Abstract
AbstractA new method for the detection of sea ice using GNSS‐R (Global Navigation Satellite Systems Reflectometry) is presented and applied to 33 months of data from the U.K. TechDemoSat‐1 mission. This method of sea ice detection shows the potential for a future GNSS‐R polar mission, attaining an agreement of over 98% and 96% in the Antarctic and Arctic, respectively, when compared to the European Space Agency's Climate Change Initiative sea ice concentration product. The algorithm uses a combination of two parameters derived from the delay‐Doppler Maps to quantify the spread of power in delay and Doppler. Application of thresholds then allows sea ice to be distinguished from open water. Differences between the TechDemoSat‐1 sea ice detection and comparison data sets are explored. The results provide information on the seasonal and multiyear changes in sea ice distribution of the Arctic and Antarctic. Future potential and applications of this technique are discussed.
Highlights
Monitoring sea ice is important to observe and understand global climate processes and their changes, due to the dynamic role that sea ice plays in the physics of the Earth's climate, not least in altering the Earth's albedo (Stroeve et al, 2011)
The delay‐Doppler maps (DDMs) from TDS‐1 are not calibrated with regard to direct signal power, observables from the maximum‐normalized DDMs were considered, such as the ratio of power in the signal box to that of the noise and the percentage of total power contained in signal boxes of varying sizes
This study has shown that sea ice detection using GNSS‐R is possible with an agreement of 98.4% in the Antarctic and 96.6% in the Arctic through the use of two combined parameters and appropriate thresholds
Summary
Monitoring sea ice is important to observe and understand global climate processes and their changes, due to the dynamic role that sea ice plays in the physics of the Earth's climate, not least in altering the Earth's albedo (Stroeve et al, 2011). Cryospheric applications include the detection and altimetry of sea ice (e.g., Alonso‐Arroyo et al, 2017; Hu et al, 2017; Li et al, 2017; Yan & Huang, 2016), the altimetry of glacial ice (e.g., Cardellach et al, 2004; Cartwright et al, 2018; Rius et al, 2017), and permittivity of reflective surfaces (Belmonte Rivas et al, 2010; Fabra et al, 2012) The use of these signals of opportunity and the need only for a receiver in space mean that GNSS‐R is an extremely low‐cost and, being a passive system, low‐power method of remote sensing.
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