Journal of Marine Systems xxx (2013) xxx–xxx

MARSYS-02443; No of Pages 14

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Journal of Marine Systems

j ourna l homepage: www.e lsev ie r .com/ locate / jmarsys

The Atlantic Multidecadal Oscillation: Its manifestations and impactswith special emphasis on the Atlantic region north of 60°N

Kenneth F. Drinkwater a,⁎, Martin Miles b, Iselin Medhaug c, Odd Helge Otterå b, Trond Kristiansen a,Svein Sundby a, Yongqi Gao d

a Institute of Marine Research and Bjerknes Centre for Climate Research, Box 1870 Nordnes, N-5817 Bergen, Norwayb Uni Research and Bjerknes Centre for Climate Research, Allégaten 70, 5007 Bergen, Norwayc Geophysical Institute and Bjerknes Centre for Climate Research, University of Bergen, Allégaten 70, 5007 Bergen, Norwayd Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Thormøhlensgt 47, 5006 Bergen, Norway

⁎ Corresponding author. Tel.: +47 55236990.E-mail address: ken.drinkwater@imr.no (K.F. Drinkwa

0924-7963/$ – see front matter © 2013 Elsevier B.V. All rhttp://dx.doi.org/10.1016/j.jmarsys.2013.11.001

Please cite this article as: Drinkwater, K.F., etthe Atlantic region north of 60..., J. Mar. Syst

a b s t r a c t

a r t i c l e i n f o

Article history:Received 31 August 2013Received in revised form 31 October 2013Accepted 1 November 2013Available online xxxx

Keywords:AMOClimateEcosystemBarents SeaNorwegian Sea

This paper examines the multidecadal variability in the northern North Atlantic and the Arctic. Observations,modeling and paleo data provide evidence of a strong link between the atmospheric and physical oceanographicvariability in these northern regionswith Atlantic sea surface temperatures farther south as expressed by the At-lanticMultidecadal Oscillation (AMO). Air and sea temperatures over the past 100–150 years reveal cool periodsin the late 1800s to early 1900s and in the 1970s to 1980swithwarmperiods during the 1920s to 1960s and fromthe 1990s through to the present, similar to the variability in the AMO index where a positive (negative) AMOindex represents warm (cold) periods. Sea-ice extent in the north has also varied at multidecadal scales withthe ice retreating during thewarm periods and expanding during the cold periods. The presence of multidecadalvariability is also suggested from marine sediment paleo data as well as ice-core oxygen isotope data. Observa-tions of biological impacts of the multidecadal variability in the northern regions include a general increase inplankton and fish productivity, as well as expansion of the species distributions northward, in conjunctionwith the AMOwarm periods and the opposite during AMO cold periods. In addition, a review of themechanismsresponsible for the AMO and a brief discussion of the linkages between the multidecadal variability in the north-ern and southern hemispheres, including between the Arctic and Antarctic, are presented.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Our primary motivation for this study has been to examine theevidence for multidecadal variability in the waters of the northernNorth Atlantic and the Arctic, and their links to the multidecadal var-iability elsewhere in the Atlantic Ocean. Instrumental records docu-ment that the sea surface temperatures (SSTs) in the North Atlanticbasin have varied on multidecadal time scales over the last150 years or more (e.g., Bjerknes, 1964; Delworth and Mann, 2000;Deser and Blackmon, 1993; Kushnir, 1994; Polyakov and Johnson,2000; Schlesinger and Ramankutty, 1994). This pattern of observedmultidecadal SST variations has commonly been referred to as the“Atlantic Multidecadal Oscillation” or AMO following Kerr (2000).It is not clear to what extent the variations constitute a true oscillationand so a better descriptionwould actually be AtlanticMultidecadal Var-iability (AMV; Knight et al., 2005). However, given the extensive use ofthe term in the literature and within this special issue, we will continueto use the expression AMO within the present paper.

ter).

ights reserved.

al., The Atlantic Multidecada. (2013), http://dx.doi.org/10.

Enfield et al. (2001) defined an AMO Index as the 10-year runningmean of the linear detrended sea surface temperature anomalies(SSTAs) averaged over the North Atlantic Ocean from 70°N to the equa-torwith AMO+(AMO–) values corresponding towarm (cold) conditions(Fig. 1). Sutton and Hodson (2005) used SSTs within the area boundedby 0°–60°N and 75°–7.5°W. They low-pass filtered the data with a 37-point Henderson filter, then detrended and also removed the mean.Others have estimated AMO indices that differ slightly in the area ofthe North Atlantic chosen to average over or in the detrending method(e.g. Guan and Nigam, 2009; Ting et al., 2009; Trenberth and Shea,2006). However, the main temporal and spatial characteristics are sim-ilar. Temporally, the principal pattern is one of cooling in the late 1800sand early 1900s, a warm period beginning in the 1920s and extendinginto the 1960s, a cool period in the 1970s and the 1980s and anotherwarm period beginning in the 1990s extending through to the present(Enfield et al., 2001; Kelly et al., 1982; Sutton and Hodson, 2005; seealso Fig. 1). The period of this SST variability is approximately60–80 years (Delworth and Mann, 2000; Schlesinger and Ramankutty,1994; Sutton and Hodson, 2005). There is spatial and temporal vari-ability in themultidecadal SST signal within the North Atlantic, how-ever. The precise timing of the SST peaks and troughs do differslightly with location and larger amplitudes occur in a horseshoe

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Fig. 1. The unsmoothed Kaplan SST dataset Atlantic Multidecadal Oscillation (AMO) for the period 1856–2008 (http://www.cdc.noaa.gov/Timeseries/AMO/). Also shown is the 10-yearrunning mean of the AMO where positive AMO is colored orange and negative AMO is colored green. (For interpretation of the references to color in this figure, the reader is referredto the web version of this article.)

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pattern encompassing the Labrador Sea and south of Greenland, theeastern portions of the North Atlantic and the tropical Atlantic (seee.g. Alexander et al., in this issue).

Paleoclimatic studies suggest that such multidecadal variabilityhas been a persistent feature in the more distant past (Delworthand Mann, 2000; Gray et al., 2004; Kilbourne et al., in this issue).However, it is worth noting that until recently the interpretation ofmultidecadal variability before 1850 was mainly based on high-resolution terrestrial proxy records as very few high-resolution re-cords were available for the North Atlantic Ocean. An exceptionwas a coral record from the low-latitude Atlantic that showedmultidecadal variability but suggested that it only became signifi-cant there after about 1730 (Saenger et al., 2009).

In the following section, the mechanistic hypotheses proposed toaccount for the AMO signal in the North Atlantic are reviewed. Theimportance of the AMO-like variability in atmospheric and physicaloceanographic variables in the higher latitude regions of the NorthAtlantic and in the high Arctic is then presented followed by a

Fig. 2. Low-pass filtered ensemble model mean historical AMO (from 5 realizations of the Berganthropogenic external forcing (color shading) since 1850. One standard deviation of the en(black) and ERSST.v3 (orange) data sets are also shown. The long-term trends are indicatedwitto color in this figure, the reader is referred to the web version of this article.)

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

discussion of their biological impacts. Emphasis is placed on AMOsignals in the Atlantic area north of 60°N because it has receivedmuch less attention than regions farther to the south. The next sec-tion briefly describes some of the linkages between the AMO and cli-mate signals elsewhere around the globe while the final sectionsummarizes the major highlights of the paper.

