VOL. 17, NO. 5

JOURNAL OF CLIMATE

1 MARCH 2004

The Effects of North Atlantic SST and Sea Ice Anomalies on the Winter Circulation in
CCM3. Part I: Main Features and Storm Track Characteristics of the Response
GUDRUN MAGNUSDOTTIR
Department of Earth System Science, University of California, Irvine, Irvine, California

CLARA DESER AND R. SARAVANAN
National Center for Atmospheric Research,* Boulder, Colorado(Manuscript received 16 January 2003, in final form 6 October 2003)
ABSTRACT
Observed multidecadal trends in extratropical atmospheric flow, such as the positive trend in the North Atlantic
Oscillation (NAO) index, may be attributable to a number of causes. This study addresses the question of whether
the atmospheric trends may be caused by observed trends in oceanic boundary forcing. Experiments were carriedout using the NCAR atmospheric general circulation model with specified sea surface temperature (SST) andsea ice anomalies confined to the North Atlantic sector. The spatial pattern of the anomalous forcing was chosen
to be realistic in that it corresponds to the recent 40-yr trend in SST and sea ice, but the anomaly amplitude
was exaggerated in order to make the response statistically more robust. The wintertime response to both typesof forcing resembles the NAO to first order. Even for an exaggerated amplitude, the atmospheric response to
the SST anomaly is quite weak compared to the observed positive trend in the NAO, but has the same sign,
indicative of a weak positive feedback. The anomalies in sea ice extent are more efficient than SST anomalies
at exciting an atmospheric response comparable in amplitude to the observed NAO trend. However, this atmospheric response has the opposite sign to the observed trend, indicative of a significant negative feedback
associated with the sea ice forcing. Additional experiments using SST anomalies with opposite sign to theobserved trend indicate that there are significant nonlinearities associated with the atmospheric response.
The transient eddy response to the observed SST trend is consistent with the positive NAO response, with
the North Atlantic storm track amplifying downstream and developing a more pronounced meridional tilt. In
contrast, the storm track response to the observed sea ice trend corresponds to a weaker, southward-shifted,
more zonal storm track, which is consistent with the negative NAO response.

1. Introduction
Trends in climate variables have been the subject ofintense study in recent years. Of particular importanceis the question of whether the observed trends are attributable to natural variability or to anthropogenic forcing effects. Since the climate system is composed ofmany interacting components, such as the atmosphereand the ocean, a trend in one component could well becaused by trends in another component. For example,
the observed trend in atmospheric flow could be forcedby trends in oceanic surface conditions. Understanding
the interactions between different components of the* The National Center for Atmospheric Research is sponsored by
the National Science Foundation.
Corresponding author address: Dr. Gudrun Magnusdottir, Department of Earth System Science, University of California, Irvine,
Irvine, CA 92697-3100.
E-mail: gudrun@uci.edu

q 2004 American Meteorological Society

climate system would greatly help us in interpreting theobserved climatic trends.
In this study, we focus on one particular form ofinteraction, that between the atmosphere and the ocean,in the North Atlantic region. The North Atlantic Oscillation (NAO) is the dominant mode of atmospheric lowfrequency variability over the North Atlantic and adjacent continents during the winter season (e.g., Hurrell1995). It is characterized by a seesaw in mass between
the subpolar low and the subtropical high. A positive
NAO index refers to exaggerated pressure extrema inthese two semipermanent systems. A negative NAO index refers to the reverse situation. On interannular andshorter time scales the NAO is thought to be primarily
driven by internal atmospheric variability (Saravanan1998). On longer time scales it is probably forced, atleast in part, by other components of the climate systemsuch as the ocean and sea ice. Changes in the NAO go
hand in hand with changes in the atmospheric distribution of temperature, precipitation, storminess, andother features of the atmospheric circulation (e.g., Hur-

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FIG. 1. (a), (b), (c) The 40-yr trends in winter-mean (DJFM) SST, sea ice concentration, and 500-hPa geopotential
height, respectively. Positive contours are solid, negative contours are dashed–dotted, and the zero contour is suppressed.
Note that the projection in (a), (b) is polar stereographic but the figures only include the Arctic Ocean and North Atlantic
Ocean north of 308N. In (a), the least squares trend in SST is for the period 1954–94. Contour interval is 0.2 K. In (b),the trend in sea ice concentration is for the period 1958–97 in % (40 yr)21. Contour interval is 10%. In (c), the leastsquares trend in 500-hPa geopotential height is for 1954–94. Contour interval is 25 m. Panel (d) shows the first EOF
of the DJFM-mean 500-hPa geopotential height field in the control simulation. Contour interval is 10 m.

rell and van Loon 1997). Stephenson and Pavan (2003)
recently investigated the NAO and its variability in 17
coupled climate models and compared the results to theobservational record. To avoid getting embroiled in semantics let us clarify terminology. We shall use the term
NAO for the Arctic Oscillation (AO) as well as the
NAO. The area of influence of the AO is the entire polar
cap, whereas the NAO is limited to the North Atlantic
and surrounding coastal areas. Some studies suggest that
there are fundamental differences between the two terms(e.g., Ambaum et al. 2001), while others argue that they
are simply different characterizations of the same phe-nomenon (e.g., Wallace 2000). Here, we use the term
NAO even though the area considered may be the entire
polar cap.
We consider the observed linear trend over a recent
40-yr period in three different climatic variables: the500-hPa geopotential height, sea surface temperatures(SSTs), and sea ice concentration (Figs. 1a–1c). For the
500-hPa height and SST, the linear trends were computed by least squares fitting of a straight line to boreal
winter (December–March) means of the climatic variables from 1954 to 1994. The geopotential height data
were obtained from the National Centers for Environ-1 MARCH 2004

