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Atmospheric forcing of sea ice in Hudson Bayduring 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 ofHudson Bay in the context of atmospheric forcing from 1980 to 2005. Both griddedCanadian Ice Service (CIS) data and Passive Microwave (PMW) data are used to examinethe 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% perdecade, 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 seaice 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 increasein temperature in late November; PMW data show similar results. Regression analysisbetween SAT and standardized climate indices over the 1951–2005 period show that theEast Pacific/North Pacific index is highly predictive of interannual SATs followed bythe North Atlantic Oscillation and Arctic Oscillation indices. The data show that theHudson Bay area has recently undergone a climate regime shift, in the mid 1990s, whichhas resulted in a significant reduction in sea ice during the freezeup period and that thesechanges 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 hasundergone significant changes in ice extent and concentra-tion. In this paper we define sea ice extent (SIE) as the geo-graphic distribution of sea ice (presence/absence) within thestudy region and sea ice concentration (SIC) as the percentageconcentration of sea ice within a particular subset of the studyarea. From 1953 to 2006 the total SIE at the end of thesummer melt season in September declined at a rate of−7.8% per decade [Stroeve et al., 2007]. The trends in SICvary depending on the time period examined and the geo-graphic location. Passive microwave (PMW) data show thattrends in SIC during the 1979–1996 period were relativelysmall throughout the Arctic, −2.2 and −3.0% per decade, incontrast to the 1997–2007 period, which showed that declinesin SIC accelerated to −10.1 and −10.7% per decade [Comisoet al., 2008].[3] Deser and Teng [2008] showed that during the early

part of the PMW period (1979–1993), ice trends in the icemarginal zones within the polar seas varied geographically.During the winter the Labrador and Bering seas had largepositive trends in SIC; the Greenland and Barents seas and

the Sea of Okhotsk had large negative trends. In 1993–2007SIC trends were consistently negative throughout the Arcticand subarctic seas. Summer trends during the first half of thesatellite record showed negative trends in the eastern SiberianSea and positive trends in the Barents, Kara, and easternBeaufort seas, in contrast to the second half of the satelliterecord, which was dominated by negative trends throughoutthe Arctic.[4] In Hudson Bay (HB) a number of studies have exam-

ined trends in SIE. Parkinson et al. [1999] showed that during1979–1996, only very slight negative trends were detectablewithin 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 seasonaltrends were statistically significant. Gough et al. [2004]found no significant trends in freezeup dates for the fallperiod in southwestern HB (1971–2003) using Canadian IceService (CIS) data (Environment Canada, CIS daily analysisice 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 pointobservations. Of the 25 points used throughout HB duringthe freezeup period, only 6 points, located in the northernreaches of HB, showed statistically significant freezeup datetrends (based on an SIC ≥50%); results indicated thatfreezeup was occurring 0.32–0.55 day/yr earlier (1971–2003). Kinnard et al. [2006] showed no significant trends inSICs based on CIS data from 1980 to 2004. The most recent

1Centre for EarthObservation Science, University ofManitoba,Winnipeg,Manitoba, Canada.

Copyright 2010 by the American Geophysical Union.0148‐0227/10/2009JC005334

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, C05009, doi:10.1029/2009JC005334, 2010

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http://dx.doi.org/10.1029/2009JC005334

work by Parkinson and Cavalieri [2008] showed statisticallysignificant annual trends for SIE in HB (including FoxeBasin), 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 usedin their study were collected from the early 1960s to theearly 1990s (the data collection program was terminated in∼1990). Temperature trends were predominantly negativeand ice thickness trends were predominantly positive in HBduring the fall and winter periods.[7] The variations in SIC and SIE throughout the Arctic and

sub‐Arctic have been variously attributed to some combina-tion of anthropogenic forcing due to greenhouse gases andlow‐frequency oscillations in atmospheric circulation andassociated positive feedback mechanisms [Johannessen etal., 2004; Holland et al., 2006]. Interannual variations inSIC anomalies in the Arctic from 1960 to the mid 1990s arepartly explained by variations in the Arctic Oscillation (AO)and North Atlantic Oscillation (NAO) [Venegas and Mysak,2000; Deser, 2000; Polyakov and Johnson, 2000; Comisoet 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 oceanicheat transport [J. Zhang et al., 2004]. In addition to thegradual warming of the Arctic over the last 50 years,Lindsay and Zhang [2005] have also suggested that thetemporary phase change associated with the Pacific DecadalOscillation (PDO) together with the AO in 1988 may havecontributed significantly to the flushing of older ice outof the Arctic. More recently, warming in the high Arctichas accelerated, independent of any indices, even beyondworst‐case scenarios using greenhouse gas forcing, sug-gesting that factors such as the sea ice‐albedo feedbackmechanism are contributing significantly to recent decreasesin 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 iceexport) and more reflective of atmospheric forcing, specif-ically changes in air temperature and winds. Interannualvariations in SIE in HB have been attributed largely to anumber of standardized hemispheric indices that are asso-ciatedwith characteristic wind, temperature, and precipitationpatterns. Wang et al. [1994] and Mysak et al. [1996] showedthat both the NAO and the Southern Oscillation Index (SOI)were associated with peak SIEs in HB (1953–1993). Strongpositive NAOs were associated with a deepened IcelandicLow, northerly winds, and lower temperatures over easternCanada, whereas negative NAOs were associated withsoutherly winds and warmer temperatures. Years with strongnegative SOIs during the spring/summer/fall period wereassociated with more ice production during the freezeupperiod, with the largest negative SAT anomalies occurringin August (cool summer); years with strong positive SOIstended to have positive temperature anomalies. The largestsea ice anomalies within HB were associated with strongnegative SOIs during the summer and strong positive NAOsduring the winter. Prinsenberg et al. [1997], Kinnard et al.[2006], and Qian et al. [2008] all showed that NAO vari-

ability is the main factor controlling temperature variation inthe winter season over eastern Canada, with positive NAOindices coinciding with early formation of sea ice in HB. Inaddition to the NAO, Kinnard et al. [2006] showed that theice regime in HB was significantly correlated with the EastPacific/North Pacific oscillation (EP/NP) index during thespring (r = 0.63) and summer (r = 0.57), both being signifi-cant at the p < 0.05 level. A positive phase of the EP/NP indexcorresponds to a high pressure located over Alaska/westernCanada and a low pressure over the central North Pacific andeastern North America. This configuration acts to draw coolArctic air south to eastern North America including the HBregion.[9] In summary, previous work has shown that the dis-