2. AMOmechanisms

A number of mechanisms have been proposed in recent years toaccount for the observed variability in the AMO. Both atmosphericand oceanic processes are suggested to play important roles. One hy-pothesis suggests that SST variations in the Atlantic are ultimatelyatmospherically-induced, whereby random fluctuations in the atmo-spheric circulation give rise to a low-frequency SST response throughsurface energy fluxes, Ekman currents and thermal inertia (i.e., thestochastic climate model of Deser et al., 2010; Frankignoul andHasselmann, 1977). The most commonly accepted view, however,

en Climate Model) forced with only natural external forcing (light blue) and natural plussemble spread is indicated by the gray band. The observed AMO based on the HadSST3h dashed lines. Modified based on Otterå et al. (2010). (For interpretation of the references

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Fig. 3. The time series of the 10-year running mean of the annual detrended air tempera-ture anomalies from Nuuk, West Greenland, and the AMO Index. In this and subsequentsimilar figures, the latter was linearly detrended and filtered using a 121-month runningmean obtained from http://www.esrl.noaa.gov/psd/data/timeseries/AMO/. The correla-tion coefficient (r) and its significance level (ρ) after adjustment for the number of inde-pendent degrees of freedom using the method of Garrett and Toulany (1981) are alsoprovided.

Fig. 5. The time series of the 10-year runningmean of the annual number of months of seaice (storis) off West Greenland (data from Valeur (1976)) and the AMO Index.

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is that the AMO, at least partially, reflects natural internal variationsin the strength of the Atlantic Meridional Overturning Circulation(AMOC), where Polyakov et al. (2005, 2010) noted that a strongerthan normal overturning is associated with warmer North Atlantictemperatures.

The AMOC is a combination of the wind-driven and density-drivencomponents of the Atlantic circulation, with its variability connectedto both the Southern Ocean winds and density variations in the regionsof deep-water formation in the high northern latitudes (Marshall et al.,2001b and references therein). The Southern Oceanwinds are assumedto have a larger effect on the mean state (Delworth and Zeng, 2008)while the deep-water formation is assumed to control shorter-termvariability.

The paradigm that North Atlantic multidecadal variability is re-lated to changes in the ocean circulation goes back to the pioneeringwork by Jackob Bjerknes in the early 1960s (Bjerknes, 1964). He ob-served the slow-varying warming and cooling periods in the NorthAtlantic and attributed these temperature variations to the advec-tion of warm water from the subtropics. Later, several model studiesdemonstrated AMOC oscillations on multidecadal time scales withaccompanying changes in Atlantic SSTs (Delworth et al., 1993;Knight et al., 2006; Timmermann et al., 1998). The time scale ofthese oscillations and the governing mechanisms vary greatly betweenmodels. To what extent the AMO is due to an ocean only mode (e.g.,Delworth et al., 1993; Latif et al., 2004), a coupled air–sea mode (e.g.,Gastineau et al., 2012; Gulev et al., 2013; Timmermann et al., 1998),

Fig. 4. The time series of the 10-year running mean of the annual detrended sea temper-ature anomalies from Kola Section north of the Murman Peninsula in Russia, and theAMO Index.

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

or an atmospheric excitation or damping of the ocean (e.g., Delworthand Greatbatch, 2000; Delworth and Mann, 2000; Griffies andTziperman, 1995), has not been firmly established. However, new ob-servational evidence from the mid-latitude Atlantic strongly suggestthat on longer time-scales (i.e. N10 years) the ocean is the main deter-minant of the surface turbulent heat fluxes and forces the atmosphere,while on shorter time scales the opposite holds (Gulev et al., 2013).

Fig. 6.Multidecadalfluctuations in sea ice linked to the AMO, 1750–2000. Original time se-ries (gray) andmultidecadal 50–120 year component (black) reconstructed fromwaveletdecomposition: (a) AMO modern Index, not de-trended, i.e., North Atlantic SST anomaly.(b) AMO proxy reconstruction, not de-trended, 10-year running average (Gray et al.,2004). (c) Fram Strait (FS) ice export reconstructed from historical ice extent along SWGreenland (Schmith and Hansen, 2003). (d) Icelandic (I) sea-ice severity index(1750–1870) and sea-ice incidence index (1880–2000). (e) Western Nordic Seas (WNS)winter sea-ice extent reconstructed from paleo proxies (Macias-Fauria et al., 2010). Thereduced ice periods are seen to correspond to warm AMO periods.

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Fig. 7. The relation between spatial and temporal scales of ocean climate phenomena.AMO: Sutton and Hodson (2005); North Pacific Index (NPI): Deser et al. (2004);North Pacific Gyre Oscillation (NPGO): Di Lorenzo et al. (2008).

Fig. 9. The relationship of the 10-year running mean of the combined roe index (FNC) forNortheast Arctic cod off Norway (see text for description) with the AMO Index.

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In many climate models, the AMO generally results from variationsin the AMOC. Although many of these modeling studies have founda relationship between AMO and AMOC, they have usually onlyused preindustrial control simulations. While the relationship be-tween AMO and AMOC previously appeared robust in these models,when full forcing is included, this may no longer be the case. Indeed,there was no consistency in the AMO–AMOC relationshipwhen com-paring the results from the full suite of either IPCC AR4 (Medhaugand Furevik, 2011) or AR5 models (Zhang and Wang, 2013).

The mechanisms for AMOC variability leading to the temperaturechanges can broadly be put into two classes: 1) ocean advective pro-cesses and 2) local air–sea flux interactions. For the advective pro-cesses, several mechanisms have been proposed that include bothheat and salt/freshwater anomalies being transported into convectiveregions causing density anomalies, and hence affecting deep-water for-mation (e.g., Bentsen et al., 2004; Delworth and Mann, 2000; Delworthet al., 1993; Jungclaus et al., 2005; Knight et al., 2005; Latif et al., 2004).Delworth et al. (1993) attributed the AMOC variability associated withdensity changes in the sinking regions to variations in the local near-surface salinity. An increase in local salinity can occur through advec-tion from the south of warm, salty waters. Cooling of these high salinitywaters as they move into higher northern latitudes results in increased

Fig. 8. The relationship of the 10-year running means of the anomalies of the fisherycatches of West Greenland cod with the AMO Index. The correlation coefficient betweenthe cod and the AMO was not statistically significant and is not provided.

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

deep-water formation, sinking and a spin up of the overturning circula-tion. This increased overturning circulation returns the excess salinitysouthward at depth, drawingwarm surfacewater northward at the sur-face. Other modeling studies have shown density variations in the sink-ing region, and hence deep convection, being controlled or modulatedby atmospherically-driven freshwater transports from the Arctic,where an increased freshwater transport stratifies the water column,inhibits convection and slows down the overturning (e.g., Delworthet al., 1997; Holland et al., 2001; Jungclaus et al., 2005).

The AMOC is also found to be associated with the North AtlanticOscillation (NAO) through stochastic forcing. A positive phase ofthe NAO is associated with an increased air–sea heat flux in the Labra-dor Sea region due to the colder and dryer than normal northerly airmasses blowing over the region (Hurrell, 1995). The increased heatloss over the Labrador Sea region destabilizes the water column, in-creasing deep convection and deep-water formation, hence increasingthe AMOC (e.g., Dickson et al., 1996; Häkkinen, 1999; Medhaug et al.,2012). A negative phase of the NAO is associated with fewer storms inthe Nordic Seas, giving favorable conditions for deep convection inthis region. This is because less heat is transported into the regionwhen there are fewer storms, leaving more cold and dry air masses todominate at such times. Earlier studies assumed a direct connection be-tween the deep-water formation in the Nordic Seas and the overflow ofdeep water to the North Atlantic. However, this is not necessarily so,owing to the barrier formed by the Greenland–Scotland Ridge that sep-arates the Nordic Seas and the North Atlantic. The variability in thedeep-water properties originating in the Nordic Seas, which is assumedto contribute approximately two-thirds of the North Atlantic DeepWater (NADW) (Dickson and Brown, 1994) and which forms thelower limb of the AMOC, is associated with the atmosphere's Scandina-vian Pattern. This pattern,which in its negative phase results in strongernortherly winds over the Nordic Seas, spins up the circulation andhence increases the exchange of heat and water across the Green-land–Scotland Ridge (Medhaug et al., 2012).