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mental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay et al. 1996),
the SST data from version 2 of the Global Sea Ice and
Sea Surface Temperature (GISST2) dataset (Rayner etal. 1995). The sea ice concentration trend is for theperiod 1958–97, and is taken from Deser et al. (2000).
The trend in winter-mean, sea ice concentration is a
drastic reduction in sea ice east of Greenland over the
40-yr period, and a lesser increase west of Greenlandand into the Labrador Sea. The SST trend has an extensive area of cooling in the subpolar gyre that is of
maximum amplitude 1.5 K, a lesser warming off theeast coast and a lesser yet warming in the far northeastern Atlantic. Note that the 500-hPa height trend pattern (Fig. 1c) has a significant projection onto the NAO
spatial pattern, consistent with the decadal trends toward
a more positive NAO noted by Hurrell (1995). For comparison, in Fig. 1d we show the first EOF of the wintermean 500-hPa geopotential height for a control simulation in our atmospheric general circulation model(AGCM) where SST and sea ice extent have a climatological annual cycle that is repeated every year. Notethe similarity of the spatial patterns in Figs. 1c and 1d,especially over the North Atlantic and adjacent continents.
After inspecting Fig. 1, one may pose the question:
Were the trends in the SST and sea ice caused by theobserved trends in atmospheric flow, or were the trends
in the atmospheric flow caused by the trends in SST
and sea ice? Atmospheric forcing of the ocean tends todominate air–sea interaction in the mid- and high latitudes (Deser and Timlin 1997; Frankignoul et al. 1998;
Saravanan 1998). Therefore, to a first approximation,
one may expect that the SST and sea ice trends are justa response to the atmospheric trends. Indeed, Seager etal. (2000) and Deser et al. (2000) invoke atmosphericforcing to explain the observed variability in SST and
sea ice, respectively. However, there is still the possibility that there is a significant feedback associated withthe atmospheric response to the oceanic trends, although
this may not be the dominant form of interaction. In
particular, we would like to know if the atmospheric
response to the oceanic trends has the same spatial pattern as the observed atmospheric trend. If that were thecase, it would be indicative of a positive feedback inthe climate system. The results of Rodwell et al. (1999)
and Peng et al. (2002) would seem to suggest that there
is a weak positive feedback. However, there are significant subtropical and tropical components to the SST
anomalies used in these studies, making it difficult todetermine if the feedback is truly extratropical. If theatmospheric response had the opposite sign to the observed trend, it would be indicative of a negative feedback. In contrast to the above two studies, a recent study
by Schneider et al. (2003) finds little resemblance between the observed atmospheric trend over the North
Atlantic and the simulated ensemble mean of North Atlantic atmospheric response in experiments forced by859

the observed trend in global SSTs. In the present study
and a companion study (Deser et al. 2004, hereafterreferred to as Part II), we analyze a series of AGCM
experiments that examine the winter response to observed trends in lower boundary conditions in the extratropical North Atlantic. We consider the response toboth SST anomalies and sea ice anomalies.
The atmospheric response to extratropical SST anomalies has been the subject of numerous observationaland modeling studies. However, this response is still
poorly understood, largely due to the large internal variability of the midlatitude atmosphere, which tends to
obscure any direct effect of the SST anomaly. Kushnir
et al. (2002) summarized observational and modelingstudies of the atmospheric response to isolated midlatitude SST anomalies. The response of AGCMs to interannual SST anomalies is weak, but not negligible,
and sometimes nonlinear to the amplitude and sign ofchange. The response may also be nonlinear in termsof geographical regions, such that the effects of isolated
SST anomalies in different regions may not be additive.
Several modeling studies have found that the response
is highly sensitive to the location of the SST anomaly
relative to the storm track and the mean jet, as well as
to the jet strength. This result is rather worrisome inlight of the fact that some of the models have significant
errors in the location and strength of these features.
Thus, results tend to be model dependent. The AGCM
that we use, version 3 of the Community Climate Model(CCM3), has been found to produce realistic simulationsof the extratropical mean winter circulation and its variability (e.g., Hurrell et al. 1998; Saravanan 1998; Magnusdottir 2001).
The effect of sea ice anomalies on the atmosphericflow has received less attention than the effect of midlatitude SST anomalies. Many earlier studies used idealized sea ice perturbations, such as removing all of thesea ice or changing its extent or concentration in a zonally symmetric manner, to force the atmosphere (e.g.,
Simmonds and Budd 1991; Murray and Simmonds
1995; Menendez et al. 1999). Some recent studies havebegun using sea ice perturbations derived from observed
anomaly patterns to force the atmosphere. Honda et al.
(1999) used sea ice anomalies based upon observed extreme conditions of heavy and light sea ice cover in the
Sea of Okhotsk, with some exaggeration of the spatial
extent of the anomaly. Alexander et al. (2004) used
actual observed sea ice anomalies, for specific seasonsthat had large anomalies, to force an AGCM.
What sets the current experiments apart from manyother AGCM studies is the realistic spatial structure of
the boundary forcing, and the parallel investigation of
the relative roles of SST and sea ice forcing. The spatial
structure of the SST and sea ice anomalies is based onthat of the recent 40-yr trends (Figs. 1a,b), restricted to
the North Atlantic (NA) region only. We investigate theresponse with respect to amplitude and polarity of the
SST forcing. For each polarity of SST forcing, we con-

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FIG. 2. (a) SST anomaly for the month of Feb for the case SST15 (corresponding to bicentennial
SST trend). Contour interval is 1 K, positive contours are solid, negative contours are dashed–dotted, the zero contour is suppressed. (b) Sea ice anomaly for the month of Feb for the case
ICE2. Light shading indicates that sea ice is added, dark shading indicates that sea ice is removed.
The projection is the same as in Figs. 1a,b.

sider two amplitudes, corresponding to centennially andbicentennially scaled trends. We examine two amplitudes of sea ice forcing and we separately examine thetwo major regions of the exaggerated amplitude, sea ice
forcing. The amplitude of sea ice forcing is harder toquantify than that of SST forcing since the model assumes that either there is sea ice or there is open ocean
at a given grid point. Therefore, we only consider thetrend in the extent of sea ice, not in its concentration,even though the trend in concentration is expected toplay an important role. The exaggerated sea ice anomaly
corresponds to approximately double the areal extent of
the trend in sea ice change over a recent 40-yr period.
When the SST is changed, the sea ice is held fixedat the climatological extent. Conversely, when we force
the model by changing the sea ice distribution, we hold
SST fixed at the climatological value. We have usedexaggerated forcing amplitudes because the atmospheric
response to midlatitude SST and sea ice anomalies isrelatively weak, that is, when compared to the amplitudes of internally generated atmospheric variability.
The forcing amplitudes that we have used allow us toobtain a statistically robust response with about 60 yr
of model integration.
The outline of this study is as follows: section 2 gives
an overview of the model and the numerical experiments. Section 3 examines the midtropospheric response, both in terms of winter-mean and monthly meangeopotential height. Section 4 contains a more thoroughexamination of results for the December–January–February–March (DJFM) mean response in various fields
including surface energy flux, precipitation, the lowerlevel temperature, the upper-level flow, and the storm