tribution of sea ice anomalies throughout the Arctic andsubarctic seas have not been uniform over the PMW satelliterecord (1978 to now). This observation is significant for theHB region and eastern Canada in general. Whereas much ofthe Arctic was warming, the HB region was actually cooling(1979–1993), hence the positive sea ice anomalies early inthe PMW record [Deser and Teng, 2008], the lack of signifi-cant statistical trends in SIE from 1979 to 1996 [Parkinson etal., 1999], and the increasing sea ice thickness from1960 to theearly 1990s [Gagnon and Gough, 2006]. More recent datahave shown thatwarming has occurred inHB since 1999–2003[Gagnon and Gough, 2005; Ford et al., 2009; Laidler et al.,2009] and that statistically significant negative SIC trendsare now evident in the Foxe Basin and HB [Parkinson andCavalieri, 2008].[10] This paper seeks to build on previous work as it relates

to the HB region by examining both SIE and SIC and thenexamining the possible atmospheric forcing mechanismslinked to these sea ice metrics. In this paper we (1) providedetailed gridded representations of SAT trends of the landsurrounding HB to provide a context for the observedchanges in SIC and SIE; (2) show the weekly evolution ofsea ice cover during the fall period from 1980 to 2005,provide gridded maps of SIC trends over 1980–2005, andprovide SIC difference maps comparing the “cool period”(1980–1995) to the “warm period” (1996–2005); (3) quantifythe relationship between SAT anomalies and SIC anomaliesand SIE; and (4) examine the relationships between SATanomalies and standardized atmospheric indices relevant tothe fall period in HB.

2. Methods

2.1. Study Area

[11] HB is a large, shallow, inland sububarctic sea; itcovers 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‐freeduring August–September. It has two openings: one to thenorthwest via Roes Welcome Sound and the other east ofSouth Hampton Island into the Hudson Strait. HB is isolatedfrom open ocean circulation, therefore variations in sea icecover are largely a function of atmospheric forcing [Wang etal., 1994]. Currents within HB are dominantly wind drivenand cyclonic at all depths, reaching a maximum in Novemberwhen the winds are strongest [Prinsenberg, 1986; Saucieret al., 2004]. The circulation pattern in James Bay is alsocyclonic, driven by a combination of winds and runoff dilu-

HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB C05009C05009

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tion [Prinsenberg, 1986]. The HB basin drains an area of3.7 × 106 km2 in North America and its freshwater dis-charge of ∼950 km3/yr represents 20% of the total annualrunoff to the Arctic Ocean [Déry and Wood, 2004]. Duringthe fall period SSTs are highest in the James Bay area andsoutheastern HB, extending north along the east coast ofHB [Saucier et al., 2004]. This area is typically the last tofreeze up.

2.2. Surface Air Temperature (SAT) Data

[12] We use a SAT product known as CANGRID, devel-oped for climate change studies by the Climate ResearchDivision of Environment Canada. It uses adjusted historicalCanadian climate data [Vincent and Gullet, 1999] thataccount for changes resulting from reporting station systemchanges. A full description of the Canada‐only data set isprovided by McKenney et al. [2005]. The CANGRID griddata have a spatial resolution of 50 km and cover landsurfaces only.[13] The CANGRID data used in this study consist of

monthly air temperature anomalies dating back to 1950, aperiod when most of the stations in the region were observingon a regular basis (E. Milewska, Environment Canada, per-sonal communication, 2009). The bounds used to compute

the mean HB regional temperature anomalies (per month peryear) were 50°–65°N and 72.5°–100°W (Figure 2). The useof temperature anomalies in gridding data has the advantageof removing location, physiographic, and elevation effects.Monthly temperature anomalies were computed for eachmonth per year relative to the 1980–2005 mean to match thenormals computed for sea ice data. A 3 month running meanwas applied to the monthly SAT anomaly data ending in(including) the month of interest; the intent here was toincorporate lead‐up SATs to obtain a (moving) seasonaltemperature index (anomaly) value.We tested both normalityand autocorrelation (assumptions of the general linear model)and we found each to be sufficiently low to allow for use ofparametric analysis. SAT anomaly trends and their statisticalsignificance (p; at 0.10, 0.05, and 0.01) were mapped basedon the least‐squares fit per grid point (n = 1128). The trendmaps intend to show the regional distribution of SATanomalies around HB.[14] These temperature data were used (1) to examine

general temperature trends from 1950 to 2005, (2) to establishrelationships between SAT anomalies and HB‐wide meanSIC anomalies and SIEs per week(s) of year (WOY; 1980–2005), and (3) to examine the relationship between SATanomalies and atmospheric indices.

Figure 1. Study site map.


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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 DataCenter [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, NOAAAVHRR, RADARSAT‐1, and ENVISAT ASAR. GIS infor-mation from the U.S. National Ice Center and spatial data fromother national and international partners may be integrated toproduce the final product. Although the CIS data go back to1970, the charts produced since the early 1980s are of moreconsistent quality, owing to improvements in Earth obser-vation technology. Data used in the study are from 1980 to2005. For the HB area the CIS data have temporal limitationsin terms of doing ice climatology work, especially during thefall period. OnlyWOY 43–48 have a consistent set of weeklyobservations 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) encom-passing 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 fromthe 26 year means. To determine trends in sea ice concen-tration anomalies, a least‐squares linear regression was cal-culated for each grid point over the 26 year period, where theslope 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 auto-correlation (assumptions of the general linear model) andwe found each to be sufficiently low to allow for use ofparametric analysis. We thus opted for the parametric generallinear model rather than a nonparametric equivalent. Thestatistical significance of each trend per grid point wascomputed and trends meeting the p = 0.1, 0.05, and 0.01levels 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 into1980–1995 and 1996–2005. The 1996 segmentation waschosen for two reasons: (1) the period prior to this year wasrepresentative of a relatively cooler period dominated bypositive SIC anomalies and therefore provided a good con-trast to the warmer period following 1995, dominated bynegative sea ice anomalies; and (2) there was a significantchange in technology with the introduction of RADARSAT‐1data in 1996, which allowed for improved mapping ofnearshore areas owing to increased resolution and improveddetectability of new and young ice. The change in technologyexplains the positive nearshore anomalies that appear duringthe relatively warmer period (1996–2005).[20] The SIC trend maps were supplemented with SIC

difference maps showing the mean differences in SIC over1980–1995 versus 1996–2005. The statistical significanceof the differences between the two time periods was assessedper grid point using a two‐tailed Student’s t test. Significantdifferences were mapped at p = 0.1, 0.05, and 0.01 probabilitylevels for each WOY (43–48). Again, normality assumptionswere tested and the parametric approach was selected overthe 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) thepreceding criteria; those meeting the SIC criteria per gridpoint/week were summed and divided by the number ofyears within the observational window. The ≥20% SICprobability 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]. Probabilitymaps were produced for each WOY for the entire time series(1980–2005), in part to describe the freezeup sequence. Iceprobability difference maps were also generated using the≥80% SIC data perWOY.Mean differences (and significance)in SIEs using SICs ≥80% were computed for 1980–1995versus 1996–2005.

