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中国自动土壤水分观测资料质量控制方法设计与效果检验

王佳强 赵煜飞 任芝花 高静

气象2018,Vol.44Issue(2):244-257,14.
气象2018,Vol.44Issue(2):244-257,14.DOI:10.7519/j.issn.1000-0526.2018.02.004

中国自动土壤水分观测资料质量控制方法设计与效果检验

Design and Verification of Quality Control Methods for Automatic Soil Moisture Observation Data in China

王佳强 1赵煜飞 1任芝花 1高静1

作者信息

  • 1. 国家气象信息中心,北京100081
  • 折叠

摘要

Abstract

Soil moisture data play a key role in the study of climate change and agricultural drought monitoring,agricultural weather forecast and service.In order to effectively eliminate the abnormal data in observations,this paper puts forward a set of quality control (QC) methods which could be applied to the data of automatic soil moisture observation station (ASMOS) in China.First,based on the data of ASMOS 2014 in China,the abnormal data are divided into four categories according to their characters.Secondly,under the consideration of three aspects:threshold value check,internal consistency check,time consistency check,the QC methods are designed,which include abnormal extreme check,abnormal increase check,abnormal decrease check and abnormal constant check.Finally,the QC methods are verified by using the data of ASMOS and soil volumetric water content products of CMA Land Data Assimilation System (CLDAS-V2.0) in China in 2014-2015.The results show that:(1) the four kinds QC methods can effectively identify the four types of abnormal data.(2) The results from the four kinds QC methods are in good agreement in temporal continuity and spatial distribution.(3) The QC methods can effectively reduce the root mean square error (RMSE) between observation and the CLDAS data.At present,the methods have been applied to the Meteorological Data Processing Service System.

关键词

中国区域/自动土壤水分观测站/逐小时资料/土壤体积含水量/质量控制/CLDAS

Key words

China region/automatic soil moisture observation station (ASMOS)/hourly data/soil volumetric moisture content/quality control/CMA Land Data Assimilation System (CLDAS)

分类

天文与地球科学

引用本文复制引用

王佳强,赵煜飞,任芝花,高静..中国自动土壤水分观测资料质量控制方法设计与效果检验[J].气象,2018,44(2):244-257,14.

基金项目

公益性行业(气象)科研专项(GYHY201106038)和国家自然科学基金项目(91637313)共同资助 (气象)

气象

OA北大核心CSCDCSTPCD

1000-0526

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