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An Analogy toward the Real-Time Multivariate MJO Index to Improve the Estimation of the Impacts of the MJO on the Precipitation Variability over Iran in the Boreal Cold Months

机译:对实时多元MJO指数的类比,提高MJO对北方寒冷多月份伊朗降水变异性的影响

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In addition to the tropical data, the OLR/U850/U200 data on a restricted region in southwestern Asia (17.5°N-35°N, 30°E-60°E) has been incorporated into the calculation of the Real-time Multivariate MJO (RMM) index. Introducing this data modifies the leading EOFs of the RMM index slightly and rotates them 14° eastward as a consequence of the change in the column variances of the RMM anomaly matrix at 30°E-60°E longitudes. However, the leading principal components of the new index, which is called Regionally Modified RMM (hereafter, RM-RMM), remain approximately unchanged. Owing to this close relationship between the two indices, the 14° phase-shift is considered as a basis for comparing the influences of the intraseasonal tropics-southwestern Asia variabilities on the precipitation over Iran with those of the MJO. Accordingly, by generating the spatial patterns of the precipitation anomaly, precipitation occurrence probability and other fields based on every active phase of the RM-RMM and RMM indices, the significant differences are revealed between the corresponding phases of the two indices for the phases 1, 3, 5, 7, and 8, separately. These results ameliorate the estimation of the impacts of the MJO on the precipitation and indicate that the RM-RMM index could be used as a companion to the RMM to forecast the precipitation in Iran. Remarkably, the precipitation forecast skill of the lag-regression model based on the RM-RMM index exceeds that of the model based on the RMM for certain time lags during the phases 1, 3, 5, 7 and 8 of the two indices.
机译:除了热带数据外,亚洲西南部(17.5°N-35°N,30°E-60°E)的禁区OLR / U850 / U200数据已被纳入实时多变量的计算MJO(RMM)索引。介绍该数据稍微修改RMM指数的领先EOF,并在向后向后旋转14°,因为RMM异常矩阵的柱差在30°E-60°E的长度的柱子中的变化。但是,新索引的主要主组件称为区域修改的RMM(以下,RM-RMM)保持大致不变。由于这两个指数之间的这种密切关系,14°相移被认为是比较了对西南部亚洲西南亚洲可变量对伊朗的降水的影响的基础。因此,通过产生基于RM-RMM和RMM指标的每个活动阶段的降水异常,降水发生概率和其他场的空间模式,在两个指数的相应阶段之间揭示了显着差异,阶段1的相应阶段, 3,5,7和8分别。这些结果改善了MJO对降水量的影响,并表明RM-RMM指数可以用作RMM的伴侣预测伊朗降水。值得注意的是,基于RM-RMM索引的滞后模型的降水预测技术基于在两个指数的阶段1,3,5,7和8期间基于RMM基于RMM的模型的模型。

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