Assessment of radar‐derived snow depth over <scp>A</scp>rctic sea ice

Newman, Thomas; Farrell, S. L.; Richter‐Menge, Jacqueline A.; Connor, L. N.; Kurtz, N. T.; Elder, Bruce; McAdoo, D. C.

doi:10.1002/2014jc010284

Cited by 66 publications

(87 citation statements)

References 33 publications

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“…Although the data in Fig. 6 represent level ice in the landing areas excluding local variations like sastrugi, the results are in agreement with other studies of in situ data (Sturm et al, 2006;Farrell et al, 2012;Newman et al, 2014) and data from IceBridge airborne surveys (Kurtz and Farrel, 2011;Kwok, 2017). It is noteworthy that the snow depth distribution in The Cryosphere Discuss., https://doi.org /10.5194/tc-2017-278 Manuscript under review for journal The Cryosphere Discussion started: 22 December 2017 c Author(s) 2017.…”

Section: Depth Of Undisturbed Snow Coversupporting

confidence: 90%

Snow depth on Arctic sea ice from historical in situ data

Shalina¹,

Sandven²

2017

Preprint

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Abstract.In this paper we analyze snow data from Soviet airborne expeditions Sever that was collected in the Arctic around places of landings in March, April and May and cover much wider area than the region of observations of Soviet North Pole drifting stations. Particularly, there were a lot of Sever observations in the Eurasian seas. We investigate the following snow parameters: average snow depth on the level ice, height and area of sastrugi, depth of snow dunes attached to ice ridges and 10 depth of snow on hummocks. We have built new snow depth climatology for the late winter that was calculated using both Sever expedition and North Pole drifting station observations. Our result refines the description of snow depth in the central Arctic and provides detailed information on snow depth in the marginal seas. In the 1970s-80s the snow cover in the central Arctic had the following characteristics: the snow depth of the undisturbed snow was 21.2 cm, the depth of sastrugi (that occupied about 36% of the ice surface) was 36.2 cm and the depth of snow assembled near the hummocks and ridges was 15 about 65 cm. For the marginal seas Sever observations revealed that the average depth of undisturbed snow on the level ice changed from 9.8 cm in the Laptev Sea to 15.3 cm in the East Siberian Sea, the topmost value in the East Siberian Sea is explained by the highest proportion of multiyear ice there. Observations demonstrated a very high spatial variability of snow depth in the marginal seas characterized by standard deviation changing from 66 to 100%. Average height of sastrugi in the Eurasian seas varied from 23 cm to about 32 cm with standard deviation from 50 to 56%. Average area covered by sastrugi 20 in the marginal seas was estimated as 36.5% of the area of the ice floe where those features have been observed. The snow map introduced here as a new climatology is built from Sever and North Pole data, with the latter amounted to 6.1% of the whole data set. On the whole, our snow depth map reveals lower values comparing to Warren climatology in the central Arctic and shows refined information for the Eurasian seas.

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Section: Depth Of Undisturbed Snow Coversupporting

confidence: 90%

Snow depth on Arctic sea ice from historical in situ data

Shalina¹,

Sandven²

2017

Preprint

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“…We then discriminate between first year ice (FYI) and multiyear ice (MYI) to investigate whether f depends on the ice age. In general, MYI has a thicker snow layer than FYI [see, e.g., Newman et al, 2014], and we examine the claim of Kwok [2014] that the residual error due to snow pack scattering is larger for thicker snow depths.…”

Section: Discussionmentioning

confidence: 99%

“…The airborne data will be more sensitive to the presence of thinner ice floes that may be missed by the satellites (due to the large satellite footprint and rejection of complex waveforms [Wingham et al, 2006]), as well as pressure ridges. It has been shown recently that the OIB radar system is impacted by ice surface morphology, and estimating snow depth uncertainty over heavily deformed sea ice remains challenging [Newman et al, 2014]. Using a wavelet technique, Newman et al [2014] found that snow radar-derived snow depths over MYI were larger than in the OIB Sea Ice Freeboard, Thickness, and Snow Depth product by 1 cm and 4 cm in 2011 and 2012, respectively.…”

Section: 1002/2015gl064823mentioning

confidence: 99%

Arctic sea ice freeboard from AltiKa and comparison with CryoSat‐2 and Operation IceBridge

Armitage

Ridout

2015

Geophysical Research Letters

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Satellite radar altimeters have improved our knowledge of Arctic sea ice thickness over the past decade. The main sources of uncertainty in sea ice thickness retrievals are associated with inadequate knowledge of the snow layer depth and the radar interaction with the snow pack. Here we adapt a method of deriving sea ice freeboard from CryoSat‐2 to data from the AltiKa Ka band radar altimeter over the 2013–14 Arctic sea ice growth season. AltiKa measures basin‐averaged freeboards between 4.4 cm and 6.9 cm larger than CryoSat‐2 in October and March, respectively. Using airborne laser and radar measurements from spring 2013 and 2014, we estimate the effective scattering horizon for each sensor. While CryoSat‐2 echoes penetrate to the ice surface over first‐year ice and penetrate the majority (82 ± 3%) of the snow layer over multiyear ice, AltiKa echoes are scattered from roughly the midpoint (46 ± 5%) of the snow layer over both ice types.

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“…The Wavelet algorithm, described by Newman et al (2014), operates on each trace (column) of an echogram independently and has three components: interface detection through the use of the Haar wavelet-continuous wavelet transform (Haar-CWT), topographic filtering using the h topo parameter (to mitigate against heavily deformed ice topography on the radar point of closest approach), and the assignment of precision to each derived snow depth using radar system parameters.…”

Section: Waveletmentioning

confidence: 99%

Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge

et al. 2017

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Abstract. Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air-snow (a-s) and snow-ice (s-i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two groundbased campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice.

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Assessment of radar‐derived snow depth over Arctic sea ice

Cited by 66 publications

References 33 publications

Snow depth on Arctic sea ice from historical in situ data

Snow depth on Arctic sea ice from historical in situ data

Arctic sea ice freeboard from AltiKa and comparison with CryoSat‐2 and Operation IceBridge

Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge

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