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...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:01426c56772145ce884c3556e23684ac 2023-05-15T14:03:50+02:00 A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) N. Steiner M. Tedesco 2014-01-01 https://doi.org/10.5194/tc-8-25-2014 http://www.the-cryosphere.net/8/25/2014/tc-8-25-2014.pdf https://doaj.org/article/01426c56772145ce884c3556e23684ac en eng Copernicus Publications 1994-0416 1994-0424 doi:10.5194/tc-8-25-2014 http://www.the-cryosphere.net/8/25/2014/tc-8-25-2014.pdf https://doaj.org/article/01426c56772145ce884c3556e23684ac undefined The Cryosphere, Vol 8, Iss 1, Pp 25-40 (2014) geo Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2014 fttriple https://doi.org/10.5194/tc-8-25-2014 2023-01-22T19:22:50Z 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). Article in Journal/Newspaper Antarc* Antarctica The Cryosphere Unknown The Cryosphere 8 1 25 40 |
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English |
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geo N. Steiner M. Tedesco A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) |
topic_facet |
geo |
description |
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). |
format |
Article in Journal/Newspaper |
author |
N. Steiner M. Tedesco |
author_facet |
N. Steiner M. Tedesco |
author_sort |
N. Steiner |
title |
A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) |
title_short |
A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) |
title_full |
A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) |
title_fullStr |
A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) |
title_full_unstemmed |
A wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over Antarctica (2000–2009) |
title_sort |
wavelet melt detection algorithm applied to enhanced-resolution scatterometer data over antarctica (2000–2009) |
publisher |
Copernicus Publications |
publishDate |
2014 |
url |
https://doi.org/10.5194/tc-8-25-2014 http://www.the-cryosphere.net/8/25/2014/tc-8-25-2014.pdf https://doaj.org/article/01426c56772145ce884c3556e23684ac |
genre |
Antarc* Antarctica The Cryosphere |
genre_facet |
Antarc* Antarctica The Cryosphere |
op_source |
The Cryosphere, Vol 8, Iss 1, Pp 25-40 (2014) |
op_relation |
1994-0416 1994-0424 doi:10.5194/tc-8-25-2014 http://www.the-cryosphere.net/8/25/2014/tc-8-25-2014.pdf https://doaj.org/article/01426c56772145ce884c3556e23684ac |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/tc-8-25-2014 |
container_title |
The Cryosphere |
container_volume |
8 |
container_issue |
1 |
container_start_page |
25 |
op_container_end_page |
40 |
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1766274690096037888 |