Analysis of Sea Ice Leads in Baffin Island Sea Using Spaced Based Infrared Remote Sensing Data and Mathematical Hydrological Models

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1 International Journal of Geosciences Research ISSN Vol. 1 No. 1, pp (2013) Analysis of Sea Ice Leads in Baffin Island Sea Using Spaced Based Infrared Remote Sensing Data and Mathematical Hydrological Models Nasser Najibi 1*, Abbas Abedini 2 and Hossein Najibi 3 1 Shanghai Astronomical Observatory, University of Chinese Academy of Sciences, Shanghai, China 2 Institute of Geodesy, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Stuttgart, Germany 3 School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran Abstract In glaciology the sea ice has been explained as a frozen shape of ocean surface water which normally forms, grows, and melts strictly in the ocean so that up to 15 percent of the world's oceans are covered by sea ice while the glaciers, ice sheets, and ice shelves form on the land. In this study the variations of sea ice surface temperature of Baffin Island Sea have been measured with space based radar remote sensing during the Arctic Lead Experiment (LeadEx) to identify the springtime of the ice leads. In order to apply a threshold surface temperature for the lead ice of -20 to -30 C the hydrological mathematical models and the surface temperature fluctuations between warm and thin lead ice as well as cool and older sea ice as a lead signature have been analyzed. Furthermore the proposed ice thickness model shows the 4 to - 2 C temperature s threshold corresponding to an ice thickness of about 0.5 to 3.5 m related to 789 sea ice leads. Finally a basic heat flux model with its trend is applied to surface temperature values in order to estimate lead ice thickness and sea ice values based on the surface temperature. Keywords: Ice thickness, Sea ice leads, Surface temperature, Hydrological models, Remote sensing data 1. Introduction While sea ice occurs mostly in the Polar Regions, it also influences the global climate. Since sea ice has a bright surface and much of the sunlight is reflected back into space (NSIDC report, 2011). As a result, the areas covered by sea ice don t absorb much solar energy, and therefore the air temperature in the Polar Regions remains relatively cool (Maksym and Markus, 2008). If gradually warming temperatures melt sea ice over time, the fewer portion of bright surfaces are available to reflect sunlight back into space, and more solar energy is absorbed at the surface, and finally the temperature rises further (Eicken, 1992). This chain of events starts a cycle of warming and melting. This cycle is temporarily halted when the dark days of the polar winter return, but it starts again in the following spring. Even a small increase in temperature can lead to greater * Corresponding author: nsr.najibi@gmail.com