track response as seen in time-filtered (co)variancefields. Finally, section 5 contains some concluding remarks.
A companion study (Part II) uses an EOF decomposition technique to provide a detailed analysis of the
response in terms of a directly forced component versus
a component produced by the projection of the responseon the internal variability of the model.
2. Model and experiments
The numerical model is the NCAR CCM3 in the standard configuration as detailed in Kiehl et al. (1998). The
model resolution is T42 with 18 vertical layers in a
hybrid-sigma coordinate system. This version of CCM
presents major improvements over earlier versions especially in terms of the physical parameterizations resulting in a more realistic thermal structure and hydrologic cycle. Hack et al. (1998) present a comprehensive
study of the simulated hydrologic and thermodynamic
characteristics of CCM3 based on a 15-yr integration
using observed monthly mean SSTs from 1979 to 1993.
Hurrell et al. (1998) use the same 15-yr simulation to
examine the representation of the dynamical fields by
CCM3. This simulation is almost identical to our control
case, CTRL, which is an 84-yr simulation using 1 yr ofclimatological monthly mean SSTs that are repeatedeach year. The instantaneous dynamical fields are saved
twice per day. Additional fields are saved as daily andmonthly averages. Magnusdottir (2001) analyzed therepresentation of Northern Hemispheric (NH) storm
tracks in the control simulation as compared to NCEP
reanalysis. They found that compared to other AGCMs,

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TABLE 1. The different numerical experiments and the imposed oceanic boundary conditions in SST and in sea ice. SST clim refers to theclimatological SST, NAtrend refers to the 40-yr trend in SST in the extratropical North Atlantic. SICE clim refers to the climatological sea ice
extent in the North Atlantic and Arctic Ocean. Here Etrend and Wtrend refer to the 40-yr trend in sea ice extent, east and west of Greenland,
respectively. The max response in 500-hPa geopotential height (m) in each case is shown in the last column.
Experiment nameMonthly SST

Monthly sea ice extent

Max 500-hPa (m)geopotential response

CTRL
SST12.5
SST15
SST22.5
SST25
ICE1
ICE2
ICELABICEGRN

SSTclim
SSTclim 1 2.5 3 NAtrend
SSTclim 1 5 3 NAtrend
SSTclim 2 2.5 3 NAtrend
SSTclim 2 5 3 NAtrend
SSTclim
SSTclim
SSTclim
SSTclim

SICEclim
SICEclim
SICEclim
SICEclim
SICEclim
SICEclim 1 Wtrend 1 Etrend
SICEclim 1 2 3 (Wtrend 1 Etrend )SICEclim 1 2 3 Wtrend
SICEclim 1 2 3 Etrend

0
221
230
42
82
52
91
239
106

the North Atlantic storm track is quite well represented
in CCM3. Its strength (in terms of high-pass-filteredtransient eddy streamfunction variance) is slightly underestimated and its shape tends to be slightly too zonal
over the mid- to eastern North Atlantic.
The prescribed lower boundary condition is determined from monthly mean SST fields, linearly interpolated in time between months. Sea ice is prescribedin the model whenever the SST goes below the thresholdvalue of 21.88C. Since sea ice is not explicitly represented in the model, only surface properties such as
albedo and the surface energy fluxes change when thesea surface is covered by ice. We use two different
boundary forcings, that of SST anomalies and that ofsea ice anomalies. When forcing the model with SST
anomalies, we hold the sea ice extent constant at climatological values. When forcing with sea ice anomalies, we hold the SST distribution constant at climatological values. The anomalies are calculated for eachcalendar month. For most of the year the boundaryforcing anomalies in each case are quite similar. Thus,
we only show these fields for one month, that of February.
Figure 2a shows the spatial structure of the SST perturbation that is added to the SST for February. This
structure is based on the least squares linear trend in
the GISST2 dataset for the same month (Rayner et al.
1995), but only for the years from 1954 to 1994. (Theentire dataset extends from 1903 to 1994). The trend
was computed for the NA region, north of 208N, andthe SST anomaly corresponds to the pattern of the trend(scaled by a factor of 5 in Fig. 2a) north of 308N. The
SST anomaly was set to zero at 208N and constrained
to vary linearly between 208 and 308N. The familiar
structure of the North Atlantic tripole of SST variability(e.g., Kushnir et al. 2002, and references therein) is
evident from the figure. As displayed in the figure, thetrend is scaled to correspond to an equivalent bicentennial trend in SST. The different experiments vary interms of the amplitude of the perturbation, not its spatial
structure. The term ‘‘trend factor’’ is used to refer tothe factor by which the 40-yr trend in SST is multipliedin each experiment before adding it to the SST field.
We conducted five different experiments, characterized
by trend factors 0, 2.5, 22.5, 5, and 25, which we name
CTRL, SST12.5, SST22.5, SST15, and SST25, respectively. We shall primarily discuss results from thetwo SST-forced cases: SST25 and SST15.
We conducted four experiments where the sea ice
extent was changed, but the SST was held fixed at climatological values. As in the case for SST forcing, we
considered an exaggerated anomaly, that was based on
the 40-yr monthly trend in sea ice distribution in the
North Atlantic/Arctic region from Deser et al. (2000),
but the areal extent of the anomaly was approximately
doubled. Figure 2b shows the February sea ice anomaly
for this exaggerated case that we term ICE2. The dark
shaded area indicates removal of sea ice, the light shaded
area indicates that sea ice is added. The anomaly has
decreased sea ice east of Greenland and increased sea
ice west of Greenland and into the Labrador Sea. We
ran an experiment that we term ICE1 that has about half
the areal extent of the sea ice anomaly of ICE2 andcorresponds more closely with the 40-yr trend. We ran
two additional experiments, one where we only applied
the sea ice forcing of ICE2 west of Greenland (increased
ice extent in Fig. 2b), termed ICELAB, and the otherwhere we only applied the forcing east of Greenland(removed sea ice), termed ICEGRN. We shall primarily
focus attention on the case ICE2.
All experiments were run for at least 61 yr. The experiments CTRL and SST15 are two decades longer.
Table 1 summarizes all nine experiments. The 40-yr SST
trend is denoted by NAtrend , the sea ice trend east ofGreenland is denoted by Etrend , and that west of Greenland is denoted by Wtrend . For both sets of experiments,
the boundary forcing for February, which is shown in
Fig. 2, is a good representation of the forcing applied
over the entire winter season. The last column in Table
1 shows the maximum (or minimum for negative numbers) response in 500-hPa geopotential height in eachcase. The value of this number gives a good indicationof the robustness of the response in many other fields.
This is further discussed in the next section.

