Observations of sea ice thickness, surface roughness and ice motion in Amundsen Gulf

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1 Click Here for Full Article JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113,, doi: /2007jc004456, 2008 Observations of sea ice thickness, surface roughness and ice motion in Amundsen Gulf I. K. Peterson, 1 S. J. Prinsenberg, 1 and J. S. Holladay 2 Received 19 July 2007; revised 11 October 2007; accepted 26 February 2008; published 14 June [1] Ice thickness and surface roughness measurements of first-year (FY) sea ice were collected with a fix-mounted helicopter-borne electromagnetic (HEM) -laser system in Amundsen Gulf in April to May The modal ice thickness values are in good qualitative agreement with different ice types identified in synthetic aperture radar (SAR) imagery and shown on ice charts produced by the Canadian Ice Service. Modal ice thickness values which generally represent level ice thicknesses were about 2.0 m over landfast ice. A large range of modal ice thicknesses was observed in the mobile ice region, with values of about 0.2 m (young ice) in leads (where there was high radar backscatter), 0.6 m (thin FY ice) in the polynya (where there was medium to high backscatter), and about m (thick FY ice) elsewhere. High surface roughnesses are strongly associated with high radar backscatter in SAR imagery, and are observed in areas of large shear. The ratio of the standard deviations of ice draft and averaged roughness in an area of landfast ice is in good agreement with the ratio of the standard deviations of ice draft and ice-equivalent roughness expected from isostasy, with constant level ice and snow thickness. However, the standard deviation of ice-equivalent roughness may be significantly underestimated, due to differences in snow thickness between level and deformed ice, and limitations of the laser processing method. Modal ice (plus snow) thicknesses measured with the HEM system are within the range of historical values measured at Cape Parry. Citation: Peterson, I. K., S. J. Prinsenberg, and J. S. Holladay (2008), Observations of sea ice thickness, surface roughness and ice motion in Amundsen Gulf, J. Geophys. Res., 113,, doi: /2007jc Introduction [2] Measurements of sea ice thickness are important for assessing climate change, and as input and validation data sets for global climate models. Ice thickness is of particular interest in the Arctic, where a significant decline in ice draft since the 1960 s has been reported, based on measurements obtained with upward-looking sonar mounted on submarines [Rothrock et al., 1999]. [3] Ice draft measurements from submarine upwardlooking sonar have been used in combination with ice elevation data from airborne-laser profiling, for comparing probability density functions of ice draft and ice elevation, as well as ridge keels and sails [Wadhams, 1980]. More recently, statistics on ice draft and keels have been obtained from moored upward-looking sonar observations [Melling and Riedel, 1996]. Sonar ice draft data from both submarines [e.g., Comiso et al., 1991] and moorings [Melling, 1998] have been used for the interpretation of synthetic aperture radar (SAR) data and validation of radar signatures of sea ice. 1 Coastal Ocean Science, Bedford Institute of Oceanography, Fisheries and Oceans Canada, Dartmouth, Nova Scotia, Canada. 2 Geosensors Inc., Toronto, Ontario, Canada. Copyright 2008 by the American Geophysical Union /08/2007JC004456$09.00 [4] Since the 1980s, airborne measurements of ice-plussnow thickness have been collected using electromagnetic (EM) induction instruments towed beneath a helicopter [Kovacs et al., 1987; Rossiter and Holladay, 1994; Haas et al., 2006]. To address the operational difficulties associated with towed systems, an EM sensor which is fix-mounted on the front of the helicopter was developed for ice-thickness measurement and has been in use since 2001 [Prinsenberg et al., 2002]. Ice thickness data from helicopter-borne sensors have also been used for SAR validation [Prinsenberg et al., 1996]. [5] In the spring of 2004, a field study was conducted to collect measurements of ice-plus-snow thickness (hereafter referred to as ice thickness) using helicopter EM sensors in Amundsen Gulf and over the Mackenzie Shelf (Figure 1) as part of the Canadian Arctic Shelf Exchange Study (CASES). Amundsen Gulf represents one of two possible western endpoints of the Northwest Passage, which may be an increasingly important shipping route in the future due to climate change. The location of the edge of consolidated ice which forms each winter in the Gulf varies significantly from year to year. In the spring, a flaw polynya develops west of the consolidated ice due to predominant easterly and southeasterly winds [Canadian Ice Service, 2002; Carmack and Macdonald, 2002]. The mean annual ice flux from Amundsen Gulf into the Arctic Ocean is positive, with over 1of14

