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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, C05009, doi:10.1029/2009JC005334, 2010
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Atmospheric forcing of sea ice in Hudson Bay
during the fall period, 1980–2005
K. P. Hochheim1 and D. G. Barber1
Received 18 February 2009; revised 2 November 2009; accepted 18 November 2009; published 11 May 2010.
[1] The principal objective of this study is to describe the autumn sea ice regime of
Hudson Bay in the context of atmospheric forcing from 1980 to 2005. Both gridded
Canadian Ice Service (CIS) data and Passive Microwave (PMW) data are used to examine
the freezeup period for weeks of year (WOY) 43–52. Sea ice concentration (SIC)
anomalies reveal statistically significant trends, ranging from −23.3% to −26.9% per
decade, during WOY 43–48 using the CIS data and trends ranging from −12.7% to
−16.8% per decade during WOY 45–50 using the PMW data. Surface air temperature
(SAT) anomalies are highly correlated with SIC anomalies (r2 = 0.52–0.72) and with sea
ice extents (r2 = 0.53–0.72). CIS data show that mean sea ice extents based on SICs ≥80%
(consolidated ice) have decreased by 1.05 × 105 to 1.17 × 105 km2 for every 1°C increase
in temperature in late November; PMW data show similar results. Regression analysis
between SAT and standardized climate indices over the 1951–2005 period show that the
East Pacific/North Pacific index is highly predictive of interannual SATs followed by
the North Atlantic Oscillation and Arctic Oscillation indices. The data show that the
Hudson Bay area has recently undergone a climate regime shift, in the mid 1990s, which
has resulted in a significant reduction in sea ice during the freezeup period and that these
changes appear to be related to atmospheric indices.
Citation: Hochheim, K. P., and D. G. Barber (2010), Atmospheric forcing of sea ice in Hudson Bay during the fall period,
1980–2005, J. Geophys. Res., 115, C05009, doi:10.1029/2009JC005334.
1. Introduction
[2] Over the past several decades Arctic sea ice has
undergone significant changes in ice extent and concentration. In this paper we define sea ice extent (SIE) as the geographic distribution of sea ice (presence/absence) within the
study region and sea ice concentration (SIC) as the percentage
concentration of sea ice within a particular subset of the study
area. From 1953 to 2006 the total SIE at the end of the
summer melt season in September declined at a rate of
−7.8% per decade [Stroeve et al., 2007]. The trends in SIC
vary depending on the time period examined and the geographic location. Passive microwave (PMW) data show that
trends in SIC during the 1979–1996 period were relatively
small throughout the Arctic, −2.2 and −3.0% per decade, in
contrast to the 1997–2007 period, which showed that declines
in SIC accelerated to −10.1 and −10.7% per decade [Comiso
et al., 2008].
[3] Deser and Teng [2008] showed that during the early
part of the PMW period (1979–1993), ice trends in the ice
marginal zones within the polar seas varied geographically.
During the winter the Labrador and Bering seas had large
positive trends in SIC; the Greenland and Barents seas and
1
Centre for Earth Observation Science, University of Manitoba, Winnipeg,
Manitoba, Canada.
Copyright 2010 by the American Geophysical Union.
0148‐0227/10/2009JC005334
the Sea of Okhotsk had large negative trends. In 1993–2007
SIC trends were consistently negative throughout the Arctic
and subarctic seas. Summer trends during the first half of the
satellite record showed negative trends in the eastern Siberian
Sea and positive trends in the Barents, Kara, and eastern
Beaufort seas, in contrast to the second half of the satellite
record, which was dominated by negative trends throughout
the Arctic.
[4] In Hudson Bay (HB) a number of studies have examined trends in SIE. Parkinson et al. [1999] showed that during
1979–1996, only very slight negative trends were detectable
within HB (including Foxe Basin): annual trends were
−1.4 × 103 ± 1.4 × 103 km2/yr; autumn trends were larger,
at −2.9 × 103 ± 3.6 × 103 km2/yr; and none of the seasonal
trends were statistically significant. Gough et al. [2004]
found no significant trends in freezeup dates for the fall
period in southwestern HB (1971–2003) using Canadian Ice
Service (CIS) data (Environment Canada, CIS daily analysis
ice charts; available at http://ice‐glaces.ec.gc.ca).
[5] Gagnon and Gough [2005], on the contrary, found
statistically significant trends in freezeup dates using point
observations. Of the 25 points used throughout HB during
the freezeup period, only 6 points, located in the northern
reaches of HB, showed statistically significant freezeup date
trends (based on an SIC ≥50%); results indicated that
freezeup was occurring 0.32–0.55 day/yr earlier (1971–
2003). Kinnard et al. [2006] showed no significant trends in
SICs based on CIS data from 1980 to 2004. The most recent
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work by Parkinson and Cavalieri [2008] showed statistically
significant annual trends for SIE in HB (including Foxe
Basin), with decreases of −4.5 × 103 ± 0.9 × 103 km2/yr
(or −5.3% ± 1.1% per decade); fall trends were −8.5 × 103 ±
1.9 × 103 km2/yr (or −12.93% ± 2.9% per decade).
[6] Gagnon and Gough [2006] used ice thickness data
from the CIS to examine trends in thickness. The data used
in their study were collected from the early 1960s to the
early 1990s (the data collection program was terminated in
∼1990). Temperature trends were predominantly negative
and ice thickness trends were predominantly positive in HB
during the fall and winter periods.
[7] The variations in SIC and SIE throughout the Arctic and
sub‐Arctic have been variously attributed to some combination of anthropogenic forcing due to greenhouse gases and
low‐frequency oscillations in atmospheric circulation and
associated positive feedback mechanisms [Johannessen et
al., 2004; Holland et al., 2006]. Interannual variations in
SIC anomalies in the Arctic from 1960 to the mid 1990s are
partly explained by variations in the Arctic Oscillation (AO)
and North Atlantic Oscillation (NAO) [Venegas and Mysak,
2000; Deser, 2000; Polyakov and Johnson, 2000; Comiso
et al., 2008; Deser and Teng 2008; Overland et al., 2008]
and their effects on ice circulation (ice export) [Rigor et al.,
2002], air temperature [Polyakov et al., 2003], and oceanic
heat transport [J. Zhang et al., 2004]. In addition to the
gradual warming of the Arctic over the last 50 years,
Lindsay and Zhang [2005] have also suggested that the
temporary phase change associated with the Pacific Decadal
Oscillation (PDO) together with the AO in 1988 may have
contributed significantly to the flushing of older ice out
of the Arctic. More recently, warming in the high Arctic
has accelerated, independent of any indices, even beyond
worst‐case scenarios using greenhouse gas forcing, suggesting that factors such as the sea ice‐albedo feedback
mechanism are contributing significantly to recent decreases
in SIE [Lindsay and Zhang, 2005; Holland et al., 2006].
[8] The HB region differs from the Arctic Ocean and
adjacent seas in that it is essentially a closed system and,
therefore, isolated from the effects of open‐ocean circulation
[Wang et al., 1994] (e.g., warm‐water intrusions and sea ice
export) and more reflective of atmospheric forcing, specifically changes in air temperature and winds. Interannual
variations in SIE in HB have been attributed largely to a
number of standardized hemispheric indices that are associated with characteristic wind, temperature, and precipitation
patterns. Wang et al. [1994] and Mysak et al. [1996] showed
that both the NAO and the Southern Oscillation Index (SOI)
were associated with peak SIEs in HB (1953–1993). Strong
positive NAOs were associated with a deepened Icelandic
Low, northerly winds, and lower temperatures over eastern
Canada, whereas negative NAOs were associated with
southerly winds and warmer temperatures. Years with strong
negative SOIs during the spring/summer/fall period were
associated with more ice production during the freezeup
period, with the largest negative SAT anomalies occurring
in August (cool summer); years with strong positive SOIs
tended to have positive temperature anomalies. The largest
sea ice anomalies within HB were associated with strong
negative SOIs during the summer and strong positive NAOs
during the winter. Prinsenberg et al. [1997], Kinnard et al.