Fig. 10. The relationship of the 10-year running means of the anomalies of the spawningstock biomass (SSB) of the spring spawning Norwegian herring with the AMO Index.

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Although the AMOC is found to be strongly associatedwith the NAO,Guan and Nigam (2009) did not find a significant correlation betweenthe AMO and the NAO. Gastineau et al. (2012) on the other handfound a two-way relationship between the AMO and NAO. From bothobservations and a model, they could identify the horseshoe shapedsummer SST anomaly pattern in the North Atlantic preceding a winterNAO-like pattern in the atmosphere, a result similar to Czaja andFrankignoul (1999, 2002). In addition, Gastineau et al. (2012) foundthat the modeled horseshoe pattern was in part formed by the internalspring and summer variability of the atmosphere. A similar SST patternalso followed an intensification of the AMOC (Marshall et al., 2001a).

Häkkinen et al. (2011) highlighted the similarity in the AMOwithan index of atmospheric blocking over the North Atlantic. Thisblocking, which occurs between Greenland and Western Europe,prevents unimpeded westerly winds across the Atlantic, therebyresulting in shifts in the storm tracks over the Atlantic. They foundthat under increased blocking, the subsequent changes in thewinds lead to weaker ocean gyres and reduced heat loss from theocean, which contribute to the warm phase of the AMO.

A complete understanding of multidecadal variability also re-quires knowledge of the natural and anthropogenic external radia-tive forcings that act on the climate system. Up until recently theseforcings have been considered to play only a minor role in the AMO.This was supported by a host of general circulation model studies thattended to produce Atlantic multidecadal variability in the absence ofany external forcing (Delworth and Greatbatch, 2000; Delworth andMann, 2000; Jungclaus et al., 2005). Furthermore, some studies estimat-ed the forced response based on a multi-model ensemble of IPCC AR4model simulations and found little evidence of significant changes inNorth Atlantic SSTs due to external forcing (Knight, 2009; Kravtsovand Spannagle, 2008; Ting et al., 2009).

Several studies, however, have questioned the prevailing hypothesisthat North Atlantic SST variability is caused by internal ocean variability.Mann and Emmanuel (2006) suggested that since the late 19th centurythe Atlantic SST evolution has largely been controlled by anthropogeniclarge-scale warming but has regionally been offset by a cooling causedby late 20th century tropospheric aerosol forcing. The importanceof tropospheric sulfate aerosols was further highlighted in thestudy by Chang et al. (2011), in which they found that such aerosolscould have played a key role for the 20th century evolution of thetropical Atlantic interhemispheric gradient in SST thereby modulat-ing the AMO signal. They also found IPCC AR4 models that includeda more complex treatment of aerosol physics tended to better simu-late the 20th century historical interhemispheric tropical AtlanticSST gradient.

Recently, other studies have highlighted the potential importantrole of volcanic aerosols in explaining longer-term changes in Atlan-tic SSTs. For instance a recent analysis of tropical North Atlantic SSTsconcluded that up to 70% of the trend since 1980 could be explainedby regional variability in aerosols, where the bulk of this was causedby late 20th century volcanic eruptions (Evan et al., 2009). More re-cently, Booth et al. (2012), using an Earth system climate model,found that the aerosol emissions and periods of volcanic activitycould account for 76% of the AMO variability from 1960 to 2005.These model results have however been criticized by Zhang et al.(2013) for differences between model results and observations ofkey variables such as ocean heat content. According to Zhang et al.(2013) these discrepancies might be strongly influenced by the aero-sol effects and thus cast doubt about the apparent AMO-link to theaerosol forcing. Other modeling studies have highlighted the poten-tial impact of volcanic aerosols on decadal scale climate variability(Stenchikov et al., 2009; Otterå et al., 2010; see Fig. 2). The simulatedAMO in the Bergen Climate Model (BCM; Otterå et al., 2010), whenforced with all relevant natural and anthropogenic forcings, showclear similarities with the observations both in terms of its phasingand its amplitude (Otterå et al., 2010; Fig. 2). The spread of the five

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

ensemble members covers most of the variations in the observedAMO. The BCM therefore suggests that the AMO is not strictly ran-dom, but that warm and cold periods during the last 150 yearshave been strongly influenced by volcanoes and other external forc-ings (e.g. Booth et al., 2012; Otterå et al., 2010). In particular, Otterået al. (2010) suggested that volcanoes play an important role in At-lantic decadal SST variability both through their direct influence ontropical SSTs and their systematic influence on the NAO and theAMOC.

Medhaug and Furevik (2011) compared the whole suite of IPCC AR4models and found that no consistent conclusion could be drawn inregards to the AMOC driving the SST variability in a fully coupled/forcedsystem. It is therefore likely that different mechanisms dominate in dif-ferent climate models and/or the connections found in control simula-tions using the same models are masked in the fully forcedsimulations. Even though the spatial patterns of temperature variabilitywere found to be similar in themodels, theywere not necessarily corre-lated with periods of strong and weak AMOC (Medhaug and Furevik,2011). Therefore, caution should be taken when using the spatial pat-tern and time series of the AMO back in time based upon paleo-proxies from land (e.g., Gray et al., 2004). These proxies can be influ-enced by the local climate and therefore will not necessarily tell us thefull story about the spatial and temporal evolution of the warm andcold phases in the ocean.

3. AMO signals in the northern North Atlantic

3.1. Temperatures and circulation patterns

Modern datasets, historical observations, and paleoceanographicreconstructions all demonstrate AMO-like variability in the temper-atures of the Atlantic subarctic and Arctic marine realm north of60°N. For example, the 10-year running means of the linearlydetrended air temperature anomalies (1861–2010) relative to1961–1990 climatology from Nuuk inWest Greenland are shown to-gether with the AMO index in Fig. 3. Their correlation is statisticallysignificant (r = 0.49, ρ = 0.05) after adjusting for autocorrelationby determining the number of independent degrees of freedom usingthe method of Garrett and Toulany (1981). A similar multidecadal pat-ternwas observed by Johannessen et al. (2004) using hemispheric aver-ages of air temperatures, which further showed the amplitude of themultidecadal variability increased north of about 60°N. Chylek et al.(2009) analyzed observed air temperatures covering 1950–2008 from37 meteorological stations around the northern hemisphere north of64°N in two latitudinal bands (64°–70°N and 70°–90°N). They foundAMO-like variability in both bands with the largest signal in the higherlatitudinal band. The amplitude in both bands varied seasonally withhigher values in the autumn and winter. Chylek et al. (2010), whenthey extended the observed air temperature data back to 1903, againfound a strong match with the AMO signal.

