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An important feature of ocean circulation in the Atlantic is the cross-equatorial and northward transport of water masses at the surface and southward transport at the bottom of the ocean by the Atlantic Meridional Overturning Circulation (AMOC). However, the link between the AMOC and tropical Atlantic variability remain poorly understood. This is partly due lack of long-term observations of the AMOC, with the longest direct measurements available since 2004. Here we construct a dynamic sea-level proxy of the AMOC variability during the twentieth century, which is strongly correlated with the AMOC index during the observational period from 2005-2019 (r=0.50; p=1.48×10-9). This sea-level proxy exhibits a 10-15 year periodicity similar to the pan-Atlantic Decadal Oscillation (ADO) – the north-south bands of alternate anomalies in surface-ocean temperatures with the maximum variance over the tropical Atlantic, and winds from colder bands to the warmer. The sea level-derived proxy leads the ADO pattern by several years, through the interactions of overturning and gyre circulations with Kelvin wave anomalies that propagate from the North Atlantic to the low latitudes and by the thermocline feedback in the Atlantic cold tongue region. The peak of the sea surface temperature variability in the tropical Atlantic in turn drives inter-hemispheric atmospheric teleconnections represented by negative North Atlantic Oscillation phase over the North Atlantic. These findings imply that, rather than a passive role postulated by the prevailing thermodynamic paradigm, AMOC-related ocean circulation plays an active role in ADO variability.

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. Acknowledgments. The research leading to these results has received funding from the Blue-Action Project (European Union’s Horizon 2020 research and innovation program, Grant 727852), the Trond Mohn Foundation with the project Bjerknes Climate Prediction Unit (BCPU, Grant BFS2018TMT01), the NordForsk under the Nordic Centre of Excellence (ARCPATH, 76654), and from the Bjerknes Centre with the project SKD MEDEVAC. The research leading to these results has also received funding from the German Federal Ministry of Education and Research (BMBF) through the JPI Climate/JPI Oceans NextG-Climate Science-ROADMAP (FKZ: 01LP2002A; DM and Norwegian Grant 316618/JPIC/JPIO-04; HRL and NK and ANR-19-JPOC-003; JM). PO was funded by the Spanish Ministry for the Economy, Industry and Competitiveness through the grant RYC-2017-22772. SY also receives financial support from the Danish National Center for Climate Research (NCKF). The National Center for Atmospheric Research is a major facility sponsored by the U.S. National Science Foundation (NSF) under Cooperative Agreement 1852977. EM is supported by the U.S. NSF Office of Polar Programs Grant 1737377. The prediction simulations using EC-EARTH anomaly initialization system were performed by SMHI on resources provided by the Swedish National Infrastructure for Computing (SNIC). Peer Reviewed "Article signat per 16 autors/es: H. R. Langehaug, P. Ortega, F. Counillon, D. Matei, E. Maroon, N. Keenlyside, J. Mignot, Y. Wang, D. Swingedouw, I. Bethke, S. Yang, G. Danabasoglu, A. Bellucci, P. Ruggieri, D. Nicolì, and M. Årthun"

ICAWA : International Conference AWA, Lanzarote, ESP, 17-/04/2018 - 20/04/2018; Many questions remain open concerning the effect of environmental variability on abundance and distribution dynamics of round sardinella (Sardinella aurita) over the Canary upwelling system. This issue is of special relevance due to the great role that sardinella plays in northwest African fisheries and marine ecosystems. Here, the possible climate drivers of sardinella population migration along the northwest Africa are addressed. To this aim, we have used data provided by the coupled model compounded by the Regional Oceanic Modelling System ROMS, configured for the northwest African upwelling system, and by the biogeochemical model PISCES, which simulates plankton productivity and carbon biomass based upon the main nutrients. This coupled model has been run over the period 1980-2009 using an atmospheric reanalysis and consistent oceanic boundary conditions. Finally, an evolutionary individual-based Lagrangian model has been used to simulate the spatio-temporal behaviour of sardinella according to the environmental constraints obtained from ROMS-PISCES. Strikingly, a robust anomalous increase (decrease) of sardinella biomass has been identified from early to late winter off Cape Blanc (Saharan coast) in response to the Pacific El Niño conditions. This dipolar pattern reflects an alteration of the normal migration of sardinella between the Saharan and the Mauritanian waters and seems to be primarily mediated by the effect that El Niño-related anomalous winds has on the meridional currents along the northwest African coast. This sardinella response to El Niño is reinforced in late winter through an anomalous warming of the Mauritanian waters due to an anomalous weakening of coastal upwelling also forced by the aforementioned El Niño-related anomalous winds. According to our results this anomalous response of sardinella biomass might be predicted, for El Niño years, few months in advance from the El Niño-related SST patterns. This fact opens the possibility to the development of predictive tools, which should be necessarily assessed in further works.