[2006], and Qian et al. [2008] all showed that NAO vari-
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ability is the main factor controlling temperature variation in
the winter season over eastern Canada, with positive NAO
indices coinciding with early formation of sea ice in HB. In
addition to the NAO, Kinnard et al. [2006] showed that the
ice regime in HB was significantly correlated with the East
Pacific/North Pacific oscillation (EP/NP) index during the
spring (r = 0.63) and summer (r = 0.57), both being significant at the p < 0.05 level. A positive phase of the EP/NP index
corresponds to a high pressure located over Alaska/western
Canada and a low pressure over the central North Pacific and
eastern North America. This configuration acts to draw cool
Arctic air south to eastern North America including the HB
region.
[9] In summary, previous work has shown that the distribution of sea ice anomalies throughout the Arctic and
subarctic seas have not been uniform over the PMW satellite
record (1978 to now). This observation is significant for the
HB region and eastern Canada in general. Whereas much of
the Arctic was warming, the HB region was actually cooling
(1979–1993), hence the positive sea ice anomalies early in
the PMW record [Deser and Teng, 2008], the lack of significant statistical trends in SIE from 1979 to 1996 [Parkinson et
al., 1999], and the increasing sea ice thickness from 1960 to the
early 1990s [Gagnon and Gough, 2006]. More recent data
have shown that warming has occurred in HB since 1999–2003
[Gagnon and Gough, 2005; Ford et al., 2009; Laidler et al.,
2009] and that statistically significant negative SIC trends
are now evident in the Foxe Basin and HB [Parkinson and
Cavalieri, 2008].
[10] This paper seeks to build on previous work as it relates
to the HB region by examining both SIE and SIC and then
examining the possible atmospheric forcing mechanisms
linked to these sea ice metrics. In this paper we (1) provide
detailed gridded representations of SAT trends of the land
surrounding HB to provide a context for the observed
changes in SIC and SIE; (2) show the weekly evolution of
sea ice cover during the fall period from 1980 to 2005,
provide gridded maps of SIC trends over 1980–2005, and
provide SIC difference maps comparing the “cool period”
(1980–1995) to the “warm period” (1996–2005); (3) quantify
the relationship between SAT anomalies and SIC anomalies
and SIE; and (4) examine the relationships between SAT
anomalies and standardized atmospheric indices relevant to
the fall period in HB.
2. Methods
2.1. Study Area
[11] HB is a large, shallow, inland sububarctic sea; it
covers approximately 804,000 km2, and its mean depth is
<150 m [Prinsenberg, 1986] (Figure 1). HB is 95%–100%
ice covered during the winter months and typically ice‐free
during August–September. It has two openings: one to the
northwest via Roes Welcome Sound and the other east of
South Hampton Island into the Hudson Strait. HB is isolated
from open ocean circulation, therefore variations in sea ice
cover are largely a function of atmospheric forcing [Wang et
al., 1994]. Currents within HB are dominantly wind driven
and cyclonic at all depths, reaching a maximum in November
when the winds are strongest [Prinsenberg, 1986; Saucier
et al., 2004]. The circulation pattern in James Bay is also
cyclonic, driven by a combination of winds and runoff dilu-
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Figure 1. Study site map.
tion [Prinsenberg, 1986]. The HB basin drains an area of
3.7 × 106 km2 in North America and its freshwater discharge of ∼950 km3/yr represents 20% of the total annual
runoff to the Arctic Ocean [Déry and Wood, 2004]. During
the fall period SSTs are highest in the James Bay area and
southeastern HB, extending north along the east coast of
HB [Saucier et al., 2004]. This area is typically the last to
freeze up.
2.2. Surface Air Temperature (SAT) Data
[12] We use a SAT product known as CANGRID, developed for climate change studies by the Climate Research
Division of Environment Canada. It uses adjusted historical
Canadian climate data [Vincent and Gullet, 1999] that
account for changes resulting from reporting station system
changes. A full description of the Canada‐only data set is
provided by McKenney et al. [2005]. The CANGRID grid
data have a spatial resolution of 50 km and cover land
surfaces only.
[13] The CANGRID data used in this study consist of
monthly air temperature anomalies dating back to 1950, a
period when most of the stations in the region were observing
on a regular basis (E. Milewska, Environment Canada, personal communication, 2009). The bounds used to compute
the mean HB regional temperature anomalies (per month per
year) were 50°–65°N and 72.5°–100°W (Figure 2). The use
of temperature anomalies in gridding data has the advantage
of removing location, physiographic, and elevation effects.
Monthly temperature anomalies were computed for each
month per year relative to the 1980–2005 mean to match the
normals computed for sea ice data. A 3 month running mean
was applied to the monthly SAT anomaly data ending in
(including) the month of interest; the intent here was to
incorporate lead‐up SATs to obtain a (moving) seasonal
temperature index (anomaly) value. We tested both normality
and autocorrelation (assumptions of the general linear model)
and we found each to be sufficiently low to allow for use of
parametric analysis. SAT anomaly trends and their statistical
significance ( p; at 0.10, 0.05, and 0.01) were mapped based
on the least‐squares fit per grid point (n = 1128). The trend
maps intend to show the regional distribution of SAT
anomalies around HB.
[14] These temperature data were used (1) to examine
general temperature trends from 1950 to 2005, (2) to establish
relationships between SAT anomalies and HB‐wide mean
SIC anomalies and SIEs per week(s) of year (WOY; 1980–
2005), and (3) to examine the relationship between SAT
anomalies and atmospheric indices.
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
Figure 2. Surface air temperature (SAT) stations used to
create the CANGRD data of Environment Canada. The
dashed line delineates the area used to generate the regional
air temperature anomaly index for Hudson Bay (HB).
2.3. Sea Ice Data
[15] The SIC and SIE data were obtained from two sources:
CIS digital ice charts (available at http://ice‐glaces.ec.gc.ca)
and PMW data processed at the National Snow and Ice Data
Center [Cavalieri et al., 1996].
2.3.1. Canadian Ice Service (CIS) Data
[16] CIS ice charts are produced weekly from a variety
of sources, including aerial reconnaissance data, NOAA
AVHRR, RADARSAT‐1, and ENVISAT ASAR. GIS information from the U.S. National Ice Center and spatial data from
other national and international partners may be integrated to
produce the final product. Although the CIS data go back to
1970, the charts produced since the early 1980s are of more
consistent quality, owing to improvements in Earth observation technology. Data used in the study are from 1980 to
2005. For the HB area the CIS data have temporal limitations
in terms of doing ice climatology work, especially during the
fall period. Only WOY 43–48 have a consistent set of weekly
observations for the 26 year period being examined (Table 1).
[17] Each CIS data file was converted from its .e00 GIS
format to a 2.5 km2 resolution grid (n = 128,656) encompassing only those areas within HB (including James Bay)
that were consistently observed during the 26 year period
(see Figure 1).
[18] Sea ice anomalies for each grid point per year per
WOY were computed by subtracting the weekly SICs from
the 26 year means. To determine trends in sea ice concentration anomalies, a least‐squares linear regression was calculated for each grid point over the 26 year period, where the
slope of the regression indicates the trend per year following
[Parkinson et al., 1999; Galley et al., 2008; Parkinson and
Cavalieri, 2008]. Data were tested for normality and autocorrelation (assumptions of the general linear model) and
we found each to be sufficiently low to allow for use of
parametric analysis. We thus opted for the parametric general
linear model rather than a nonparametric equivalent. The
statistical significance of each trend per grid point was
computed and trends meeting the p = 0.1, 0.05, and 0.01
levels of significance were mapped.
[19] We noted a natural demarcation point in this time
series, and as a result we also subset this time series into
1980–1995 and 1996–2005. The 1996 segmentation was
chosen for two reasons: (1) the period prior to this year was
representative of a relatively cooler period dominated by
positive SIC anomalies and therefore provided a good contrast to the warmer period following 1995, dominated by
negative sea ice anomalies; and (2) there was a significant
change in technology with the introduction of RADARSAT‐1
data in 1996, which allowed for improved mapping of
nearshore areas owing to increased resolution and improved
detectability of new and young ice. The change in technology
explains the positive nearshore anomalies that appear during
the relatively warmer period (1996–2005).
