DOI: 10.1002/2014GL060659
论文题名: Impact of quality control of satellite soil moisture data on their assimilation into land surface model
作者: Yin J. ; Zhan X. ; Zheng Y. ; Liu J. ; Hain C.R. ; Fang L.
刊名: Geophysical Research Letters
ISSN: 0094-9691
EISSN: 1944-9422
出版年: 2014
卷: 41, 期: 20 起始页码: 7159
结束页码: 7166
语种: 英语
英文关键词: data assimilation
; green vegetation fraction
; quality control
; SMOPS soil moisture product
Scopus关键词: Computer simulation
; Information services
; Moisture
; Moisture control
; Quality assurance
; Quality control
; Satellites
; Soil moisture
; Soils
; Surface measurement
; Vegetation
; Weather forecasting
; Data assimilation
; Environmental satellites
; National Weather Services
; Numerical weather prediction models
; Root zone soil moistures
; Satellite soil moisture
; SMOPS soil moisture product
; Vegetation fractions
; Soil surveys
; data assimilation
; fractionation
; in situ measurement
; land surface
; NOAA satellite
; numerical model
; quality control
; satellite data
; satellite imagery
; soil moisture
; vegetation structure
英文摘要: A global Soil Moisture Operational Product System (SMOPS) has been developed to process satellite soil moisture observational data at the NOAA National Environmental Satellite, Data, and Information Service for improving numerical weather prediction (NWP) models at the NOAA National Weather Service (NWS). A few studies have shown the benefits of assimilating satellite soil moisture data in land surface models (LSMs), which are the components of most NWP models. In this study, synthetic experiments are conducted to determine how soil moisture data quality control may impact the benefit of their assimilation into LSMs. It is found that using green vegetation fraction to quality control the SMOPS soil moisture product may significantly increase the benefit of assimilating it into Noah LSM in terms of increasing the agreement of Noah LSM surface and root zone soil moisture simulations with the corresponding in situ measurements. The quality control procedures and parameters are suggested for the assimilation of SMOPS data into NWS NWP models. Key Points Quality control rules of satellite soil moisture data product from NOAA-NESDIS soil moisture product system (SMOPS) are established for their assimilation into Noah land surface model using green vegetation fraction criteriaApplying the quality control rules in the assimilation of SMOPS data products significantly improves the agreement of Noah LSM soil moisture simulations with in situ measurements ©2014. American Geophysical Union. All Rights Reserved. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911425923&doi=10.1002%2f2014GL060659&partnerID=40&md5=a17d096880d6e7583febf8c13b22e9eb
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/6955
Appears in Collections: 气候减缓与适应
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作者单位: Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China
Recommended Citation:
Yin J.,Zhan X.,Zheng Y.,et al. Impact of quality control of satellite soil moisture data on their assimilation into land surface model[J]. Geophysical Research Letters,2014-01-01,41(20).