Crossing the deep convective regions in the North Atlantic

by Sijia Zou

MSM_Mooring launch locations

Figure 1: Mooring launch locations (white squares at 53N array, the central Labrador Sea and west Irminger Sea) and CTD stations (small yellow squares). This picture is from Johannes Karstensen (chief scientist of the cruise) with permission.

Another promising year for measuring Atlantic Meridional Overturning Circulation starts with cruise Maria S. Merian 54 (MSM 54), which departed St. John’s, Canada on 12th May and will end on 7th June in Reykjavik, Iceland. During this cruise, we will deploy seven moorings at the exit of the Labrador Sea near 53N, and two deep ones at the entrance near the west Greenland coast (Figure 1, right). These moorings serve to measure the magnitude and variability of the deep western boundary current as well as the connection of deep layer transport between entrance and exit of the Labrador Sea. Besides, direct measurements of the convective activity will be accomplished with mooring deployments in the central Labrador Sea (K1 and SeaCycler) and the central Irminger Sea (CIS). These observations will collectively contribute to our understanding of how the boundary current (both strength and property) varies with time, and the how these changes are related to the convections.

Along the cruise, we will be conducting 90 CTD casts, crossing the Labrador Sea and west Irminger Sea. We are excited to expect a thick, cold and fresh Labrador Sea Water layer comparable to the ever-observed deepest convection in 1994.

Now we have been at sea for 5 days. The weather was not as good as what I have hoped: it was windy and cold during the first 3 days and got foggy afterwards. Hopefully the weather is getting better so that we can have everything progressed as scheduled.

Just BTW: Food is great on MSM (Figure 2). People are nice (Figure 2). I wish I could speak some German.

MSM_port of St. Johns

At the port of St. Johns, Canada on May 12th before cruise started. by Sijia Zou

MSM_students

With two other students (Christina Schmidt on the left and Patricia Handmann on the right) from GEOMAR (photo credit to Marilena Oltmanns). The flying hair in this photo tells you how important it is to wear a hat on the ship.

) One of the great dinners on board (half chicken!!).

One of the great dinners on board (half chicken!!).

Posted in Cruises

Thursday 12.05. – Saturday 14.05.16

by Amelie Klein

MSM_crew

After some small highlights like supposed explosives in Mareike’s notebook and an unexpected upgrade to Premium Economy for some of us, we arrived at St. John’s. Thanks to the early flight an the time shift we had enough time to discover the town of St. John’s after the check in in the hotel where we stayed during the first night.

First of all, we said hello at the Merian and went on a small (and quite windy) tour to Signal Hill, from which you have a great view over the harbor and which became popular as Marconi received the first transatlantic radio signal here in 1901. In the evening we went to the city center and enjoyed dinner in a nice Canadian restaurant. The colorful houses and open-minded and witty people make up the great flair of St. John’s.

On Thursday we moved into our cabins at the Merian, which will be our home for the next weeks. After last preparations for the

Wiebke clothed in a survival suit  (Photograph by Johannes Karstensen)

Wiebke clothed in a survival suit
(Photograph by Johannes Karstensen)

cruise and refueling there was the official welcoming by the crew and the security instructions. In the afternoon the Maria S. Merian then left the harbor and after the successfully mastered security exercises during which the most of us entered a rescue boat for the first time, we were introduced to our tasks on the ship. In the evening the first CTD measurement was carried out.

The next day was transit to the next station an actually for most of us this day (Friday) can be summed up in two words: Sea sick or tired due to the anti-sickness pills.

Saturday morning most guys had recovered and after breakfast we spotted the first icebergs, becoming bigger and more the farther we traveled on.

The first icebergs (Photographs: Nora Fried)

The first icebergs (Photographs: Nora Fried)

The first icebergs (Photographs: Nora Fried)

The first icebergs (Photographs: Nora Fried)

Posted in News

Taking part in Maria S Merians long, long journey through the Atlantic Ocean and beyond

by Johannes Karstensen, chiefscientist MSM54 expeditionMSM53

 The ocean-class German research ships are rarely seen in Germany. They follow a route that is composed by many individual expeditions and converting the ships travel into a long, long journey; for Maria S Merian this journey takes place primarily in the North Atlantic and it transition into the Arctic Ocean. As a consequence – the scientists have to travel to where the ship is and have to bring with them (again by ship, but container ships) the equipment that is needed for the experiments to be performed at sea.

Without equipment brought by the scientists the Maria S Merian is not at all an empty ship – she carries a lot of equipment, required by almost all groups that make use of the ship, such as cranes, work shops, communication devices, instrumentation. However, most important – the ship is manned with a skilled, experienced and simply great crew, providing all support to not only conduct experiments at sea but to find a comfortable atmosphere which makes life at sea easy for us, the non-seamen.

In the last ten years I have been six times to St. Johns, Canada – all times to enter a ship (two times the Maria S Merian) for expeditions to the Labrador Sea. Typically I arrive 3 to 4 days before the cruise starts, just to be here when the ship arrives and to help loading and setting up equipment. The arrival of the ship is always special; for example people often eagerly wait to be back to shore, leaving the steadily moving platform behind – but to discover that the movement continues even on land for the next couple of days. St. Johns is a convenient harbour for us, just 1.5 days transit to one of our main working areas (the “53°N array”) – but it is also a nice little town settled around a large natural harbour bay.