[20] The SIC trend maps were supplemented with SIC
difference maps showing the mean differences in SIC over
1980–1995 versus 1996–2005. The statistical significance
of the differences between the two time periods was assessed
per grid point using a two‐tailed Student’s t test. Significant
differences were mapped at p = 0.1, 0.05, and 0.01 probability
levels for each WOY (43–48). Again, normality assumptions
were tested and the parametric approach was selected over
the nonparametric equivalent.
[21] Ice probability maps were also computed for SICs
≥20% and ≥80% per grid point. Each grid point per year/
week was classified as meeting (1) or not meeting (0) the
preceding criteria; those meeting the SIC criteria per grid
point/week were summed and divided by the number of
years within the observational window. The ≥20% SIC
probability maps depict the leading ice edge during freezeup,
while the ≥80% SIC probability maps are intended to depict
“consolidated ice” [after Galley et al., 2008]. Probability
maps were produced for each WOY for the entire time series
(1980–2005), in part to describe the freezeup sequence. Ice
probability difference maps were also generated using the
≥80% SIC data per WOY. Mean differences (and significance)
in SIEs using SICs ≥80% were computed for 1980–1995
versus 1996–2005.
Table 1. Week of Year and Associated Datesa
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a
WOY
Dates
43
44
45
46
47
48
49
50
51
52
01
02
22–28 Oct
29 Oct to 4 Nov
5–11 Nov
12–18 Nov
19–25 Nov
26 Nov to 3 Dec
4–9 Dec
10–16 Dec
17–23 Dec
24–30 Dec
1–7 Jan
8–14 Jan
WOY, week of year.
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
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2.3.2. Passive Microwave (PMW) Data
[22] Because of significant gaps in the observational record
of the CIS data during the freezeup period, from WOY 49 to
WOY 02, SIC data from PMW data [Cavalieri et al., 1996]
were used to supplement the CIS data, thus providing a
second estimate of change for the full freezeup period
(WOY 43 to 02) These data are provided in a polar stereographic projection and have a spatial resolution of 25 × 25 km.
[23] By use of the daily SIC data, a weekly data set was
created for WOY 43–02. Sea ice anomaly maps were computed per WOY using the 26 year mean (1980–2005) as the
baseline. SIC trends and significance were computed using
the anomaly data as they were for the CIS data. Although the
SICs computed from the PMW data are internally consistent,
it is well understood that these data tend to seasonally underestimate SICs relative to the CIS data [Agnew and Howell,
2003], especially in ice marginal zones and during freezeup
and melt conditions. Our use of anomalies rather than absolute
concentrations minimizes this problem of underestimation,
since we are in fact presenting relative (rather than absolute)
change. Even with these limitations, the PMW data set is one
of the best data sources available to monitor seasonal ice
cover on a weekly basis, as CIS data are not always consistently available. As with the CIS data, differences in SIE
were computed for WOY 46–52 based on SICs ≥60%, 1980–
1995 versus 1996–2005, and their statistical significance was
determined.
2.3.3. Sea Ice Thickness Data
[24] Ice thickness data have been collected in HB by the CIS
(Environment Canada; available at http://ice‐glaces.ec.gc.ca)
from the late 1950s to the early 1990s, when data collection
ended. Work published thus far [Gagnon and Gough, 2006]
has not included the recent warming trend. Data collection in
HB started again in 2002. The only station collecting ice
thickness is Coral Harbour in northern HB (R. Chagnon,
CIS, personal communication, 2008). Because of gaps in the
data, mean ice thickness, and SATs, comparisons were made
between the following time periods: 1980–1989 and 2002–
2007. Statistical significance of the mean differences was
computed using a two‐tailed Student’s t test.
from the Climate Diagnostics Center (National Oceanic
and Atmospheric Administration; http://www.cdc.noaa.gov/
ClimateIndices) for the AO index and from the Joint Institute
for the Study of the Atmosphere and Ocean (http://jisao.
washington.edu/) for the PDO index.
[27] Since the indices fluctuate on a monthly basis, longer‐
term seasonal means were computed leading the month of
interest. The AO and NAO means were computed based on a
4 month lead (ending in the month of interest); indices related
to the Pacific region were computed based on a 5 month lead
(SOI, PDO, and EP/NP). Recall that SAT anomalies used in
this study were based on a 3 month moving average, so the
4–5 month leads to establish the dominant seasonal phase of
an index and hence the dominant atmospheric circulation
pattern are reasonable.
[28] Correlations between standardized climate indices and
SAT anomalies were made interannually over several time
periods, 1951–2005, 1980–2005, and the “cool” and “warm”
episodes within 1980–2005. We tested the interannual data
for both normality and autocorrelation (assumptions of the
general linear model) and we found each to be sufficiently
low to allow for use of parametric analysis. Because of the
inherent variability of the indices and the varying periodicity
of each of them (e.g., the AO (and NAO) operates at 2 to 3.5,
5.7 to 7.8, and 12 to 20 year scales [Venegas and Mysak,
2000; Jevrejeva et al., 2003], and the PDO index displays a
periodicity at scales of 20 to 30 years [Lindsay and Zhang,
2005]), 5 year running means for both the index and SAT
anomalies were also used to look at more general trends, thus
complementing the interannual statistics. Although results
based on the running means meet most of the assumptions of
linear regression, the data are by definition autocorrelated
(Table 10). We therefore caution the reader to use the statistical relationships as evidence for the underlying processes
controlling these relationships rather than for hypothesis
testing. Using a running mean is consistent with the 5 year
running mean used by Déry and Wood [2004] and the 7 year
running mean used by Polyakova et al. [2006] to assess long‐
term trends in indices, versus precipitation, SATs, etc.
2.4. Hemispheric Teleconnections
[25] Hemispheric teleconnections were examined in the
context of interannual regional SATs during the fall period in
HB. Various climate indices have previously been identified
as potentially significant in relation to HB SATs, including
the NAO, AO, SOI, EP/NP index, and PDO. Details of how
each index functions are well presented in the literature and,
as such, are not repeated here. Each index has an associated
seasonal pressure and SAT pattern. A correlation map of each
index (in its positive phase) showing its associated 500 mb
geopotential heights and SATs were generated using Web
tools at the National Oceanic and Atmospheric Administration
Earth System Research Laboratory (http://www.cdc.noaa.gov/
data/correlation/index.html/) based on National Centers for
Environmental Prediction/National Center for Atmospheric
Research reanalysis data [Kalnay et al., 1996] for the period
1980–2005. The observed pressure and temperature patterns
are discussed in relation to the HB area.
[26] The monthly standardized teleconnection data were
downloaded from NOAA’s National Weather Service Climate Prediction Centre ftp site (NAO, EP/NP, SOI) and
3. Results
[29] Results are presented in the following order: (1) a
review of SAT trends in the HB region from 1950 to 2005,
to provide a context for the observed sea ice anomalies and
trends; (2) sea ice conditions and trends in HB from 1980 to
2005 and their relationship to basin‐wide SAT anomalies;
and (3) correlation of longer‐term fall SAT anomalies in HB
with observed variations in standardized teleconnections.
3.1. Hudson Bay Air Temperature Trends
[30] The trends in SAT anomalies (Figure 3) are based on
a 3 month running mean ending in the month of interest.
The temperature trends throughout HB and the surrounding
region are positive, indicating a warming of 0.2 to 1.8°C per
decade, depending on the month and location. In general, the
largest increases are on the eastern half of HB and the lowest
are along the southern coast of HB between the Nelson River
Estuary and James Bay.
[31] In October temperatures are warming from 0.6 to
0.8°C/decade around the northern and eastern coasts of HB
(at 95%–99% probability); lower SAT trends are evident on
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Figure 3. SAT anomaly trends (b) based on 3 month running means ending in (including) the month of
interest. Significance (p) of trends at 0.01, 0.05, and 0.10 levels.
the western side of HB (0.4 to 0.6/decade), with trends at
0.4°C generally being nonsignificant. November trends
increase to 1.0°C per decade to the north of HB and remain
statistically significant (95%), while the highest trends are
observed in Hudson Strait to the east (1.2°C/decade). The
highest SAT anomaly trends occur in December, ranging
from 1.1 to 1.4°C per decade (90%–95%) in northwestern
HB to 1.2 to 1.6°C per decade in the eastern portion of the
HB region (95%–99%). In January temperature trends
decrease to 0.4 to 0.8°C/decade in the north and northwest
(not statistically significant) and to 0.8 to 1.2°C per decade
along the southeastern coast of HB including James Bay
(significant at 90%–95% probability).
