FN Archimer Export Format
PT J
TI Improved Estimates of Changes in Upper Ocean Salinity and the Hydrological Cycle
BT 
AF Cheng, Lijing
   Trenberth, Kevin E.
   Gruber, Nicolas
   Abraham, John P.
   Fasullo, John T.
   Li, Guancheng
   Mann, Michael E.
   Zhao, Xuanming
   Zhu, Jiang
AS 1:1,2,3;2:4;3:5;4:6;5:4;6:1,3;7:7;8:1,3;9:1,2,3;
FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;
C1 International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
   Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China
   University of Chinese Academy of Sciences, Beijing, China
   National Center for Atmospheric Research, Boulder, Colorado
   Environmental Physics Group, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Zürich, Switzerland
   University of St. Thomas, School of Engineering, St. Paul, Minnesota
   Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania
C2 CHINESE ACAD SCI, CHINA
   CHINESE ACAD SCI, CHINA
   UNIV CHINESE ACAD SCI, CHINA
   NCAR NATL CTR ATMOSPHER RES, USA
   ETH ZURICH, SWITZERLAND
   UNIV ST THOMAS, USA
   UNIV PENN STATE, USA
IF 5.148
TC 99
UR https://archimer.ifremer.fr/doc/00779/89080/94653.pdf
   https://archimer.ifremer.fr/doc/00779/89080/94654.pdf
LA English
DT Article
CR OISO - OCÉAN INDIEN SERVICE D'OBSERVATION
DE ;Climate change;Salinity;Climate records;Sampling
AB Ocean salinity records the hydrological cycle and its changes, but data scarcity and the large changes in sampling make the reconstructions of long-term salinity changes challenging. Here, we present a new observational estimate of changes in ocean salinity since 1960 from the surface to 2000 m. We overcome some of the inconsistencies present in existing salinity reconstructions by using an interpolation technique that uses information on the spatiotemporal covariability of salinity taken from model simulations. The interpolation technique is comprehensively evaluated using recent Argo-dominated observations through subsample tests. The new product strengthens previous findings that ocean surface and subsurface salinity contrasts have increased (i.e., the existing salinity pattern has amplified). We quantify this contrast by assessing the difference between the salinity in regions of high and low salinity averaged over the top 2000 m, a metric we refer to as SC2000. The increase in SC2000 is highly distinguishable from the sampling error and less affected by interannual variability and sampling error than if this metric was computed just for the surface. SC2000 increased by 1.9% ± 0.6% from 1960 to 1990 and by 3.3% ± 0.4% from 1991 to 2017 (5.2% ± 0.4% for 1960–2017), indicating an acceleration of the pattern amplification in recent decades. Combining this estimate with model simulations, we show that the change in SC2000 since 1960 emerges clearly as an anthropogenic signal from the natural variability. Based on the salinity-contrast metrics and model simulations, we find a water cycle amplification of 2.6% ± 4.4% K−1since 1960, with the larger error than salinity metric mainly being due to model uncertainty. 
PY 2020
PD DEC
SO Journal Of Climate
SN 0894-8755
PU American Meteorological Society
VL 33
IS 23
UT 000615171300020
BP 10357
EP 10381
DI 10.1175/JCLI-D-20-0366.1
ID 89080
ER

EF