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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, C05009, doi:10.1029/2009JC005334, 2010 Click Here for Full Article

Atmospheric forcing of ice in Hudson 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 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 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 the had large negative trends. In 1993–2007 SIC trends were consistently negative throughout the Arctic [2] Over the past several decades Arctic sea ice has and subarctic . Summer trends during the first half of the undergone significant changes in ice extent and concentra- satellite record showed negative trends in the eastern Siberian tion. In this paper we define sea ice extent (SIE) as the geo- Sea and positive trends in the Barents, Kara, and eastern graphic distribution of sea ice (presence/absence) within the Beaufort seas, in contrast to the second half of the satellite study and sea ice concentration (SIC) as the percentage record, which was dominated by negative trends throughout concentration of sea ice within a particular subset of the study the Arctic. area. From 1953 to 2006 the total SIE at the end of the [4] In Hudson Bay (HB) a number of studies have exam- summer melt season in September declined at a rate of ined trends in SIE. Parkinson et al. [1999] showed that during −7.8% per decade [Stroeve et al., 2007]. The trends in SIC 1979–1996, only very slight negative trends were detectable vary depending on the time period examined and the geo- within HB (including ): annual trends were graphic location. Passive microwave (PMW) data show that − 3 3 2 – 1.4 × 10 ± 1.4 × 10 km /yr; autumn trends were larger, trends in SIC during the 1979 1996 period were relatively − 3 3 2 − − at 2.9 × 10 ± 3.6 × 10 km /yr; and none of the seasonal small throughout the Arctic, 2.2 and 3.0% per decade, in trends were statistically significant. Gough et al. [2004] contrast to the 1997–2007 period, which showed that declines found no significant trends in freezeup dates for the fall in SIC accelerated to −10.1 and −10.7% per decade [Comiso period in southwestern HB (1971–2003) using Canadian Ice et al., 2008]. Service (CIS) data (Environment , CIS daily analysis [3] Deser and Teng [2008] showed that during the early ice charts; available at http://ice‐glaces.ec.gc.ca). part of the PMW period (1979–1993), ice trends in the ice [5] Gagnon and Gough [2005], on the contrary, found marginal zones within the polar seas varied geographically. statistically significant trends in freezeup dates using point During the winter the and Bering seas had large observations. Of the 25 points used throughout HB during positive trends in SIC; the and Barents seas and the freezeup period, only 6 points, located in the northern reaches of HB, showed statistically significant freezeup date

1 trends (based on an SIC ≥50%); results indicated that Centre for Observation Science, University of , , – – Manitoba, Canada. freezeup was occurring 0.32 0.55 day/yr earlier (1971 2003). Kinnard et al. [2006] showed no significant trends in Copyright 2010 by the American Geophysical Union. SICs based on CIS data from 1980 to 2004. The most recent 0148‐0227/10/2009JC005334