[32] These results show that the air temperature around HB
has been warming, particularly in the northern and eastern
portions. Figure 4 puts the gridded temperature trends into
context relative to longer‐term (1950–2005) mean SAT
anomalies around HB for the months of October to December.
It is evident from the graphs that (1) SAT anomalies for a
given month vary significantly interannually; (2) the temperature fluctuations have a cyclical nature (smoothing spline
fit l = 0.04778; minimal smoothing); and (3) temperatures
in the past have been relatively cooler, especially in the 1970s
to the mid 1990s, and have warmed significantly since the
mid 1990s, which is particularly evident in November and
December data (stiff smoothing spline l = 1612.676).
[33] Comparing all semidecadal mean temperature anomalies for October (Figure 4b), only the last decade (1996–2005)
is identified as being statistically different from the other
periods based on both the Student t test (two tailed) and the
Tukey‐Kramer honestly significant difference (HSD) test.
The mean temperature difference in HB for October, 1980–
1995 versus 1996–2005, is 0.99°C; the mean regional temperature trend computed over 1980–2005 is 0.5°C per decade
(p = 0.025); and the trend computed from the hinge point
(∼1989) to 2005 is 1.1°C per decade ( p = 0.0098).
[34] In November the semidecadal mean temperature
anomalies (Figure 4d) identify the 1996–2005 period as
being statistically different from the two preceding periods,
spanning 1970–1995, with the Tukey‐Kramer HSD test identifying 1996–2005 as the only statistically different period. The
mean temperature difference between the latter two periods is
1.44°C. The temperature trend averaged over the HB region
from 1980 to 2005 for November (Figure 4c) is 0.71°C per
decade (p = 0.056), computed from the inflection point
(∼1989); the temperature trend is 1.8°C per decade (p = 0.005).
SAT anomalies show a slight negative trend in SAT from
1950 to 1989 (−0.12°C/decade) but the trend is nonsignificant.
[35] In December both the Student t test and the Tukey‐
Kramer test show 1996–2005 to be statistically different from
the two preceding periods; 1996–2005 is 1.94°C warmer than
1970–1979 on average and 1.85°C warmer than 1980–1995
(Figure 4f). The regional temperature trend computed over
HB for December (Figure 4e) is 1.0°C per decade from 1980
to 2005 (p = 0.024) and 2.3°C per decade from 1989 to
2005 ( p = 0.008). SAT anomalies show a negative trend in
SAT from 1950 to 1989 (−0.28°C/decade) but the trend is
nonsignificant.
3.2. Fall Sea Ice Distribution and Trends
3.2.1. Fall Freezeup Sequence, 1980–2005
[36] The early freezeup sequence for the study period is
represented by CIS data (WOY 43–48) showing mean SICs
and sea ice probability maps (for SICs ≥80% and ≥20%) for
1980–2005 (Figure 5). Freezeup starts in the northern portion
of HB around the shores of South Hampton Island and along
the northwestern coast of HB (WOY 43). The probabilities
of ≥20% ice cover are highest within the northern inlets
and bays, with about a 10% probability of freezeup occurring
along the coast extending down to Cape Churchill. During
WOY 43 there is <30% probability of “consolidated ice”
(≥80% SIC) occurring in northern HB.
6 of 20
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Figure 4. SAT anomalies surrounding HB (1951–2005) using 3 month averages ending in (a) October,
(c) November, and (e) December, with smoothing splines, i.e., (i) flexible spline fit (l = 0.047) and (ii) stiff
spline fit (l = 1612.676), and interannual SAT anomalies trends per month for 1980–2005 (shaded line) and
1989–2005 (bold line). (b) October semidecadal mean temperature comparisons, with 1996 to 2005 identified as being statistically different. (d) November semidecadal mean temperature comparisons with 1996
to 2005 identified as being statistically different. (f) December semidecadal mean temperature comparisons,
with 1996 to 2005 identified as being statistically different. Means comparison (diamonds) shows the mean
(centerline) and the upper and lower 95% confidence limits, delineated by the tips of the diamonds.
[37] During WOY 44, mean nearshore SICs increase and
start to expand offshore from the north and northwest. Ice
development begins to extend southward along the coast to
the Nelson Estuary and in a narrow band along the southern
coast toward James Bay. The probability of consolidated ice
remains very low (10%–30%) for the most part, with higher
probabilities (40%–60%) of consolidated ice in the northern
coastal regions and inlets. During WOY 45 ice development
progresses south and southeastward, with pronounced ice
development from Cape Churchill and the Nelson River
estuary to James Bay; probabilities are high (60%–100%)
that the SIC along the north and northwest coasts is consolidated, and probabilities of consolidated ice remain low
(≤40%) along the southern coast to James Bay. In WOY 46–
48 consolidated sea ice (≥80% SIC) extends well into the
HB in the north and west. During WOY 47–48 consolidated
ice extends along the southern coast of HB into western
James Bay, eventually encompassing Akimiski Island in
7 of 20
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Figure 5. Fall freezeup sequence for HB based on Canadian Ice Service (CIS) data per week of year
(WOY), 1980–2005, using (a) mean weekly sea ice concentrations (SICs), (b) ice probabilities based
on SICs ≥80%, and (c) probabilities based on SICs ≥20%.
WOY 48. The central portion of HB remains fairly open
(SIC ≤50%).
[38] The east coast of HB starts to freeze much later (WOY
46); ice first develops along the northeastern portion of the
coast and then extends southward toward James Bay in the
following weeks. The probability of nearshore consolidated
ice along the east coast of HB remains low in WOY 48 (40%).
[39] The remaining freezeup sequence is shown using
SIC data derived from PMW data (Figure 6). For purposes
of comparison, WOY 43–48 are shown again. Despite the
absolute differences between the data sets, the general pattern
of freezeup is consistent with the CIS data. It shows that the
northern and northwest portions of HB start to freeze first,
followed by the extension of ice along the south shore of HB
into James Bay (WOY 46–47). The central portion of HB
freezes from the north to the south and southeast, with the
southeastern portion of the Bay freezing last. The PMW data
show that HB is consolidated by late December to early
January. Evidence of early winter latent heat polynyas in
James Bay and northwestern HB, formed as a result of
persistent westerly and northwesterly winds, is apparent in
WOY 02.
Figure 6. Fall freezeup sequence based on passive microwave (PMW) data using mean SICs (1980–
2005) per WOY.
8 of 20
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Figure 7. Linear trends (b) in SIC anomalies using CIS data (1980–2005) and statistical significance (p)
of trends at 90%–99% probability (WOY 43–48).
3.2.2. Trends in Sea Ice Concentration (SIC)
[40] Trends in sea ice anomalies were computed for
WOY 43–48 using the CIS data (Figure 7) and for WOY
43–02 using the PMW data (Figure 8). Both data sets show
that significant negative trends in sea ice anomalies occur
throughout the fall period, indicating a decrease in SICs.
Some positive trends appear along coastal regions using the
CIS data. The CIS database was queried and it was found that,
since 1996, nearshore new and young ice has been mapped,
despite warmer air temperatures. The improved capability of
detecting and mapping new and young nearshore ice since
1996 coincides with the introduction of high‐resolution
RADARSAT‐1. Positive nearshore anomalies are therefore
considered unrepresentative in the context of the historical
Figure 8. Linear trends (b) in SIC anomalies using PMW data (1980–2005) and statistical significance
( p) of trends at 90%–99% probability (WOY 43–02).
9 of 20
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Table 2. Summary of Mean Sea Ice Concentration Anomaly Trends per Decade in Hudson Bay Using Canadian Ice Service Dataa
WOY
43
44
45
46
47
48
Trends Based on 90%–99% Probability
b, 10 years (90%–99% prob.)
