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苏海锋, 戴新刚, 熊喆, 等. 2022. 21世纪黑河流域降水统计降尺度及预估[J]. 气候与环境研究, 27(5): 591−603. doi: 10.3878/j.issn.1006-9585.2021.21081
引用本文: 苏海锋, 戴新刚, 熊喆, 等. 2022. 21世纪黑河流域降水统计降尺度及预估[J]. 气候与环境研究, 27(5): 591−603. doi: 10.3878/j.issn.1006-9585.2021.21081
SU Haifeng, DAI Xingang, XIONG Zhe, et al. 2022. Precipitation Projection with Statistical Downscaling along the Heihe River Basin for the 21st Century [J]. Climatic and Environmental Research (in Chinese), 27 (5): 591−603. doi: 10.3878/j.issn.1006-9585.2021.21081
Citation: SU Haifeng, DAI Xingang, XIONG Zhe, et al. 2022. Precipitation Projection with Statistical Downscaling along the Heihe River Basin for the 21st Century [J]. Climatic and Environmental Research (in Chinese), 27 (5): 591−603. doi: 10.3878/j.issn.1006-9585.2021.21081

21世纪黑河流域降水统计降尺度及预估

Precipitation Projection with Statistical Downscaling along the Heihe River Basin for the 21st Century

  • 摘要: 借助第五阶段国际耦合模式比较计划(CMIP5)多模式集合数据、欧洲中期预报中心再分析资料及黑河流域站点观测记录等,检验了模式降水估计偏差,设计了3种降尺度方法,对2011~2100年模式集合预估降水做了降尺度偏差订正。结果表明,即使去掉模式气候飘移,在黑河流域的模拟或估计降水偏差依然较大。本文选用15个CMIP5模式集合做降水预估。依据贝叶斯模式平均(BMA)和多元线性回归(MLR)构造降尺度模型,其因子有700 hPa位势高度场、经向风和比湿等。检验表明,两种降尺度模型各有优缺点,BMA降尺度降水平均值精度较高,但方差和相关系数较低;MLR的方差和相关系数均较高,但在黑河下游极端干旱区或少雨季节易出现“负降水”偏差。在降尺度模型中加入模式降水因子后,BMA的降水方差和相关系数均有明显提高,MLR的负降水问题得到一定程度抑制。BMA模型在黑河上游最优,MLR在中、下游及整个流域最优。因此,选用BMA和MLR对RCP4.5情景下2011~2100年的降水预估做降尺度偏差订正,结果表明,经BMA和MLR降尺度后预估的整个黑河流域降水呈下降趋势,相对于1971~2000年参考期,流域前期(2011~2040年)、中期(2041~2070年)、后期(2071~2100年)降水下降率依次为−9.7%、−12.5、−12.1%,即前、中期降水明显减少,后期变化不大。其中上游降水有一个弱的增加趋势,其变化率依次为1.4%、1.6%、2.3%;中游降水呈明显减少趋势,其变化率依次为−16.3%、−21.4%、−22.6%;下游降水前期减少,中、后期明显增加,其变化率依次为−13.0%、4.2%、21.4%。该预估结果表明,随着全球气候暖化,黑河上游祁连山区降水会缓慢增加,但中游农耕区降水明显减少,流域水资源供需矛盾可能会进一步加剧。因此,黑河流域未来的分水方案及相关的生态、农业、经济等发展规划需要据此做一些调整,以适应未来气候和黑河流域水资源的可能变化。

     

    Abstract: This paper focuses on the precipitation projection of the Heihe River basin with downscaling for 2011–2100 using Coupled Model Intercomparison Project Phase 5 multimodel ensemble, combined with European Center for Medium-Range Weather Forecasts reanalysis data and meteorological stations observation in the Heihe River basin. Grid precipitation projection is mapped onto observatory sites through three downscaling methods for bias corrections, which include the model drift removal (MDR), multivariate linear regression (MLR), and Bayesian model average (BMA). Results show that an overestimate of the 15-model ensemble precipitation in the Heihe River basin has not yet been totally removed after MDR is removed, owing to the presence of a nonstationary bias. However, it works well on bias correction if MLR and BMA are used in downscaling with the factors of v-wind, specific humidity, and geopotential height on 700 hPa. The test demonstrates that BMA has a good estimate on averaged precipitation, but it gives a low variance and correlation coefficient with the meteorological stations observation. Conversely, MLR can produce a good variance in precipitation and a high correlation coefficient, but a negative precipitation estimate often appears in the lower reaches of the river, especially in cold and dry seasons. These problems have been overcome to a great extent as soon as the model precipitation is introduced into the downscaling models. Moreover, the test also shows that BMA is in favor of the bias correction in the upper reaches of the river, whereas MLR is good at the site-precipitation estimate in the middle and lower reaches or the whole river basin. The precipitation projection with downscaling shows that the averaged precipitation at 14 sites of the basin would decrease in comparison with that of the 1971–2000 observation, with the rates of −9.7%, −12.5, and −12.1% for 2011–2040, 2041–2070, and 2071–2100, respectively. The rates of projected precipitations are 1.4%, 1.6%, and 2.3% in the upper reaches; −16.3%, −21.4%, and −22.6% in the middle reaches; and 13.0%, 4.2%, and 21.4% in the lower reaches for the three periods of projection, respectively. The projection shows that the precipitation would be increasing slowly in the upper reaches of the Heihe River basin, decreasing significantly in the middle reaches and for 2011–2040, and then increasing remarkably for 2041–2100 in the lower reaches. This implies that the water shortage problem would be intensified in the middle reaches, a farmland area with climate warming under RCP4.5 scenarios. A strategic adjustment is recommended to the structure of the agriculture and economics around the middle reaches for adapting to future climate change along the Heihe River basin.

     

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