The Ocean Takes a Deep Breath

by Brad deYoung

A team of scientists  from across the country is studying how the ocean breathes. They are studying the exchange of gases, carbon dioxide and oxygen, in the Labrador Sea, one of the few places in the planet where water sinks deep into the ocean carrying these gases with it. The scientists are part of a team working on an NSERC funded CCAR project called VITALS – Ventilations Interactions and Transports Across the Labrador Sea http://knossos.eas.ualberta.ca/vitals/. They have put together a video to describe how the ocean breathes.

This research combines new observations and modelling to determine what controls the exchange of these gases and how they are linked to and interact with the climate system. This video explains how the deep ocean connects with the atmosphere and the role of this deep breathing in climate change. The leaders of this program are Paul Myers (University of Alberta), Roberta Hamme (University of Victoria), Jean-Eric Tremblay (Univesite Laval), Jaime Palter (University of Rhode Island), Doug Wallace (Dalhousie University) and Brad deYoung (Memorial University.

 

View other OSNAP related videos: http://www.o-snap.org/outreach/video-and-animation/

Posted in News

Studying the ocean, where there is no ocean

by Xianmin Hu

I have been in Edmonton for almost ten years (PhD study and then postdoc of University of Alberta). When I tell people I am studying (physical) oceanography, they always laugh at me. I wish I had a perfect answer when they ask me “Why are you studying the ocean here? There is no ocean in Edmonton.” Physical Oceanography sounds strange to most, so I always “hide” the physical part in the name.

Well, there are too many things I can’t explain to them well enough. I count myself as an oceanographer but I don’t swim. Actually I prefer to move upward as I do climbing …. My friends joked that that I am preparing for the sea level changes. We know the sea level changes slowly, so one step higher might be the most efficient way (selfish though) to step away from the sea level rising problem.

With very little experience at sea, I am working with computers most of the time. Yes, I am one of them, the mysterious numerical ocean modellers. I have been working with the NEMO model (same name of the famous little fish) for years. To be more specific, I mainly do simulations with a regional configuration called ANHA. Someone once asked, “Is ANHA your girlfriend?” Of course, he was joking. ANHA stands for the Arctic Ocean and Northern Hemisphere Atlantic configuration. However, he was also right. To me, when you opt to sacrifice your personal time on one thing, it could be love; otherwise, it is just a one-way “benefit friendship”.

Sorry for drifting too far away, which is also a common problem in numerical modelling. Let’s pull it back to the ocean. My concern of the ocean is the salt. Life needs more salt, however, an ocean modeller may not agree because more salt leads to the model drift, particularly in the high latitude, which makes people feel bad for models.

However, sometimes, it is not necessarily the fault of the model itself. The ocean is thirsty. If there is little river discharge and rain, the Arctic Ocean and Atlantic Ocean salinity could look something like figure 1.

Figure 1 Simulated Sea Surface Salinity (SSS) with little freshwater into the ocean

Well, let’s feed the ocean with a reasonable amount of river discharge and precipitation, and the ocean looks much better (figure 2).

Figure 2 Simulated SSS with realistic freshwater into the ocean

Look (figure 2), can you see the freshwater plumes from the the big rivers? I was very excited to “see” these rivers showing up in the simulation. Meanwhile, a picky person like you may also notice the fresh water around southern Greenland. Yes, we can assume Greenland is just a rock island in the model. But we know the Greenland Ice Sheet (GrIS) is melting and feeding the surrounding ocean with a large amount of freshwater. Here we must give Jonathan Bamber credit for his freshwater estimates from the Greenland Ice Sheet.

The ocean is pretty happy with the freshwater from Greenland, thus, it is willing to tell us more about her, even the secret pathway of the Greenland meltwater (figure 3).

Figure 3 Vertical integrated (whole water column) of the Greenland meltwater passive tracer

Not a big surprise, it agrees with the general ocean circulation in this region as we know it. However, did you ever think about the spatial distribution, e.g., how much is accumulated in Baffin Bay and how far it can go down to south along the east coast of North America? The models do tell people something that is hidden behind what we see.

In the end, a nice story was made, but still, there is no ocean in Edmonton….

Posted in Student/Postdoc Blog

OSNAP Challenge 2017

In the summer of 2016, the OSNAP team collected data from the full array for the first time. Prior to publishing the first estimate of the meridional overturning circulation (MOC) this coming fall, we invited the ocean community to predict the overturning variability at the OSNAP line. Four groups entered this OSNAP challenge by submitting predictions from September 2014 (initial deployment of the OSNAP line) to August 2016. This OSNAP challenge was certainly challenging given that there were no previous OSNAP data from which to base the predictions. As such, we are grateful to the modelling community for participating in such a speculative activity.