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FIG. 3. DJFM-mean response in 500-hPa geopotential height for (a) SST12.5, (b) SST15, (c) SST22.5, (d)SST25, (e) ICE1, (f ) ICE2, (g) ICELAB, and (h) ICEGRN. Contour interval is 10 m. Positive contours are solid,
negative contours are dashed–dotted, and the zero contour is suppressed.

3. The large-scale midtropospheric response
The response in any field is obtained by subtracting
the mean of the field in the control from the mean of
the field in the perturbation experiment. We take thewinter season to include December–March. This choicefor the extent of the winter season was guided in partby the first EOF of 500-hPa height for the control case,in this instance computed only over the NA basin (where
the boundary forcing is applied). It clearly corresponds
to the NAO for those four months, whereas for November and April that was not the case.
The response in geopotential height is equivalent barotropic in the free atmosphere. The winter-mean response in 500-hPa geopotential is shown in Figs. 3a–h
for all cases. The response is statistically significant at
95% according to a t test roughly for absolute values
greater than 10 m (not shown). Overall, the pattern of
response is reminiscent of the first EOF of geopotential
height in CTRL (Fig. 1d), at least over the polar cap
and farther south in the North Atlantic and adjacentcontinents. For the SST experiments (Figs. 3a–d) a farstronger (and opposite) response is obtained when we
subtract the anomaly in Fig. 2a, which corresponds toa positive SST anomaly in the subpolar gyre, than when
we add it to the climatological SST field. Thus the response is nonlinear in the polarity of the SST anomaly.
The response in the two former cases (SST22.5 andSST25) corresponds to positive height anomalies overthe polar cap with negative anomalies farther south in
the North Atlantic. For this polarity of the SST forcing,where we subtract the SST trend (Figs. 3c,d), the response appears quite linear in amplitude of forcing. That
is not the case for the experiments where the trend is
added as can be seen from Figs. 3a,b and from the thelast column of Table 1, which gives the greatest amplitude of the response in each case. To briefly summarize: the experiments that are forced by SST anomalies that are in the same sense as the trend in SST (Figs.
3a,b), show a 500-hPa geopotential height response thatis of similar spatial pattern to that of the trend in 500hPa geopotential shown in Fig. 1c, but of smaller amplitude. This occurs even though the amplitude of the1 MARCH 2004

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863

FIG. 3. (Continued )SST anomaly pattern has been amplified fivefold in experiment SST15 (Fig. 3b). This is indicative of a relatively weak positive feedback, consistent with resultsof Rodwell et al. (1999) and Peng et al. (2002).
For the two sea ice experiments, ICE1 and ICE2
(Figs. 3e,f), the sign of the response is opposite to thatof the positive trend-factor SST cases, or positive overthe polar cap and negative farther south. The amplitude
of response in ICE2 is considerably greater than for
SST15, but still somewhat smaller than the trend in
500-hPa geopotential height (Fig. 1c). This indicates anegative feedback. We did not perform experiments withcombined SST and sea ice forcing in the initial set ofexperiments, but based on the strength of the sea ice
forced response compared to that forced by the SST
trend one might conclude that the overall feedback is
negative. Later we found that this is indeed the case.
However, it can be dangerous to assume any type of
linearity. For example, it is striking how similar the
response of ICEGRN (Fig. 3h), where the forcing is
confined to sea ice removal east of Greenland, is to thefull, exaggerated forcing, sea ice experiment (ICE2),
which in addition to the above includes an area of in-creased sea ice southwest of Greenland. By contrast, theresponse in experiment ICELAB (Fig. 3g) does not havethe same spatial pattern and is of considerably smaller
amplitude and opposite sign. In fact, for ICELAB only
the region of negative response over the southern tip ofGreenland and surrounding ocean is statistically significant at 95% according to a local t test. The response
in other experiments was substantially more robust according to this test.
We want to explore further the similarity of the general pattern of response of the 500-hPa geopotential to
the first EOF of the DJFM-mean 500-hPa height in
CTRL. This EOF (Fig. 1d), which corresponds to the
NAO, explains 32% of the variance. The second EOF
corresponds to the Pacific–North American (PNA) pattern and explains 13% of the variance. The domain for
the EOF calculation was the Northern Hemisphere,
north of 308N. We ask if there is a substantial shift ofan NAO index in the three large forcing-amplitude experiments (SST15, SST25, and ICE2). Since the polarity of the EOF in Fig. 1d corresponds to a positive
NAO, we simply project the response time series in eachcase onto this pattern to obtain the shift in NAO index.

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FIG. 4. Histograms resulting from the projection of the time series of DJFM-mean response in 500-hPa geopotential height in each caseonto the first EOF of the DJFM-mean 500-hPa geopotential height in the control case (CTRL). The horizontal axis is labeled in std devs,
the vertical axis indicates number of samples (winters). The vertical line indicates zero std dev. For consistency between different cases,
only the first 61 yr of each time series was used. (a) Case SST25. The mean is shifted to 20.75. (b) Case SST15. The mean is shifted to
10.31. (c) Case ICE2. The mean is shifted to 20.92. (d) Control case for comparison. The mean is at 0.028.