Modern gridded oceanographic datasets incorporate enough datafrom the North Atlantic region to allow reliable inference on AMOlinkages north of 60°N. Medhaug and Furevik (2011) analyzed theSST dataset of Kaplan et al. (1998). They found that the correlationcoefficients between the individual gridded SSTs and the AMOindex were consistently positive (r = 0.6–0.8) in the ~60°–70°N re-gion spanning from the Labrador Sea to the Norwegian Sea. A 15-year running mean filter was applied to the gridded SST data andthey were also detrended. The results were similar to those foundby Polyakov et al. (2010) using other oceanographic datasets andthe correlation patterns were also consistent with those frommulti-model simulations (Medhaug and Furevik, 2011). In the mostrecent years, characterized by an AMO+ phase (Fig. 1), satellite dataand other oceanographic measurements show increasing sea tempera-tures in the subarctic Atlantic and the Arctic Ocean (e.g., Polyakov et al.,2005). The temperature anomalies remain positive after detrending to

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Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadal Oscillation: Its manifestations and impacts with special emphasis onthe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.1016/j.jmarsys.2013.11.001

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account for the possibility of anthropogenic warming, meaning thatnatural variability such as the AMO plays a significant role in these ob-served temperature fluctuations (Polyakov et al., 2010).

Regional differences in the multidecadal signal in the high-latitudesare apparent. For example, the timing of the onset of the cold periodfollowing the early twentieth century warming period (ETCW) thatbegan in the 1920s varied slightly across the northern North Atlantic,beginning first in the northeast during the late 1950s to the early1960s and last in the northwest in the late 1960s to early 1970s. Alsothere were amplitude differences. Comparing the observed SST differ-ence between awarm 15-year period (1941–1955) and the subsequentcold 15-year period (1967–1981) showed the largest difference to benorth of Iceland (N0.5 °C), slightly larger than the next warmest anom-aly in the subpolar gyre south of Greenland (Medhaug and Furevik,2011). An amplified AMO signal is observed in the region aroundIceland and south Greenland during the current warm phase, withanomalously high SSTs and subsurface temperatures in the waters offsouthwest and southeast Greenland since the mid-1990s (Seale et al.,2011). Periods of anomalously high SSTs off southeast Greenland duringwarm phases of the AMOmay result in the enhanced presence of tem-perate Irminger Current waters. Thesewarmwaters off Greenland haveintruded into the adjacent fjords and contributed to submarinemeltingand rapid retreat of the marine-terminating Greenland ice-sheet gla-ciers in recent years (e.g., Holland et al., 2008; Howat et al., 2008), par-ticularly in southeast Greenland (62°–67°N). The lack of retreat inmarine glaciers farther north in East Greenland (67°–72°N) is consistentwith the location of the northern limit of warm Irminger Currentwatersapparent from satellite SST sequences in the 2000s (Seale et al., 2011).

Oceanographic observations during the 1960s/1970s cold (AMO−)period (e.g., Belkin et al., 1998; Dickson et al., 1988 and referencestherein) revealed that negative SST anomalies were associated withenhanced polar waters and sea-ice export from the Arctic throughFram Strait. Thompson et al. (2010), using several different datasets,showed that hemispheric SSTs decreased by 0.3 °C between1968–1972, primarily due to the abrupt cooling in the North Atlantic(50°N–70°N; 70°W–0°). As the time scale of the rapid decline wasconsiderably shorter thanmultidecadal SST variability, these authorsconcluded that the AMO could not explain hemispheric differencesin SST; moreover, they implied that the results were incompatiblewith oscillatory multidecadal variability. However, an alternativeperspective is that inherently irregular, higher frequency variabilitysuperposed upon the multidecadal variability is to be expected. Fur-thermore, other authors (Dima and Lohmann, 2007; Zhang andVallis, 2006) suggest that such ocean-ice changes in the Iceland–Greenland region may even be an intrinsic, mechanistic part of theAMO.

Long historical records of ocean temperature observations, primarilycoastal SSTs from Iceland andGreenland and other parts in the northernNorth Atlantic, extend back to the late 1800 s or early 1900s, andcapture two negative and two positive AMO phases. Changes observedduring the ETCW (AMO+) were detailed in Drinkwater (2006) andreferences therein. Among the more notable changes were an abruptrise in ocean temperatures measured off Iceland (e.g., Hanna et al.,2006) and West Greenland (Smed, 1947; Stein, 2007) between1918 and the early 1920s. The changes were not limited to the SSTs,as increased temperatures down to 500 m depth were documentedoff West Greenland (Dunbar, 1946; Jensen, 1939). It is interesting tonote that the waters in the western Labrador Sea, in particular on theLabrador and northeastern Newfoundland shelves do not display anAMO-like signal. This may be a result of forcing from the Arctic by ad-vection through the Canadian Arctic Archipelago (Jones et al., 2003) al-though this has not been proven.

Fig. 11. Sea surface temperature anomaly for the North Atlantic averaged over 5 year perio1980–1985, (g) 1985–1990, (h) 1990–1995, and (i) 1995–2000. Anomalies estimated as 5-yearilation database (http://www.atmos.umd.edu/ocean/).

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

In the Northeast Atlantic, long observational records of ocean tem-peratures exhibit multidecadal fluctuations that are generally in phasewith the AMO (Fig. 4). During the ETCW, themean annual temperaturefrom 0 to 200 m in the Kola transect in the southern Barents Sea in-creased sharply by 0.5 °C during the 1920s and remained high untilthe late 1950s to early 1960s before decreasing (Fig. 4). These Kola tem-peratures, provided by the Polar Research Institute of Marine Fisheriesand Oceanography (PINRO) in Murmansk, Russia (http://www.pinro.ru) are representative of temperature variability in the southern BarentsSea (Ingvaldsen et al., 2003; Tereshchenko, 1996). Yndestad (1999) andlater Stenevik and Sundby (2007) noted the long-term variability in theKola Section temperatures but did not mention the AMO specifically.Skagseth et al. (2008) illustrated the similarity between the Kola tem-perature and AMO. Later Levitus et al. (2009) showed that themultidecadal variability of Barents Sea water temperatures from 1900to 2006 was correlated with the AMO (also see Fig. 4). They developedan area-averaged time series of temperature for the 100–150 m depthlayer in an expanded area around the Kola Section. This record wasdominated by multidecadal variability with a temperature range fromthe minimum to the maximum of order 4 °C.

A pertinent question is whether there are changes in the circulationpatterns at multidecadal frequencies that are in phase with the AMO.Although current measurements are relatively few and usually ofshort duration, those that do exist provide some insights. For example,during the ETCW, the transport of relatively warm Irminger Currentwater south of Greenland, which eventually forms the offshore branchof the northward-flowing West Greenland Current, was apparentlyabove normal throughout most of the AMO+ period from the 1930s tothe 1950s (Beverton and Lee, 1965). Estimates of flow near Cape Fare-well, Greenland, indicated that peak transports during 1931–1938were 3 times greater than those during the period before and after(Beverton and Lee, 1965; Drinkwater, 2006 and references therein).Transports in the West Greenland Current also seemed to have in-creased in the current AMO+ period, particularly since 1995 (Myerset al., 2007; Stein, 2004; Yashayaev, 2007). The flow of Atlantic waterto the west and north of Iceland is thought to have increased in the1920s and pushed the cold East Icelandic Current farther offshore(Stefánsson, 1954). This is consistent with the sea-ice distributionsand the increased southwesterly winds off northern Iceland duringthis warm period, and is supported by variability evident from SSTobservations from northern (Hanna et al., 2006) and eastern Iceland(Wood et al., 2010), which co-vary with the AMO.

Changes in ocean circulation are also evident farther to the north-east. The West Spitsbergen Current, which is the northward-flowingbranch of the North Atlantic Current to the west of Svalbard, also ap-peared to have increased in strength during the ETCW. This causedthe thickness of the cold surface layer in the Arctic Ocean todecrease from 200 to 100 m (Drinkwater, 2006). The inflow ofAtlantic waters into the Barents Sea is thought to increase duringAMO+ phases based on modeling studies and observations of thethermohaline conditions there (e.g., Levitus et al., 2009). Polyakovet al. (2005, 2007) found evidence for enhanced Atlantic waterinflow to the Arctic Ocean during the early 2000s and showed thelong-term variability to be dominated by multidecadal variability.