2 Figure 1. Portion of regional composite ice chart of the Western Arctic region for 15 May 2004 produced by the Canadian Ice Service, showing the Amundsen Gulf area. The large dot indicates the overwintering site of CCGS Amundsen. half the variance described by the cross-strait gradient in sea level pressure [Kwok, 2006]. [6] In this paper, sea ice thickness, roughness and ice motion data collected during the 2004 field study in Amundsen Gulf region are described. The data are compared qualitatively with Radarsat SAR (synthetic aperture radar) and Envisat ASAR (advanced SAR) satellite imagery since radar backscatter is a function of both ice type (or level ice thickness) and surface roughness. 2. Data Collection [7] During the 3-week field survey (20 April to 11 May 2004), sea ice thickness and surface roughness were measured with a fix-mounted helicopter-borne electromagnetic (FEM) system called the IcePic (Figure 2), which is built by Geosensors Inc. and consists of a cylindrical sensor package mounted to the front of a BO-105 Canadian Coast Guard helicopter [Prinsenberg et al., 2002]. An EM sensor (using transmitter frequencies of 1.7, 5.0, 11.7, and 35.1 khz) provides the distance from the sensor to the ice-water interface, a laser altimeter provides the distance to the surface of the snow or ice, and an attitude sensor provides pitch and roll measurements. Together, the sensors give the snow-plus-ice thickness using a 1-D inversion model [Rossiter and Holladay, 1994]. The laser altimeter data is also used to provide profiles of ice surface roughness, defined as the height of the ice (or snow) surface relative to the surrounding level ice (or snow) surface. The sampling rate for the ice thickness and roughness data is 10 Hz, corresponding to a sampling interval of 4 5 m. [8] The IcePic can be used either to obtain spot samples of level ice thickness by soft-landing on the ice, or to collect short ice-thickness profiles by flying at low altitude over the ice; the latter observation method was most often used during CASES. The footprint size is dependent on the height of the sensor above the seawater, the frequency, and the EM component [Reid et al., 2006]. The accuracy of snow-plusice thickness measurements from the IcePic is approximately ±0.1 m for level ice [Prinsenberg et al., 2002]. [9] The laser altimeter is manufactured by Optech Inc. and has a footprint size of several centimeters. Surface roughness profiles are extracted from the laser altimeter data using a three-step high-pass filtering procedure to remove variations in the helicopter altitude [Hibler, 1972; Dierking, 1995]. This processing is required when no differential GPS data are available for altitude correction. Ice roughness is defined here as the height of the ice (or snow) surface relative to the minimum surrounding level ice (or snow) surface. Ice elevation, which can be obtained Figure 2. The Ice Pic, a fix-mounted helicopter-borne electromagnetic (HEM) laser system for measuring sea ice thickness and ice surface roughness, is shown on the front of a BO105 CCG helicopter. A pod fixed to the helicopter skid-gear houses a video camera and a second laser altimeter. 2of14

3 Figure 3. Hourly vector wind (a), wind speed (b) and air temperature (c) at the CCGS Amundsen (70.05 N, W) in April May The dates on which survey flights were conducted are marked along the top of the lower panel, and the acquisition times of the SAR images in Figures 4, 6, and 8 are marked along the bottom of the lower panel. using differential GPS data, is defined as the height of the ice (or snow) surface relative to sea level. The cut-off frequency of the high-pass filter corresponds to a wavelength of 90 m, and the window size for locating minima is 22 m for a flying speed of 45 m/s. This window size was chosen as it is on the order of typical ridge widths and because the sampling interval is relatively long (4 5 m). [10] The survey data were collected from 20 April to 11 May using as a base the CCGS Amundsen which was frozen into landfast ice in Franklin Bay the previous winter. Information on ice drift during the spring ice breakup was obtained from satellite-tracked ice beacons, but for logistical reasons, they were not deployed until 8 May when a flight north to Banks Island was conducted. 3. Observations 3.1. Ice and Atmospheric Conditions [11] Ice conditions around the time of the field study are shown by the ice chart for 15 May produced by the Canadian Ice Service (Figure 1). Ice concentrations and ice types in various regions are described by the egg code. The first line of the egg code represents the total ice concentration in tenths, and the second line represents the partial concentrations of various ice types given in the third line (7., 4., 1., and 7 correspond to old ice, thick FY ice, medium FY ice and thin FY ice respectively). [12] Three ice regimes are visible in the Amundsen Gulf area. The first regime (area A) consists of consolidated or compact (10 tenths concentration) thick FY ice (>1.2 m thickness) in Franklin Bay and east of Cape Lambert. Much of this ice is landfast (consolidated) during the winter and spring period, although a few areas represent compact ice that is intermittently mobile. The second regime (area B) consists of very close (>9 tenths but less than 10 tenths concentration) thick FY ice north of Franklin Bay. The third regime (area C) represents a polynya consisting of very close thin FY ice ( m). It lies west of the landfast ice south of Cape Lambert and continues north as a shore polynya along the southwest coast of Banks Island. Ice throughout the second and third regimes is intermittently mobile. [13] Wind and air temperature data collected on the CCGS Amundsen in Franklin Bay are shown in Figure 3. There were two major wind events during the survey, with strong easterly winds on 28 April, and strong northwesterly winds on 4 May. Air temperatures in the early part of the survey (20 26 April) were generally about 20 C, rising to temperatures of up to 4 C in the latter part of the survey from 27 April to 10 May. The average snow thickness around the ship in April and May 2004 was about m. 3of14