Table 1. Week of Year and Associated Datesa

WOY Dates

43 22–28 Oct44 29 Oct to 4 Nov45 5–11 Nov46 12–18 Nov47 19–25 Nov48 26 Nov to 3 Dec49 4–9 Dec50 10–16 Dec51 17–23 Dec52 24–30 Dec01 1–7 Jan02 8–14 Jan

aWOY, week of year.

Figure 2. Surface air temperature (SAT) stations used tocreate the CANGRD data of Environment Canada. Thedashed line delineates the area used to generate the regionalair temperature anomaly index for Hudson Bay (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 toWOY 02, SIC data from PMW data [Cavalieri et al., 1996]were used to supplement the CIS data, thus providing asecond estimate of change for the full freezeup period(WOY 43 to 02) These data are provided in a polar stereo-graphic 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 com-puted per WOY using the 26 year mean (1980–2005) as thebaseline. SIC trends and significance were computed usingthe anomaly data as they were for the CIS data. Although theSICs computed from the PMW data are internally consistent,it is well understood that these data tend to seasonally under-estimate SICs relative to the CIS data [Agnew and Howell,2003], especially in ice marginal zones and during freezeupand melt conditions. Our use of anomalies rather than absoluteconcentrations 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 oneof the best data sources available to monitor seasonal icecover on a weekly basis, as CIS data are not always con-sistently available. As with the CIS data, differences in SIEwere computed for WOY 46–52 based on SICs ≥60%, 1980–1995 versus 1996–2005, and their statistical significance wasdetermined.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 collectionended. Work published thus far [Gagnon and Gough, 2006]has not included the recent warming trend. Data collection inHB started again in 2002. The only station collecting icethickness is Coral Harbour in northern HB (R. Chagnon,CIS, personal communication, 2008). Because of gaps in thedata, mean ice thickness, and SATs, comparisons were madebetween the following time periods: 1980–1989 and 2002–2007. Statistical significance of the mean differences wascomputed using a two‐tailed Student’s t test.

2.4. Hemispheric Teleconnections

[25] Hemispheric teleconnections were examined in thecontext of interannual regional SATs during the fall period inHB. Various climate indices have previously been identifiedas potentially significant in relation to HB SATs, includingthe NAO, AO, SOI, EP/NP index, and PDO. Details of howeach index functions are well presented in the literature and,as such, are not repeated here. Each index has an associatedseasonal pressure and SAT pattern. A correlation map of eachindex (in its positive phase) showing its associated 500 mbgeopotential heights and SATs were generated using Webtools at the National Oceanic and Atmospheric AdministrationEarth System Research Laboratory (http://www.cdc.noaa.gov/data/correlation/index.html/) based on National Centers forEnvironmental Prediction/National Center for AtmosphericResearch reanalysis data [Kalnay et al., 1996] for the period1980–2005. The observed pressure and temperature patternsare discussed in relation to the HB area.[26] The monthly standardized teleconnection data were

downloaded from NOAA’s National Weather Service Cli-mate Prediction Centre ftp site (NAO, EP/NP, SOI) and

from the Climate Diagnostics Center (National Oceanicand Atmospheric Administration; http://www.cdc.noaa.gov/ClimateIndices) for the AO index and from the Joint Institutefor 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 ofinterest. The AO and NAO means were computed based on a4 month lead (ending in the month of interest); indices relatedto the Pacific region were computed based on a 5 month lead(SOI, PDO, and EP/NP). Recall that SAT anomalies used inthis study were based on a 3 month moving average, so the4–5 month leads to establish the dominant seasonal phase ofan index and hence the dominant atmospheric circulationpattern are reasonable.[28] Correlations between standardized climate indices and

SAT anomalies were made interannually over several timeperiods, 1951–2005, 1980–2005, and the “cool” and “warm”episodes within 1980–2005. We tested the interannual datafor both normality and autocorrelation (assumptions of thegeneral linear model) and we found each to be sufficientlylow to allow for use of parametric analysis. Because of theinherent variability of the indices and the varying periodicityof 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 aperiodicity at scales of 20 to 30 years [Lindsay and Zhang,2005]), 5 year running means for both the index and SATanomalies were also used to look at more general trends, thuscomplementing the interannual statistics. Although resultsbased on the running means meet most of the assumptions oflinear regression, the data are by definition autocorrelated(Table 10). We therefore caution the reader to use the sta-tistical relationships as evidence for the underlying processescontrolling these relationships rather than for hypothesistesting. Using a running mean is consistent with the 5 yearrunning mean used by Déry and Wood [2004] and the 7 yearrunning mean used by Polyakova et al. [2006] to assess long‐term trends in indices, versus precipitation, SATs, etc.

3. Results

[29] Results are presented in the following order: (1) areview of SAT trends in the HB region from 1950 to 2005,to provide a context for the observed sea ice anomalies andtrends; (2) sea ice conditions and trends in HB from 1980 to2005 and their relationship to basin‐wide SAT anomalies;and (3) correlation of longer‐term fall SAT anomalies in HBwith observed variations in standardized teleconnections.

