming will lead to increases in water stress.
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Key words:
- Xiong'an District /
- Climate change /
- Extreme events /
- RegCM4 model
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图 1 分析区域和RegCM4中的地形分布(填色部分,单位:m)。绿色线代表各主要河流,紫色线为雄安新区的雄县、安新和容城三县,×号表示气象观测站点位置,圆点为主要城市
Figure 1. Region of interest and the topography in RegCM4 (shaded, units: m). Green lines indicate major rives, purple lines are the three counties of Xiongxian, Anxin, and Rongcheng of the Xiong'an District, × represents locations of the meteorological stations, and dots represent the major cities of the region
图 2 当代(1986~2005年)的气温和降水:(a)观测的年平均气温(单位:℃);(b)观测的年平均降水量(单位:mm);(c)年平均气温多模拟集合的偏差(单位:℃);(d)年平均降水多模拟集合的相对偏差;(e)观测(黑色)与多模拟集合(红色)的逐月平均气温(单位:℃);(f)观测(黑色)与多模拟集合(红色)的逐月平均降水量(单位:mm)
Figure 2. Multi-year averaged annual temperature and precipitation in the present day (1986–2005): (a) Observed annual mean temperature (units: ℃); (b) observed annual mean precipitation (units: mm); (c) bias of ensemble mean annual temperature (units: ℃); (d) relative bias of ensemble mean annual precipitation; (e) annual cycle of monthly mean temperature from observations (black) and ensemble averages (red) (units: ℃); (f) annual cycle of monthly mean precipitation from observations (black) and ensemble averages (red) (units:mm)
图 3 当代极端事件指数的分布。观测的(a)日最高气温最高值(TXx,单位:℃)、(c)日最低气温最低值(TNn,单位:℃)、(e)日最大降水量(RX1day,单位:mm)和多模拟集合(b)TXx(单位:℃)、(d)TNn(单位:℃)、(f)RX1day的偏差
Figure 3. Spatial distributions of the climate extreme indices in the present day. Observed (a) annual maximum value of daily maximum temperature (TXx) (units: ℃), (c) annual minimum value of daily minimum temperature (TNn) (units: ℃), and (e) annual maximum 1-day precipitation (RX1day) (units: mm); and the biases of ensemble averages of (b) TXx (units: ℃), (d) TNn (units: ℃) and (f) RX1day
图 4 多模拟集合的未来气温(单位:℃)和降水变化预估:(a)21世纪中期(2046~2065年)的年平均气温;(b)21世纪中期的年平均降水量;(c)区域平均的21世纪中期(蓝色)和末期(2079~2098年,红色)的四季气温;(d)同(c)但为降水量。图b中的“ +”表示4个模拟中的至少3个结果同符号,图c、d中的圆点为平均值,竖线表示4个模拟间的1个标准差的范围
Figure 4. The ensemble average of projected changes in temperature (units: ℃) and precipitation: (a) Annual mean temperature in the mid-21st century (2046–2065); (b) annual mean precipitation in the mid-21st century; (c) changes of temperature in the four seasons in the mid (blue) and end of the 21st century (2079–2098); (d) same as (c) but for precipitation. The "+" in (b) indicates at least 3 out of the 4 simulations agree on the sign of change, the dot and vertical lines in (c) and (d) indicates the mean and 1 standard deviation of the 4 projections
图 5 多模拟集合21世纪中期极端事件和水资源指数变化的预估:(a)TXx(单位:℃);(b)TNn(单位:℃);(c)RX1day;(d)IWR。(c)和(d)中的“ +”表示4个模拟中的至少3个结果同符号
Figure 5. Ensemble means of projected changes in climate extremes and water stress index in the mid-21st century: (a) TXx (units: ℃); (b) TNn; (c) RX1day; (d) index of water stress (IWR). The "+" in (c) and (d) indicates at least 3 out of the 4 simulations agree on the sign of change
表 1 用于驱动RegCM4的4个CMIP5全球气候模式信息及RegCM4的积分时间
Table 1. Information on the four CMIP5 driving models and the time periods of the RegCM4 simulations
模式名称和国家 分辨率(以经度×纬度格点数表示) 文献 积分时间 CSIRO-MK3-6-0澳大利亚 192×96 Rotstayn et al. (2010) 1951~2100年 EC-EARTH欧洲 320×160 Hazeleger et al. (2010) 1979~2098年 HadGEM2-ES英国 192×145 Johns et al. (2006); Martin et al. (2006); Ringer et al. (2006) 1961~2099年 MPI-ESM-MR德国 192×96 Marsland et al. (2003); Raddatz et al. (2007) 1980~2099年 表 2 雄安及周边区域平均的各要素多模拟集合偏差
Table 2. The biases of the ensemble averaged present day (1986–2005) variables over Xiong'an and the surrounding region of interest
偏差/℃ 相对偏差 气温 TXx TNn 降水 RX1day 雄安 0.1 2.3 1.3 16% 22% 分析区域 −0.8 0.8 −2.3 64% 60% 表 3 雄安及周边区域平均各要素未来变化的集合模拟预估值及范围(以±1个标准差表示)
Table 3. Ensemble averages of projected changes and spread (as indicated by ±1 standard deviation) of the variables over Xiong'an and the surrounding region of interest
未来变化的集合模拟预估值及范围 变量 21世纪中期(雄安/分析区域) 21世纪末期(雄安/分析区域) 年平均气温/℃ 1.6±0.5/1.6±0.5 2.2±0.6/2.1±0.6 年平均降水 8%±10%/5%±8% 1%±7%/1%±9% TXx/℃ 2.0±0.5/1.9±0.3 2.8±0.3/2.7±0.4 TNn/℃ 1.6±1.2/2.1±1.1 2.9±1.6/3.0±0.7 RX1day 16%±16%/13%±13% 5%±12%/8%±19% IWR 1%±5%/6%±6% 9%±4%/14%±9% -
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