−26.9
−23.1
−23.7
−25.0
−23.7
SD
4.8
6.4
4.5
5.0
6.8
% of HB area
0.11
1.28
8.51
13.52
15.2
Trends in SIC Regardless of Significance (1980–2005), Including Percent Area of HB Affected
b, all
−19.2
−16.4
−16.6
−17.0
−14.3
SD
7.8
7.6
7.5
7.8
7.6
% of HB area
0.49
6.26
22.3
43.93
69.32
−23.3
7.5
26.18
−13.8
9.5
76.12
WOY, week of year; SIC, sea ice concentration; b, anomaly trends; HB, Hudson Bay.
a
data and are excluded from any statistical summaries, despite
their appearance in CIS data.
[41] The sea ice anomaly trends per WOY follow the ice
marginal zone. The trends identified as being statistically
significant (90%–99% level) are summarized in Tables 2
and 3. The statistically significant trends based on the CIS
data estimate reductions in SICs ranging from −23.3% to
−26.9% per decade, implying mean reductions in SICs over
the last 26 years of −61% to −71% (Table 2, a). Mean trends
within HB, regardless of significance, for the CIS data range
anywhere from −13.8% to −19.2% per decade, depending
on the WOY, indicating more general reductions in SIC
concentrations of −36% to −50% over broad areas of HB
during the last 26 years.
[42] The statistically significant trends computed with the
PMW data are lower, but cover a broader area, compared to
the statistically significant trends of the CIS data. During
WOY 45–50 the PMW data estimate SIC trends ranging
from −12.7% to −16.8% per decade, indicating changes in
SICs in the past 26 years ranging from −33% to −44%
(Table 3). As HB sea ice consolidates late in the freezeup
period (WOY 51–02), interannual variation in anomalies
decrease and trends become progressively smaller, from
−12.1% to −0.8% per decade.
[43] When the mean CIS anomalies (meeting 90%–99%
probability) are plotted by year per WOY (Figure 9), it
becomes evident that SIC anomalies from 1980 to 1995 are
typically positive (20% to 60%), with a number of negative
anomaly events. From 1996 to 2005 mean SIC anomalies in
WOY 43–45 are exclusively negative (−20% to −40%);
during WOY 46–48 almost all years have negative anomalies
except for 2002 and 2004, where anomalies were slightly
positive.
3.2.3. SIC Difference Mapping
3.2.3.1. CIS Data
[44] On the basis of SAT and SIC anomaly data we have
identified two periods or climate regimes within the 1980 to
2005 time series. The cool period (1980–1995) shows positive anomalies and the warmer period (+0.90 to +1.94°C;
1996–2005) represents negative anomalies within the time
series.
[45] Using the CIS data, change between these two periods
is illustrated in two ways: (1) by a means comparison, to
identify statistically significant changes (at 90%–99% levels)
in mean SICs per grid point (Figure 10); and (2) by a probability difference map of SICs ≥80% (Figure 11c), to illustrate change in the probability of “consolidated ice.” Both
products are functionally equivalent, with the former illustrating statistically significant changes in SIC and the latter
illustrating shifts in probability.
[46] Table 4 summarizes the statistically significant changes
in mean SIC (%) between the two periods for each WOY.
Table 4 also reports the mean sea SIE (based on ≥20% SIC)
over 1980–2005 per WOY expressed as a percentage of the
total HB area and lists the percentage area of HB that has
undergone statistically significant change in mean SIC (% HB
(DSIC)). The differences in mean SIC between the two periods
per WOY has decreased consistently on average between
−35% and −38% over each WOY within statistically significant areas, and this change has occurred over a significant
portion of the mean SIE. For example, early in the season
(WOY 43) the mean SIE is 0.57% of the HB area (or 4.58 ×
103 km2); nevertheless, 72% of that area (3.29 × 103 km2) has
shown statistically significant change, from a mean SIC of
45% to one of 8% (Table 4). Ending in WOY 48, the mean
SIE is typically 92% of the HB area (or 7.39 × 105 km2);
∼42% of that area (or 3.11 × 105 km2) has undergone significant change, from a mean SIC of 69% down to one of 30%.
[47] A different representation of change within the HB is
provided by the sea ice probability map, showing, in this
case, changes in SICs ≥80% (defined hereinafter as consolidated ice) (Figure 11). The differences between the two
time periods are quite dramatic for each week. In WOY 43
the probability of any “consolidated ice” has almost been
Table 3. Summary of Mean Sea Ice Concentration Trends per Decade Using Passive Microwave Data Based on 90%–99% Probability,
Including Percent of Hudson Bay Area Affecteda
WOY
b, 10 yr (90%–99% prob.)
SD
% of HB area
45
46
47
48
49
50
51
52
01
02
−12.7
4.3
9.4
−16.1
4.8
34.0
−16.8
4.7
52.0
−14.9
4.6
50.3
−14.3
5.7
57.4
−15.5
4.3
36.8
−12.1
6.7
41.5
−09.0
5.3
33.4
−05.7
2.4
14.8
−00.8
2.2
10.0
WOY, week of year; b, mean sea ice concentration trends; HB, Hudson Bay. Trends are from 1980–2005.
a
10 of 20
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
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Figure 9. Mean SIC anomalies per year computed from grid points with significant ( p = 0.1 − 0.01)
linear trends using CIS data (WOY 43–48).
eliminated, with the exception of some sheltered bays and
inlets along the southern coast of South Hampton Island and
the northwestern coast of HB. The same is true in WOY 44
along the southeastern portion of South Hampton Island,
where in 1980–1995 a high probability of consolidated ice is
reduced to a 0%–10% probability. In WOY 45 the percentage
area where one would expect a high probability (60%–100%)
of SIC ≥80% is reduced from 9% to 0.87% of the HB area
(D 6.54 × 105 km2); in WOY 46 the area is reduced from
19.1% to 6.3% of the HB area (D 1.03 × 105 km2); in
WOY 47 the area is reduced from 37.5% to 20.3% of HB
(D 1.35 × 105 km2); and in WOY 48 the area is reduced
from 75% to 38.3% of the HB area (D 2.95 × 105 km2). Some
of the largest changes in probability of consolidated ice are
evident in WOY 48 along the southern coast of HB, from the
Nelson River estuary down into James Bay, and along the
northeastern coast of HB, extending into the central basin.
Here probabilities of consolidated ice have decreased by
−50%, to >more than −70%, thus often reducing the probabilities of consolidated ice to 0%–10% during the 1996–2005
period.
[48] Table 5 summarizes the differences in SIE between
the two periods based on SICs ≥80%. The mean differences
in ice extents between each period are statistically significant at 95% levels except for WOY 46 (90%). In WOY 47
to 48 the extent of consolidated ice between the two periods
Figure 10. (a) SIC difference mapping using CIS data per WOY: (a) change (D) in mean SIC anomalies
(%), 1980–1995 versus 1996–2005; (b) statistical significance ( p) of change based on Student’s t test.
11 of 20
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
Figure 11. Probabilities of SICs ≥80% (a) for the “cool” period (1980–1995) and (b) for the “warm”
period (1996–2005). (c) Change in probability of SICs ≥80%, 1980–1995 versus 1996–2005.
decreased by 1.71 × 105 to 1.82 × 105 km2. On the basis of
the results shown, there is at least a 1 week delay in the
formation of consolidated ice.
