Snow Radar Derived Surface Elevations and Snow Depths Multi-Year Time Series over Greenland Sea-Ice During IceBridge Campaigns

This paper presents estimates of snow depth over sea ice from the 2009 through 2011 NASA Operation IceBridge [1] spring campaigns over Greenland and the Arctic Ocean, derived from Kansas University's wideband Snow Radar [2] over annually repeated sea-ice transects. We compare the estimates of the top surface interface heights between NASA's Atmospheric Topographic Mapper (ATM) [3] and the Snow Radar. We follow this by comparison of multi-year snow depth records over repeated sea-ice transects to derive snow depth changes over the area. For the purpose of this paper our analysis will concentrate on flights over North/South basin transects off Greenland, which are the closest overlapping tracks over this time period. The Snow Radar backscatter returns allow for surface and interface layer types to be differentiated between snow, ice, land and water using a tracking and classification algorithm developed and discussed in the paper. The classification is possible due to different scattering properties of surfaces and volumes at the radar's operating frequencies (2-6.5 GHz), as well as the geometries in which they are viewed by the radar. These properties allow the returns to be classified by a set of features that can be used to identify the type of the surface or interfaces preset in each vertical profile. We applied a Support Vector Machine (SVM) learning algorithm [4] to the Snow Radar data to classify each detected interface into one of four types. The SVM algorithm was trained on radar echograms whose interfaces were visually classified and verified against coincident aircraft data obtained by CAMBOT [5] and DMS [6] imaging sensors as well as the scanning ATM lidar. Once the interface locations were detected for each vertical profile we derived a range to each interface that was used to estimate the heights above the WGS84 ellipsoid for direct comparisons with ATM. Snow Radar measurements were calibrated against ATM data over areas free of snow cover and over GPS land surveyed areas of Thule and Sondrestrom air bases. The radar measurements were compared against the ATM and the GPS measurements that were located in the estimated radar footprints, which resulted in an overall error of ~ 0.3 m between the radar and ATM. The agreement between ATM and GPS survey is within +/- 0.1 m. References: [1] http://www.nasa.gov/mission_pages/icebridge/ [2] Panzer, B. et. al, "An ultra-wideband, microwave radar for measuring snow thickness on sea ice and mapping near-surface internal layers in polar firn," Submitted to J. of Glaciology Instr. and Tech., July 23, 2012. [3] Krabill, William B. 2009 and 2011, updated current year. IceBridge ATM L1B Qfit Elevation and Return Strength. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [4] Chih-Chung Chang and Chih-Jen Lin. "Libsvm: a library for support vector machines", ACM Transactions on Intelligent Systems and Technology, 2:2:27:1-27:27, 2011. [5] Krabill, William B. 2009 and 2011, updated current year. IceBridge CAMBOT L1B Geolocated Images, [2009-04-25, 2011-04-15]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [6] Dominguez, Roseanne. 2011, updated current year. IceBridge DMS L1B Geolocated and Orthorectified Images. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media