In Fig. 4 we plot the histograms of the resulting projected time series for the four cases: SST25 in (a),SST15 in (b), ICE2 in (c), and CTRL in (d), for comparison. (In this instance, we only use the first 61 yr ofeach time series for consistency between cases.) The
vertical dashed–dotted line in the plots indicates zerostandard deviation (s), and as expected the mean of
CTRL is zero. For SST25 in (a) the mean is shifted to20.8 s, for ICE2 in (c) it is shifted to 20.9. The shift
for the mean of SST15 is much less or 10.3 s. Thus,in both experiments, SST25 and ICE2, the shift of the
NAO index is almost of a standard deviation to negativevalues whereas in experiment SST15 the shift is onlya third of that, and to a positive value. Note that thismethodology assumes that the NAO in all the experiments maintains the same spatial structure and same
variance as CTRL. It assumes that only the mean may
shift.
The month to month variability in 500-hPa geopotential response was quite pronounced in the different
cases, especially between the months of February andMarch. In Fig. 5 we show this monthly response for thefour winter months for the SST25 case. The largest
response is reached at the end of winter in March (Fig.
5d). The largest 500-hPa geopotential response was alsoreached in March in the ICE2 experiment. In contrast,
the SST15 experiment showed the largest geopotential
response in February and the smallest response in March.

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865

FIG. 5. Monthly mean response in 500-hPa geopotential height for SST25: (a) Dec, (b) Jan,(c) Feb, (d) Mar. Contour interval is 10 m, positive contours are solid, negative contours aredashed–dotted, and the zero contour is suppressed.

4. The mean winter response
Here we examine further the winter-mean response.
First we consider the local response in surface energy
flux, precipitation as well as the thermal and geopotential response in vertical cross sections along a fixed
latitude. We then examine the upper-tropospheric response. Of particular interest is how the storm track
responds in relation to the midtropospheric, mass-field
response, and how transient eddy feedback may be modifying the response in each case.
a. The local response
The response in net surface energy flux (radiative,
latent, and sensible) is shown in Figs. 6a,b,c for cases
SST25, SST15 and ICE2, respectively. For comparison, Fig. 6d shows the net surface energy flux for CTRL.
The response in the experiments forced by SST anomalies show the familiar negative feedback in surface flux
(Barsugli and Battisti 1998), such that the response towarm SST anomalies is increased net flux into the atmosphere, and decreased surface flux for negative SST

anomalies. Note that the response in these two experiments is not equal and opposite. The surface response
to positive SST anomalies is stronger, however the spatial pattern is quite similar. The spatial pattern of the
response is also similar for the two cases that have SST
anomalies corresponding to the centennial positive andnegative SST trend (SST12.5 and SST22.5, notshown), but the amplitude is not simply half that of thecorresponding bicentennial case, rather it is smaller.
A different sea ice distribution corresponds to isolating the atmosphere from the ocean where sea ice isextended into regions where it was previously absent,
and opening the ocean surface to the atmosphere in
regions that were previously covered with ice. As shownin Fig. 6c, this results in a much more drastic response
in surface flux (note that the contour interval in Fig. 6cis double that in Figs. 6a,b). Where ice is removed, eastof Greenland, the surface flux has a large positive response, followed by a negative response downstream.
Where sea ice is extended into the Labrador Sea, theresponse in surface flux is strongly negative, followed
by a positive response downstream. The fact that the866

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FIG. 6. DJFM-mean response in net surface energy flux (the projection is the same as in Figs.
1a,b): (a) SST25, (b) SST15, (c) ICE2. Contour interval is 50 W m22 in (a), (b); and 100 W
m 22 in (c); negative contours are dashed–dotted; and the zero contour is suppressed. (d) Net
DJFM-mean surface energy flux in the CTRL simulation. Contour interval is 100 W m 22 .

response in surface energy flux is strongly positive
downstream of where the sea ice has been extended
reflects the impact of isolating the atmosphere from theocean over the ice, such that it becomes cold and dry,
and when it gets advected over the open ocean there isa sudden burst in surface energy flux. The opposite applies downstream of areas that have been cleared of sea
ice. In the case ICELAB (not shown), the response insurface fluxes was almost identical to the part of the
response in ICE that is south of 638N.
Let us consider a longitudinal cross section through
578N, crossing the NA basin from 708W to 308E. This
latitude circle crosses through the center of the mostintense SST anomaly as seen in Fig. 2a. In Fig. 7, weshow the response in geopotential and temperature for
SST25 (Figs. 7a,c) and SST15 (Figs. 7b,d) in the longitude–height plane. The response in geopotential (Figs.
7a,b) clearly shows the equivalent barotropic nature of
the response, reaching maximum amplitude at tropopause level, above the maximum SST anomaly. The
warming in SST25 (Fig. 7c) decreases with height inthe troposphere. Above the tropopause the response intemperature is negative in this case. For SST15 (Fig.
7d) the cooling at the surface decreases with height andchanges to warming in the stratosphere. This differencein the temperature response leads to very different vertical development in the two cases. When the atmosphere is warmed from below (as in SST25), static

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FIG. 7. Cross sections through the longitude–height plane at 578N, extending from 708W to 308E, showing the DJFM response of (a), (c)SST25 and (b), (d) SST15. Negative contours are dashed–dotted. Response in geopotential is shown in (a), (b); contour interval is 5 m.
Response in temperature is shown in (c), (d); contour interval is 0.25 K.

stability is decreased leading to more vertical development, whereas with the cooling from below (SST15),
static stability is increased. This effect shows up clearlyin cross sections for heating rate (not shown) where theatmospheric response of positive heating rate extends
almost to tropopause level, whereas the response ofcooling has less vertical extent. This will be discussed
further in Part II of this study.
As might be expected, there is close correspondence
in each case between the response in total precipitation,
the vertically integrated total heating, and convective
cloudiness. The first is shown in Fig. 8. There is increased precipitation over the warm SST anomalies, decreased precipitation over the cold SST anomalies, withamplitudes of the former greater than those of the latter,for each anomaly pattern with both polarities. This may
be explained partly by the nonlinear dependence of saturation vapor pressure on temperature. Vertical stability

plays a more important role as discussed above. Downstream of the major NA SST anomaly, there is a smaller
SST anomaly of opposite sign in the region of the North
Sea (see Fig. 2a). The response in precipitation in thisarea shows up clearly, and surprisingly, the signal iseven stronger when this SST anomaly is negative insign (as it is in SST25). (The stronger response in
SST25 in this area can also be seen in cross sections
for heating rate.) This may indicate nonlocal control on
the precipitation in the area since positive SST anomalies generate a larger local response in precipitation
than negative SST anomalies. In fact, in the next section
we shall see that SST15 and SST25 respond oppositely
in storm track activity in this area.
The ICE2 case shows a strong positive precipitation
response where sea ice has been removed, east of Greenland. Immediately downstream of this area, precipitation
has decreased. Precipitation is also strongly reduced