3.2.3.2. PMW Data
[49] Because of temporal limitations of the CIS data,
PMW data are used to document relative changes in SIE
beyond WOY 48. As PMW data tend to underestimate SICs
Table 4. Summary of Mean Sea Ice Concentration Differences
Using Canadian Ice Service Data for 1980–1995 Versus 1996–
2005 Within the Areas Identified as Being Statistically Different
(90%–99% Level), Mean Sea Ice Extent in Hudson Bay for 1980–
2005, and Percent Area of HB That Has Undergone Significant
(90%–99% Probability) Change in SIC for Weeks of Year 43–48a
WOY
Period
Mean SIC
(%)
43
1980–1995
1996–2005
Diff. (D)
1980–1995
1996–2005
Diff. (D)
1980–1995
1996–2005
Diff. (D)
1980–1995
1996–2005
Diff. (D)
1980–1995
1996–2005
Diff. (D)
1980–1995
1996–2005
Diff. (D)
44.9
7.54
−37.36
42.29
5.66
−36.63
47.84
9.81
−38.03
52.34
17.4
−34.94
51.07
14.62
−36.45
69.22
30.74
−38.48
44
45
46
47
48
SD
(%)
4.77
5.25
SIE,
1980–2005
(%)
% of
HB Area
(DSIC)
0.57
0.41
[Agnew and Howell, 2003], change detection is based on
SIEs using SICs ≥60%. We start with WOY 46 to provide
some overlap with the CIS data. The mean differences in SIE
between the two periods for each WOY were statistically
significant (at the 95%–99% level) (Table 6). For example, in
WOY 46 SIE is reduced from ∼14% (1.19 × 105 km2) to 0.8%
(6.2 × 103 km2) of the HB area. The maximum differences in
SIE occur in WOY 47 to 50, with differences in extent
ranging from −1.74 × 105 to 2.41 × 105 km2, depending on the
week. In late December the relative differences in SIE between the two periods become progressively smaller, as the
sea ice is typically more consolidated late in the season.
3.2.4. Air Temperature Versus SIC Anomalies and SIE
[50] The results presented thus far have shown that the
SAT of the land surrounding HB within the time series
Table 5. Summary of Mean Differences in Sea Ice Extent Based on
Sea Ice Concentrations ≥80% for 1980–1995 Versus 1996–2005
Using Canadian Ice Service Data for Weeks of Year 45–48a
12.03
7.1
6.4
5.45
16.42
12.5
Data
CIS
23.14
Week
45
17.08
19.03
17.25
46
46.18
25.4
18.51
19.99
47
76.33
38.81
13.59
17.79
48
92.17
38.7
a
SIC, sea ice concentration; SIE, sea ice extent; HB, Hudson Bay; WOY,
weeks of year. Mean SIE for HB is based on SICs ≥20%.
a
12 of 20
Year
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
SIE
(% of
HB Area)
12.85
3.41
−9.44
26.62
12.92
−13.69
46.04
23.37
−22.66
67.15
45.88
−21.27
SD
(%)
10.82
2.65
20.14
12.42
27.77
12.66
25.72
21.04
Area
(km2)
p
5
1.03 × 10
2.74 × 104
−7.59 × 104
2.14 × 105
1.04 × 105
−1.10 × 105
3.70 × 105
1.88 × 105
−1.82 × 105
5.40 × 105
3.69 × 105
−1.71 × 105
0.013
0.066
0.02
0.038
SIE, sea ice extent; CIS, Canadian Ice Service; WOY, weeks of year.
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
Table 6. Summary of Mean Differences in Sea Ice Extent Based
on Sea Ice Concentrations ≥60% for 1980–1995 Versus 1996–
2005 Using Passive Microwave Data for Weeks of Year 46–52a
WOY
46
47
48
49
50
51
52
Year
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
1980–1995
1995–2005
Diff. (D)
SIE
(% of
HB Area)
14.74
0.77
−13.97
30.37
7.32
−23.05
51.91
25.12
−26.79
73.25
43.28
−29.98
87.77
66.14
−21.63
95.18
79.93
−15.25
99.29
92.67
−6.61
SD
(%)
16.66
0.96
22.95
7.14
23.75
14.78
20.3
22.69
15.43
25.31
10.07
19.1
2.25
11.03
Area
(km2)
p
5
1.19 × 10
6.20 × 103
−1.12 × 105
2.44 × 105
5.89 × 104
−1.85 × 105
4.17 × 105
2.02 × 105
−2.15 × 105
5.89 × 105
3.48 × 105
−2.41 × 105
7.06 × 105
5.32 × 105
−1.74 × 105
7.65 × 105
6.43 × 105
−1.23 × 105
7.98 × 105
7.45 × 105
−5.32 × 104
0.015
0.005
0.004
0.002
0.012
0.013
0.027
a
HB, Hudson Bay; SIE, sea ice extent; WOY, weeks of year.
(1980–2005) has warmed significantly since 1995, accompanied by a significant reduction in SIC and, ultimately,
SIE. Here we quantify the dependence of weekly SIC
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anomalies computed from CIS data (WOY 45–48) and from
the PMW on interannual air temperature anomalies.
[51] The relationships between SIC anomalies computed
from CIS and PMW data versus SAT anomalies are summarized in Figure 12 and Table 7. Coefficients of determination (r2) range from 0.50 to 0.60 for CIS data and from
0.54 to 0.72 for PMW data, suggesting that interannual sea
ice anomalies are dependent on SAT anomalies. The data
show that, over WOY 45–48, a 1°C increase in SAT results
in a decrease in SICs by −14% on average using CIS data.
The trends in SIC anomalies are somewhat lower using the
PMW data (Table 7). In week 45 the relationship between
SIC anomalies and SAT anomalies is curvilinear, because it
is very early in the freezeup period so positive SIC anomalies
are favored; the same occurs in week 52, where negative
anomalies are favored, as ice is typically consolidating at
this point. During WOY 46–51 all the relationships are linear;
the highest correlations occur during weeks 47–49 (r2 =
0.62–0.72; p < 0.0001), when SIC anomalies are more evenly
distributed (period of maximum interannual variation). SIC
anomaly trends during WOY 47–49 range from −9.6% to
−12.6%. The correlation between air temperature anomalies
and SIC anomalies remains high (r2 = 0.60–0.72; p <
0.0001) during WOY 50–52, when slopes gradually decrease
from −8.08 to −3.29.
[52] The degree to which SAT anomalies are predictive of
interannual SIE is illustrated in Figure 13 for CIS data
(WOY 47–48) and PMW data (WOY 48–49) These are
periods of maximum interannual variation for each data set;
regression coefficients are summarized in Table 8. For CIS
data the areal extent was based on SICs ≥80%, and for
PMW data it was based on SICs ≥60% to generally approx-
Figure 12. Relationships between SAT anomalies surrounding HB versus SIC anomalies based on CIS
and PMW data.
13 of 20
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Table 7. Regression Parameters for Sea Ice Concentration Anomalies Versus Air Temperature Anomalies for Canadian Ice Service
Data for WOY 45–48 and Passive Microwave Data for WOY
45–52a
Source
CIS
PMW
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
WOY
Slope b1
45
46
47
48
45
46
47
48
49
50
51
52
−14.7849
−14.6069
−13.9777
−13.5203
−9.0919
−10.9469
−12.2011
−12.6211
−9.6249
−8.0852
−5.6422
−3.2933
b2
2.7213
−0.9322
RMSE
r2
p
20.43
21.00
18.89
16.14
11.31
14.53
13.77
11.67
11.90
11.71
7.78
4.47
0.52
0.50
0.54
0.60
0.67
0.54
0.62
0.71
0.67
0.60
0.62
0.72
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001; 0.0166
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001; 0.0063
a
RMSE, root mean square error; CIS, Canadian Ice Service; WOY, week
of year; PMW, passive microwave. Polynomial fits are italicized. See
Figure 12.
imate the CIS extents. The areal extent of the ice is expressed
as a percentage of the HB area. For the CIS data mean ice
extents over 1980–2005 were 37.3% (or 3.00 × 105 km2) for
week 47 and 58.9% (or 4.58 × 105 km2) for week 48, with
Table 8. Regression Parameters for Sea Ice Extent Versus Surface
Air Temperature Anomalies for Weeks of Maximum Variation in
SIEa
Data
WOY
Intercept
Slope
RMSE
r2
P
CIS
47
48
48
49
37.320
58.967
41.604
61.725
−13.051
−14.505
−14.422
−12.038
17.738
15.870
13.410
15.076
0.53
0.64
0.71
0.67
<0.0001
<0.0001
<0.0001
<0.0001
PMW
a
CIS, Canadian Ice Service; PMW, passive microwave; RMSE, root mean
square error; WOY, week of year; SIE, sea ice extent (% of Hudson Bay
area).
slopes ranging from a −13.1% to a −14.5% (or −1.05 × 105 to
−1.17 × 105 km2) decrease in areal extent per 1°C increase.
