## Simon Jungblut · Viola Liebich · Maya Bode *Editors*

# YOUMARES 8 – Oceans Across Boundaries: Learning from each other

Proceedings of the 2017 conference for YOUng MARine RESearchers in Kiel, Germany

YOUMARES 8 – Oceans Across Boundaries: Learning from each other

Icebergs at the mouth of Scoresby Sund (Kangertittivaq), East Greenland. Maria S. Merian Expedition MSM 56, July 2016. (Photo: Boris Koch, AWI)

Simon Jungblut • Viola Liebich • Maya Bode Editors

# YOUMARES 8 – Oceans Across Boundaries: Learning from each other

Proceedings of the 2017 conference for YOUng MARine RESearchers in Kiel, Germany

*Editors* Simon Jungblut BreMarE – Bremen Marine Ecology, Marine Zoology University of Bremen Bremen, Germany

Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Bremerhaven, Germany

Maya Bode BreMarE – Bremen Marine Ecology, Marine Zoology University of Bremen Bremen, Germany

Deutsche Gesellschaft für Meeresforschung (DGM) e.V., Biozentrum Klein Flottbek Hamburg, Germany

Viola Liebich Deutsche Gesellschaft für Meeresforschung (DGM) e.V., Biozentrum Klein Flottbek Hamburg, Germany

ISBN 978-3-319-93283-5 ISBN 978-3-319-93284-2 (eBook) https://doi.org/10.1007/978-3-319-93284-2

Library of Congress Control Number:<PHONE_NUMBER>

© The Editor(s) (if applicable) and The Author(s) 2018. This book is an open access publication.

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*To all Young Marine Researchers*

## **Foreword**

YOUMARES is a bottom-up conference, which has been organized for 8 years now by highly engaged young people that are enthusiastic about marine sciences. It was initiated by the working group on studies and education of the German Society for Marine Research (DGM) with the aim of building a network for young marine researchers.

From my perspective, part of the success of the YOUMARES conferences is the bottom-up concept that generates a multitude of new and creative ideas, presentation formats, and communication approaches. Another unique feature is that YOUMARES is also open for pupils and young university students interested in marine sciences. As a wonderful example, the organizers of a previous YOUMARES conference contacted local schools and convinced an English teacher to introduce the topic of fisheries biology in her class. As a result, the entire school class later attended the YOUMARES fisheries biology session.

The challenge of the bottom-up concept is the natural fluctuation within the organizing committee and it requires highly engaged people with good organizing skills to sustain YOUMARES. In my view, on the other hand, the fundamental benefit for team members and participants is a substantial gain of soft skills, long-lasting contacts and friendships, and the build-up of personal networks.

Over 180 participants from 23 nations attended YOUMARES 8 and it was, again, highly inspiring to see the creative ideas developed by organizers and participants. Apart from the science itself, many sessions at YOUMARES 8 addressed gender aspects in science, compatibility of research and family, or proposal writing aspects, which are not always part of the classical education in an early scientist's career.

The publication of these proceedings is unique and faced several challenges: Is the science sound and does the effort interfere with ongoing tasks, for example, in the authors' PhD project? How can the proceedings be financed without having a research institution in the background? Who takes care of organizing submissions, peer-review process, and revisions? All of these aspects were dealt with by the organizers with enormous creativity and momentum. Their effort included proposal writing, acquisition of funding and supporters who helped organizing contributions and reviews.

This peer-reviewed publication documents the YOUMARES effort and, at the same time, supports the future careers of the contributors. Several chapters inherently express young marine researchers' concerns toward the fundamental environmental and societal challenges in the marine realm, such as climate change, littering, or human pressure on coasts. Meeting these challenges requires multidisciplinary, international, and cross-generation interplay, and to cite one chapter: "The Static, Boundary-Based Norm of Scientific Thinking Must Be Overcome."

I congratulate the organizers and contributors for their effort and recommend reading these proceedings – the laurels of highly engaged marine researchers, who will shape marine science in future.

Alfred Wegener Institute, Helmholtz Centre for Polar Boris Koch and Marine Research, Bremerhaven, Germany MARUM Center for Marine Environmental Sciences, Bremen, Germany University of Applied Sciences, Bremerhaven, Germany March 28, 2018

vii

## **Preface**

This proceedings volume is the final product of the YOUMARES 8 conference, held from 13 to 15 September 2018 in Kiel, Germany. YOUMARES is a conference series organized by and for YOUng MARine RESearchers under the auspices of the German Society for Marine Research (Deutsche Gesellschaft für Meeresforschung e.V. – DGM). Especially bachelor, master, and PhD students from all fields of marine sciences are asked to contribute to the conference. Their presentations represent current issues of marine research and are organized in thematic sessions, which are hosted mostly by PhD students or young post-docs. In addition to organizing and moderating their session, the session hosts are given the opportunity to write a literature review of a session-related topic of their choice. These literature reviews, together with all conference abstracts, are compiled in this book. The articles, i.e., peer-reviewed chapters of this book, represent the current state of knowledge of their specific topic, while the corresponding abstracts represent ongoing research projects.

The 2017 edition of the YOUMARES series was hosted by the Kiel University and the GEOMAR Helmholtz Centre for Ocean Research in Kiel. Over 180 young researchers contributed over 90 talks and 27 poster presentations. Including all helpers, this eighth edition of YOUMARES was the biggest YOUMARES conference so far. The icebreaker event took place in the foyer of the east shore building of GEOMAR, whereas presentations, talks, and workshops were held in a seminar building of the Kiel University. Keynote talks were given by Prof. Dr. Mojib Latif (GEOMAR Helmholtz Centre for Ocean Research, Kiel) on "The Role of the Oceans in Climate Change," and by Dr. Claudia Hanfland (Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven) on "Career Planning – Advice from the Cheshire Cat."

We hope that these articles and abstracts are a source of knowledge and inspiration for the conference participants, authors, and all interested people. We hope that this book will provide the conference participants with sustainable memories about the conference in Kiel and that it also encourages interested people to join the YOUMARES network.

Bremen, Germany Simon Jungblut Hamburg, Germany Viola Liebich Bremen, Germany Maya Bode March 2018

## **Acknowledgments**

We would like to thank many helpers for taking over smaller and bigger tasks during all phases of the preparation and realization of the conference in Kiel. Without the strong support of these volunteers, organizing a conference of such a size would be impossible. We would like to thank all of them: Jan Brüwer, Andreas Eich, Joeline Ezekiel, Thea Hamm, Lena Heel, Lisa Hentschel, Dorothee Hohensee, Elham Kamyab, Maral Khosravi, Veloisa Mascarenhas, Ola Nour, Olga Sazonova, Timothy Tompson, and Mara Weidung.

We are very grateful to the Kiel University and the GEOMAR Helmholtz Centre for Ocean Research Kiel for providing the space and rooms for the conference and icebreaker venues. Special thanks go to Wiebke Basse (Integrated School of Ocean Sciences ISOS of the Kiel Cluster of Excellence "The Future Ocean") and Michael Mattern for their organizational and technical support prior to and during the conference.

The keynote lectures of Mojib Latif (GEOMAR Helmholtz Centre for Ocean Research Kiel) and Claudia Hanfland (Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven) received much attention. We are grateful to both for presenting interesting and stimulating plenary talks.

The workshops during the conference were organized by several people to which we are all grateful: Francisco Barboza, Hanna Campen, Markus Franz, Jonas Geburzi, Lydia Gustavs, Daniel Hartmann, Marie Heidenreich, Lisa Hentschel, Maysa Ito, Veit Klimpel, Frank Schweikert, and Martin Visbeck.

Several partners financially supported the conference: Norddeutsche Stiftung für Umwelt und Entwicklung, SubCtech, DFG-Schwerpunktprogramm Antarktisforschung, Bornhöft Meerestechnik, Aida, and Deutsche See.

Springer Nature provided book vouchers to award the best oral and poster presentations.

The Zoological Museum Kiel is thanked for offering free entrance to their exhibitions for all conference participants.

The Staats- und Universitätsbibliothek Bremen and the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research supported the publication of this proceedings book.

Thanks go to Alexandrine Chernonet, Judith Terpos, and Springer for their support during the editing and publishing process of this book.

All chapters of this book have been peer-reviewed by internationally renowned scientists. The reviews contributed significantly to the quality of the chapters. We would like to thank all reviewers for their time and their excellent work: Tina Dohna, Erik Duemichen, Tor Eldevik, Lucy Gwen Gillis, Gustaaf Hallegraeff, Charlotte Havermans, Ferenc Jordán, Trevor McIntyre, Paul Myers, Ingo Richter, Paris Vasilakopoulos, Aurore Voldoire, Jan Marcin Węsławski, Christian Wild, Argyro Zenetos, and further anonymous reviewers.

We editors are most grateful to all participants, session hosts, and presenters of the conference and to the contributing authors of this book. You all did a great job in presenting and representing your (fields of) research. Without you, YOUMARES would not be worth to organize.

## **Contents**

## **Contributors**

**Mona Andskog** Faculty of Biology and Chemistry, University of Bremen, Bremen, Germany Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany

**Francisco R. Barboza** GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany

**Maya Bode** BreMarE – Bremen Marine Ecology, Marine Zoology, University of Bremen, Bremen, Germany

Deutsche Gesellschaft für Meeresforschung (DGM) e.V., Biozentrum Klein Flottbek, Hamburg, Germany

**Jan David Brüwer** Red Sea Research Center, Division of Biological and Environmental Science and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

Faculty of Biology and Chemistry, University of Bremen, Bremen, Germany

Max Planck Institute for Marine Microbiology, Bremen, Germany

**Hagen Buck-Wiese** Faculty of Biology and Chemistry, University of Bremen, Bremen, Germany

Max Planck Institute for Marine Microbiology, Bremen, Germany

**Camila Campos** Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany

**Xochitl Cormon** Institute for Marine Ecosystem and Fishery Science, Centre for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany

**Maha J. Cziesielski** Red Sea Research Centre, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia

**Tina Dippe** GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany

**Hannah S. Earp** Faculty of Biology and Chemistry, University of Bremen, Bremen, Germany Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany School of Ocean Sciences, Bangor University, Menai Bridge, Wales, UK

**Markus Franz** GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany

**Jonas C. Geburzi** Zoological Institute and Museum, Kiel University, Kiel, Germany

Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Wadden Sea Station, List/Sylt, Germany

**Jana K. Geuer** Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany

**Thea Hamm** GEOMAR Helmholtz Center for Ocean Research, Kiel, Germany

**Jan Harlaß** GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany

**Brigitte C. Heylen** Behavioural Ecology and Ecophysiology, University of Antwerp, Antwerp, Belgium

Terrestrial Ecology Unit, Ghent University, Ghent, Belgium

**Myriel Horn** Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany

**Maysa Ito** GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany

**Simon Jungblut** BreMarE – Bremen Marine Ecology, Marine Zoology, University of Bremen, Bremen, Germany

Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany

**Laura Käse** Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Biologische Anstalt Helgoland, Helgoland, Germany

**Therese Keck** Institute for Space Sciences, Freie Universität Berlin, Berlin, Germany

**Martin Krebs** GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany

**Viola Liebich** Deutsche Gesellschaft für Meeresforschung (DGM) e.V., Biozentrum Klein Flottbek, Hamburg, Germany

**Claudia Lorenz** Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Biologische Anstalt Helgoland, Helgoland, Germany

**Joke F. Lübbecke** GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany Faculty of Mathematics and Natural Sciences, Christian Albrechts University, Kiel, Germany

**Maciej K. Mańko** Department of Marine Plankton Research, Institute of Oceanography, University of Gdańsk, Gdynia, Poland

**Veloisa Mascarenhas** Institut für Chemie und Biologie des Meeres, Universität Oldenburg, Wilhelmshaven, Germany

**Morgan L. McCarthy** School of Biological Sciences, The University of Queensland, St. Lucia, QLD, Australia

Marine Biology, Vrije Universiteit Brussel (VUB), Brussels, Belgium

**Dominik A. Nachtsheim** Institute for Terrestrial and Aquatic Wildlife Research, University of Veterinary Medicine Hannover, Büsum, Germany

BreMarE – Bremen Marine Ecology, Marine Zoology, University of Bremen, Bremen, Germany

**Sarah Piehl** Department of Animal Ecology I and BayCEER, University of Bayreuth, Bayreuth, Germany

**Natalie Prinz** Faculty of Biology and Chemistry, University of Bremen, Bremen, Germany Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany

**Camilla Sguotti** Institute for Marine Ecosystem and Fishery Science, Centre for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany

**Katarzyna S. Walczyńska** Department of Marine Plankton Research, Institute of Oceanography, University of Gdańsk, Gdynia, Poland

**Agata Weydmann** Department of Marine Plankton Research, Institute of Oceanography, University of Gdańsk, Gdynia, Poland

## **About the Editors**

**Dr. Simon Jungblut** is a marine ecologist and zoologist. After completing a bachelor's degree in biology and chemistry at the University of Bremen, Germany, he studied the international program Erasmus Mundus Master of Science in Marine Biodiversity and Conservation at the University of Bremen; the University of Oviedo, Spain; and Ghent University, Belgium. Afterwards, he completed a PhD project entitled: "Ecology and Ecophysiology on Invasive and Native Decapod Crabs in the Southern North Sea" at the University of Bremen in cooperation with the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research in Bremerhaven and was awarded the doctoral title in natural sciences at the University of Bremen in December 2017.