4 Figure 4. Ice displacements between April and 7 May 2004 from RADARSAT SAR and ENVISAT ASAR data (circles at the start of the displacements). The limits of the compact ice (blue line), and the landfast ice (green line) are also shown. The red crosses indicate the locations of the ice beacon deployments on 8 March. # CSA/ASC Figure 5. Trajectories of satellite-tracked ice beacons from 8 May to 29 May of14

5 Figure 6a. Mosaic of ENVISAT ASAR APP images acquired on April 2004 (HH polarization) overlain with modal ice thickness values for April The green line indicates the limit of the landfast ice. # ESA Ice Motion [14] Ice displacements over the period of the field study were inferred from satellite imagery to aid in the comparison of data collected throughout the study area at different times. In Figure 4, ice displacements derived by tracking features manually in SAR images from April and 7 May are shown. The ice in Franklin Bay was immobile (i.e., landfast) south of 70.2 N. Ice drifted eastward as a wedge of compact ice east of the Cape Bathurst peninsula, northward in the polynya area, and westward north of 70.5 N. Comparison of many images between 20 April and 8 May indicated that ice motion was often negligible for periods of a day or more. The drift pattern in Figure 4 can be attributed to the two strong wind events on 28 April and 4 May respectively (Figure 3). Strong easterly winds on 28 April account for the westward drift north of 70.5 N. Such winds would have a limited effect on the drift of ice east of the Cape Bathurst peninsula because of opposing ice pressure due to the coastline. On the other hand, strong northwesterly winds on 4 May account for the eastward drift of ice east of the Cape Bathurst peninsula, and for the narrowing of the polynya in the ice charts between 1 May and 15 May. [15] The intermittent nature of ice motion is shown using five satellite-tracked ice beacons deployed in the close pack ice region on 8 May (after the period of the ice drift pattern in Figure 4), to monitor the spring breakup. As indicated by the drift tracks (Figure 5), ice motion was negligible until 23 May (day 144) when the beacons drifted north to northwest due to the strong southerly winds (Figure 3). Over the following week, the beacons continued to drift northwest, in agreement with the enlargement of the polynya in the 1 June ice chart. The lack of motion over a period of 155 d indicates that the internal ice stress was sufficient to balance the wind stress throughout this period, 5of14

6 Figure 6b. Radarsat SAR image acquired on 07 May 2004 overlain with modal ice thickness values for May The green and blue lines indicate the limits of the landfast ice and compact ice respectively. # CSA and that ice motion under similar ice conditions is expected to occur only during strong wind events. [16] Thus based on the ice motion and wind information, the ice thickness data were divided into two periods: before 27 April and after 5 May. Since the only data collected between the two periods were collected over landfast ice on 29 April, they were combined with the early period Modal and Mean Ice Thickness [17] The mode of ice thickness along the profiles was computed using a window size of 299 points (or about 1.4 km), and generally represents the predominant level ice thickness since relatively narrow leads and ridges are filtered out. The modal ice thicknesses for the late April and early May surveys are overlain on SAR imagery shown in Figures 6a and 6b respectively. The overall modes for the landfast (area A1) and mobile ice areas are listed in Table 1, with the histograms shown in Figure 7. For May, the mobile ice region is sub-divided into compact ice (area A2), veryclose ice (area B) and the polynya (area C), as shown in the 1 May and 15 May ice charts. [18] In the landfast area (area A1), the modal ice thicknesses are generally about 2m, with higher values where high radar backscatter is present (Figures 6a and 6b). The overall modes and means of ice thickness in the landfast area for April and May are in good agreement (Table 1), and the mode and mean for the combined data are 1.97 m and 2.30 m respectively. Thus assuming the modal ice thickness represents the level ice thickness, the mean thickness is 17% greater than the level ice thickness because of the presence of deformed ice. [19] In the SAR images (Figures 6a and 6b), the landfast area (area A1) appears to be composed of brighter-toned floes with darker-toned FY ice in between, which presumably formed at a later date. The modal ice thickness in different dark-toned areas varies considerably from about 1.6 m to 2.1 m, and probably reflects different histories of freezeup 6of14