[53] For PMW data mean SIEs over 1980–2005 were
41.6% (or 3.35 × 105 km2) for week 48 and 61.7% (4.96 ×
105 km2) for week 49. The trends in SIE estimated from
PMW using SIC ≥60% for WOY 48 and 49 were −14.42%
and −12.04% (or −1.16 × 105 and −9.68 × 104 km2),
respectively, for each increase in 1°C.
3.2.5. SAT and Ice Thickness
[54] Recent updates of thickness data from the CIS show
that the ice thickness in Coral Harbour (the only reporting
ice station on HB) has decreased during the fall period,
Figure 13. Relationships between SAT anomalies surrounding HB and sea ice extent (SIE) expressed as
percentage area of HB (total HB area, 804 × 103 km2) for weeks of maximum interannual variation in SIE
using (a) CIS data (SIC ≥80%) and (b) PMW data (SIC ≥60%).
14 of 20
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Figure 14. Mean change (D) in sea ice thickness (cm) and
SATs for Coral Harbour (1980–1989 versus 2002–2007)
for (a) the month of November, which showed a mean change
in ice thickness D of −19.4 cm, corresponding to an average
1.98°C increase in SAT; and (b) the month of December,
when the ice thickness has decreased by 40 cm, with an average increase in SAT of 2.54°C. Snow thickness (not shown)
showed no significant differences being the two periods.
corresponding to a period of increased SAT anomalies. Data
are shown for mid November and mid December (Figure 14).
In November the mean difference in ice thickness between
1980–1989 and 2002–2007 was −19.4 cm (p = 0.0458),
while the mean difference in air temperature in Coral Harbour
during the same period was 1.98°C ( p = 0.002). In mid
December the mean ice thickness decreased from 72 to
32 cm (−40.9 cm; p = 0.0012), while the mean SAT anomaly
increased by 2.54°C (p = 0.0025). Changes in snow cover
between the two periods were statistically insignificant for
both November and December.
3.3. SAT Anomalies Versus Teleconnection Indices
[55] For the fall period a number of indices were examined to determine if any were predictive of fall temperatures
and ice conditions in HB. These included the NAO, AO,
PDO, SOI, and EP/NP index. The geopotential height and
temperature correlation maps for each index in its positive
phase are presented for the late summer‐early fall period for
the 1980–2005 time series (Figures 15a–15e) to provide a
general spatial context prior to examining the HB region in
more detail. Each of the indices shown, with the exception
of the SOI, shows that the HB area has a tendency toward
cooler air surface temperatures when the indices are in their
positive phase.
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[56] The extent to which the various indices are predictive
of interannual SAT anomalies for the region surrounding
HB for the periods ending in October to December are
summarized in Table 9. Coefficients of determination (r2)
were computed for two periods, 1951–2005 and 1980–2005,
corresponding to the periods for which ice data are available
(see section 2.4).
[57] Of all the indices the EP/NP index was consistently
predictive of interannual air temperatures during the fall
period. During the month of October the interannual EP/NP
index was predictive of SAT from 1951 to 2005 (r2 = 0.54,
p < 0.0001), and more so from 1980 to 2005 (r2 = 0.75;
p < 0.0001). In November (September to November) the
relationships held true, with 62% of the variance in SAT
surrounding HB being explained by the EP/NP index over
1951–2005 and 79% over 1980–2005. An EP/NP index was
not computed for December and is therefore not shown.
[58] The NAO index was not statistically significant in
October and was only weakly correlated in November. The
AO was not significant at all with the exception of a weak
correlation in October (1951–2005). The low correlations
between the NAO and the AO very early in the season are
consistent with the observation that AO and NAO tend to be
strongest in the winter [Barry and Carleton, 2001]. The
PDO was significant (at 90%–95%) in both November and
December but the coefficients of determination were very
weak (r2 = 0.05–0.21).
[59] To show more general tendencies in the indices
versus SAT, 5 year running means were applied to the data.
Means comparisons were made at 7 year intervals to examine
the extent to which mean air temperature and index values
varied over time (Figure 16). Three spline fits (l = 0.01 (no
smoothing), 6.20 (moderate), and 1612.7 (high)) were added
to the temporal plots for illustrative purposes to highlight the
cyclical nature of the indices and SAT anomalies, including
the longer‐term low‐frequency variations exhibited by each
of the variables from 1951 to 2005.
[60] The means over the 1999–2005 period (Figure 16),
with few exceptions, were statistically different from those in
the two preceding intervals (1985–1991, 1992–1998). Also,
all indices changed phase in the mid 1990s and showed trends
in index values that are typically associated with warmer fall
temperatures for the HB region.
[61] In terms of air temperature, the 1999 to 2005 period is
statistically warmer (mean SAT anomaly 0.83°) compared to
all preceding periods. The first two periods encompassing
1957–1970 are significantly warmer compared to 1992–98
(D = 0.36°C) and significantly cooler (D = −0.63°C) than the
1999–2005 anomalies.
[62] The temporal plot of the EP/NP index shows that
it was positive from 1965–97 with occasional reversals
(1970–71, 1983–85, 1991–92), and consistently negative
from 1998–2005. Based on the means comparisons the
1999–2005 period is statistically different relative to all
preceding periods. Table 10 summarizes the extent to which
the various indices exhibit covariance to the mean air temperatures in HB computed for November, the period of
maximum sea ice variability. The EP/NP index is shown
to be highly predictive of SAT surrounding Hudson Bay
back to 1951 (r2 = 0.75) and from 1980 to 2005 period
(r2 = 0.89).
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
Figure 15. Seasonal correlation of indices in their positive phase with (a) 500 mb geopotential heights,
using 4 month means for the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) and 5 month
means for the Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI), and East Pacific/
North Pacific oscillation (EP/NP) index (ending November), and (b) mean SAT for October to November
(1980–2005) (http://www.cdc.noaa.gov/Correlation/).
[63] Although the NAO index shows considerable variation, it has largely remained positive from 1973 to 1996
(Figure 16c), with a few reversals (1977, 1983–1984, 1988–
1989); a positive NAO is associated with cooler tempera-
tures in HB. During the 1999–2005 interval the mean NAO
index became strongly negative and is statistically different
from that in all preceding periods with the exception of
1964–1970. The most recent trend favors warmer fall tem-
Table 9. Coefficients of Determination (r2) for Annual Mean Air Temperature Anomalies Versus Hemispheric Indices, EP/NP, NAO,
AO, PDO, and SOI, Ending in October, November, and Decembera
Years
Month
EP/NP
p
NAO
p
AO
p
PDO
p
SOI
p
1951–2005
1980–2005
1951–2005
1980–2005
1951–2005
1980–2005
Oct
−0.54
−0.75
−0.62
−0.79
NA
NA
<0.0001
<0.0001
<0.0001
<0.0001
−0.04
0.01
−0.15
−0.14
−0.07
−0.07
NS
NS
0.004
0.060
0.060
NS
0.11
0.08
0.01
0.00
−0.00
−0.00
0.010
NS
NS
NS
NS
NS
−0.02
−0.12
−0.09
−0.21
−0.05
−0.13
NS
0.081
0.029
0.020
0.089
0.066
0.07
0.15
0.06
0.07
0.01
0.02
0.048
0.047
0.082
NS
NS
NS
Nov
Dec
a
AO, Arctic Oscillation; EP/NP, East Pacific/North Pacific oscillation index; NA, not available; NAO, North Atlantic Oscillation; NS, not significant
(90%–99% confidence interval); PDO, Pacific Decadal Oscillation; SOI, Southern Oscillation Index. A minus sign indicates a negative correlation; p
identifies the significance of the relationship; bold characters = 95–99% prob.
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
Figure 16. Temporal plots of mean October to November SATs and hemispheric indices using a 5 year
running mean. For illustrative purposes three spline fits (l = 0.01, no smoothing; l = 6.20, moderate
smoothing; l = 1612.7, stiff spline) are applied to the SATs and indices. Seven year means comparisons for
(a) SAT, (b) EP/NP index, (c) NAO, (d) AO, (e) PDO, and (f) SOI show that the latter period (1999–2005),
without exception, is statistically different from the preceding period. Means comparison (diamonds) shows
the mean (centerline) and the upper and lower 95% confidence limits, delineated by the tips of the diamonds.