BatteryPark_Karstensen

Caption: View from Battery Park on St. Johns harbour. The two research ships (easy to identify by the “A” formed crane mounted at the stern, are the Irish Celtic Explorer (keft) and the German Maria S. Merian (right). credit: J. Karstensen

We, a science crew of 20 people, need for the installations and experiments planned during this trip (called MSM54) an amount of material that came in 7 containers. We fixed 4 containers to the ships deck but the rest of the material is now distributed in the labs.

The science crew is composed of five people from Canada’s Dalhousie University, one person from Duke University in the US, and 14 persons from GEOMAR in Germany. We are a mix of students (9), from PhD to BSc, technicians (7), and full scientists (4). A lot of the work that will be done is very technical – installing quite heavy equipment that ultimately serves us to conduct our experiments at sea generating data that is of use for our scientific investigations. What we are really after is to better understand how our ocean regulates climate – for example by taking up heat and other substances in specific regions, such as the Labrador Sea, where large amounts of near surface water sink to sometime deeper than 2000m depth, and from where it spreads far into the ocean interior.

What regulates the sinking process and how does the water spread in the ocean interior are some of the questions we want to answer. The 53°N-Array has been first installed in 1997, long before I came to Kiel to work in this region. It is a unique time series not only because it is operational since so long, but because it has been well designed from the beginning. Setting up a time series has similarities in buying a house – the only thing that matters is the location!

On this trip we will recovery many instruments that were installed during the last service of the array in 2014. For that cruise we started, guess where? – in St. Johns, correct! but on the French Research Vessel NO Thalassa. Not only the two of us who participated in the Thalassa expedition are now very excited to see how well the instrumentation had worked over the last two years. In 2018 we plan to come to the Labrador Sea again to service the “53°N-Array” – and I hope I can one more time join the long, long journey of the RV Maria S Merian.

Johannes_C.Schmidt

Credit: C. Schmidt

 

Posted in Cruises

OSNAP at EGU 2016

Session OS1.4 The North Atlantic: natural variability and global change
Tuesday (08:00-19:30)

Laura de Steur and Femke de Jong
EGU2016-9380
Variability in the Irminger Sea: new results from continuous ocean measurements between 2014-2015

Helen Pillar, Patrick Heimbach, Helen Johnson and David Marshall
EGU2016-13947
Dynamical Attribution of Recent Variability in Atlantic Overturning

 

Posted in News

OSNAP at Ocean Sciences 2016

Talks

Monday, 22 February

Neill Mackay
03:15-03:30 PM
Room 228-230
PO13E-06: Circulation and mixing in the subpolar North Atlantic diagnosed from climatology using a Regional Thermohaline Inverse Method (RTHIM)

The Overturning in the Subpolar North Atlantic Program (OSNAP) aims to quantify the subpolar Atlantic Meridional Overturning Circulation (AMOC), including associated advective and diffusive transport of heat and freshwater. The OSNAP observational array will provide a continuous subpolar record of the AMOC from Labrador-Greenland-Scotland during 2014-2018. To understand the significance of high- and low- frequency changes measured by the array, including changes to AMOC metrics, water mass transformation and transports, Argo observations provide a useful complementary constraint for an inverse method, with the aim of resolving intra-seasonal timescales.

A novel inverse method in thermohaline coordinates has recently been demonstrated as being able to diagnose aspects of the global overturning circulation and mixing from model data. Here we have further developed a Regional Thermohaline Inverse Method, (RTHIM) and have validated it with the NEMO model in the OSNAP region, before applying it to a seasonal Argo climatology.

In an ocean basin there exists a balance between surface heat and freshwater fluxes, advective fluxes at an open boundary and interior diffusive mixing. RTHIM makes use of this balance to determine unknown velocities at the open boundary and diffusive fluxes of heat and salt within the domain volume. We identify key transport and mixing regions and events, relevant to the subpolar AMOC, and discuss the robustness of the inverse solutions. RTHIM is also able to identify the particular contributions to AMOC volume transport changes from temperature and salinity components.

Tuesday, 23 February

Susan Lozier
Plenary lecture
10:30–11:30 AM
Great Hall A&B
A Decade after The Day After Tomorrow: Our Current Understanding of the Ocean’s Overturning Circulation

In 1800 Count Rumford ascertained the ocean’s meridional overturning circulation from a single profile of ocean temperature constructed with the use of a rope, a wooden bucket and a rudimentary thermometer. Over two centuries later, data from floats, gliders and moorings deployed across the North Atlantic has transformed our understanding of the temporal and spatial variability of the meridional overturning: the component of the climate system responsible for sequestering heat and anthropogenic carbon dioxide in the deep ocean. In this talk I will review our current understanding of the overturning circulation with a particular focus on what we currently do and don’t understand about the mechanisms controlling its temporal change.

Thursday, February 25, 2016

Ric Williams
08:00-08:15 AM
Rooms 211-213
PC41A-01 Climate sensitivity to ocean sequestration of heat and carbon.