7 Table 1. Mode and Mean of Ice Thickness, and Mean Roughness for Landfast Ice (Area A1), Mobile Compact Ice (Area A2), Mobile Very-Close Ice (Area B) and the Polynya (Area C) Based on Data Collected April and 6 10 May Region Month Mode (Ice Thickness, m) Mean (Ice Thickness, m) Mean (Roughness, m) Number of Points A1 (landfast, thick FY) Apr ,000 A1 (landfast, thick FY) May ,000 A1 (Landfast, thick FY) Apr May ,000 A2, B (mobile, thick FY) Apr ,000 A2 (mobile, compact) May ,500 B (mobile, VClose <70.7 N) May ,000 B mobile VClose >70.7 N May ,000 C Polynya (thin FY) May ,700 and snow cover. The relatively high thicknesses in the darktoned areas (>1.5 m) are consistent with the ice charts which show consolidated ice in the area between 1 January 2004 and the time of the survey. The dark tone of these areas probably indicates that the ice formed under calm sea conditions, whereas the brighter tone of older ice may be due to the ice forming under turbulent conditions or to increased deformation. [20] In the mobile ice area (areas A2, B, and C), modal ice thicknesses range from about 0.1 m in leads to over 2.5 m in areas of very deformed ice (Figures 6a and 6b). The leads appear bright in the SAR imagery because of the presence of frost flowers rather than because of wind roughening of open leads, as confirmed by visual observations. In general, lower modal ice thicknesses are observed in the northern Gulf near Banks Island than in the south (Figure 6b). This is consistent with prevailing northerly winds during the winter months [Canadian Ice Service, 2002], which would tend to cause ice divergence in the northern Gulf, and therefore younger and less deformed ice. Modal ice thicknesses of less than 1m are observed in the polynya area (area C), corresponding to a bright-toned region in the SAR imagery (Figure 6b). Relatively low ice thicknesses of about 1.3 m are also observed in both the April and May surveys at about 70.6 N, W, where drift was minimal in this area over the period of the surveys Figure 7. Histograms of ice thickness for the (a) April May landfast ice (area A1), (b) April mobile ice (area A2, B), (c) May mobile compact ice (area A2), (d) May mobile very-close ice south of 70.7 N (area B), (e) May mobile very-close ice north of 70.7 N (area B), and (f) May thin first-year ice in Polynya (area C). 7of14

8 Figure 8a. Mosaic of ENVISAT ASAR APP images acquired on April 2004 (HH polarization) overlain with mean surface roughness values over 1.4 km for April # ESA (Figure 4). Modal ice thicknesses of over 2.5 m were observed in several areas representing highly deformed ice, and correspond to high radar backscatter in the SAR imagery. In the April data, deformed ice areas can be seen near Cape Bathurst and along the edge of the landfast ice, where high shear is expected. [21] The overall mode and mean of ice thickness for the mobile area (areas A2, B) in April (1.9 m and 2.3 m respectively) and the mobile compact ice area (area A2) in May (2.0 m and 2.4 m) are very similar to those for the landfast ice area (area A1) (2.0 m and 2.3 m) (Table 1, and Figure 7). To the north in the very-close area for May (area B), the mode and mean decrease to 1.8 m and 1.7 m respectively south of 70.7 N and to 1.6 m and 1.5 m respectively north of 70.7 N. A secondary mode of m can be seen in the histograms for both the April mobile ice (area A2, B) and May mobile very-close ice areas (area B) (Figures 7b and 7d), representing the greencolored areas in Figures 6a and 6b. Small modes of m in April, and 0.5 m and m in May are also present for very-close ice (area B), and generally represent the leads. The mode and mean of ice thickness in the polynya (area C) are m and 1.0 m respectively. In comparison, the expected ice growth is 0.55 m, based on a freezing-degree model [Anderson, 1961] and air temperatures measured on the CCGS Amundsen from 5 April to 8of14

9 Figure 8b. Radarsat SAR image acquired on 7 May 2004 overlain with mean surface roughness values over 1.4 km for 6 10 May # CSA May. Level ice-plus-snow thicknesses may be slightly greater on 6 May due to snow cover, to the ice forming from a wind-swept frazil layer of non-zero thickness, or to differences in air temperature between the polynya and the ship Surface Roughness [22] The mean of surface roughness along the profiles was computed using the same window size of 299 points (Figures 8a and 8b). Lowest surface roughnesses are found in the bright-toned leads. For the April survey, high roughness is observed in the same areas where high modal ice thicknesses were observed (near Cape Bathurst, near the edge of the landfast ice, and within the landfast area corresponding to high radar backscatter). In these areas, the modal ice thickness is likely higher than the level ice thickness because of the high degree of deformation, combined with the EM footprint. Low surface roughness is present in areas with low radar backscatter within the landfast region. For the May survey, high roughness can be seen along several flight lines at 70.5 N, where a line of high backscatter can be seen in the SAR image. High roughness is also present along this line in the April data. In general, lower surface roughnesses are found in the north and east near Banks Island and the polynya than in the south. 9 of 14

