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Non-stationarities in the relationships of heavy precipitation events in the Mediterranean area and the large-scale circulation in the second half of the 20th century

机译:地中海地区强降水事件与20世纪下半叶大尺度环流之间关系的非平稳性

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In the context of analyzing temporal varying relationships of heavy precipitation events in the Mediterranean area and associated anomalies of the large-scale circulation, quantile regression models were established. The models were calibrated using different circulation and thermodynamic variables at the 700 hPa and 850 hPa levels as predictors as well as daily precipitation time series at different stations in the Mediterranean area as predictand. Analyses were done for the second half of the 20th century. In the scope of assessing nonstationarities in the predictor-predictand relationships the time series were divided into calibration and validation periods. 100 randomized subsamples were used to calibrate/validate the models under stationary conditions. The highest and lowest skill score of the 100 random samples was used to determine the range of random variability. The model performance under non-stationary conditions was derived from the skill scores of cross-validated running subintervals. If the skill scores of several consecutive years are outside the range of random variability a non-stationarity was declaimed. Particularly the Iberian Peninsula and the Levant region were affected by non-stationarities, the former with significant positive deviations of the skill scores, the latter with significant negative deviations. By means of a case study for the Levant region we determined three possible reasons for non-stationary behavior in the predictor-predictand relationships. The Mediterranean Oscillation as a superordinate system affects the cyclone activity in the Mediterranean basin and the location and intensity of the Cyprus low. Overall, it is demonstrated that non-stationarities have to be taken into account within statistical downscaling model development. (C) 2016 Elsevier B.V. All rights reserved.
机译:在分析地中海地区强降水事件的时间变化关系和大尺度环流的相关异常过程中,建立了分位数回归模型。使用700 hPa和850 hPa水平的不同循环和热力学变量作为预测因子以及地中海地区不同站点的每日降水时间序列作为预测因子,对模型进行了校准。在20世纪下半叶进行了分析。在评估预测变量与预测变量之间的非平稳性的范围内,时间序列分为校准期和验证期。在固定条件下,使用100个随机子样本来校准/验证模型。 100个随机样本的最高和最低技能得分用于确定随机变异性的范围。非平稳条件下的模型性能源自交叉验证的跑步子时间间隔的技能得分。如果连续几年的技能得分不在随机变异范围之内,则认为非平稳性。特别是伊比利亚半岛和黎凡特地区受到不稳定的影响,前者的技能得分有明显的正偏差,而后者则有明显的负偏差。通过对黎凡特地区的案例研究,我们确定了预测因子与预测因子之间关系非平稳行为的三个可能原因。作为上级系统的地中海涛动影响了地中海盆地的旋风活动以及塞浦路斯的位置和强度。总体而言,这表明在统计缩减模型开发过程中必须考虑非平稳性。 (C)2016 Elsevier B.V.保留所有权利。

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