Results

A preliminary analysis from OSNAP yields a mean MOC of 13.15 Sv with a standard deviation of 3.31 Sv during the 21-month period for September 2014 – May 2016. All predictions are shown in Figure 1. We assessed the accuracy of each prediction by both the root-mean-square-error (RMSE) from the observed time series and its temporal correlation (r) with the observed time series.

Table 1. Skill of the four predictions, ranked according to RMSE.

Model # Group RMSE (Sv) Correlation (r)
1 Ben Moat (NOC, UK) 3.30 0.59
2 Laura Jackson (Met Office, UK) 5.87 0.50
3 Charlène Feucher (University of Alberta, Canada) 6.34 -0.14
4 Andrea Storto (CMCC, Italy) 9.86 0.33
  Mean of predictions 6.34  


Winner

Ben Moat and his group from the National Oceanography Centre (NOC) in Southampton, UK won the competition with the lowest RMSE and highest correlation. Congrats to Ben and his colleagues! For their efforts they will receive the grand prize of OSNAP T-shirts!

Figure 1. The MOC time series for 2014-2016. The black line shows the observational time series. Colored lines show the four entries (ranked according to RMSE). Numbers in the upper left hand corner indicate the mean MOC plus/minus one standard deviation for each of the submitted time series. Note: Instrument failures near the end of the two-year deployment limited the OSNAP observational estimate to 21 months (September 2014 – May 2016).

More on the prediction

If you would like to know more about how each prediction was made, here are links to blog entries by some of the participants:

[1] OSNAP Challenge by Charlène Feucher, University of Alberta

Posted in News

Extended Ellett Line research cruise and Subpolar North Atlantic transport

By Elizabeth Comer

In my last blog a year ago I mentioned I would be going to sea for the Extended Ellett Line (fig. 1) annual research cruise, which is part of the OSNAP array.  I boarded the RRS Discovery during June and we steamed towards Iceland, where we started sampling at each CDT station whilst heading back to Scotland. During this cruise I focussed mainly on the ADCP measurements and processing, as I was going to start using it within my research and this was the perfect way to get familiar with it. I had a brilliant time on this cruise, as the photos hopefully depict (fig. 2, 3 and 4), and it was a great insight to Oceanography in the field.

Now onto how this data will aid my research. The aim of my current research is to investigate the long-term mean and variability in volume, freshwater and heat transport of the Subpolar North Atlantic. All the hydrographic and velocity measurements collected annually are used to compute these transports, providing a near 20-year timeseries. It is important that we take continuous measurements at this location and compute these transports as 90% of the Atlantic inflow into the Nordica Sea and Arctic takes place between Iceland and Scotland, as well as roughly half the returning dense water. This research will add to our knowledge of how the Meridional Overturning Circulation in the Subpolar Atlantic is varying on a decadal to seasonal timescale, and add insight to the mechanisms controlling it. This observational data also enables the enhancement of oceanic models to produce transport variabilities on longer timescales.

The research into the long-term transport that has been carried out with my Supervisors Dr Penny Holliday and Prof Sheldon Bacon will be published in the near future, but below is a taster of the 18-year (1997-2015) mean Lowered-ADCP velocity across the section (fig. 5). This data is used to produce the long-term absolute velocity by providing a reference velocity for the geostrophic velocity field, which the transports are computed from. In this study I investigate how the transport varies across the region, highlighting the key routes for transport and why it is important we know this. Furthermore, the Scottish Continental Slope Current that runs northward along the Scottish shelf edge and the Rockall-Hatton Bank have the highest temperatures and salinities of the region. Hence, I hypothesis that these are fundamental routes for heat transport northward.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Posted in Student/Postdoc Blog

OSNAP at EGU

April 23-28, 2017 in Vienna, Austria
Meeting Website

Monday, 24 Apr 2017
The North Atlantic: natural variability and global change (co-organized)
OS1.2/AS1.20/CL1.29
Oral Presentations:
Location: Room D2

On the Nature of the Mesoscale Variability in Denmark Strait
Robert Pickart, Wilken von Appen, Dana Mastropole, Hedinn Valdimarsson, Kjetil Vage, Steingriumur Jonsson, Kerstin Jochumsen, and James Girton
EGU2017-5372
09:00-09:15
View Abstract

OSNAP Update: Measuring the AMOC in the subpolar North Atlantic
M Susan Lozier
EGU2017-10341
10:30–10:45
View Abstract

Overflow Water Pathways in the Subpolar North Atlantic Observed with Deep Floats
Amy Bower, Heather Furey, and Susan Lozier
EGU2017-8103
11:00–11:15
View Abstract

Observed and Modeled Pathways of the Iceland Scotland Overflow Water in the eastern North Atlantic
Sijia Zou, Susan Lozier, Walter Zenk, Amy Bower, and William Johns
EGU2017-9794
11:15-11:30
View Abstract