10 Figure 9. Example of a profile of surface roughness (upper line) and ice draft (lower line) for landfast ice on 21 April 2004 (Flight 4055). [23] The overall mean roughnesses for the different ice regimes (Table 1) show a similar pattern to the mean ice thicknesses, with roughness values of m in the landfast and compact ice areas (areas A1 and A2), 0.08 m in the very-close ice to the north (area B) and 0.07 m in the polynya (area C). In comparison, the mean ice thicknesses in the three areas were m, m, and 1.0 m respectively Deformed Ice Thickness [24] Surface roughness and ice thickness are expected to be closely related because of isostasy. However, although the accuracy of the ice thickness measurements is about 0.1m over level ice, ice thickness may be underestimated over deformed ice because of pockets of seawater within the ridge keels. Since the inversion procedure solves for ice conductivity in addition to ice thickness, error of this type should be lower than if ice conductivity was neglected, or assumed to have a value typical of level ice. Other sources of error are 2-D or 3-D effects not accounted for in the inversion model. As a rough test of the accuracy of deformed ice thickness, ice thickness and surface roughness are compared to examine how well they conform to isostasy. [25] The ice thickness measurements depend in part on the laser measurements, which are also used to derive surface roughness. To minimize this dependence, the roughnesses are subtracted from the thickness to give the draft relative to the level ice (or snow) surface. A plot of surface roughness and ice draft for one of the three flight lines (Figure 9), clearly shows the correlation between ice roughness and draft. [26] Based on isostasy, for ice draft (H d ), and ice elevation (H e ), (both relative to sea level), where R ¼ r w r i H d ¼ RH ð e R 0 H s Þ ð1þ r i and R 0 ¼ 1 r s r i ; and r i is ice density, r w is surface seawater density and r s is snow density. For typical sea ice densities of Mg m 3 and a seawater density of Mg m 3, R is , and for a snow density of 0.3 Mg m 3, R 0 = [27] For elevation and draft relative to the level ice surface, H 0 d ¼ H d þ H r H 0 e ¼ H e H r where H e 0 is the ice roughness, and the reference elevation H r is the freeboard of level ice. [28] Thus from equations (1) (3), the ice draft relative to the level ice surface is ð2þ ð3þ Hd 0 ¼ RH0 e R0 H s þ ðr þ 1ÞHr ð4þ and for constant level ice freeboard and snow thickness, the ice draft is a linear function of the roughness. [29] Since the footprint of the ice draft measurements is much larger than that of the roughness measurements, the roughness measurements were averaged spatially. The footprint size was estimated from two short ice thickness profiles consisting of 2-m-thick level ice on either side of a narrow lead. One of the profiles is plotted in Figure 10. The flight path was perpendicular to the direction of the lead and the sensor height above seawater was 6.5 and 6.7 m respectively for the two profiles. The ice thickness profiles were compared to a step function averaged over various window lengths. For both profiles, the maximum correlation corresponded to an averaging length of 2.4 times the mean height above seawater (Figure 10). In comparison, the theoretical quadrature footprints for the four EM frequencies and a sensor height of 6.5 m are 4.6, 3.4, 2.8, and 2.5 times the height above seawater, based on Reid et al. [2006]. Thus the observed footprint size is similar to the theoretical footprint size for the highest frequency. [30] During sampling in general, linear features such as ridges and leads are oriented at various directions relative to the flight path, so that the effective footprint size is greater 10 of 14

11 Figure 10. Ice thickness data collected from east side of lead on 21 April 2004 (Flight 4055), which was used to compute footprint size (represented by horizontal line). than that for a perpendicular orientation. Assuming for simplicity the width of a ridge is negligible compared to the length, then the probability of flying over it is proportional to the cosine of the angle of the ridge relative to the across-track direction. Thus the probability function of the angle is given by f(q) =a cosq, 0 q p/2, and since R p=2 0 f(q)dq = 1, a = 1. Thus the expected angle is R p=2 0 q cosq dq = (p 2)/2, or This implies an effective footprint size of 2.9 times the mean height above seawater. [31] Surface roughness and ice draft were compared for three lines near the edge of the landfast ice, where the level ice is relatively constant and there is high variability in surface roughness and draft (Table 2). The flying height is about 6 m, and the mean ice thickness of deformed ice (which is taken to be ice greater than 2.1 m) is 3.0 m. Thus the expected footprint size is 26 m (2.9 times the height above seawater, 9 m). In Table 2, the roughness data were averaged over lengths of 14 m to 51 m to examine the sensitivity of the results to averaging length. For averaging lengths of 14, 23, 32, 41, and 51 m, the roughness data were averaged over 3, 5, 7, 9, and 11 points with equal weights, and for the averaging length of 28 m, the data were averaged over 7 points with half weights for the first and last point. [32] For the