Propagation of Thermohaline Anomalies and Their Predictive Potential along the Atlantic Water Pathway

Author:

Langehaug H. R.1,Ortega P.2,Counillon F.13,Matei D.4,Maroon E.5,Keenlyside N.3,Mignot J.6,Wang Y.1,Swingedouw D.7,Bethke I.3,Yang S.8,Danabasoglu G.9,Bellucci A.1011,Ruggieri P.1012,Nicolì D.10,Årthun M.3

Affiliation:

1. a Nansen Environmental and Remote Sensing Center, and Bjerknes Centre for Climate Research, Bergen, Norway

2. b Barcelona Supercomputing Center, Barcelona, Spain

3. c Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway

4. d Max Planck Institute for Meteorology, Hamburg, Germany

5. e University of Wisconsin–Madison, Madison, Wisconsin

6. f UMR LOCEAN, Sorbonne Université/IRD/MNHN/CNRS, IPSL, Paris, France

7. g Environnements et paléoenvironnements océaniques et continentaux (EPOC), UMR CNRS 5805 EPOC, Université de Bordeaux, Allée Geoffroy-Saint-Hilaire, Pessac, France

8. h Danish Meteorological Institute, Copenhagen, Denmark

9. i National Center for Atmospheric Research, Boulder, Colorado

10. j Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Bologna, Italy

11. k Istituto di Scienze dell’Atmosfera e del Clima, Consiglio Nazionale delle Ricerche, Bologna, Italy

12. l Department of Physics and Astronomy, University of Bologna, Bologna, Italy

Abstract

Abstract We assess to what extent seven state-of-the-art dynamical prediction systems can retrospectively predict winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic seas in the period 1970–2005. We focus on the region where warm water flows poleward (i.e., the Atlantic water pathway to the Arctic) and on interannual-to-decadal time scales. Observational studies demonstrate predictability several years in advance in this region, but we find that SST skill is low with significant skill only at a lead time of 1–2 years. To better understand why the prediction systems have predictive skill or lack thereof, we assess the skill of the systems to reproduce a spatiotemporal SST pattern based on observations. The physical mechanism underlying this pattern is a propagation of oceanic anomalies from low to high latitudes along the major currents, the North Atlantic Current and the Norwegian Atlantic Current. We find that the prediction systems have difficulties in reproducing this pattern. To identify whether the misrepresentation is due to incorrect model physics, we assess the respective uninitialized historical simulations. These simulations also tend to misrepresent the spatiotemporal SST pattern, indicating that the physical mechanism is not properly simulated. However, the representation of the pattern is slightly degraded in the predictions compared to historical runs, which could be a result of initialization shocks and forecast drift effects. Ways to enhance predictions could include improved initialization and better simulation of poleward circulation of anomalies. This might require model resolutions in which flow over complex bathymetry and the physics of mesoscale ocean eddies and their interactions with the atmosphere are resolved. Significance Statement In this study, we find that dynamical prediction systems and their respective climate models struggle to realistically represent ocean surface temperature variability in the eastern subpolar North Atlantic and Nordic seas on interannual-to-decadal time scales. In previous studies, ocean advection is proposed as a key mechanism in propagating temperature anomalies along the Atlantic water pathway toward the Arctic Ocean. Our analysis suggests that the predicted temperature anomalies are not properly circulated to the north; this is a result of model errors that seems to be exacerbated by the effect of initialization shocks and forecast drift. Better climate predictions in the study region will thus require improving the initialization step, as well as enhancing process representation in the climate models.

Funder

Horizon 2020 Framework Programme

Trond Mohn Foundation

NordForsk

National Science Foundation

Publisher

American Meteorological Society

Subject

Atmospheric Science

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