A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009)
Melting is mapped over Antarctica at a high spatial resolution using a novel melt detection algorithm based on wavelets and multiscale analysis. The method is applied to Ku-band (13.4 GHz) normalized backscattering measured by SeaWinds onboard the satellite QuikSCAT and spatially enhanced on a 5 km...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2014-01-01
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| Series: | The Cryosphere |
| Online Access: | http://www.the-cryosphere.net/8/25/2014/tc-8-25-2014.pdf |
| Summary: | Melting is mapped over Antarctica at a high spatial resolution using a novel
melt detection algorithm based on wavelets and multiscale analysis. The
method is applied to Ku-band (13.4 GHz) normalized backscattering measured
by SeaWinds onboard the satellite QuikSCAT and spatially enhanced on a 5 km grid over the
operational life of the sensor (1999–2009). Wavelet-based estimates of
melt spatial extent and duration are compared with those obtained by means
of threshold-based detection methods, where melting is detected when the
measured 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 product
of melted area and melting duration, found using a fixed threshold and
wavelet-based melt algorithm are found to have a relative difference within
7% for all years. Most of the difference between melting records
determined from QuikSCAT is related to short-duration backscatter changes
identified as melting using the threshold methodology but not the
wavelet-based method. The ability to classify melting based on relative
persistence is a critical aspect of the wavelet-based algorithm. Compared with
AWS air-temperature records, both methods show a relative agreement to within
10% based on estimated melt conditions, although the fixed threshold
generally finds a greater agreement with AWS. Melting maps obtained with the
wavelet-based approach are also compared with those obtained from spaceborne
brightness temperatures recorded by the Special Sensor Microwave/Image
(SSM/I). With respect to passive microwave records, we find a higher degree
of agreement (9% relative difference) for the melting index using the
wavelet-based approach than threshold-based methods (11% relative
difference). |
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| ISSN: | 1994-0416 1994-0424 |