Oceanographic measurements are typically limited to the last50–150 years, thus encompassing just one or at most twomultidecadal‘cycles’. A relevant question is whether there is an AMO signal in longerpaleoceanographic records that can serve as proxies for SST in thenorthern seas. There are presently few marine core records fromsites in the northern North Atlantic with high-enough sedimentationrates to provide temporal resolution commensurate to resolve themultidecadal variability. Although the disparate analyses of records

ds: (a) 1955–1960, (b) 1960–1965, (c) 1965–1970, (d) 1970–1975, (e) 1975–1980, (f)averaged deviations from the 1960–1991 climatology using the Simple Ocean Data Assim-

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published thus far do not yield an unequivocal, coherent picture,there are some indications of quasi-persistent multidecadal variabil-ity in previous millennia. From the northern Icelandic Shelf, recon-structions of SST from marine sediments reflect the relativeinfluence of temperate Irminger Current waters that flow northalong eastern Iceland before moving eastward on the northernIcelandic Shelf where it mixes with cold waters carried by the EastIcelandic Current. Time–frequency analysis of the Sicre et al.(2008) SST reconstruction found a multidecadal signal centered onabout 70 years (Knudsen et al., 2011).

In the Norwegian Sea, Risebrobakken et al. (2003) used foraminiferato reconstruct SSTs over the Vøring Plateau (66°58′N, 07°39′E),which is an indicator of the influence of Atlantic Water carried bythe Norwegian Atlantic Current. Spectral analysis found indicationsof multidecadal variability, with increased spectral power at a periodof about 81 years, which appeared to be consistent throughout theHolocene. In regions where high-resolution marine-core sequencesare presently lacking, some records based on high-latitude corallinealgae have recently been reconstructed. For example, a 115-yearcomposite record of coralline algal growth-increment width fromaround Newfoundland has been shown to reflect the AMO (Halfaret al., 2011). Multidecadal temperature variability has also beenidentified from oxygen isotope data taken from ice cores. Chyleket al. (2011) reported temperature variability with a time scale of45–85 years in a 559-year time series pieced together from 5 sepa-rate ice core samples taken from Greenland (4) and Ellesmere Island(1).

While these paleo records are suggestive of multidecadal periodicityand show connections with the AMO record, not all are statisticallysignificant. Thus, testing the robustness of the multidecadal temper-ature variability in the northern regions and its links to the AMOmust await more and longer paleo records.

3.2. Sea ice

Evidence for a multidecadal signal in subarctic and Arctic sea icecomes primarily from historical observations, some with nearly200 years of data, as well as from high-resolution paleo-proxy re-constructions. Modern hemispheric datasets of sea-ice concentra-tion are either too short or too unreliable for the period before the1950s; therefore, historical sea-ice time series from various locationsmust be used to examine multidecadal variability, despite theirquantitative limitations.

Based on 20th century observations from the Russian Arctic seas,Polyakov et al. (2003) suggested a multidecadal signal or “low-fre-quency oscillation” in sea ice. The signal appeared strongest in theKara Sea,with aweaker, lagged signal propagating eastward into the Si-berian Arctic seas. Frankcombe et al. (2010) recently showed that theKara Sea ice is significantly correlated with the AMO index, where ahigh AMO index precedes a minimum in sea-ice extent and the lag isconsistent with the propagation of warm Atlantic water into the region.Kinnard et al. (2011) suggested that enhanced ocean heat transport tothe Arctic could possibly be the key driver for the reduction in the Arcticsea-ice cover on multidecadal scales.

Multidecadal fluctuations are also evident in century-scale recordsfrom other regions, including a composite index of four historicalsea-ice records for the northern North Atlantic (Wood et al., 2010).The 20th century observations show sea-ice fluctuations that are inqualitative agreement with the expected sign of the change, i.e. re-ductions during warm (AMO+) periods such as the ETCW(Drinkwater, 2006 and references therein) and increases duringcold (AMO−) periods (Vinje, 2001; Wood et al., 2010). A time series(1899–1971) of the duration of sea ice (“storis”) on the shelf offsouthwestern Greenland shows an AMO-like signal (Valeur, 1976;Fig. 5). Modeling studies also reveal that Arctic sea ice is stronglylinked to the AMO (Day et al., 2012) as well as the AMOC (Day et al.,

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

2012; Mahajan et al., 2011). Day et al. (2012) found that 5 to 30% ofthe variability in September sea-ice extent in the Arctic between 1979and 2010 was linked to AMO variability.

Analyses of oceanographic indices and of sea ice over approximatelythe last century and a half (Schmith and Hansen, 2003), as well ashigh-resolution paleo proxy data of sea ice from shelves and fjordsin southeastern Greenland (Andresen et al., 2011) and West Green-land (Lloyd et al., 2011), indicate that local conditions display theAMO warm and cold phases, including apparent effects on the calv-ing of the major marine glaciers that terminate in the fjords.

However, strong observational evidence of a robust sea ice–AMOconnection has been elusive until recently, largely because century-scale sea-ice and SST datasets are not commensurate to tracking morethan one complete ‘cycle’. Advances in developing longer sea-ice timeseries from historical (e.g., Divine and Dick, 2006) and high-resolutionpaleo-environmental proxies (e.g., Macias-Fauria et al., 2010; Moroset al., 2006) have made it possible to more robustly identify and trackmultidecadal sea-ice variability, and establish linkages to the AMO.Possible connections between reconstructed sea-ice variability andthe AMO have been suggested (Divine and Dick, 2006; Macias-Fauria et al., 2010, respectively); however these authors only point-ed out the similar time scales. A comparison of sea-ice variability andthe AMO is shown in Fig. 6, focusing on three independent sea-ice re-cords from the Greenland Sea region, together with two AMO indi-ces. The sea-ice records are a Fram Strait ice export reconstruction(Schmith and Hansen, 2003), an historical sea-ice series fromIceland, and a paleo-proxy reconstruction for the western NordicSeas (Macias-Fauria et al., 2010). The AMO records used for compar-isonwere an instrumental-based series and the proxy reconstructionbased on tree rings (Gray et al., 2004).

The most recent AMO cold phase (1970s and 1980s) and the earlierone (late 1800s and early 1900s) were both associated with enhancedsea-ice export through Fram Strait, negative SST anomalies and in-creased sea ice in the subpolar Atlantic (Fig. 6). The ETCW began withan abrupt rise in SSTs (Fig. 6a) around 1920 and terminated by anabrupt drop in the late 1960s, both punctuated with abrupt changes insea ice in the Greenland Sea/Iceland region (Fig. 6c–e). Extending thecomparison further back using a tree ring derived AMO proxy(Fig. 6b), it is evident that the wavelength and phasing of the wavelet-filtered signals of the sea-ice records and the AMO are consistent andhave the expected sign, i.e., reduced sea ice during the warm AMO+

phases and vice versa. This demonstrates persistent covariability ofthe AMO and sea ice.

A relevant question is whether the AMO-related variability evidentin the historical sea-ice series from the Greenland Sea and Iceland areapparent in longer sea-ice records. Sea-ice proxies are usually basedon material from marine sediments, and as such there are few recordswhose resolution is adequate enough to identify multidecadal variabil-ity. One such high-resolution sea-ice proxy is from a marine core fromthe North Icelandic Shelf (Moros et al., 2006). Because marine recordshave uneven temporal sampling as well as dating uncertainties, com-parisons with other annually-resolved sea-ice or AMO records areoften imprecise. However, the presence of multidecadal fluctuations insea-ice cover was tested using spectral analysis (Moros et al., 2006)and wavelet filtering (Miles et al., unpublished results). Both methodsidentified a distinct multidecadal signal (period of ~60–70 years)through several millennia, albeit weaker in some intervals. This quasi-persistence is similar to the modulation of AMO-related signals foundin other paleo records from the North Atlantic region (Knudsen et al.,2011), notably δ18O from the ice cap in eastern Greenland and recon-structed SSTs from north of Iceland.