three lines combined, the ratio of the standard deviation of ice draft to the standard deviation of roughness is 7.3 for an averaging length of 23 m, and is 7.8 for an averaging length of 28 m. Thus the ratio for the derived footprint size of 26 m is about 7.6, using either linear interpolation or a quadratic fit to all the data. Since the ratio expected due to isostasy is 7.9 to 8.3, this suggests that any negative bias in the mean draft of deformed ice, and therefore in the ice thickness, is less than 10%. The ratio of 7.6 is similar to the ratio of 7.9 reported by Comiso et al. [1991], which was derived from scaling the probability density functions of upward-looking sonar and laser data in the Arctic Ocean. [33] Table 2 also shows the correlation coefficients for the various averaging lengths, and it can be seen that the maximum correlation (r = 0.67) is for an averaging length of 41 m, with slightly lower correlations for averaging lengths close to the observed footprint size, 26 m (r = 0.63 for a length of 23 m, and r = 0.65 for a length of 28 m). It might be expected that the maximum correlation would correspond to the footprint size. The discrepancy is probably due to the variability of the laser data, such that the error of the roughness estimate over level floes will decrease as the number of points increases. Table 2. Standard Deviations and Correlation Coefficients (r) for Ice Draft and Roughness Data Collected Along Three Lines Near the Edge of the Landfast Ice a Line Averaging Window Length, m Std (Ice Draft), m Std (Roughness), m Std (Draft)/ Std(Roughness) r Mean Sampling Interval, m Number of Points , , ,800 All ,300 All ,300 All ,300 All ,300 All ,300 All ,300 a The mean sampling interval of the ice draft and roughness data is also shown. All correlations are significant at the 95% level. 11 of 14

12 Figure 11. Probability density function of surface roughness (dotted line), surface roughness averaged over 28 m (squares), and ice draft (line with dots). The ice draft axis has been transformed as (Draft-1.2)/7.8. [34] The ratio of the standard deviations (or square root of the variance ratio) as shown in Table 2 represents the slope of a neutral regression, which has been used in cases when it is unclear which measurement contains more noise [Garrett and Petrie, 1981]. Thus if the relationship between draft (H d 0 ) and roughness (H e 0 ) is expressed as H 0 d ¼ a þ bh0 e ð5þ where a = H 0 d bh 0 e and b = std(h d 0 )/std(h e 0 ), then a = 1.24 m and b = 7.8, using draft and roughness data from all three lines with an averaging length of 28 m. From equation (4), the value of the intercept (a) in equation (5) is expected to vary in different areas depending on the level ice thickness and snow thickness. It is smaller than the modal ice thickness, likely because the apparent roughness for level ice has a value greater than zero that depends on laser measurement error and on variations in snow thickness on scales less than the window size for the laser processing. Thus when subtracted from the ice thickness, the resulting ice draft will be lower than the modal ice thickness. Together, the positive roughness and decreased draft will tend to shift the regression line to the right, or lower the intercept. [35] Figure 11 shows the probability density functions (pdf) of surface roughness (before and after averaging) and ice draft, where the ice draft has been transformed according to the neutral regression line. The scales for ice roughness and ice draft are shown along the bottom and top axes respectively. The probability density functions for surface roughness follows a negative exponential distribution. The slope of the pdf for roughnesses less than about 0.3 m is more negative than for higher roughnesses, and may represent the effect of snow drifts. The pdf for ice draft is highest from m, corresponding to level ice. Thicker ice drafts, which correspond to deformed ice, also follow a negative exponential function, in agreement with many other studies [e.g., Comiso et al., 1991]. The range of draft is smaller however than in studies involving upward-looking sonar measurements largely because of the increased footprint size. The range of roughness is smaller than the range of elevation in the Comiso et al. [1991] study north of Greenland, likely because of greater ice pressure and the presence of thicker multiyear ice in the latter area. 0 [36] Since ice thickness, H t = H d + H 0 e, then from 0 equation (5), H t =a+(b+1)h e = 1.24 m H 0 e. Using this equation, for an ice thickness equal to the modal ice thickness for landfast ice in Table 1 (1.97 m), the roughness is m, which can be considered the background roughness over level ice due to factors such as snow drifts and measurement error. Using the overall mean surface roughness value for landfast ice of m, the mean ice thickness value should be 2.32 m, very close to the value observed, 2.30 m Landfast Ice Thickness [37] The modal ice (plus snow) thickness for the landfast ice (area A1), 1.97 m, is shown along with historical drillhole measurements of ice-plus-snow thickness at Cape Parry for the years 1960 to 1992, which represent the annual mean values collected by the Canadian Ice Service from 20 April to 28 May (Figure 12). The thicknesses are plotted as a function of mean winter (November April) air temperature at Inuvik and Cambridge Bay. The value measured in 2004 is well within the range of historical drillhole measurements. It can also be seen that the year of 12 of 14

