Analysis of the interannual variability in satellite gravity solutions: detection of climate modes fingerprints in water mass displacements across continents and oceans

Julia Pfeffer,Anne Barnoud,Anny Cazenave

doi:10.1007/s00382-021-05953-z

Abstract

This study analyzes the interannual variability of the water mass transport measured by satellite gravity missions in regard to eight major climate modes known to influence the Earth’s climate from regional to global scales. Using sparsity promoting techniques (i.e., LASSO), we automatically select the most relevant predictors of the climate variability among the eight candidates considered. The El Niño–Southern Oscillation, Southern Annular Mode and Arctic Oscillation are shown to account for a large part the interannual variability of the water mass transport observed in extratropical ocean basins (up to 40%) and shallow seas (up to 70%). A combination of three Pacific and one Atlantic modes is needed to account for most (up to 60%) of the interannual variability of the terrestrial water storage observed in the North Amazon, Parana and Zambezi basins. With our technique, the impact of climate modes on water mass changes can be tracked across distinct water reservoirs (oceans, continents and ice-covered regions) and we show that a combination of climate modes is necessary to explain at best the natural variability in water mass transport. The climate modes predictions based on LASSO inversions can be used to reduce the inter-annual variability in satellite gravity measurements and detect processes unrelated with the natural variability of climate but with similar spatio-temporal signatures. However, significant residuals in the satellite gravity measurements remain unexplained at inter-annual time scales and more complex models solving the water mass balance should be employed to better predict the variability of water mass distributions.

Highlights

Climate variability exerts profound influences on the water cycle, and society
A classical empirical orthogonal functions (EOF) analysis of the water mass changes observed by GRACE and GRACE-FO and the inferred correlations with climate indices are presented in the online resource (OR)
A large (10–15 mm) positive anomaly lies across the Southern Pacific and the Southern Ocean, which was detected in the EOF analyses of the JPL and CSR solutions

Summary

Introduction

Climate variability exerts profound influences on the water cycle, and society. Climate modes synthesize emergent characteristics of the climate system in various regions of the world. These repeating patterns of the climate variability are usually identified through the statistical analysis (e.g., regional average, empirical orthogonal functions (EOF), principal component analysis) of one or several climate fields, such as sea surface temperature, air temperature, air pressure, sea level pressure, sea surface height, precipitation, wind speed and wind direction. The Atlantic Multidecadal Oscillation (AMO), has been reported to have nearly global influences on the climate system (e.g., Knight et al 2006), including Amazonian (e.g., Kayano et al 2016) or Sahelian (e.g., Mohino et al 2011) rainfall, Atlantic hurricanes (e.g., Zhang and Delworth 2006), North American (e.g., Hu et al 2011) and European summer climate (e.g., Zampieri et al 2017). It has been suggested that climate modes may not be stationary and that the spatial and temporal characteristics of climate modes, as well as their relationships with one another, may be evolving in a changing climate (e.g., Litzow et al 2020)

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