C05009 1of20 C05009 HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB C05009 work by Parkinson and Cavalieri [2008] showed statistically ability is the main factor controlling temperature variation in significant annual trends for SIE in HB (including Foxe the winter season over , with positive NAO Basin), with decreases of −4.5 × 103 ± 0.9 × 103 km2/yr indices coinciding with early formation of sea ice in HB. In (or −5.3% ± 1.1% per decade); fall trends were −8.5 × 103 ± addition to the NAO, Kinnard et al. [2006] showed that the 1.9 × 103 km2/yr (or −12.93% ± 2.9% per decade). ice regime in HB was significantly correlated with the East [6] Gagnon and Gough [2006] used ice thickness data Pacific/North Pacific oscillation (EP/NP) index during the from the CIS to examine trends in thickness. The data used spring (r = 0.63) and summer (r = 0.57), both being signifi- in their study were collected from the early 1960s to the cant at the p < 0.05 level. A positive phase of the EP/NP index early 1990s (the data collection program was terminated in corresponds to a high pressure located over Alaska/western ∼1990). Temperature trends were predominantly negative Canada and a low pressure over the central North Pacific and and ice thickness trends were predominantly positive in HB eastern . This configuration acts to draw cool during the fall and winter periods. Arctic air south to eastern North America including the HB [7] The variations in SIC and SIE throughout the Arctic and region. sub‐Arctic have been variously attributed to some combina- [9] In summary, previous work has shown that the dis- tion of anthropogenic forcing due to greenhouse gases and tribution of sea ice anomalies throughout the Arctic and low‐frequency oscillations in atmospheric circulation and subarctic seas have not been uniform over the PMW satellite associated positive feedback mechanisms [Johannessen et record (1978 to now). This observation is significant for the al., 2004; Holland et al., 2006]. Interannual variations in HB region and eastern Canada in general. Whereas much of SIC anomalies in the Arctic from 1960 to the mid 1990s are the Arctic was warming, the HB region was actually cooling partly explained by variations in the Arctic Oscillation (AO) (1979–1993), hence the positive sea ice anomalies early in and North Atlantic Oscillation (NAO) [Venegas and Mysak, the PMW record [Deser and Teng, 2008], the lack of signifi- 2000; Deser, 2000; Polyakov and Johnson, 2000; Comiso cant statistical trends in SIE from 1979 to 1996 [Parkinson et et al., 2008; Deser and Teng 2008; Overland et al., 2008] al., 1999], and the increasing sea ice thickness from 1960 to the and their effects on ice circulation (ice export) [Rigor et al., early 1990s [Gagnon and Gough,2006].Morerecentdata 2002], air temperature [Polyakov et al., 2003], and oceanic have shown that warming has occurred in HB since 1999–2003 heat transport [J. Zhang et al., 2004]. In addition to the [Gagnon and Gough, 2005; Ford et al., 2009; Laidler et al., gradual warming of the Arctic over the last 50 years, 2009] and that statistically significant negative SIC trends Lindsay and Zhang [2005] have also suggested that the are now evident in the Foxe Basin and HB [Parkinson and temporary phase change associated with the Pacific Decadal Cavalieri,2008]. Oscillation (PDO) together with the AO in 1988 may have [10] This paper seeks to build on previous work as it relates contributed significantly to the flushing of older ice out to the HB region by examining both SIE and SIC and then of the Arctic. More recently, warming in the high Arctic examining the possible atmospheric forcing mechanisms has accelerated, independent of any indices, even beyond linked to these sea ice metrics. In this paper we (1) provide worst‐case scenarios using greenhouse gas forcing, sug- detailed gridded representations of SAT trends of the land gesting that factors such as the sea ice‐albedo feedback surrounding HB to provide a context for the observed mechanism are contributing significantly to recent decreases changes in SIC and SIE; (2) show the weekly evolution of in SIE [Lindsay and Zhang, 2005; Holland et al., 2006]. sea ice cover during the fall period from 1980 to 2005, [8] The HB region differs from the Arctic and provide gridded maps of SIC trends over 1980–2005, and adjacent seas in that it is essentially a closed system and, provide SIC difference maps comparing the “cool period” therefore, isolated from the effects of open‐ocean circulation (1980–1995) to the “warm period” (1996–2005); (3) quantify [Wang et al., 1994] (e.g., warm‐water intrusions and sea ice the relationship between SAT anomalies and SIC anomalies export) and more reflective of atmospheric forcing, specif- and SIE; and (4) examine the relationships between SAT ically changes in air temperature and winds. Interannual anomalies and standardized atmospheric indices relevant to variations in SIE in HB have been attributed largely to a the fall period in HB. number of standardized hemispheric indices that are asso- ciated with characteristic wind, temperature, and 2. Methods patterns. Wang et al. [1994] and Mysak et al. [1996] showed that both the NAO and the Southern Oscillation Index (SOI) 2.1. Study Area were associated with peak SIEs in HB (1953–1993). Strong [11] HB is a large, shallow, inland sububarctic sea; it positive NAOs were associated with a deepened Icelandic covers approximately 804,000 km2, and its mean depth is Low, northerly winds, and lower temperatures over eastern <150 m [Prinsenberg, 1986] (Figure 1). HB is 95%–100% Canada, whereas negative NAOs were associated with ice covered during the winter months and typically ice‐free southerly winds and warmer temperatures. Years with strong during August–September. It has two openings: one to the negative SOIs during the spring/summer/fall period were northwest via and the other east of associated with more ice production during the freezeup South Hampton Island into the . HB is isolated period, with the largest negative SAT anomalies occurring from open ocean circulation, therefore variations in sea ice in August (cool summer); years with strong positive SOIs cover are largely a function of atmospheric forcing [Wang et tended to have positive temperature anomalies. The largest al., 1994]. Currents within HB are dominantly wind driven sea ice anomalies within HB were associated with strong and cyclonic at all depths, reaching a maximum in November negative SOIs during the summer and strong positive NAOs when the winds are strongest [Prinsenberg, 1986; Saucier during the winter. Prinsenberg et al. [1997], Kinnard et al. et al., 2004]. The circulation pattern in is also [2006], and Qian et al. [2008] all showed that NAO vari- 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 the mean HB regional temperature anomalies (per month per 3.7 × 106 km2 in North America and its freshwater dis- year) were 50°–65°N and 72.5°–100°W (Figure 2). The use charge of ∼950 km3/yr represents 20% of the total annual of temperature anomalies in gridding data has the advantage runoff to the [Déry and Wood, 2004]. During of removing location, physiographic, and elevation effects. the fall period SSTs are highest in the James Bay area and Monthly temperature anomalies were computed for each southeastern HB, extending north along the east coast of month per year relative to the 1980–2005 mean to match the HB [Saucier et al., 2004]. This area is typically the last to normals computed for sea ice data. A 3 month running mean freeze up. was applied to the monthly SAT anomaly data ending in (including) the month of interest; the intent here was to 2.2. Surface Air Temperature (SAT) Data incorporate lead‐up SATs to obtain a (moving) seasonal temperature index (anomaly) value. We tested both normality [12] We use a SAT product known as CANGRID, devel- and autocorrelation (assumptions of the general linear model) oped for climate change studies by the Climate Research and we found each to be sufficiently low to allow for use of Division of Environment Canada. It uses adjusted historical parametric analysis. SAT anomaly trends and their statistical Canadian climate data [Vincent and Gullet, 1999] that significance (p; at 0.10, 0.05, and 0.01) were mapped based account for changes resulting from reporting station system on the least‐squares fit per grid point (n = 1128). The trend changes. A full description of the Canada‐only data set is maps intend to show the regional distribution of SAT provided by McKenney et al. [2005]. The CANGRID grid anomalies around HB. data have a spatial resolution of 50 km and cover land [14] These temperature data were used (1) to examine surfaces only. general temperature trends from 1950 to 2005, (2) to establish [13] The CANGRID data used in this study consist of relationships between SAT anomalies and HB‐wide mean monthly air temperature anomalies dating back to 1950, a SIC anomalies and SIEs per week(s) of year (WOY; 1980– period when most of the stations in the region were observing on a regular basis (E. Milewska, Environment Canada, per- 2005), and (3) to examine the relationship between SAT anomalies and atmospheric indices. sonal communication, 2009). The bounds used to compute

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Cavalieri, 2008]. Data were tested for normality and auto- correlation (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 con- trast 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 Figure 2. Surface air temperature (SAT) stations used to 1980–1995 versus 1996–2005. The statistical significance create the CANGRD data of Environment Canada. The of the differences between the two time periods was assessed dashed line delineates the area used to generate the regional per grid point using a two‐tailed Student’s t test. Significant air temperature anomaly index for Hudson Bay (HB). 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 2.3. Sea Ice Data the nonparametric equivalent. [15] The SIC and SIE data were obtained from two sources: [21] Ice probability maps were also computed for SICs CIS digital ice charts (available at http://ice‐glaces.ec.gc.ca) ≥20% and ≥80% per grid point. Each grid point per year/ and PMW data processed at the National Snow and Ice Data week was classified as meeting (1) or not meeting (0) the Center [Cavalieri et al., 1996]. preceding criteria; those meeting the SIC criteria per grid 2.3.1. Canadian Ice Service (CIS) Data point/week were summed and divided by the number of ≥ [16] CIS ice charts are produced weekly from a variety years within the observational window. The 20% SIC of sources, including aerial reconnaissance data, NOAA probability maps depict the leading ice edge during freezeup, AVHRR, RADARSAT‐1, and ENVISAT ASAR. GIS infor- while the ≥80% SIC probability maps are intended to depict mation from the U.S. National Ice Center and spatial data from “consolidated ice” [after Galley et al., 2008]. Probability other national and international partners may be integrated to maps were produced for each WOY for the entire time series produce the final product. Although the CIS data go back to (1980–2005), in part to describe the freezeup sequence. Ice 1970, the charts produced since the early 1980s are of more probability difference maps were also generated using the consistent quality, owing to improvements in Earth obser- ≥80% SIC data per WOY. Mean differences (and significance) vation technology. Data used in the study are from 1980 to in SIEs using SICs ≥80% were computed for 1980–1995 2005. For the HB area the CIS data have temporal limitations versus 1996–2005. in terms of doing ice climatology work, especially during the fall period. Only WOY 43–48 have a consistent set of weekly Table 1. Week of Year and Associated Datesa observations for the 26 year period being examined (Table 1). [17] Each CIS data file was converted from its .e00 GIS WOY Dates 2 format to a 2.5 km resolution grid (n = 128,656) encom- 43 22–28 Oct passing only those areas within HB (including James Bay) 44 29 Oct to 4 Nov that were consistently observed during the 26 year period 45 5–11 Nov (see Figure 1). 46 12–18 Nov 47 19–25 Nov [18] Sea ice anomalies for each grid point per year per 48 26 Nov to 3 Dec WOY were computed by subtracting the weekly SICs from 49 4–9 Dec the 26 year means. To determine trends in sea ice concen- 50 10–16 Dec tration anomalies, a least‐squares linear regression was cal- 51 17–23 Dec culated for each grid point over the 26 year period, where the 52 24–30 Dec 01 1–7 Jan slope of the regression indicates the trend per year following 02 8–14 Jan [Parkinson et al., 1999; Galley et al., 2008; Parkinson and aWOY, week of year.