13 Figure 12. Scatterplot of annual mean ice-plus-snow thickness (15 April to 28 May) measured at Cape Parry from (Canadian Ice Service) against annual mean air temperature at Inuvik and Cambridge Bay (November to April). The dot represents the modal ice thickness for landfast ice (Table 1) measured with the FEM system in the field study (2004) was normal in terms of winter-spring air temperature, which is closely related to the freezing degree-days. The historical ice-plus-snow data are negatively correlated (r = 0.58, p < 0.05) with air temperature (Figure 12). Although the 2004 modal landfast ice thickness value is close to the regression line, clearly there are large uncertainties in assuming this value to be representative of ice thickness at the Cape Parry site. 4. Discussion and Conclusions [38] Because of the relatively good agreement with isostasy assuming constant level ice thickness and snow thickness, and using a reasonable value for the footprint to average the laser data, the EM system does not appear to seriously underestimate deformed ice thicknesses averaged over the EM footprint. However, it is likely that the snow thickness over deformed ice is less than that over level ice. On the basis of snow thicknesses near the ship, the snow thickness was set to 0.18 m over level ice (defined as ice with draft less than 2.1 m) and to zero over deformed ice. This increased the standard deviation of the ice-equivalent 0 roughness, (H e R 0 H s ), in equation (4) by 20%, for an averaging length of 28 m. However, it is also possible that the snow thickness over deformed ice is greater than zero, particularly if the deformation occurred early in the winter, and if snow was trapped in the hollows of the deformed ice surface. [39] Since it is also likely that the roughness over level ice is due to snow while the roughness over deformed ice is due to ice, the snow thickness was then set to the roughness over level ice, and to zero over deformed ice. This had a much smaller effect on the standard deviation of the ice-equivalent roughness (6%), although not surprisingly, the correlation coefficient increased from 0.65 to [40] In addition, the roughness of deformed ice (relative to the level ice (or snow) surface) may be underestimated as a result of the high-pass filtering procedure used to remove variations in helicopter altitude. In large areas of deformed ice, the elevation at the locations of minimum roughness may be significantly higher than the elevation of level ice. [41] There is also some uncertainty regarding the correction to the footprint size due to flight path orientation. However. However, even without this correction, the footprint size is 22 m (2.4 times 9 m), which implies that the ratio of the standard deviation of ice draft to the standard deviation of roughness is 7.2 (Table 2) and is still within 13% of the expected value based on isostasy assuming constant level ice thickness and snow thickness. [42] In conclusion, ice thickness measurements were collected in this field study with a fix-mounted HEM system for the first time in the Arctic. This system is less cumbersome to use and provides a smaller EM footprint than conventional towed HEM systems. The synoptic measurements covering large areas provide a powerful complement to satellite data for Arctic climate studies, as well as for operational purposes, and for validating algorithms based on satellite data. [43] Other results obtained from measurements in Amundsen Gulf in April May 2004 are as follows. [44] (1) Modal ice thickness values which generally represent level ice thicknesses were about 2.0 m over landfast ice. Modal ice thicknesses of 1.2 and m were observed in the mobile ice region south of 70.7 N, 0.5 and 1.6 m north of 70.7 N, m in the polynya, and m in the leads. Lower modal ice thicknesses are 13 of 14

14 observed north of 70.7 N than to the south, perhaps because the ice in the north can drift freely during periods of easterly winds, while to the south the ice is blocked by the Cape Bathurst peninsula. This would result in a higher proportion of younger, thinner level ice and less deformed ice in the north than to the south. [45] (2) The modal ice thickness values which generally represent level ice thicknesses are in good agreement with the corresponding ice chart produced by the Canadian Ice Service, which is based primarily on SAR imagery. In particular, the ice chart shows thin first-year ice ( m) in the polynya, and thick first-year ice (>1.2 m) elsewhere in the region. However, the EM data provide more detailed information on the thickness distribution within the thick first-year ice category (>1.2 m) shown on the ice charts. [46] (3) High surface roughnesses are strongly associated with high radar backscatter in SAR imagery, and are observed in areas of large shear such as near Cape Bathurst and along the edge of the landfast ice region. They are also observed in a broad area within the landfast region. [47] (4) The footprint of the ice thickness measurements appears to be about 2.4 times