Transport of Iceland-Scotland Overflow waters in the Deep Western Boundary Current along the Reykjanes Ridge
William Johns, Adam Houk, Greg Koman, Sijia Zou, and Susan Lozier
EGU2017-9415
11:30–11:45
View Abstract

Gulf Stream transport and mixing processes via coherent structure dynamics
Chris Wilson, Yi Liu, Melissa Green, and Chris Hughes
EGU2017-10345
14:00–14:15
View Abstract

Transport Structure and Energetic of the North Atlantic Current in Subpolar Gyre from Observations
Loïc Houpert, Mark Inall, Estelle Dumont, Stefan Gary, Marie Porter, William Johns, and Stuart Cunningham
EGU2017-5593
14:30–14:45
View Abstract

Poster Presentations
Location: Hall X4
Time: 17:30–19:00

Volume, heat and freshwater transport in the Irminger Current
M. Femke de Jong, Laura de Steur, Stelios Kritsotalakis
EGU2017-9635
X4.28
View Abstract

Assessing variability in the size and strength of the North Atlantic subpolar gyre
Nick Foukal and Susan Lozier
EGU2017-10141
X4.6
View Abstract

Transport and seasonal variability of the East Reykjanes Ridge Current
Greg Koman, Adam Houk, Cobi Christiansen, and Bill Johns
EGU2017-8490
X4.43
View Abstract

On the Linkage between Labrador Sea Water Volume and Overturning Circulation in the Labrador Sea
Feili Li and Susan Lozier
EGU2017-9776
X4.48
View Abstract

Application of a Regional Thermohaline Inverse Method to observational reanalyses in an Arctic domain
Neill Mackay, Chris Wilson, and Jan Zika
EGU2017-17329
Poster: X4.60
View Abstract

The AMOC as a mechanism for nutrient supply to the Eastern North Atlantic
Ryan Peabody and Susan Lozier
EGU2017-17315
X4.56
View Abstract

Gyre scale deep convection in the subpolar North Atlantic Ocean during winter 2014-2015
Anne Piron, Virginie Thierry, Herlé Mercier, and Guy Caniaux
EGU2017-10183
X4.49
View Abstract

Circulation in the region of the Reykjanes Ridge in June-July 2015
Petit Tillys, Mercier Herle, and Thierry Virginie
EGU2017-13328
X4.25
View Abstract

Tuesday, 25 Apr 2017
Room: G2

Mesoscale eddies control meridional heat flux variability in the subpolar North Atlantic
Jian Zhao, Amy Bower, Jiayan Yang, Xiaopei Lin, and Chun Zhou
EGU2017-17050
09:15-09:30
View Abstract 

 

Posted in News

Deep-water masses in the Subpolar North Atlantic, where do they occur and what are the physics behind them?

by Patricia Handmann

In October 2014 I started my PhD at GEOMAR and Kiel University. I was coming from KIT (Karlsruhe Institute of Technology ), where I studied experimental and theoretical physics and worked on cloud microphysics for a year as part of my diploma (masters) thesis. Before I started my diploma thesis I got the chance of an internship at Alfred-Wegener Institute and worked on quality control of some old cruise data from RV POLARSIRKEL in 1980/81, which was a great experience. I had a lot of fun during these three months at AWI while getting to know this new field of ocean physics. So when I was looking for a PhD after this internship I was intrigued by the general topic of deep-water formation in the northern and southern hemisphere. When I started at GEOMAR this idea quickly evolved into a more focused study comparing a high-resolution ocean model (VIKING20) with observations from the 53°N array. This boundary current observatory is maintained by Kiel scientists since 1997 to document the changes of the deep-water circulation in the Subpolar North Atlantic (SPNA).

My main research question is: What are processes imprinting variability to the deep-water masses in the SPNA, where do they occur and what are the physics behind them.

But lets start with some background information …

The exit of the Labrador Sea is a key location in the subpolar North Atlantic concerning the integral quantities of the Deep Western Boundary Current (DWBC). It is the place where deep water masses from different origins and pathways meet. The combination of these is collectively called North Atlantic Deep Water (NADW).

To evaluate the high resolution model VIKING20 by means of integral quantities at the exit of the Labrador Sea, and to interpret the observed hydrographic and dynamic DWBC features with consideration of the underlying physical processes and forcing is the aim of my work.

I found that the VIKING20 model, which is driven by CORE2 atmospheric forcing, can be nicely compared to more than decade-long observations at the exit of the Labrador Sea near 53°N. VIKING20 is a high resolution (1/20°) nest, based on the global configuration of the NEMO-LIM2 ocean-sea ice model ORCA25 in the North Atlantic and implemented by two-way nesting (Behrens [2013];Böning et al. [2016]). The average flow field, being one of the integral quantities of the boundary current at 53°N including the bottom flow-intensification, is reproduced by VIKING20 (figure 1).