The oceans have a profound influence on the weather and climate of South Africa. Not only, most rainfall comes from condensation of water vapor originating from the flux of moisture from ocean to atmosphere but the temperature of the remote and surrounding oceans have an impact of the interannual variability of rainfall. A good example of this remote effect is the impact of the ocean during El Nino when the temperature of the Pacific and Indian Ocean is higher than normal. This creates more rainfall above the higher sea surface temperature thus modifying the global Walker and Hadley circulation. Air usually rises in the equatorial regions, especially above the ocean creating rainfall which increases further the ascending motion of air. The air is eventually pushed poleward and then cools and sinks in the subtropical region where Southern Africa sits, creating high pressure and subsidence which is not favorable to rainfall. This is one of the teleconnection mechanisms linking remote oceanic region to South Africa. The aim of the project was to better understand the role of the ocean on weather, climate and rivers of Southern Africa. Little work has been done to connect streamflow to the El Nino Southern Oscillation previous to that project. We also looked at the tropical Atlantic Ocean, which is closer to us although but smaller where a similar phenomenon to El Nino occurs, the Benguela Nino. Closer to South Africa, the Agulhas Current was known to impact the atmosphere above it due to high turbulent flux of moisture from sea to atmosphere. In the past, due to low resolution reanalyzed climate data that did not integrate the Agulhas Current, it was not possible to study the impact of the Agulhas Current on local climate with reanalyzed climate dataset such as ERA or NCEP. This project made some important advance to that matter using new high resolution reanalyzed climate data and a model and offer some sounds evidence on the impact of the Agulhas Current on coastal rainfall. A list of publication originating directly from the project and a list of student and thesis supported by the project is found at the end of the executive summary.

36 pages, 12 figures, 1 table, he tropical Atlantic is home to multiple coupled climate variations covering a wide range of timescales and impacting societally relevant phenomena such as continental rainfall, Atlantic hurricane activity, oceanic biological productivity, and atmospheric circulation in the equatorial Pacific. The tropical Atlantic also connects the southern and northern branches of the Atlantic meridional overturning circulation and receives freshwater input from some of the world’s largest rivers. To address these diverse, unique, and interconnected research challenges, a rich network of ocean observations has developed, building on the backbone of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). This network has evolved naturally over time and out of necessity in order to address the most important outstanding scientific questions and to improve predictions of tropical Atlantic severe weather and global climate variability and change. The tropical Atlantic observing system is motivated by goals to understand and better predict phenomena such as tropical Atlantic interannual to decadal variability and climate change; multidecadal variability and its links to the meridional overturning circulation; air-sea fluxes of CO2 and their implications for the fate of anthropogenic CO2; the Amazon River plume and its interactions with biogeochemistry, vertical mixing, and hurricanes; the highly productive eastern boundary and equatorial upwelling systems; and oceanic oxygen minimum zones, their impacts on biogeochemical cycles and marine ecosystems, and their feedbacks to climate. Past success of the tropical Atlantic observing system is the result of an international commitment to sustained observations and scientific cooperation, a willingness to evolve with changing research and monitoring needs, and a desire to share data openly with the scientific community and operational centers. The observing system must continue to evolve in order to meet an expanding set of research priorities and operational challenges. This paper discusses the tropical Atlantic observing system, including emerging scientific questions that demand sustained ocean observations, the potential for further integration of the observing system, and the requirements for sustaining and enhancing the tropical Atlantic observing system, MM-R received funding from the MORDICUS grant under contract ANR-13-SENV-0002-01 and the MSCA-IF-EF-ST FESTIVAL (H2020-EU project 797236). GF, MG, RLu, RP, RW, and CS were supported by NOAA/OAR through base funds to AOML and the Ocean Observing and Monitoring Division (OOMD; fund reference 100007298). This is NOAA/PMEL contribution #4918. PB, MDe, JH, RH, and JL are grateful for continuing support from the GEOMAR Helmholtz Centre for Ocean Research Kiel. German participation is further supported by different programs funded by the Deutsche Forschungsgemeinschaft, the Deutsche Bundesministerium für Bildung und Forschung (BMBF), and the European Union. The EU-PREFACE project funded by the EU FP7/2007–2013 programme (Grant No. 603521) contributed to results synthesized here. LCC was supported by the UERJ/Prociencia-2018 research grant. JOS received funding from the Cluster of Excellence Future Ocean (EXC80-DFG), the EU-PREFACE project (Grant No. 603521) and the BMBF-AWA project (Grant No. 01DG12073C)

