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Observed poleward freshwater transport since 1970

Nature volume 602, pages 617–622 (2022)Cite this article

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Abstract

Warming-induced global water cycle changes pose a significant challenge to global ecosystems and human society. However, quantifying historical water cycle change is difficult owing to a dearth of direct observations, particularly over the ocean, where 77% and 85% of global precipitation and evaporation occur, respectively1,2,3. Air–sea fluxes of freshwater imprint on ocean salinity such that mean salinity is lowest in the warmest and coldest parts of the ocean, and is highest at intermediate temperatures4. Here we track salinity trends in the warm, salty fraction of the ocean, and quantify the observed net poleward transport of freshwater in the Earth system from 1970 to 2014. Over this period, poleward freshwater transport from warm to cold ocean regions has occurred at a rate of 34–62 milli-sverdrups (mSv = 103 m3 s−1), a rate that is not replicated in the current generation of climate models (the Climate Model Intercomparison Project Phase 6 (CMIP6)). In CMIP6 models, surface freshwater flux intensification in warm ocean regions leads to an approximately equivalent change in ocean freshwater content, with little impact from ocean mixing and circulation. Should this partition of processes hold for the real world, the implication is that the historical surface flux amplification is weaker (0.3–4.6%) in CMIP6 compared with observations (3.0–7.4%). These results establish a historical constraint on poleward freshwater transport that will assist in addressing biases in climate models.

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Fig. 1: Coherent patterns of historical salinity change in observed and modelled zonally averaged salinity.
Fig. 2: Enhanced salinity contrasts in observed and modelled global T–S curves.
Fig. 3: Historical freshwater content change in observations and climate models, quantified from 1970 to 2014.
Fig. 4: Impact of changing surface freshwater fluxes on freshwater content in climate models.

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Data availability

All datasets used in this study are publicly available. EN4 data are available from the Met Office Hadley Centre (https://www.metoffice.gov.uk/hadobs/en4/download.html), IAP data are available from the Chinese Academy of Sciences (temperature: https://climatedataguide.ucar.edu/climate-data/ ocean-temperature-analysis-and-heat-content- estimate-institute-atmospheric-physics; salinity: http://159.226.119.60/cheng/), Ishii data are available from the National Center for Atmospheric Research (https://rda.ucar.edu/datasets/ds285.3/) and ERA5 data are available from ECMWF (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5). CMIP6 and DAMIP model outputs are available from the Earth System Grid Federation34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59 (ESGF; https://sgf-node.llnl.gov/search/cmip6).

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Acknowledgements

We acknowledge the World Climate Research Programme, the CMIP6 and DAMIP climate modelling groups, the ESGF and the funding agencies supporting CMIP6, DAMIP and ESGF. Modelling and analysis were undertaken with National Computational Infrastructure facilities, supported by the Australian Government. This work is supported by the Australian Research Council Centre of Excellence for Climate Extremes, the Centre for Southern Hemisphere Oceans Research (a joint research centre between the Qingdao National Laboratory for Marine Science and Technology and CSIRO) and the Australian Research Council Discovery Project scheme (DP190101173). We appreciate feedback from L. Zhang, which served to greatly sharpen the focus and direction of this work.

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Authors and Affiliations

  1. School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales, Australia

    Taimoor Sohail & Jan D. Zika

  2. UNSW Data Science Hub, University of New South Wales, Sydney, New South Wales, Australia

    Jan D. Zika

  3. Australian Centre for Excellence in Antarctic Science (ACEAS), University of New South Wales, Sydney, New South Wales, Australia

    Jan D. Zika & John A. Church

  4. Climate Science Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Hobart, Tasmania, Australia

    Damien B. Irving

  5. Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia

    Damien B. Irving & John A. Church

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Contributions

This study was conceived by T.S. and J.D.Z. T.S. wrote the manuscript, with editing and feedback from all co-authors. D.B.I. analysed the raw CMIP6 and DAMIP files, binning into fixed-temperature space, and zonally averaging the CMIP6 data. T.S. analysed all observational datasets, as well as the binned and zonally averaged CMIP6 and DAMIP files. All authors contributed to the research direction of the study by providing scientific advice and help with interpretation of results through all stages of the research process.

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Correspondence to Taimoor Sohail.

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Nature thanks Lei Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Time-averaged T—S curve and surface freshwater fluxes in observations and models.

a) Global T – S curve averaged from 1970 to 2014 in the observations14,21,23 and over the pre-industrial control period in the CMIP6 models24, and b) global surface freshwater fluxes \({{\mathscr{F}}}_{s}\), averaged over the pre-industrial control period in the CMIP6 models, and integrated from hot to cold. Thin grey lines represent each of the 20 CMIP6 models analysed, from Table S1, and thick grey line represents the CMIP6 multi-model mean (MMM). The right-hand y-axis shows the corresponding accumulated temperature-percentile in observations, and horizontal dotted lines indicate the warmest 2% and warmest 6% of the ocean by volume.

Extended Data Fig. 2 Comparing mean salinity changes in fixed-temperature and temperature-percentile frameworks.