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2.3.2. Passive Microwave (PMW) Data from the Climate Diagnostics Center (National Oceanic [22] Because of significant gaps in the observational record and Atmospheric Administration; http://www.cdc.noaa.gov/ of the CIS data during the freezeup period, from WOY 49 to ClimateIndices) for the AO index and from the Joint Institute WOY 02, SIC data from PMW data [Cavalieri et al., 1996] for the Study of the Atmosphere and Ocean (http://jisao. were used to supplement the CIS data, thus providing a washington.edu/) for the PDO index. second estimate of change for the full freezeup period [27] Since the indices fluctuate on a monthly basis, longer‐ (WOY 43 to 02) These data are provided in a polar stereo- term seasonal means were computed leading the month of graphic projection and have a spatial resolution of 25 × 25 km. interest. The AO and NAO means were computed based on a [23] By use of the daily SIC data, a weekly data set was 4 month lead (ending in the month of interest); indices related created for WOY 43–02. Sea ice anomaly maps were com- to the Pacific region were computed based on a 5 month lead puted per WOY using the 26 year mean (1980–2005) as the (SOI, PDO, and EP/NP). Recall that SAT anomalies used in baseline. SIC trends and significance were computed using this study were based on a 3 month moving average, so the the anomaly data as they were for the CIS data. Although the 4–5 month leads to establish the dominant seasonal phase of SICs computed from the PMW data are internally consistent, an index and hence the dominant atmospheric circulation it is well understood that these data tend to seasonally under- pattern are reasonable. estimate SICs relative to the CIS data [Agnew and Howell, [28] Correlations between standardized climate indices and 2003], especially in ice marginal zones and during freezeup SAT anomalies were made interannually over several time and melt conditions. Our use of anomalies rather than absolute periods, 1951–2005, 1980–2005, and the “cool” and “warm” concentrations minimizes this problem of underestimation, episodes within 1980–2005. We tested the interannual data since we are in fact presenting relative (rather than absolute) for both normality and autocorrelation (assumptions of the change. Even with these limitations, the PMW data set is one general linear model) and we found each to be sufficiently of the best data sources available to monitor seasonal ice low to allow for use of parametric analysis. Because of the cover on a weekly basis, as CIS data are not always con- inherent variability of the indices and the varying periodicity sistently available. As with the CIS data, differences in SIE of each of them (e.g., the AO (and NAO) operates at 2 to 3.5, were computed for WOY 46–52 based on SICs ≥60%, 1980– 5.7 to 7.8, and 12 to 20 year scales [Venegas and Mysak, 1995 versus 1996–2005, and their statistical significance was 2000; Jevrejeva et al., 2003], and the PDO index displays a determined. periodicity at scales of 20 to 30 years [Lindsay and Zhang, 2.3.3. Sea Ice Thickness Data 2005]), 5 year running means for both the index and SAT [24] Ice thickness data have been collected in HB by the CIS anomalies were also used to look at more general trends, thus (Environment Canada; available at http://ice‐glaces.ec.gc.ca) complementing the interannual statistics. Although results from the late 1950s to the early 1990s, when data collection based on the running means meet most of the assumptions of ended. Work published thus far [Gagnon and Gough, 2006] linear regression, the data are by definition autocorrelated has not included the recent warming trend. Data collection in (Table 10). We therefore caution the reader to use the sta- HB started again in 2002. The only station collecting ice tistical relationships as evidence for the underlying processes thickness is in northern HB (R. Chagnon, controlling these relationships rather than for hypothesis CIS, personal communication, 2008). Because of gaps in the testing. Using a running mean is consistent with the 5 year data, mean ice thickness, and SATs, comparisons were made running mean used by Déry and Wood [2004] and the 7 year between the following time periods: 1980–1989 and 2002– running mean used by Polyakova et al. [2006] to assess long‐ 2007. Statistical significance of the mean differences was term trends in indices, versus precipitation, SATs, etc. computed using a two‐tailed Student’s t test. 2.4. Hemispheric Teleconnections 3. Results [25] Hemispheric teleconnections were examined in the [29] Results are presented in the following order: (1) a context of interannual regional SATs during the fall period in review of SAT trends in the HB region from 1950 to 2005, HB. Various climate indices have previously been identified to provide a context for the observed sea ice anomalies and as potentially significant in relation to HB SATs, including trends; (2) sea ice conditions and trends in HB from 1980 to the NAO, AO, SOI, EP/NP index, and PDO. Details of how 2005 and their relationship to basin‐wide SAT anomalies; each index functions are well presented in the literature and, and (3) correlation of longer‐term fall SAT anomalies in HB as such, are not repeated here. Each index has an associated with observed variations in standardized teleconnections. seasonal pressure and SAT pattern. A correlation map of each index (in its positive phase) showing its associated 500 mb 3.1. Hudson Bay Air Temperature Trends geopotential heights and SATs were generated using Web [30] The trends in SAT anomalies (Figure 3) are based on tools at the National Oceanic and Atmospheric Administration a 3 month running mean ending in the month of interest. Earth System Research Laboratory (http://www.cdc.noaa.gov/ The temperature trends throughout HB and the surrounding data/correlation/index.html/) based on National Centers for region are positive, indicating a warming of 0.2 to 1.8°C per Environmental Prediction/National Center for Atmospheric decade, depending on the month and location. In general, the Research reanalysis data [Kalnay et al., 1996] for the period largest increases are on the eastern half of HB and the lowest 1980–2005. The observed pressure and temperature patterns are along the southern coast of HB between the Nelson are discussed in relation to the HB area. Estuary and James Bay. [26] The monthly standardized teleconnection data were [31] In October temperatures are warming from 0.6 to downloaded from NOAA’s National Weather Service Cli- 0.8°C/decade around the northern and eastern coasts of HB mate Prediction Centre ftp site (NAO, EP/NP, SOI) and (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 [34] In November the semidecadal mean temperature 0.4°C generally being nonsignificant. November trends anomalies (Figure 4d) identify the 1996–2005 period as increase to 1.0°C per decade to the north of HB and remain being statistically different from the two preceding periods, statistically significant (95%), while the highest trends are spanning 1970–1995, with the Tukey‐Kramer HSD test iden- observed in Hudson Strait to the east (1.2°C/decade). The tifying 1996–2005 as the only statistically different period. The highest SAT anomaly trends occur in December, ranging mean temperature difference between the latter two periods is from 1.1 to 1.4°C per decade (90%–95%) in northwestern 1.44°C. The temperature trend averaged over the HB region HB to 1.2 to 1.6°C per decade in the eastern portion of the from 1980 to 2005 for November (Figure 4c) is 0.71°C per HB region (95%–99%). In January temperature trends decade (p = 0.056), computed from the inflection point decrease to 0.4 to 0.8°C/decade in the north and northwest (∼1989); the temperature trend is 1.8°C per decade (p =0.005). (not statistically significant) and to 0.8 to 1.2°C per decade SAT anomalies show a slight negative trend in SAT from along the southeastern coast of HB including James Bay 1950 to 1989 (−0.12°C/decade) but the trend is nonsignificant. (significant at 90%–95% probability). [35] In December both the Student t test and the Tukey‐ [32] These results show that the air temperature around HB Kramer test show 1996–2005 to be statistically different from has been warming, particularly in the northern and eastern the two preceding periods; 1996–2005 is 1.94°C warmer than portions. Figure 4 puts the gridded temperature trends into 1970–1979 on average and 1.85°C warmer than 1980–1995 context relative to longer‐term (1950–2005) mean SAT (Figure 4f). The regional temperature trend computed over anomalies around HB for the months of October to December. HB for December (Figure 4e) is 1.0°C per decade from 1980 It is evident from the graphs that (1) SAT anomalies for a to 2005 (p = 0.024) and 2.3°C per decade from 1989 to given month vary significantly interannually; (2) the tem- 2005 (p = 0.008). SAT anomalies show a negative trend in perature fluctuations have a cyclical nature (smoothing spline SAT from 1950 to 1989 (−0.28°C/decade) but the trend is fit l = 0.04778; minimal smoothing); and (3) temperatures nonsignificant. in the past have been relatively cooler, especially in the 1970s to the mid 1990s, and have warmed significantly since the 3.2. Fall Sea Ice Distribution and Trends mid 1990s, which is particularly evident in November and 3.2.1. Fall Freezeup Sequence, 1980–2005 December data (stiff smoothing spline l = 1612.676). [36] The early freezeup sequence for the study period is [33] Comparing all semidecadal mean temperature anoma- represented by CIS data (WOY 43–48) showing mean SICs lies for October (Figure 4b), only the last decade (1996–2005) and sea ice probability maps (for SICs ≥80% and ≥20%) for is identified as being statistically different from the other 1980–2005 (Figure 5). Freezeup starts in the northern portion periods based on both the Student t test (two tailed) and the of HB around the shores of South Hampton Island and along Tukey‐Kramer honestly significant difference (HSD) test. the northwestern coast of HB (WOY 43). The probabilities The mean temperature difference in HB for October, 1980– of ≥20% ice cover are highest within the northern inlets 1995 versus 1996–2005, is 0.99°C; the mean regional tem- and bays, with about a 10% probability of freezeup occurring perature trend computed over 1980–2005 is 0.5°C per decade along the coast extending down to Cape Churchill. During (p = 0.025); and the trend computed from the hinge point WOY 43 there is <30% probability of “consolidated ice” (∼1989) to 2005 is 1.1°C per decade (p = 0.0098). (≥80% SIC) occurring in northern HB.