Ocean ventilation is a crucial process leading to heat and anthropogenic carbon being sequestered from the atmosphere. The rate by which the global ocean sequesters heat and carbon has a profound effect on the transient global warming. This climate response is empirically defined in terms of a climate index, the transient climate response to emissions (TCRE). Here, we provide a theoretical framework to understand how the TCRE can be interpreted in terms of a product of three differential terms: the dependence of surface warming on radiative forcing, the fractional radiative forcing contribution from atmospheric CO2 and the dependence of radiative forcing from atmospheric CO2 on cumulative carbon emissions. This framework is used to diagnose two models, an Earth System Model of Intermediate Complexity, configured as an idealised coupled atmosphere and ocean, and an IPCC-class Earth System Model. In both models, the centennial trends in the TCRE are controlled by the response of the ocean, which acts to sequester both heat and carbon; there is a decrease in the dependence of radiative forcing from CO2 on carbon emissions, which is partly compensated by an increase in the dependence of surface warming on radiative forcing. On decadal timescales, there are larger changes in the TCRE due to changes in ocean heat uptake and changes in non-CO2 radiative forcing linked to other greenhouse gases and aerosols. Our framework may be used to interpret the response of different climate models and used to provide traceability between simple and complex climate models.

Helen Johnson
08:45 – 09:00am
Rooms 203-205
PO41A-04 Dynamical Attribution of Recent Variability in Atlantic Overturning

Attributing observed variability of the Atlantic Meridional Overturning Circulation (AMOC) to past changes in surface forcing is challenging but essential for detecting any influence of anthropogenic forcing and reducing uncertainty in future climate predictions. Here we obtain quantitative estimates of wind and buoyancy-driven AMOC variations at 25◦N by projecting observed atmospheric anomalies onto model-based dynamical patterns of AMOC sensitivity to surface wind, thermal and freshwater forcing over the preceding 15 years. We show that local wind forcing dominates AMOC variability on short timescales, whereas subpolar heat fluxes dominate on decadal timescales. The reconstructed transport time series successfully reproduces most of the interannual variability observed by the RAPID-MOCHA array. However, the apparent decadal trend in the RAPID-MOCHA time series is not captured, requiring improved model representation of ocean adjustment to subpolar heat fluxes over at least the past two decades, and highlighting the importance of sustained monitoring of the high latitude North Atlantic.

Patricia Handmann et al
09:30 – 09:45 AM
Rooms 203-205
PO41A-07 North Atlantic Deep Western Boundary Current Dynamics as Simulated by the VIKING20 Model Compared with Labrador Sea Observations

The connection of dynamic and hydrographic properties simulated by the VIKING20 model driven by CORE2 atmospheric forcing will be presented and 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, implemented by two-way nesting in a global configuration of the NEMO-LIM2 ocean-sea ice model in the North Atlantic (ORCA25). The exit of the Labrador Sea is the place where water masses from different origins and pathways meet and which are collectively called North Atlantic Deep Water (NADW). The VIKING20 flow field on average reproduces the observed structure as well as the bottom intensification of the western boundary current at 53°N. Here, we investigate the properties of the observed and modeled deep western boundary current by comparing North Atlantic water masses and currents simulated by the high resolution model with moored and hydrographic data from almost 20 year-long observations at 53°N. As comparable density fields in the model in comparison to the observations are found at shallower depths, we will present an evaluation of dynamic and hydrographic changes connected to each other and to atmospheric forcing in the model and observed data. In addition the following key questions will be addressed: How is energy distributed in baroclinic and barotropic components in observations and model in comparison to each other? The seasonal cycle can be found in the shallow Labrador Current in the model and the observations, but how deep is it reaching and causing dynamic and hydrographic changes?

Stuart Cunningham et al
03:00 – 03:15 PM
Rooms 203-205
O43A-05: The Subpolar AMOC: Dynamic Response of the Horizontal and Overturning Circulations due to Ocean Heat Content Changes between 1990 and 2014

Ocean heat content (OHC) in the subpolar region of the North Atlantic varies on interannual to decadal timescales and with spatial variations between its sub-basins as large as the temporal variability. In 2014 the Overturning in the Subpolar North Atlantic Programme (OSNAP) installed a mooring array across the Labrador Sea and from Greenland to Scotland. The objective of the array is to measure volume, heat and fresh-water fluxes. By combining Argo and altimeter data for the period 1990 to 2014 we describe and quantify the anomalous horizontal and overturning circulations and fluxes of heat and fresh-water driven by the long-term OHC changes. We thus provide a longer-term context for the new observations being made as part of OSNAP. Changes to the horizontal circulation involve deceleration of the gyre rim currents, lateral shifts of major open ocean current features and increased exchanges in the eastern intergyre region. These changes impact the Atlantic Meridional Overturning Circulation (AMOC) in density space causing a rich vertical anomalous structure. The net impact over this 24 year period is a reduction in northward heat-flux and decrease in southward fresh-water flux.

Friday, February 26, 2016

Johannes Karstensen et al
03:00 – 03:15 PM
Rooms 203-205
PO53A-05: Observations and causes of hydrographic variability in den deep western boundary current at the exit of the Labrador Sea.