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
Table 10. Matrix of Coefficients of Determination (r2) for
Climate Indices Versus Surface Air Temperature Based on the
5 Year Running Mean for 1980–2005, 1950–2005, 1980–1995,
and 1995–2005a
EP/NP
NAO
AO
PDO
SOI
AT
0.24
0.12
0.17
−0.05
−0.75
NAO
AO
PDO
SOI
AT
0.45
0.34
0.55P
−0.22
−0.89
NAO
AO
PDO
SOI
AT
0.15
0.13
−0.02
0.00
−0.74
NAO
AO
PDO
SOI
AT
0.54
0.52
0.74
−0.64
−0.97
NAO
AO
PDO
SOI
−0.40
−0.20
0.08
−0.35
−0.70P
0.23
0.00
0.06
0.00
−0.77
−0.89P
0.78P
1950–2005 (n = 51)
0.31
0.08
−0.01
−0.39
0.28
−0.02
−0.14
1980–2005 (n = 26)
0.33
0.33P
−0.23
−0.65
0.44P
−0.34P
−0.50
1980–1995 (n = 16)
0.09
−0.23
−0.14
−0.38
0.00
0.03
−0.36
1995–2005 (n = 11)
0.43
0.29
−0.32
−0.66
0.56
−0.87
−0.55
a
AO, Arctic Oscillation; AT, air temperature; EP/NP, East Pacific/North
Pacific oscillation index; NAO, North Atlantic Oscillation; PDO, Pacific
Decadal Oscillation; SOI, Southern Oscillation. A dash indicates a
negative correlation. P indicates a second‐order polynomial. Boldface
italic correlations are significant at 99% level, boldface correlations are
significant at 95% level, italic correlations are significant at 90% level,
and regular text correlations are nonsignificant.
peratures. The NAO index is correlated with regional SAT
anomalies from 1951 to 2005 (r2 = 0.39) and from 1980 to
2005 (r2 = 0.65) (Table 10). For 1951–2005 the EP/NP and
NAO indices together explained 80% of the variance in SAT,
and for 1980–2005 the EP/NP and NAO indices together
explained 94% of the variation.
[64] The AO index values have been predominantly negative from 1955 to 1972 and positive from 1973 to 1996, with
one reversal from 1980 to 1985 (Figure 16d). From 1997 to
2005 the AO index has been positive. The low‐frequency
trend shown by l = 1612.7 indicates that the AO has a long‐
term periodicity (complete cycle not shown) overlain with
shorter‐term fluctuations (≤15–20 years). The AO indices are
now trending to negative values favoring warmer temperatures in HB. The most recent period (1999–2005) has been
consistently negative and statistically different from the two
preceding periods, which are positive and associated with
cooler November temperatures in HB. The AO index has a
weak correlation with SAT from 1951 to 2005 (r2 = 0.14); the
correlation improves over the 1980–2005 period (r2 = 0.50).
The EN/NP and AO together explained ∼90% of the variance
in SAT anomalies based on a 5 year running mean. The PDO
index typically has a ≥20–30 year cycle. Through the 1980s
and into the late 1990s the fall PDO was positive and is now
trending to a negative cycle (Figure 16e). The last period
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(1999–2005) is statistically different from the three preceding
periods (over 1978–1998), which were in the positive phase
of the cycle. The negative phase of this index is associated
with warmer fall temperatures in HB. Over 1950–2005 the
PDO index is not strongly correlated with SAT (r2 = 0.20),
although slightly better than the AO. During the 1980–2005
the PDO is more highly correlated (r2 = 0.70).
[65] The SOI is quite variable and generally the most
poorly correlated index (interannually) with SAT anomalies
in HB (Table 10). Despite that, it is interesting to note that
the very low‐frequency pattern (l = 1612.7) appears to be
the inverse of the low‐frequency decadal pattern exhibited
by the other indices, with a notable regime shift around
1976–1977 [Y. Zhang et al., 1997] (Figure 16f). Negative
SOIs are loosely associated with cooler fall temperatures in
HB and extreme SIE events in HB when in phase with a
strong positive NAO [e.g., Wang et al., 1994].
[66] Table 10 also lists correlations within the “cool” and
“warm” phases of the standardized atmospheric indices in
the 1980–2005 time series. The EP/NP index is the most
highly correlated within the 1980–1995 period (r2 = 0.74),
followed by the NAO and AO indices, at r2 = 0.38 and 0.36,
respectively, with the PDO and SOI not showing any significance. Together, the EP/NP index with either the NAO
or the AO explains ∼84% of the variance in SAT anomalies
in HB. During the warming phase all indices have changed
phase, indicative of warmer fall temperatures for HB. All
indices are highly correlated (r2 = 0.50–0.97).
[67] We suggest caution in implying causal relationships
to all of the various indices and the observed SAT anomaly
trend. What can be stated is that, since 1995, the various
indices have changed phase and that the EP/NP, NAO, and
AO indices appear to be those most consistently correlated
with SAT anomalies over all periods, with the EP/NP index
being the single most predictive index during the fall period
and the NAO and AO contributing significantly in terms of
improving the explained variance in SAT anomalies when
using multiple regression.
4. Conclusions
[68] Based on the CANGRID data we have shown that SAT
anomaly trends were positive (warming) around HB from 1980
to 2005. The highest and most significant trends occurred in the
northern and eastern portions of HB, with overall trends in
SAT anomalies increasing from October (0.6–0.8°C/decade)
to December (1.1–1.6°C/decade). Although statistically nonsignificant, the regional mean interannual SAT anomalies
show a slight cooling period over HB from 1950 to 1989,
most evident in November and December, followed by a
statistically significant increase in SAT during the mid 1990s
to 2005.
[69] Both CIS data and PMW data showed that SIC
anomalies were decreasing throughout the fall (WOY 43–01),
with the most significant (negative) trends in SIC anomalies
following the marginal ice zone. The statistically significant
trends in SIC anomalies using the CIS data showed negative
trends in SIC ranging from −23.3% to −26.9% per decade for
weeks 43–48, resulting in significant reductions in SIE over
the last 26 years. Statistically significant trends in SIC
anomalies using the PMW data were lower but were more
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HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB
broadly distributed throughout HB, ranging from −14.3% to
−16.8% per decade for weeks 46–50.
[70] Interannual SIE was closely related to variations in
SAT evidenced by both CIS data and PMW data. The CIS
data showed that for every 1°C increase in the mean regional
air temperature around HB, the area of SIC ≥80% (consolidated ice) deceased by 1.05 × 105 to 1.17 × 105 km2 for
weeks 47–48 (late November). Similar results were shown
for changes in SIEs using PMW data based on a slightly
lower SIC threshold (SICs ≥60%).
[71] Regional SAT anomalies around HB were shown to
be closely related to atmospheric indices. The EP/NP index
was predictive of SAT anomalies in HB dating back to 1950.
The NAO and AO were much less predictive; they typically
exert their strongest influence during the winter period. Five
year running means were also applied to the SAT and to the
teleconnections data. These data showed that the EP/NP
index together with the NAO and AO explained ∼80%–90%
of the variance with SAT anomalies in November from 1951
to 2005. The SOI index was consistently the most poorly
correlated with SATs (R2 = 0.08) on an interannual basis,
whereas the PDO was more predictive of SATs than the AO
index over 1951–2005.
[72] Examining the longer‐term trends in air temperature
and the hemispheric indices using a 5 year running mean, it
is apparent that the climate has been undergoing a regime
shift in the last 15 years and that this shift in HB during the
fall appears to be associated with the low‐frequency oscillation pattern inherent in the various indices, particularly the
EP/NP, NAO, and AO. The phase change in the mid 1990s
coincides with warmer SATs in HB and associated negative
SIC anomalies and SIEs. We plan to extend this HB work
by examining the winter‐to‐summer period for these same
relationships in a follow‐up paper.
[ 73 ] Acknowledgments. This work was funded by the Natural
Sciences and Engineering Research Council, Canada Research Chairs program, and ArcticNet Networks of Centers of Excellence program with grants
to D.G.B. Thanks go to R. Galley for gridding and extracting the CIS data
and to the anonymous reviewers and editors of Journal of Geophysical
Research—Oceans for improving the clarity of this presentation.
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