A comparison of shipborne and airborne electromagnetic methods for Antarctic sea ice thickness measurements

2003 ◽  
Vol 34 (1-2) ◽  
pp. 46-50 ◽  
Author(s):  
James E. Reid ◽  
Julian Vrbancich ◽  
Anthony P. Worby
Keyword(s):  
Sea Ice ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Electromagnetic Methods ◽  
Airborne Electromagnetic ◽  
Thickness Measurements

Estimating the thickness of ridged sea ice from ship observations in the Ross Sea

2003 ◽  
Vol 15 (1) ◽  
pp. 47-54 ◽  
Author(s):  
TINA TIN ◽  
MARTIN O. JEFFRIES ◽  
MIKKO LENSU ◽  
JUKKA TUHKURI
Keyword(s):  
Sea Ice ◽  
Ross Sea ◽  
Low Cost ◽  
Thickness Distribution ◽  
Ice Thickness ◽  
Equivalent Thickness ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Using Data ◽  
Original Formula

Ship-based observations of sea ice thickness using the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol provide information on ice thickness distribution at relatively low cost. This protocol uses a simple formula to calculate the mass of ice in ridges based on surface observations. We present two new formulae and compare these with results from the “Original” formula using data obtained in the Ross Sea in autumn and winter. The new “r-star” formula uses a more realistic ratio of sail and keel areas to transform dimensions of sails to estimates of mean keel areas. As a result, estimates of “equivalent thickness” (i.e. mean thickness of ice in ridged areas) increased by over 200%. The new “Probability” formula goes one step further, by incorporating the probability that a sail is associated with a keel underwater, and the probability that keels may be found under level surfaces. This resulted in estimates of equivalent thickness comparable with the Original formula. Estimates of equivalent thickness at one or two degree latitude resolution are sufficiently accurate for validating sea ice models. Although ridges are small features in the Ross Sea, we have shown that they constitute a significant fraction of the total ice mass.

Post-processing calibration of frequency-domain electromagnetic data for sea ice thickness measurements

2004 ◽  
Vol 2004 (1) ◽  
pp. 1-4
Author(s):  
James Reid ◽  
John Bishop ◽  
Angus Munro ◽  
Andi Pfaffling ◽  
Kazu Tateyama ◽  
...  
Keyword(s):  
Sea Ice ◽  
Frequency Domain ◽  
Ice Thickness ◽  
Post Processing ◽  
Sea Ice Thickness ◽  
Electromagnetic Data ◽  
Thickness Measurements

Data-derived spatial-resolution errors of Antarctic sea-ice thickness

2013 ◽  
Vol 36 (3) ◽  
pp. 202-220 ◽  
Author(s):  
Mary D. Stampone ◽  
Cathleen A. Geiger ◽  
Tracy L. DeLiberty ◽  
E. Rachel Bernstein
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice

scholarly journals Snow depth uncertainty and its implications on satellite derived Antarctic sea ice thickness

2018 ◽  
Author(s):  
Daniel Price ◽  
Iman Soltanzadeh ◽  
Wolfgang Rack
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Snow Accumulation ◽  
In Situ Measurements ◽  
Ice Thickness ◽  
Growth Season ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Fast Ice

Abstract. Knowledge of the snow depth distribution on Antarctic sea ice is poor but is critical to obtaining sea ice thickness from satellite altimetry measurements of freeboard. We examine the usefulness of various snow products to provide snow depth information over Antarctic fast ice with a focus on a novel approach using a high-resolution numerical snow accumulation model (SnowModel). We compare this model to results from ECMWF ERA-Interim precipitation, EOS Aqua AMSR-E passive microwave snow depths and in situ measurements at the end of the sea ice growth season. The fast ice was segmented into three areas by fastening date and the onset of snow accumulation was calibrated to these dates. SnowModel falls within 0.02 m snow water equivalent (swe) of in situ measurements across the entire study area, but exhibits deviations of 0.05 m swe from these measurements in the east where large topographic features appear to have caused a positive bias in snow depth. AMSR-E provides swe values half that of SnowModel for the majority of the sea ice growth season. The coarser resolution ERA-Interim, not segmented for sea ice freeze up area reveals a mean swe value 0.01 m higher than in situ measurements. These various snow datasets and in situ information are used to infer sea ice thickness in combination with CryoSat-2 (CS-2) freeboard data. CS-2 is capable of capturing the seasonal trend of sea ice freeboard growth but thickness results are highly dependent on the assumptions involved in separating snow and ice freeboard. With various assumptions about the radar penetration into the snow cover, the sea ice thickness estimates vary by up to 2 m. However, we find the best agreement between CS-2 derived and in situ thickness when a radar penetration of 0.05-0.10 m into the snow cover is assumed.