The hydrographic variability of the Deep Western Boundary Current (DWBC) in the Labrador Sea is discussed using observational data from the period 1997 to 2014. This variability of the DWBC occurs on time scales from a few days to multiannual. The hydrographic data is analyzed in terms of signals originating from different “behavioral modes” of the DWBC, including the re-positioning of the core along the sloping topography, the pulsing of the core, and the advection of watermass anomalies within the core. Cross-correlation spectra show that the hydrographic variability on time scales of a few days can be explained by the periodic re-location of the core due to topographic waves. Variability on longer time scales can be interpreted by long-term re-location of the core, potentially related to an adjustment of the core to circulation changes on gyre scale. However, along-flow advection of anomalies is likely another source for this long-term variability. Possible scenarios for the generation of hydrographic variability in the source regions of the DWBC are discussed.

Poster Presentations

Monday, February 22, 2016 04:00 PM – 06:00 PM
Ernest N. Morial Convention Center, Poster Hall

HE14B High Latitude Air-Sea-Ice Interactions  in a Changing Climate II Posters

Marilena Oltmanns et al
HE14B-1415: The Role of Local and Regional Atmospheric Forcing for Convection in the Subpolar North Atlantic
https://agu.confex.com/agu/os16/meetingapp.cgi/Paper/92491

Tuesday, February 22, 2016 04:00 PM – 06:00 PM
Ernest N. Morial Convention Center, Poster Hall

 PO24B: Mesoscale and Submesoscale Processes: Characterization, Dynamics, and Representation VI Posters

Chris Wilson 
PO24B-2949:
An Update to the ‘Barrier or Blender’ Model of the Gulf Stream, Based on Lagrangian Analysis of Aviso Altimetry.

Thursday, February 25, 2016 04:00 PM – 06:00 PM
Ernest N. Morial Convention Center, Poster Hall

PO44 Atlantic Meridional Overturning Circulation: Past, Present, and Future III Posters

Chun Zhou
PO44A-3118: Subpolar North Atlantic glider observations for OSNAP

Friday, February 26, 2016 04:00 PM – 06:00 PM
Ernest N. Morial Convention Center, Poster Hall

PO54A: Atlantic Meridional Overturning Circulation: Past, Present, and Future V Posters

Amy Bower
PO54A-3225: The Charlie-Gibbs Fracture Zone: A Crossroads of the Atlantic Meridional Overturning Circulation

Nicholas Foukal and Susan Lozier
PO54A-3229: Variability in Lagrangian-derived througput from the subtropical to the subpolar gyres in the North Atlantic and its impact on inter-gyre heat transport.

Penny Holliday
PO54A-3222: The AMOC and subpolar gyre circulation at the OSNAP section in summer 2014.

Ric Williams
PO44A-3130: Gyre-specific Ocean Heat Content Changes Controlled by the Meridional Overturning in the North Atlantic

Sijia Zou
PO54A-3224: Contradictory Pathways between Labrador Sea Water Advection and Property Propagation.

PO54B: Climate Trends, Hydrographic Variability, Circulation, and Air-Land-Sea Interactions in the Marginal Seas of the North Atlantic III Posters

Femke de Jong & Laura de Steur
PO54B-3241: Record deep convection in the Irminger Sea: Observations from the LOCO mooring during winter 2014-2015.

Laura de Steur & Femke de Jong
PO54B-3242: Transport variability of the Irminger Current: First year-round results from a mooring array on the Reykjanes Ridge.

Loïc Houpert
PO54B-3234: Glider Observations of the Properties, Circulation and Formation of Water Masses on the Rockall Plateau in the North Atlantic.

Virginie Thierry
PO54B-3239: Argo float observations of basin-scale deep convection in the Irminger Sea during winter 2011-2012.

Posted in News

Structure of currents and their transport in the eastern Subpolar North Atlantic

By Elizabeth Comer

As part of the OSNAP array, the Extended Ellett Line (EEL) is a repeat hydrographic section that crosses between Iceland and Scotland. This line measures part of the Atlantic Meridional Overturning Circulation in particular capturing the majority of warm water flowing northwards from the Atlantic into the Nordic Seas and around half of the returning cold deep water (Figure 1). The heat that is transported northwards is released along its journey transferring heat and moisture to the atmosphere. The amount of heat being carried determines how much is released, therefore making it an important factor in climate predictions. By making measurements along the EEL we can investigate the currents’ structure and long-term changes in heat and freshwater transport. The EEL provides the perfect platform for investigating the heat and freshwater changes over time through its yearly measurements over 40 years.

Figure 1. A schematic of the Atlantic Meridional Overturning Circulation (Curry and Mauritzen, 2005).

Figure 1. A schematic of the Atlantic Meridional Overturning Circulation (Curry and Mauritzen, 2005).

The EEL has measured velocity from the ocean’s full depth using an instrument called the Lowered-Acoustic Doppler Current Profiler (LADCP). This instrument is lowered through the water column and relies on the changes in return frequency of acoustic pulses to determine the water’s speed (Figure 2). The LADCP data is an exciting chance for us to see the in-situ velocity of the entire water column. Combining this velocity and hydrographic salinity and temperature measurements from each survey will provide the heat and freshwater transports across the EEL.

