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Density-compensated overturning in the Labrador Sea


The Atlantic Meridional Overturning Circulation, a key constituent of the climate system, is projected to slow down in the twenty-first century due to a weakening of the Labrador Sea convection, itself a response to greenhouse gas warming and/or enhanced freshwater flux from the Arctic. However, the first observations from the Overturning in the Subpolar North Atlantic Program reveal a minimal response of the Meridional Overturning Circulation to the strong Labrador Sea convection during the winters of 2015–2016. From an analysis of the observational and reanalysis data, we show here that this weak response can be explained by a strong density compensation in the Labrador Sea. Although convection induces important changes of temperature and salinity in the basin interior, the export of the thermal and haline anomalies to the boundary current largely takes place along density surfaces. As a result, the transformation across density surfaces, that is, the imprint on the overturning circulation, is relatively small. This finding highlights the critical relationship between temperature and salinity in determining the overturning strength in the Labrador Sea and underlines the necessity of accurate freshwater flux estimates for improved Meridional Overturning Circulation predictions.

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Fig. 1: Observed circulation along OSNAP West.
Fig. 2: Observed property fields along OSNAP West.
Fig. 3: Observed transformation in θS space.
Fig. 4: A schematic of the transformation along OSNAP West.
Fig. 5: Variability of LSW volume and overturning transports.

Data availability

OSNAP data were collected and made freely available by the OSNAP project and all the national programs that contribute to it ( Data from the full OSNAP array for the first 21 months (31 July 2014 to 20 April 2016) were used to produce the 30-day mean time series across the whole section, as well as the gridded property fields. This derived data is at Data from GloSea5 (re-gridded to 1 × 1°) is available from under product name GLOBAL_REANALYSIS_PHY_001_026. EN4.2.1 data used in Extended Data Figs. 4 and 6 were downloaded from

Code availability

The code used to generate MOC and transport in the temperature and salinity space can be accessed upon request to S.Z.


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S.Z., M.S.L. and F.L. gratefully acknowledge the Physical Oceanography Program of the US National Science Foundation (fund code 3331843). R.A. acknowledges support from NSF award OCE 1553593. L.J. is funded by the Copernicus Marine Environment Monitoring Service (CMEMS: 23-GLO-RAN). The authors acknowledge the work of K. A. Peterson in creating the GloSea5 reanalysis.

Author information




S.Z., M.S.L. and F.L. led the data analysis. F.L. conducted the MOC calculation. R.A. proposed and formulated the calculation for overturning in temperature and salinity space. L.J. provided the GloSea5 data and assisted with the calculation of MOC. All the authors contributed to interpretation of the results and writing of the manuscript .

Corresponding author

Correspondence to Sijia Zou.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editor: Heike Langenberg.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Simulated mean property distribution in GloSea5.

(a) Mean potential temperature averaged between August 2014 and April 2016 along simulated OSNAP West section. (b) Mean salinity from the same source. (c) Mean PV (×10−12m−1s−1) from the same source. The simulated OSNAP West section is created using model grid points that minimize the distance from the grid locations to the observational locations. Temperature, salinity and PV are then extracted along the section. Note that the section definition allows for an accurate calculation of the transport on the model grid.

Extended Data Fig. 2 Simulated mean circulation in GloSea5.

(a) The mean velocity perpendicular to the simulated OSNAP West section during August 2014 and April 2016. Positive (negative) velocities indicate flow into (out of) the basin. Mean volume flux in each density class is labeled, similar to that in Fig. 1b. Note that the along-isopycnal transport in each layer is stronger in GloSea5 compared to the observations (Fig. 1b). This is because that when integrating the total positive/negative transport across the section, the recirculation branches in the basin interior are also included. (b) Mean volume flux in θ-S space from the reanalysis. Black arrow indicates direction of the diapycnal transformation.

Extended Data Fig. 3 Simulated mean overturning streamfunction in GloSea5.

(a) The mean overturning streamfunction in density space during August 2014 - April 2016 (solid black), with monthly SD shaded in gray. Dashed curve indicates the overturning streamfunction averaged over the entire temporal domain from the reanalysis (that is 1993-2017). (b) Similar to (a), but in θ space. (c) Similar to (a), but in S space.

Extended Data Fig. 4 Observed monthly variability of LSW volume.

Monthly time series of the total area (unit: m2) with low potential vorticity (PV≤6 × 10−12m−1s−1) across OSNAP West from observations (black), and the total volume (unit: m3) with low PV in the entire Labrador Basin (gray) from the Met Office Hadley Centre observational datasets EN4.2.1 (S. A. Good, M. J. Martin, M. J. & N. A. Rayner, N. A., J. Geophys. Res. Oceans 118, 6704–6716; 2013). Plotted are the anomalies relative to the 21-month mean.

Extended Data Fig. 5 Observed relationship between MOCθ (MOCS) and temperature (salinity) distribution.

(a) Observed monthly anomalies of MOCθ (orange) since August 2014 and potential temperature difference between the WGC and the LC (that is θ[WGC]−θ[LC]) at 700–800 m (solid black), the depths at which the correlation between the two time series is the strongest. The temperature anomalies for the WGC (that is θ[WGC]) are plotted in dashed black and the negative temperature anomalies for the LC (that is −θ[LC]) are shown in dashed gray. (b) Similar to (a), but for MOCS and salinity anomalies in the boundary current.

Extended Data Fig. 6 Strong monthly LSW layer volume variability.

Plotted in black is the LSW layer (27.70-27.80 kg/m3) volume variability within the Labrador Sea (northwest of OSNAP West) since August 2014, which is derived from EN4.2.1 (S. A. Good, M. J. Martin, M. J. & N. A. Rayner, N. A., J. Geophys. Res. Oceans 118, 6704–6716; 2013). Observed monthly transport in the LSW layer across OSNAP West is plotted in blue. The variability between the two time series is similar (r = 0.61), but the magnitude differs significantly.

Extended Data Fig. 7 Simulated monthly LSW volume and overturning transports in GloSea5.

Climatological monthly time series of newly-formed LSW volume (gray bars), MOCθ (dashed orange), MOCS (dashed blue), and MOCσ (dashed black) from GloSea5 during 1993-2017. Shaded areas represent 2×standard deviation of the annually varying transport for each month. The simulated transport time series during the OSNAP time period (August 2014 – April 2016) are plotted in solid colored lines.

Extended Data Fig. 8 Relationship between interannual MOCθ (MOCS) and temperature (salinity) distribution in GloSea5.

(a) Simulated annual anomalies of MOCθ (orange) and the temperature difference between the WGC and the LC (that is θ[WGC]−θ[LC]) at 200-300m (solid black). The depths between 200-300m are where the maximum correlation between MOCθ and temperature difference is reached. The temperature anomalies for the WGC alone (that is θ[WGC]) are plotted in dashed black and the minus temperature anomalies for the LC (that is −θ[LC]) are plotted in dashed gray. (b) Similar to (a), but for MOCS and salinity anomalies in the boundary current.

Extended Data Fig. 9 Observed overturning streamfunction with the traditional calculation.

The 21-month mean overturning streamfunction integrated from low density to high density (solid black), with monthly standard deviation shaded in gray. The MOC with this calculation is 1.4 ± 1.7Sv (see Methods).

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Zou, S., Lozier, M.S., Li, F. et al. Density-compensated overturning in the Labrador Sea. Nat. Geosci. 13, 121–126 (2020).

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