3.1. Hudson Bay Air Temperature Trends

[30] The trends in SAT anomalies (Figure 3) are based ona 3 month running mean ending in the month of interest.The temperature trends throughout HB and the surroundingregion are positive, indicating a warming of 0.2 to 1.8°C perdecade, depending on the month and location. In general, thelargest increases are on the eastern half of HB and the lowestare along the southern coast of HB between the Nelson RiverEstuary 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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the western side of HB (0.4 to 0.6/decade), with trends at0.4°C generally being nonsignificant. November trendsincrease to 1.0°C per decade to the north of HB and remainstatistically significant (95%), while the highest trends areobserved in Hudson Strait to the east (1.2°C/decade). Thehighest SAT anomaly trends occur in December, rangingfrom 1.1 to 1.4°C per decade (90%–95%) in northwesternHB to 1.2 to 1.6°C per decade in the eastern portion of theHB region (95%–99%). In January temperature trendsdecrease 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 decadealong 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 easternportions. Figure 4 puts the gridded temperature trends intocontext relative to longer‐term (1950–2005) mean SATanomalies around HB for the months of October to December.It is evident from the graphs that (1) SAT anomalies for agiven month vary significantly interannually; (2) the tem-perature fluctuations have a cyclical nature (smoothing splinefit l = 0.04778; minimal smoothing); and (3) temperaturesin the past have been relatively cooler, especially in the 1970sto the mid 1990s, and have warmed significantly since themid 1990s, which is particularly evident in November andDecember data (stiff smoothing spline l = 1612.676).[33] Comparing all semidecadal mean temperature anoma-

lies for October (Figure 4b), only the last decade (1996–2005)is identified as being statistically different from the otherperiods based on both the Student t test (two tailed) and theTukey‐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 tem-perature 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 temperatureanomalies (Figure 4d) identify the 1996–2005 period asbeing statistically different from the two preceding periods,spanning 1970–1995, with the Tukey‐Kramer HSD test iden-tifying 1996–2005 as the only statistically different period. Themean temperature difference between the latter two periods is1.44°C. The temperature trend averaged over the HB regionfrom 1980 to 2005 for November (Figure 4c) is 0.71°C perdecade (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 from1950 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 fromthe two preceding periods; 1996–2005 is 1.94°C warmer than1970–1979 on average and 1.85°C warmer than 1980–1995(Figure 4f). The regional temperature trend computed overHB for December (Figure 4e) is 1.0°C per decade from 1980to 2005 (p = 0.024) and 2.3°C per decade from 1989 to2005 (p = 0.008). SAT anomalies show a negative trend inSAT from 1950 to 1989 (−0.28°C/decade) but the trend isnonsignificant.

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 SICsand sea ice probability maps (for SICs ≥80% and ≥20%) for1980–2005 (Figure 5). Freezeup starts in the northern portionof HB around the shores of South Hampton Island and alongthe northwestern coast of HB (WOY 43). The probabilitiesof ≥20% ice cover are highest within the northern inletsand bays, with about a 10% probability of freezeup occurringalong the coast extending down to Cape Churchill. DuringWOY 43 there is <30% probability of “consolidated ice”(≥80% SIC) occurring in northern HB.

Figure 3. SAT anomaly trends (b) based on 3 month running means ending in (including) the month ofinterest. Significance (p) of trends at 0.01, 0.05, and 0.10 levels.


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[37] During WOY 44, mean nearshore SICs increase andstart to expand offshore from the north and northwest. Icedevelopment begins to extend southward along the coast tothe Nelson Estuary and in a narrow band along the southerncoast toward James Bay. The probability of consolidated iceremains very low (10%–30%) for the most part, with higherprobabilities (40%–60%) of consolidated ice in the northerncoastal regions and inlets. During WOY 45 ice developmentprogresses south and southeastward, with pronounced ice

development from Cape Churchill and the Nelson Riverestuary to James Bay; probabilities are high (60%–100%)that the SIC along the north and northwest coasts is con-solidated, 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 theHB in the north and west. During WOY 47–48 consolidatedice extends along the southern coast of HB into westernJames Bay, eventually encompassing Akimiski Island in

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) stiffspline fit (l = 1612.676), and interannual SAT anomalies trends per month for 1980–2005 (shaded line) and1989–2005 (bold line). (b) October semidecadal mean temperature comparisons, with 1996 to 2005 iden-tified as being statistically different. (d) November semidecadal mean temperature comparisons with 1996to 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.


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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 thecoast and then extends southward toward James Bay in thefollowing weeks. The probability of nearshore consolidatedice along the east coast of HB remains low inWOY 48 (40%).[39] The remaining freezeup sequence is shown using

SIC data derived from PMW data (Figure 6). For purposesof comparison, WOY 43–48 are shown again. Despite theabsolute differences between the data sets, the general pattern

of freezeup is consistent with the CIS data. It shows that thenorthern and northwest portions of HB start to freeze first,followed by the extension of ice along the south shore of HBinto James Bay (WOY 46–47). The central portion of HBfreezes from the north to the south and southeast, with thesoutheastern portion of the Bay freezing last. The PMW datashow that HB is consolidated by late December to earlyJanuary. Evidence of early winter latent heat polynyas inJames Bay and northwestern HB, formed as a result ofpersistent westerly and northwesterly winds, is apparent inWOY 02.

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 basedon SICs ≥80%, and (c) probabilities based on SICs ≥20%.

Figure 6. Fall freezeup sequence based on passive microwave (PMW) data using mean SICs (1980–2005) per WOY.


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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 WOY43–02 using the PMW data (Figure 8). Both data sets showthat significant negative trends in sea ice anomalies occurthroughout 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 ofdetecting and mapping new and young nearshore ice since1996 coincides with the introduction of high‐resolutionRADARSAT‐1. Positive nearshore anomalies are thereforeconsidered unrepresentative in the context of the historical

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).

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).


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data and are excluded from any statistical summaries, despitetheir appearance in CIS data.[41] The sea ice anomaly trends per WOY follow the ice

marginal zone. The trends identified as being statisticallysignificant (90%–99% level) are summarized in Tables 2and 3. The statistically significant trends based on the CISdata estimate reductions in SICs ranging from −23.3% to−26.9% per decade, implying mean reductions in SICs overthe last 26 years of −61% to −71% (Table 2, a). Mean trendswithin HB, regardless of significance, for the CIS data rangeanywhere from −13.8% to −19.2% per decade, dependingon the WOY, indicating more general reductions in SICconcentrations of −36% to −50% over broad areas of HBduring the last 26 years.[42] The statistically significant trends computed with the

