Abstract's details

Improving long term estimates of global mean sea level, global ocean heat content and Earth's energy imbalance using CDR water vapour data

Anne Barnoud (Magellium, 1 rue Ariane, 31520 Ramonville Saint-Agne, France)


Bruno Picard (Fluctus, Rabastens, France); Benoit Meyssignac (LEGOS, Université de Toulouse, CNES, CNRS, UPS, IRD, 31000 Toulouse, France); Florence Marti (Magellium, 1 rue Ariane, 31520 Ramonville Saint-Agne, France); Michaël Ablain (Magellium, 1 rue Ariane, 31520 Ramonville Saint-Agne, France); Rémy Roca (LEGOS, Université de Toulouse, CNES, CNRS, UPS, IRD, 31000 Toulouse, France)

Event: 2022 Ocean Surface Topography Science Team Meeting

Session: Quantifying Errors and Uncertainties in Altimetry data

Presentation type: Type Oral

The Earth’s energy imbalance (EEI) quantifies the excess of radiative energy received from the sun compared to the infrared energy radiated by the Earth. The EEI has recently been estimated from global ocean heat content (GOHC) based on satellite altimetry and satellite gravimetric data with a typical accuracy of 0.2 W.m-2 (with a 90% confidence level) on decadal time scales which is not sufficient to monitor and understand the climate variability due to large volcanic eruptions, to the recent hiatus or to anthropogenic activities. The wet tropospheric correction (WTC) used to compute the altimetric-based sea level data is derived from the microwave radiometers (MWR) on board the altimetry missions. It is identified as a major source of error in the global mean sea level (GMSL) rise (Ablain et al., 2019), affecting the GOHC and EEI estimates derived from satellite geodetic data. In this study, we show that the MWR-derived WTC from altimetry missions is responsible for about 15 % of the EEI trend uncertainty variance.

Motivated by the recent emergence of high long-term stability of climate data records (CDR) of water vapour outlined by the GEWEX water vapour assessment (Schröder et al., 2016), we also investigate the feasibility and advantages of using these data to estimate a more stable WTC for altimetric-based sea level data, hence to improve our knowledge on the GMSL, GOHC and EEI. To compute the WTC from CDR water vapour data, we use a polynomial formula whose coefficients and associated uncertainties are determined using ECMWF ERA5 reanalysis data. Then, we use CDR water vapour data provided by HOAPS and REMSS to compute a new WTC along the L2P altimetric tracks. With an empirical approach, we estimate that the CDR-derived WTC trend has an uncertainty of 0.05 mm/yr whatever the dataset and the period considered. Over 2016/2020, the comparison of MWR-based with CDR-based WTC shows a likely drift of the Jason-3 MWR of the order of 0.5 mm.yr-1 that would tend to overestimate the GMSL trend, the GOHC trend and the EEI mean. Over 08/2002-08/2016, the EEI mean so far estimated to 0.748 ± 0.129 W.m⁻² with the usual radiometer WTC is now estimated to 0.829 ± 0.122 W.m⁻² using REMSS CDR water vapour data (standard uncertainties). This corresponds to a trend increase of 11 % and a relative uncertainty variance reduction of 12 %. This study suggests that a new WTC combining high-frequencies from the radiometer and low-frequencies from the CDR data could help improve the long term estimates of the EEI. However, a better characterisation of the water vapour uncertainties is needed to estimate more accurately the uncertainty of the CDR-derived WTC and its impact on the GMSL, GOHC and EEI time series.

Oral presentation show times:

Room Start Date End Date
Sala Grande Thu, Nov 03 2022,10:15 Thu, Nov 03 2022,10:30
Anne Barnoud
Magellium, 1 rue Ariane, 31520 Ramonville Saint-Agne