Figure1: Mean velocity field computed from LADCP and mooring data from 53°N (left) (Fischer et al. [2010]) and the mean velocity field of the full resolution Model section at 53°N for the period from 1958 till 2009 (right).

Although circulation and recirculation is stronger and more barotropic in the model than in the observations the overall transport at 53°N including both circulation and recirculation coincides with the observed transport of NADW of ~30 Sv (Zantopp et al. [2017]). Is the model, apart from its challenges in hydrography and hence different baroclinicity, still reproducing variability imprinting processes on Labrador Sea Water (LSW) and the lower North Atlantic Deep Water (LNADW)?

Figure 2: Transport time-series of observations at 53°N, already published in Zantopp et al. [2017] with overlaid low pass filtered model transports of LSW (top) and LNADW (bottom).

In both model and observations the low pass filtered time series are less correlated than the high frequency containing raw transport signal. This could be interpreted as reproduction of low frequency variability imprinting processes that are reproduced by the model. 

But pursuing a PhD in Physical Oceanography does not only include programming and working on data in an office, it is also hands on ship work. Hence I was also able to gain some subpolar and Labrador Sea experience during the cruise MSM54 from St. Johns to Reykjavik from mid May to June 2016. On this cruise I could see and experience the Labrador Sea. We exchanged the mooring array at 53°N and did a high resolution hydrographic survey to maintain the high quality and dense coverage of data in the Labrador Sea. Furthermore moorings in the central Labrador Sea, Irminger Sea and near the west Greenland shelf break where renewed. Knowing what the problems and powers of observational oceanography in this region are is helping me a lot in understanding challenges in my model – observation comparison process.

My current work focuses on the low frequency variability in the model and the observations. Some of the exciting findings will be published soon.

The processes causing this variability are still subject to ongoing research.

Bibliography

Behrens, E. (2013), The oceanic response to Greenland melting: the effect of increasing model resolution, Kiel, Christian-Albrechts-Universität, Diss., 2013.

Böning, C. W., E. Behrens, A. Biastoch, K. Getzlaff, and J. L. Bamber (2016), Emerging impact of Greenland meltwater on deepwater formation in the North Atlantic Ocean, Nature Geoscience.

Fischer, J., M. Visbeck, R. Zantopp, and N. Nunes (2010), Interannual to decadal variability of outflow from the Labrador Sea, Geophysical Research Letters, 37(24).

Zantopp, R., J. Fischer, M. Visbeck, and J. Karstensen (2017), From interannual to decadal—17 years of boundary current transports at the exit of the Labrador Sea, Journal of Geophysical Research: Oceans.

Posted in Student/Postdoc Blog

Observed southward spreading of the Iceland Scotland Overflow Water along the eastern flank of the Mid-Atlantic Ridge

by Sijia Zou

In the past a few months, I have been working on identifying the spreading pathways of Iceland Scotland Overflow Water (ISOW) in the eastern North Atlantic, with focus on its southward spreading along the eastern flank of the Mid-Atlantic Ridge (MAR).

The ISOW is formed in the Nordic Seas and overflows into the Iceland basin over the sill between Iceland and Scotland. Together with the Denmark Strait Overflow Water (DSOW) that overflows via the sill in Denmark Strait, and the Labrador Sea Water (LSW) formed in the Labrador Sea, these deep waters make up the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). An understanding of the spreading pathways of these deep water masses is fundamental to our understanding of AMOC structure.

Traditionally, the Deep Western Boundary Current (DWBC) was considered the major conduit from the subpolar to the subtropical gyre for these deep water masses: ISOW travels cyclonically in the Iceland basin within the DWBC, enters the western subpolar gyre via the Charlie-Gibbs Fracture Zone (CGFZ) (see Figure 1, solid blue curve) and joins the DSOW and LSW in the DWBC in the western basin.

However, recent studies question the DWBC’s representativeness of the lower limb of the AMOC. In the western North Atlantic, where all the three deep water masses are present, Lagrangian floats and model simulations reveal interior pathways of the deep waters from the subpolar gyre to the subtropical gyre (Bower et al., 2009; Gary et al., 2012; Lozier et al., 2013; Gary et al., 2011; Lavender et al., 2005; Xu et al., 2015). In the eastern North Atlantic, where ISOW is the primary deep water, two other ISOW pathways are identified (see Figure 1, dashed red curves): one crosses gaps in the Reykjanes Ridge (RR) north of the CGFZ (Xu et al., 2010; Chang et al., 2009), and the other flows southward along the eastern flank of the MAR into the Western European Basin (Xu et al., 2010; Lankhorst and Zenk, 2006). These two pathways are less well studied or observed.

