Error variance-covariance matrix of global mean sea level estimated from satellite altimetry (TOPEX, Jason 1, Jason 2, Jason 3)

Date 2018-12-18
Temporal extent 1993-01-01 -2017-12-31
Author(s) Ablain MichaelORCID1, Meyssignac BenoitORCID2, Zawadzki Lionel1, Jugier RémiORCID1, Ribes AurélienORCID3, Cazenave AnnyORCID2, Picot NicolasORCID2
Affiliation(s) 1 : CLS - Collecte Localisation Satellite, France
2 : CNES, LEGOS, Toulouse, France
3 : CNRM - Centre National de Recherche Météorologique, France
DOI 10.17882/58344
Publisher SEANOE
Keyword(s) error variance-covariance matrix, sea level, uncertainty, altimetry, Topex, Jason
Abstract

Satellite altimetry missions now provide more than 25 years of accurate, continuous and quasi-global measurements of sea level along the reference ground track of TOPEX-Poseidon. These measurements are used by different groups to build the Global Mean Sea Level (GMSL) record, an essential climate change indicator. Estimating a realistic uncertainty of the GMSL record is of crucial importance for climate studies such as estimating precisely the current rate and acceleration of sea level, analyzing the closure of the sea level budget, understanding the causes for sea level rise, detecting and attributing the response of sea level to anthropogenic activity, or estimating the Earth energy imbalance. Ablain et al. (2015) estimated the uncertainty of the GMSL trend over the period 1993-2014 by thoroughly analyzing the error budget of the satellite altimeters and showed that it amounts to 0.5 mm.yr-1 (90% confidence level). Here, we extend Ablain et al. (2015) analysis by providing a comprehensive description of the uncertainties in the satellite GMSL record. We analyse 25 years of satellite altimetry data and estimate for the first time the error variance-covariance matrix for the GMSL record with a time resolution of 10 days. Three types of errors that can affect satellite altimetry measurements are modelled (drifts, biases, noise) and combined together to derive a realistic estimate of the GMSL error variance-covariance matrix. From the error variance-covariance matrix, the uncertainty on any metrics related to GMSL can be derived including the 90% confidence envelop of the GMSL record on a 10-day basis, the GMSL trend and acceleration uncertainties over any time periods of 2 years and longer in between October 1992 and December 2017. Over 1993-2017 we find a GMSL trend of 3.35+-0.4 mm.yr-1 (90% CL) and a GMSL acceleration of 0.12 +-0.07 mm.yr-2 (90% CL) in agreement (within error bars) with previous studies. The full GMSL error variance-covariance matrix is freely available here.

Licence CC-BY-NC
Acknowledgments We thank CNES and the AVISO project for providing the data from TOPEX, Jason 1, Jason 2 and Jason 3.
Sensor metadata

Satellite altimetry measurement from TOPEX, JASON 1, JASON 2 and JASON 3

Data
File Size Format Processing Access
60898.nc 5 MB NC, NetCDF Processed data Open access
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How to cite 

Ablain Michael, Meyssignac Benoit, Zawadzki Lionel, Jugier Rémi, Ribes Aurélien, Cazenave Anny, Picot Nicolas (2018). Error variance-covariance matrix of global mean sea level estimated from satellite altimetry (TOPEX, Jason 1, Jason 2, Jason 3). SEANOE. https://doi.org/10.17882/58344


In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :


Ablain Michaël, Meyssignac Benoit, Zawadzki Lionel, Jugier Rémi, Ribes Aurélien, Cazenave Anny, Picot Nicolas (2019). Uncertainty in Satellite estimate of Global Mean Sea Level changes, trend and acceleration. Earth System Science Data Discussions, 1-26. https://doi.org/10.5194/essd-2019-10