2 2 N. Najibi, A. Abedini and H. Najibi 2013 Analysis of Sea Ice Leads warming over time, making the Polar Regions with the most sensitive areas to bring, climatically, major changes on Earth (Vancoppenolle et al, 2007). In addition to this, sea ice also affects the normal movement of ocean waters called basic ocean currents. When sea ice forms, most of the salt is pushed into the ocean water below the ice, although some salt may become trapped in small pockets between ice crystals; meanwhile the water below sea ice has a higher concentration of salt and is denser than surrounding ocean water, and so eventually it sinks. The cold, dense and polar water sinks and moves along the ocean bottom towards the equator, while warm water from mid-depth to the surface travels from the equator towards the poles (Tang et al, 2007). The changes in the amount of sea ice can disrupt normal ocean circulation, thereby leading to changes in the global climate. Furthermore too much or too little sea ice can be a problem for wildlife and people who hunt and travel in Polar Regions. In the Arctic, sea ice can be assumed an obstacle to normal shipping routes through the Northern Sea route and Northwest Passage. Because ice is expelled from sea ice as it freezes and develops, brine rejection from lead ice is greater than from thick ice (Perovich and Richter- Menge, 2000). Leads are also influential in the mechanical behavior of the ice pack (Gow et al., 1990). The leads have lower albedo than the older sea ice that surrounds them and so affect the absorption of shortwave solar radiation. While Pegau and Paulson (2001) observed an albedo of in open summertime leads, Perovich (1998) states the albedo of bare (snow-free) ice as 0.7, and Pinto et al. (2003) observed an albedo of 0.85 for snowcovered ice. Generally, a lead will absorb a greater fraction of incoming shortwave solar radiation when it first opens, before the formation of ice on its surface; as ice grows on a lead and snow covers its surface, a greater fraction of solar radiation is reflected. Recent studies have assessed the distribution and density of Arctic leads. Lindsay and Rothrock (1995) used advanced, very high resolution radiometer (AVHRR) images taken from a polarorbiting satellite in 1989 to assess lead characteristics with 270 cells, each 200 km square, across the central Arctic and peripheral seas. The AVHRR instrument was unable to resolve leads widths under 1 km, larger than all but the widest leads are identified in this study, because of this no one was interested in using AVHRR data for lead characteristics studies, but it, nonetheless, offers good coverage over much of a year for many parts of the Arctic Ocean. Tschudi et al (2007) present a high-resolution assessment of springtime leads in the Baffin Island and North Pole Seas from the 1998 Surface Heat Budget of the Arctic Ocean (SHEBA) field campaign. They employ aircraft observations from a passive microwave radiometer, video camera, and infrared pyrometer. This study needed to use and maintain many facilities and tools, which is not an economical benefit. Wadhams (1981) and Wadhams et al. (2010) use submarine sonar to observe the underside of sea ice and observe the distribution of leads, although they thoroughly studied the underside of sea ice leads they still had many gaps in their work. Key et al. (1994) use a variety of satellite-borne instruments to assess the effect of sensor resolution on observed lead characteristics. Although in most of the recent works they didn t consider hydrological models which has critical role to analyze sea ice leads in this study, a 20 km transect of energy flux data, collected during lowaltitude flights over Baffin Island Sea ice during Arctic lead experiment (LeadEx) to identify and characterize leads is analyzed. The corresponding hydrological equations and values for the identification and characterization of leads using a surface temperature anomaly as a signature are presented. Even though the advert of new space geodesy observations and data especially Gravity Recovery and Climate Experiment (GRACE) and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) provide us with high rate opportunities to study sea ice leads they still need more resolution models to observe narrow regions such as, Baffin Island Sea. 2. Materials and Methods For this study, as it can be seen in the following satellite imagery, we have selected Baffin Island Sea which is located between Greenland, North Pole and Northern Canada (Figure 1). In this region, leads are formed as the floating floes of ice pack are subjected to edge torque from

3 International Journal of Geosciences Research Vol. 1 No. 1, pp coastlines and from adjacent floes, and are acted upon by wind and water current shear (Perovich and Richter-Menge, 2000); the ice pack accommodates these forces by reorientation, buckling, and the opening of ice leads. Except during the summer melt season, leads constitute one of the only interruptions in the polar ice pack. Ice surface temperature data used in this analysis was collected during the LeadEx. The LeadEx project was designed to study the effects of leads in the ocean-atmosphere system, including the heat flux to the atmosphere and the brine formation within leads. Air temperature was continually recorded at plane exterior, plane interior, and twice within the longwave sensor armature. In addition, on-board sensors recorded UTM, latitude / longitude coordinates, plane altitude, speed, pitch, roll, and bearing. Spring air temperature in the circumpolar seas averages 10 C; however, a steep temperature gradient within the floating ice pack allows the temperature of sea water only meters away to remain at -1.8 C. While the thick ice pack inhibits energy flux to the atmosphere by forming an insulating layer, leads have less insulating capacity and a warmer surface temperature (Figure 2). Figure 1: Satellite image of Baffin Island Sea [N and N 74 30, W and W ] which is located between Greenland (from right-side) and Northern Canada (from left-side) and Arctic Ocean (from down-side) (Image acquired from NASA Global map, US Dept. of State Geographer, 2012).

4 4 N. Najibi, A. Abedini and H. Najibi 2013 Analysis of Sea Ice Leads Figure 2: The false color infrared remote image of Baffin Island Sea ice surface temperature over a lead. This image was taken during the 2002 Arctic Lead Experiment with an aircraft-mounted sensor (In the image, black indicates the cool, older ice pack and yellow indicates the warm, thin ice of the newly formed lead. The blue rim across the lower edge of the image reflects an area of intermediate temperature and possibly of more advanced ice regrowth across the lead. The green indicates variable float boundary between ocean and sea ice).