ICAWA : International Conference AWA, Mindelo, CPV, 13-/11/2017 - 17/11/2017; The project 'Enhancing Prediction of Tropical Atlantic Climate and its Impacts – PREFACE' (www.preface-project.eu) is a 4.5 year research project funded by the European Union under FP7- Environment. The project gathers 28 partners from 18 countries across Africa and Europe, with expertise in oceanography, climate modelling and prediction, and fisheries science, targeting climate prediction and marine-ecosystem changes in the eastern boundary and equatorial upwelling regions of the tropical Atlantic. Since 2013 and in a spirit of strong international cooperation, PREFACE has made important contributions towards improving the Atlantic observational network and climate prediction models – whilst enhancing local capacity and harvesting the synergy from inter-projects collaboration – such that we can now usefully forecast climate from a season to a decade in advance over large regions of the tropical Atlantic Ocean, and over parts of continental South America and Africa. A particular example is the skill in predictions of ocean surface temperature and Sahel rainfall a season to several years ahead. There is also a potential to predict stock biomass from a season to years in advance. We showed that the upwelling intensity in North West Africa and consequent marine productivity are redistributed due to warming trends, and we report a northern spatial shift of round sardinella. In the southeast Atlantic, a similar shift is reported on the same species. Such potentially predictable changes impact food security management and demand adequate policy measures. However, more work is required to make the most use of these predictions. Climate model errors and modelling of biophysical relations continue to be a major challenge. These introduce uncertainties in future projections of climate change and its impacts in this region. They also limit shorter-term climate prediction. Thus much more work is needed to improve models. Collaborative climate research on the Atlantic remains a key priority.

This paper provides an update on research in the relatively new and fast-moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about 6–9 years. Recent multimodel results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialized multimodel ensemble decadal hindcasts than in single model results, with multimodel initialized predictions for near-term climate showing somewhat less global warming than uninitialized simulations. Some decadal hindcasts have shown statistically reliable predictions of surface temperature over various land and ocean regions for lead times of up to 6–9 years, but this needs to be investigated in a wider set of models. As in the early days of El Niño–Southern Oscillation (ENSO) prediction, improvements to models will reduce the need for bias adjustment, and increase the reliability, and thus usefulness, of decadal climate predictions in the future.

Atmosphere-ocean general circulation models (CGCMs) show important systematic errors. Simulated precipitation in the tropics is generally overestimated over the oceans south of the equator, and stratocumulus (SCu) clouds are underestimated above too warm sea surface temperatures (SSTs). In the extratropics, SSTs are also too warm over the Southern Ocean. We argue that ameliorating these extratropical errors in a CGCM can result in an improved model's performance in the tropics depending upon the success in simulating the sensitivity of SCu to underlying SST. Our arguments are supported by the very different response obtained with two CGCMs to an idealized reduction of solar radiation flux incident at the top of the atmosphere over the Southern Ocean. It is shown that local perturbation impacts are very similar in the two models but that SST reductions in the SCu regions of the southern subtropics are stronger in the model with the stronger SCu-SST feedbacks., NOAA's Climate Program Office, Climate Variability and Predictability Program Award. Grant Number: NA14OAR4310278. European Union Seventh Framework Programme. Grant Numbers: FP7/2007–2013, 60352

It is highly debated whether global warming contributed to the strong hurricane activity observed during the last decade. The crux of the recent debate is the limited length of the reliable instrumental record that exacerbates the detection of possible long-term changes in hurricane activity, which naturally exhibits strong multidecadal variations that are associated with the Atlantic Multidecadal Oscillation (AMO). The AMO, itself a major mode of climate variability, remains also poorly understood because of limited data. Here, we present the first coral-based proxy record (δ