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FIG. 8. DJFM-mean response in precipitation (the projection is the same as in Figs. 1a,b): (a)SST25, (b) SST15, and (c) ICE2. Contour interval is 0.5 mm day 21 , negative contours aredashed–dotted, and the zero contour is suppressed. (d) Net DJFM-mean precipitation in the CTRL
simulation. Contour interval is 1 mm day 21.

over the area where sea ice has been extended. We examined cross sections (not shown) of the response ingeopotential, temperature and heating rate, in this casethrough 718N, which is through the most extensive areaof sea ice removal within the NA basin. These crosssections revealed that in spite of the large response insurface flux, the heating was quite shallow, or confinedto the layer below 600 hPa. We attribute this verticalstructure to the large static stability that has to be overcome at this high latitude (see Part II of this study fordetails).
Finally, there is a broad area of weakly increaesd
precipitation over most of the Atlantic between 358 and
508N in the ICE2 case. This increased precipitation in

midlatitudes, along with the response in 500-hPa geopotential, is reminiscent of a negative NAO scenario.
We shall examine this further in the next section, in
terms of the storm track response.
b. The free tropospheric response
We shall focus on the mean upper-tropospheric response in terms of streamfunction, depicted by c , andderived or closely related fields. First, let us comment
briefly on data analysis and notation. We use square
brackets to represent a zonal average, the star to represent the deviation from the zonal average (e.g., x 5[x] 1 x*). The overbar represents a time mean over the1 MARCH 2004

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FIG. 9. DJFM-mean response in 300-hPa eddy streamfunction in 10 6 m 2 s 21 , contour interval
is 1: (a) SST25, (b) SST15, and (c) ICE2. Negative contours are dashed–dotted and the zero
contour is suppressed. (d) DJFM-mean 300-hPa eddy streamfunction in CTRL simulation in 10 6m 2 s 21 and the contour interval is 4.

four months (DJFM) of the entire time series (for eachcase), and the prime represents the deviation from thetime mean (e.g., x 5 x 1 x9). When we examine timemean fields that are quadratic in transient eddy variables(e.g., x9y9 ), it is implicit that the fields are time filtered
so that only variations of 2–8-day time scale are included.
The free tropospheric response is equivalent barotropic. Thus, there is close correspondence between theextratropical 500-hPa gepotential response seen in Fig.
3 and the 300-hPa streamfunction response (not shown).
By subtracting the zonal average of the mean streamfunction response in each case, we get a representationof the stationary eddy response. Figures 9a–9c show the
response in c * for the different cases; Fig. 9d shows
the c * field for the CTRL case. Even though the freetropospheric streamfunction response is the weakest in
the SST15 case, it results in slight downstream amplification of the NA stationary waves, seen in Fig. 9b.
This has important consequences for other fields in thiscase. The other two cases, SST25 and ICE2, depicted

in Figs. 9a and 9c, respectively, lead to a weakened NA
stationary wave pattern compared to CTRL. Both the
response leading to strengthened and weakened NA stationary waves is statistically significant at 95% according to a local t test.
The response in 300-hPa zonal velocity is shown in
Fig. 10. Again, the response for SST15 (Fig. 10b) has
the smallest amplitude, but it results in the downstream
amplification of the NA jet over northern Europe, sothat the jet (seen for the CTRL case in Fig. 10d) develops a more pronounced meridional tilt over the Atlantic in this case. Both SST25 and ICE2 result in a
jet at 300 hPa that is more zonally oriented, with reduced
wind speeds on its poleward side and increased windspeeds equatorward. This and the weakened stationary
waves described above are the usual accompaniment ofa negative NAO scenario (e.g., DeWeaver and Nigam
2000).
The storm tracks in the CTRL case, as depicted by
the high-pass-filtered 300-hPa streamfunction variance(c 9 2 ), are shown in Fig. 11d. The NA storm track shows

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FIG. 10. DJFM-mean response in 300-hPa zonal wind in m s 21 , contour interval is 1: (a) SST25,(b) SST15, and (c) ICE2. Negative contours are dashed–dotted and the zero contour is suppressed.
(d) DJFM-mean 300-hPa zonal wind in CTRL simulation in m s 21 and the contour interval is 5.

up as a maximum in this field stretching toward thenortheast from the East Coast of the United States acrossthe Atlantic. The response in this field for the cases
SST25, SST15, and ICE2, are shown in Figs. 11a,b,c,
respectively. Our focus here is on the region of andsurrounding the NA ocean where the boundary forcing
is applied. Up to this point, the response in various freetropospheric fields associated with SST25 and ICE2
have been rather similar, especially in light of the very
different boundary forcing. However, from this point
on, we note several differences in the response for thetwo cases.
The storm track response for SST25 (Fig. 11a) is
indicative of a poleward shift in that a secondary maximum develops across Greenland around 708N, storm
activity decreases south of that latitude belt to about
408N and then increases again, but by considerably less.
This signature is robust as it shows up almost identicallyin both halves of the 61-yr time series. Note that in thiscase the decrease in storm activity is more pronounced
than the increase because it reaches over a larger area.
The area of increased storm activity is located over amuch narrower part of the basin. Examining the baroclinic fields to determine what supports this change instorm activity, the response in 700-hPa temperature,
shown in Fig. 12a, is a warm anomaly with maximum
amplitude of 4 K, on the northern side of the positive
SST anomaly. The response pattern of the high-passfiltered 700-hPa northward transient eddy heat flux
y 9T9 , shown in Fig. 13a, is such that it is negative over
the area of positive SST anomaly and positive to thenorth, where storm track activity has increased. Thus,
there is divergence of transient eddy heat flux in thearea of maximum warming, which is familiar from otherstudies (e.g., Trenberth and Hurrel 1994; Magnusdottir
2001) and the temperature anomaly is maintained by
the mean flow. A very similar signature is found for thehigh-pass-filtered 850-hPa northward transient eddy
moisture flux. Thus, the response in the transient meridional energy fluxes supports the northward shift instorm track activity. Note that this response is at odds
with the classical view of a negative NAO type response
because it has been associated with a southward migration of the storm track (e.g., Wanner et al. 2001;

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871

FIG. 11. DJFM-mean response in 300-hPa streamfunction variance (c 9 2 ) in 10 13 m 4 s 22 , contour
interval is 1: (a) SST25, (b) SST15, and (c) ICE2. Negative contours are dashed–dotted andthe zero contour is suppressed. (d) DJFM-mean 300-hPa streamfunction variance in CTRL simulation in 1013 m 4 s 22 and the contour interval is 5.