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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 iden- tified 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 development from Cape Churchill and the start to expand offshore from the north and northwest. Ice estuary to James Bay; probabilities are high (60%–100%) development begins to extend southward along the coast to that the SIC along the north and northwest coasts is con- the Nelson Estuary and in a narrow band along the southern solidated, and probabilities of consolidated ice remain low coast toward James Bay. The probability of consolidated ice (≤40%) along the southern coast to James Bay. In WOY 46– remains very low (10%–30%) for the most part, with higher 48 consolidated sea ice (≥80% SIC) extends well into the probabilities (40%–60%) of consolidated ice in the northern HB in the north and west. During WOY 47–48 consolidated coastal and inlets. During WOY 45 ice development ice extends along the southern coast of HB into western progresses south and southeastward, with pronounced ice James Bay, eventually encompassing in

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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 of freezeup is consistent with the CIS data. It shows that the (SIC ≤50%). northern and northwest portions of HB start to freeze first, [38] The east coast of HB starts to freeze much later (WOY followed by the extension of ice along the south shore of HB 46); ice first develops along the northeastern portion of the into James Bay (WOY 46–47). The central portion of HB coast and then extends southward toward James Bay in the freezes from the north to the south and southeast, with the following weeks. The probability of nearshore consolidated southeastern portion of the Bay freezing last. The PMW data ice along the east coast of HB remains low in WOY 48 (40%). show that HB is consolidated by late December to early [39] The remaining freezeup sequence is shown using January. Evidence of early winter latent heat in SIC data derived from PMW data (Figure 6). For purposes James Bay and northwestern HB, formed as a result of of comparison, WOY 43–48 are shown again. Despite the persistent westerly and northwesterly winds, is apparent in absolute differences between the data sets, the general pattern WOY 02.

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

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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) CIS data. The CIS database was queried and it was found that, [40] Trends in sea ice anomalies were computed for since 1996, nearshore new and young ice has been mapped, WOY 43–48 using the CIS data (Figure 7) and for WOY despite warmer air temperatures. The improved capability of 43–02 using the PMW data (Figure 8). Both data sets show detecting and mapping new and young nearshore ice since that significant negative trends in sea ice anomalies occur 1996 coincides with the introduction of high‐resolution throughout the fall period, indicating a decrease in SICs. RADARSAT‐1. Positive nearshore anomalies are therefore Some positive trends appear along coastal regions using the 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).

