ASCAT Wind Superobbing Based on Feature Box
Joint Authors
Zhang, Weimin
Duan, Boheng
Dai, Haijin
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-22
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Redundant observations impose a computational burden on an operational data assimilation system, and assimilation using high-resolution satellite observation data sets at full resolution leads to poorer analyses and forecasts than lower resolution data sets, since high-resolution data may introduce correlated error in the assimilation.
Thus, it is essential to thin the observations to alleviate these problems.
Superobbing like other data thinning methods lowers the effect of correlated error by reducing the data density.
Besides, it has the added advantage of reducing the uncorrelated error through averaging.
However, thinning method using averaging could lead to the loss of some meteorological features, especially in extreme weather conditions.
In this paper, we offer a new superobbing method which takes into consideration the meteorological features.
The new method shows very good error characteristic, and the numerical simulation experiment of typhoon “Lionrock” (2016) shows that it has a positive impact on the analysis and forecast compared to the traditional superobbing.
American Psychological Association (APA)
Duan, Boheng& Zhang, Weimin& Dai, Haijin. 2018. ASCAT Wind Superobbing Based on Feature Box. Advances in Meteorology،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1118689
Modern Language Association (MLA)
Duan, Boheng…[et al.]. ASCAT Wind Superobbing Based on Feature Box. Advances in Meteorology No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1118689
American Medical Association (AMA)
Duan, Boheng& Zhang, Weimin& Dai, Haijin. ASCAT Wind Superobbing Based on Feature Box. Advances in Meteorology. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1118689
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118689