SCIENCE CHINA Earth Sciences, Volume 62 , Issue 5 : 771-782(2019) https://doi.org/10.1007/s11430-018-9276-6

Relationship between sea surface salinity and ocean circulation and climate change

More info
  • ReceivedApr 5, 2018
  • AcceptedSep 25, 2018
  • PublishedJan 11, 2019


Funded by

the Chinese Academy of Sciences(Grant,No.,XDA19060501)

the State Oceanic Administration of China(Grant,No.,GASI-IPOV,AI-02)

and the National Natural Science Foundation of China(Grant,Nos.,41525019,41506019,&,41830538)


We thank Water Cycle Observation Mission (WCOM) group and PhD Student Qiwei SUN for their helps. Argo salinity data is available at (http://www.argo.ucsd.edu), EN4salinity data is obtained from (http://hadobs.metoffice.com/en4/index.html), CCMP wind data is provided by RSS (http://www.remss.com), sea surface height data is provided by AVISO (https://www.aviso.altimetry.fr), GPCP precipitation data is obtained from NASA/GSFC, evaporation data is provided by OAFlux (http://oaflux.whoi.edu), and ERA Interim sea level pressure data is provided by ECMWF (http://apps.ecmwf.int/datasets). This work was supported by the Chinese Academy of Sciences (Grant No. XDA19060501), the State Oceanic Administration of China (Grant No. GASI-IPOV AI-02), and the National Natural Science Foundation of China (Grant Nos. 41525019, 41506019 & 41830538).


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  • Figure 1

    Annual mean Argo sea surface salinity (SSS) (shaded, unit: psu) and evaporation minus precipitation (E-P, contour, unit: mm day−1).

  • Figure 2

    The interannual root mean square of the anomalies for Argo sea surface salinity (shaded, unit: psu) and evaporation minus precipitation (E-P, contour, unit: mm day−1), and the regional mean SSS (black curve) and E-P (blue curve) anomalies in the eastern equatorial Indian Ocean, western equatorial Pacific, eastern equatorial Pacific, northern Bay of Bengal, northwestern Atlantic, and western equatorial Atlantic. The anomalies are with respect to the climatology over the period from 2001 to 2017, and the long-term linear trend is subtracted. The bold curves in subgraphs 1–6 denote the 5-year running average. Note that in subgraph 6, the scale is half of the SSS anomaly in the region.

  • Figure 3

    Correlation of Argo SSS anomalies with precipitation (P), evaporation (E), and E-P. The dotted region passed the 95% confidence level according to a two-tailed Student’s t-test.

  • Figure 4

    Argo SSS linear trend (shaded, unit: psu) and the ratio of the long-term trend to the interannual variability (contour) for 2001–2017, and the average time series of the six maximum-value regions, namely the tropical southeast Indian Ocean, tropical northwestern Pacific, eastern equatorial Indian Ocean, southeastern Pacific, North Atlantic, and southwest Atlantic (unit: psu). The bold curves in subgraphs 1--6 denote the 5-year running average; and the gray lines superimposed in subgraph 1, 2, 4, and 5.

  • Figure 5

    Empirical orthogonal function (EOF) first mode of ERA-Interim sea surface pressure (unit: hPa) and cross-calibrated multiplatform wind field low frequency variation (unit: m s−1). (a) Spatial distribution; (b) time series. The seasonal cycles are removed and a 5-yearrunning average is applied.

  • Figure 6

    Time series of regional mean sea surface salinity in EN4 (unit: psu). (a) Northwestern Pacific and (b) southeastern Indian Ocean corresponding to regions 1 and 2 in Figure 4a, respectively. Bold curves denote the 5-year running average.

  • Figure 7

    (a) The linear trend in the AVISO sea surface height (SSH) anomaly during 1993–2016, (b) the time series of the regional mean SSH anomaly in the northwestern Pacific, and (c) the southeastern Indian Ocean (unit: cm). Rectangles in (a) denote the regions for (b) and (c), while bold curves in (b) and (c) denote the 5-year running average.


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