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首页> 外文期刊>Fresenius Environmental Bulletin >HOMOGENEITY ANALYSIS OF LONG-TERM MONTHLY PRECIPITATION DATA OF TURKEY
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HOMOGENEITY ANALYSIS OF LONG-TERM MONTHLY PRECIPITATION DATA OF TURKEY

机译:土耳其长期每月降水数据的均一性分析

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摘要

Availability of a long-term, continuous and homogeneous precipitation series is always essential for climate and hydrologic studies. Nevertheless, precipitation data may suffer from inhomogeneity, owing to various non-climatic factors. The observing network in Turkey is under conti-nous development and but at the same time prone to effects of urbanization and changes in land-use conditions. This study aims to characterize homogeneity of the long-term Turkish precipitation data in order to ensure that they can be used reliably. Several parametric and non-parametric tests are applied to de-tect inhomogeneities with long-term monthly precipitation data of 211 stations scattered across Turkey for the period from 1973 to 2002. The homogeneity analysis was performed in two steps. In the first step, 4 parametric tests were applied to the data. Initially, the results indicated that 3 stations with the Kruskal-Wallis test, 13 stations with the Fried-man tests, 5 stations with the oneway ANOVA tests, and 73 stations with the Bartlett's tests were inhomogeneous. Further analyses indicated that only 2 of 211 stations resulted to be inhomogeneous under the all 4 tests. Again, 2 out of 211 stations were inhomogeneous according to the result of 3 tests. Finally, only 7 out of 211 stations demonstrated inhomogeneity according to 2 of the tests. In the second step, 27 pairs of stations which have closest proximity to each other are tested for homogeneity using the non-parametric Mann-Whitney and Wil-coxon signed-rank tests. A total of 10 pairs of stations exhibited inhomogeneity for the both tests. It was observed that most of the stations, which are characterized as inhomogeneous, are located in Eastern Anatolia, and 3 of them lie around Lake Van, which is the largest water-body inside Turkey. When the inhomogeneous stations were checked against their meta-data, nothing conclusive was found to justify the inhomogeneities, except Gokceada station, which experienced considerable increase in plant canopy in its surrounding. It is expected that replacing the conventional network with the more up-to-date sensors (called AWOS) may create a great challenge in homogeneity of the Turkish precipitation series.
机译:长期,连续且均匀的降水序列的可用性对于气候和水文研究始终至关重要。然而,由于各种非气候因素,降水数据可能会出现不均匀性。土耳其的观测网络正在持续发展,但同时容易受到城市化和土地利用条件变化的影响。这项研究旨在表征土耳其长期降水数据的均匀性,以确保可以可靠地使用它们。 1973年至2002年期间,利用分布在土耳其的211个站点的长期每月降水数据,使用了一些参数和非参数测试来检测不均匀性。均质性分析分两个步骤进行。第一步,对数据应用了4个参数测试。最初,结果表明,使用Kruskal-Wallis测试的3个站点,使用Friedman测试的13个站点,使用单向ANOVA测试的5个站点和通过Bartlett's测试的73个站点是不均匀的。进一步的分析表明,在所有4个测试中,211个站点中只有2个是不均匀的。同样,根据3个测试的结果,在211个站点中有2个是不均匀的。最后,根据两项测试,在211个站点中只有7个表现出不均匀性。在第二步中,使用非参数Mann-Whitney和Wil-coxon符号秩检验来测试27对彼此最接近的站点的同质性。两种测试中总共有10对站显示出不均匀性。据观察,大多数站的特征是不均匀的,位于安纳托利亚东部,其中三个站位于范湖附近,范湖是土耳其内部最大的水体。当检查非均质站的元数据时,除了Gokceada站(其周围植物冠层大量增加)外,没有任何结论可证明非均质性。可以预期的是,用最新的传感器(称为AWOS)代替常规网络可能会对土耳其降水序列的同质性提出巨大挑战。

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