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Statistical Multisite Simulations of Summertime Precipitation over South Korea and Its Future Change Based on Observational Data

机译:基于观测数据的韩国夏季降水及其未来变化的统计多站点模拟

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In this study, a weather generator for summer (May 19 -September 15) precipitation over South Korea is developed. Precipitation data for 33 years (1979-2011) observed at 57 stations of Korea Meteorological Administration (KMA) are used to develop a new weather generator. Using the cyclostationary empirical orthogonal function (CSEOF) technique, the observed precipitation data is described as a linear combination of deterministic evolution patterns and corresponding stochastic amplitude (principal component) time series. An autoregressive-moving average (ARMA) model is used to generate one hundred sets of synthetic amplitude time series for the period of 1979-2061 (83 years) with similar statistical properties of the original amplitude time series. Based on these synthetic time series and the annually repeating evolution patterns, one hundred sets of synthetic summer precipitation were generated. Statistical characteristics of the synthetic datasets are examined in comparison with those of the KMA observational record for the period of the observational record. Characteristic changes of synthetic precipitations for a future period are also examined. The seasonal cycle in the synthetic precipitation is reproduced faithfully with typical bimodal peaks of summer precipitation. The spatial correlation patterns of the synthetic precipitation are fairly similar to that of the observational data. The frequency-intensity relationship of the synthetic precipitation also looks similar to that of the observational data. In the future period, precipitation amount increases except in the precipitation range of (0,10) mm day~(-1) with nearly no change in the frequency of no-rain days; frequency increase is particularly conspicuous in the range of (100,500) mm day~(-1).
机译:在这项研究中,开发了韩国夏季(5月19日至9月15日)降水的天气发生器。在韩国气象厅(KMA)的57个站点观测到的33年(1979-2011年)的降水数据被用于开发新的气象发生器。使用循环平稳经验正交函数(CSEOF)技术,将观测到的降水数据描述为确定性演化模式和相应的随机振幅(主分量)时间序列的线性组合。使用自回归移动平均(ARMA)模型来生成1979年至2061年(83年)期间的一百套合成振幅时间序列,其统计特性与原始振幅时间序列相似。基于这些合成时间序列和每年重复的演化模式,产生了一百套合成夏季降水。在观察记录期间内,将与KMA观察记录的统计特征进行比较,检查合成数据集的统计特征。还检查了未来一段时间合成降水的特征变化。用夏季降水的典型双峰峰值忠实地再现了合成降水的季节周期。合成降水的空间相关模式与观测数据非常相似。合成降水的频率-强度关系也看起来与观测数据相似。未来一段时间,除(0,10)mm·day〜(-1)的降水范围外,降水量增加,无雨日的频率几乎没有变化。在(100,500)mm日〜(-1)的范围内,频率增加尤为明显。

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