5 International Journal of Geosciences Research Vol. 1 No. 1, pp Results and Discussion The reduced insulating capacity of leads makes them foci of ocean-atmosphere heat exchange (Gow et al., 1990) with rates of heat flux up to 100 times greater (Maykut, 1978). As a result of this enhanced heat flow, leads in that represent only that several percent of the ice pack area may account for 50% of total heat flux from the ocean to the atmosphere. Because of the strong transfer of heat to the atmosphere at leads, annual ice production at leads and young ice is twice that for thick ice (> 0.8m) (Figure 3). This ice thickness model is parameterized by data collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaign. The SHEBA campaign was designed to measure the atmospheric conditions, mass balance, and heat flux over sea ice and leads in the Baffin Island and North Pole Seas. Observations for the SHEBA experiment were collected from October 2000 to October 2008 from an ice camp which drifted from 60 N, 50 W to 85 N, 90 W. Because of signal noise in some measurements taken at LeadEx, this model employs measurements for downward longwave and downward shortwave collected during the SHEBA campaign and summarized by Huwald et al. (2005a). The sections of the surface temperature transect collected at LeadEx include measurements taken over land during takeoff and landing and taken during periods of selective flight over leads. In order to create a transect representative of random linear paths over sea ice, data collected over land, as indicated by aircraft GPS records, and data collected during deviations from a direct bearing were excluded from the sample group. Figure 3: The surface temperatures transect values are showing that the temperature spikes over leads. Here, the baseline pack ice temperature is relatively cool at ~-25º C (regard to all 20%, 10% and 1% approximations), while temperatures over leads reach -2º C.

6 6 N. Najibi, A. Abedini and H. Najibi 2013 Analysis of Sea Ice Leads In the springtime Baffin Island Sea, air temperature above the ice is very cold (~ -35 C), and water in leads begins to refreeze almost immediately after the opening of the lead. The surface of a lead remains open for water for only a brief period; however, leads with thin ice cover continue to exhibit lead characteristics, including rapid ice growth and high heat flux. It is considered appropriate to include in the definition of a lead those fissures with only thin ice cover, and it is also considered necessary to establish a threshold value for lead ice thickness; ice thinner than the threshold value will be classified as part of a lead. A similar survey of leads performed by Tschudi et al (2007) used an ice thickness threshold of <140 cm to define a lead. Because the LeadEx dataset lacked accurate downward shortwave and longwave radiation data, the researchers were unequipped to generate the transect of ice thickness values, which could be applied to a thickness threshold. Instead, the lead identification strategy was based on ice surface temperature. Surface temperature of a lead cools as ice forms across a lead and thickens (Perovich and Richter- Menge 2000). It is interpreted that warm ice is thinner ice, and defined as leads areas of ice with surface temperatures above -2 C. The ice thickness model which discussed later in this paper, obviously shows that this surface temperature threshold corresponds to an ice thickness of ~300 cm. Figure 4: Sea ice threshold and ice thickness model energy budget diagram. The ice thickness over leads can be estimated by assuming that the net atmospheric heat flux at the surface is equal to conductive heat flux through the ice. The calculation also assumes a linear temperature gradient within the ice, and as such, is most accurate for thin ice, such as that in newly formed leads, where a linear temperature gradient is an appropriate approximation.

7 International Journal of Geosciences Research Vol. 1 No. 1, pp Figure 5: The surface temperatures transect residual values for 20 %, 10 % and 1 % approximations are showing so that the temperature spikes over leads. Ice Thickness and Mathematical Hydrological Models In order to ascertain ice thickness from radiation data, an ice thickness model was developed. The model assumes net atmospheric heat flux at the ice surface equal to conductive heat flux through the ice (Figure 4). The model accepts surface temperature (T s ) as an input parameter. The values for downward shortwave radiation (Q swd ), upward shortwave radiation (Q swu ), and downward longwave radiation (Q lwd ) are based on observational data from the SHEBA dataset reported in Huwald et al. (2005b). The air temperature and ocean temperature (T o ) were assumed to be universally -24º C and -5.8º C, respectively, and the heat conductivity constant for ice (K) was a constant The model output is a value for ice thickness (h). Table 1 lists of parameters used their symbols, and values. The ice thickness is determined according to: h = K *(T s T o ) (1) Q total Although the total heat flux at the ice surface is calculated as the sum of surface heat fluxes, where fluxes upward from the ice surface to the atmosphere are positive in sign, the surface flux is computed: Q total = Q lwu + Q swu + Q sens + Q lat (Q lwd + Q swd ) (2) where Q lwu, Q sens, and Q lat are modeled values. The upward longwave radiation (Q lwu ) is calculated from the emission temperature of the ice using the surface temperature parameter (T s ), the Stephan- Boltzmann constant (σ) and the emissivity of ice (e) as: Q lwu = e *σ *T s 4 (3) The sensible heat flux (Q sens ) is calculated from air density (ρ), specific heat of air (C pa ), sensible heat coefficient (C sens ), geostrophic wind current (U a ) and surface temperature (T s ) air temperature (T a ) difference as: Q sens = ρ C * C * U *( T T ) (4) * pa sens a s a

