Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses

The goals of this project are to model the microwave properties of snow over sea ice through High Performance Computing (HPC) three dimensional (3D) simulations of solutions of Maxwell equations and 3D simulations of snow microstructure. To apply the 3D simulation results to the analysis of active a...

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Main Author: Leung Tsang
Format: Dataset
Language:unknown
Published: Arctic Data Center 2019
Subjects:
Online Access:https://doi.org/10.18739/A2J96094G
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record_format openpolar
spelling dataone:doi:10.18739/A2J96094G 2024-10-03T18:46:25+00:00 Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses Leung Tsang Model runs were conducted independent of place. The model was developed at the University of Michigan ENVELOPE(-83.71427,-83.71427,42.29234,42.29234) BEGINDATE: 2015-09-01T00:00:00Z ENDDATE: 2019-09-01T00:00:00Z 2019-01-01T00:00:00Z https://doi.org/10.18739/A2J96094G unknown Arctic Data Center Dataset 2019 dataone:urn:node:ARCTIC https://doi.org/10.18739/A2J96094G 2024-10-03T18:15:14Z The goals of this project are to model the microwave properties of snow over sea ice through High Performance Computing (HPC) three dimensional (3D) simulations of solutions of Maxwell equations and 3D simulations of snow microstructure. To apply the 3D simulation results to the analysis of active and passive microwave remote sensing data of snow over sea ice; and to design future microwave remote sensing measurements including signals of opportunities. During the project period, we have developed techniques for 3D full wave numerical solutions of Maxwell equations (NMM3D) for snow over sea ice. We have applied the 3D simulation results to the analysis of active and passive microwave remote sensing data of snow and sea ice. We have generated Lookup Tables (LUTs) that relate different properties of snow and sea ice to brightness temperature (Tb) and backscatter responses with NMM3D. For passive remote sensing, we have generated LUTs of Tb at Ku (17 gigahertz) and Ka (37 gigahertz) band for retrieval of Snow Depth (SD) over sea ice with Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E/2) observations. For active remote sensing, LUTs of snow over sea ice at Ku and Ka band have been built. We also have built backscatter LUT for sea ice at L (1-2 gigahertz), C (4-8 gigahertz) and X (8-12 gigahertz) bands. In the 3D full wave simulations, the scattering matrix of the snowpack is directly obtained including both amplitude and phase. Both bistatic scattering coefficients and brightness temperatures (Tbs) of the snowpack are computed. Simulation results demonstrate backscattering enhancement effects and coherent layer effects which are missed in radiative transfer theory that only describes the incoherent wave interactions. We also found that the roughness of the snow/ice interface weakens the coherent layer effects. Our simulations also demonstrated that both Tb and backscattering are highly related to roughness of the snow/ice interface and the ice/water interface. The snow/ice interface roughness increases Tbs and backscatter more at high frequency and for thick ice, while the ice/water interface roughness increases Tbs and backscatter more at low frequency and for thin ice. Results from the numerical simulations were used to characterize signatures of microwave signals at different bands. This dataset contains lookup tables relating properties of snow and sea ice to brightness temperature and backscatter responses. Dataset Sea ice Arctic Data Center (via DataONE) ENVELOPE(-83.71427,-83.71427,42.29234,42.29234)
institution Open Polar
collection Arctic Data Center (via DataONE)
op_collection_id dataone:urn:node:ARCTIC
language unknown
description The goals of this project are to model the microwave properties of snow over sea ice through High Performance Computing (HPC) three dimensional (3D) simulations of solutions of Maxwell equations and 3D simulations of snow microstructure. To apply the 3D simulation results to the analysis of active and passive microwave remote sensing data of snow over sea ice; and to design future microwave remote sensing measurements including signals of opportunities. During the project period, we have developed techniques for 3D full wave numerical solutions of Maxwell equations (NMM3D) for snow over sea ice. We have applied the 3D simulation results to the analysis of active and passive microwave remote sensing data of snow and sea ice. We have generated Lookup Tables (LUTs) that relate different properties of snow and sea ice to brightness temperature (Tb) and backscatter responses with NMM3D. For passive remote sensing, we have generated LUTs of Tb at Ku (17 gigahertz) and Ka (37 gigahertz) band for retrieval of Snow Depth (SD) over sea ice with Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E/2) observations. For active remote sensing, LUTs of snow over sea ice at Ku and Ka band have been built. We also have built backscatter LUT for sea ice at L (1-2 gigahertz), C (4-8 gigahertz) and X (8-12 gigahertz) bands. In the 3D full wave simulations, the scattering matrix of the snowpack is directly obtained including both amplitude and phase. Both bistatic scattering coefficients and brightness temperatures (Tbs) of the snowpack are computed. Simulation results demonstrate backscattering enhancement effects and coherent layer effects which are missed in radiative transfer theory that only describes the incoherent wave interactions. We also found that the roughness of the snow/ice interface weakens the coherent layer effects. Our simulations also demonstrated that both Tb and backscattering are highly related to roughness of the snow/ice interface and the ice/water interface. The snow/ice interface roughness increases Tbs and backscatter more at high frequency and for thick ice, while the ice/water interface roughness increases Tbs and backscatter more at low frequency and for thin ice. Results from the numerical simulations were used to characterize signatures of microwave signals at different bands. This dataset contains lookup tables relating properties of snow and sea ice to brightness temperature and backscatter responses.
format Dataset
author Leung Tsang
spellingShingle Leung Tsang
Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
author_facet Leung Tsang
author_sort Leung Tsang
title Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
title_short Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
title_full Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
title_fullStr Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
title_full_unstemmed Lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
title_sort lookup tables relating different properties of snow and sea ice to brightness temperature and backscatter responses
publisher Arctic Data Center
publishDate 2019
url https://doi.org/10.18739/A2J96094G
op_coverage Model runs were conducted independent of place. The model was developed at the University of Michigan
ENVELOPE(-83.71427,-83.71427,42.29234,42.29234)
BEGINDATE: 2015-09-01T00:00:00Z ENDDATE: 2019-09-01T00:00:00Z
long_lat ENVELOPE(-83.71427,-83.71427,42.29234,42.29234)
genre Sea ice
genre_facet Sea ice
op_doi https://doi.org/10.18739/A2J96094G
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