Since 2015, Simon is actively contributing to the YOUMARES conference series. After hosting some conference sessions, he is the main organizer of the scientific program since 2017.

**Dr. Viola Liebich** is a biologist from Berlin, who worked on invasive tunicates for her diploma thesis at the Wadden Sea Station Sylt of the Alfred Wegener Institute. With a PhD scholarship by the International Max Planck Research School for Maritime Affairs, Hamburg, and after her thesis work at the Institute for Hydrobiology and Fisheries Science, Hamburg, and the Royal Netherlands Institute for Sea Research, Texel, the Netherlands, she finished her thesis "Invasive Plankton: Implications of and for Ballast Water Management" in 2013.

For three years, until 2015, Viola Liebich worked for a project on sustainable brown shrimp fishery and stakeholder communication at the WWF Center for Marine Conservation and started her voluntary YOUMARES work one year later. In 2017, she also became elected member of the DGM steering group. She is currently working as a self-employed consultant on marine and maritime management (envio maritime).

**Dr. Maya Bode** is a marine biologist, who accomplished her Bachelor of Science in biology at the University of Göttingen, Germany, and her Master of Science in marine biology at the University of Bremen, Germany. Thereafter, she completed her PhD thesis entitled "Pelagic Biodiversity and Ecophysiology of Copepods in the Eastern Atlantic Ocean: Latitudinal and Bathymetric Aspects" at the University of Bremen in cooperation with the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research in Bremerhaven and the German Center for Marine Biodiversity Research (DZMB) at the Senckenberg am Meer in Wilhelmshaven. She received her doctorate in natural sciences at the University of Bremen in March 2016.

Since 2016, Maya is a board member of the German Society for Marine Research (DGM) and actively contributes to the YOUMARES conference series as organizer of the scientific program.

## **YOUMARES – A Conference from and for YOUng MARine RESearchers**

Viola Liebich, Maya Bode, and Simon Jungblut

#### **Abstract**

YOUMARES is an annual early-career scientist conference series. It is an initiative of the German Society for Marine Research (DGM) and takes place in changing cities of northern Germany. The conference series is organized in a bottom-up structure: from and for YOUng MARine RESearchers. In this chapter, we describe the concept of YOUMARES together with its historical development from a single-person initiative to a conference venue of about 200 participants. Furthermore, the three authors added some personals experiences and insights, what YOUMARES means to them.

#### **Concept and Structure of YOUMARES**

Education is the central key component for the progression of societies. As such, it is the basis to cope with the *challeng*es of globalization.  It is, therefore, of pivotal interest that young researchers commit themselves to shape

V. Liebich (\*)

M. Bode

Deutsche Gesellschaft für Meeresforschung (DGM) e.V., Biozentrum Klein Flottbek, Hamburg, Germany e-mail<EMAIL_ADDRESS>
S. Jungblut

BreMarE – Bremen Marine Ecology, Marine Zoology, University of Bremen, Bremen, Germany

Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany e-mail<EMAIL_ADDRESS>
the future of this ecosystem in a sustainable way. To jointly develop the most important future topics, a vibrant and interdisciplinary network of research, economy, and society is necessary. As such, YOUMARES is much more than a regular annual research conference. It is a platform which aims to establish a network especially for early career scientists (Einsporn 2011). It thereby promotes the research and communication activities of High School, Bachelor, Master, and PhD students. Similar to regular conferences, the participants have the possibility to present their research in oral or poster presentations. Additionally, different kinds of workshops, plenary discussions and social events enable the participants to extensively exchange with each other at eye level. Providing an exchange platform should ultimately lead to a young researcher network and to the enhancement of individual and collective competence (Fig. 1).

YOUMARES is an initiative of the working group "Studies and Education" of the German Society for Marine Research (Deutsche Gesellschaft für Meeresforschung e.V. – DGM). Right from the beginning in 2010 on, an essential part of the idea was to drive the organization of the conference bottom-up (Einsporn 2011). The whole conference is organized by early career scientists. In each winter a core organization team publishes a "Call for Sessions", which encourages young marine researchers from all kinds of scientific fields to apply alone or in pairs for hosting one of the scientific sessions at the upcoming conference. The applications contain the CVs, a motivation letter and most importantly a "Call for Abstracts" for the proposed session. If two or more applicant groups propose similar sessions, the core organization team brings them into contact and encourages them to organize a joint session. Once the applications are reviewed and the sessions are being set, the different "Calls for Abstracts" are published. The session hosts have several responsibilities. They handle the abstracts of their sessions and organize, structure, and moderate their session at the actual conference. Additionally, they are asked to write a literature review of the field of research (or one aspect of it)

Deutsche Gesellschaft für Meeresforschung (DGM) e.V., Biozentrum Klein Flottbek, Hamburg, Germany e-mail<EMAIL_ADDRESS>
BreMarE – Bremen Marine Ecology, Marine Zoology, University of Bremen, Bremen, Germany

**Fig. 1** The interplay between the provision of an exchange platform for early career scientists, networking efforts, and the enhancement of competence

they cover with their session. The product of all these efforts of the session hosts is the book at hand. It summarizes the literature reviews of most sessions and all presenter abstracts of the latest edition of the conference series, YOUMARES 8, held from 13 to 15 September 2017 in Kiel, Germany.

#### **A Brief History of Getting Larger**

YOUMARES was established by the initiative of a single person – Marc Einsporn. Marc came up with the idea of a platform where especially the young generation of scientists would be able to exchange and to present their research to an audience of a similar career stage. Starting off as a national conference, the first YOUMARES took place under a different name ("Netzwerktreffen junge Meeresforschung") in Hamburg in June 2010 with less than 50 participants (Table 1, Einsporn 2010). Already 1 year later, the name "YOUMARES" was established and it took place with about 130 participants over 3 days in September (Einsporn 2011). From then on, the conference acquired an international reputation and was held each September in different cities in northern Germany. By 2017, eight editions of YOUMARES took place; so far in seven different cities (Table 1). Already in 2012, participants came from more than ten different countries, in 2013 from more than 15 different countries (Wiedling and Einsporn 2012, Einsporn et al. 2013). Over the years, YOUMARES has expanded into the largest meeting of young marine scientists in Germany. The most recent edition, YOUMARES 8, had about 195 participants and 95 oral presentations (Table 1). Organizing an event of this size obviously requires a large team of organizers and helpers.

The topical sessions of each YOUMARES edition offer an interesting insight into the spectrum and the diversity of research early career scientists are conducting in the marine field (Table 2). In few cases, the same people applied for hosting a session in subsequent years. However, some topics are reoccurring relatively often over the years as for instance aquaculture, plastic pollution, invasive species, coral reefs and polar regions.

#### **How to Get in Contact: Personal Experiences as a Young Researcher**

#### **YOUMARES – Science Works Best When Being Shared**

#### Viola Liebich

I had joined YOUMARES as a participant some years ago when I was still a PhD student. When I first heard about this conference I didn't realize just how special it was, to be honest. Being on-site, I liked the atmosphere and noticed the rather young audience. However, it was only later in my PhD career that I joined 'big' and 'professional' meetings in an international set-up. The topic of my PhD was the introduction of invasive species via ballast water and I took a turn joining an EU project 'with application'. Applied science still has a bit of a stale taste to it for many researchers. The different worlds seem to collide on ballast water management conferences when biologists meet vessel fleet managers, government representatives, lawyers, engineers, and project managers – the guys in suits as they were called in my old institute. Dinners often were five courses served with wine you had to fight off to be not re-filled all the time. Now, was that an inspiring and relaxing atmosphere? No, I enjoyed the nice food but didn't feel comfortable talking to people I didn't know and went home with a missed chance to enlarge my network. But YOUMARES had showed me that we are as scientists not alone with our topics, ideas, questions, and problems. I learned from my first supervisor that science works best when being shared and that is, in my opinion, what YOUMARES also stands for.

Thus, when I got the chance to organize this year's YOUMARES as head of the team, I recalled that feeling. Above all, I wanted to create that easy atmosphere with people of similar minds – as if we would all meet up in a student house kitchen. At the same time, we had the expectation to offer a professional conference. The bottom-up approach done by young volunteers when organizing it should not be an excuse that the conference and everything around it doesn't provide you the best options. Although it was often challenging to find the time to call after sponsors, facility

**Table 1** Key data of YOUMARES conferences until 2017

**Table 2** Session topics of YOUMARES conferences until 2017

**Table 2** (continued)

**Table 2** (continued)

details, caterers, accommodation offers, and of course all the scientific input, we put our mind to it. And I am very proud of this year's team. We achieved all we could have hoped for and managed to make YOUMARES 8 the biggest one so far!

#### **YOUMARES and the DGM – Interlinking the Young and the Experienced**

#### Maya Bode

My first contact to YOUMARES was from a different point of view: When I was in the final stage of my PhD thesis, I participated in the DGM-Meeresforum in Bremen in 2015 where marine researchers met politicians and climate scientists. Discussions about hot topics such as the plastic problem, geoengineering and deep sea diversity, and the limits and responsibility of human actions were indeed inspiring. Especially the interdisciplinary exchange between young and experienced researchers was extremely motivating: that we, as young marine researchers, really have the possibility to change what is going on in the world, if we efficiently use our resources, as such work together, constantly update ourselves about recent research findings and interlink various disciplines of marine sciences, engineering, social sciences, politics, and economics. As vast as the ocean may appear, we know and experience these days that resources and ecosystem's carrying capacities are limited and already overexploited in many regions of the world ocean. Efficient science with the ultimate aim to serve nature and society needs creativity and constant interdisciplinary exchange of knowledge. During the last decades, the society of marine scientists has grown and together with new technologies and sophisticated networking, we have the opportunity – better than ever before – to exchange new findings, bring our knowledge into the world and enhance interdisciplinary research, partnerships, and cooperation. YOUMARES serves as such a platform and has the potential to make marine research more efficient in the future.

To help to aim this goal, I became a member of the DGM in 2015 and helped organizing the YOUMARES 7 as scientific coordinator. Then, in 2016, I became a board member of the DGM with the main motivation to enhance the exchange of experienced and young marine researchers. Since 2015, the DGM-Meeresforum takes place each year, 1 day before the YOUMARES, bringing together young and experienced scientists, in the afternoon by inspiring talks and discussions and later in the evening by getting together at the icebreaker party of the YOUMARES. The DGM was founded in 1980 as a platform for exchange of information and views on all kinds of marine topics, having around 400 members nowadays. For the future, I would like to be part of the DGM growing larger and achieving a new standing and reputation among marine researchers and political institutions. With the experience of the DGM members and potential new young members, together with the DGM-Meeresforum and YOUMARES as an annual meeting and conference, we create a large and sustainable network all around the world.

#### **YOUMARES – A Conference for the Future**

Simon Jungblut

My first contact with YOUMARES was back in 2013. The conference was about to be held at the University of Oldenburg and was obviously growing bigger in the last editions. During this time, I was a student in the "Erasmus Mundus Master of Science in Marine Biodiversity and Conservation" and based at the University of Bremen. At some point, I read about YOUMARES online and shortly thereafter some posters appeared on the black-boards in our faculty building. The posters advertised YOUMARES as "convention for young scientists and engineers". That raised my interest. I identified myself with being a "young scientist" and decided to participate in the conference as a listener. The whole conference was interesting and amazing. I spoke to a lot of other participants and learned about their study programs and institutes. In addition, the talks and posters were interesting and informative. Right from the beginning I liked the concept of giving young students and scientists a relaxed and open platform to present and discuss their first research projects. After hosting sessions in the years 2015 and 2016, I took over the scientific organization of YOUMARES 8 in 2017. I was responsible for the scientific program of the conference. This included collecting and first review of session applications and later abstract applications, the arrangement of the time schedule and the on-site coordination of hosts, conference participants and plenary speakers.

Being a part of the organization team was a totally new aspect for me. I liked to connect people and to bring them together to discuss and to network. The bases for shaping the networking experiences of young researchers are, to my experience, the shared research interests of the participants but also that the conference provides useful interdisciplinary workshops and other socializing activities. Thus, I see the future of YOUMARES in promoting such workshops and activities, side by side with the scientific presentations. Participants should be able to present their research to a broad, young audience and to participate workshops providing skills, which are useful for their future scientific life. Additionally, there should be enough room and time to effectively connect to other young scientists. Connecting young researchers might be a key component to help them establish collaborations. In this sense, a conference like YOUMARES helps to make research more efficient and more interdisciplinary, which ultimately might be a step towards a more efficient battle against the big problems the world ocean is facing right now.

