Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics

Study on satellite altimeter sea state bias estimation comprehensive model

Authors
Hongli Miao, Xin Wang, Guizhong Wang, Guoshou Zhang, Jie Zhang
Corresponding Author
Hongli Miao
Available Online June 2015.
DOI
https://doi.org/10.2991/icecee-15.2015.193How to use a DOI?
Keywords
satellite altimetry; sea state bias; parametric model; nonparametric model; latitude segmentation
Abstract
The sea state bias (SSB) is one of the most prominent errors in satellite altimetry. The empirical model was mostly used in practical estimation of SSB, which includes the parametric model and nonparametric model. The estimation of SSB for the global area will result to large deviation with a single model, due to the different distribution of sea condition as well as the different accuracy of the two models. In this paper, two models were applied in regions of different latitude. The results of two models were statistical analyzed and evaluated. The analysis indicate that: the nonparametric model is more effective in the area further north than 30°N while the parametric model is more effective in other areas.
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Proceedings
2015 2nd International Conference on Electrical, Computer Engineering and Electronics
Part of series
Advances in Computer Science Research
Publication Date
June 2015
ISBN
978-94-62520-81-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/icecee-15.2015.193How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hongli Miao
AU  - Xin Wang
AU  - Guizhong Wang
AU  - Guoshou Zhang
AU  - Jie Zhang
PY  - 2015/06
DA  - 2015/06
TI  - Study on satellite altimeter sea state bias estimation comprehensive model
BT  - 2015 2nd International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1020
EP  - 1024
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.193
DO  - https://doi.org/10.2991/icecee-15.2015.193
ID  - Miao2015/06
ER  -