Next Article in Journal
Local Effects of Forests on Temperatures across Europe
Previous Article in Journal
Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Remote Sens. 2018, 10(4), 528;

Spatio-Temporal Variability of Annual Sea Level Cycle in the Baltic Sea

College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
Shenzhen AeroImgInfo Technology Co., Ltd., Shenzhen 518000, China
College of Oceanography, Hohai University, Nanjing 210098, China
Jiangsu Key Laboratory of Coast Ocean Resources, Development and Environment Security, Hohai University, Nanjing 210098, China
Global Science and Technology, National Oceanic and Atmospheric Administration (NOAA)-National Environmental Satellite, Data, and Information Service (NESDIS), College Park, MD 20740, USA
Author to whom correspondence should be addressed.
Received: 28 February 2018 / Revised: 19 March 2018 / Accepted: 28 March 2018 / Published: 29 March 2018
(This article belongs to the Section Ocean Remote Sensing)
Full-Text   |   PDF [58979 KB, uploaded 3 May 2018]   |  


In coastal and semi-enclosed seas, the mean local sea level can significantly influence the magnitude of flooding in inundation areas. Using the cyclostationary empirical orthogonal function (CSEOF) method, we examine the spatial patterns and temporal variations of annual sea level cycle in the Baltic Sea based on satellite altimetry data, tide gauge data, and regional model reanalysis during 1993 and 2014. All datasets demonstrate coherent spatial and temporal annual sea level variability, although the model reanalysis shows a smaller interannual variation of annual sea level amplitude than other datasets. A large annual sea level cycle is observed in the Baltic Sea, except in the Danish straits from December to February. Compared with altimetry data, tide gauge data exhibit a stronger annual sea level cycle in the Baltic Sea (e.g., along the coasts and in the Gulf of Finland and the Gulf of Bothnia), particularly in the winter. Moreover, the maps of the maximum and minimum annual sea level amplitude imply that all datasets underestimate the maximum annual sea level amplitude. Analysis of the atmospheric forcing factors (e.g., sea level pressure, North Atlantic Oscillation (NAO), winds and air temperature), which may contribute to the interannual variation of the annual sea level cycle shows that both the zonal wind and winter NAO (e.g., from December to March) are highly correlated with the annual cycle variations in the tide gauge data in 1900–2012. In the altimetry era (1993–2014), all the atmospheric forcing factors are linked to the annual sea level cycle variations, particularly in 1996, 2010 and 2012, when a significant increase and drop of annual sea level amplitude are observed from all datasets, respectively. View Full-Text
Keywords: sea level; altimeter; Baltic Sea; annual cycle; CSEOF sea level; altimeter; Baltic Sea; annual cycle; CSEOF

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Cheng, Y.; Xu, Q.; Li, X. Spatio-Temporal Variability of Annual Sea Level Cycle in the Baltic Sea. Remote Sens. 2018, 10, 528.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top