Figure 1. A schematic plot of ISOW major spreading pathways. Abbreviated letters are: Iceland Faroe Ridge (IFR); Faroe-Shetland Channel (FSC); Faroe Bank Channel (FBC); Reykjanes Ridge (RR); Wyville-Thomson Ridge (WTR); Rockall Trough (RT); Rockall Plateau (RP); Porcupine Bank (PB); Bight Fracture Zone (BFZ); Charlie Gibbs Fracture Zone (CGFZ). Mooring locations are shown as black diamonds. CTD section is shown as a black dashed line.

To study the southward spreading of the ISOW east of the MAR, I have been using previously unpublished current meter data east of the CGFZ from Dr. Walter Zenk at GEOMAR in Germany. The moorings C, G, F, Z, M, A, R and T (labeled in white in Figure 1), were deployed between 1998 and 1999 and stayed in water for 1 year.

Figure 2 (left) shows the mean velocity at mooring locations at current meter depths between 1650 and 3890m. The deep-reaching northeastward North Atlantic Current is observed at moorings G, F and Z. A bottom-intensified southward flow is observed at mooring R, with a maximum southward velocity 8 cm/s measured by the bottom current meter at 3967 dbar. This strong southward spreading is in the salty ISOW layer, as shown in the hydrographic section from the CTD section (Figure 2, right) in June 1999, when moorings M, A, R and T were recovered. A similar southward spreading of deep waters in the ISOW layer is seen from the velocity fields in a high resolution model (1/12°) FLAME, with overall weaker magnitude and strong interannual variability (not shown).

A manuscript with these results is in preparation. In the manuscript, detailed analysis of this southward branch is conducted, including the spreading from a Lagrangian perspective, the origin of the south-flowing deep waters and a quantification of different branches of ISOW pathways in the eastern North Atlantic. In addition, the RAFOS floats released east of the RR at ISOW depths during the OSNAP cruise in the summer of 2014 will provide further evidence of the various spreading of ISOW. 

This analysis work is completed with my advisor Susan Lozier, Walter Zenk, Bill Johns from University of Miami and Amy Bower from WHOI.

Figure 2. (Top) Mean velocities at the depths of all current meters for moorings C, G, F, Z, M, A, R and T (black diamonds). Moorings C, G, F and Z were deployed on June 25 1999 and recovered on July 1 2000. Moorings M, A, R and T were deployed on August 9 1998 and recovered on June 16 1999. All current meters are located between 1650 and 3890 dbar. The CTD section was shown as black dashed line. (Bottom) Observed salinity in June 1999 east of the MAR (~51.5°N) from the CTD stations shown in the left panel. The longitudes of the moorings M, A, R and T are shown as black circles. The Isopycnals are shown in dashed gray.

 

Posted in News

Los mares de mi vida (The seas of my life)

By Yarisbel Garcia Quintana

I have been close to the ocean since I can remember. I grew up surrounded by it, in an island rooted in between the Caribbean Sea, and the Gulf of Mexico: Cuba. The summer trips to the beach were all that I waited for during the classes period. I still remember the first time I saw it, and wondered where all that blue ended.

Years passed and even when I graduated from Meteorology, I found myself working by the sea. And when I say by the sea, I mean door, 5 steps, sand, and water. From time to time hurricanes strike the island. The Centre of Environmental Services of Matanzas, where I worked, is in charge of monitoring the erosion of the beaches in Matanzas (Province of Cuba) suffer as a consequence of storms and sea level rise. Due to erosion, projects for the artificial regeneration of the beach are regularly needed. A better planning of these projects includes an in-depth study of the near shore ocean currents involved in the transport of the sediments that feed the dune system. This studies lead me to my Master degree research: studying ocean currents of the Gulf of Valence, Spain. 

Thanks to my Master’s research I got the opportunity to explored some of the seas surrounding the Spanish peninsula, where my main role was to be in charge of the ADCP measuring and data post-processing. I had the chance to be on board of vessels like Garcia del Cid (Figure 1), Odon de Buen (Figure 2), and Sarmiento de Gamboa (Figure 3). Every time the cruise was confined to the coast of Valence, within the Mediterranean Sea. I found the Mediterranean to be very predictable, changing mostly with the seasons and not much within the day.  The Cantabrian Sea, north of the peninsula, was different story. Still like ice in the morning, but changing rapidly after noon following the change in the wind pattern, making almost impossible the recovery of sediment samples from the ocean floor, due to bad sea conditions. On board of the CIMA Oceanografico (Figure 4) I participated in a cruise around the Canary Island, to determine the ocean currents affecting the dune system of Maspalomas. I will never forget that experience. I will always remember when, following my colleagues, I jumped into the water for a swim, without knowing that a prominent feature of the Canary Current, is the presence of upwelling, resulting in a colder swimming than I expected.  

