A novel approach to statistical downscaling considering nonstationarities: application to daily precipitation in the Mediterranean area
A novel approach to statistical downscaling considering nonstationarities: application to daily precipitation in the Mediterranean area
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DOI：
10.1002/jgrd.50112
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发表时间：
2013-01-27
影响因子：
4.4
通讯作者：
Jacobeit, J.
中科院分区：
文献类型：
--
作者：
Hertig, E.;Jacobeit, J.
在本研究中，在统计降尺度的框架内的预测predictor-predictand关系的非平稳性。在这种情况下，一种新的验证方法，其中明确考虑到非平稳性。该方法基于运行校准周期的结果。平均模型性能的自举置信区间（通过平均所有校准/验证期的性能得出）和个体模型误差的自举置信区间的（非）重叠用于识别（非）稳态模型性能。指定的程序证明了平均每日降水量在地中海地区使用的偏见，以评估模型的技能。采用基于循环和基于传递函数的组合方法作为降尺度技术。在这种情况下，大规模的季节性大气制度，天气尺度的每日环流模式，以及它们的内部类型的特点，与每日站为基础的降水。结果表明，非定常性是由于不同的特定的环流配置的预报降水关系。在这方面，循环模式的频率变化可以抑制或增加非平稳关系的影响。在温室效应增加的条件下评估未来降水变化的范围内，识别和分析预测因子-降水关系中的非平稳性导致为未来评估选择具体的统计降尺度模型。使用RCP 4.5情景假设，强烈的日降水量增加变得明显的西部和北方地中海地区的大部分地区在冬季。在春季、夏季和秋季，直到21世纪世纪末，降水量的减少显然主导着整个地中海地区。引文：Hertig，E.，和J. Jacobeit（2013），一种考虑非平稳性的统计降尺度新方法：应用于地中海地区的每日降水量，J. Geophys。Res. Atmos.，118，520-533，doi：10.1002/jgrd.50112。
In the present study, nonstationarities in predictor-predictand relationships within the framework of statistical downscaling are investigated. In this context, a novel validation approach is introduced in which nonstationarities are explicitly taken into account. The method is based on results from running calibration periods. The (non) overlaps of the bootstrap confidence interval of the mean model performance (derived by averaging the performances of all calibration/verification periods) and the bootstrap confidence intervals of the individual model errors are used to identify (non) stationary model performance. The specified procedure is demonstrated for mean daily precipitation in the Mediterranean area using the bias to assess model skill. A combined circulation-based and transfer function-based approach is employed as a downscaling technique. In this context, large-scale seasonal atmospheric regimes, synoptic-scale daily circulation patterns, and their within-type characteristics, are related to daily station-based precipitation. Results show that nonstationarities are due to varying predictors-precipitation relationships of specific circulation configurations. In this regard, frequency changes of circulation patterns can damp or increase the effects of nonstationary relationships. Within the scope of assessing future precipitation changes under increased greenhouse warming conditions, the identification and analysis of nonstationarities in the predictors-precipitation relationships leads to a substantiated selection of specific statistical downscaling models for the future assessments. Using RCP4.5 scenario assumptions, strong increases of daily precipitation become apparent over large parts of the western and northern Mediterranean regions in winter. In spring, summer, and autumn, decreases of precipitation until the end of the 21st century clearly dominate over the entire Mediterranean area. Citation: Hertig, E., and J. Jacobeit (2013), A novel approach to statistical downscaling considering nonstationarities: application to daily precipitation in the Mediterranean area, J. Geophys. Res. Atmos., 118, 520-533, doi:10.1002/jgrd.50112.