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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 −23.3 SD 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 Affected b, all −19.2 −16.4 −16.6 −17.0 −14.3 −13.8 SD 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. data and are excluded from any statistical summaries, despite 2005 time series. The cool period (1980–1995) shows posi- their appearance in CIS data. tive anomalies and the warmer period (+0.90 to +1.94°C; [41] The sea ice anomaly trends per WOY follow the ice 1996–2005) represents negative anomalies within the time marginal zone. The trends identified as being statistically series. significant (90%–99% level) are summarized in Tables 2 [45] Using the CIS data, change between these two periods and 3. The statistically significant trends based on the CIS is illustrated in two ways: (1) by a means comparison, to data estimate reductions in SICs ranging from −23.3% to identify statistically significant changes (at 90%–99% levels) −26.9% per decade, implying mean reductions in SICs over in mean SICs per grid point (Figure 10); and (2) by a prob- the last 26 years of −61% to −71% (Table 2, a). Mean trends ability difference map of SICs ≥80% (Figure 11c), to illus- within HB, regardless of significance, for the CIS data range trate change in the probability of “consolidated ice.” Both anywhere from −13.8% to −19.2% per decade, depending products are functionally equivalent, with the former illus- on the WOY, indicating more general reductions in SIC trating statistically significant changes in SIC and the latter concentrations of −36% to −50% over broad areas of HB illustrating shifts in probability. during the last 26 years. [46] Table 4 summarizes the statistically significant changes [42] The statistically significant trends computed with the in mean SIC (%) between the two periods for each WOY. PMW data are lower, but cover a broader area, compared to Table 4 also reports the mean sea SIE (based on ≥20% SIC) the statistically significant trends of the CIS data. During over 1980–2005 per WOY expressed as a percentage of the WOY 45–50 the PMW data estimate SIC trends ranging total HB area and lists the percentage area of HB that has from −12.7% to −16.8% per decade, indicating changes in undergone statistically significant change in mean SIC (% HB SICs in the past 26 years ranging from −33% to −44% (DSIC)). The differences in mean SIC between the two periods (Table 3). As HB sea ice consolidates late in the freezeup per WOY has decreased consistently on average between period (WOY 51–02), interannual variation in anomalies −35% and −38% over each WOY within statistically signifi- decrease and trends become progressively smaller, from cant areas, and this change has occurred over a significant −12.1% to −0.8% per decade. portion of the mean SIE. For example, early in the season [43] When the mean CIS anomalies (meeting 90%–99% (WOY 43) the mean SIE is 0.57% of the HB area (or 4.58 × probability) are plotted by year per WOY (Figure 9), it 103 km2); nevertheless, 72% of that area (3.29 × 103 km2)has becomes evident that SIC anomalies from 1980 to 1995 are shown statistically significant change, from a mean SIC of typically positive (20% to 60%), with a number of negative 45% to one of 8% (Table 4). Ending in WOY 48, the mean anomaly events. From 1996 to 2005 mean SIC anomalies in SIE is typically 92% of the HB area (or 7.39 × 105 km2); WOY 43–45 are exclusively negative (−20% to −40%); ∼42% of that area (or 3.11 × 105 km2) has undergone signifi- during WOY 46–48 almost all years have negative anomalies cant change, from a mean SIC of 69% down to one of 30%. except for 2002 and 2004, where anomalies were slightly [47] A different representation of change within the HB is positive. provided by the sea ice probability map, showing, in this 3.2.3. SIC Difference Mapping case, changes in SICs ≥80% (defined hereinafter as con- 3.2.3.1. CIS Data solidated ice) (Figure 11). The differences between the two [44] On the basis of SAT and SIC anomaly data we have time periods are quite dramatic for each week. In WOY 43 identified two periods or climate regimes within the 1980 to 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 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 −00.8 SD 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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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 of the largest changes in probability of consolidated ice are inlets along the southern coast of South Hampton Island and evident in WOY 48 along the southern coast of HB, from the the northwestern coast of HB. The same is true in WOY 44 Nelson River estuary down into James Bay, and along the along the southeastern portion of South Hampton Island, northeastern coast of HB, extending into the central basin. where in 1980–1995 a high probability of consolidated ice is Here probabilities of consolidated ice have decreased by reduced to a 0%–10% probability. In WOY 45 the percentage −50%, to >more than −70%, thus often reducing the proba- area where one would expect a high probability (60%–100%) bilities of consolidated ice to 0%–10% during the 1996–2005 of SIC ≥80% is reduced from 9% to 0.87% of the HB area period. 5 2 (D 6.54 × 10 km ); in WOY 46 the area is reduced from [48] Table 5 summarizes the differences in SIE between 19.1% to 6.3% of the HB area (D 1.03 × 105 km2); in the two periods based on SICs ≥80%. The mean differences WOY 47 the area is reduced from 37.5% to 20.3% of HB in ice extents between each period are statistically signifi- (D 1.35 × 105 km2); and in WOY 48 the area is reduced cant at 95% levels except for WOY 46 (90%). In WOY 47 from 75% to 38.3% of the HB area (D 2.95 × 105 km2). Some 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.

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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 [Agnew and Howell, 2003], change detection is based on the results shown, there is at least a 1 week delay in the SIEs using SICs ≥60%. We start with WOY 46 to provide formation of consolidated ice. some overlap with the CIS data. The mean differences in SIE 3.2.3.2. PMW Data between the two periods for each WOY were statistically [49] Because of temporal limitations of the CIS data, significant (at the 95%–99% level) (Table 6). For example, in PMW data are used to document relative changes in SIE WOY 46 SIE is reduced from ∼14% (1.19 × 105 km2) to 0.8% beyond WOY 48. As PMW data tend to underestimate SICs (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 Table 4. Summary of Mean Sea Ice Concentration Differences week. In late December the relative differences in SIE be- Using Canadian Ice Service Data for 1980–1995 Versus 1996– tween the two periods become progressively smaller, as the 2005 Within the Areas Identified as Being Statistically Different sea ice is typically more consolidated late in the season. (90%–99% Level), Mean Sea Ice Extent in Hudson Bay for 1980– 3.2.4. Air Temperature Versus SIC Anomalies and SIE 2005, and Percent Area of HB That Has Undergone Significant [50] The results presented thus far have shown that the (90%–99% Probability) Change in SIC for Weeks of Year 43–48a SAT of the land surrounding HB within the time series SIE, %of Mean SIC SD 1980–2005 HB Area WOY Period (%) (%) (%) (DSIC) Table 5. Summary of Mean Differences in Sea Ice Extent Based on 43 1980–1995 44.9 4.77 Sea Ice Concentrations ≥80% for 1980–1995 Versus 1996–2005 – 1996 2005 7.54 5.25 Using Canadian Ice Service Data for Weeks of Year 45–48a Diff. (D) −37.36 0.57 0.41 44 1980–1995 42.29 12.03 SIE 1996–2005 5.66 7.1 (% of SD Area Diff. (D) −36.63 6.4 5.45 Data Week Year HB Area) (%) (km2) p 45 1980–1995 47.84 16.42 1996–2005 9.81 12.5 CIS 45 1980–1995 12.85 10.82 1.03 × 105 Diff. (D) −38.03 23.14 17.08 1995–2005 3.41 2.65 2.74 × 104 46 1980–1995 52.34 19.03 Diff. (D) −9.44 −7.59 × 104 0.013 1996–2005 17.4 17.25 46 1980–1995 26.62 20.14 2.14 × 105 Diff. (D) −34.94 46.18 25.4 1995–2005 12.92 12.42 1.04 × 105 47 1980–1995 51.07 18.51 Diff. (D) −13.69 −1.10 × 105 0.066 1996–2005 14.62 19.99 47 1980–1995 46.04 27.77 3.70 × 105 Diff. (D) −36.45 76.33 38.81 1995–2005 23.37 12.66 1.88 × 105 48 1980–1995 69.22 13.59 Diff. (D) −22.66 −1.82 × 105 0.02 1996–2005 30.74 17.79 48 1980–1995 67.15 25.72 5.40 × 105 Diff. (D) −38.48 92.17 38.7 1995–2005 45.88 21.04 3.69 × 105 Diff. (D) −21.27 −1.71 × 105 0.038 aSIC, sea ice concentration; SIE, sea ice extent; HB, Hudson Bay; WOY, weeks of year. Mean SIE for HB is based on SICs ≥20%. aSIE, sea ice extent; CIS, Canadian Ice Service; WOY, weeks of year.

