Abstract
Anthropogenic greenhouse gas emissions have caused an imbalance in the energy content of the Earth's system, warming the atmosphere, the land surface, the cryosphere and the ocean. On a global scale, over the last five decades, the ocean has stored more than 90% of the heat excess associated with the Earth energy imbalance. This absorption of heat by the ocean leads to an increased Oceanic Heat Content (OHC). As the OHC rises, the global mean sea-level increases due to thermal expansion, a mechanism known as the global mean thermosteric sea-level (TSL) rise. In order to monitor accurately the global OHC and global mean TSL, one of the main sources of data is in situ Temperature and Salinity profiles. These profiles need to be interpolated on a regular grid to prevent any bias due to regional over or under-sampling. However, to date, OHC and TSL estimates and their associated uncertainties are sensitive to the parameterization and a priori assumption of the interpolation tools. To address this issue in a controlled framework, we run sensitive experiments where we adjust the configuration of the In Situ Analysis System (ISAS) interpolation tool. To do so, we extracted “synthetic profiles” of Temperature and Salinity from NEMO simulations, integrated over the 1980-2020 period.  We interpolated these profiles with ISAS and compared them with the original model outputs. This comparison allows us to improve the parameterization and a priori assumption of ISAS in order to, ultimately, provide a better understanding of the sensitivity of the global and regional OHC and TSL estimates. Here we present the first results of this work.
Published Version
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