This is the research that I am currently carrying out and alongside this I will be taking part in the 2016 EEL research cruise, which requires being at sea for a month. So far, I have only been on weekly length research cruises so this will be a first and exciting experience for me. I am not only looking forward to collecting and processing my own data, but joining in with other scientists and learning new methods of data collection. Another first for me will be attending the Ocean Sciences Conference in New Orleans this February. This will be a great opportunity for me to meet researchers in my field, share experiences with other early career scientists and gain feedback on my research. These experiences will both not only enhance my learning, but build my confidence when explaining my research to different audiences.

Figure 2. This diagram shows what happens to the acoustic pulses when they reflect off of moving particles of water (https://www.whoi.edu/instruments/viewInstrument.do?id=819, Credit: Sontek)

Figure 2. This diagram shows what happens to the acoustic pulses when they reflect off of moving particles of water (https://www.whoi.edu/instruments/viewInstrument.do?id=819, Credit: Sontek)

Posted in News

Predicting the next 18 months of the AMOC at the RAPID line with a statistical model

by Nick Foukal, graduate student at Duke University

As the RAPID team prepares to release the next 18 months of AMOC measurements from the mooring array at 26°N, I have been busy building a statistical model to predict those observations. Statistical models extrapolate into the future using data on past states of the system and differ from physical models in that there is no dynamical constraint placed on the predictions. Whereas physical models might demonstrate how the AMOC responds to wind and air/sea buoyancy fluxes and build predictions based on that information, statistical models only need to know what the system has done in the past to predict the future. So in many ways, statistical models are not as useful as physical models; they cannot tell you why a system behaves the way it does, or how future changes to the environment may affect the system, but oftentimes statistical models can tell you the minimum amount of information you need to make accurate predictions.

Another useful trait of statistical models is that they provide a baseline metric from which to judge the performance of physical models. Weather forecasting is an example of this: until advances in computational capability and the advent of continuous satellite measurements improved the numerical weather forecasting models, the best-performing weather forecast models were statistical models. My goal in this project is to evaluate where oceanography is on the journey toward predictive skill: can physical models outperform a relatively simple statistical model in predicting the next 18 months of the AMOC?

State-space analysis is one of many ways to build a statistical model. The basic tenet of the state-space model that I use here is that the future state is a function of the current state. This type of state-space analysis also requires stationarity in the system, thus trends or oscillations with periods longer than the period of measurement must be removed. In addition, autocorrelation and known oscillations at periods shorter than the period of measurement should also be removed (if the oscillations are assumed to be stationary into the future) so that the state-space model can focus on the ‘unpredicted’ aspect of the data.

Given these requirements, I downloaded ten years of RAPID data (April 2004 – March 2014) at 12-hourly resolution, averaged the data to 10-day resolution due to the 10-day time scales of flow compensation between the upper and lower limbs of the AMOC as reported in Kanzow et al. [2007], calculated the integral auto-decorrelation time scale (36 days) and then averaged the data at 40-day resolution to produce a time series of independent observations. To remove the seasonal cycle, I calculated a continuous seasonal climatology (Fig. 1) by taking a 30-day running mean of the data padded with the December data at the beginning and the January data at the end. This padding ensured that the climatology was not biased by when the year began and ended and the running-mean ensured that the climatology was a continuous function rather than based on monthly means.

Figure 1. The climatological seasonal cycle of the RAPID AMOC data (2004-2014). The seasonal cycle has an amplitude of 4.68 Sv., RMSE of 2.98 Sv. and explains 24% of the variance in the data. The minimum occurs in March and there is a broad maximum from July through November.

Figure 1. The climatological seasonal cycle of the RAPID AMOC data (2004-2014). The seasonal cycle has an amplitude of 4.68 Sv., RMSE of 2.98 Sv. and explains 24% of the variance in the data. The minimum occurs in March and there is a broad maximum from July through November.

To analyze trends or oscillations beyond the study period, I fit the data with five models: a linear trend line, a step-function with the mean from April 2004 to April 2008 and the mean from May 2008 to March 2014 (based on results from Smeed et al. [2013]), two linear trend lines for the same time periods as the step function, a quadratic fit, and a sine curve. The fit with the lowest RMSE is the sine curve (Fig. 2).

Figure 2. The sine curve fit to the AMOC observations without the seasonal climatology. The sine curve has an amplitude of 2 Sv., period of 10.41 years and phase shift of 6.16 years. This sine function has the lowest RMSE (2.6 Sv.) when compared to a linear fit, a step function fit (2004-2008 and 2008-2014), a quadratic, and two linear fits (2004-2008 and 2008-2014). The maximum of the sine curve occurs at the end of October 2005 and the minimum occurs in early January 2011. The next maximum predicted by just this component is in the Spring of 2016 while the most recent inflection point occurred in mid-2013.

Figure 2. The sine curve fit to the AMOC observations without the seasonal climatology. The sine curve has an amplitude of 2 Sv., period of 10.41 years and phase shift of 6.16 years. This sine function has the lowest RMSE (2.6 Sv.) when compared to a linear fit, a step function fit (2004-2008 and 2008-2014), a quadratic, and two linear fits (2004-2008 and 2008-2014). The maximum of the sine curve occurs at the end of October 2005 and the minimum occurs in early January 2011. The next maximum predicted by just this component is in the Spring of 2016 while the most recent inflection point occurred in mid-2013.

