Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys
We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88 ∘ S, an elevat...
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Copernicus Publications
2020
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Online Access: | https://doi.org/10.5194/tc-14-3287-2020 https://doaj.org/article/bc397f91697e4b768dcc92818e0b5de6 |
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ftdoajarticles:oai:doaj.org/article:bc397f91697e4b768dcc92818e0b5de6 2023-05-15T18:32:28+02:00 Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys M. Studinger B. C. Medley K. M. Brunt K. A. Casey N. T. Kurtz S. S. Manizade T. A. Neumann T. B. Overly 2020-10-01T00:00:00Z https://doi.org/10.5194/tc-14-3287-2020 https://doaj.org/article/bc397f91697e4b768dcc92818e0b5de6 EN eng Copernicus Publications https://tc.copernicus.org/articles/14/3287/2020/tc-14-3287-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-3287-2020 1994-0416 1994-0424 https://doaj.org/article/bc397f91697e4b768dcc92818e0b5de6 The Cryosphere, Vol 14, Pp 3287-3308 (2020) Environmental sciences GE1-350 Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.5194/tc-14-3287-2020 2022-12-31T03:24:29Z We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88 ∘ S, an elevation bias validation site for ICESat-2 and potential validation site for CryoSat-2. We find significant small-scale variability ( <10 km) in snow accumulation based on the snow radar subsurface stratigraphy, indicating areas of strong wind redistribution are prevalent at 88 ∘ S. In general, highs in snow accumulation rate correspond with topographic lows, resulting in a negative correlation coefficient of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><msup><mi>r</mi><mn mathvariant="normal">2</mn></msup><mo>=</mo><mo>-</mo><mn mathvariant="normal">0.32</mn></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="54pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="5ed32971497199b4f64d23960fca493d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3287-2020-ie00001.svg" width="54pt" height="14pt" src="tc-14-3287-2020-ie00001.png"/></svg:svg> between accumulation rate and MSWD (mean slope in the mean wind direction). This relationship is strongest in areas where the dominant wind direction is parallel to the survey profile, which is expected as the geophysical surveys only capture a two-dimensional cross section of snow redistribution. Variability in snow accumulation appears to correlate with variability in MSWD. The correlation coefficient between the standard deviations of accumulation rate and MSWD is r 2 =0.48 , indicating a stronger link between the standard deviations than the actual parameters. Our analysis shows that there is no simple relationship between surface slope, wind ... Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 14 10 3287 3308 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
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Environmental sciences GE1-350 Geology QE1-996.5 M. Studinger B. C. Medley K. M. Brunt K. A. Casey N. T. Kurtz S. S. Manizade T. A. Neumann T. B. Overly Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88 ∘ S, an elevation bias validation site for ICESat-2 and potential validation site for CryoSat-2. We find significant small-scale variability ( <10 km) in snow accumulation based on the snow radar subsurface stratigraphy, indicating areas of strong wind redistribution are prevalent at 88 ∘ S. In general, highs in snow accumulation rate correspond with topographic lows, resulting in a negative correlation coefficient of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5" display="inline" overflow="scroll" dspmath="mathml"><mrow><msup><mi>r</mi><mn mathvariant="normal">2</mn></msup><mo>=</mo><mo>-</mo><mn mathvariant="normal">0.32</mn></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="54pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="5ed32971497199b4f64d23960fca493d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-3287-2020-ie00001.svg" width="54pt" height="14pt" src="tc-14-3287-2020-ie00001.png"/></svg:svg> between accumulation rate and MSWD (mean slope in the mean wind direction). This relationship is strongest in areas where the dominant wind direction is parallel to the survey profile, which is expected as the geophysical surveys only capture a two-dimensional cross section of snow redistribution. Variability in snow accumulation appears to correlate with variability in MSWD. The correlation coefficient between the standard deviations of accumulation rate and MSWD is r 2 =0.48 , indicating a stronger link between the standard deviations than the actual parameters. Our analysis shows that there is no simple relationship between surface slope, wind ... |
format |
Article in Journal/Newspaper |
author |
M. Studinger B. C. Medley K. M. Brunt K. A. Casey N. T. Kurtz S. S. Manizade T. A. Neumann T. B. Overly |
author_facet |
M. Studinger B. C. Medley K. M. Brunt K. A. Casey N. T. Kurtz S. S. Manizade T. A. Neumann T. B. Overly |
author_sort |
M. Studinger |
title |
Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys |
title_short |
Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys |
title_full |
Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys |
title_fullStr |
Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys |
title_full_unstemmed |
Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys |
title_sort |
temporal and spatial variability in surface roughness and accumulation rate around 88° s from repeat airborne geophysical surveys |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/tc-14-3287-2020 https://doaj.org/article/bc397f91697e4b768dcc92818e0b5de6 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 14, Pp 3287-3308 (2020) |
op_relation |
https://tc.copernicus.org/articles/14/3287/2020/tc-14-3287-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-3287-2020 1994-0416 1994-0424 https://doaj.org/article/bc397f91697e4b768dcc92818e0b5de6 |
op_doi |
https://doi.org/10.5194/tc-14-3287-2020 |
container_title |
The Cryosphere |
container_volume |
14 |
container_issue |
10 |
container_start_page |
3287 |
op_container_end_page |
3308 |
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1766216582238830592 |