8 8 N. Najibi, A. Abedini and H. Najibi 2013 Analysis of Sea Ice Leads The latent heat flux (Q lat ) is calculated from air density (ρ), latent heat of sublimation (L s ), latent heat transfer coefficient (C lat ), geostrophic wind current (U a ), specific humidities of the ice surface (q surf ) and air (q air ); according to Q lat = ρ * L s *C lat * U a *(q surf q air ) (5) where the specific humidity (q surf ) is calculated from saturation vapor pressure (e s ) and surface air pressure (P surf ) where 0.622e q surf = s P surf 0.378e s (6) and saturation vapor pressure (e s ) is Cice e s = 6.11*exp( 1 *(T s ) ) (7) T s Cice 2 where T s is ice surface temperature and Cice 1 and Cice 2 are constant coefficients. Finally the residuals related to those approximations have been computed (Figure 5). The modeled ice thickness calculation assumes a linear temperature gradient within the ice (Table 1). Table 1 Parameters Used in Ice Thickness Model (from Huwald et al. (2005a)) Symbol Variable or Constant Name Value Units c ice1 empirical constant C ice2 empirical constant 7.66 c water1 empirical constant c water2 empirical constant C lat latent heat transfer coefficient 1.0 x 10-3 C pa heat capacity of air 1.01 x 10 3 J kg -1 K -1 C sens sensible heat transfer coefficient 1.0 x 10-3 e emissivity of ice 0.99 e s saturation vapor pressure modeled value σ Stefan-Boltzmann Constant 5.67 x 10-8 W m -2 K -4 H ice thickness modeled value m K thermal conductivity of ice 2.03 W m -1 K -1 L s latent heat of sublimation 2.83 x 10 6 J kg -1 P s Surface air pressure hpa q air specific humidity of air modeled value q surf specific humidity at ice surface modeled value Q lat latent heat flux modeled value W m -2 Q lwd longwave radiation downward 220 W m -2 Q lwu longwave radiation upward modeled value W m -2 Q sens sensible heat flux modeled value W m -2 Q swd shortwave radiation downward 142 W m -2 Q swu shortwave radiation upward 121 W m -2 Q total total heat flux from ice surface to atmosphere modeled value W m -2 ρ air density 1.28 kg m -3 T a air temperature 212 K T o ocean temperature 235 K U a geostrophic wind speed 5 m s -1

9 International Journal of Geosciences Research Vol. 1 No. 1, pp Figure 6: Ice thickness modeled from surface temperature and surface radiative fluxes. This model is inaccurate for thicker ice due to non-linear temperature gradients in thick ice, as indicated by the exponential increase in ice thickness. The two histogram boxes indicate critical trend of the model. The left-side histogram shows the commencement of sustainability of ice thickness rather than the surface temperature while the right-side histogram emphasizes the smoothing trend of sea ice model which is going to be more indifference to the changes of surface temperature. Cwater1* ( Ts) EsatWater = 6.11* exp( ) (8) Ts Cwater2 While this is an appropriate approximation for thin ice, the non-linear temperature gradient in thick ice limits the range of temperatures for which the model is accurate. Figure 6 shows modeled ice thickness over the range of ice surface temperatures 4 C to -2 C (Figure 6). 4. Conclusion The researchers lead identification algorithm and model were applied to this transect of sea ice surface temperatures. Over this transect, the leads were identified. The average surface temperature in the whole of transects, including both lead and non-lead sea ice, is -25 C degrees (with 1% approximation), and the average surface temperature for lead ice is -1 C. The maximum lead surface temperature recorded was -49 C (shown in Figure 5). Leads vary in width, and most of the leads identified were relatively narrow. Of identified leads, only 45 % were over 100 m wide, and ice in these wider leads averaged 3.3 C cooler than ice in narrow leads. The abundance of leads of different widths using a power law distribution, as in Lindsay and Rothrock (1995) and Wadhams (1981). The number of leads of a particular width decreases for large lead widths, following a N(w) = w -b power law distribution, where w is the lead width and b = 1.4. As it can be seen in figure 6, the two histogram boxes have different roles in this designed model. The left-side histogram in ~ -1 C shows the starting point of sustainability of ice thickness length rather than the surface temperature above it. The right-side histogram emphasizes the smoothing trend of sea ice model which is beginning in ~ -1.5 C degree which is going to be