Now, as a PhD student at the University of Alberta, in Edmonton and far from the sea, I use a coupled ocean-sea ice numerical model to keep in touch with the ocean. I have been using four different numerical experiments to investigate the sensitivity on the Labrador Sea Water formation rate, and the AMOC strength, to (i) model resolution, (ii) Greenland melt increase, (iii) a decrease in the high frequency atmospheric phenomena, and (iv) an increase in the precipitation.  But this does not mean that I get to be in front of the computer all the time. In 2015, I participated in a Floating University organized by the ArcTrain program, on board of the Polarstern (Figure 5). Leaving from Svalbard, and into the Nordic Seas and a glimpse of the Arctic Ocean, it was the perfect experience that introduced me to the Arctic and Sub-Arctic Oceans. No, this time I did not jump.

Next experience will be on board of the Research Vessel Maria S. Merian, from Southampton, UK, to St. John’s, Canada. I cannot be exited enough for this new adventure. I am looking forward to it, and not just because they have an amazing chef on board, but because I will have again the honour to be at sea, learn from it, and from lots of brilliant people which during 28 days, I will have the chance to call colleagues.

 

Figure 1: Research/Survey Vessel Garcia del Cid. (photo credit: me)

Figure 2: Terns (charran in Spanish) on board of the Research Vessel Odon de Buen. (photo credit: me)

Figure 3: Sun set from the Research Vessel Sarmiento de Gamboa. (photo credit: me)

Figure 4: Research Vessel CIMA Oceanografico, somewhere near the Canary Island. (photo credit: me)

Figure 5: Tea on the Polartern while in Fram Strait. Red blob on the left is my self, red blob on the right PhD student Laura Gillard. (photo credit: Mathilde Jutras)

 

 

Posted in News

The AMOC and the AMO

Nick Foukal

For the past few months I have been working on an independent study with my advisor, Susan Lozier, researching the connection between the Atlantic Meridional Overturning Circulation (AMOC) and the Atlantic Multidecadal Oscillation (AMO). As the first part of this project, I conducted a literature review and in this post I would like to discuss the current state of the field.

But first a quick explanation of the AMO. The AMO is the average sea-surface temperature (SST) over the entire North Atlantic after the long-term warming trend is removed. In reconstructions of North Atlantic SST from the mid-1800s to present, the basin-wide mean time series appears to oscillate with a period of 60-80 years with warm periods in the late 1800s, 1920s to 1960s, and the 1990s to the present, and cold periods in between (Fig. 1). Some prefer to refer to this oscillation as “variability” because the 60-80 year period of the AMO is at the very edge of detection by direct measurements so “AMO” and “AMV” are used interchangeably in the literature.

Figure 1. The AMO from the NOAA Extended Reconstructed Sea Surface Temperature (ERSST) version 4 (1856-2016). The globally-averaged SST time series (black dashed) is subtracted from the local North Atlantic SST (area-weighted average shown in black solid line) to yield the detrended North Atlantic SST, which is then spatially averaged to derive the AMO (red thin). A 10 year low-pass filter is used to analyze low-frequency variability (red thick). The official NOAA AMO index (Trenberth and Shea, 2006; red dashed) is shown for comparison. In the top panel, the map of linear regressions between the local SST and the annual AMO demonstrate the spatial signature of the AMO. All regressions shown have p-values less than 0.05.

 

The AMOC has long been connected to North Atlantic SST in the paleoceanographic literature (which relies on ocean sediment cores for proxy-based SST reconstructions) because an increase in the AMOC would increase the oceanic heat transport and thus warm the SST. But within the shorter time-scale field of observational physical oceanography (which relies on observations of SST from ships, autonomous instruments and satellites among other platforms), there are multiple different SST forcing mechanisms to consider, including air-sea heat fluxes, vertical mixing and horizontal heat flux convergences/divergences. Though the AMOC may indirectly affect all of these terms, only this last term can be directly forced by variations in the AMOC. So the AMO lies in an interesting area between paleoceanography and observational physical oceanography – this middle ground is one of the many reasons why there is still ample confusion with the AMO and its forcing mechanisms.

