Abstract's details

Estimation of the Topex A/B bias and associated uncertainty - A mutli methods approach

Victor Quet (CLS (Collecte Localisation Satellite), France)

Anna Mangilli (CLS (Collecte Localisation Satellite), France); Franck Octau (ALTEN pour CLS (Collecte Localisation Satellite), France); Pierre Prandi (CLS (Collecte Localisation Satellite), France); Benoit Meyssignac (CNES/LEGOS , France)

Event: 2023 Ocean Surface Topography Science Team Meeting

Session: Regional and Global CAL/VAL for Assembling a Climate Data Record

Presentation type: Forum only

Topex data have recently been reprocessed (GDR-F products) and this reprocessing has an impact on the Topex A / Topex B bias (February 1999) which has to be re-estimated. An accurate evaluation of this bias and associated uncertainty is important regarding two issues: (1) ensuring the continuity of the mean sea level record since 1993 and the preparation of the next version of reprocessed L2P products (L2P DT 24) and (2) the contribution of the associated uncertainty in the error budget of the Global Mean Sea Level. The uncertainty of the Topex bias is estimated to be ten times higher than other inter mission bias uncertainties (see Guerou et al. 2022: https://doi.org/10.5194/egusphere-2022-330), due to the lack of a verification phase between TPA and B

In this presentation, we use the latest release of TOPEX data to revisit the TPA/TPB bias. We compare different methods to estimate this bias. Each method has its own set of hypotheses that are presented and discussed, as well as their respective uncertainties. Our results suggest that the most accurate solution uses available ERS-2 data at that time. The impact of including reprocessed TOPEX data on the GMSL trend and acceleration is also discussed.

Contribution: CVL2023-Estimation_of_the_Topex_A_B_bias_and_associated_uncertainty_-_A_mutli_methods_approach.pdf (pdf, 2748 ko)

Corresponding author:

Victor Quet

CLS (Collecte Localisation Satellite)

France

vquet@groupcls.com

Back to the list of abstract