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郭彦, 李建平. 一种分离时间尺度的统计降尺度模型的建立和应用——以华北汛期降水为例[J]. 大气科学, 2012, 36(2): 385-396. DOI: 10.3878/j.issn.1006-9895.2011.11045
引用本文: 郭彦, 李建平. 一种分离时间尺度的统计降尺度模型的建立和应用——以华北汛期降水为例[J]. 大气科学, 2012, 36(2): 385-396. DOI: 10.3878/j.issn.1006-9895.2011.11045
GUO Yan, LI Jianping. A Time-Scale Decomposition Statistical Downscaling Model: Case Study of North China Rainfall in Rainy Season[J]. Chinese Journal of Atmospheric Sciences, 2012, 36(2): 385-396. DOI: 10.3878/j.issn.1006-9895.2011.11045
Citation: GUO Yan, LI Jianping. A Time-Scale Decomposition Statistical Downscaling Model: Case Study of North China Rainfall in Rainy Season[J]. Chinese Journal of Atmospheric Sciences, 2012, 36(2): 385-396. DOI: 10.3878/j.issn.1006-9895.2011.11045

一种分离时间尺度的统计降尺度模型的建立和应用——以华北汛期降水为例

A Time-Scale Decomposition Statistical Downscaling Model: Case Study of North China Rainfall in Rainy Season

  • 摘要: 针对预报量变化中存在受不同物理因子控制的不同时间尺度变率特征, 本文提出了分离时间尺度的统计降尺度模型。应用滤波方法, 将不同尺度的变率分量分开, 在各自对应的时间尺度上利用不同的大尺度气候因子分别建立降尺度模型。华北汛期 (7~8月) 降水具有年际变率和年代际变率, 本文以华北汛期降水为例利用分离时间尺度的统计降尺度模型进行预测研究。采用的预报因子来自海平面气压场、 500 hPa位势高度场、 850 hPa经向风场和海表温度场以及一些已知的大尺度气候指数。利用基于交叉检验的逐步回归法建立模型。结果表明, 年际尺度上, 华北汛期降水与前期6月赤道中东太平洋海温以及同期中国东部的低层经向风密切相关; 年代际尺度上, 在东印度洋—西太平洋暖池海温的作用下, 华北降水与前期6月西南印度洋海平面气压有同步变化关系。年际模型和年代际模型的结果相加得到对总降水量的降尺度结果。1991~2008年的独立检验中, 模型估计的降水和观测降水的相关系数是0.82, 平均均方根误差是14.8%。结合模式的回报资料, 利用降尺度模型对1991~2001年的华北汛期降水进行回报试验。相比于模式直接预测的降水, 降尺度模型预测的结果有明显改进。改进了模式预测中年际变率过小的问题, 与观测降水的相关系数由0.12提高到0.45。

     

    Abstract: A time-scale decomposition (TSD) approach was introduced to statistically downscale the predictand which contains distinct variablity linked with distinct large-scale predictors. It decomposed both the predictand and the predictors into distinct components through filtering and calibrated distinct predictive equations, respectively. Due to the interannual and inter-decadal variability in July-August North China rainfall, it was used as a case to be downscaled by TSD approach. Sea level pressure, 500-hPa geopotential height, 850-hPa meridional wind, and sea surface temperature were considered as predictor parameters; several well-known large-scale climate indices were also taken as potential predictors. An approach of cross-validation-based stepwise regression was used to formulate the regression equations. The downscaling model for the interannual rainfall variability was linked to the sea surface temperature over the mid-eastern tropical Pacific in June and the 850-hPa meridional wind over East China in July-August, while that for the inter-decadal rainfall variability was related to the sea level pressure over the southwestern Indian Ocean in June under the effect of sea surface temperature over the Indian Ocean-Pacific warm pool. The downscaled interannual and inter-decadal rainfall components were added together to obtain the downscaled total rainfall. The results in the independent validation period (1991-2008) showed that the TSD approach performed well to downscale July-August North China rainfall with the correlation coefficient of 0.82 and relative root-mean-square error of 14.8%. With the hindcasted predictors by general circulation models (GCMs), the downscaling model was used to hindcast July-August North China rainfall over 1991-2001. Compared to GCM-hindcasted rainfall, the downscaling model showed better performance, which improved the original bias in terms of insufficient interannual variation in GCM hindcast. The correlation coefficient between the observed and downscaled rainfall reached 0.45, much higher than 0.12 in GCM hindcast.

     

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