scholarly journals About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice

2015 ◽  
Vol 9 (5) ◽  
pp. 4893-4923 ◽  
Author(s):  
S. Schwegmann ◽  
E. Rinne ◽  
R. Ricker ◽  
S. Hendricks ◽  
V. Helm
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Altimeter Data ◽  
Ice Thickness ◽  
Radar Altimeter ◽  
Growth Season ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Abstract Knowledge ◽  
Modal Values

Abstract. Knowledge about Antarctic sea-ice volume and its changes over the past decades has been sparse due to the lack of systematic sea-ice thickness measurements in this remote area. Recently, first attempts have been made to develop a sea-ice thickness product over the Southern Ocean from space-borne radar altimetry and results look promising. Today, more than 20 years of radar altimeter data are potentially available for such products. However, data come from different sources, and the characteristics of individual sensors differ. Hence, it is important to study the consistency between single sensors in order to develop long and consistent time series over the potentially available measurement period. Here, the consistency between freeboard measurements of the Radar Altimeter 2 on-board Envisat and freeboard measurements from the Synthetic-Aperture Interferometric Radar Altimeter on-board CryoSat-2 is tested for their overlap period in 2011. Results indicate that mean and modal values are comparable over the sea-ice growth season (May–October) and partly also beyond. In general, Envisat data shows higher freeboards in the seasonal ice zone while CryoSat-2 freeboards are higher in the perennial ice zone and near the coasts. This has consequences for the agreement in individual sectors of the Southern Ocean, where one or the other ice class may dominate. Nevertheless, over the growth season, mean freeboard for the entire (regional separated) Southern Ocean differs generally by not more than 2 cm (5 cm, except for the Amundsen/Bellingshausen Sea) between Envisat and CryoSat-2, and the differences between modal freeboard lie generally within ±10 cm and often even below.

scholarly journals A comparison between Envisat and ICESat sea ice thickness in the Antarctic

2020 ◽  
Author(s):  
Jinfei Wang ◽  
Chao Min ◽  
Robert Ricker ◽  
Qinghua Yang ◽  
Qian Shi ◽  
...  
Keyword(s):  
Sea Ice ◽  
European Space Agency ◽  
Weddell Sea ◽  
Ice Thickness ◽  
Radar Altimeter ◽  
Average Deviation ◽  
Absolute Deviation ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
The Antarctic

Abstract. The crucial role that Antarctic sea ice plays in the global climate system is strongly linked to its thickness. While in situ observations are too sparse in the Antarctic to determine long-term trends of the Antarctic sea ice thickness on a global scale, satellite radar altimetry data can be applied with a promising prospect. A newly released Envisat-derived product from the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI), including sea ice freeboard and sea ice thickness, covers the entire Antarctic year-round from 2002 to 2012. In this study, the SICCI Envisat sea ice thickness in the Antarctic is firstly compared with a conceptually new proposed ICESat ice thickness that has been derived from an algorithm employing modified ice density. Both data sets have been validated with the Weddell Sea upward looking sonar measurements (ULS), indicating that ICESat agrees better with field observations. The inter-comparisons are conducted for three seasons except winter based on the ICESat operating periods. According to the results, the deviations between Envisat and ICESat sea ice thickness are different considering different seasons, years and regions. More specifically, the smallest average deviation between Envisat and ICESat sea ice thickness exists in spring by −0.03 m while larger deviations exist in summer and autumn by 0.86 m and 0.62 m, respectively. Although the smallest absolute deviation occurs in spring 2005 by 0.02 m, the largest correlation coefficient appears in autumn 2004 by 0.77. The largest positive deviation occurs in the western Weddell Sea by 1.03 m in summer while the largest negative deviation occurs in the Eastern Antarctic by −0.25 m in spring. Potential reasons for those deviations mainly deduce from the limitations of Envisat radar altimeter affected by the weather conditions and the surface roughness as well as the different retrieval algorithms. The better performance in spring of Envisat has a potential relation with relative humidity.

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