Cause of Substantial Global Mean Sea Level Rise Over 2014-2016

GEOPHYSICAL RESEARCH LETTERS(2023)

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摘要
Global mean sea level rose by 15 mm over June 2014 - May 2016. This rise is 7 mm larger than the 8 mm increase associated with the long-term trend of 4 mm/yr estimated over 2006-2016. Using a combination of satellite gravimetry data and in situ measurements, we find that 20% of this rise is explained by ocean thermal expansion and 80% by an ocean mass increase, the latter being largely correlated with an equivalent terrestrial water storage (TWS) decrease. Half of the global ocean mass increase during that period can be attributed to the South American continent where we find a significant contribution of the TWS over the Amazon basin (5 mm). This TWS change between oceans and continents occurred during two El Nino events: one aborted in 2014-2015 and an extreme event in 2015-2016 which affected precipitation patterns, especially over the equatorial Pacific ocean and over South America. Plain Language Summary Interannual variability of global mean sea level (GMSL) change is linked to natural climate modes of variability such as El Nino Southern Oscillation (ENSO). Over May 2014-June 2016, two consecutive El Nino events (warm phase of ENSO) occurred in the tropical Pacific ocean: one aborted in 2014-2015 and an extreme event in 2015-2016. At the same time, satellite altimetry recorded a GMSL increase of 15 mm. 80% of the rise was due to a global ocean mass increase. Half of the global ocean mass increase is attributed to the South American continent with an exceptional contribution from the Amazon basin (5 mm). Those unusual El Nino events affected the precipitation pattern worldwide, decreasing the TWS in the Amazon basin and therefore leading to an increase of the global mean ocean mass. Our results suggest the importance of TWS changes, especially in the tropics, to explain interannual variability of GMSL recorded by satellite altimetry.
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关键词
global mean sea level,satellite altimetry,GRACE,argo data,interannual variability
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