#### **References**

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

**Can Climate Models Simulate the Observed Strong Summer Surface Cooling in the Equatorial Atlantic?**

Tina Dippe, Martin Krebs, Jan Harlaß, and Joke F. Lübbecke

#### **Abstract**

Variability in the tropical Atlantic Ocean is dominated by the seasonal cycle. A defining feature is the migration of the inter-tropical convergence zone into the northern hemisphere and the formation of a so-called cold tongue in sea surface temperatures (SSTs) in late boreal spring. Between April and August, cooling leads to a drop in SSTs of approximately 5°. The pronounced seasonal cycle in the equatorial Atlantic affects surrounding continents, and even minor deviations from it can have striking consequences for local agricultures.

Here, we report how state-of-the-art coupled global climate models (CGCMs) still struggle to simulate the observed seasonal cycle in the equatorial Atlantic, focusing on the formation of the cold tongue. We review the basic processes that establish the observed seasonal cycle in the tropical Atlantic, highlight common biases and their potential origins, and discuss how they relate to the dynamics of the real world. We also briefly discuss the implications of the equatorial Atlantic warm bias for CGCM-based reliable, socio-economically relevant seasonal predictions in the region.

 Defined here as the ocean area between 15°N and 15°S, they occupy only about 13% of the earth's surface, but receive approximately 30% of the global net surface insolation.1 Processes both in the ocean and the atmosphere redistribute surplus heat from low to higher latitudes. Without these mechanisms, the tropics would get steadily warmer, while the polar regions would radiate away more heat than they receive and hence continue to cool. The oceans help to establish the overall radiative equilibrium that is responsible for our relatively stable climate (Trenberth and Caron 2001).

Apart from the energy surplus, another defining feature of an equatorial ocean is that the effect of the earth's rotation vanishes at the equator, giving rise to a physical framework that is subtly different from its higher-latitude counterpart. The effect of the earth's rotation manifests in a pseudo-force that is called the Coriolis force. It deflects large-scale motion towards the right of the movement on the northern hemisphere and towards the left on the southern hemisphere. It provides rotation to large weather systems and explains why large-scale movement curves or even becomes circular. An exception is the equator, where the Coriolis force vanishes and movement can be straightforward. Additionally, the nonexistent Coriolis force at the equator acts as a barrier for the transmission of information within the ocean, for example

T. Dippe (\*) · M. Krebs · J. Harlaß GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany e-mail<EMAIL_ADDRESS><EMAIL_ADDRESS>
J. F. Lübbecke GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany

Faculty of Mathematics and Natural Sciences, Christian Albrechts University, Kiel, Germany e-mail<EMAIL_ADDRESS>
<sup>1</sup>Based on data by Trenberth et al. (2009).

<sup>©</sup> The Author(s) 2018 7 S. Jungblut et al. (eds.), *YOUMARES 8 – Oceans Across Boundaries: Learning from each other*, https://doi.org/10.1007/978-3-319-93284-2\_2

**Fig. 1** The observed tropical Atlantic mean state sea surface temperature (SST) and precipitation: Annual mean sea surface temperatures are shown as shading, precipitation in contours. White boxes indicate the Atl3 and WAtl region in the eastern and western tropical Atlantic, respectively. The used datasets are the NOAA Optimum Interpolated SST dataset (OISST, Reynolds et al. 2007; Banzon et al. 2016), and the NOAA Climate Prediction Center (CPC) Merged Analysis of Precipitation dataset. (CMAP, Xie and Arkin 1997)

via equatorial Kelvin waves. Communicating information from the southern to the northern hemisphere and vice versa is hence a non-trivial enterprise in the ocean.

While the basic set-up of the marine tropical climate system is identical in all three tropical oceans, details differ between basins. The Pacific Ocean has the largest extent and is characterized by a relatively simple land-ocean geometry; it behaves much like a perfect theoretical ocean. The tropical Atlantic, in contrast, is much narrower and the surrounding continents interact with the ocean in complex ways. For example, the tropical Atlantic appears to be more susceptible to extra-equatorial influences (e.g., Foltz and McPhaden 2010; Richter et al. 2013; Lübbecke et al. 2014; Nnamchi et al. 2016), and variability is due to a number of interacting mechanisms on overlapping time scales (Sutton et al. 2000; Xie and Carton 2004). Therefore, the tropical Atlantic is less readily understood than the tropical Pacific, and still poses substantial challenges to the scientific community.

The mean state of the tropical Atlantic is characterized by a complex interplay of atmospheric and oceanic features. These are i) the trade wind systems of both the northern and southern hemispheres, ii) a system of alternating shallow zonal2 currents in the ocean, and iii) a zonal gradient in upper-ocean heat content that is also reflected in a pronounced zonal gradient in sea surface temperatures (SSTs), with warm temperatures in the west and cooler surface waters in the east. Figure 1 illustrates the mean state of SST and precipitation.

The trade winds are part of the climate system's hemispheric response to the strong temperature gradient between the polar and the equatorial regions. Intense (solar) surface heating at the equator produces warm and humid, ascending air masses. During the ascend, part of the air moisture condensates and releases latent heat, which further accelerates the rising motion. The upward flow moves mass from the surface layer towards the top of the troposphere, effectively decreasing surface pressure and forming a low-pressure trough. At the surface, a compensation flow towards the lowpressure trough is established. Due to the rotation of the earth, however, the flow veers to the west and creates the surface trade winds. The northeasterly and southeasterly trade winds of the northern and southern hemispheres, respectively, converge in the inter-tropical convergence zone (ITCZ), a zonal band of intense precipitation and almost vanishing horizontal winds (Fig. 1). Because the ITCZ is located to the north of the equator in the Atlantic, the equatorial Atlantic is not dominated by the ITCZ itself, but by the trade wind system of the southern hemisphere that provides relatively steady easterly winds on the equator. (See below for why the ITCZ is, on average, not residing on the equator in the tropical Atlantic.)

A consequence of the easterly wind forcing at the ocean surface and the vanishing Coriolis force at the equator is that the wind pushes the warm surface waters westward. Water piles up to the east of Brazil in the Atlantic warm pool, providing water temperatures of approximately 28 °C at the surface. Conversely, the surface layer of warm water in the eastern tropical Atlantic is thinned out considerably – the eastern part of the basin stores much less heat in the upper ocean than the western part. A pronounced zonal gradient in upper-ocean heat content is established. Figure 8a illustrates this mean state.

The pressure below the ocean surface is not uniform across the basin either. At the equator, the bulk of warm water in the western ocean basin adds pressure to the water

<sup>2&</sup>quot;Zonal" refers to an east-west orientation, i.e. one that is parallel to the equator. A north-south orientation is called "meridional".

**Fig. 2** Upwelling driven by horizontal divergence. Consider an ocean in a state of rest. In a simple model, a layer of warm water is sitting on top of a layer of colder water. Both the interfaces between the warm surface layer and the atmosphere, and between the colder subsurface water and surface layer are approximately even (horizontal dashed blue lines). When a divergence is created in the upper layer, mass is transported away from the divergence (light blue arrows in the surface layer). Because water is approximately incompressible, mass must be conserved. A vertical flow from the subsurface layer compensates the horizontal divergence (dark blue, upward arrow). In reality, this domes the interface between the surface and the subsurface layers. The sea surface adapts to the doming interface by decreasing in a similar fashion, albeit with a much smaller amplitude

column, while eastern ocean pressure is reduced. The resulting east-west pressure gradient is balanced by a strong eastward current right below the surface – the equatorial undercurrent (EUC) (Cromwell 1953; Cromwell et al. 1954). At the surface, on the other hand, the direct wind forcing and meridional pressure gradients produce a complex system of alternating zonal current bands (e.g., Schott et al. 2003; Brandt et al. 2006, 2008).

The three-dimensional flow of the upper equatorial oceans directly below the well-mixed surface layer is characterized by a slow but steady upward motion of, at best, a few meters per day (Rhein et al. 2010). This so-called "upwelling" is maintained by two processes. First, the Coriolis force deflects the off-equatorial components of the wind-induced westward displacement of surface water masses into opposite directions. On the northern hemisphere, westward flow veers north, while the Coriolis force directs it south on the southern hemisphere. Zonal wind-driven upper ocean mass transports diverge; they effectively transport mass away from the equator. However, because mass is conserved, sea level sags imperceptibly, and upwelling transports colder, subsurface water closer to the surface by creating a "dome" in the interface between the warm surface water and cooler subsurface water. The ratio between the surface and subsurface layer thicknesses changes in response to the surface divergence. Figure 2 illustrates how divergent flow in the surface layer creates upwelling and changes the geometry of the involved interfaces between both the atmosphere and the ocean, and the ocean surface and subsurface layers.

Second, a small meridional contribution to the equatorial wind field contributes to maintaining equatorial upwelling. These meridional contributions are illustrated in Fig. 7b by the equatorial wind vectors that do not point straight to the west but rather to the northwest, as they are part of the southern hemisphere trade wind regime crossing the equator into the northern hemisphere for most of the year. In the ocean, they induce meridional surface mass transports slightly off the equator (Philander and Pacanowski 1981). Again, the Coriolis force redirects these meridional motions into zonal mass transports of opposite signs, which contribute to the upper ocean horizontal divergence.

Over the course of the year, the set-up of this basic state varies. Due to the tilted rotational axis of the earth, the latitude of maximum insolation shifts into the northern hemisphere in boreal – i.e. northern hemispheric – summer, and into the southern hemisphere in boreal winter. The ITCZ, accompanied by the trade wind systems of both hemispheres, migrates in a similar fashion. However, the ITCZ does not oscillate around the equator but stays north of it for most of the year (Hastenrath 1991; Mitchell and Wallace 1992). Xie (2004) reviewed the "riddle" of the asymmetric ITCZ and concluded that it is, contrary to intuition, not so much the overall distribution of landmasses and oceans that anchors the Atlantic ITCZ to the northern hemisphere, but a combination of air-sea coupling and the shape of the West-African shoreline. More recently, Frierson et al. (2013) also demonstrated how the meridional temperature gradient between the warm northern hemisphere and the relatively colder southern hemisphere impacts the ITCZ behavior. All factors combine to pull the trade wind system of the southern hemisphere across the equator and establish the highest SSTs to the north of the equator.

Driven by the changing trade wind systems, the zonal surface current systems vary in strength and location. The intensity of the Equatorial Undercurrent, while firmly pinned to the equator, varies as well (Johns et al. 2014). Variations in the wind forcing lead to seasonally recurring intensifications of the zonal heat content gradient.

One of the most striking elements of the tropical Atlantic seasonal cycle is the formation of the Atlantic cold tongue in the eastern equatorial Atlantic during boreal summer. The cold tongue is characterized by an intense cooling of the upper ocean. Figure 3a shows that SSTs in the Atl3 region (3°S–3°N, 20°W–0°E) drop from 28 °C to about 23 °C between April and August, forming a distinct, tongueshaped pattern of relatively cool surface water that stretches from the West African coast into the central equatorial Atlantic (Figs. 3b, c). The observed temperature difference between April and August in the upper 50 m of the Atl3 region alone corresponds to a change in thermal energy of

**Fig. 3** Observed cold tongue based on the NOAA Optimum Interpolated SST dataset (OISST). (**a**) Exemplary time series of monthly mean Atl3 sea surface temperature (SST, dark blue) and the climatological seasonal cycle (light blue). For the seasonal cycle,

monthly mean data has been averaged for each calendar month for the period 1981–2012. (**b**) and (**c**) Climatological SST fields for April and August, illustrating the climatological conditions when SSTs reach their maximum just before the onset of the cold tongue, and when the cold tongue is fully developed, respectively

1351.16 EJ.3 That is 13 times the US-American energy consumption of 2014, or 2.6 times the total global energy consumption of 2011.

The formation of the cold tongue co-occurs with seasonal changes in the atmospheric circulation. An important and well-known aspect of this is the strong co-variability between the onset of the cold tongue and the onset of the West African monsoon (e.g., Okumura and Xie 2004; Brandt et al. 2011a; Caniaux et al. 2011), a key element of large-scale precipitation in western Africa and hence a crucial factor of agriculture. Understanding the complex processes that shape the coupled atmosphere-ocean-land climate system of the equatorial Atlantic is a task of high societal relevance.

In concert with accurate and long-term observations, climate models are an essential tool to investigate the equatorial Atlantic. Here we address the question of how well state-ofthe-art climate models are able to reproduce the observed seasonal cycle of the equatorial Atlantic. The section "Climate models: A crash course" gives an overview on coupled climate models and introduces the concept of model biases. The section "Can climate models reproduce the observed seasonality of the equatorial atlantic climate system?" reports common biases in the tropical Atlantic and how they relate to the formation of the modeled cold tongue. An outlook in the last section addresses the usefulness of climate models for studies of cold tongue variability, a crucial source of tropical Atlantic climate variability that strongly affects the surrounding continents.