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Table 6. Summary of Mean Differences in Sea Ice Extent Based anomalies computed from CIS data (WOY 45–48) and from on Sea Ice Concentrations ≥60% for 1980–1995 Versus 1996– the PMW on interannual air temperature anomalies. a 2005 Using Passive Microwave Data for Weeks of Year 46–52 [51] The relationships between SIC anomalies computed from CIS and PMW data versus SAT anomalies are sum- SIE (% of SD Area marized in Figure 12 and Table 7. Coefficients of determi- 2 WOY Year HB Area) (%) (km2) p nation (r ) range from 0.50 to 0.60 for CIS data and from 0.54 to 0.72 for PMW data, suggesting that interannual sea 46 1980–1995 14.74 16.66 1.19 × 105 1995–2005 0.77 0.96 6.20 × 103 ice anomalies are dependent on SAT anomalies. The data Diff. (D) −13.97 −1.12 × 105 0.015 show that, over WOY 45–48, a 1°C increase in SAT results 47 1980–1995 30.37 22.95 2.44 × 105 in a decrease in SICs by −14% on average using CIS data. 4 1995–2005 7.32 7.14 5.89 × 10 The trends in SIC anomalies are somewhat lower using the Diff. (D) −23.05 −1.85 × 105 0.005 48 1980–1995 51.91 23.75 4.17 × 105 PMW data (Table 7). In week 45 the relationship between 1995–2005 25.12 14.78 2.02 × 105 SIC anomalies and SAT anomalies is curvilinear, because it Diff. (D) −26.79 −2.15 × 105 0.004 is very early in the freezeup period so positive SIC anomalies 49 1980–1995 73.25 20.3 5.89 × 105 are favored; the same occurs in week 52, where negative – 5 1995 2005 43.28 22.69 3.48 × 10 anomalies are favored, as ice is typically consolidating at Diff. (D) −29.98 −2.41 × 105 0.002 – 5 this point. During WOY 46–51 all the relationships are linear; 50 1980 1995 87.77 15.43 7.06 × 10 2 1995–2005 66.14 25.31 5.32 × 105 the highest correlations occur during weeks 47–49 (r = Diff. (D) −21.63 −1.74 × 105 0.012 0.62–0.72; p < 0.0001), when SIC anomalies are more evenly 51 1980–1995 95.18 10.07 7.65 × 105 5 distributed (period of maximum interannual variation). SIC 1995–2005 79.93 19.1 6.43 × 10 – − Diff. (D) −15.25 −1.23 × 105 0.013 anomaly trends during WOY 47 49 range from 9.6% to 52 1980–1995 99.29 2.25 7.98 × 105 −12.6%. The correlation between air temperature anomalies 2 1995–2005 92.67 11.03 7.45 × 105 and SIC anomalies remains high (r = 0.60–0.72; p < Diff. (D) −6.61 −5.32 × 104 0.027 0.0001) during WOY 50–52, when slopes gradually decrease − − aHB, Hudson Bay; SIE, sea ice extent; WOY, weeks of year. 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 – (1980 2005) has warmed significantly since 1995, accom- periods of maximum interannual variation for each data set; panied by a significant reduction in SIC and, ultimately, regression coefficients are summarized in Table 8. For CIS SIE. Here we quantify the dependence of weekly SIC 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.

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Table 7. Regression Parameters for Sea Ice Concentration Anoma- Table 8. Regression Parameters for Sea Ice Extent Versus Surface lies Versus Air Temperature Anomalies for Canadian Ice Service Air Temperature Anomalies for Weeks of Maximum Variation in Data for WOY 45–48 and Passive Microwave Data for WOY SIEa 45–52a Data WOY Intercept Slope RMSE r2 P Source WOY Slope b b RMSE r2 p 1 2 CIS 47 37.320 −13.051 17.738 0.53 <0.0001 CIS 45 −14.7849 20.43 0.52 <0.0001 48 58.967 −14.505 15.870 0.64 <0.0001 46 −14.6069 21.00 0.50 <0.0001 PMW 48 41.604 −14.422 13.410 0.71 <0.0001 47 −13.9777 18.89 0.54 <0.0001 49 61.725 −12.038 15.076 0.67 <0.0001 48 −13.5203 16.14 0.60 <0.0001 aCIS, Canadian Ice Service; PMW, passive microwave; RMSE, root mean PMW 45 −9.0919 2.7213 11.31 0.67 <0.0001; 0.0166 square error; WOY, week of year; SIE, sea ice extent (% of Hudson Bay 46 −10.9469 14.53 0.54 <0.0001 area). 47 −12.2011 13.77 0.62 <0.0001 48 −12.6211 11.67 0.71 <0.0001 49 −9.6249 11.90 0.67 <0.0001 50 −8.0852 11.71 0.60 <0.0001 slopes ranging from a −13.1% to a −14.5% (or −1.05 × 105 to 51 −5.6422 7.78 0.62 <0.0001 −1.17 × 105 km2) decrease in areal extent per 1°C increase. 52 −3.2933 −0.9322 4.47 0.72 <0.0001; 0.0063 [53] For PMW data mean SIEs over 1980–2005 were aRMSE, root mean square error; CIS, Canadian Ice Service; WOY, week 41.6% (or 3.35 × 105 km2) for week 48 and 61.7% (4.96 × of year; PMW, passive microwave. Polynomial fits are italicized. See 105 km2) for week 49. The trends in SIE estimated from Figure 12. 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. imate the CIS extents. The areal extent of the ice is expressed 3.2.5. SAT and Ice Thickness as a percentage of the HB area. For the CIS data mean ice [54] Recent updates of thickness data from the CIS show extents over 1980–2005 were 37.3% (or 3.00 × 105 km2) for 5 2 that the ice thickness in Coral Harbour (the only reporting week 47 and 58.9% (or 4.58 × 10 km ) for week 48, with 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%).

