基于CMIP5模式预估长江上游流域气温及降水时空特征
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摘要
针对8个气候模式模拟的降水量较观测值系统偏大、模拟的平均气温较观测值系统偏小的问题,采用双线性内插降尺度方法及等距离分位数误差修正方法来减小系统误差,修正后的模拟效果均得到了大幅改善,且多个模式集合平均的模拟效果优于各个模式。基于长江上游82个气象站点的气象数据,利用修正后的8个模式预估长江上游2006～2099年降水、气温的变化情况。结果表明,在RCP4.5和RCP8.5情景下,8个气候模式模拟的长江上游未来时期的降水、气温均呈增加趋势,气温呈显著性增加;RCP4.5情景下的降水、气温增加趋势逐渐减弱,RCP8.5则逐渐增强,且RCP8.5的年际波动更大,4、5月的升温幅度要低于其他月份,且RCP8.5情景下的升温趋势要高于RCP4.5。两种情景下流域降水空间分布不均,呈东部及盆地多川西高原少、南多北少。冬季的降水线性趋势低,夏、秋季区域变化比较明显;秋、冬季的升温幅度要高于春、夏季。
In view of the problem that the bias of the simulated precipitation by 8climate models is larger than that of the observed,the bias of the simulated temperature is less than that of the observed,the raw data by means of bias correction spatial disaggregation and the statistical downscaling approach of climate models were used to reduce systematic error and improve the simulated effect greatly.Based on the observations of 82 meteorological stations in the upstream of the Yangtze River Basin,the corrected data of eight models were used to predict the future temperature and precipitation from 2006 to 2099.The results show that under scenarios of RCP4.5 and RCP8.5,the simulations of temperature and precipitation with 8climate models increase in the upper reaches of the Yangtze River in the future,and the upward trend of temperature is obvious.Under the RCP4.5scenario,the upward trend of temperature and precipitation decreases gradually.On the contrary,the corresponding trend increases under RCP8.5.Furthermore,the annual variations of temperature and precipitation are larger.The rise amplitude of temperature in April and May is lower than others,and the upward trend of temperature rise in RCP8.5is higher than that of RCP4.5.The spatial distribution of regional precipitation is not uniform,and the distribution of precipitation in the southern,eastern regions and Sichuan basin is greater than that in northern regions and the western Sichuan plateau in the basin.The trend of precipitation in winter is less than other seasons,the upward trend of temperature rise in autumn and winter is higher than others.
In view of the problem that the bias of the simulated precipitation by 8climate models is larger than that of the observed,the bias of the simulated temperature is less than that of the observed,the raw data by means of bias correction spatial disaggregation and the statistical downscaling approach of climate models were used to reduce systematic error and improve the simulated effect greatly.Based on the observations of 82 meteorological stations in the upstream of the Yangtze River Basin,the corrected data of eight models were used to predict the future temperature and precipitation from 2006 to 2099.The results show that under scenarios of RCP4.5 and RCP8.5,the simulations of temperature and precipitation with 8climate models increase in the upper reaches of the Yangtze River in the future,and the upward trend of temperature is obvious.Under the RCP4.5scenario,the upward trend of temperature and precipitation decreases gradually.On the contrary,the corresponding trend increases under RCP8.5.Furthermore,the annual variations of temperature and precipitation are larger.The rise amplitude of temperature in April and May is lower than others,and the upward trend of temperature rise in RCP8.5is higher than that of RCP4.5.The spatial distribution of regional precipitation is not uniform,and the distribution of precipitation in the southern,eastern regions and Sichuan basin is greater than that in northern regions and the western Sichuan plateau in the basin.The trend of precipitation in winter is less than other seasons,the upward trend of temperature rise in autumn and winter is higher than others.
引文
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[3]周天军,李立娟,李红梅,等.气候变化的归因和预估模拟研究[J].大气科学,2008,32(4):906-922.
[4]Hellstrom C,Chen D L,Achberger C,et al.Comparison of Climate Change Scenarios for Sweden Based on Statistical and Dynamical Downscaling of Monthly Precipitation[J].Climate Research,2001,19(1):45-55.
[5]Taylor K E,Stouffer R J,Meehl G A.An Overview of CMIP5and the Experiment Design[J].Bulletin of the American Meteorological Society,2011,93(4):485-498.
[6]Vuuren D P V,Edmonds J,Kainuma M,et al.The Representative Concentration Pathways:An Overview[J].Climatic Change,2011,109(1-2):5-31.
[7]Wang L,Chen W.A CMIP5Multimodel Projection of Future Temperature,Precipitation,and Climatological Drought in China[J].International Journal of Climatology,2014,34(6):2 059-2 078.
[8]Li H,Sheffield J,Wood E F.Bias Correction of Monthly Precipitation and Temperature Fields from Intergovernmental Panel on Climate Change AR4Models Using Equidistant Quantile Matching[J].Journal of Geophysical Research Atmospheres,2010,115(D10):985-993.