PMW data are lower, but cover a broader area, compared tothe statistically significant trends of the CIS data. DuringWOY 45–50 the PMW data estimate SIC trends rangingfrom −12.7% to −16.8% per decade, indicating changes inSICs in the past 26 years ranging from −33% to −44%(Table 3). As HB sea ice consolidates late in the freezeupperiod (WOY 51–02), interannual variation in anomaliesdecrease 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), itbecomes evident that SIC anomalies from 1980 to 1995 aretypically positive (20% to 60%), with a number of negativeanomaly events. From 1996 to 2005 mean SIC anomalies inWOY 43–45 are exclusively negative (−20% to −40%);duringWOY 46–48 almost all years have negative anomaliesexcept for 2002 and 2004, where anomalies were slightlypositive.3.2.3. SIC Difference Mapping3.2.3.1. 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 posi-tive anomalies and the warmer period (+0.90 to +1.94°C;1996–2005) represents negative anomalies within the timeseries.[45] Using the CIS data, change between these two periods

is illustrated in two ways: (1) by a means comparison, toidentify statistically significant changes (at 90%–99% levels)in mean SICs per grid point (Figure 10); and (2) by a prob-ability difference map of SICs ≥80% (Figure 11c), to illus-trate change in the probability of “consolidated ice.” Bothproducts are functionally equivalent, with the former illus-trating statistically significant changes in SIC and the latterillustrating 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 thetotal HB area and lists the percentage area of HB that hasundergone statistically significant change in mean SIC (% HB(DSIC)). The differences inmean SIC between the two periodsper WOY has decreased consistently on average between−35% and −38% over each WOY within statistically signifi-cant areas, and this change has occurred over a significantportion 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) hasshown statistically significant change, from a mean SIC of45% to one of 8% (Table 4). Ending in WOY 48, the meanSIE is typically 92% of the HB area (or 7.39 × 105 km2);∼42% of that area (or 3.11 × 105 km2) has undergone signifi-cant 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 thiscase, changes in SICs ≥80% (defined hereinafter as con-solidated ice) (Figure 11). The differences between the twotime periods are quite dramatic for each week. In WOY 43the probability of any “consolidated ice” has almost been

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% Probabilityb, 10 years (90%–99% prob.) −26.9 −23.1 −23.7 −25.0 −23.7 −23.3SD 4.8 6.4 4.5 5.0 6.8 7.5% of HB area 0.11 1.28 8.51 13.52 15.2 26.18

Trends in SIC Regardless of Significance (1980–2005), Including Percent Area of HB Affectedb, all −19.2 −16.4 −16.6 −17.0 −14.3 −13.8SD 7.8 7.6 7.5 7.8 7.6 9.5% of HB area 0.49 6.26 22.3 43.93 69.32 76.12

aWOY, week of year; SIC, sea ice concentration; b, anomaly trends; HB, Hudson Bay.

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

45 46 47 48 49 50 51 52 01 02

b, 10 yr (90%–99% prob.) −12.7 −16.1 −16.8 −14.9 −14.3 −15.5 −12.1 −09.0 −05.7 −00.8SD 4.3 4.8 4.7 4.6 5.7 4.3 6.7 5.3 2.4 2.2% of HB area 9.4 34.0 52.0 50.3 57.4 36.8 41.5 33.4 14.8 10.0

aWOY, week of year; b, mean sea ice concentration trends; HB, Hudson Bay. Trends are from 1980–2005.


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eliminated, with the exception of some sheltered bays andinlets along the southern coast of South Hampton Island andthe northwestern coast of HB. The same is true in WOY 44along the southeastern portion of South Hampton Island,where in 1980–1995 a high probability of consolidated ice isreduced to a 0%–10% probability. InWOY 45 the percentagearea 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 from19.1% to 6.3% of the HB area (D 1.03 × 105 km2); inWOY 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 reducedfrom 75% to 38.3% of the HB area (D 2.95 × 105 km2). Some

of the largest changes in probability of consolidated ice areevident in WOY 48 along the southern coast of HB, from theNelson River estuary down into James Bay, and along thenortheastern 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 proba-bilities of consolidated ice to 0%–10% during the 1996–2005period.[48] Table 5 summarizes the differences in SIE between

the two periods based on SICs ≥80%. The mean differencesin ice extents between each period are statistically signifi-cant at 95% levels except for WOY 46 (90%). In WOY 47to 48 the extent of consolidated ice between the two periods

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).

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.


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decreased by 1.71 × 105 to 1.82 × 105 km2. On the basis ofthe results shown, there is at least a 1 week delay in theformation 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 SIEbeyond WOY 48. As PMW data tend to underestimate SICs

[Agnew and Howell, 2003], change detection is based onSIEs using SICs ≥60%. We start with WOY 46 to providesome overlap with the CIS data. The mean differences in SIEbetween the two periods for each WOY were statisticallysignificant (at the 95%–99% level) (Table 6). For example, inWOY 46 SIE is reduced from ∼14% (1.19 × 105 km2) to 0.8%(6.2 × 103 km2) of the HB area. The maximum differences inSIE occur in WOY 47 to 50, with differences in extentranging from −1.74 × 105 to 2.41 × 105 km2, depending on theweek. In late December the relative differences in SIE be-tween the two periods become progressively smaller, as thesea 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

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.

Table 4. Summary of Mean Sea Ice Concentration DifferencesUsing 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 PeriodMean SIC

(%)SD(%)

SIE,1980–2005

(%)

% ofHB Area(DSIC)

43 1980–1995 44.9 4.771996–2005 7.54 5.25Diff. (D) −37.36 0.57 0.41

44 1980–1995 42.29 12.031996–2005 5.66 7.1Diff. (D) −36.63 6.4 5.45

45 1980–1995 47.84 16.421996–2005 9.81 12.5Diff. (D) −38.03 23.14 17.08

46 1980–1995 52.34 19.031996–2005 17.4 17.25Diff. (D) −34.94 46.18 25.4

47 1980–1995 51.07 18.511996–2005 14.62 19.99Diff. (D) −36.45 76.33 38.81

48 1980–1995 69.22 13.591996–2005 30.74 17.79Diff. (D) −38.48 92.17 38.7

aSIC, sea ice concentration; SIE, sea ice extent; HB, Hudson Bay; WOY,weeks of year. Mean SIE for HB is based on SICs ≥20%.

