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Global reconstructed daily surge levels from the 20th Century Reanalysis (1871–2010)

Abstract: Studying the effect of global patterns of wind and pressure gradients on the sea level variation (storm surge) is a key issue in understanding the recent climate change effect on the dynamical state of the ocean. The analysis of the spatial and temporal variability of storm surges from observations is a difficult task to accomplish since observations are not homogeneous in time, scarce in space, and moreover, their temporal coverage is limited. A recent global surge database developed by AVISO (DAC, Dynamic Atmospheric Correction) fulfilled the lack of data in terms of spatial coverage, but not regarding time extent, since it only includes the last two decades (1992–2014). In this work, we use the 20th Century Reanalysis V2 (20CR), which spans the years 1871 to 2010, to statistically reconstruct daily maximum surge levels at a global scale. A multivariate linear regression model is fitted between daily mean ERA-interim sea level pressure fields and daily maximum surge levels from DAC. Following, the statistical model is used to reconstruct daily surges using mean sea level pressure fields from 20CR. The verification of the statistical model shows good agreements between DAC levels and the reconstructed surge levels from the 20CR. The validation of the reconstructed surge with tide gauges, distributed throughout the domain, shows good accuracy both in terms of high correlations and small errors. A time series comparison is also depicted at specific tide gauges for the beginning of the 20th century, showing a high concordance. Therefore, this work provides to the scientific community, a daily database of maximum surge levels; which correspond to an extension of the DAC database, from 1871 to 2010. This database can be used to improve the knowledge on historical storm surge conditions, allowing the study of their temporal and spatial variability.

 Fuente: Global and Planetary Change Volume 148, January 2017, Pages 9–21

 Publisher: Elsevier

 Publication date: 01/01/2017

 No. of pages: 13

 Publication type: Article

 DOI: 10.1016/j.gloplacha.2016.11.006

 ISSN: 0921-8181,1872-6364

 Spanish project: Grants TRA2014-59570-R ; BIA2014-59643-R ; BIA2015-70644-R.

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