Ultrawideband Radar Measurements of Thickness of Snow Over Sea Ice

Kanagaratnam, P.; Markus, T.; Lytle, VI; Heavey, Brandon; Jansen, PW; Prescott, G.E.; Gogineni, S.

doi:10.1109/tgrs.2007.900673

Cited by 48 publications

(42 citation statements)

References 18 publications

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“…In the last decade however, airborne‐based GPR has revolutionized observational ice sheet accumulation observations. The Center for Remote Sensing of Ice Sheets began development of several airborne radar systems, capable of surveying to different depths and at varying vertical resolutions, around the year 2000 (Kanagaratnam et al, , ). Their continued improvement over the years accelerated in 2009 with the start of NASA Operation IceBridge (OIB) campaigns that are currently scheduled to run through 2019.…”

Section: Methods To Estimate Ice Sheet Smbmentioning

confidence: 99%

Observing and Modeling Ice Sheet Surface Mass Balance

Lenaerts

Medley

Broeke

et al. 2019

Reviews of Geophysics

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152

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Surface mass balance (SMB) provides mass input to the surface of the Antarctic and Greenland Ice Sheets and therefore comprises an important control on ice sheet mass balance and resulting contribution to global sea level change. As ice sheet SMB varies highly across multiple scales of space (meters to hundreds of kilometers) and time (hourly to decadal), it is notoriously challenging to observe and represent in models. In addition, SMB consists of multiple components, all of which depend on complex interactions between the atmosphere and the snow/ice surface, large‐scale atmospheric circulation and ocean conditions, and ice sheet topography. In this review, we present the state‐of‐the‐art knowledge and recent advances in ice sheet SMB observations and models, highlight current shortcomings, and propose future directions. Novel observational methods allow mapping SMB across larger areas, longer time periods, and/or at very high (subdaily) temporal frequency. As a recent observational breakthrough, cosmic ray counters provide direct estimates of SMB, circumventing the need for accurate snow density observations upon which many other techniques rely. Regional atmospheric climate models have drastically improved their simulation of ice sheet SMB in the last decade, thanks to the inclusion or improved representation of essential processes (e.g., clouds, blowing snow, and snow albedo), and by enhancing horizontal resolution (5–30 km). Future modeling efforts are required in improving Earth system models to match regional atmospheric climate model performance in simulating ice sheet SMB, and in reinforcing the efforts in developing statistical and dynamic downscaling to represent smaller‐scale SMB processes.

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Section: Methods To Estimate Ice Sheet Smbmentioning

confidence: 99%

Observing and Modeling Ice Sheet Surface Mass Balance

Lenaerts

Medley

Broeke

et al. 2019

Reviews of Geophysics

160

152

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“…Snow depth measurements over sea ice have been reported both from ground measurements (e.g. Warren et al, 1999;Massom et al, 2001) and more recently through satellite and airborne measurements (e.g Kanagaratnam et al, 2007;Kwok and Cunningham, 2008;Kwok et al, 2011;Galin et al, 2012). Two studies provide an overview of snow thicknesses over sea ice.…”

Section: The Role Of Snow and Snow Type In The Influence Of Black Carmentioning

confidence: 99%

The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

Marks

King

2013

The Cryosphere

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Abstract. The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering crosssections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption crosssection over the visible wavelengths suggests black carbon is the dominating light-absorbing impurity. The response of first-year and multi-year sea ice albedo to increasing black carbon, from 1 to 1024 ng g −1 , in a top 5 cm layer of a 155 cm-thick sea ice was calculated using a radiative-transfer model. The albedo of the first-year sea ice is more sensitive to additional loadings of black carbon than the multi-year sea ice. An addition of 8 ng g −1 of black carbon causes a decrease to 98.7 % of the original albedo for first-year sea ice compared to a decrease to 99.7 % for the albedo of multiyear sea ice, at a wavelength of 500 nm. The albedo of sea ice is surprisingly unresponsive to additional black carbon up to 100 ng g −1 . Snow layers on sea ice may mitigate the effects of black carbon in sea ice. Wet and dry snow layers of 0.5, 1, 2, 5 and 10 cm depth were added onto the sea ice surface. The albedo of the snow surface was calculated whilst the black carbon in the underlying sea ice was increased. A layer of snow 0.5 cm thick greatly diminishes the effect of black carbon in sea ice on the surface albedo. The albedo of a 2-5 cm snow layer (less than the e-folding depth of snow) is still influenced by the underlying sea ice, but the effect of additional black carbon in the sea ice is masked.

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“…These lead to strong signal scatter on the one hand, and to highly variable signal propagation velocities, which must be known to calculate thickness from travel time. Recent new technology developments have led to the design of broadband, continuous-wave frequency-modulated (CWFM) radars for snow and ice thickness measurements, which may improve some of the issues related to absorption and resolution (Kanagaratnam et al, 2007;Holt et al, 2008).…”

Section: Measurement Techniquesmentioning

confidence: 99%

Dynamics versus Thermodynamics: The Sea Ice Thickness Distribution

Haas

2003

Sea Ice

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Changes of sea ice coverage are commonly taken as an indicator for climate change. Since 30 years, the area of the Arctic and Southern oceans covered by sea ice is routinely monitored by satellite radiometers (Chapter 6). These observations show that the ice coverage of the Arctic Ocean strongly declines during summer, with an average rate of -11.1% per decade. However, in 2007 and 2008, this trend was drastically exceeded when sea ice extent reduced to record lows of only 4.13 and 4.52 km 2 , less than 20% of previous summers, and raising concerns that the Arctic Ocean might become ice-free during summers within the next few decades. However, winter ice coverage of the Arctic Ocean decreases at a much slower pace of only -2.8% per decade. And in contrast to the Arctic, sea ice coverage of the Southern Ocean increases slightly, with 0.6% and 3.4% per decade in the winter and summer, respectively.The sea ice decline in the Arctic is much more rapid than predicted by any of the Intergovernmental Panel for Climate Change (IPCC) climate models . This demonstrates our limited understanding of the processes of sea ice growth and melt, and ice motion and deformation. For a full understanding of the areal changes, additional information on ice thickness is required, but is largely missing up to the date of this writing. This chapter will discuss the importance of ice thickness information, the most frequently used ice thickness measurement techniques and results from observations of long-term, interannual and seasonal thickness variations.In Chapter 2, it was described how sea ice initially forms from open water and subsequently grows into an ice cover, or in other terms, how sea ice grows thermodynamically. One of the basic concepts is that the more the ice grows thicker, the colder the air is due to the establishment of greater temperature gradients in the ice, and higher freezing rates. Vice versa, it would follow that as a consequence of climate warming, the polar sea ice cover would become thinner. However, another process contributes to the sea ice thickness distribution: Due to its relative thinness -some decimetres to a few metres -sea ice fl oating over deep water is subject to winds and currents which steadily move the ice around, i.e. the ice cover drifts. As a result, it breaks up into fl oes interspersed by open water leads. With changing drift directions and speeds, the ice fl oes will be pushed together and collide with each other. If the resulting forces in the ice become too large, it will fi nally break. The resulting

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Ultrawideband Radar Measurements of Thickness of Snow Over Sea Ice

Cited by 48 publications

References 18 publications

Observing and Modeling Ice Sheet Surface Mass Balance

Observing and Modeling Ice Sheet Surface Mass Balance

The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

Dynamics versus Thermodynamics: The Sea Ice Thickness Distribution

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