the mean height above seawater, based on limited data. The ratio of the standard deviations of ice draft and averaged roughness in an area of landfast ice is in good agreement with the ratio of the standard deviations of ice draft and ice-equivalent roughness expected from isostasy, with constant level ice and snow thickness. However, the standard deviation of ice-equivalent roughness may be significantly underestimated, due to differences in snow thickness between level and deformed ice, and limitations of the laser processing method. [48] (5) Modal ice (plus snow) thicknesses measured with the HEM system are within the range of historical values measured at Cape Parry. [49] (6) Observations from satellite-tracked ice beacons and SAR imagery show that before ice breakup, ice motion is intermittent and limited to relatively short periods of high winds, separated by periods of as much as 2 weeks or longer when motion is negligible. Ice displacements during the ice thickness survey could be explained by an easterly wind event causing strong shear at Cape Bathurst, followed by a northwesterly wind event causing a net southeastward displacement east of the Cape Bathurst peninsula. In areas with little ice displacement, modal ice thicknesses before and after the strong wind events were similar. [50] Acknowledgments. The authors thank the personnel of the CCGS Amundsen for their help and patience during the helicopter survey and in particular Captain Bernard Tremblay, helicopter engineer Bertrand Murray and helicopter pilot Yvon Coté. They all contributed to make the work more enjoyable and efficient. The work was supported by CASES (L. Fortier and D. Barber), through the Can. Space Agency-GRIP program, the Panel of Energy and Research Development and through Geo. Service Canada Atlantic Region (G. Mason) and Devon Oil Canada (D. Scott and B. Wright). We thank Tim Papakyriakou for providing the temperature and wind data from CCGS Amundsen, and the anonymous reviewers for their constructive comments. Radarsat data were provided by the Canadian Ice Service and ENVISAT ASAR data were provided by the European Space Agency under AO Project 178. References Anderson, D. L. (1961), Growth of sea ice, J. Glaciol., 3, Canadian Ice Service (2002), Sea Ice Climatic Atlas, Northern Canadian Waters, , vii+194 pp., Environment Canada, Ottawa, Ont. Carmack, E. C., and R. W. Macdonald (2002), Oceanography of the Canadian shelf of the Beaufort Sea: A setting for marine life, Arctic, 56(1), Comiso, J. C., P. Wadhams, W. Krabill, R. Swift, J. Crawford, and W. Tucker (1991), Top/bottom multisensor remote sensing of Arctic sea ice, J. Geophys. Res., 96(C2), Dierking, W. (1995), Laser profiling of the ice surface topography during the Winter Weddell Gyre Study 1992, J. Geophys. Res., 100(C3), Garrett, C. J. R., and B. Petrie (1981), Dynamical aspects of the flow through the Strait of Belle Isle, J. Phys. Oceanogr., 11, Haas, C., S. Hendricks, and M. Doble (2006), Comparison of the sea ice thickness distribution in the Lincoln Sea and adjacent Arctic Ocean in 2004 and 2005, Ann. Glaciol., 44, Hibler, W. D. (1972), Removal of aircraft altitude variation from laser profiles of the Arctic pack, J. Geophys. Res., 77(36), Kovacs, A., N. C. Valleau, and J. S. Holladay (1987), Airborne electromagnetic sounding of sea ice thickness and sub-ice bathymetry, Cold Reg. Scie. Technol., 14, Kwok, R. (2006), Exchange of sea ice between the Arctic Ocean and the Canadian Arctic Archipelago, Geophys. Res. Lett., 33, L16501, doi: /2006gl Melling, H. (1998), Detection of features in first-year pack ice by synthetic aperture radar (SAR), Int. J. Remote Sens., 19(6), Melling, H., and D. A. Riedel (1996), Development of seasonal pack ice in the Beaufort Sea during the winter of : A view from below, J. Geophys. Res., 101(C5), 11,975 11,991. Prinsenberg, S. J., I. K. Peterson, and S. Holladay (1996), Comparison of airborne Electromagnetic ice thickness data with NOAA/AVHRR and ERS-1/SAR images, Atmos. Ocean, 34(1), Prinsenberg, S. J., J. S. Holladay, and J. Lee (2002), Measuring ice thickness with EISFlow TM, a fixed-mounted helicopter electromagnetic-laser system, in Proc. 12th (2002) Int. Offshore Polar Engineering Conf., edited by J. S. Chung et al., vol. 1, pp , International Society of Offshore and Polar Engineers, Kitakyushu, Japan, May. Reid, J. E., A. Pfaffling, and J. Vrbancich (2006), Airborne electromagnetic footprints in 1D earths, Geophysics, 71(2), G63 G72. Rossiter, J. R., and J. S. Holladay (1994), Ice-thickness measurement, in Remote Sensing of Sea Ice and Icebergs, edited by S. Haykin et al., pp , John Wiley, Hoboken, N. J. Rothrock, D. A., Y. Yu, and G. A. Maykut (1999), Thinning of the arctic sea-ice cover, Geophys. Res. Lett., 26(23), Wadhams, P. (1980), A comparison of sonar and laser profiles along corresponding tracks in the Arctic Ocean, in Sea Ice Processes and Models, edited by R. S. Pritchard, pp , Univ. of Washington Press, Seattle, Wash. J. S. Holladay, Geosensors Inc., 66 Mann Ave., Toronto, ON M4S 2Y3, Canada. I. K. Peterson and S. J. Prinsenberg, Coastal Ocean Science, Bedford Institute of Oceanography, Fisheries and Oceans Canada, P.O. Box 1006, 1 Challenger Drive, Dartmouth, NS, Canada B2Y 4A2. (petersoni@mar. dfo-mpo.gc.ca) 14 of 14