To predict the AMOC signal that remained after the seasonal and long-term oscillations were removed, I fit the parameters of a state-space model to the ten years of anomalies (Fig. 3). The two parameters that require optimization are the number of dimensions and the number of nearest neighbors. Dimensions refers to the number of previous observations in time to use in the prediction, and the number of nearest neighbors refers to the number of time periods with similar AMOC variability (each consisting of the number of dimensions) to use. I tested models with zero to 25 dimensions and zero to 25 nearest neighbors by calculating each of the models’ RMSE when compared to the observations for the MOC observations from 2004-2014. The model with the lowest RMSE (2.46 Sv) has 10 dimensions (each prediction uses information from the past 400 days), and 14 nearest neighbors. The fact that the model needs just over one year of previous data implies that there may be residual seasonality that the seasonal climatology did not remove.

Figure 3. The state-space model fit to RAPID AMOC observations without the climatological seasonal and sinusoid cycles. The model uses 10 dimensions (400 days) and 14 nearest neighbors. State-space models with many nearest neighbors typically under-predict the amount of variance in the original data because the number of values that are averaged to create a prediction is too large.

Figure 3. The state-space model fit to RAPID AMOC observations without the climatological seasonal and sinusoid cycles. The model uses 10 dimensions (400 days) and 14 nearest neighbors. State-space models with many nearest neighbors typically under-predict the amount of variance in the original data because the number of values that are averaged to create a prediction is too large.

When the three components (seasonal cycle, long-term oscillation and state-space model) are combined (Fig. 4), they recreate 48.5% of the variability in the observations from 2004-2014 and have a cumulative RMSE of 2.46 Sv. In comparison, models with just the mean MOC (RMSE = 3.42 Sv. and 0% of variance), the climatological seasonal cycle (RMSE = 2.98 Sv. and 23% of variance) and the climatological seasonal cycle plus the long-term sinusoid (RMSE = 2.60 Sv. and 42.1% of variance), do not fit the data as well. The combined model also produces a prediction for the next 18 months of the AMOC (Fig. 4, blue). Of the 6.11 Sv. amplitude in the predicted values, over 75% is due to the seasonal cycle, with the increasing sine component (Fig. 2, blue) slightly compensated by the negative state-space component (Fig. 3, blue). The two peaks in the combined model’s prediction (Fig. 4, blue) of 20.28 Sv. and 20.14 Sv. occur in October 2014 and August 2015, respectively, and the trough of 16.06 Sv. occurs in February 2015.

Figure 4. A comparison of statistical models with predictions for the next two years of RAPID AMOC based on the model that combines the seasonal, long-term and state-space models. The average standard deviation for the next two years (blue shading) is +/- 2.4 Sv. The error does not diverge because it depicts the amount of spread in each individual prediction of the next time step provided that the previous prediction was accurate.

Figure 4. A comparison of statistical models with predictions for the next two years of RAPID AMOC based on the model that combines the seasonal, long-term and state-space models. The average standard deviation for the next two years (blue shading) is +/- 2.4 Sv. The error does not diverge because it depicts the amount of spread in each individual prediction of the next time step provided that the previous prediction was accurate.

 

References

Kanzow, T. et al. (2007) Observed Flow Compensation Associated with the MOC at 26.5°N in the Atlantic. Science, vol. 307, pp. 938-941.

Smeed, D. et al. (2013) Observed decline of the Atlantic Meridional Overturning Circulation 2004 to 2012. Ocean Science Discussions, vol. 10, pp. 1619-1645.

 

 

Posted in News

Ice, Wind & Fury

By Marilena Oltmanns

*This article was originally published in Oceanus magazine.

 

Dead silence falls over Tasiilaq.

Whatever mid-winter daylight appeared briefly in this village on the southeast coast of Greenland is long gone, leaving the afternoon pitch black. A fresh layer of snow from the morning covers the ground, reflecting the darkness around it. The vacuum of space is clear, and stars glint behind snow-covered mountains.

But any hint of pastoral calm is about to be obliterated.

The temperature has plummeted to -4° Fahrenheit and is still falling. Suddenly the wind picks up, and in an instant the silence vanishes. Village dogs start barking furiously. Icy gusts whistle through the spaces between the boards of wooden huts, a banshee-like warning of the bombardment to come from ice balls, rocks, untethered sleighs—anything that is unsecured.

By now, every creature in Tasiilaq knows: A piteraq is colliding with the town, and going outside into the elements would be suicide.

Torrential winds

During piteraqs, a torrent of cold air suddenly sweeps down off the Greenland ice cap and thunders down the steep slopes of ice-covered mountains, an avalanche of freezing winds that can reach hurricane intensity and flood everything in their path below. These rivers of air gain even more velocity as they converge and rush through narrow coastal fjords, the steep-sided inlets named by the Norsemen who made landfall here in the 10th century.

With more than 2,000 inhabitants, Tasiilaq is the seventh-largest town in Greenland and the most populous community on the eastern coast. The 1970 piteraq in Tasiilaq had wind gusts estimated at 160 miles per hour that savaged the town into near ruin. Not all piteraqs are as devastating as that one, but strong winds with speeds above 40 miles per hour can occur as frequently as 15 times per year. They haunt Tasiilaq in all seasons except summer.

