Impact of snow accumulation on CryoSat‐2 range retrievals over Arctic sea ice: An observational approach with buoy data

Ricker, Robert; Hendricks, Stefan; Perovich, Donald K.; Helm, Veit; Gerdes, Rüdiger

doi:10.1002/2015gl064081

Cited by 75 publications

(77 citation statements)

References 31 publications

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“…summer-winter, may change slightly with the form of the retracker, e.g. Ricker et al (2015) showed some influence of the form of the retracker on sea ice freeboard results, we suspect that any CS2-detected elevation will be more dependent on the changing conditions than on the detailed form of the retracker.…”

Section: Discussionmentioning

confidence: 91%

CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps

et al. 2015

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Abstract. We show that the CryoSat-2 radar altimeter can provide useful estimates of surface elevation change on a variety of Arctic ice caps, on both monthly and yearly timescales. Changing conditions, however, can lead to a varying bias between the elevation estimated from the radar altimeter and the physical surface due to changes in the ratio of subsurface to surface backscatter. Under melting conditions the radar returns are predominantly from the surface so that if surface melt is extensive across the ice cap estimates of summer elevation loss can be made with the frequent coverage provided by CryoSat-2. For example, the average summer elevation decreases on the Barnes Ice Cap, Baffin Island, Canada were 2.05 ± 0.36 m (2011), 2.55 ± 0.32 m (2012), 1.38 ± 0.40 m (2013) and 1.44 ± 0.37 m (2014), losses which were not balanced by the winter snow accumulation. As winter-to-winter conditions were similar, the net elevation losses were 1.0 ± 0.20 m (winter 2010/11 to winter 2011/12), 1.39 ± 0.20 m (2011/12 to 2012/13) and 0.36 ± 0.20 m (2012/13 to 2013/14); for a total surface elevation loss of 2.75 ± 0.20 m over this 3-year period. In contrast, the uncertainty in height change from Devon Ice Cap, Canada, and Austfonna, Svalbard, can be up to twice as large because of the presence of firn and the possibility of a varying bias between the true surface and the detected elevation due to changing year-to-year conditions. Nevertheless, the surface elevation change estimates from CryoSat for both ice caps are consistent with field and meteorological measurements.

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Section: Discussionmentioning

confidence: 91%

CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps

et al. 2015

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“…Snow depth is also a requirement for altimetry-based retrieval of sea ice properties (e.g., ice thickness), whereby inadequate knowledge of snow depth distribution directly impacts the availability and quality of derived products [Giles et al, 2007;Kern et al, 2015;Ricker et al, 2015]. Despite its broad importance, remotely sensed estimates of snow depth on sea ice have previously only been available from coarse resolution passive microwave data [e.g.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Operation IceBridge quick‐look snow depth estimates on sea ice

King

Howell

Derksen

et al. 2015

Geophysical Research Letters

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We evaluate Operation IceBridge (OIB) “quick‐look” snow depth on sea ice retrievals using in situ measurements taken over immobile first‐year ice (FYI) and multiyear ice (MYI) during March of 2014. Good agreement was found over undeformed FYI (−4.5 cm mean bias) with reduced agreement over deformed FYI (−6.6 cm mean bias). Over MYI, the mean bias was −5.7 cm, but 54% of retrievals were discarded by the OIB retrieval process as compared to only 10% over FYI. Footprint scale analysis revealed a root‐mean‐square error (RMSE) of 6.2 cm over undeformed FYI with RMSE of 10.5 cm and 17.5 cm in the more complex deformed FYI and MYI environments. Correlation analysis was used to demonstrate contrasting retrieval uncertainty associated with spatial aggregation and ice surface roughness.

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“…In order to reduce the effect of deformed sea ice on the freeboard and to reduce noise, we calculate modal CS2 freeboard for the relevant grid cells. The modal value is retrieved by fitting a log-normal function to the freeboard distribution of a grid cell and picking the value at the probability maximum [11]. The CS2 freeboard itself is retrieved according to Section 2.2.1.…”

Section: Airborne Laser Scanner Data and Coincident Cryosat-2 Freeboardmentioning

confidence: 99%

“…One source of the high scattering are the different scales of the footprint. While CS2 has a footprint of approximately 300 × 1650 m, the ALS provides a spatial resolution in the range of centimeters and a swath width in the range of ∼100 m. Another source of discrepancy is the fact that the ALS scans the snow surface, while the CS2 radar penetrates into the snow, potentially scattered by internal layers [11,12]. Although we carefully supervise the ALS modal freeboard, it also contains interpolation errors in the instantaneous sea surface height, despite the potentially more accurate lead detection compared to CS2.…”

Section: Comparison With Coincident Airborne Laser Scanner Measurementsmentioning

confidence: 99%

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The Impact of Geophysical Corrections on Sea-Ice Freeboard Retrieved from Satellite Altimetry

2016

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Satellite altimetry is the only method to monitor global changes in sea-ice thickness and volume over decades. Such missions (e.g., ERS, Envisat, ICESat, CryoSat-2) are based on the conversion of freeboard into thickness by assuming hydrostatic equilibrium. Freeboard, the height of the ice above the water level, is therefore a crucial parameter. Freeboard is a relative quantity, computed by subtracting the instantaneous sea surface height from the sea-ice surface elevations. Hence, the impact of geophysical range corrections depends on the performance of the interpolation between subsequent leads to retrieve the sea surface height, and the magnitude of the correction. In this study, we investigate this impact by considering CryoSat-2 sea-ice freeboard retrievals in autumn and spring. Our findings show that major parts of the Arctic are not noticeably affected by the corrections. However, we find areas with very low lead density like the multiyear ice north of Canada, and landfast ice zones, where the impact can be substantial. In March 2015, 7.17% and 2.69% of all valid CryoSat-2 freeboard grid cells are affected by the ocean tides and the inverse barometric correction by more than 1 cm. They represent by far the major contributions among the impacts of the individual corrections.

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Impact of snow accumulation on CryoSat‐2 range retrievals over Arctic sea ice: An observational approach with buoy data

Cited by 75 publications

References 31 publications

CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps

CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps

Evaluation of Operation IceBridge quick‐look snow depth estimates on sea ice

The Impact of Geophysical Corrections on Sea-Ice Freeboard Retrieved from Satellite Altimetry

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