Circumpolar Mapping of Ground-Fast Lake Ice

Abstract

Shallow lakes are common across the entire Arctic. They play an important role as methane sources and wildlife habitats, and they are also associated with thermokarst processes which are characteristic of permafrost environments. Many lakes freeze to the ground along their rims and often over the entire extent during winter time. Knowledge on the spatial patterns of ground-fast and floating ice is important as it relates to methane release, talik formation and hydrological processes, but no circumpolar account of this phenomenon is currently available. Previous studies have shown that ground-fast ice can easily be detected using C-band Synthetic Aperture Radar (SAR) backscatter intensity data acquired from satellites. A major challenge is that backscatter intensity varies across the satellite scenes due to incidence angle effects. Circumpolar application therefore requires the inclusion of incidence angle dependencies into the detection algorithm. An approach using ENVISAT ASAR Wide Swath data (approximately 120 m spatial resolution) has therefore been developed supported by bathymetric measurements for lakes in Siberia. This approach was then further applied across the entire Arctic for late winter 2008. Ground-fast ice fraction has been derived for (1) two million lake objects larger than 0.025 km 2 (post-processed GlobeLand30), (2) a 50 × 50 km grid and (3) within certain zones relevant for climate studies (permafrost type, last glacial maximum, Yedoma). Especially lakes smaller than approximately 0.1 km 2 may freeze completely to the ground. The proportion of ground-fast ice increases with increasing soil organic carbon content in the proximity of the lakes. This underlines the importance of such lakes for emission studies and the need to map the occurrence of ground-fast lake ice. Clusters of variable fractions of ground-fast ice occur especially in Yedoma regions of Eastern Siberia and Alaska. This reflects the nature of thaw lake dynamics. Analyses of lake depth measurements from several sites suggest that the used method yields the potential to utilize ground-fast lake ice information over larger areas with respect to landscape development, but results need to be treated with care, specifically for larger lakes and along river courses.

Simplified Normalization of C-Band Synthetic Aperture Radar Data for Terrestrial Applications in High Latitude Environments

“…Various approaches for angular normalization exist. Advanced approaches are based on histogram or frequency matching [2], while many empirical approaches rely on fitting a first or second order polynomial to incidence angle and backscatter values [3][4][5][6][7][8]. Previous studies [7,9] have pointed out that the relationship between incidence angle and backscatter can be considered as linear for a limited incidence angle range.…”

Toward understanding the contribution of waterbodies to the methane emissions of a permafrost landscape on a regional scale—A case study from the Mackenzie Delta, Canada

“…Marsh, ), forming so‐called bedfast or grounded ice, whereas deeper waterbodies remain unfrozen beneath the ice cover. Synthetic Aperture Radar (SAR) data can be used to distinguish these two different waterbody ice regimes based on strong differences in the backscatter intensity signatures from grounded and floating ice (e.g., Antonova et al., ; Bartsch et al., ; Jones et al., ). The SAR signal penetrates through fresh ice and, in case of floating ice, scatters back from the rough ice bottom, resulting in high backscatter intensity.…”

Surface State across Scales; Temporal and Spatial Patterns in Land Surface Freeze/Thaw Dynamics

“…This may lead to different results (frozen or unfrozen) for a certain day due to daily temperature variations. The melting snow class in the ASCAT product has not been considered as unfrozen for the purpose of this study, although the ground below may start to thaw when snow is melting [49]. First, the detection of melting snow for a certain day depends on actual acquisition timing (a.m. or p.m., not all days with melting might be captured), and second, melting snow is not available from the ASAR product as it only gives information on the day of year of the freeze and thaw.…”

“…Floating ice produces relatively high backscatter (higher compared to summer values) [49]; therefore, the presence of lakes reduces backscatter in summer, under calm conditions, increases short term under windy conditions [65], and floating ice remains after snow melt [66] and increases backscatter in winter (depending on ice growth patterns). This all introduces noise that may lead to a lower performance of the threshold and edge detection algorithms.…”