The apparent relationship between sea ice and the AMO is notnecessarily one-way, i.e., the sea-ice cover may not merely respondpassively to the AMO. There are modeling (e.g., Delworth et al., 1997)and observational suggestions (Zhang and Vallis, 2006) that sea-iceanomalies, primarily east of Greenland, may interact with, and possibly

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even lead, AMO variability. Based on model calculations and century-scale observations, Zhang and Vallis (2006) suggested thatmultidecadal variations of the Iceland sea-ice extent and LabradorSea SST may influence the AMO. More sea ice/freshwater and low sa-linity conditions in the North Atlantic subpolar region that occurredin the early 20th century (before the ETCW), as well as during andafter the 1960s, might have contributed to the weakening of theThermohaline Circulation (THC) and the onset of the cold AMO−

phases. The THC is the density driven component of the AMOC. Sim-ilarly, high salinities might also be important for the AMO+ phase. Thesuggestion by Zhang and Vallis (2006) is supported by an independentobservational analysis by Dima and Lohmann (2007), who proposed adeterministic mechanism for the AMO that relies on atmosphere–ocean–ice interactions. Central to the feedback loop is sea-ice exportthrough Fram Strait, and the authors argued that such export, as inthe late 1960s and 1970s, are an intrinsic part of AMO.

Regardless of the uncertainties in the underlying principal mecha-nisms of the sea-ice–AMO linkages, it is evident that multidecadal sea-ice variability is directly or indirectly related to natural fluctuations inthe North Atlantic. There is now a strong body of long-term evidenceto support modeling results that suggest linkages between arctic seaice and the AMO.

4. Arctic–Antarctic connections

While the AMO is defined in terms of North Atlantic sea surfacetemperature variability, it has been linked to multidecadal signalselsewhere around the globe including the Pacific Ocean (e.g., Guanand Nigam, 2009; Hetzinger et al., 2012; Sutton and Hodson, 2005,2007), the Indian Ocean (e.g., Knight et al., 2006; Luo et al., 2011)and terrestrial climate signals in North and South America, Africaand Europe (e.g., Folland et al., 1986; Sutton and Hodson, 2007).However, one of the most interesting connections from our northernNorth Atlantic and Arctic perspective is the AMO link to conditions inthe southern hemisphere. The dipole pattern of AMO with the oppo-site sign in the southern hemisphere has been pointed out for exam-ple by Sutton and Hodson (2005) based on SSTs in theworld's oceansto 40°S and Latif et al. (2006) based on SSTs throughout the globesouth to Antarctica. More recently, Chylek et al. (2010) showed ananticorrelation at multidecadal time scales between detrended airtemperatures based on observations in both the Arctic and Antarctic.The recent warming in the Arctic has thus resulted in a tendency forcooling in the Antarctic. This cooling, coupled with opposing anthro-pogenic warming, may partly explain the lack of any temperaturerise there in recent decades. The observed anti-correlated air tem-perature variability of the Antarctic and the Arctic is thought to belinked through the Atlantic Ocean circulation (Chylek et al., 2010).Modeling studies by Latif et al. (2006) suggested that it was associat-ed with the density-driven component of the AMOC, i.e. the THC.

This phenomenon is an internal oscillation of the earth and showsup in global climate models (Latif et al., 2006; Park and Latif, 2010)along with other teleconnection patterns with shorter periodicityand smaller spatial scale. An example of the latter is the NAO,which manifests itself as opposite climate signals in western andeastern parts of the northern North Atlantic (e.g., Rodionov, 1995).Put into a framework of spatial and temporal scales of the range ofclimate phenomena (Fig. 7) the AMO stands out as one of the pres-ently known climate patterns with the largest scale and the longestperiod that is not externally forced. Although the length of reliabletime series sets the limit to identifying global internal phenomena oflonger time scales and larger spatial scales, global climate modeling in-dicates that centennial-scale climate pattern may exist (Dommengetand Latif, 2008).

Clearly, there is overwhelming evidence for an oceanic connectionbetween the Northern and Southern Hemispheres including the Arcticand Antarctic at multidecadal time scales climate variability. This

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

phenomenon, involving the AMO, as well as possible longer timescale oscillations, requires more research to confirm the relationshipand elucidate its mechanism.

5. Biological impacts

5.1. Historical data

Having established the presence of an AMO signal in the tempera-ture and sea-ice data from the northern regions, what impact didthese have on the biology? In general, warm and cold periods havelong been linked to variability in recruitment dynamics and growth offish, particularly for boreal species such as Atlantic cod, Gadus morhua(Brander, 1995; Ottersen and Loeng, 2000). Cod inhabit the continentalshelves of the North Atlantic from Georges Bank and the North Sea inthe south to West Greenland and the Barents Sea in the north(Sundby, 2000). Cod stocks that occupy the coldest waters within thisgeographic range tend to experience increased recruitment and highergrowth during warmer-than-normal years and vice versa for thosecod found in the warmest waters (Drinkwater, 2005; Planque andFrédou, 1999). Based on these findings one would expect, and indeedfinds, that cod is linked to the AMO variability, including increasedabundances in the more northern regions of the North Atlantic. Al-though not referring to the AMO specifically, Drinkwater (2006)reviewed the biological responses in the northern North Atlanticduring the ETCW. He found that the cod stocks off West Greenland,Iceland and northern Norway (Northeast Arctic cod stock) all record-ed high abundances and spawning stock biomasses during this peri-od. The increased productivity of these stocks was attributed to bothhigh recruitment and higher growth rates, driven by increased pri-mary and secondary production (Drinkwater, 2006). During thiswarm period, these stocks also expanded their geographical bound-aries northward. For example, off West Greenland cod spread fromthe extreme southwestern region northwards up to Disko Island(circa 70°N), a distance of around 1500 km between about 1920 tothe mid-1930s (Drinkwater, 2006; Jensen, 1939). In the Barents Sea,cod spread northward moving onto Bear Island Bank, which resultedin the opening of a cod fishery there after an absence of almost40 years (Blacker, 1957). They also spreadnorthward offWest Spitsber-gen (Beverton and Lee, 1965).

The abundance of cod off West Greenland that had built up duringthe positive phase of the AMO, declined and collapsed commerciallyby the early 1970s owing to both deteriorating environmental condi-tions (colder temperatures, AMO− phase) as well as intense fishingpressure (Horsted, 2000). As the stock abundance declined, the codgradually retreated southward along West Greenland (Drinkwater,2006). A plot of the West Greenland cod catches and the AMO isshown in Fig. 8. Note that the rise in West Greenland cod catches oc-curred several years after the AMO increase (Fig. 8). This was not dueto any time lag between theAMO and the increase in local temperatures(Fig. 3: air temperatures; Smed (1947): sea temperatures). The cod,however, drifted as larvae from Iceland and it took time for them tobecome established in sufficient numbers off West Greenland forthe fishery to develop. In addition, any possible earlier large scalerise in the catches was prevented by World War II. The high catches,even after the decline in the AMO (Fig. 8) and cooler temperaturesbegan to prevail, are believed to be a residual effect of the adult codremaining in the region. It is thought that the primary effect of thecooler temperatures is through decreased survival of the eggs andlarvae, both directly on the stage durations and indirectly througheffects on the prey for the larvae. During the AMO− phase after theETCW, cod numbers also declined off Iceland (Schopka, 1994) andin the Barents Sea there was a decline in the spawning stock biomass(Hylen, 2002), reduced growth rates (Drinkwater, 2006) and a dis-tributional shift to the southeast (Midttun et al., 1981).

