Bivariate Reconstruction of Sea Level from 1900-2014

Robert Leben (University of Colorado Boulder, United States)

CoAuthors

Benjamin Hamlington (Old Dominion University, USA); Se-Hyeon Cheon (Old Dominion University, USA); Michael Shannon (University of Colorado Boulder, USA)

Event: 2016 Ocean Surface Topography Science Team Meeting

Session: Science I: Current and past mean sea level observations

Presentation type: Type Poster

Monthly sea level maps have been reconstructed for the time period from January 1900 through December 2014 based on historical measurements of sea level from tide gauges and sea surface temperature (SST) from surface marine observations. This gridded sea level dataset is unique because it accurately reconstructs both climate signals and global mean sea level (GMSL) over the entire 115-year record, which only recently became feasible with the development of a novel bivariate reconstruction technique. Sea level reconstructions based solely on sea level measurements before 1950 are limited to reconstruction of GMSL because the historical tide gauge distribution is too sparse to map interannual and decadal sea level patterns associated with climate variability. The bivariate sea level reconstruction is formed using cyclostationary basis functions computed from satellite measurements of SST and sea level anomaly. SST basis functions are transformed using a simple regression technique to exhibit temporal evolution equivalent to the corresponding altimeter-derived SLA basis functions. The resulting SLA and SST basis functions are fit to sea level and SST measurements to produce a reconstructed sea level data set spanning the historical record. The method was extensively tested in a reconstruction of Pacific Ocean sea level and demonstrated accurate reconstruction of climate signals such as the El Nino/Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) when compared to commonly used indices over the time period from 1900 to present. The technique has now been applied on a global scale by combining tandem reconstructions of Indo-Pacific and Atlantic sea level. A preliminary evaluation of the dataset is presented in preparation for public release. This bivariate reconstruction of sea level provides a more complete global view of the historical record of sea level and the probable impacts of climate variability on GMSL and regional sea level change now and in the future.
 

Poster show times:

RoomStart DateEnd Date
Grande Halle Thu, Nov 03 2016,11:00 Thu, Nov 03 2016,18:00
Robert Leben
University of Colorado Boulder
United States
leben@colorado.edu