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Bias Correction in Monthly Records of Satellite Soil Moisture Using Nonuniform CDFs
Joint Authors
Shi, Chun-Xiang
Wang, Shan
Shan, Huiling
Zhang, Chi
Wang, Yuexing
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-07-16
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
It is important to eliminate systematic biases in the field of soil moisture data assimilation.
One simple method for bias removal is to match cumulative distribution functions (CDFs) of modeled soil moisture data to satellite soil moisture data.
Traditional methods approximate numerical CDFs using 12 or 20 uniformly spaced samples.
In this paper, we applied the Douglas–Peucker curve approximation algorithm to approximate the CDFs and found that three nonuniformly spaced samples can achieve the same reduction in standard deviation.
Meanwhile, the matching results are always closely related to the temporal and spatial availability of soil moisture observed by automatic soil moisture station (ASM).
We also applied the new nonuniformly spaced sampling method to a shorter time series.
Instead of processing a whole year of data at once, we divided it into 12 datasets and used three nonuniformly spaced samples to approximate the model data’s CDF for each month.
The matching results demonstrate that NU-CDF3 reduced the SD, improved R, and reduced the RMSD in over 70% of the stations, when compared with U-CDF12.
Additionally, the SD and RMSD have been reduced by over 4% with R improved by more than 9%.
American Psychological Association (APA)
Wang, Shan& Shan, Huiling& Zhang, Chi& Wang, Yuexing& Shi, Chun-Xiang. 2018. Bias Correction in Monthly Records of Satellite Soil Moisture Using Nonuniform CDFs. Advances in Meteorology،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1118645
Modern Language Association (MLA)
Wang, Shan…[et al.]. Bias Correction in Monthly Records of Satellite Soil Moisture Using Nonuniform CDFs. Advances in Meteorology No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1118645
American Medical Association (AMA)
Wang, Shan& Shan, Huiling& Zhang, Chi& Wang, Yuexing& Shi, Chun-Xiang. Bias Correction in Monthly Records of Satellite Soil Moisture Using Nonuniform CDFs. Advances in Meteorology. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1118645
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118645