FEASIBILITY OF ESTIMATING SNOW EMISSIVITY VIA ASSIMILATION OF MULTIFREQUENCY PASSIVE MICROWAVE DATA

Sayed M. Bateni; Mahdi Navari; Sujay Kumar; Essam Heggy

doi:10.1109/IGARSS47720.2021.9554893

FEASIBILITY OF ESTIMATING SNOW EMISSIVITY VIA ASSIMILATION OF MULTIFREQUENCY PASSIVE MICROWAVE DATA

Sayed M. Bateni, Mahdi Navari, Sujay Kumar, Essam Heggy

Research output: Contribution to conference › Paper › peer-review

Abstract

Prior studies have shown that models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Hence, in this study, we merged Common Land Model (CLM) and snow emission (MEMLS) models with multi-frequency passive microwave data within an EnBS scheme to estimate snow emissivity. Its feasibility was tested via a test where passive microwave (at 1.4, 18.7, 36.5, and 87 GHz) measurements at the point scale were individually and simultaneously assimilated to estimate snow emissivity. The contribution of each channel in estimating the true snow emissivity is examined at the local-scale observation site of the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA-CLPX) Field Campaign in Fall 2002-Winter 2003. All of the assimilated passive microwave measurements are found to contain complementary information for retrieving snow emissivity.

Original language	English
Pages	5582-5585
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9554893
Publication status	Published - 2021
Externally published	Yes
Event	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium Duration: 12 Jul 2021 → 16 Jul 2021

Conference

Conference	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Country/Territory	Belgium
City	Brussels
Period	12/07/21 → 16/07/21

Keywords

Ensemble Batch Smoother (EnBS)
Snow emissivity
data assimilation
passive microwave data

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10.1109/IGARSS47720.2021.9554893

Cite this

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title = "FEASIBILITY OF ESTIMATING SNOW EMISSIVITY VIA ASSIMILATION OF MULTIFREQUENCY PASSIVE MICROWAVE DATA",

abstract = "Prior studies have shown that models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Hence, in this study, we merged Common Land Model (CLM) and snow emission (MEMLS) models with multi-frequency passive microwave data within an EnBS scheme to estimate snow emissivity. Its feasibility was tested via a test where passive microwave (at 1.4, 18.7, 36.5, and 87 GHz) measurements at the point scale were individually and simultaneously assimilated to estimate snow emissivity. The contribution of each channel in estimating the true snow emissivity is examined at the local-scale observation site of the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA-CLPX) Field Campaign in Fall 2002-Winter 2003. All of the assimilated passive microwave measurements are found to contain complementary information for retrieving snow emissivity.",

keywords = "Ensemble Batch Smoother (EnBS), Snow emissivity, data assimilation, passive microwave data",

author = "Bateni, {Sayed M.} and Mahdi Navari and Sujay Kumar and Essam Heggy",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",

year = "2021",

doi = "10.1109/IGARSS47720.2021.9554893",

language = "English",

pages = "5582--5585",

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T1 - FEASIBILITY OF ESTIMATING SNOW EMISSIVITY VIA ASSIMILATION OF MULTIFREQUENCY PASSIVE MICROWAVE DATA

AU - Bateni, Sayed M.

AU - Navari, Mahdi

AU - Kumar, Sujay

AU - Heggy, Essam

PY - 2021

Y1 - 2021

N2 - Prior studies have shown that models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Hence, in this study, we merged Common Land Model (CLM) and snow emission (MEMLS) models with multi-frequency passive microwave data within an EnBS scheme to estimate snow emissivity. Its feasibility was tested via a test where passive microwave (at 1.4, 18.7, 36.5, and 87 GHz) measurements at the point scale were individually and simultaneously assimilated to estimate snow emissivity. The contribution of each channel in estimating the true snow emissivity is examined at the local-scale observation site of the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA-CLPX) Field Campaign in Fall 2002-Winter 2003. All of the assimilated passive microwave measurements are found to contain complementary information for retrieving snow emissivity.

AB - Prior studies have shown that models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Hence, in this study, we merged Common Land Model (CLM) and snow emission (MEMLS) models with multi-frequency passive microwave data within an EnBS scheme to estimate snow emissivity. Its feasibility was tested via a test where passive microwave (at 1.4, 18.7, 36.5, and 87 GHz) measurements at the point scale were individually and simultaneously assimilated to estimate snow emissivity. The contribution of each channel in estimating the true snow emissivity is examined at the local-scale observation site of the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA-CLPX) Field Campaign in Fall 2002-Winter 2003. All of the assimilated passive microwave measurements are found to contain complementary information for retrieving snow emissivity.

KW - Ensemble Batch Smoother (EnBS)

KW - Snow emissivity

KW - data assimilation

KW - passive microwave data

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U2 - 10.1109/IGARSS47720.2021.9554893

DO - 10.1109/IGARSS47720.2021.9554893

M3 - Paper

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EP - 5585

T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021

Y2 - 12 July 2021 through 16 July 2021

ER -

FEASIBILITY OF ESTIMATING SNOW EMISSIVITY VIA ASSIMILATION OF MULTIFREQUENCY PASSIVE MICROWAVE DATA

Abstract

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Keywords

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