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高原气象  2018, Vol. 37 Issue (6): 1449-1457    DOI: 10.7522/j.issn.1000-0534.2018.00060
论文     
青藏高原中、东部气象站降水资料时间序列的构建与应用
刘田1,2, 阳坤1,2,3, 秦军1,2, 田富强4
1. 中国科学院青藏高原环境与地表过程实验室, 中国科学院青藏高原研究所, 北京 100101;
2. 中国科学院大学, 北京 100049;
3. 清华大学地球系统科学系, 北京 100084;
4. 水沙科学与水利水电工程国家重点实验室, 清华大学水利水电工程系, 北京 100084
Construction and Applications of Time Series of Monthly Precipitation at Weather Stations in the Central and Eastern Qinghai-Tibetan Plateau
LIU Tian1,2, YANG Kun1,2,3, QIN Jun1,2, TIAN Fuqiang4
1. Key Laboratory of Tibetan Environment Changes and Land Surface Process, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Department of Earth System Science, Tsinghua University, Beijing 100084, China;
4. Department of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
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摘要: 气象台站观测可以提供高精度的局地降水信息,但是台站数据缺失对降水趋势分析等气候变化研究有严重影响。青藏高原站点非常稀疏且难以维护,这种影响尤为严重。借助贝叶斯线性回归方法,建立缺失数据站点与其相邻站点降水量之间的数学关系,对月降水量时间序列进行插补和延长,重构了1979-2015年间青藏高原中、东部148个站点的月降水完整时间序列。交叉验证显示插补和延长后的结果基本上能还原缺失数据站点降水的季节变化,且该方法优于几种常用的插值方法。构建的时间序列显示,1998年后高原东南部年降水量明显减少,东北部2002年以来则略有上升,而东南和东北部的过渡带则没有明显的年代际变化。
关键词: 青藏高原站点降水插补和延长贝叶斯线性回归    
Abstract: Weather stations can provide high-accuracy local precipitation information, but individual stations usually have different time series, which may have a significant influence on the precipitation trend analysis and relevant studies. This impact may be particularly severe in the Qinghai-Tibetan Plateau, where the stations are very sparse and are hard for operations. The number of available China Meteorological Administration (CMA) stations decreased from 146 to 130 in the central and eastern Qinghai-Tibetan Plateau during 1979-2015, mainly due to the deactivation of some stations and the change of station types. In this study, an upscaling theory method based on the Bayesian linear regression was used to establish the mathematical relationship for precipitation value between a station with missing data and its adjacent stations with available data. The method is then used to interpolate and extend the monthly precipitation time series. It was constructed the time series of monthly precipitation at 148 stations in the central and eastern Qinghai-Tibetan Plateau and its surrounding areas during the period of 1979-2015. Cross-validation, using 29 time series complete stations, displays the constructed time series after interpolation and extension can generally restore the seasonal variation of the precipitation at stations with missing data. The new method is superior to several commonly used interpolation methods to a certain extent, including inverse distance weighted (IDW), local polynomial (LP), and kriging method. To illustrate the value of reconstructed precipitation data, two preliminary applications of the data were introduced, including satellite precipitation correction and regional precipitation trend analysis. The fusion of satellite precipitation (Tropical Rainfall Measurement Mission, TRMM) and gauge precipitation after interpolation and extension, indicates that the introduction of interpolation stations data can change the local precipitation distribution characteristics. To a certain extent, increasing the number of available stations helps to improve interpolation accuracy of grid precipitation. The interpolation and extension are helpful to quantify the spatial distribution and the temporal variation of precipitation in central and eastern Qinghai-Tibetan Plateau. Improving the precipitation grid interpolation accuracy in particular, the constructed time series then demonstrates that annual precipitation decreased significantly in the Southeast Qinghai-Tibetan Plateau after about 1998 but jumped slightly to a higher-level in the Northeast Qinghai-Tibetan Plateau since 2002, while no decadal change is seen in the transitional zone between the Southeast and Northeast Qinghai-Tibetan Plateau. This spatial difference in precipitation can roughly explain the spatial pattern of regional water cycles (glacier mass balances, lake water volume changes, and river runoff changes).
Key words: Qinghai-Tibetan Plateau    gauge precipitation    interpolation and extension    bayesian linear regression
收稿日期: 2018-01-09 出版日期: 2018-12-24
:  P4112.1  
基金资助: 国家自然科学基金项目(91537210);中国科学院前沿科学重点研究计划项目(QYZDY-SSW-DQC011-03);中国科学院国际合作局对外合作重点项目(131C11KYSB20160061)
通讯作者: 阳坤(1970-),男,四川广安人,研究员,主要从事陆面过程模拟与数据同化研究.E-mail:yangk@itpcas.ac.cn     E-mail: yangk@itpcas.ac.cn
作者简介: 刘田(1992-),女,河南禹州人,硕士研究生,主要从事青藏高原降水研究.E-mail:liutian@itpcas.ac.cn
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引用本文:

刘田, 阳坤, 秦军, 田富强. 青藏高原中、东部气象站降水资料时间序列的构建与应用[J]. 高原气象, 2018, 37(6): 1449-1457.

LIU Tian, YANG Kun, QIN Jun, TIAN Fuqiang. Construction and Applications of Time Series of Monthly Precipitation at Weather Stations in the Central and Eastern Qinghai-Tibetan Plateau. Plateau Meteorology, 2018, 37(6): 1449-1457.

链接本文:

http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2018.00060        http://www.gyqx.ac.cn/CN/Y2018/V37/I6/1449

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