Trigo et al. 2002; Rogers 1997). However, it should be
noted that the storm track as represented both by c 9 2
and y 9T9 is weakly amplified over the middle of the NAbasin, just south of 408N.
Let us consider the transient eddy response fields for
the ICE2 case. The 300-hPa streamfunction variance,
shown in Fig. 11c, depicts a general decrease in storm
activity over the NA basin, north of 508N and a smaller
amplitude increase tilted northeastward over the eastern
half of the basin south of about 558N. In this case theresponse in 700-hPa temperature (Fig. 12c) corresponds
to warming over an area that is restricted to west of thearea of ice removal, immediately off the east coast ofGreenland. There is an extensive area of smaller amplitude cooling south of this region, immediately southof the region where sea ice has been extended into theLabrador Sea. The 700-hPa northward transient eddy
heat flux, in Fig. 13c, shows a modest increase over thesouthern part of the area of cooling (south of 408N) anda much stronger decrease almost everywhere else over
the NA basin. There is a small area of increased transient

eddy heat flux east of Greenland. The (co)variance fields
described here are all robust, in that they are almost
identical in the two halves of the entire 61-yr time series.
The picture that emerges from this simulation (ICE2)
is that despite the warming of the low- to midtroposphere at high latitudes, the warming is mostly restricted
to the area over Greenland and farther west. Even
though there is a modest increase in transient eddy heat
flux east of Greenland, it is not in an area of high baroclinity (note the small amplitude of y 9T9 in this area
for the CTRL; Fig. 13d). One can speculate that werethe continental barrier of Greenland not in the way, theeddy response might be different (see also Kristjansson
and McInnes 1999). With the current land configuration,
the increased baroclinity east of Greenland is simply too
far removed from baroclinic energy sources for storm
activity to significantly increase.
The SST15 case turns out to be quite interesting interms of storm track activity. Figure 11b shows the response in terms of streamfunction variance. There isincreased storm track activity over the entire North At-

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lantic, especially at the downstream end of the storm
track, over the North Sea and northern Europe. The
response in 700-hPa temperature (Fig. 12b) is coolingover the entire polar cap, note that its amplitude is lessthan the warming for the SST25 case. The response intransient eddy heat flux is that of an increase right in
the area of high eddy heat flux in the CTRL case, thus
amplifying the storm track and leading to its downstream development. A similar signature was found in
the 850-hPa transient eddy moisture flux. Furthermore,
the features of the (co)variance fields described here
were robust in that they were almost identical in thetwo halves of the 80-yr time series.
One important question that we have not addressedis how the transient eddy response in each case may be
modifying the mean flow and thereby providing secondary forcing on the flow. Even though we shall notprovide a quantitative answer here, by using simple arguments, we can can get an indication of how the mean
streamfunction may be forced by this effect. Figure 14dshows the control-case field of barotropic forcing of themean streamfunction by the high-frequency transients.
This term is the more important of two terms that appear
as forcing on the streamfunction under the assumptionof quasigeostrophic, inviscid flow. Hoskins et al. (1983)
denoted this field by S , where S 5 2¹ 22 (= · v9z 9 ) or
equals the inverse Laplacian of the convergence of thetransient eddy vorticity flux. As seen in Fig. 14d, thisterm is particularly important at the downstream end of
the Pacific storm track, extending across North America,
the North Atlantic, and into Eurasia. Thus S is importantin the general area of the oceanic boundary forcing.
[Sections 2a,b of Magnusdottir (2001) contain moredetails on the physical relevance of this field as well as
a comparison of S from this control simulation (CTRL)
with S obtained from NCEP data.] Figures 14a–14c
show the response in this field for the three cases,
SST25, SST15 and ICE2, respectively. Even though
the inverse Laplacian leads to spatial smoothing, admittedly the response as seen in this term is quite noisy.
When we compared the two halves of the entire timeseries, certain features stood out and we shall concentrate on those. For SST25 and ICE2 the response in
S corresponds to weaker flow across the North Atlantic.
For SST15, the response in S corresponds to stronger
flow over the northeastern part of the North Atlantic,
close to 608N. This is consistent with the response inmean streamfunction as well as the mean zonal flow.
Thus we can infer that transient eddy feedback is important in these cases for the respective regions, eventhough we can only quantify this effect if we assume
an upper-level barotropic flow.
←
FIG. 12. DJFM-mean response in 700-hPa temperature (K), contour
interval is 0.5 K, and the zero contour is omitted: (a) SST25, (b)SST15, and (c) ICE2.

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FIG. 13. DJFM-mean response in 700-hPa transient eddy meridional heat flux (y 9T9 ; in K ms 21), contour interval is 2 (the projection is the same as in Figs. 1a,b): (a) SST25, (b) SST15,
and (c) ICE2. Negative contours are dashed–dotted and the zero contour is suppressed. (d) DJFMmean 700-hPa transient eddy heat flux in CTRL simulation (K m s 21 ) and the contour interval
is 5.

We have not attempted to provide a thoroughly comprehensive analysis of the storm track response in eachcase and our results are therefore not entirely conclusive.
However, in light of results on the indirect (or modal)
geopotential response and its deviation from the total
response (the direct or nonmodal response) presented inPart II, it is interesting that the storm track response isconsistent with those ideas. Thus, the two negative NAO
response experiments show common elements in thestorm track response, namely, a tendency for a more
zonal storm track that is also detected in observationsof negative NAO scenarios. This is likely associatedwith the indirect part of the response, whereas the manydifferences between the two storm tracks are likely associated with differences between the direct (or nonmodal) part of the response. The positive NAO case,
SST15, has a storm track response that is consistent
with observations of the positive NAO storm track,
namely, a more pronounced meridional tilt and downstream amplification. This we can likely attribute to theindirect or modal part of the response.
5. Concluding remarks
We have carried out a modeling study of the atmospheric response to oceanic boundary forcing in the874

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FIG. 14. DJFM-mean response in 300-hPa barotropic forcing of the mean streamfunction bytransient eddies (S ; in m 2 s 22 ), contour interval is 4, negative contours are dashed–dotted, andthe zero contour is suppressed: (a) SST25, (b) SST15, and (c) ICE2. (d) The S for CTRL
simulation in m 2 s 22, and the contour interval is 20.