There is one telltale sign that a piteraq is coming: The sky suddenly becomes clear—indicating that the wind has shifted direction and is now coming from the mountains and the vast Greenland Ice Sheet beyond. After the 1970 storm, Tasiilaq created an officialwarning system that sounds an alarm when a piteraq is forecast and completely shuts down the town until the piteraq subsides.

So piteraqs are well known to Greenlanders, but they have not been well studied by scientists. That’s not surprising for a phenomenon that occurs in such a remote, harsh environment. As a consequence, little is known about how they form and what their impacts are.

Our goal was to investigate some of these mysteries.

Filling in the gaps

With my Ph.D. advisor Fiamma Straneo and colleagues, we set about to do the first systematic study of piteraqs, also known as downslope wind events, or DWEs. To do this, we analyzed meteorological data collected at two weather stations in the area: one in Tasiilaq that has been operated by the Danish Meteorological Institute since 1958, and another one on a hill in nearby Sermilik Fjord, established by the University of Copenhagen in 1997. The data were collected every three hours at first and more recently in hourly and 10-minute intervals.

These stations supplied a lot of data, but in only two locations. To gain insights into the larger-scale setting in which piteraqs form, we used a tool called reanalysis, which essentially helps fill in the missing pieces between and around our two weather stations. Created by the European Centre for Medium-Range Weather Forecast, it’s a computer model that uses measurements from weather stations, satellites, radiosondes (balloons released into the air to collect data from the atmosphere), and other data sets. Then it factors in the laws of physics to reconstruct meteorological measurements where no observations exist.

With the reanalysis, we discovered that piteraqs are not simple meteorological events. They are created by a fascinating combination of factors and phenomena that includes the atmosphere, mountains, ice sheets, and fjords. And when we added in satellite data from the U.S. National Snow and Ice Data Center, we saw that the impacts of piteraqs could extend well beyond local towns. Piteraqs also affect glaciers, sea ice, and ocean temperatures in the Atlantic Ocean. By cooling the surface ocean downstream of the coast, they could even influence changes in ocean circulation and climate throughout the entire North Atlantic region from the east coast of the United States to Europe.

The trigger

The Greenland Ice Sheet cools the air directly above it. Colder air is denser and it sinks, forming a separate layer of colder air with warmer, more buoyant air above it. Like two other “fluids” with different densities—air and water—the layers of cold and less cold air masses don’t mix and maintain a boundary between them. This reservoir of bitterly cold air over the ice sheet supplies the fuel for the piteraq.

The trigger seems to be low-pressure systems, or cyclones, that occur frequently east and southeast of Greenland. As low-pressure air rises in vortexes, air rushes into the lower atmosphere void to replace it. It creates a spinning swirl of powerful winds that sneak up behind the reservoir of cold air over the ice sheet. The cyclone winds push the reservoir of cold air downhill in a jolt, releasing its bitter stockpile like a broken dam.

When the cold air rushes downhill, several different forces combine in complex ways to spawn and intensify piteraqs. Among them is a fascinating phenomenon called a mountain wave. Waves occur along the boundary between two fluids of different densities. Unlike a wave of water that rolls onto a beach, it is hard to see the mountain wave in the atmosphere, because the separate layers of warm and cold air are not as easily distinguished.

The mountain wave results in a squeezing of the lower layer. As the volume of cold air is suddenly forced into less space, it needs to accelerate out of its confines and dashes downward along the steep slopes.

During the piteraqs, the mountain wave becomes so steep that it breaks, like a big wave of water that collapses and crashes onto the shore. When the wave breaks in the atmosphere, it not only creates a lot of turbulence, it also allows a second driving force to come into play: gravitational force. Gravity accelerates the speed of anything falling downhill, even a mass of cold air. The air picks up speed, increasing the strength of the piteraq winds.

At the same time, other aspects of topography play a role in driving piteraqs. Tasiilaq is located inside a valley, which funnels the flow of cold air into a smaller and smaller space, increasing its velocity over the ice sheet toward the fjord. By the time the air reaches the fjord, it shoots out at top speed.

Far-flung impacts

Unlike an avalanche, however, the cascade does not stop at the foot of the mountains. It carries the cold air and fast winds far past the coast out to the open ocean, where another fascinating air-sea interaction occurs.

The Gulf Stream and the North Atlantic Current carry waters from near the equator a long way northward to the Greenland coast, and so wintertime ocean temperatures there can range as high as 45°F. In winter, when the contrast in temperatures between ocean and air is higher, heat from ocean waters is released into the atmosphere, and the ocean waters cool down.

Just the way cold air sinks down over the ice sheet because it is dense, cold water also sinks from ocean surface toward the seafloor. This sinking of surface seawater can act like a pump for the large-scale circulation of the ocean. As the waters sink down, other waters flow northward to replace them—carried by currents like the Gulf Stream.

That heat released by the ocean warms the North Atlantic region, especially northern Europe. If it weren’t for this ocean circulation, the climate in northern Europe would be much colder in winter.

Wind events such as piteraqs, which bring icy blasts of cold air out to ocean, may trigger the release of ocean heat to the atmosphere, which in turn, makes ocean waters cooler and denser so that they sink. These winds events may drive ocean waters in the Irminger Sea off Greenland to lose their heat and buoyancy. So we’d like to investigate how much piteraqs actually contribute to driving the sinking and the heat transport of this ocean circulation, and thus regulating our climate.