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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 Figure 14. Mean change (D) in sea ice thickness (cm) and December but the coefficients of determination were very 2 SATs for Coral Harbour (1980–1989 versus 2002–2007) weak (r = 0.05–0.21). for (a) the month of November, which showed a mean change [59] To show more general tendencies in the indices in ice thickness D of −19.4 cm, corresponding to an average versus SAT, 5 year running means were applied to the data. 1.98°C increase in SAT; and (b) the month of December, Means comparisons were made at 7 year intervals to examine when the ice thickness has decreased by 40 cm, with an aver- the extent to which mean air temperature and index values age increase in SAT of 2.54°C. Snow thickness (not shown) varied over time (Figure 16). Three spline fits (l = 0.01 (no showed no significant differences being the two periods. 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 corresponding to a period of increased SAT anomalies. Data the longer‐term low‐frequency variations exhibited by each are shown for mid November and mid December (Figure 14). of the variables from 1951 to 2005. In November the mean difference in ice thickness between [60] The means over the 1999–2005 period (Figure 16), 1980–1989 and 2002–2007 was −19.4 cm (p = 0.0458), with few exceptions, were statistically different from those in while the mean difference in air temperature in Coral Harbour the two preceding intervals (1985–1991, 1992–1998). Also, during the same period was 1.98°C (p = 0.002). In mid all indices changed phase in the mid 1990s and showed trends December the mean ice thickness decreased from 72 to in index values that are typically associated with warmer fall 32 cm (−40.9 cm; p = 0.0012), while the mean SAT anomaly temperatures for the HB region. increased by 2.54°C (p = 0.0025). Changes in snow cover [61] In terms of air temperature, the 1999 to 2005 period is between the two periods were statistically insignificant for statistically warmer (mean SAT anomaly 0.83°) compared to both November and December. all preceding periods. The first two periods encompassing 1957–1970 are significantly warmer compared to 1992–98 3.3. SAT Anomalies Versus Teleconnection Indices (D = 0.36°C) and significantly cooler (D = −0.63°C) than the 1999–2005 anomalies. [55] For the fall period a number of indices were exam- ined to determine if any were predictive of fall temperatures [62] The temporal plot of the EP/NP index shows that it was positive from 1965–97 with occasional reversals and ice conditions in HB. These included the NAO, AO, – – – PDO, SOI, and EP/NP index. The geopotential height and (1970 71, 1983 85, 1991 92), and consistently negative from 1998–2005. Based on the means comparisons the temperature correlation maps for each index in its positive – phase are presented for the late summer‐early fall period for 1999 2005 period is statistically different relative to all the 1980–2005 time series (Figures 15a–15e) to provide a preceding periods. Table 10 summarizes the extent to which general spatial context prior to examining the HB region in the various indices exhibit covariance to the mean air tem- more detail. Each of the indices shown, with the exception peratures in HB computed for November, the period of of the SOI, shows that the HB area has a tendency toward maximum sea ice variability. The EP/NP index is shown to be highly predictive of SAT surrounding Hudson Bay cooler air surface temperatures when the indices are in their 2 positive phase. back to 1951 (r = 0.75) and from 1980 to 2005 period (r2 = 0.89).

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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 varia- tures in HB. During the 1999–2005 interval the mean NAO tion, it has largely remained positive from 1973 to 1996 index became strongly negative and is statistically different (Figure 16c), with a few reversals (1977, 1983–1984, 1988– from that in all preceding periods with the exception of 1989); a positive NAO is associated with cooler tempera- 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 Oct −0.54 <0.0001 −0.04 NS 0.11 0.010 −0.02 NS 0.07 0.048 1980–2005 −0.75 <0.0001 0.01 NS 0.08 NS −0.12 0.081 0.15 0.047 1951–2005 Nov −0.62 <0.0001 −0.15 0.004 0.01 NS −0.09 0.029 0.06 0.082 1980–2005 −0.79 <0.0001 −0.14 0.060 0.00 NS −0.21 0.020 0.07 NS 1951–2005 Dec NA −0.07 0.060 −0.00 NS −0.05 0.089 0.01 NS 1980–2005 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; p identifies 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 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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Table 10. Matrix of Coefficients of Determination (r2)for (1999–2005) is statistically different from the three preceding Climate Indices Versus Surface Air Temperature Based on the periods (over 1978–1998), which were in the positive phase 5 Year Running Mean for 1980–2005, 1950–2005, 1980–1995, of the cycle. The negative phase of this index is associated and 1995–2005a with warmer fall temperatures in HB. Over 1950–2005 the PDO index is not strongly correlated with SAT (r2 = 0.20), EP/NP NAO AO PDO SOI although slightly better than the AO. During the 1980–2005 1950–2005 (n=51) the PDO is more highly correlated (r2 = 0.70). NAO 0.24 [65] The SOI is quite variable and generally the most AO 0.12 0.31 PDO 0.17 0.08 0.28 poorly correlated index (interannually) with SAT anomalies SOI −0.05 −0.01 −0.02 −0.40 in HB (Table 10). Despite that, it is interesting to note that AT −0.75 −0.39 −0.14 −0.20 0.08 the very low‐frequency pattern (l = 1612.7) appears to be the inverse of the low‐frequency decadal pattern exhibited 1980–2005 (n=26) NAO 0.45 by the other indices, with a notable regime shift around AO 0.34 0.33 1976–1977 [Y. Zhang et al., 1997] (Figure 16f). Negative PDO 0.55P 0.33P 0.44P SOIs are loosely associated with cooler fall temperatures in SOI −0.22 −0.23 −0.34P −0.35 HB and extreme SIE events in HB when in phase with a −0.89 −0.65 −0.50 −0.70P AT 0.23 strong positive NAO [e.g., Wang et al., 1994]. “ ” 1980–1995 (n=16) [66] Table 10 also lists correlations within the cool and NAO 0.15 “warm” phases of the standardized atmospheric indices in AO 0.13 0.09 the 1980–2005 time series. The EP/NP index is the most PDO −0.02 −0.23 0.00 highly correlated within the 1980–1995 period (r2 = 0.74), SOI 0.00 −0.14 0.03 0.00 2 AT −0.74 −0.38 −0.36 0.06 0.00 followed by the NAO and AO indices, at r = 0.38 and 0.36, respectively, with the PDO and SOI not showing any sig- 1995–2005 (n = 11) nificance. Together, the EP/NP index with either the NAO NAO 0.54 or the AO explains ∼84% of the variance in SAT anomalies AO 0.52 0.43 in HB. During the warming phase all indices have changed PDO 0.74 0.29 0.56 −0.64 − −0.87 −0.77 phase, indicative of warmer fall temperatures for HB. All SOI 0.32 2 AT −0.97 −0.66 −0.55 −0.89P 0.78P indices are highly correlated (r = 0.50–0.97). [67] We suggest caution in implying causal relationships aAO, Arctic Oscillation; AT, air temperature; EP/NP, East Pacific/North Pacific oscillation index; NAO, North Atlantic Oscillation; PDO, Pacific to all of the various indices and the observed SAT anomaly Decadal Oscillation; SOI, Southern Oscillation. A dash indicates a trend. What can be stated is that, since 1995, the various negative correlation. P indicates a second‐order polynomial. Boldface indices have changed phase and that the EP/NP, NAO, and italic correlations are significant at 99% level, boldface correlations are AO indices appear to be those most consistently correlated significant at 95% level, italic correlations are significant at 90% level, with SAT anomalies over all periods, with the EP/NP index and regular text correlations are nonsignificant. 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 peratures. The NAO index is correlated with regional SAT using multiple regression. 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, 4. Conclusions and for 1980–2005 the EP/NP and NAO indices together explained 94% of the variation. [68] Based on the CANGRID data we have shown that SAT [64] The AO index values have been predominantly neg- anomaly trends were positive (warming) around HB from 1980 ative from 1955 to 1972 and positive from 1973 to 1996, with to 2005. The highest and most significant trends occurred in the one reversal from 1980 to 1985 (Figure 16d). From 1997 to northern and eastern portions of HB, with overall trends in 2005 the AO index has been positive. The low‐frequency SAT anomalies increasing from October (0.6–0.8°C/decade) trend shown by l = 1612.7 indicates that the AO has a long‐ to December (1.1–1.6°C/decade). Although statistically non- term periodicity (complete cycle not shown) overlain with significant, the regional mean interannual SAT anomalies shorter‐term fluctuations (≤15–20 years). The AO indices are show a slight cooling period over HB from 1950 to 1989, now trending to negative values favoring warmer tempera- most evident in November and December, followed by a tures in HB. The most recent period (1999–2005) has been statistically significant increase in SAT during the mid 1990s consistently negative and statistically different from the two to 2005. preceding periods, which are positive and associated with [69] Both CIS data and PMW data showed that SIC cooler November temperatures in HB. The AO index has a anomalies were decreasing throughout the fall (WOY 43–01), weak correlation with SAT from 1951 to 2005 (r2 = 0.14); the with the most significant (negative) trends in SIC anomalies correlation improves over the 1980–2005 period (r2 = 0.50). following the marginal ice zone. The statistically significant The EN/NP and AO together explained ∼90% of the variance trends in SIC anomalies using the CIS data showed negative in SAT anomalies based on a 5 year running mean. The PDO trends in SIC ranging from −23.3% to −26.9% per decade for index typically has a ≥20–30 year cycle. Through the 1980s weeks 43–48, resulting in significant reductions in SIE over and into the late 1990s the fall PDO was positive and is now the last 26 years. Statistically significant trends in SIC trending to a negative cycle (Figure 16e). The last period anomalies using the PMW data were lower but were more

