Data

2019-20 Honours project - Environmental Drivers of Antarctic Landfast Sea Ice Formation and Breakout

University of Tasmania, Australia
Wang, Chenhui
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://metadata.imas.utas.edu.au/geonetwork/srv/eng/search?uuid=49add25b-c9f7-4e6d-9407-376cbea45786&rft.title=2019-20 Honours project - Environmental Drivers of Antarctic Landfast Sea Ice Formation and Breakout&rft.identifier=http://metadata.imas.utas.edu.au/geonetwork/srv/eng/search?uuid=49add25b-c9f7-4e6d-9407-376cbea45786&rft.description=Antarctic Landfast sea ice (fast ice) is important climatologically, biologically and for logistics for short time-scale anomalies. Until recently, there hasn’t been an accurate, high-resolution fast ice extent dataset which can support an analysis on drivers of fast ice and most studies only investigate fast ice on limited regions of Antarctica in a limited time scale. There is a need to extend the spatial and temporal studying coverage to provide detailed information on the Antarctic coast over a longer period. This is the first detailed analysis to identify and quantify correlation between the environmental anomaly and fast ice anomaly mainly in the east Antarctic coast. By examining regional/local fast ice extent in in east Antarctic coast in the context of the broader and/or remote-teleconnected atmospheric circulation/properties using spatial correlation techniques, a strong correlation between NINO3 region and Lützow-Holm Bay fast ice and similar and significant correlation of regional scale factors from Lützow-Holm Bay to Mawson Coast mainly are found. The results of this thesis suggest that the pack ice, atmospheric factors and oceanic factors are important for interpreting fast ice anomalies. To identify and quantify correlation between the pack ice, temperature at 2m, wind at 10m, snow fall anomaly, sea surface temperature anomaly, ocean heat content anomaly and fast ice anomaly, backward multiple linear regression is conducted to demonstrate some predictive fast ice driver information by quantifying the correlation between different drivers and fast ice anomaly. The multiple linear regression also suggests that oceanic influences including pack ice are generally more important than atmospheric influences. Future experiments could be conducted to interpret fast ice anomalies in the context of the ocean mainly.Maintenance and Update Frequency: notPlannedStatement: Data is collected from ERA5 and analysed by IDL programming language.&rft.creator=Wang, Chenhui &rft.date=2020&rft.coverage=westlimit=0; southlimit=-73; eastlimit=90; northlimit=-54.999999&rft.coverage=westlimit=0; southlimit=-73; eastlimit=90; northlimit=-54.999999&rft_rights=The data described in this record are the intellectual property of the University of Tasmania through the Institute for Marine and Antarctic Studies.&rft_rights= http://creativecommons.org/licenses/by/4.0/&rft_rights=http://i.creativecommons.org/l/by/4.0/88x31.png&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Graphic&rft_rights=Creative Commons Attribution 4.0 International License&rft_rights=http://creativecommons.org/international/&rft_rights=WWW:LINK-1.0-http--related&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Text&rft_rights=The citation in a list of references is: citation author name/s (year metadata published), metadata title. Citation author organisation/s. File identifier and Data accessed at (add http link).&rft_rights=Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0&rft_subject=oceans&rft_subject=Temperature&rft_subject=Concentration&rft_subject=Wind Speed and Direction&rft_subject=Heat Content&rft_subject=Precipitation&rft_subject=Fast ice&rft_subject=SEA ICE CONCENTRATION&rft_subject=EARTH SCIENCE&rft_subject=CLIMATE INDICATORS&rft_subject=CRYOSPHERIC INDICATORS&rft_subject=SEA ICE&rft_subject=CRYOSPHERE&rft_subject=ICE GROWTH/MELT&rft_subject=OCEANS&rft_subject=Palaeoclimatology&rft_subject=EARTH SCIENCES&rft_subject=PHYSICAL GEOGRAPHY AND ENVIRONMENTAL GEOSCIENCE&rft_subject=Climatology (excl. Climate Change Processes)&rft_subject=ATMOSPHERIC SCIENCES&rft_subject=Glaciology&rft.type=dataset&rft.language=English Access the data
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The data described in this record are the intellectual property of the University of Tasmania through the Institute for Marine and Antarctic Studies.

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Brief description

Antarctic Landfast sea ice (fast ice) is important climatologically, biologically and for logistics for short time-scale anomalies. Until recently, there hasn’t been an accurate, high-resolution fast ice extent dataset which can support an analysis on drivers of fast ice and most studies only investigate fast ice on limited regions of Antarctica in a limited time scale. There is a need to extend the spatial and temporal studying coverage to provide detailed information on the Antarctic coast over a longer period. This is the first detailed analysis to identify and quantify correlation between the environmental anomaly and fast ice anomaly mainly in the east Antarctic coast. By examining regional/local fast ice extent in in east Antarctic coast in the context of the broader and/or remote-teleconnected atmospheric circulation/properties using spatial correlation techniques, a strong correlation between NINO3 region and Lützow-Holm Bay fast ice and similar and significant correlation of regional scale factors from Lützow-Holm Bay to Mawson Coast mainly are found. The results of this thesis suggest that the pack ice, atmospheric factors and oceanic factors are important for interpreting fast ice anomalies. To identify and quantify correlation between the pack ice, temperature at 2m, wind at 10m, snow fall anomaly, sea surface temperature anomaly, ocean heat content anomaly and fast ice anomaly, backward multiple linear regression is conducted to demonstrate some predictive fast ice driver information by quantifying the correlation between different drivers and fast ice anomaly. The multiple linear regression also suggests that oceanic influences including pack ice are generally more important than atmospheric influences. Future experiments could be conducted to interpret fast ice anomalies in the context of the ocean mainly.

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Maintenance and Update Frequency: notPlanned
Statement: Data is collected from ERA5 and analysed by IDL programming language.

Notes

Credit
IMAS Honours Student Program 2019-2020

Created: 2020-08-31

Data time period: 2019-07-17 to 2020-09-02

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90,-55 90,-73 0,-73 0,-55 90,-55

45,-63.9999995

text: westlimit=0; southlimit=-73; eastlimit=90; northlimit=-54.999999

Subjects
Atmospheric Sciences | CLIMATE INDICATORS | CRYOSPHERE | CRYOSPHERIC INDICATORS | Climatology (Excl. Climate Change Processes) | Concentration | EARTH SCIENCE | Earth Sciences | Fast ice | Glaciology | Heat Content | ICE GROWTH/MELT | OCEANS | Physical Geography and Environmental Geoscience | Palaeoclimatology | Precipitation | SEA ICE | SEA ICE CONCENTRATION | Temperature | Wind Speed and Direction | oceans |

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(DATA ACCESS - fast ice drivers ALL FILES [.zip direct downoad])

uri : https://data.imas.utas.edu.au/attachments/49add25b-c9f7-4e6d-9407-376cbea45786/fast_ice_drivers_all.zip

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  • global : 49add25b-c9f7-4e6d-9407-376cbea45786
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