Both the time scale (60-80 years) and the spatial signal (coherent across the entire North Atlantic, Fig. 1) is perplexing to oceanographers. The most logical forcing would be from the winds – the global wind patterns are responsible for most features in large-scale ocean circulation. But the dominant wind pattern in the North Atlantic, the westerly winds, bisect the North Atlantic around 45°N into the subtropical and subpolar gyres. Thus forcing by the westerly winds would cause opposing forcing in the two gyres, a feature that is captured by the North Atlantic Oscillation (NAO, Fig. 2) but cannot explain the basin-wide nature of the AMO. Another potential forcing mechanism is the AMOC – the AMOC redistributes heat meridionally so it could theoretically explain spatial pattern of the AMO. Zhang and Zhang (2015) posit that a southward-propagating positive AMOC anomaly leads to convergences of horizontal heat flux in the upper ocean that can explain the AMO north of 34°N. South of that latitude, the AMOC anomaly propagates quickly as a wave rather than an advective signal, so it no longer leads to heat convergences along its path. This explanation is consistent with the long-held belief of paleoceanographers that the AMOC is controlling the extra-tropical SST variability (albeit through a slightly different mechanism) but it doesn’t explain the AMO impact in the tropical North Atlantic. To explain that, a number of papers have used models and historical observations of low-level clouds (Bellomo et al., 2016; Brown et al., 2016; Yuan et al., 2016). Very simplistically, low clouds tend to cool a region because they reflect more radiation back out to space than they trap through their greenhouse effect (high clouds do the opposite – they trap more radiation than they reflect). These papers show that low frequency variability of low clouds in the tropical Atlantic varies negatively with respect to the AMO – so there are a lot of low-level clouds during cool AMO phases and few clouds during warm AMO phases, indicating that the presence of clouds could be forcing the tropical AMO signal. Taken together, these results point to concurrent AMOC anomalies in the northern portion of the study area and low level clouds in the southern portion forcing the AMO.

Figure 2. The official NOAA winter NAO index (1864-2016) and its spatial pattern. Linear regression coefficients between detrended ERSST and the annual NAO index (thin black). A 10 year low-pass filter (thick black) is applied to compare the NAO to the AMO at low frequencies. In the top panel, regressions with p-values less than 0.05 are outlined in black contours.

These explanations all assume that the AMO requires a physical forcing mechanism – an assumption that is challenged by Clement et al. [2015]. This paper demonstrates that the AMO can be recreated by slab ocean models in which the ocean is idealized as a constant (in time) depth slab of water and has no interannual variability in ocean heat transport. So in these simulations, vertical mixing and changes in horizontal heat transport cannot force the interannual variability in the AMO. Instead, the authors suggest that the AMO is simply noise with a peak in multidecadal frequencies (Fig. 3) arising from a combination of oceanic memory and random atmospheric forcing. This result has raised many questions with perhaps the most pertinent to OSNAP being how can the AMOC, with its associated heat transport variability at the RAPID line on the order of petawatts (Johns et al., 2011; 1 PW = 10^15 W = 100*global energy consumption), not influence the AMO? Results from the RAPID line, for example, have shown that upper ocean heat content in the northern subtropical gyre (26°N-42°N) decreased in response to a slowdown of the AMOC at the RAPID line in 2010 (Cunningham et al., 2013). One would assume that this also cooled the SST in this region. But does a cooling of the northern subtropical gyre lead to a basin-wide SST signal on multidecadal time scales? Does the AMOC even vary on multidecadal time scales? If the advective time scale of the upper limb of the AMOC (the time water particles take to go from the equator to the subpolar gyre) is on the order of 10-20 years, what would cause oscillations in the AMOC at 60-80 year periods? Some have posited that the strength of the Agulhas leakage from the Indian to the Atlantic Ocean may be forcing these changes (Biastoch et al. 2015), but a link this far afield may need more evidence for it to catch on.

 

Figure 3. Fourier spectra of the AMO (1854-2016). The peak value occurs at a period of 81 years so the time series (Fig. 1) shows exactly two cycles. The resolution of Fourier analysis becomes coarser as the period increases, so the location of the peak at long periods is difficult to determine exactly, but probably lies on the shorter end of the range between 54 years and 162 years.

The connection between the AMOC and the AMO is important to OSNAP because the AMO has been connected to Atlantic hurricane activity (e.g. Knight et al., 2006), North American and European climate (Trenberth and Shea, 2006; Sutton and Hodson, 2007), Sahel and Amazonian rainfall (Folland et al., 1986; Knight et al., 2006), Arctic sea ice extent (e.g. Zhang, 2015), and global temperature (e.g. Brown et al., 2015). If indeed the AMOC is forcing the AMO, then measurements like OSNAP become even more important and may even provide some long-sought after predictability in the climate system.

References
Bellomo, K. et al. (2016). New observational evidence for a positive cloud feedback that amplifies the Atlantic Multidecadal Oscillation, GRL, 43, 9852-9859.

Biastoch, A., et al. (2015) Atlantic multi-decadal oscillation covaries with Agulhas leakage. Nat. Comms., 6:10082.

Brown, P. T. et al. (2015), Regions of significant influence on unforced global mean surface air temperature variability in climate models, JGR, 120, 2, 480-494.

Brown, P. T. et al. (2016), The necessity of cloud feedback for a basin-scale Atlantic Multidecadal Oscillation, GRL, 43, 3955-3963.

Clement, A. et al. (2015). The Atlantic Multidecadal Oscillation without a role for ocean circulation, Science, 350, 6258, 320-324.