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The Northeast Arctic cod stock spawns along the west coast ofNorway with the major spawning site in the Lofoten area. There arethree other important spawning areas, one to the south of Lofoten(Møre) and two to the north (Troms and Finnmark). Data on the roeand catch numbers and/or biomass were collected from all of thespawning sites from the early 1900s to the late 1960s. Sundby andNakken (2008) defined a roe index (FN) as the total number of litersof cod roe delivered by the fishery divided by the total number of codcaught. It is thus the average number of roe per individual fish. The au-thors noted an increase in FN in Lofoten and the northern sites duringwarm periods, in contrast with cold periods when the index declined,whereas the opposite was true in the south at Møre. They interpretedthe results as a both increasing individual and population fecundityand a northward displacement of the spawning sites with increasingtemperature. For comparisonwith the AMO, in this studywe developeda combined roe index (FNC) as the sum of FN anomalies for Troms andFinnmark minus that at Møre. Defined this way, it emphasizes the rela-tive difference between the spawning in the north versus the southwithout over-weighting the major spawning at Lofoten. Fig. 9 showsthe relationship of FNCwith the AMO index. The correlation is statistical-ly significant and shows higher fecundity and more spawning in thenorth during the warm AMO+ phase. Although the roe data stoppedbeing collected several decades ago, information from the coastal fish-ing fleet in the recent warm years has suggested that there has been in-creased spawning in northern Norway (Sundby and Nakken, 2008),supporting a continuation of the link with the AMO shown in Fig. 9.

In concordance with the rise in temperatures in the 1990s, thecod abundance again increased in the Barents Sea although therehas been no significant rise in the growth rates of the cod, unlikethe earlier warm period (Drinkwater, 2009). The Barents Sea codalso have expanded their geographic boundaries north and east-wards with a farthest north location recorded during the Norwegianecosystem survey in 2012 (Bakketeig et al., 2013). Off West Green-land, there have been some indications in recent years that codabundance is increasing but the numbers are still too low for a fullcommercial cod fishery (Drinkwater, 2009). The lack of recovery isconsidered to be partly due to the reduced cod abundance inIcelandic waters, whichwere the source population of the cod duringthe ETCW. The low numbers of cod in Icelandic waters is believed tobe caused by intense fishing (Drinkwater, 2009) and points out thatany future ecosystem projections must consider the impact of fisher-ies and fisheries management policies.

Atlantic herring (Clupea harengus) off Norway is another speciesthat has shown strong multidecadal variability linked to environ-mental changes (Toresen and Østvedt, 2000; Fig. 10). During theETCW, similar to cod, there was an increase in abundance of Norwe-gian spring-spawning herring. They too expanded their territory,moving farther westward in the Norwegian Sea reaching Iceland,which resulted in the opening of the herring fisheries there(Vilhjálmsson, 1997). This industry eventually came to dominatethe Iceland economy for 3–4 decades. These herring spawn on thewest coast of Norway and then spend their first 1–3 years in the Ba-rents Sea before returning to the Norwegian Sea as adults (Toresenand Østvedt, 2000). During the mid-20th century warming period,the young herring spread farther eastward such that a herring fish-ery developed along the Murman coast of Russia (Beverton andLee, 1965) and very large catches were obtained in the warm 1930s(Cushing, 1982). With the advent of cooling, the herring abundancebegan to decline. Note that this decline occurred prior to the decreasein the AMObut ismore closely in linewith the decrease in regional tem-peratures as represented by the Kola Section (Fig. 4). However, the de-clinewas not only a response to the environment but also to the intensefishing pressure. The declining abundance levels caused the herring toretreat eastward and for several years they were found year-roundnear the west coast of Norway, where they continued to spawn. A fish-ingmoratoriumwas imposed byNorwegian fisheriesmanagement that

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lasted for 17 years. Eventually, the stock abundance increased concur-rent with the rise in Kola temperatures (Toresen and Østvedt, 2000)and the AMO and are now at a level consistent with that recorded dur-ing the ETCW(Fig. 10).With the recent increase in abundance, the adultherring have again expanded their territory westward, some as far asIceland, in a somewhat similar manner to what transpired in the previ-ous warm period (Drinkwater, 200911).

Other species also have shown responses to the warm and cold pe-riods although the datasets are generally not long enough or completeenough to show statistical relations with the AMO. Jensen (1949) andTåning (1949) documented many responses during the ETCW. For ex-ample, Atlantic salmon (Salmo salar) and haddock (Melanogrammusaeglefinus) increased in abundance and/or expanded northward offWest Greenland, while capelin (Mallotus villosus) retreated northward.At the same time, beluga whales (Delphinapterus leucas) and narwhals(Monodon monoceros) arrived earlier off Greenland and left later ontheir annual migrations. Species that tended to inhabit warmer watersto the south became occasional visitors off Greenland, Iceland andNorway and sometimes took up temporary residency during theETCW (Drinkwater, 2006; Tåning, 1949 and references within). Asthe temperatures declined in the 1970s, these species shifted theirdistributions southward and the migration timing returned to previ-ous patterns, while in the present warming period there have beenincreasing reports again of the invasion of warm water species intothe region (Astthorsson and Palsson, 2006).

It is not only fish that are affected by the multidecadal variability.Although long-term plankton datasets are rare, shorter data recordshave suggested that there was increased phytoplankton and zoo-plankton during the ETCW (Drinkwater, 2006). With the advent ofcooler temperatures, phytoplankton populations declined in re-sponse to a decrease in incoming solar radiation caused by increasedcloudiness, in some places a reduction estimated to be upwards of30% (Cushing and Dickson, 1976). As a result, there was a delay onthe order of one month in the phytoplankton bloom, e.g., in thesouthern Norwegian Sea (Robinson, 1969). A decline in the zoo-plankton abundance also occurred during this cold period in theNortheast Atlantic between the North Sea, the Norwegian Sea andIceland (Colebrook, 1978). Plankton trends in more northern areasof the North Atlantic or the Arctic at this time are not available dueto lack of data. With the rise in temperatures in the 1990s, phyto-plankton production in the Barents Sea has increased (Mueteret al., 2009). Based on satellite data, this is believed to be related toincreased light levels and a longer production period caused by thereduction in seasonal sea-ice coverage.

Benthic fauna and flora have also been affected by multidecadalvariability in its environment. Blacker (1957) showed that duringthe ETCW, in contrast to earlier years, the benthos associated withAtlantic waters spread over 500 kmnorthward alongWest Spitsbergenas a result of changes in the circulation patterns that increased the influ-ence of AtlanticWaters in the region (see Section 3.1). At the same timewithin the Barents Sea, the Atlantic benthos spread farther eastward offthe Murman Peninsula in Russia with the increasing influence of theAtlantic inflow (Nesis, 1960).

5.2. Modeling larval fish survival and recruitment

As mentioned above, the increased abundances of several of thecommercial fish species in the subarctic and temperate regions duringwarm periods of the AMO is, in large part, due to increased recruitment.The larval and juvenile stages are considered to be critical life phases de-termining recruitment. The match-mismatch in space and time be-tween the phytoplankton bloom and larval fish has been thought tobe the main driver of variability in fish recruitment (Cushing, 1990,1996). For example, increased larval haddock survival and recruitmenton the continental shelf of Nova Scotia is linked to the temporal overlapbetween phytoplankton and larval abundance (Platt et al., 2003). The

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fish larvae do not feed directly upon the phytoplankton but insteadupon the zooplankton that feed on the phytoplankton. An interestingaspect of the match-mismatch hypothesis is that although the abun-dance of zooplankton depends on the timing and duration of springblooms, most fish in temperate and subarctic waters spawn at a fixedtime (Cushing, 1990).