10 10 N. Najibi, A. Abedini and H. Najibi 2013 Analysis of Sea Ice Leads more invariable to the variations of surface temperature values. 5. Acknowledgements The authors would like to thank National Snow and Ice Data Center (NSIDC) in University of Colorado at Boulder and Applied Physics Laboratory in University of Washington for very useful information and scientific reports and for providing us with structural raw data, LeadEx References Eicken, H. (1992), "Salinity Profiles of Antarctic Sea ice: Field Data and Model Results", Journal of Geophysical Research, Vol. 97 (C10): pp , doi: /92JC Gow, A. J., Meese, D. A., Perovich, D. K. and Tucker III, W. B. (1990), "The anatomy of a freezing lead", Journal of Geophysical Research, Vol. 95, pp Huwald, H., Tremblay, L. B. and Blatter, H. (2005a), "Reconciling different observational data sets from Surface Heat Budget of the Arctic Ocean (SHEBA) for model validation purposes", Journal of Geophysical Research, Vol. 148, pp Huwald, H., Tremblay, L. B. and Blatter, H. (2005b), "A multilayer sigma-coordinate thermodynamic sea ice model: Validation against Surface Heat Budget of the Arctic Ocean (SHEBA)/Sea Ice Model Intercomparison Progect Part 2 (SIMIP2) data", Journal of Geophysical Research, Vol. 18, pp Key, J., J., Maslanik, A. and E. Ellefsen, E. (1994), "The effects of sensor field-of-view on the geometrical characteristics of sea ice leads and implications for large-area heat flux estimates", Remote Sens. Environ. Vol. 48, pp Lindsay, R. W. and Rothrock, D. A. (1995), "Arctic sea ice leads from advanced very high resolution radiometer images", Journal of Geophysical Research, Vol. 100(C3), pp Maykut, G. A. (1978), "Energy exchange over airborne remote-sensing dataset and also the required software to analyze them. We also thank University of Chinese Academy of Sciences as well as Institute of Geodesy at Faculty of Aerospace Engineering and Geodesy in University of Stuttgart for their financial supports for this work and any other kinds of help that they have extended to us. We also thank all reviewers and friends or researchers who supported us during this work. young sea ice in the Central Arctic", Journal of Geophysical Research, Vol. 87(C10), pp Maksym, T. and Markus, T. (2008), "Antarctic sea ice thickness and snow-to-ice conversion from atmospheric reanalysis and passive microwave snow depth", Journal of Geophysical Research, Vol. 11, pp doi: /2006 JC National Snow and Ice Data Center (NSIDC), 449 UCB University of Colorado at Boulder, CO , CIRES, (Accessed: 20 Jan 2011) Pegau, W. S. and Paulson C. A. (2001), "The albedo of Arctic leads in summer" Annual Glaciology, Vol. 33: pp Perovich, D. K. (1998), The optical properties of sea ice, Physics of Ice-Covered Sea, Helsinki Univ. Printing House, Vol. 1, pp Perovich, D. K. and Richter-Menge, J. A. (2000), "Ice growth and solar heating in springtime leads", Journal of Geophysical Research, Vol. 105(C3), pp Pinto, J. O., Alam, A., Maslanik, J. A., Curry, J. A. and Stone, R. S. (2003), "Surface characteristics and atmospheric footprint of springtime Arctic leads at SHEBA", Journal of Geophysical Research, Vol. 108 (C4), pp Tang, S., Qin, D., Ren, J., Kang, J. and Li, Z. (2007), "Structure, salinity and isotopic composition of multi-year landfast sea ice in Nella Fjord, Antarctica", Cold Regions Science and Technology, Vol. 49, pp

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