Table 5. Summary ofMean Differences in Sea Ice Extent Based onSea Ice Concentrations ≥80% for 1980–1995 Versus 1996–2005Using Canadian Ice Service Data for Weeks of Year 45–48a

Data Week Year

SIE(% of

HB Area)SD(%)

Area(km2) p

CIS 45 1980–1995 12.85 10.82 1.03 × 105

1995–2005 3.41 2.65 2.74 × 104

Diff. (D) −9.44 −7.59 × 104 0.01346 1980–1995 26.62 20.14 2.14 × 105

1995–2005 12.92 12.42 1.04 × 105

Diff. (D) −13.69 −1.10 × 105 0.06647 1980–1995 46.04 27.77 3.70 × 105

1995–2005 23.37 12.66 1.88 × 105

Diff. (D) −22.66 −1.82 × 105 0.0248 1980–1995 67.15 25.72 5.40 × 105

1995–2005 45.88 21.04 3.69 × 105

Diff. (D) −21.27 −1.71 × 105 0.038

aSIE, sea ice extent; CIS, Canadian Ice Service; WOY, weeks of year.


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(1980–2005) has warmed significantly since 1995, accom-panied by a significant reduction in SIC and, ultimately,SIE. Here we quantify the dependence of weekly SIC

anomalies computed from CIS data (WOY 45–48) and fromthe PMW on interannual air temperature anomalies.[51] The relationships between SIC anomalies computed

from CIS and PMW data versus SAT anomalies are sum-marized in Figure 12 and Table 7. Coefficients of determi-nation (r2) range from 0.50 to 0.60 for CIS data and from0.54 to 0.72 for PMW data, suggesting that interannual seaice anomalies are dependent on SAT anomalies. The datashow that, over WOY 45–48, a 1°C increase in SAT resultsin a decrease in SICs by −14% on average using CIS data.The trends in SIC anomalies are somewhat lower using thePMW data (Table 7). In week 45 the relationship betweenSIC anomalies and SAT anomalies is curvilinear, because itis very early in the freezeup period so positive SIC anomaliesare favored; the same occurs in week 52, where negativeanomalies are favored, as ice is typically consolidating atthis point. DuringWOY 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 evenlydistributed (period of maximum interannual variation). SICanomaly trends during WOY 47–49 range from −9.6% to−12.6%. The correlation between air temperature anomaliesand SIC anomalies remains high (r2 = 0.60–0.72; p <0.0001) duringWOY 50–52, when slopes gradually decreasefrom −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 areperiods of maximum interannual variation for each data set;regression coefficients are summarized in Table 8. For CISdata the areal extent was based on SICs ≥80%, and forPMW data it was based on SICs ≥60% to generally approx-

Table 6. Summary of Mean Differences in Sea Ice Extent Basedon Sea Ice Concentrations ≥60% for 1980–1995 Versus 1996–2005 Using Passive Microwave Data for Weeks of Year 46–52a

WOY Year

SIE(% of

HB Area)SD(%)

Area(km2) p

46 1980–1995 14.74 16.66 1.19 × 105

1995–2005 0.77 0.96 6.20 × 103

Diff. (D) −13.97 −1.12 × 105 0.01547 1980–1995 30.37 22.95 2.44 × 105

1995–2005 7.32 7.14 5.89 × 104

Diff. (D) −23.05 −1.85 × 105 0.00548 1980–1995 51.91 23.75 4.17 × 105

1995–2005 25.12 14.78 2.02 × 105

Diff. (D) −26.79 −2.15 × 105 0.00449 1980–1995 73.25 20.3 5.89 × 105

1995–2005 43.28 22.69 3.48 × 105

Diff. (D) −29.98 −2.41 × 105 0.00250 1980–1995 87.77 15.43 7.06 × 105

1995–2005 66.14 25.31 5.32 × 105

Diff. (D) −21.63 −1.74 × 105 0.01251 1980–1995 95.18 10.07 7.65 × 105

1995–2005 79.93 19.1 6.43 × 105

Diff. (D) −15.25 −1.23 × 105 0.01352 1980–1995 99.29 2.25 7.98 × 105

1995–2005 92.67 11.03 7.45 × 105

Diff. (D) −6.61 −5.32 × 104 0.027

aHB, Hudson Bay; SIE, sea ice extent; WOY, weeks of year.

Figure 12. Relationships between SAT anomalies surrounding HB versus SIC anomalies based on CISand PMW data.


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imate the CIS extents. The areal extent of the ice is expressedas a percentage of the HB area. For the CIS data mean iceextents over 1980–2005 were 37.3% (or 3.00 × 105 km2) forweek 47 and 58.9% (or 4.58 × 105 km2) for week 48, with

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 fromPMW 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 reportingice station on HB) has decreased during the fall period,

Table 7. Regression Parameters for Sea Ice Concentration Anoma-lies Versus Air Temperature Anomalies for Canadian Ice ServiceData for WOY 45–48 and Passive Microwave Data for WOY45–52a

Source WOY Slope b1 b2 RMSE r2 p

CIS 45 −14.7849 20.43 0.52 <0.000146 −14.6069 21.00 0.50 <0.000147 −13.9777 18.89 0.54 <0.000148 −13.5203 16.14 0.60 <0.0001

PMW 45 −9.0919 2.7213 11.31 0.67 <0.0001; 0.016646 −10.9469 14.53 0.54 <0.000147 −12.2011 13.77 0.62 <0.000148 −12.6211 11.67 0.71 <0.000149 −9.6249 11.90 0.67 <0.000150 −8.0852 11.71 0.60 <0.000151 −5.6422 7.78 0.62 <0.000152 −3.2933 −0.9322 4.47 0.72 <0.0001; 0.0063

aRMSE, root mean square error; CIS, Canadian Ice Service; WOY, weekof year; PMW, passive microwave. Polynomial fits are italicized. SeeFigure 12.

Figure 13. Relationships between SAT anomalies surrounding HB and sea ice extent (SIE) expressed aspercentage area of HB (total HB area, 804 × 103 km2) for weeks of maximum interannual variation in SIEusing (a) CIS data (SIC ≥80%) and (b) PMW data (SIC ≥60%).

Table 8. Regression Parameters for Sea Ice Extent Versus SurfaceAir Temperature Anomalies for Weeks of Maximum Variation inSIEa

Data WOY Intercept Slope RMSE r2 P

CIS 47 37.320 −13.051 17.738 0.53 <0.000148 58.967 −14.505 15.870 0.64 <0.0001

PMW 48 41.604 −14.422 13.410 0.71 <0.000149 61.725 −12.038 15.076 0.67 <0.0001

aCIS, Canadian Ice Service; PMW, passive microwave; RMSE, root meansquare error; WOY, week of year; SIE, sea ice extent (% of Hudson Bayarea).


