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Melting is mapped over Antarctica at a high spatial resolution using a novelmelt detection algorithm based on wavelets and multiscale analysis. Themethod is applied to Ku-band (13.4 GHz) normalized backscattering measuredby SeaWinds onboard the satellite QuikSCAT and spatially enhanced on a 5 km grid over theoperational life of the sensor (1999–2009). Wavelet-based estimates ofmelt spatial extent and duration are compared with those obtained by meansof threshold-based detection methods, where melting is detected when themeasured backscattering is 3 dB below the preceding winter mean value.Results from both methods are assessed by means of automatic weather station(AWS) air surface temperature records. The yearly melting index, the productof melted area and melting duration, found using a fixed threshold andwavelet-based melt algorithm are found to have a relative difference within7% for all years. Most of the difference between melting recordsdetermined from QuikSCAT is related to short-duration backscatter changesidentified as melting using the threshold methodology but not thewavelet-based method. The ability to classify melting based on relativepersistence is a critical aspect of the wavelet-based algorithm. Compared withAWS air-temperature records, both methods show a relative agreement to within10% based on estimated melt conditions, although the fixed thresholdgenerally finds a greater agreement with AWS. Melting maps obtained with thewavelet-based approach are also compared with those obtained from spacebornebrightness temperatures recorded by the Special Sensor Microwave/Image(SSM/I). With respect to passive microwave records, we find a higher degreeof agreement (9% relative difference) for the melting index using thewavelet-based approach than threshold-based methods (11% relativedifference)

A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009)