North Atlantic region. We considered two kinds of forcing: SST anomalies and sea ice anomalies. We used theobserved multidecadal trends in SST and sea ice to motivate our choice for the spatial patterns of anomalous
forcing, thus ensuring that our forcing has ‘‘realistic’’spatial structure. However, we used exaggerated amplitudes for the strength of these anomalies to improve
the signal-to-noise ratio in our numerical experiments.
We find that even with exaggerated forcing amplitudes and integrations of at least 61 yr in length, there
is significant sensitivity of the response pattern to thecalendar month; that is, the February response was quite
different from the March response, even though theboundary forcing in each case is almost identical inwinter. Only by computing wintertime seasonal averages, were we able to obtain statistically robust patterns
for the atmospheric response to SST and sea ice anomalies. We expect that if we integrated longer, some ofthis subseasonal variability would disappear or the signal-to-noise ratio would be larger. However, some ofthe variability would remain because the backgroundflow is not the same from month to month.
Our primary finding is that the wintertime atmospheric response to the multidecadal trends in SST and
sea ice resembles the NAO, to first order. However, evenfor the exaggerated forcing amplitudes that we haveused, the atmospheric response to the SST trend patternis quite weak compared to the observed trend in atmospheric flow. For the observed sign of the SST trend,
the atmospheric response has the same sign as the observed trend. This is indicative of a weak positive feedback on the NAO, and is consistent with the SST forcing
results of Rodwell et al. (1999) and Peng et al. (2002).
We find that sea ice anomalies are more efficient at
exciting an atmospheric response than the SST anomalies, for the forcing amplitudes that we have considered. For the observed sign of sea ice trend, the atmospheric response has the opposite sign to the observed atmospheric trend, but is comparable in amplitude. Taking into account the factor of 2 exaggeration

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in the extent of the sea ice anomaly, we conclude thatthe atmospheric response to the observed sea ice trend
is about half the amplitude of the observed trend in 500hPa height, but the sign of the response is opposite to
the atmospheric trend, thus the feedback is negative.
However, there is an important caveat. We have only
considered anomalies in the extent of sea ice and not
in its concentration. Other studies (e.g., Murray andSimmonds 1995; Alexander et al. 2004) have noted thatchanges in ice concentration (i.e., allowing for grid boxes over the ocean that are partially covered by sea ice)
can also play an important role in determining the atmospheric response. Alexander et al. (2004), who used
observed sea ice anomalies to force the atmosphere,reach a similar conclusion as to the sign of the feedback.
Because response to the SST anomalies is weak, we
expected the overall response to the combined SST and
sea ice trends to be dominated by the response to sea
ice forcing. Indeed, that turns out to be the case in one
additional experiment, which is forced by combining
the SST anomalies corresponding to the equivalent bicentennial trend (of SST15) and the exaggerated sea
ice anomalies (of ICE2). The response in this experiment is almost identical to that in ICE2 in all fields.
This confirms our expectation that the sea ice boundary
forcing in the North Atlantic sector dominates the atmospheric response and nonlinear interactions between
the response to the two different types of boundary forcing are inconsequential. Since the atmospheric circulation is thought to force the observed variability in sea
ice (Deser et al. 2000) as well as in SST (Seager et al.
2000) over recent decades, during which the atmospheric circulation has been characterized by a positive NAO,
our modeling study suggests that the atmospheric response to observed SST and sea ice trends acts as asignificant negative feedback on the whole North Atlantic climate system.
Although there are gross similarities between the atmospheric response to SST and sea ice trends and theNAO, there are also significant differences in the details.
In particular, we show in Part II of this study that one
can decompose the total atmospheric response into a
direct response and an indirect response, with only thelatter bearing a close resemblance to the NAO. Anotherimportant result that emerges from our study is that there
is substantial nonlinearity in the atmospheric response
to SST anomalies. Positive SST anomalies are more
efficient at exciting a strong atmospheric response whencompared to negative SST anomalies. This issue is also
explored in more detail in Part II of the study.
We find some interesting features in the storm track
response to oceanic boundary forcing. Based upon theobserved relationship between the NAO and the Atlantic
storm track, one would expect the positive NAO phase
to be associated with a more meridionally tilted storm
track. For the negative NAO phase, one would expect
the storm track to be more zonally oriented. We findthat the storm track response to SST and sea ice anom-alies exhibits the same sensitivities. When forced withthe observed sign of the sea ice trends, the storm tracktends to be more zonally oriented, corresponding to thenegative NAO response. When forced with the observed
sign of the SST trend, the storm track exhibits an increased meridional tilt, as expected from the weak positive NAO response. The spatial structure of the transient eddy forcing associated with the storm track response is consistent with the forcing needed to explain
the tropospheric flow response, underscoring the importance of the transient eddies, as noted in other studies(e.g., Kushnir and Lau 1992; Peng and Whitaker 1999).
Although we have tried to address some of the important questions regarding the atmospheric response to
SST and sea ice trends in the North Atlantic, there arestill several outstanding questions. For example, wehave not computed the atmospheric response to the actual trends in SST and sea ice over the last 40 years,
without any exaggeration in amplitude. While this iscertainly of great interest, more realistic experiments
would require significantly larger computational resources so that statistically robust results may be obtained.
Acknowledgments. The authors wish to thank Xia-Lin
Ma for programming support, Mike Alexander for helpful comments on the original manuscript, and threeanonymous reviewers for helpful reviews. This work
was supported by NOAA OGP under Grants
NA96GP0420 and NA16GP2006, and NSF underGrants 9908883 and 0301800. An allocation of computer time was made by the SCD of NCAR.
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