18 of 20 C05009 HOCHHEIM AND BARBER: ATMOSPHERIC FORCING OF SEA ICE IN HB C05009 broadly distributed throughout HB, ranging from −14.3% to Gagnon, A. S., and W. A. Gough (2005), Trends in the dates of ice freeze‐up −16.8% per decade for weeks 46–50. and breakup over Hudson Bay, Canada. Arctic, 58(4), 370–382. Gagnon, A. S., and W. A. Gough (2006), East‐west asymmetry in ice thick- [70] Interannual SIE was closely related to variations in ness trends over Hudson Bay, Canada, Clim. Res., 32, 177–186, SAT evidenced by both CIS data and PMW data. The CIS doi:10.3354/cr032177. data showed that for every 1°C increase in the mean regional Galley, R. J., E. Key, D. G. Barber, B. J. Hwang, and J. K. Ehn (2008), ≥ Spatial and temporal variability of sea ice in the southern air temperature around HB, the area of SIC 80% (consol- – 5 5 2 and : 1980 2004, J. Geophys. Res., 113, C05S95, idated ice) deceased by 1.05 × 10 to 1.17 × 10 km for doi:10.1029/2007JC004553. weeks 47–48 (late November). Similar results were shown Gough, W. A., A. R. Cornwell, and L. J. S. Tsuji (2004), Trends in seasonal for changes in SIEs using PMW data based on a slightly sea ice duration in southwestern Hudson Bay, Arctic, 57(3), 299–305. ≥ Holland, M. M., C. M. Bitz, and B. Tremblay (2006), Future abrupt reduc- lower SIC threshold (SICs 60%). tions in the summer Arctic sea ice, Geophys. Res. Lett., 33, L23503, [71] Regional SAT anomalies around HB were shown to doi:10.1029/2006GL028024. be closely related to atmospheric indices. The EP/NP index Jevrejeva, S., J. C. Moore, and A. Grinsted (2003), Influence of the Arctic Oscillation and El Niño‐Southern Oscillation (ENSO) on ice conditions was predictive of SAT anomalies in HB dating back to 1950. in the : The wavelet approach, J. Geophys. Res., 108(D21), The NAO and AO were much less predictive; they typically 4677, doi:10.1029/2003JD003417. exert their strongest influence during the winter period. Five Johannessen, O. M., et al. (2004), Arctic climate change: Observed and year running means were also applied to the SAT and to the modeled temperature and sea‐ice variability, Tellus, 56A(4), 328–341. Kalnay, E., et al. (1996), The NCEP/NCAR Reanalysis 40‐Year Project, teleconnections data. These data showed that the EP/NP Bull. Am. Meteorol. Soc., 77, 437–471, doi:10.1175/1520-0477(1996) index together with the NAO and AO explained ∼80%–90% 077<0437:TNYRP>2.0.CO;2. of the variance with SAT anomalies in November from 1951 Kinnard, C., C. M. Zdanowicz, D. A. Fisher, B. Alt, and S. McCourt (2006), Climatic analysis of sea‐ice variability in the Canadian Arctic to 2005. The SOI index was consistently the most poorly – – 2 from operational charts, 1980 2004, Ann. Glaciol., 44,391 402, correlated with SATs (R = 0.08) on an interannual basis, doi:10.3189/172756406781811123. whereas the PDO was more predictive of SATs than the AO Laidler, G. J., J. D. Ford, W. A. Gough, T. Ikummaq, A. S. Gagnon, S. Kowal, index over 1951–2005. K. Qrunnut, and C. Irngaut (2009) Assessing vulnerability to sea ice change in Igloolik, Clim. Change, 94 363–97. [72] Examining the longer‐term trends in air temperature Lindsay, R. W., and J. Zhang (2005), The thinning of arctic sea ice, 1988–2003: and the hemispheric indices using a 5 year running mean, it Have we passed a tipping point? J. Clim., 18,4879–4894, doi:10.1175/ is apparent that the climate has been undergoing a regime JCLI3587.1. McKenney, D., P. Papadopol, K. Campbell, K. Lawrence, and M. Hutchinson shift in the last 15 years and that this shift in HB during the (2005), Spatial models of Canadian and North American‐wide 1971/2000 fall appears to be associated with the low‐frequency oscil- minimum and maximum temperature, total precipitation and derived bio- lation pattern inherent in the various indices, particularly the climatic variables, 1 p., Frontline Technical Note No. 107, Canadian Forestry Service, Sault Ste. Marie. EP/NP, NAO, and AO. The phase change in the mid 1990s Mysak, L. A., R. G. Ingram, J. Wang, and A. Van Der Baaren (1996), The coincides with warmer SATs in HB and associated negative anomalous sea‐ice extent in Hudson Bay, and the Labrador SIC anomalies and SIEs. We plan to extend this HB work Sea during three simultaneous NAO and ENSO episodes, Atmos. Ocean, by examining the winter‐to‐summer period for these same 34, 313–343. ‐ Overland, J. E., M. Wang, and S. Salo (2008), The recent Arctic warm period, relationships in a follow up paper. Tellus, 60A, 589–597. Parkinson, C. L., and D. J. Cavalieri (2008), Arctic sea ice variability and trends, 1979–2006, J. Geophys. Res., 113, C07003, doi:10.1029/ [73] Acknowledgments. This work was funded by the Natural 2007JC004558. Sciences and Engineering Research Council, Canada Research Chairs pro- Parkinson, C. L., D. J. Cavalieri, P. Gloersen, H. J. Zwally, and J. C. 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