Large-scale inverse ku-band backscatter modeling of sea ice

Abstract—Polar sea ice characteristics provide important inputs to models of several geophysical processes. Microwave scatterometers are ideal for monitoring these regions due to their sensitivity to ice properties and insensitivity to atmospheric distortions. Many forward electromagnetic scattering...

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Main Authors: Quinn P. Remund, David G. Long, Senior Member
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.9511
http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.391.9511 2023-05-15T13:11:56+02:00 Large-scale inverse ku-band backscatter modeling of sea ice Quinn P. Remund David G. Long Senior Member The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.9511 http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.9511 http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf models sea ice text ftciteseerx 2016-01-08T02:17:49Z Abstract—Polar sea ice characteristics provide important inputs to models of several geophysical processes. Microwave scatterometers are ideal for monitoring these regions due to their sensitivity to ice properties and insensitivity to atmospheric distortions. Many forward electromagnetic scattering models have been proposed to predict the normalized radar cross section ( ) from sea ice characteristics. These models are based on very small scale ice features and generally assume that the region of interest is spatially homogeneous. Unfortunately, spaceborne scatterometer footprints are very large (5–50 km) and usually contain very heterogeneous mixtures of sea ice surface parameters. In this paper, we use scatterometer data in a large-scale inverse modeling experiment. Given the limited data resolution, we adopt a simple geometric optics forward-scattering model to analyze surface and volume scattering contributions to observed Ku-band signatures. A model inversion technique based on recursive optimization of an objective function is developed. The result is a least squares estimate of three surface parameters: the power reflection coefficient at nadir, the rms surface slope, and the volume scattering albedo. Simulations demonstrate the performance of the method in the presence of noise. The inverse model is implemented using Ku-band image reconstructed data collected by the National Aeronautics and Space Administration scatterometer. The results are used to analyze and interpret phenomena occurring in the Antarctic and the Arctic. Index Terms—Inverse modeling, National Aeronautics and Space Administration (NASA) Scatterometer (NSCAT), scattering Text albedo Antarc* Antarctic Arctic Sea ice Unknown Antarctic Arctic The Antarctic
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
topic models
sea ice
spellingShingle models
sea ice
Quinn P. Remund
David G. Long
Senior Member
Large-scale inverse ku-band backscatter modeling of sea ice
topic_facet models
sea ice
description Abstract—Polar sea ice characteristics provide important inputs to models of several geophysical processes. Microwave scatterometers are ideal for monitoring these regions due to their sensitivity to ice properties and insensitivity to atmospheric distortions. Many forward electromagnetic scattering models have been proposed to predict the normalized radar cross section ( ) from sea ice characteristics. These models are based on very small scale ice features and generally assume that the region of interest is spatially homogeneous. Unfortunately, spaceborne scatterometer footprints are very large (5–50 km) and usually contain very heterogeneous mixtures of sea ice surface parameters. In this paper, we use scatterometer data in a large-scale inverse modeling experiment. Given the limited data resolution, we adopt a simple geometric optics forward-scattering model to analyze surface and volume scattering contributions to observed Ku-band signatures. A model inversion technique based on recursive optimization of an objective function is developed. The result is a least squares estimate of three surface parameters: the power reflection coefficient at nadir, the rms surface slope, and the volume scattering albedo. Simulations demonstrate the performance of the method in the presence of noise. The inverse model is implemented using Ku-band image reconstructed data collected by the National Aeronautics and Space Administration scatterometer. The results are used to analyze and interpret phenomena occurring in the Antarctic and the Arctic. Index Terms—Inverse modeling, National Aeronautics and Space Administration (NASA) Scatterometer (NSCAT), scattering
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Quinn P. Remund
David G. Long
Senior Member
author_facet Quinn P. Remund
David G. Long
Senior Member
author_sort Quinn P. Remund
title Large-scale inverse ku-band backscatter modeling of sea ice
title_short Large-scale inverse ku-band backscatter modeling of sea ice
title_full Large-scale inverse ku-band backscatter modeling of sea ice
title_fullStr Large-scale inverse ku-band backscatter modeling of sea ice
title_full_unstemmed Large-scale inverse ku-band backscatter modeling of sea ice
title_sort large-scale inverse ku-band backscatter modeling of sea ice
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.9511
http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf
geographic Antarctic
Arctic
The Antarctic
geographic_facet Antarctic
Arctic
The Antarctic
genre albedo
Antarc*
Antarctic
Arctic
Sea ice
genre_facet albedo
Antarc*
Antarctic
Arctic
Sea ice
op_source http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.391.9511
http://www.mers.byu.edu/long/papers/TGARS2003Remund.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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