#### **Climate Models: A Crash Course**

Climate models numerically solve the Navier-Stokes equations for a set of specified assumptions. The Navier-Stokes equations are a system of non-linear partial differential equations that describe the behavior of fluids, from a drop of water that hits the surface of a puddle, to global circulation systems such as the trade wind systems. They are highly complex and can only be solved numerically when they are approximated to focus on a specific class of fluid processes. For climate models, these processes are mostly related to the large-scale global circulation, synoptic phenomena, and possibly mesoscale phenomena4 such as ocean eddies. The approximated Navier-Stokes equations that are used in current climate models are called the primitive equations.

Climate models consist of a number of "building blocks". The two core building blocks are an atmosphere and an ocean general circulation model (GCM). Given appropriate surface and boundary forcing, both GCM types can be run

<sup>3</sup>Based on thermal data from the World Ocean Atlas (WOA2013v2, Locarnini et al. 2013).

<sup>4</sup>Size on the order of 10–50 km.

independently. Phillips (1956) demonstrated this by designing the first successful atmospheric GCM. To allow the oceanic and atmospheric blocks to interact with each other, a coupling module exchanges information at the air-sea interface. A coupler and the atmospheric and oceanic GCMs together form the simplest coupled GCM (CGCM). Such a basic CGCM lacks a number of relevant processes, relating for example to the land and sea ice components of the climate system or the impact of vegetation. To introduce these important aspects into the model, CGCMs are "upgraded" with additional building blocks to form earth system models. If a basic CGCM is a simple brick house of only one room, a full-fledged earth system model is a mansion with specialized rooms for different tasks. Important additional building blocks for an earth system model are modules that simulate the behavior of sea ice, ice sheets and snow cover on land, vegetation and other surface processes such as river runoff into the ocean, atmospheric chemistry, biogeochemistry in the ocean or even geological processes of varying complexity.

In order to solve the model equations numerically, CGCMs need to discretize the real world into finite spatial and temporal units. The basis for such a discretization is a three-dimensional grid of grid boxes that each contain a single value of a given variable. The CGCM applies the model equations to the grid boxes and integrates them forward in time. Essentially, each grid box is a mini-model that is, however, exchanging information with neighboring grid boxes.

An important characteristic of a model grid is its resolution, i.e. the size of its grid boxes.5 It defines, among other things, which processes can be resolved. As an example, consider the development of cumulus clouds. While cumulus clouds have a horizontal scale of less than 10 km, state-ofthe-art models use a resolution of about 100 km. On such a grid CGCMs cannot simulate cumulus clouds directly. Consequently, the climatic impacts of such clouds have to be parameterized, i.e. their effect must be captured by the model in a simpler way that is supported by observations. For convective6 and mixing processes alone – important aspects of cumulus clouds -, a number of parameterization schemes exist that subtly alter the behavior of large-scale processes in the models.

In addition to horizontal processes, models must be able to capture vertical motions in the climate system. Cumulus clouds, for example, extent vertically throughout varying portions of the troposphere, and vertical movement within clouds is a key factor of precipitation. On a larger scale, ascending air masses within the ITCZ define an important aspect of the tropical climate system (cf. Section "The equatorial atlantic: A climate hot spot"). Models need to be able to reproduce these vertical movements. They require vertical layering, giving rise to the three-dimensional structure of a model grid. A common feature of all models is that their vertical levels are unevenly distributed. Because properties usually change drastically close to the air-sea interface, resolving these strong gradients requires a high vertical resolution. Conversely, the thickest levels are farthest away from the air-sea interface. In the ocean, the last model level usually ends at the sea floor; the atmosphere, however, is not bounded that clearly. Some models only resolve the troposphere, our "weather" sphere that reaches up to approximately 15 km, while a number of recent atmosphere models incorporate the stratosphere as well (up to 80 km).

Figure 4 illustrates schematically how the different "building blocks" of a CGCM work together and how the real world must be discretized into grid boxes to allow a numerical solution of the primitive equations.

CGCMs are initialized either from a state of rest – i.e. the ocean and atmosphere are without motion and only establish their general circulation patterns during the first stage of the simulation, the so-called "spin-up" – or from a more specific state that is generally derived from observations. In both cases, the model needs time to smooth out initial imbalances and establish an equilibrium. Additionally, climatically relevant forcing parameters must be prescribed to the model in the form of boundary conditions. A prominent example of such a boundary condition is the strength and variability of the solar forcing, our energy source on earth, or the atmospheric CO2 concentration.

Climate models are used to address a host of research questions. They aid scientists in interpreting observations, infer mechanisms, or provide information on how the climate system might evolve in the future. All of these tasks, however, require that CGCMs are able to produce a realistic climate. Due to various limitations, this is not always the case. A common manifestation of the shortcomings of a climate model is the formation of biases.

A bias is a systematic difference between the modeled and the observed climate. This difference can occur in any statistical property of any model variable. While standard biases are routinely monitored during the development and application of climate models, non-obvious biases may be present in simulations that look fine otherwise. Consider, for example, SST in a given location. While routine bias controls may have found a realistic mean SST, closer inspection could reveal that SST anomalies tend to be too high. Because positive and negative anomalies cancel each other out on

<sup>5</sup>Note that, usually, not all grid boxes of a GCM have the same size, neither in terms of absolute surface area, nor in terms of longitudinal and latitudinal extent. A common practice in ocean models, for example, is to refine the latitudinal resolution towards the equator to better resolve the fine structures of the equatorial oceans. In a similar fashion, Sein et al. (2016) recently discussed grid layouts for ocean models that increase their spatial resolution in certain target areas.

<sup>6</sup>Convection: upward motion in the atmosphere.

**Fig. 4** Schematic of a Coupled General Circulation Model (CGCM). On the most basic level, the earth is a closed system that receives energy from the sun and radiates away thermal energy (yellow arrows at the "top of the atmosphere"). A CGCM tries to simulate the processes within this system. It consists of a number of modules that interact with each other. Important modules in state-of-the-art CGCMs are the oceanand-sea-ice module, the atmospheric module, and additional modules that simulate, for example, land surface processes or vegetation. These "building blocks" of the CGCM exchange information with each other via an additional "coupling module". Coupling is a computationally expensive operation that can account for up to a third of the total required computational resources of a CGCM. A CGCM solves an approximation to the Navier-Stokes equations numerically.  To solve them, the model must discretize the real world into finite spatial and temporal units. In the three-dimensional space domain, this discretization results in a layered grid. Each grid box contains a single value for each model variable. Processes acting on spatial scales that are smaller than the extent of the grid box must be parameterized. Prominent examples of these "sub-grid" processes are, for example, the formation of clouds and precipitation

average, this biased variance would not be obvious. In a similar manner, positive and negative SST anomalies might not be distributed realistically, with the model perhaps producing a few very strong positive anomalies and many weak negative anomalies that still form the expected average. In this case, the modeled SST distribution is skewed with respect to observations.

An additional limitation on the hunt for biases is that a bias can only be diagnosed in comparison to a reliable observational benchmark. Many parameters of the real climate system, however, are hard to observe or have only been observed for a short time. In general, large-scale patterns on the earth's surface and throughout the atmosphere can be observed relatively easily with satellite-borne remote sensing instruments. SST, for example, has been carefully monitored by a number of satellite missions since the 1980s. Processes below the ocean surface, however, can usually not be monitored from space. Instead, observational data have to be obtained by measurements from ships, moored instruments and autonomous vehicles such as gliders and floats. For the tropical oceans, the TAO/TRITON mooring array in the Pacific (McPhaden 1995), the PIRATA array in the Atlantic (Bourlès et al. 2008), and the RAMA array in the Indian Ocean (McPhaden et al. 2009) provide, among others, information on temperature, salinity, current velocities and air-sea fluxes. Additionally, an increasing number of hydrographic observations have become available over the last decade due to the Argo program (Roemmich et al. 2009). While all of these measurements provide invaluable information about the state of the tropical oceans, they are not spatially continuous and have only been operational for the last few decades. Obtaining information about the evolution of the climate system in the past remains a core challenge of climate research.

Although no climate model is exactly like the other, some biases are shared by a wide range of state-of-the-art CGCMs. Figure 5 shows the global pattern of the annual mean SST bias for the average of 33 CGCMs and an experiment with the Kiel Climate Model (KCM, Park et al. 2009). Positive values indicate that modeled SST is warmer than in observations and vice versa. We validated the performance of these CGCMs and the KCM in terms of SST against the satellite derived Optimum Interpolated SST dataset (OISST, Reynolds et al. 2007; Banzon et al. 2016). Figure 5 shows that while the KCM is a unique model that has individual flaws and strengths, the characteristics of its equatorial Atlantic SST bias are well comparable to other current CGCMs (examples of other models are shown, among others, in Wahl et al. 2011; Xu et al. 2014; Ding et al. 2015; Harlaß et al. 2017).

The KCM is a state-of-the-art CGCM that was integrated with radiative forcing for the period 1981–2012 in rather coarse resolution. The ocean-sea ice model NEMO (Madec 2008) was run with 31 vertical levels and a horizontal resolution of 2° that is refined to 0.5° in the equatorial region. The atmospheric model ECHAM5 (Roeckner et al. 2003) is run with 19 vertical levels and a global horizontal resolution of approximately 3.75°. Results from KCM simulations are selected here for consistency reasons. We stress again that while the KCM differs wildly from other CGCMs in some aspects, its simulation of the tropical Atlantic is representative for most current-generation CGCMs.

#### **Can Climate Models Reproduce the Observed Seasonality of the Equatorial Atlantic Climate System?**

#### **The Equatorial Atlantic Warm Bias: Symptoms**

The annual mean SST bias varies considerably between different regions of the ocean (Fig. 5). Striking features of the global SST bias pattern are the pronounced warm biases

**Fig. 5** Annual mean global sea surface temperature (SST) bias in (**a**) the ensemble mean of 33 Coupled General Circulation Models (CGCMs) contributing to the Coupled Model Intercomparison Project, Phase 5 (CMIP5, Taylor et al. 2012) and (**b**) one integration of the Kiel Climate Model (KCM). For CMIP5, the chosen experiments were "historical" experiments that were forced by the observed changes in atmospheric composition. The KCM was run with an atmospheric horizontal resolution of approximately 3.75° and with 19 vertical levels. The

ocean model had a horizontal resolution of 2° that was refined to 0.5° towards the equator, and 31 vertical levels. The annual mean SST bias was diagnosed with respect to the NOAA Optimum Interpolated SST dataset (OISST) for the period 1982–2009. Using an ensemble mean of three ensembles instead of a single integration to diagnose the KCM SST bias changed the results only negligibly. This demonstrates how robust a feature the annual mean SST bias pattern is in the KCM

**Fig. 6** Seasonal cycle of Atl3 sea surface temperature (SST) in observations (NOAA Optimum Interpolated SST dataset, black), and the Kiel Climate Model (KCM, red). Red shading illustrates the bias magnitude for each month

along the subtropical western shorelines of all continents. These biases appear, for example, along the western US-American as well as the Peruvian and Chilean coasts in the Pacific, or off Angola and Namibia in the Atlantic. They are anchored to the eastern boundary upwelling systems, where cold subsurface waters are brought close to the ocean surface. Here, SST biases can reach annual mean amplitudes of up to 7 °C in current climate models (Xu et al. 2014).

In this section, we focus on the pronounced warm bias that covers the equatorial Atlantic cold tongue region. The annual mean SST bias in the Atl3 region has a magnitude of approximately 2 °C.7 In the upper 50 m of Atl3 in the KCM, this corresponds to a heat surplus of approximately 380 EJ, an amount of energy that could melt 47 times the ice volume of the Antarctic ice sheet.8

An important aspect of the equatorial Atlantic SST bias is that it varies over the course of the year. Figure 6 shows that the SST bias of the KCM is smallest in boreal winter, with a value of less than 1 °C in February. During the cold tongue formation, it rapidly increases to almost 4 °C until July. For the rest of the year, it slowly decreases again. This implies that the KCM struggles to simulate the observed strong cooling that is associated with the development of the cold tongue in boreal summer. Indeed, Fig. 6 shows that the KCM – similar to most state-of-the-art CGCMs (e.g., Richter and Xie 2008; Richter et al. 2014b) – does not produce a coherent cold tongue that is comparable in strength to observations. A key process of the equatorial Atlantic climate system is missing from the simulations.

