Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)

[Data description] Monthly total freeboard (Ft),snow depth (hs), and snow depth uncertainty over Arctic sea ice data for January-February-March months of the 2003-2020 period produced by Lee and Shi et al. (2021, manuscript under review) are provided. Both variables are derived from satellite passiv...

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Main Authors: Lee, Sang-Moo, Shi, Hoyeon, Sohn, Byung-Ju, Gasiewski, Albin. J., Meier, Walter N., Dybkjær, Gorm
Format: Other/Unknown Material
Language:English
Published: Zenodo 2021
Subjects:
Online Access:https://doi.org/10.5281/zenodo.5081765
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record_format openpolar
spelling ftzenodo:oai:zenodo.org:5081765 2024-09-15T18:19:06+00:00 Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020) Lee, Sang-Moo Shi, Hoyeon Sohn, Byung-Ju Gasiewski, Albin. J. Meier, Walter N. Dybkjær, Gorm 2021-03-28 https://doi.org/10.5281/zenodo.5081765 eng eng Zenodo https://doi.org/10.5281/zenodo.4642221 https://doi.org/10.5281/zenodo.5081765 oai:zenodo.org:5081765 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode Snow on sea ice total freeboard Sea ice Arctic climate Satellite observations info:eu-repo/semantics/other 2021 ftzenodo https://doi.org/10.5281/zenodo.508176510.5281/zenodo.4642221 2024-07-26T07:24:47Z [Data description] Monthly total freeboard (Ft),snow depth (hs), and snow depth uncertainty over Arctic sea ice data for January-February-March months of the 2003-2020 period produced by Lee and Shi et al. (2021, manuscript under review) are provided. Both variables are derived from satellite passive infrared and microwave measurements: Total freeboard was obtained from AMSR-E&2 measurements and snow depth was estimated from the AMSR and AVHRR measurements. The uploaded file titled "monthly averaged total freeboard and snow depth (JFM 2003-2020).zip" contains two directories: one for total freeboard and the other for snow depth. Naming convention is "variable_yyyymm.bin" and data format is 32-bit floating point array in shape of 304 x 448 (25 km polar stereographic grid). Here we provide an example Python code to read monthly snow depth of January 2003 using numpy. import numpy as np hs = np.fromfile('hs_200301.bin', dtype=np.float32).reshape(448,304) Geocoordinate tools for the 25 km polar stereographic grid are available at NSIDC website (https://nsidc.org/data/polar-stereo/tools_geo_pixel.html) [Abbreviations] AMSR: Advanced Microwave Scanning Radiometer AVHRR: Advanced Very High Resolution Radiometer NSIDC: National Snow and Ice Data Center Update for version 3: snow depth uncertainty is now included. Other/Unknown Material National Snow and Ice Data Center Sea ice Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
topic Snow on sea ice
total freeboard
Sea ice
Arctic climate
Satellite observations
spellingShingle Snow on sea ice
total freeboard
Sea ice
Arctic climate
Satellite observations
Lee, Sang-Moo
Shi, Hoyeon
Sohn, Byung-Ju
Gasiewski, Albin. J.
Meier, Walter N.
Dybkjær, Gorm
Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)
topic_facet Snow on sea ice
total freeboard
Sea ice
Arctic climate
Satellite observations
description [Data description] Monthly total freeboard (Ft),snow depth (hs), and snow depth uncertainty over Arctic sea ice data for January-February-March months of the 2003-2020 period produced by Lee and Shi et al. (2021, manuscript under review) are provided. Both variables are derived from satellite passive infrared and microwave measurements: Total freeboard was obtained from AMSR-E&2 measurements and snow depth was estimated from the AMSR and AVHRR measurements. The uploaded file titled "monthly averaged total freeboard and snow depth (JFM 2003-2020).zip" contains two directories: one for total freeboard and the other for snow depth. Naming convention is "variable_yyyymm.bin" and data format is 32-bit floating point array in shape of 304 x 448 (25 km polar stereographic grid). Here we provide an example Python code to read monthly snow depth of January 2003 using numpy. import numpy as np hs = np.fromfile('hs_200301.bin', dtype=np.float32).reshape(448,304) Geocoordinate tools for the 25 km polar stereographic grid are available at NSIDC website (https://nsidc.org/data/polar-stereo/tools_geo_pixel.html) [Abbreviations] AMSR: Advanced Microwave Scanning Radiometer AVHRR: Advanced Very High Resolution Radiometer NSIDC: National Snow and Ice Data Center Update for version 3: snow depth uncertainty is now included.
format Other/Unknown Material
author Lee, Sang-Moo
Shi, Hoyeon
Sohn, Byung-Ju
Gasiewski, Albin. J.
Meier, Walter N.
Dybkjær, Gorm
author_facet Lee, Sang-Moo
Shi, Hoyeon
Sohn, Byung-Ju
Gasiewski, Albin. J.
Meier, Walter N.
Dybkjær, Gorm
author_sort Lee, Sang-Moo
title Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)
title_short Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)
title_full Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)
title_fullStr Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)
title_full_unstemmed Monthly total freeboard and snow depth over Arctic sea ice from AMSR-E&2 and AVHRR measurements (2003-2020)
title_sort monthly total freeboard and snow depth over arctic sea ice from amsr-e&2 and avhrr measurements (2003-2020)
publisher Zenodo
publishDate 2021
url https://doi.org/10.5281/zenodo.5081765
genre National Snow and Ice Data Center
Sea ice
genre_facet National Snow and Ice Data Center
Sea ice
op_relation https://doi.org/10.5281/zenodo.4642221
https://doi.org/10.5281/zenodo.5081765
oai:zenodo.org:5081765
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.508176510.5281/zenodo.4642221
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