Cunningham, S. et al. (2013) Atlantic Meridional Overturning Circulation slowdown cooled the subtropical ocean, GRL, 40, 6202-6207.

Folland, C. K. et al. (1986) Sahel rainfall and worldwide sea temperatures, 1901-85, Nature, 320, 6063, 602-607.

Johns, W. E. et al. (2011) Continuous, array-based estimates of Atlantic Ocean heat transport, Journal of Climate, 24, 2429-2449.

Knight, J. R. et al. (2006) Climate impacts of the Atlantic Multidecadal Oscillation, GRL, 33, L17706.

Sutton, R. T. and Hodson, D. L. R. (2007) Climate response to basin-scale warming and cooling of the North Atlantic Ocean. Journal of Climate, 20, 891-907.

Trenberth, K. E. and Shea, D. J. (2006) Atlantic hurricanes and natural variability in 2005. GRL, 33, L12704.

Yuan, T. et al. (2016) Positive low cloud and dust feedbacks amplify tropical North Atlantic Multidecadal Oscillation, GRL, 43, 1349-1356.

Zhang, J. and Zhang, R. (2015) On the evolution of the Atlantic Meridional Overturning Circulation Fingerprint and implications for decadal predictability in the North Atlantic, GRL, 42, 5419-5426.

Zhang, R. (2015) Mechanisms of low frequency variability of summer Arctic sea ice extent, PNAS, 112, 15, 4570-4575.

Posted in News

What’s an inverse model?

By Neill Mackay

One of the challenges in oceanography is that taking observations is expensive and time-consuming, and while the observations we do make are essential to our understanding, it is only possible to observe a tiny fraction of the vast history of the ocean in time and space. We turn to models to try to fill in the blanks, and my work as a post-doc at the National Oceanography Centre in Liverpool makes use of a particular type of model called an inverse model.

With the usual sort of ocean model, or ‘forward model’, we take an initial guess at the state of the ocean and set of physical laws and press ‘play’, and the model runs forwards in time, producing outputs for some later point which can be compared with the real ocean observations. The difficulty is in choosing the initial state which results in a good fit between the model output and the observations. Various parameters, such as mixing rate – how fast or slowly water with different properties becomes homogenised in the ocean – might be adjusted within the model to improve the fit. An inverse model is kind of a backwards model, as we start with the observations, apply the same set (or a subset) of physical laws and obtain the desired parameters as outputs. These parameters can then tell us something useful about a particular region of the ocean we are studying.

In OSNAP, the mooring arrays will provide a set of continuous observations along a section over a period of years. The inverse model we are developing, called the Regional Thermohaline Inverse Model or ‘RTHIM’ for short, will help to provide some context for the mooring observations by telling us something about what happens in the region to the north of the section (i.e. within the Subpolar Gyre), and also what may have happened over a longer time period before the observations started. RTHIM makes use of all the available historical observations of the region from satellites, automated floats and oceanographic surveys, going back more than 25 years. It works on the principle that the temperature and salinity (saltiness) of the water in the region (the ‘Thermohaline’ bit) changes either when water flows in or out of the region from the rest of the ocean; or when heat or freshwater is transferred through the ocean surface (e.g. through cooling by the winds or rainfall, respectively); or when different types of water are mixed together in the interior. Making use of this balance, RTHIM allows us to work out the flow of different waters into and out of the Subpolar Gyre, and the rates of mixing within it, without using the OSNAP array observations. We can then compare our inverse solution with the observations, and in addition we can find solutions for a time before the OSNAP mooring arrays were deployed. This means that variability measured by the OSNAP array over time, for example of the flow into and out of the Subpolar Gyre, can be put in context. Importantly then we can start to tease out where observed changes are due to natural variability, and where they are part of a trend – such as one related to man-made climate change.

Figure 1: Velocities on the section from an RTHIM solution. The inverse model was applied to the whole of the Arctic, bounded by a line of latitude at 65°N, which is somewhat north of the OSNAP array (only part of the section in longitude is plotted). Red (positive) regions of the plot indicate flow into the Arctic (i.e. northward) and blue (negative) regions indicate flow out of the Arctic (i.e. southward). RTHIM will eventually be applied using a section which coincides with the OSNAP array, to allow a direct comparison with the observations.

Figure 1: Velocities on the section from an RTHIM solution. The inverse model was applied to the whole of the Arctic, bounded by a line of latitude at 65°N, which is somewhat north of the OSNAP array (only part of the section in longitude is plotted). Red (positive) regions of the plot indicate flow into the Arctic (i.e. northward) and blue (negative) regions indicate flow out of the Arctic (i.e. southward). RTHIM will eventually be applied using a section which coincides with the OSNAP array, to allow a direct comparison with the observations.

 

Posted in Student/Postdoc Blog

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