Because the ocean and the atmosphere are strongly coupled in the tropics, the missing cold tongue is only one symptom of a fundamentally biased equatorial Atlantic in current climate models. Figure 7 illustrates the bias of the zonal wind component in the KCM. During spring, the KCM strongly underestimates the magnitude of zonal wind in the western tropical Atlantic (Fig. 7a). While the absolute value of zonal wind is higher in the KCM than in observations, especially during spring, the magnitude is much smaller. Instead of the generally easterly winds (negative values), associated with the trade winds, the KCM simulates very weak westerly winds (positive values). This "westerly wind bias" – so-called because the simulated zonal winds are much too westerly compared to the observed trade winds – is another typical bias pattern in state-of-the-art GCMs. It agrees with an ITCZ that is displaced too far to the south, a feature that is common to both coupled and atmosphere-only GCMs (e.g., Doi et al. 2012; Richter et al. 2012; Siongco et al. 2015).

An important question is: How do the different bias symptoms relate to each other dynamically, and how do these

<sup>7</sup>Note, however, that by no means *all* climate models develop such a strong equatorial Atlantic warm bias. Some models are capable of simulating a more realistic tropical Atlantic, but these models represent but a tiny minority of all current CGCMs.

<sup>8</sup>We used the thermal data from WOA2013v2 to compare our model results with. The Antarctic ice volume is based on the Bedmap2 dataset (Fretwell et al. 2013).

dynamics compare to the observed processes that shape the tropical Atlantic climate system? In the next subsection, we first review the basic processes that establish the observed seasonal cycle in the tropical Atlantic, and then compare the observations with what is happening in state-of-the-art climate models.

#### **Which Processes Produce the Equatorial Atlantic Warm Bias?**

A good first assumption about the seasonal cycle is that it is driven by the seasonal movement of the sun. Such a seasonal cycle should be symmetric. In the tropical Atlantic, however, it is clearly asymmetric. Figure 6 shows that the cooling period between April and August is much shorter – or, equivalently, more intense – than the subsequent period of gradual warming that lasts until the following April. Processes other than the seasonal forcing of solar insolation must contribute to the fast growth of the summer cold tongue.

Recent studies of the tropical Atlantic suggest that the rapid formation of the cold tongue involves a coupled, positive feedback (Keenlyside and Latif 2007; Burls et al. 2011; Richter et al. 2016). A feedback establishes a relationship between two or more variables. In a negative feedback small perturbations in one variable are compensated by changes in the other such that the system returns to its original, stable state. The opposite is true for a positive feedback. Here, a perturbation – even a small one – in one variable provokes changes in the other variables that reinforce the original perturbation. The system continues to diverge from its initial state. The perturbation grows until the feedback is disrupted.

The dominant positive feedback in the equatorial oceans is the Bjerknes feedback (Bjerknes 1969). It relates three key properties of an equatorial ocean basin to each other: SST in the eastern ocean basin; zonal wind variability in the western

**Fig. 8** The Bjerknes feedback. (**a**) Mean state. Along the equator, the surface wind field is dominated by the trade winds of the southern hemisphere. Both the zonal and meridional components of the trade winds contribute to surface divergences close to the equator, producing equatorial upwelling (thick blue arrow). Steady equatorial easterly wind forcing (blue arrows) pushes warm surface waters (light blue layer) towards the western ocean basin and builds up the warm pool. Warm and moist air rises above the warm pool (orange arrow). In contrast, the surface mixed layer is thin in the eastern basin, upwelling is more efficient there, and SSTs are, on average, cooler than in the warm pool (approximately 25.5 °C and 28.5 °C, respectively; the equatorial SST distribution is sketched in the bar below the figure). (**b**) The positive Bjerknes feedback alters the state of the tropical ocean. The trade

winds weaken, and zonal surface winds in the western ocean basin decrease. The balance between the subsurface pressure gradient and wind stress forcing is disrupted, and part of the warm pool "sloshes back" into the central ocean basin, redistributing warm surface water more evenly across the ocean basin. The tilt in the interface between the surface and subsurface waters decreases, and upwelling is less efficient in providing cold subsurface water to the surface layer in the eastern ocean basin. The cold tongue region warms (orange ovals). Sea level pressure (SLP) over the warm anomalies decreases, and convection shifts towards the central ocean basin. The surface wind response to this shift in surface convection and the zonal SLP distribution further weakens the trade wind regimes and closes the feedback

ocean basin; and the zonal distribution of upper ocean heat content along the equator, with large heat reservoirs and thick surface layers in the western warm pool, and thin surface layers in the cold tongue region in the east.

Figures 8a and b illustrate, respectively, the mean state of an equatorial ocean and how the Bjerknes feedback alters it. Consider a weakening of the easterly trade winds in the western ocean basin (or equivalently a decrease in easterly zonal wind stress at the ocean surface). The balance between the wind stress and the piled-up warm water in the western ocean basin temporarily fades, and the piled-up warm pool "sloshes back" into the eastern ocean basin, redistributing the upper ocean heat content more evenly across the equatorial basin.9 The zonal gradient in heat content is leveled out, and the additional heat in the eastern ocean basin helps to establish a positive SST anomaly. This process can last several months in the equatorial Pacific and approximately one month in the equatorial Atlantic. (These different time scales are mainly due to the different east-west extents of the basins and hence signal propagation speeds.)

In the tropics, the atmosphere is closely coupled to the ocean. It reacts strongly to underlying SST variability by developing an anomalous wind field that converges over a warmer-than-usual patch of water (Gill 1980). The local changes in the wind field co-occur with changes in the zonal pressure gradient along the equator. The altered zonal pressure gradient in turn induces further weakening of the easterly trade winds in the western ocean basin, closing the feedback loop. An equivalent process with opposite signs takes place when the trade winds intensify in the western ocean basin.

The Bjerknes feedback is restricted to the equatorial ocean basins. While the ingredients of the feedback – wind, upper ocean heat content and SST variability – are present in every region of the ocean and usually interact with each other in one way or the other, the fully coupled Bjerknes feedback requires that information is zonally transmitted across almost the entire zonal extent of the basin, both in the atmosphere and the ocean. This is only possible when the Coriolis force vanishes or is negligibly small, since it would otherwise deflect the involved physical motions into curved movements. A direct, zonal exchange between the eastern and western ocean basins would not be possible in the presence of the Coriolis force.

<sup>9</sup>In the framework of this explanation, an interesting observation is that the Bjerknes feedback can only operate as long as the reservoir of warm water in the western warm pool is not empty. Once this is the case, the feedback breaks down, the SST anomaly stops to grow and the warm pool fills up again. A negative feedback has replaced the positive feedback. For the tropical Pacific, this sequence of alternating feedbacks has been described by Jin (1997) in the framework of the *recharge oscillator*. The name relates to the idea that the equatorial ocean is "charged" with warm water in the warm pool region – or, equivalently, heat – that is then discharged to the atmosphere during a warm event.

In the tropical Atlantic, a number of seasonal processes in the coupled atmosphere-ocean system produce a climate state that allows the Bjerknes feedback to operate during early boreal summer. Although we explain the processes in a sequential manner below, note that clear causalities are hard to establish in a coupled system. Different aspects of the phenomenon – here: the northward movement of the ITCZ and the development of the Atlantic cold tongue – cannot be disentangled from each other. Neither does the ITCZ move north *because* of the cold tongue development, nor does the cold tongue develop *because* the ITCZ moves north. Rather, both phenomena co-occur as manifestations of the same coupled phenomenon.

One key ingredient of the equatorial Atlantic seasonal cycle is the northward migration of the marine ITCZ (Xie and Philander 1994). In boreal spring, the ITCZ is in its southernmost position. The trade wind regimes of both hemispheres converge close to the equator and produce weak equatorial surface winds. When the ITCZ moves north in late boreal spring, the southern hemisphere trade winds cross the equator. Starting in March–April, surface winds intensify (illustrated by an increase in magnitude in Fig. 7a) and contribute to enhanced equatorial upwelling.

The spring strengthening of western equatorial *zonal* surface winds enhances the zonal gradient in upper ocean heat content. Strong easterly winds push the surface waters more efficiently towards the western warm pool, thinning out the warm surface layer in the eastern ocean basin and transporting the cooling signal westward. As a result, cold subsurface water lodges closer to the ocean surface. This background state requires very little subsurface water to be mixed into the surface layer to produce a substantial cooling. The western equatorial zonal spring winds "precondition" the eastern equatorial Atlantic for the formation of the cold tongue (e.g., Merle 1980; Okumura and Xie 2006; Grodsky et al. 2008; Hormann and Brandt 2009; Marin et al. 2009).

In concert with the development of the first seasonal cooling signals in May and June, the West African monsoon sets in (e.g., Okumura and Xie 2004; Brandt et al. 2011b; Caniaux et al. 2011; Giannini et al. 2003). From an atmospheric perspective, the monsoon onset is characterized by accelerating southeasterly surface winds in the Gulf of Guinea in late boreal spring. The strengthening *meridional* component of these winds enhances upwelling slightly to the south of the equator, and downwelling slightly to the north. The intensified upwelling provides additional initial cooling to the eastern equatorial region by mixing colder subsurface water into the warm surface layer. From the ocean perspective, on the other hand, cooling SSTs in the eastern equatorial Atlantic intensify the southerly winds in the Gulf of Guinea, which in turn contributes to the northward migration of convection and rainfall associated with the West African monsoon (Okumura and Xie 2004).

Lastly, oceanic processes contribute to the formation of the cold tongue. A number of studies found that vertical mixing at the base of the surface layer – where temperature gradients are strongest – seasonally varies in strength (e.g., Hazeleger and Haarsma 2005; Jouanno et al. 2011; Hummels et al. 2013, 2014). A likely explanation for this is that the intensities of the westward surface current and the eastward equatorial undercurrent vary over the course of the year. When the relative velocities of the two currents are strong, the vertical velocity shear at their boundary increases,10 and frictional processes mix colder subsurface water into the warm surface layer. Figure 9 illustrates both the spring state of the tropical Atlantic and the basic processes that produce the first cooling signals in early boreal summer.

The net effect of these interacting processes – the northward migration of the ITCZ and the associated strengthening of the southern hemisphere trade winds on the equator, the thinning of the of eastern equatorial surface layer, the enhanced upwelling along the equator and especially in the cold tongue region, and the increased mixing at the base of the surface mixed layer – is that the first cold anomalies develop in the eastern equatorial Atlantic in late April. The atmosphere in turn reacts to the cold anomalies, and the Bjerknes feedback sets in. Starting in May, it lends additional growth to the cold tongue (Burls et al. 2011). In August, the seasonally active Bjerknes feedback loop breaks down (Dippe et al. 2017) and a more moderate warming sets in. In the absence of the Bjerknes feedback the cold tongue can no longer be maintained and dissolves, due to mixing processes in the ocean and surface heat exchange with the atmosphere.

Many models struggle to simulate a seasonally active Bjerknes feedback that is comparable to observations in both strength and seasonality. Richter and Xie (2008) pointed out that model performance with respect to the Atlantic Bjerknes feedback is quite diverse between models that participated in the Coupled Model Intercomparison Project, Phase 3 (CMIP3, Meehl et al. 2007). Likewise, Deppenmeier et al. (2016) found systematic weaknesses in the CMIP5 models. For example, many models displace the Atlantic warm pool towards the central equatorial Atlantic (Chang et al. 2007; Richter and Xie 2008; Liu et al. 2013). This displacement is a consequence of the westerly wind bias in the western equatorial Atlantic (Wahl et al. 2011; Richter et al. 2012, 2014b). Figure 7 illustrates for the KCM that the spring winds are much weaker in the model than in observations. Consequently, the surface wind stress is not sufficient to pile up warm sur-

<sup>10</sup> "Velocity shear" is a different term for "velocity gradient". A flow is sheared when different layers of the flow have different velocities. Depending on the magnitude of the shear and the viscosity of the fluid, the shear produces local turbulence and mixing due to frictional processes within the fluid. If no turbulence occurs, the flow is called "laminar".

**Fig. 9** Initial cold tongue cooling in the tropical Atlantic. (**a**) Spring conditions. The highest sea surface temperatures (SSTs) and the lowest sea level pressures (SLPs) are found approximately on the equator (dashed black line), forming the equatorial low pressure trough (darkblue shading). The trade wind systems of both the northern and the southern hemispheres (dark blue arrows) converge in the trough and anchor the Inter-Tropical Convergence Zone (ITCZ, clouds and strong precipitation) to the equator. Zonal surface wind forcing is relaxed during spring, warm surface waters are distributed more evenly across the basin. At the ocean surface, the South Equatorial Current (SEC) transports water towards the west. Below the surface, close to the interface between the surface layer and the subsurface, the Equatorial Under-Current (EUC) transports water towards the east. (**b**) Initial cold tongue cooling: In early boreal summer, the ITCZ migrates away from the

face waters in the western ocean basin in a manner comparable to observations. Heat content is distributed more evenly across the equatorial ocean basin and supplies additional heat to the eastern surface layer. Even if the model produced wind variability that could serve as a valid initial perturbation to trigger the Bjerknes feedback,11 the biased background state of the ocean could not support the feedback. The cold tongue fails to establish.