To quantify the potential importance of match-mismatch dynamicson the survival of larval cod (Gadus morhua) during both warm andcold years, Kristiansen et al. (2011) used an individual-based model(IBM). They focused on four important cod spawning grounds in theNorth Atlantic; Georges Bank, the southwestern coast of Iceland, theNorth Sea, and Lofoten on the west coast of Norway. Using a re-analysis of thephysical conditions of the ocean, thewarmest and coldestyears between 1960 and 2002were selected for each spawning ground.The cold yearswere 1965, 1963, 1983, and 1977 for Georges Bank, NorthSea, Iceland, and Lofoten, respectively, and coincided with negativeAMO, whereas warm years for the 4 sites (1999, 1999, 1960, and1990) occurred during positive AMO (Figs. 1, 11).

The study found that a warm year extends the period during springwhen high survival of larval cod is likely, which increased the cumula-tive number of fish that survived the larval and early juvenile stages. Aprolonged season such as that initiated by a warm year, tended to in-crease the duration of the overlap between the larva and its prey dueto an early onset of the spring bloom. Even small changes in survivalprobability during the early ontogenetic stages amplify the number offish that survive to join the adult stages. An extended duration togetherwith increased ocean temperature can therefore strongly elevate therecruitment potential through enhanced prey production and in-creased growth rates. The combined effect is a reduction in thetime required for development into a bigger juvenile fish that canmore easily escape its predators (Hare and Cowen, 1997; Houde,1987; Leggett and Deblois, 1994). The study concluded that a keyfactor for enhancing survival was the temporal duration of the over-lap between high larval cod and their prey abundance and not the ac-tual timing of the peak abundance (Kristiansen et al., 2011).

However, the study also suggests that other factors besides temper-ature may influence recruitment across the North Atlantic and that theresponse to temperature depends on the individual cod stocks(Drinkwater, 2005). In a comparative analysis of cod stocks across theNorth Atlantic (Planque and Frédou, 1999), positive recruitment ofcod was associated with SST for cold water stocks (adults that inhabitbottom water temperatures b6 °C), while negative for warm waterstocks (inhabit bottom water temperatures N9 °C). Mid-range stocks(bottom water 7–8 °C) showed no relationship between changes inSST and recruitment. One explanation for the variable response of anecosystem to ocean warming is the zooplankton species compositionand tolerance for thermal ranges. In ecosystems such as the North Seawhere temperatures are high (above 9 °C), a further increase in tem-perature has been observed to result in a shift in the species composi-tion of the zooplankton from cold-water dominated to warm-waterdominated (Beaugrand et al., 2002). Such a shift occurred during the1990s when the cold-water species Calanus finmarchicusmoved north-wards and was replaced by the warm water species Calanushelgolandicus from the south. During years of high AMO, changes inocean temperature in some areas may reach thermal limits resultingin shifts in the zooplankton species composition, which can have strongeffects on the survival of larval and juvenile fish that depends on thetiming and abundance of particular zooplankton species as prey. Theshift in composition in the North Sea led to a decrease in recruitmentof cod because of decreased survival during the early stages due to ashortage of prey and a reduction in prey quality (Beaugrand et al.,2003). The C. helgolandicus has a different phenology leading to achange in the timing of high abundance of zooplankton from earlyspring to early autumn, and the species is also much less lipid rich, re-quiring the larva to find more prey items to satisfy the energy require-ment for metabolism and growth.

Please cite this article as: Drinkwater, K.F., et al., The Atlantic Multidecadathe Atlantic region north of 60..., J. Mar. Syst. (2013), http://dx.doi.org/10.

6. Summary

This paper provides an overview of the influence of the AMO and itsimpacts in the northern North Atlantic (north of 60°N) and into the Arc-tic. Observations, modeling and paleo data show consistent evidence ofa strong link between these regions and the AMO signal. Air and seatemperatures in the northern regions over the past 100–150 years re-veal the AMO pattern of cool periods in the late 1800s to early 1900sand in the 1970s to 1980s with warm periods during the 1920s to1960s and from the 1990s through to the present. This applies notonly to the SSTs but also to subsurface waters. Sea-ice extent has alsovaried at multidecadal scales with the ice retreating during warm pe-riods and expanding during cold periods. Although high resolutionpaleo data from marine sediments and ice core data are relatively rarein these northern regions, the few available datasets do show evidenceof multidecadal variability of order about 60 to 80 years.

We discussed linkages between the multidecadal variability in theocean temperatures between the southern and northern hemispheres.Observations and modeling studies have shown an out of phase rela-tionship between ocean temperatures in the northern and southernhemispheres, including between the Arctic and Antarctic.

The multidecadal climate variability in the northern North Atlanticand the Arctic has impacted the marine organisms of these regions,with most of the information derived from the subarctic regions andthe Barents Sea (an Arctic Ocean continental sea), since there is a lackof data in the high Arctic. Although no long-term plankton datasetsspanning one or two oscillations of the AMO are available even in thesubarctic, several shorter-term datasets suggest higher primary produc-tion in the northern regions during warm periods and reduced produc-tion in cold periods. In those areaswith seasonal ice cover, this has beenexplained as due to increased light levels and a longer production sea-son with less sea ice and vice versa during periods with more ice. In-creased northward flow of warm waters during the AMO+ phases hasbeen found to shift the boundary between Atlantic and Arctic benthicspecies to the north, or in the case of the Barents Sea, to the east. Byfar the greatest evidence for multidecadal biological impacts connectedto the AMO comes from the century-longfisheries datasets for commer-cial species such as Atlantic cod and herring. They generally show in-creased fish productivity during the warm periods and reducedproductivity during the cold periods. The former is because of increasedgrowth and recruitment. Modeling studies suggest that during thewarm years, increased larval survival and hence recruitment occursdue to a longer duration of overlap between the larvae and their prey.Data on other species also suggest a multidecadal effect but their shorttime series makes it impossible to confirm. Comparisons of the re-sponses of cod across the northern North Atlantic to the ETCW andthe recent warming have shown that heavy fishing pressure can reducefish stocks such that expected responses based on past fish-environment relationships will not always occur.

In addition to the above, a brief discussion of the mechanisms re-sponsible for the AMO was presented. Although extensive modelingand data collections have been carried out, the primary forcing factorof the AMO is still under debate, with no firm conclusions reached.While it is generally accepted that it is related to the AMOC, the relativeimportance of wind forcing, aerosols and volcanic eruptions, atmo-spheric blocking, etc. still has not been fully resolved.

Acknowledgments

This is publication number A434 from the Bjerknes Centre for Cli-mate Research. We wish to thank the Centre for the financial supportto undertake this project. Partial support was also provided by theCentre for Climate Dynamics at the Bjerknes Centre (IMMUNITY pro-ject) and the NSF Arctic System Science program (0531286). Wethank the two anonymous reviewers and Janet Nye for providingvaluable comments on an earlier draft. Thanks are also due to

l Oscillation: Its manifestations and impacts with special emphasis on1016/j.jmarsys.2013.11.001

12 K.F. Drinkwater et al. / Journal of Marine Systems xxx (2013) xxx–xxx

Juergen Alheit for taking the lead in organizing the ICES AMO Work-shop in Woods Hole, at which this work was first presented, and forspearheading the special issue from the workshop results.

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