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A statistical downscaling model for summer rainfall over Pakistan

机译:巴基斯坦夏季降水的统计降尺度模型

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摘要

A statistical approach is utilized to construct an interannual model for summer (July-August) rainfall over the western parts of South Asian Monsoon. Observed monthly rainfall data for selected stations of Pakistan for the last 55 years (1960-2014) is taken as predictand. Recommended climate indices along with the oceanic and atmospheric data on global scales, for the period April-June are employed as predictors. First 40 years data has been taken as training period and the rest as validation period. Cross-validation stepwise regression approach adopted to select the robust predictors. Upper tropospheric zonal wind at 200 hPa over the northeastern Atlantic is finally selected as the best predictor for interannual model. Besides, the next possible candidate 'geopotential height at upper troposphere' is taken as the indirect predictor for being a source of energy transportation from core region (northeast Atlantic/western Europe) to the study area. The model performed well for both the training as well as validation period with correlation coefficient of 0.71 and tolerable root mean square errors. Cross-validation of the model has been processed by incorporating JRA-55 data for potential predictors in addition to NCEP and fragmentation of study period to five non-overlapping test samples. Subsequently, to verify the outcome of the model on physical grounds, observational analyses as well as the model simulations are incorporated. It is revealed that originating from the jet exit region through large vorticity gradients, zonally dominating waves may transport energy and momentum to the downstream areas of west-central Asia, that ultimately affect interannual variability of the specific rainfall. It has been detected that both the circumglobal teleconnection and Rossby wave propagation play vital roles in modulating the proposed mechanism.
机译:利用统计方法构建了南亚季风西部地区夏季(7月至8月)降雨的年际模型。将过去55年(1960-2014年)巴基斯坦部分气象站的每月观测雨量数据作为预测值。推荐的气候指数以及全球范围内4月至6月的海洋和大气数据被用作预测指标。前40年的数据用作培训期,其余的作为验证期。采用交叉验证逐步回归方法来选择鲁棒的预测因子。最终选择了东北大西洋上空200 hPa的对流层高纬向风作为年际模型的最佳预测器。此外,下一个可能的候选“对流层上层的地势高度”被认为是从核心区域(东北大西洋/西欧)到研究区域的能量传输来源的间接预测因子。该模型在训练和验证期间均表现良好,相关系数为0.71,且均方根误差可容忍。除NCEP之外,还通过结合JRA-55数据作为潜在预测变量来处理模型的交叉验证,并将研究期分为五个非重叠测试样本。随后,为了在物理基础上验证模型的结果,将观察性分析以及模型仿真结合在一起。结果表明,纬向占主导地位的波源是来自喷气出口区域的大涡度梯度,它可能会将能量和动量传输到中亚西部的下游地区,最终影响特定降雨的年际变化。已经发现,环境全局遥相关和罗斯比波传播在调制所提出的机制中都起着至关重要的作用。

著录项

  • 来源
    《Climate dynamics》 |2016年第8期|2653-2666|共14页
  • 作者单位

    Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China|Univ Chinese Acad Sci, Beijing 100049, Peoples R China;

    Beijing Normal Univ, Coll Global Change & Earth Syst Sci GCESS, Beijing 100875, Peoples R China|Joint Ctr Global Change Studies, Beijing 100875, Peoples R China;

    North China Sea Marine Forecasting Ctr State Ocea, Qingdao 266061, Peoples R China;

    Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China|Univ Chinese Acad Sci, Beijing 100049, Peoples R China;

    Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Interannual model; ENSO; Summer monsoon; CVSR; CGT;

    机译:年际模型;ENSO;夏季风;CVSR;CGT;

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