An interesting equivalent of this mechanism has been observed in the real ocean by Marin et al. (2009). The study compares the Atlantic cold tongue in two years with grossly different wind variability and finds that in the year with relatively weak spring winds in the western equatorial Atlantic – this compares well to the climatological, biased state in many CGCMs -, the zonal heat content gradient in the upper ocean does not develop. The winds fail to precondition the tropical Atlantic for the growth of the cold tongue.

Studies with current atmospheric GCMs have found the westerly wind bias in boreal spring to be an intrinsic feature of (uncoupled) atmospheric GCMs (Richter et al. 2012,

equator into the northern hemisphere. The trade winds of the southern hemisphere follow the low pressure trough and cross the equator. In the western ocean basin, zonal surface winds increase and push the warm surface water more efficiently towards the west. The warm pool deepens in the west, while the surface layer thins in the east. Additionally, both the meridional and zonal components of the wind field in the eastern ocean basin strengthen and contribute to a local surface divergence that is compensated by enhanced upwelling (thick, dark-blue arrow). Lastly, both the SEC and EUC increase in strength. Enhanced vertical velocity gradients in the vicinity of the interface between the surface and the subsurface water layers produce shear instabilities (black squiggly lines) that mix the cold subsurface water efficiently into the surface layer

2014b; Harlaß et al. 2017). Coupling an already biased atmospheric GCM to an ocean GCM induces positive feedbacks that amplify the wind and SST biases in the equatorial Atlantic. Additionally, Grodsky et al. (2012) showed that an ocean GCM, too, is intrinsically biased in the tropical Atlantic, although the magnitude of this bias is much smaller than the warm bias in a coupled model.

The atmospheric westerly wind bias has been linked to a seesaw pattern in rainfall biases over South America and Africa (Chang et al. 2007; Richter et al. 2012, 2014b; Patricola et al. 2012). The proposed physical mechanism that links precipitation to the wind is the following: Tropical rainfall is tied to strong convection. Ascending moist and warm air masses create a local negative pressure anomaly at the surface that alters the zonal gradient in surface pressure along the equator. Surface winds, in turn, are dynamically related to surface pressure gradients.12

A current hypothesis of what prevents climate models from developing a cold tongue comparable to observations in

<sup>11</sup>This is by no means a given. As shown below and hinted at above, the equatorial Atlantic bias also manifests in the atmosphere and may well prevent the model from establishing the link between eastern ocean SST and western ocean wind variability that is necessary to close the Bjerknes feedback loop.

<sup>12</sup>Wind compensates pressure gradients. That is why large-scale storm systems are organized around low core pressures: The storm winds try to flow into the low pressure at the "heart" of the storm and eliminate the strong pressure gradient between the storm center and the storm environment. The Coriolis force provides rotation to storm systems by deflecting the pressure compensation flow.

boreal summer thus is: Opposing rainfall biases in South America and Africa produce a zonal surface pressure gradient along the equator that is weaker than in observations. The resulting winds in the equatorial western Atlantic are too weak in magnitude and cannot reproduce the observed distribution of upper ocean heat content. Consequently, the seasonally induced equatorial upwelling in early boreal summer is not sufficient to produce the observed cooling that finally triggers the Bjerknes feedback.

In agreement with these mechanisms, a number of studies have found that a physically sound way to reduce the equatorial Atlantic warm bias is to improve the atmospheric models. Tozuka et al. (2011) showed that tweaking the convection scheme can project strongly on the ability of the models to simulate the correct distribution of climatological SSTs in the equatorial Atlantic. Harlaß et al. (2015) conducted a number of experiments with the KCM that varied both the horizontal and vertical resolution of the atmospheric GCM, while keeping a constant coarse resolution for the ocean GCM. For sufficiently high atmospheric resolutions, the western equatorial wind bias strongly decreased and the equatorial Atlantic warm bias nearly vanished. The seasonal cycle as a whole greatly improved. In a follow-up study, Harlaß et al. (2017) found that sea level pressure and precipitation gradients along the equator are not sensitive to the atmospheric resolution. Nevertheless, the wind bias in their study decreased significantly. To explain this, they propose that the position of maximum precipitation and zonal momentum transport play an important role in giving rise to the zonal wind bias. Zonal momentum can be either transported by mixing it from the free troposphere into the boundary layer or by meridional advection into the western equatorial Atlantic (Zermeño-Diaz and Zhang 2013; Richter et al. 2014b, 2017). These findings agree with the study of Richter et al. (2014a), who found that zonal wind variability in the western equatorial Atlantic is strongly related to vertical momentum transports in the overlying atmosphere. Further studies by Voldoire et al. (2014), Wahl et al. (2011), and DeWitt (2005) confirm the importance of the atmospheric component of a CGCM to properly simulate the complex tropical Atlantic climate system.

#### **Outlook: Implications for the Usability of CGCMs in the Equatorial Atlantic**

Using the KCM, a CGCM that simulates the tropical Atlantic in a manner very similar to a wide range of state-of-the-art CGCMs, we have shown exemplary that coupled global climate models currently struggle to simulate a realistic equatorial Atlantic climate system. The dominant feature of this problem is that CGCMs struggle to simulate the defining feature of the seasonal cycle – the formation of the Atlantic cold tongue in early boreal summer. An important cause of this bias is a strong and seasonally varying westerly wind bias in equatorial zonal wind in atmospheric models that is present even in the absence of atmosphere-ocean coupling. While much progress has been made in understanding and reducing the equatorial Atlantic warm bias, many models still produce a profoundly unrealistic seasonal cycle in the equatorial Atlantic. How does this shortcoming affect the usefulness of coupled models in the equatorial Atlantic?

A key task of climate models is to forecast deviations from the expected climate state. For seasonal predictions, the expected climate state is the climatological seasonal cycle. Some of these deviations are generated randomly and are, by definition, unpredictable. Others are the product of – sometimes potentially predictable – climate variability.

In the tropical Atlantic, the dominant mode of year-toyear SST variability is the Atlantic Niño13 (Zebiak 1993). The Atlantic Niño is essentially a modulation of the seasonal formation of the cold tongue (Burls et al. 2012). This modulation can manifest in a range of different cold tongue measures. For example, cold tongue growth might set in earlier (or later), the cold tongue might cool more strongly, or it might, in its mature phase, occupy a larger area in the tropical Atlantic than usual. Caniaux et al. (2011) argued that all of these measures reveal an aspect of cold tongue variability, but that they do not vary consistently with each other.

Still, the Atlantic Niño is generally described in terms of Atl3 summer SSTs. While the seasonal cycle of Atl3 SSTs spans a range of roughly 5 °C, interannual variations of Atl3 SST between May and July rarely exceed amplitudes of 1 °C (Fig. 10a). The seasonal cycle of the tropical Atlantic is by far the dominant signal in Atl3 SSTs (Fig. 10b). It is the background against which the interannual variability of the Atlantic Niño plays out.

Even though the Atlantic Niño constitutes only a relatively small deviation from the seasonal cycle, its effects on adjacent rainfall patterns can be substantial (e.g., Giannini et al. 2003; García-Serrano et al. 2008; Polo et al. 2008; Rodríguez-Fonseca et al. 2011). A key demand of African countries, where food security heavily relies on agriculture, is hence to be able to reliably predict the amplitude of the Atlantic Niño a few months, ideally even more than a season, ahead. Only such relatively long-ranged forecasts would allow African farmers to adapt their farming strategy

<sup>13</sup>The name "Atlantic Niño" refers to the Pacific El Niño, because the pattern of Atlantic Niño SST anomalies is similar to the Pacific El Niño. Apart from this, a number of differences exist between the two phenomena (discussed for example in Keenlyside and Latif (2007), Burls et al. (2011), Lübbecke and McPhaden (2012), Richter et al. (2013), and Lübbecke and McPhaden (2017)). Nnamchi et al. (2015, 2016) argued that the Atlantic Niño might not be dynamical in nature, but a product of atmospheric noise forcing. Alternative names for the Atlantic Niño are Atlantic Zonal Mode or Atlantic Cold Tongue Mode.

**Fig. 10** The observed Atlantic Niño, based on the NOAA Optimum Interpolated SST dataset (OISST). (**a**) Time series of May–June-July (MJJ) Atl3 sea surface temperature (SST) anomalies. (Anomalies of a time series that, for each year, averaged MJJ monthly means together. Positive values indicate that the observed Atl3 region was warmer in MJJ of that year than on average.) (**b**) Observed seasonal cycle of Atl3 SST (black) and SST trajectories for individual years that produced warm (red) and cold (blue) Atlantic Niño events

for the upcoming season. Unfortunately, most models perform very poorly with respect to the Atlantic Niño and can provide hardly any predictive skill (Stockdale et al. 2006; Richter et al. 2017).

One reason for these shortcomings is that a prerequisite to simulate the variability of Atlantic cold tongue growth is a model that produces a realistic cold tongue. Indeed, Ding et al. (2015) showed that even a symptomatic – as opposed to a dynamically motivated and hence more process-oriented – reduction of the equatorial Atlantic SST bias in the KCM greatly improves the ability of the model to track the observed Atlantic Niño variability. This serves as an example of how the mean state interacts with climate variability. How the bias influences the predictive skill of the KCM for tropical Atlantic SST and whether the real climate system actually provides the potential to produce reliable forecasts of Atlantic Niño variability a few months in advance are the subjects of current research.

In general, the equatorial Atlantic warm bias has been an important issue since the earliest attempts of coupled global climate modeling (Davey et al. 2002) and continues to challenge the scientific community. It serves as an important reminder that model output should not always be taken at face value. Rather, models can struggle to represent observed physical processes, even though their physical basis in the form of the approximated Navier-Stokes equations is sound. In the equatorial Atlantic, the entire coupled system is offkey in coupled global climate models due to the misrepresentation of crucial physical processes. However, alternative ways exist to study the tropical Atlantic with the help of models. Akin to early modeling studies of the El Niño-Southern Oscillation, statistical models can provide some insight into the equatorial Atlantic (e.g., Wang and Chang 2008; Chang et al. 2004). Simulations with ocean-only GCMs help to understand the oceanic response to atmospheric processes (e.g., Lübbecke et al. 2010). Additionally, regional climate models of the equatorial Atlantic have been employed successfully to study different aspects of the region (e.g., Seo et al. 2006; Burls et al. 2011, 2012). Lastly, computational power continues to increase and allows for higher spatial resolution. If the equatorial Atlantic contains predictive potential, future generations of improved CGCMs are likely to unlock it at some point.

The research into various biases, their origins, their dynamics, and, most importantly, possible ways to reduce them, remains a core challenge of the global climate modeling community.

**Acknowledgements** We would like to thank Richard Greatbatch, Peter Brandt, Mojib Latif, Rebecca Hummels, and Martin Claus for discussing the manuscript with us at an early stage and contributing valuable ideas.

While we finished work on the first submitted draft of the manuscript, our colleague and friend Martin Krebs passed away. We hope this study will serve as a reminder of Martin's outstanding scientific work. TD will fondly remember how she discussed first ideas for the manuscript with Martin and how they came up with a rather wayward way to illustrate how much energy was lost from the Atl3 region during the formation of the cold tongue. Turns out that 2.6 times the total global energy consumption of 2011 is enough to power roughly 70 billion generic 600 W fridges for 4 months.

#### **Appendix**

This article is related to the YOUMARES 8 conference session no. 3: "Physical Processes in the Tropical and Subtropical Oceans: Variability, Impacts, and Connections to Other Components of the Climate System". The original Call for Abstracts and the abstracts of the presentations within this session can be found in the appendix "Conference Sessions and Abstracts", chapter "1 Physical Processes in the Tropical and Subtropical Oceans: Variability, Impacts, and Connections to Other Components of the Climate System", of this book.

#### **References**

Banzon V, Smith TM, Chin TM et al (2016) A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies. Earth Syst Sci Data 8(1):165–176. https://doi.org/10.5194/essd-8-165-2016

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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## **The Physical System of the Arctic Ocean and Subarctic Seas in a Changing Climate**

Camila Campos and Myriel Horn

#### **Abstract**

The Earth's climate is changing and the poles are particularly sensitive to the global warming, with most evident implications over the Arctic. While summer sea ice reduced significantly compared to the previous decades, and the atmospheric warming is amplified over the Arctic, changes in the ocean are less obvious due to its higher inertia. Still, impacts of the changing climate on highlatitude and polar oceans are already observable and expected to further increase. The northern seas are essential regions for the maintenance of the Atlantic Meridional Overturning Circulation, which in turn is a key aspect of the maritime climate. Alterations in heat and freshwater/ salinity content in the Arctic Ocean and adjacent seas impact and are closely linked to buoyancy flux distributions, which control the vertical and horizontal motion of water masses, thus impacting the climate system on a longer time scale. In this context, we set our focus on the Arctic Ocean and Atlantic subarctic seas, review some of the contemporary knowledge and speculations on the complex coupling between atmosphere, sea ice, and ocean, and describe the important elements of its physical oceanography. This assessment is an attempt to raise awareness that investigating the pathways and timescales of oceanic responses and contributions is fundamental to better understand the current climate change.