Ice-breakers

Piteraqs may also influence climate in another way, closer to the coast. When their powerful winds blow out into the fjord, they can push away icebergs and sea ice inside the Sermilik Fjord. Piteraqs can even break up and clear away ice that’s connected or “fastened” to the land.

At the interior end of the Sermilik Fjord, the Helheim Glacier, though seemingly stationary, is actually flowing, continually and slowly pouring ice down the mountains into the fjord. Land-fast ice and sea ice act as dams blocking the flow of ice to the ocean. Some scientists theorize that when this ice is removed, Helheim Glacier can flow faster and push more ice into the ocean.

When we compared our piteraq data with satellite observations of sea ice, we found that piteraqs reduced the sea ice cover inside Sermilik Fjord by 29 percent and also reduced the sea ice in the coastal ocean outside the fjord by 26 percent.

The sea ice pushed out to warmer waters offshore melts, and this could also have far-flung impacts. As more ice melts, it adds fresh water to the ocean surface. Fresh water is more buoyant than salt water, and this dilution could reduce the sinking of ocean waters, slow down ocean circulation, and affect regional climate.

All in all, the impacts of piteraqs are substantial and can extend far beyond Tasiilaq, where the strong winds occur, so it behooves us to unravel more about how they work. Reanalysis techniques will only take us so far, because often there are not enough observations to render an accurate picture of reality, or the physical laws are not sufficient to fill in all the gaps. Thus, there are still many open questions regarding the details of the processes that occur in the atmosphere, land, and sea during piteraqs. Further investigation with new methods will allow us to move forward to find out more about these fascinating, life-threatening, and glacier-, ocean- and climate-shifting storms.

This research was funded by U.S. National Science Foundation and the Natural Sciences and Engineering Research Council of Canada.

Posted in News

Go with the flow

‘Go with the flow’: Research on the currents in the subpolar North Atlantic

This past July chief scientist Laura de Steur and the crew of the Pelagia set out to take measurements of the subpolar gyre as part of NACLIM and OSNAP research programs. Research conducted on this cruise, and as part of these programs, is important in understanding the “role of the ocean in our climate and future climate change.” Learn more about their work this summer, and ongoing research, in this film created over the course of the cruise.

Posted in Cruises

What will the RAPID team find when they recover their ocean moorings this autumn?

by Helen Johnson, Helen Pillar, David Marshall and So Takao

NCEP2_reconstructed_timeseries_over_and_beyond_RAPID periodSince 2004, oceanographers from the National Oceanography Centre in Southampton, together with US colleagues, have been using data from ocean moorings on the eastern and western sides of the Atlantic Ocean at 26 N to monitor the strength of the Atlantic meridional overturning circulation (AMOC). This has resulted in a remarkable and unprecedented 10 year timeseries of this key climate index (black line), which is closely related to ocean heat transport in the Atlantic and, as such, of great importance for the climate of western Europe as well as the entire globe. The observations have revealed large amplitude variations in the AMOC on all time-scales, along with an apparent decline over the ten years, and significant wind-driven weakenings in several recent winters. This autumn the team will collect a further 18 months of data from their ocean moorings. But what will this latest batch of data tell us about the strength of the AMOC?

At the University of Oxford, we have been working to reconstruct the time-series of AMOC variability, based on our knowledge of how winds, heat and freshwater fluxes over the Atlantic have changed over the last few decades, combined with our understanding of how sensitive the AMOC is to variations in these quantities. We use an ocean model and its adjoint to determine the sensitivity of the AMOC to surface wind, heat and freshwater forcing over the entire globe and the preceding 15 years. We then project observed forcing anomalies onto these sensitivity patterns; only those forcing anomalies which project strongly in space and time onto the sensitivity fields will generate variability in the AMOC.

Our reconstructed AMOC time series (orange line) successfully reproduces most of the interannual variability in the observed AMOC time series; these short-timescale fluctuations are dominated by wind forcing (including, but not limited to, Ekman transport anomalies). However, the decadal trend in the observed AMOC time series is not well captured by our reconstruction. This longer timescale variability results from the integrated response of the ocean to heat fluxes over the subpolar North Atlantic over at least the last two decades, and as yet ocean models are unable to accurately represent the ocean’s adjustment to forcing anomalies on such timescales.

Since NCEP II reanalysis atmospheric forcing data is available until June 2015, our reconstructed AMOC time series extends 15 months beyond the end of the currently available observed AMOC time-series. We have reasonable confidence in that portion of the variability which is wind-driven (blue line). We therefore “predict” that the RAPID team will discover that the mean AMOC over this period has been roughly equal to that over the previous few years (a small increase of 0.3 ± 0.2 Sv over the 2009-2014 mean). We further predict that the RAPID data won’t reveal any evidence of a large “dip” over the 2014-2015 winter; in contrast we expect to find that the AMOC reached a maximum in November-January.

These predictions will be validated when the RAPID team publish their updated AMOC time-series early in 2016! And as RAPID data continue to accrue, alongside observations from higher latitudes such as those made by the OSNAP programme, we will learn more about the climatically-important longer-term AMOC changes which are currently inaccessible via our reconstruction – watch this space!

View as PDF: RAPID_prediction

Posted in News

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