Mean salinity change from 1970 to 2014, in g/kg/year, in temperature-percentiles (black lines) and absolute temperature coordinates (red lines), in a) composite observations14,21,23 and b) the CMIP6 MMM24.

Extended Data Fig. 3 Tracking northward outcrop migration of fixed-temperature and temperature-percentile surfaces.

Sea surface salinity tendency, in g/kg/year, in a) composite observations14,21,23, and b) the CMIP6 MMM24. Dashed red lines show the time-mean outcrop of the 2% and 6% warmest ocean by volume from 1970–1980, and solid red lines show the time-mean outcrop of the 2% and 6% warmest ocean by volume from 2004–2014. Solid blue lines show the time-mean outcrop location of the 1970–1980 isotherm (corresponding to the dashed red line) in 2004–2014. Maps sources are a) composite observations14,21,23 and b) the CMIP6 suite of models24.

Extended Data Fig. 4 Enhanced salinity contrasts in observed and modelled global T—S curves.

The global time-mean T–S curve from 1970–2014 (dashed black line), and the 1970–2014 time-mean T–S curve after 100 years of the 1970–2014 linear trend in temperature and salinity (solid black line), in a) observations14,21,23, and b) the subset of CMIP6 models which correspond to the DAMIP models analysed, c) the GHG-only DAMIP runs, and d) the AA-only DAMIP runs25. The y-component of the arrow vectors is the change in temperature at constant temperature-percentile [°C/century] and the x-component is the change in salinity [g/kg/century], as shown in the key in d). The colour of the arrows indicates salinification (red) or freshening (blue). The right-hand y-axis shows the corresponding accumulated temperature percentile in observations.

Extended Data Fig. 5 Impact of internal variability on freshwater content change in climate models.

The change in freshwater content in a) and b) the warmest 2% of the ocean, c) and d) the warmest 6% of the ocean, and e) and f) the layer of 2–6% warmest ocean volume, relative to a 1970–1980 baseline, in all observational data sets14,21,22,23, CMIP6 model historical model runs24, a), c) and e) 30 ACCESS-ESM1-5 historical ensemble members (thin blue lines) and b), d) and f) 28 CNRM-CM6-1 historical ensemble members (thin orange lines). Thick blue (orange) lines show the ensemble mean freshwater content change in the ACCESS-ESM1-5 (CNRM-CM6-1) model. Dotted blue (orange) lines show the specific ACCESS-ESM1-5 (CNRM-CM6-1) ensemble member used in the CMIP6 multi-model analysis. Thin grey lines represent each of the 20 CMIP6 model members analysed (from Table S1). Histograms show the rate of freshwater change, calculated as the slope of a linear regression (in mSv), of each model, ensemble member and observational product.

Extended Data Fig. 6 Impact of changing surface freshwater fluxes on freshwater content in historical climate models.

The relationship between surface freshwater flux amplification (relative to pre-industrial surface freshwater fluxes) and the rate of freshwater content change (based on the 1970–2014 linear trend; in mSv) in the DAMIP25 GHG-only, AA-only and corresponding six CMIP6 historical runs24 (red, blue and purple dots, respectively), in a) the warmest 2% of the ocean and b) the warmest 6% of the ocean. Small black dots show the broader suite of fourteen other CMIP6 historical simulations. The dotted line represents the linear regression across the DAMIP runs and their corresponding CMIP6 historical runs. The grey shaded region shows the envelope of maximum error associated with the linear regression. The green shaded region is an estimate of surface flux intensification based on the (known) observed freshwater content change and the linear regression (considering the regression error in shaded in grey). The vertical black line in the green shaded area is an estimate of surface flux intensification based on the mean rate of freshwater content change across all observations.

Extended Data Fig. 7 Relationship between surface freshwater fluxes and global freshwater content across all temperature-percentiles.

a) The global freshwater accumulation rate, integrated from hot to cold, inferred from the salinity tendency in observations14,21,22,23 and the CMIP6 models24. b) The surface freshwater flux (\(P-E+R\)) change, integrated from hot to cold, in the CMIP6 models. Thin grey lines represent each of the 20 CMIP6 model members analysed (from Table S1). c) The global freshwater accumulation rate, integrated from hot to cold, inferred from the salinity tendency in the DAMIP models25 and corresponding CMIP6 historical runs. d) The surface freshwater flux change, integrated from hot to cold, in the DAMIP model and corresponding CMIP6 historical runs. Orange shading in a) shows the standard error of the slope of the linear regression over time. The right-hand y-axis shows the corresponding temperature-percentile in the observational dataset. Horizontal dotted lines indicate the warmest 2% and warmest 6% of the ocean.

Extended Data Table 1 Suite of CMIP6 models analysed in this study
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Extended Data Table 2 Suite of DAMIP models analysed in this study
Full size table

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Sohail, T., Zika, J.D., Irving, D.B. et al. Observed poleward freshwater transport since 1970. Nature 602, 617–622 (2022). https://doi.org/10.1038/s41586-021-04370-w

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