#### **Introduction**

The Arctic region (Fig. 1) is a relative small fraction of the globe's surface, but plays a crucial role in determining global climate dynamics due to the intimate and complex couplings between cryosphere, atmosphere, ocean, and land (Serreze et al. 2007). Currently, the Arctic is undergoing remarkable environmental changes and has been in focus of the climate sciences community (Winton 2008; Overland 2016).

The Arctic near surface air temperature is warming twice as fast as the global average (Serreze and Francis 2006). This accelerated response is known as the Arctic amplification (Winton 2008; Serreze and Barry 2011; Cohen et al. 2014), and one of the most dramatic indicators of the Arctic warming has been the decline in the sea ice cover. Satellite observations reveal that the area of the Arctic sea ice during summer has steadily decreased by more than 40% in recent decades (Fig. 2) (Comiso et al. 2008; Pistone et al. 2014). Notwithstanding, observations further show a year-round loss of sea ice extent and thickness (Lindsay and Schweiger 2015; Rothrock et al. 2008), which suggest that from year to year more melt and less recovery is taking place.

The observed rate of sea ice extent reduction during the last three to four decades has occurred faster than anticipated by models participating on the Intergovernmental Panel on Climate Change Fourth Assessment Report: the observed trend for the September sea ice extent was −9.12 ± 1.54% per decade for the period 1979–2006, while the mean decline trend of all the models participating in the report was −4.3 ± 0.3% per decade (Stroeve et al. 2007). The accelerated sea ice decline has likely occurred due to a combination of decadal-scale variability in the coupled ice-oceanatmosphere-land system and radiative greenhouse gas forcing (e.g., Serreze and Barry 2011; IPCC 2014; Zhang 2015). According to model studies, the Arctic sea ice will continue shrinking and thinning year-round in the course of the twenty-first century as the global mean surface temperature rises, with projections of summer ice free Arctic in the near

Both authors contributed equally.

C. Campos · M. Horn (\*)

Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany e-mail<EMAIL_ADDRESS><EMAIL_ADDRESS>
**Fig. 1** The northern seas (produced with the help of the colormap from Thyng et al. 2016). Bathymetric and geographical map derived from the 2-min ETOPO2 database

future (Wang and Overland 2009; IPCC 2014). Nevertheless, the impacts of these projections for the weather and climate locally and elsewhere are not sufficiently well understood.

Numerous studies have been published on the relation between Arctic sea ice decline and weather and climate. While some have addressed the question how Arctic sea ice decline impacts climate (Budikova 2009; Vihma 2014; Semmler et al. 2016), Lang et al. (2017) and several others have reviewed the recent decline in Arctic sea ice and the processes responsible for it (Polyakov et al. 2012; Stroeve et al. 2012; Barnes and Screen 2015). By far, the majority of these studies focus on atmospheric pathways and, therefore, our understanding of the mechanisms, pathways, and timescales by which the ocean controls or responds to these changes remains quite limited.

Previous studies addressed how the inflow of the warm Atlantic Water (AW) to the Arctic Ocean contributes to the decline of the sea ice extent and thickness (e.g., Carmack et al. 2015; Onarheim et al. 2014). Itkin et al. (2014) has addressed this problem from the reverse perspective, and showed in idealized experiments that a weaker (i.e., thinner) sea ice cover allows higher momentum transfer into the Arctic Ocean and impacts the surface and intermediate ocean circulation. In other words, there is an intrinsic two-way **Fig. 2** Arctic summer sea ice decline (Fetterer et al. 2016, provided by the National Snow and Ice Data Center NSIDC, with permission). (**a**) Arctic September (minimum) sea ice extent in 2016 (white area) compared to the median ice edge for the period 1981 to 2010 (fuchsia line) and (**b**) average monthly September sea ice extent for the years 1979–2016, blue line: decline rate of 13.2% per decade relative to the 1981–2010 average

relation between the ocean and the sea ice, and any change in sea ice cover may impact the dynamics and thermodynamics of the ocean. Recent observations suggest that a diminishing sea ice cover to the northeast of Svalbard is responsible for reducing the stratification of the ocean and allowing more upward heat transfer, which preconditions the ice to further melting (Polyakov et al. 2010, 2017).

A significant increase in liquid freshwater content has been observed in the upper Arctic Ocean in the past two decades (Rabe et al. 2011; Giles et al. 2012; Morison et al. 2012; Rabe et al. 2014), while the Arctic sea ice volume has been shrinking significantly (Lindsay and Schweiger 2015). Sea ice and liquid fresh water are important factors for the Arctic Ocean, where they insulate the atmosphere from the warm Atlantic-derived water at intermediate depths, by limiting the upward heat transport, hence influencing the sea ice formation and melting as well as the air temperature.

After a freshening of the subpolar North Atlantic and Nordic Seas from the 1960s to the 1990s, both regions became again more saline thereafter (Curry and Mauritzen 2005; Boyer et al. 2007; Mauritzen et al. 2012). The Nordic Seas and the subpolar North Atlantic are the main regions in the northern hemisphere, where deep water formation takes place and thereby are key regions for global climate (Rhein et al. 2011). Freshwater changes could potentially influence this overturning system and thereby have a profound impact on our climate (Koenigk et al. 2007; Rennermalm et al. 2007).

In this chapter, we provided an introductory overview on the complex interactions of the coupled Arctic system in a changing climate with specific interest in the ways in which Arctic Ocean and adjacent seas may respond and modulate the observed and projected changes over high and midlatitude. Next, we give an overview of the complex interplay between the dynamics and thermodynamics of the sea ice, atmosphere and ocean. We start by addressing the sea ice cycle, variability, and importance in the climate system (Section "Arctic sea ice"). In Section "Arctic – subarctic atmosphere" we give background information on the Arctic – Subarctic atmosphere (Section "Atmospheric circulation: Why does it matter?") and present the main atmospheric circulation modes (Section "Major modes of atmospheric circulation in the Arctic"). Then, we finally get to discuss the changing climate from the ocean perspective (Section "Ocean"): at first, we describe the main geographical features and the hydrography of the northern seas; subsequently, we address recent research and discussion of the global relevance of the region in a changing world. Final remarks are given in Section "Outlook".

#### **Arctic Sea Ice**

#### **Sea Ice Cycle**

The sea ice cover has a natural cycle as a consequence of the periodic changes of incident solar radiation over high latitudes. As the cold season arrives, atmospheric temperatures rapidly begin to drop. This leads to a positive thermal gradient from ocean to the surrounding air, resulting in a direct loss of sensible heat from the upper ocean. Dynamical instability in the upper meters of the ocean is generated as a consequence to density changes caused by cooling, and a vertical mixing is maintained until a significant layer of the upper water column approaches homogeneous temperature. Once the ocean freezing temperature of −1.9 °C is achieved, sea ice structures begin to form, and during this process a salt solution (brine) is expelled into the ocean further increasing its density. However, if mixing is deep enough, the surface waters may not reach freezing temperatures due to mixing with the warmer waters at intermediate depths and sea ice formation will not occur.

After initial formation in fall, sea ice continues growing through winter months and increases in vertical and horizontal extent. It can be characterized by highly complex and variable macrostructures, such as ridges, melt ponds, leads and polynyas. By the end of wintertime, the sea ice extent has reached its maximum. During spring, the solar radiation gradually increases thereby initiating the melting phase, which carries on until the next cooling season. If all the sea ice melts away, the area is characterized by the presence of fist year ice. However, if sea ice persists until the end of the warm season a perennial (multiyear) sea ice cover establishes. The fundamental differences between them relate to the vertical growth and surface roughness.

Overall, freezing and melting are controlled by net surface heat energy flux variations during the year, and environmental conditions, e.g., wind and oceanic currents, play a role in determining expansion and thickening. Furthermore, the horizontally confined Arctic Ocean allows for thicker sea ice growth (in comparison to the Southern Ocean), and winter sea ice thickness ranges on average from 3 to 4 m. For more details the reader is referred to Thomas and Dieckmann (2010).

#### **Sea Ice Role in the Climate System**

Sea ice is a highly reflective surface, with albedo ranging from 50% to 70%. Albedo is a measure of a surface's reflectivity, and may be even higher if a snow cover is present. A thicker ice pack supports a greater layer of snow and this system can reflect up to 90% of solar energy. Additionally, it acts as an insulator between ocean and atmosphere, and, therefore, restricts heat and momentum fluxes at this interface. If the atmosphere or the ocean warms up (above melting temperatures) sea ice melts and, since the exposed ocean surface has a much lower albedo than sea ice, the overall albedo of polar areas decrease. The low reflectance oceanic surface takes in extra heat, driving major changes in the regional radiative equilibrium and further sea ice melt. The described processes is the so-called ice-albedo feedback mechanism and is accounted as the main reason of nonlinear changes over polar regions (Winton 2008; Serreze and Barry 2011; Vihma 2014). Changes to ocean density caused by the sea ice cycle are important processes for the local oceanic stratification and global oceanic circulation.

A few specific areas of the high latitude oceans are crucial for the production of dense water masses, which contribute to the lower limb of the global oceanic overturning circulation. The upper layers of the ocean are densified through cooling of surface waters and the injection of brine during sea ice formation resulting in vertical mixing and deep convection (Tomczak and Godfrey 1994). In these regions the dense water sinks and is replaced by surface water from other areas and the continuation of this process is one of the drivers of the Meridional Overturning Circulation; the sinking of these waters is compensated by upwelling at other sites (Talley et al. 2011). On the other hand, sea ice constitutes a source of relatively fresh water (with an average salinity ranging from 2 to 7 (Thomas and Dieckmann 2010)) and when it melts it decreases the density of the water directly underneath, creating a stable surface layer. Changes in the water density at the deep convection sites may alter mixing and convection processes. Hence, the presence of sea ice strongly modulates interactions between ocean and atmosphere, namely heat, mass, and momentum transfers.

In addition to all physical aspects, sea ice acts as a key component also for the Arctic ecosystem, it also determines marine transportation and offshore activities, and is of crucial societal importance. A detailed description of these aspects is beyond the scope of the present review, but we refer to the Arctic Climate Impact Assessment – Scientific Report (ACIA 2004) for a more thorough perspective.

#### **Arctic – Subarctic Atmosphere**

#### **Atmospheric Circulation: Why Does It Matter?**

The polar regions are the world's heat sink: at low latitudes the amount of incoming solar radiation (shortwave) exceeds the emitted infrared radiation (longwave), whereas there is an annual energy deficit at the poles, where more heat is emitted than absorbed. The surplus of energy is then transported from the equatorial region towards the poles in the atmosphere and ocean. In the atmosphere, this manifests as global circulation cells, which, due to turbulent interactions, transfer energy to smaller processes of regional and local importance forcing climate and weather patterns. The latter play a very important role in the coupling with ocean and sea ice, which on the other hand also force changes on the atmospheric circulation. Therefore, global climate and weather are highly dependent on these interactions between the components of the earth system (Taylor 2009).

Though temperatures have been increasing in polar and equatorial regions, it has been amplified at high latitudes, especially over the Arctic (Serreze and Barry 2011). This amplification is attributed to several feedback mechanisms (Taylor et al. 2013) and, even though the ice-albedo feedback is often cited as primary contributor, some studies suggest that other interactions, like the warming of the lower atmosphere might play a bigger role (Pithan and Mauritsen 2014). Serreze and Barry (2011) provide a thorough synthesis of research on Arctic amplification.

The fact that the temperature increase over the Arctic has been happening at a faster rate than the global average, decreases the overall meridional temperature gradient over the globe, which in turn may affect the atmospheric circulation pattern locally as well as remotely (Barnes and Screen 2015). The scientific community has been broadly concerned with possible changes over mid-latitude weather such as, e.g., the occurrence of extreme weather events and the weakening and shifting of the westerly winds (Overland 2016). These winds are strongly coupled to the track and intensity of storm systems travelling at mid-latitudes, hence it is expected that changes in the position and strength of the jet stream leads to noticeable changes in the northern hemispheric daily weather (e.g., Barnes and Screen 2015; Serreze and Barry 2011).

The particular role and responses of the atmosphere in a warming climate are beyond the scope of this work. Thus, for more comprehensive understanding we refer here to several studies which review and investigate responses of largescale atmospheric circulation to changes in sea ice cover over the Arctic (Budikova 2009; Bader et al. 2011; Vihma 2014; Semmler et al. 2016). Nevertheless, an overview on the background characteristics of the Arctic atmospheric system are given next.

#### **Major Modes of Atmospheric Circulation in the Arctic**

As explained above, atmospheric circulation and weather are linked to gradients. The system has an intrinsic seasonal variability upon which these gradients oscillate. To characterize the major atmospheric modes over the Arctic, a brief illustration on its climatology is given in terms of sea level pressure.