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corresponding to a period of increased SAT anomalies. Dataare shown for mid November and mid December (Figure 14).In November the mean difference in ice thickness between1980–1989 and 2002–2007 was −19.4 cm (p = 0.0458),while the mean difference in air temperature in Coral Harbourduring the same period was 1.98°C (p = 0.002). In midDecember the mean ice thickness decreased from 72 to32 cm (−40.9 cm; p = 0.0012), while the mean SAT anomalyincreased by 2.54°C (p = 0.0025). Changes in snow coverbetween the two periods were statistically insignificant forboth November and December.

3.3. SAT Anomalies Versus Teleconnection Indices

[55] For the fall period a number of indices were exam-ined to determine if any were predictive of fall temperaturesand ice conditions in HB. These included the NAO, AO,PDO, SOI, and EP/NP index. The geopotential height andtemperature correlation maps for each index in its positivephase are presented for the late summer‐early fall period forthe 1980–2005 time series (Figures 15a–15e) to provide ageneral spatial context prior to examining the HB region inmore detail. Each of the indices shown, with the exceptionof the SOI, shows that the HB area has a tendency towardcooler air surface temperatures when the indices are in theirpositive phase.

[56] The extent to which the various indices are predictiveof interannual SAT anomalies for the region surroundingHB for the periods ending in October to December aresummarized 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 fallperiod. During the month of October the interannual EP/NPindex 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) therelationships held true, with 62% of the variance in SATsurrounding HB being explained by the EP/NP index over1951–2005 and 79% over 1980–2005. An EP/NP index wasnot 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. TheAO was not significant at all with the exception of a weakcorrelation in October (1951–2005). The low correlationsbetween the NAO and the AO very early in the season areconsistent with the observation that AO and NAO tend to bestrongest in the winter [Barry and Carleton, 2001]. ThePDO was significant (at 90%–95%) in both November andDecember but the coefficients of determination were veryweak (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 examinethe extent to which mean air temperature and index valuesvaried over time (Figure 16). Three spline fits (l = 0.01 (nosmoothing), 6.20 (moderate), and 1612.7 (high)) were addedto the temporal plots for illustrative purposes to highlight thecyclical nature of the indices and SAT anomalies, includingthe longer‐term low‐frequency variations exhibited by eachof the variables from 1951 to 2005.[60] The means over the 1999–2005 period (Figure 16),

with few exceptions, were statistically different from those inthe two preceding intervals (1985–1991, 1992–1998). Also,all indices changed phase in the mid 1990s and showed trendsin index values that are typically associated with warmer falltemperatures for the HB region.[61] In terms of air temperature, the 1999 to 2005 period is

statistically warmer (mean SAT anomaly 0.83°) compared toall preceding periods. The first two periods encompassing1957–1970 are significantly warmer compared to 1992–98(D = 0.36°C) and significantly cooler (D = −0.63°C) than the1999–2005 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 negativefrom 1998–2005. Based on the means comparisons the1999–2005 period is statistically different relative to allpreceding periods. Table 10 summarizes the extent to whichthe various indices exhibit covariance to the mean air tem-peratures in HB computed for November, the period ofmaximum sea ice variability. The EP/NP index is shownto be highly predictive of SAT surrounding Hudson Bayback to 1951 (r2 = 0.75) and from 1980 to 2005 period(r2 = 0.89).

Figure 14. Mean change (D) in sea ice thickness (cm) andSATs for Coral Harbour (1980–1989 versus 2002–2007)for (a) the month of November, which showed a mean changein ice thickness D of −19.4 cm, corresponding to an average1.98°C increase in SAT; and (b) the month of December,when the ice thickness has decreased by 40 cm, with an aver-age increase in SAT of 2.54°C. Snow thickness (not shown)showed no significant differences being the two periods.


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[63] Although the NAO index shows considerable varia-tion, 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 NAOindex became strongly negative and is statistically differentfrom that in all preceding periods with the exception of1964–1970. The most recent trend favors warmer fall tem-

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 monthmeans 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/).

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 Oct −0.54 <0.0001 −0.04 NS 0.11 0.010 −0.02 NS 0.07 0.0481980–2005 −0.75 <0.0001 0.01 NS 0.08 NS −0.12 0.081 0.15 0.0471951–2005 Nov −0.62 <0.0001 −0.15 0.004 0.01 NS −0.09 0.029 0.06 0.0821980–2005 −0.79 <0.0001 −0.14 0.060 0.00 NS −0.21 0.020 0.07 NS1951–2005 Dec NA −0.07 0.060 −0.00 NS −0.05 0.089 0.01 NS1980–2005 NA −0.07 NS −0.00 NS −0.13 0.066 0.02 NS

aAO, 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; pidentifies the significance of the relationship; bold characters = 95–99% prob.


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Figure 16. Temporal plots of mean October to November SATs and hemispheric indices using a 5 yearrunning mean. For illustrative purposes three spline fits (l = 0.01, no smoothing; l = 6.20, moderatesmoothing; 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) showsthe mean (centerline) and the upper and lower 95% confidence limits, delineated by the tips of the diamonds.


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peratures. The NAO index is correlated with regional SATanomalies from 1951 to 2005 (r2 = 0.39) and from 1980 to2005 (r2 = 0.65) (Table 10). For 1951–2005 the EP/NP andNAO indices together explained 80% of the variance in SAT,and for 1980–2005 the EP/NP and NAO indices togetherexplained 94% of the variation.[64] The AO index values have been predominantly neg-

ative from 1955 to 1972 and positive from 1973 to 1996, withone reversal from 1980 to 1985 (Figure 16d). From 1997 to2005 the AO index has been positive. The low‐frequencytrend shown by l = 1612.7 indicates that the AO has a long‐term periodicity (complete cycle not shown) overlain withshorter‐term fluctuations (≤15–20 years). The AO indices arenow trending to negative values favoring warmer tempera-tures in HB. The most recent period (1999–2005) has beenconsistently negative and statistically different from the twopreceding periods, which are positive and associated withcooler November temperatures in HB. The AO index has aweak correlation with SAT from 1951 to 2005 (r2 = 0.14); thecorrelation improves over the 1980–2005 period (r2 = 0.50).The EN/NP and AO together explained ∼90% of the variancein SAT anomalies based on a 5 year running mean. The PDOindex typically has a ≥20–30 year cycle. Through the 1980sand into the late 1990s the fall PDO was positive and is nowtrending to a negative cycle (Figure 16e). The last period

(1999–2005) is statistically different from the three precedingperiods (over 1978–1998), which were in the positive phaseof the cycle. The negative phase of this index is associatedwith warmer fall temperatures in HB. Over 1950–2005 thePDO index is not strongly correlated with SAT (r2 = 0.20),although slightly better than the AO. During the 1980–2005the PDO is more highly correlated (r2 = 0.70).[65] The SOI is quite variable and generally the most

poorly correlated index (interannually) with SAT anomaliesin HB (Table 10). Despite that, it is interesting to note thatthe very low‐frequency pattern (l = 1612.7) appears to bethe inverse of the low‐frequency decadal pattern exhibitedby the other indices, with a notable regime shift around1976–1977 [Y. Zhang et al., 1997] (Figure 16f). NegativeSOIs are loosely associated with cooler fall temperatures inHB and extreme SIE events in HB when in phase with astrong 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 inthe 1980–2005 time series. The EP/NP index is the mosthighly 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 sig-nificance. Together, the EP/NP index with either the NAOor the AO explains ∼84% of the variance in SAT anomaliesin HB. During the warming phase all indices have changedphase, indicative of warmer fall temperatures for HB. Allindices 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 anomalytrend. What can be stated is that, since 1995, the variousindices have changed phase and that the EP/NP, NAO, andAO indices appear to be those most consistently correlatedwith SAT anomalies over all periods, with the EP/NP indexbeing the single most predictive index during the fall periodand the NAO and AO contributing significantly in terms ofimproving the explained variance in SAT anomalies whenusing multiple regression.

4. Conclusions

[68] Based on the CANGRID data we have shown that SATanomaly trendswere positive (warming) aroundHB from1980to 2005. The highest andmost significant trends occurred in thenorthern and eastern portions of HB, with overall trends inSAT anomalies increasing from October (0.6–0.8°C/decade)to December (1.1–1.6°C/decade). Although statistically non-significant, the regional mean interannual SAT anomaliesshow a slight cooling period over HB from 1950 to 1989,most evident in November and December, followed by astatistically significant increase in SAT during the mid 1990sto 2005.[69] Both CIS data and PMW data showed that SIC

anomalies were decreasing throughout the fall (WOY43–01),with the most significant (negative) trends in SIC anomaliesfollowing the marginal ice zone. The statistically significanttrends in SIC anomalies using the CIS data showed negativetrends in SIC ranging from −23.3% to −26.9% per decade forweeks 43–48, resulting in significant reductions in SIE overthe last 26 years. Statistically significant trends in SICanomalies using the PMW data were lower but were more

Table 10. Matrix of Coefficients of Determination (r2) forClimate Indices Versus Surface Air Temperature Based on the5 Year Running Mean for 1980–2005, 1950–2005, 1980–1995,and 1995–2005a

EP/NP NAO AO PDO SOI

1950–2005 (n = 51)NAO 0.24AO 0.12 0.31PDO 0.17 0.08 0.28SOI −0.05 −0.01 −0.02 −0.40AT −0.75 −0.39 −0.14 −0.20 0.08

1980–2005 (n = 26)NAO 0.45AO 0.34 0.33PDO 0.55P 0.33P 0.44PSOI −0.22 −0.23 −0.34P −0.35AT −0.89 −0.65 −0.50 −0.70P 0.23

1980–1995 (n = 16)NAO 0.15AO 0.13 0.09PDO −0.02 −0.23 0.00SOI 0.00 −0.14 0.03 0.00AT −0.74 −0.38 −0.36 0.06 0.00

1995–2005 (n = 11)NAO 0.54AO 0.52 0.43PDO 0.74 0.29 0.56SOI −0.64 −0.32 −0.87 −0.77AT −0.97 −0.66 −0.55 −0.89P 0.78P

aAO, Arctic Oscillation; AT, air temperature; EP/NP, East Pacific/NorthPacific oscillation index; NAO, North Atlantic Oscillation; PDO, PacificDecadal Oscillation; SOI, Southern Oscillation. A dash indicates anegative correlation. P indicates a second‐order polynomial. Boldfaceitalic correlations are significant at 99% level, boldface correlations aresignificant at 95% level, italic correlations are significant at 90% level,and regular text correlations are nonsignificant.


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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 CISdata showed that for every 1°C increase in the mean regionalair temperature around HB, the area of SIC ≥80% (consol-idated ice) deceased by 1.05 × 105 to 1.17 × 105 km2 forweeks 47–48 (late November). Similar results were shownfor changes in SIEs using PMW data based on a slightlylower SIC threshold (SICs ≥60%).[71] Regional SAT anomalies around HB were shown to

be closely related to atmospheric indices. The EP/NP indexwas predictive of SAT anomalies in HB dating back to 1950.The NAO and AO were much less predictive; they typicallyexert their strongest influence during the winter period. Fiveyear running means were also applied to the SAT and to theteleconnections data. These data showed that the EP/NPindex together with the NAO and AO explained ∼80%–90%of the variance with SAT anomalies in November from 1951to 2005. The SOI index was consistently the most poorlycorrelated with SATs (R2 = 0.08) on an interannual basis,whereas the PDO was more predictive of SATs than the AOindex over 1951–2005.[72] Examining the longer‐term trends in air temperature

and the hemispheric indices using a 5 year running mean, itis apparent that the climate has been undergoing a regimeshift in the last 15 years and that this shift in HB during thefall appears to be associated with the low‐frequency oscil-lation pattern inherent in the various indices, particularly theEP/NP, NAO, and AO. The phase change in the mid 1990scoincides with warmer SATs in HB and associated negativeSIC anomalies and SIEs. We plan to extend this HB workby examining the winter‐to‐summer period for these samerelationships in a follow‐up paper.

[73] Acknowledgments. This work was funded by the NaturalSciences and Engineering Research Council, Canada Research Chairs pro-gram, and ArcticNet Networks of Centers of Excellence program with grantsto D.G.B. Thanks go to R. Galley for gridding and extracting the CIS dataand to the anonymous reviewers and editors of Journal of GeophysicalResearch—Oceans for improving the clarity of this presentation.

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D. G. Barber and K. P. Hochheim, Centre for Earth Observation Science,University of Manitoba, Winnipeg, MB R3T 2N2, Canada. ([email protected])


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atmospheric forcing of sea ice in hudson bay during the ...c05009 hochheim and barber: atmospheric...

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