The prevailing atmospheric circulation over the Arctic is anticyclonic, which results from an average high-pressure system that spawns winds over the region. Although prevalent, the circulation regime may shift to cyclonic on the time scales of 5–7 years (Proshutinsky et al. 2009). Shifts from one regime to another are forced by changes in the location and intensity of the pressure systems described below. This oscillatory mode is part of the Arctic system's natural variability and may help to explain the significant, basin-scale changes of the Arctic atmosphere-ice-ocean system (Polyakov and Johnson 2000; Proshutinsky et al. 2009, 2015).

The two semi-permanent centers of low pressure, the oceanic Aleutian and Icelandic Lows, and the continental Siberian High, which extends into the Arctic as the Beaufort High, are observed as pronounced features during winter. In summer, the gradients of the polar and subpolar regions are relatively weak, and sea level pressure distribution is dominated by the subtropical, the Azores and the Pacific Highs (McBean et al. 2005). To describe the main states of the atmospheric circulation, indices were created. Based on a surface variable and obtained through statistical analysis, these are used to characterize complex climate processes and explain past variability.

The major mode of variability in the Arctic is the Arctic Oscillation (AO), and is characterized by the relation between the surface pressure anomaly in the Arctic and in mid-latitudes (Thompson and Wallace 1998). When the AO is in its positive phase, surface pressure in the polar region is low. This mode manifests as the strengthening of the zonal westerly winds

**Fig. 3** Schematic of the Arctic Oscillation and its effects (adapted from AMAP 2012, with permission). Positive Arctic Oscillation (**a**) and negative Arctic Oscillation (**b**) Accordingly, the centres of low (red encir-

which act to confine colder air over the high latitudes. On the other hand, in the negative phase of the AO, surface pressure is high in the Arctic, acting to weaken the atmospheric circulation, and thus, allowing an easier escape of the cold polar air masses towards the mid-latitudes (Fig. 3).

The regional manifestation of the AO in the North Atlantic is the North Atlantic Oscillation (NAO). It is given by the correlation of the main pressure centers in the North Atlantic, namely the Icelandic Low and the Azores High (Fig. 3). Oscillations between positive and negative phases are tied to shifts in storm tracks and associated patterns of precipitation and temperature.

For more detailed information we refer to Serreze and Barry (2014) and Turner and Marshall (2011).

#### **Ocean**

#### **Geography of the Arctic Mediterranean**

The Arctic Mediterranean consists of two major parts: the Arctic Ocean and the Nordic Seas. The Arctic Ocean is the northernmost part of the Arctic Mediterranean which is enclosed by North America, the Eurasian continent, Svalbard, and Greenland (Fig. 1). The Nordic Seas are enclosed by Svalbard, Norway, Iceland, Scotland and Greenland and include the Greenland Sea, Norwegian Sea, and Iceland Sea (also called the GIN Seas). The Arctic Ocean connects to the

cled L) and high (blue encircled H) pressure systems over the North Atlantic indicate the corresponding North Atlantic Oscillation phases (**a**: positive, **b**: negative)

Nordic Seas via the Fram Strait (between Greenland and Svalbard, ~2600 m deep) and the Barents Sea Opening (between Svalbard and Norway, ~200 m deep). Other gateways are the narrow channels through the Canadian Arctic Archipelago (Islands North West of Greenland, ~150–230 m deep) and the Bering Strait (~45 m deep and only 50 km wide), which is the only connection to the Pacific Ocean. Towards the Eurasian Continent the Arctic Ocean consists of wide, shallow shelves (<50–300 m deep), which make up almost half of the entire Arctic Ocean and comprise five marginal seas: Barents Sea, Kara Sea, Laptev Sea, East Siberian Sea and Chuckchi Sea. At the coasts of North America and Greenland the shelves are much narrower. The deep basins in the center of the Arctic Ocean are divided into two major parts, the Amerasian Basin and the Eurasian Basin. They are separated by the Lomonosov Ridge, which is approximately 1600 m deep. The Eurasian Basin consists of the Nansen Basin and the Amundsen Basin, which are separated by the Gakkel Ridge. The Mendeleyev Ridge and Alpha Ridge divide the Amerasian Basin into the Makarov Basin and the Canada Basin. With approximately 4500 m depth, the Amundsen Basin is the deepest, while the Canada Basin is by far the largest. The boundary of the Nordic Seas to the North Atlantic is Denmark Strait (~ 500–700 m deep) and the Iceland-Scotland-Ridge (~300–850 m deep). There are two fracture zones in the center of the Nordic Seas: the Greenland Fracture Zone and the Jan Mayen Fracture Zone. The shelves along the Greenland coast are wide and shallow with a steep shelf break.

#### **Arctic Ocean Circulation and Hydrography**

Since the Arctic Ocean is a largely enclosed ocean, there are only two water masses that enter the basin from other oceans: Pacific Water (PW) and Atlantic Water (AW). The lowsalinity PW is transported through the Bering Strait (Fig. 4) and is mainly advected at the surface into the Amerasian Basin and adjacent shelf regions. In addition to continental runoff and precipitation, the low salinity PW is an important Arctic fresh water source. Due to relatively small differences in temperature throughout the water column of the Arctic Ocean, the stratification is mainly determined by salinity changes (Fig. 5). Thus, the fresh (light) waters stay in the upper ocean and build the so called Polar Mixed Layer. Large parts of the Arctic Ocean are covered by sea ice which is built from these fresh surface waters at near-freezing temperatures. By sea ice formation and melt, freshwater is concentrated at the surface.

The AW is warmer but saltier than PW and Meteoric waters comprising continental run-off and net precipitation. Thereby, it is denser and can be found deeper in the water column. The significant difference in salinity creates a strong halocline between the Polar Mixed Layer and the AW layer establishing a strong permanent stratification in the deep basins (Fig. 5). The halocline, which is defined by high vertical salinity gradients (32.5 < S < 34.5), is thickest in the Canada Basin (200–250 m) and thinnest in the Nansen Basin (100–150 m). The temperatures of the halocline remain close to the freezing point. Due to heat loss and mixing with shelf waters there are many modifications of AW at intermediate depths. Just below the halocline, temperatures are highest in the Nansen Basin and decrease towards the Canada Basin (Fig. 5). The densest waters are formed on the shelves of the Barents Sea, where the AW subsequently releases heat to the atmosphere and is mixed with brine rejected from newly formed sea ice before it sinks down the shelf break into the Nansen Basin (Fig. 4). This Arctic bottom water is the densest water of the world ocean, but can only be found in the Arctic region (Tomczak and Godfrey 1994). Only a small part is able to flow over the sill of the Fram Strait into the Nordic Seas balancing the bottom/deep water formation on the Arctic shelves (e.g., Bönisch and Schlosser 1995).

The surface circulation in the central Arctic Ocean mainly comprises two features: the Beaufort Gyre and the Transpolar Drift (Fig. 4). The Beaufort Gyre is an anticyclonic circulation in the Canada Basin that is forced by a high pressure system in the lower atmosphere, the so called Beaufort High. Fresh surface waters from the shelves and from the Pacific accumulate in the interior of the gyre and leave the Arctic through the Canadian Arctic Archipelago or the Fram Strait. The Transpolar Drift is a wind-driven current that directs sea ice and waters from the Siberian shelves and the Bering Strait to the Fram Strait, where they exit the Arctic Ocean into the Nordic Seas and subpolar North Atlantic.

The relatively warm and saline AW, which is the main water source of the entire Arctic Ocean, enters the Nordic Seas from the south. The Norwegian Atlantic Current carries the AW through the Nordic Seas at the surface and splits into two main branches. One branch enters the Arctic Ocean through the Barents Sea Opening, the other, which then is called West Spitsbergen Current, flows through the Fram Strait. Only a part of the West Spitsbergen Current propagates further north into the Arctic Ocean, the other part recirculates close to the Fram Strait. The AW dives underneath

**Fig. 4** Schematic of the Arctic Ocean circulation (reproduced from Carmack et al. 2015, American Meteorological Society, used with permission). Blue arrows indicate the surface circulation, pink-blue arrows the main pathways of the Pacific Water at intermediate depths and red arrows show the Atlantic Water circulation. GIN Seas: Greenland-Iceland-Scotland Seas, usually called the "Nordic Seas"

**Fig. 5** Upper Arctic Ocean hydrography (reproduced from Rudels 2009, with permission from Elsevier). Potential temperature and salinity of the upper Nansen Basin (NB, orange), Amundsen Basin (AB, green), Makarov Basin (MB, purple), and Canada Basin (CB, blue). *PML* Polar Mixed Layer

the sea ice when reaching it North of Fram Strait and later meets the other cooled AW branch, which flows down the Barents Sea shelf slope into the Nansen Basin. Steered by the topography, the AW flows along the shelf breaks and spreads all over the Arctic Ocean forming counterclockwise circulations in all deep basins (Fig. 4).

For more details on the Arctic Ocean hydrography and circulation see Rudels (2009).

#### **Fresh water**

As salt is mainly conserved in the present-day oceans, the only way to change ocean salinity, which determines the stratification in the Arctic Ocean, is by removing or adding fresh water. Therefore, fresh water, both liquid and stored in sea ice, plays a key role in many physical processes in the Arctic. It is of high relevance for local and global climate and the thermohaline circulation, as the fresh surface layer in the Arctic Ocean limits the upward heat transfer from the AW layer to the atmosphere and sea ice and as a freshening of the upper Nordic Seas and subpolar North Atlantic may decrease deep convection due to higher stratification (e.g. Aagard and Carmack 1989; Haak et al. 2003; Häkkinen 1999; Yang et al. 2016).

By freshwater content or oceanic freshwater transport, we understand an equivalent amount of fresh water that is required to dilute water with a reference salinity to obtain the observed salinity. For the Arctic Ocean most studies use a reference salinity of 34.8 as it is approximately the average salinity of the Arctic Ocean (e.g., Aagard and Carmack 1989; Serreze et al. 2006; Holland et al. 2007; Haine et al. 2015). Others choose the reference salinity 35 as it is approximately the salinity of the AW inflow (e.g., Rabe et al. 2011, 2014). With a changing climate and related ocean changes, the estimates of the average Arctic Ocean salinity and AW inflow salinity might need to be adjusted. However, there is a starting discussion amongst scientists on the sensible choice of the reference salinity, challenging the common way to calculate freshwater content and transport (Tsubouchi et al. 2012; Bacon et al. 2015).

More than 100,000 km3 of fresh water with respect to a reference salinity of 34.8 are stored in the Arctic Ocean (Haine et al. 2015) (Fig. 6). About 95,000 km3 are stored as liquid freshwater and about 15,000 km3 in sea ice (Haine et al. 2015). Liquid fresh water is added to the Arctic Ocean by precipitation, continental run-off, glacier/ice sheet/sea ice melt, and PW inflow and is removed by evaporation, sea ice formation and advection to the North Atlantic. All these sources and sinks are affected by the recent climate change

**Fig. 6** Arctic freshwater variability (adapted from Haine et al. 2015, with permission from Elsevier). (**a**) Arctic liquid freshwater volume (Arctic Ocean, Canadian Arctic Archipelago and Baffin Bay) and (**b**)

influencing the freshwater budget of the Arctic Ocean and adjacent seas.

#### **River Runoff and Atmospheric Fluxes**

The major source of liquid fresh water in the Arctic Ocean is the continental runoff. The rivers discharge approximately 3300 km3 year−<sup>1</sup> fresh water to the upper Arctic Ocean, which accounts for 11% of the total global river discharge (Fichot et al. 2013). Considering that the upper Arctic Ocean only makes up 0.1% of Earth's total ocean volume, this is a remarkable contribution. Net precipitation (precipitation minus evaporation) over the Arctic is estimated to 2200 km3 year−<sup>1</sup> (Haine et al. 2015).

Syntheses of Arctic river discharge data revealed an increase of 7–10% in the last 30 to 60 years correlated with the NAO and global mean surface air temperature (Peterson et al. 2002; Overeem and Syvitski 2010). Niederdrenk et al. (2016) showed in a model study that a strong Icelandic low promoting warmer and wetter conditions over Eurasia leads to increased precipitation and thus enhanced river runoff to the Arctic Ocean. This mechanism is proposed to be respon-

export flux (through Davis and Fram Strait) from observations (red) and an ideal outflow model (blue). The arrows indicate estimates from Rabe et al. (2011, 2014)

sible for the most of the Arctic river runoff variability. Although Déry and Wood (2005) found a 10% decrease in annual river discharge from Canadian rivers into the Arctic Ocean and North Atlantic, the total river discharge into the Arctic Ocean increased by 5.6 km3 year−<sup>2</sup> during the second half of the twentieth century (McClelland et al. 2006). There is evidence for an intensification of the global water cycle related to global warming (Huntington 2006) explaining the positive trends in precipitation and continental runoff.

#### **Arctic Glacier and Greenland Ice Sheet Melt**