A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data
Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring melt...
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Copernicus Publications
2020
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ftdoajarticles:oai:doaj.org/article:49d417fc272b4f61b4268a6bba87e6a0 2023-05-15T13:11:41+02:00 A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data M. König N. Oppelt 2020-08-01T00:00:00Z https://doi.org/10.5194/tc-14-2567-2020 https://doaj.org/article/49d417fc272b4f61b4268a6bba87e6a0 EN eng Copernicus Publications https://tc.copernicus.org/articles/14/2567/2020/tc-14-2567-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-2567-2020 1994-0416 1994-0424 https://doaj.org/article/49d417fc272b4f61b4268a6bba87e6a0 The Cryosphere, Vol 14, Pp 2567-2579 (2020) Environmental sciences GE1-350 Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.5194/tc-14-2567-2020 2022-12-31T11:39:08Z Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring melt pond deepening in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of meltwater on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way meltwater changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm as a function of depth that is widely independent from the bottom albedo and accounts for the influence of varying solar zenith angles. We validated the model using 49 in situ melt pond spectra and corresponding depths from shallow ponds on dark and bright ice. Retrieved pond depths are accurate (root mean square error, RMSE=2.81 cm n RMSE=16 %) and highly correlated with in situ measurements ( r =0.89 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi>p</mi><mo>=</mo><mn mathvariant="normal">4.34</mn><mo>×</mo><msup><mn mathvariant="normal">10</mn><mrow><mo>-</mo><mn mathvariant="normal">17</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="81pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="e889bc451f3575818ff1fb9c7014edd0"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-2567-2020-ie00001.svg" width="81pt" height="15pt" src="tc-14-2567-2020-ie00001.png"/></svg:svg> ). The model further explains a large portion of the variation in pond depth ( R 2 =0.74 ). Our results ... Article in Journal/Newspaper albedo Arctic Sea ice The Cryosphere Directory of Open Access Journals: DOAJ Articles Arctic The Cryosphere 14 8 2567 2579 |
institution |
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 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 M. König N. Oppelt A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring melt pond deepening in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of meltwater on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way meltwater changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm as a function of depth that is widely independent from the bottom albedo and accounts for the influence of varying solar zenith angles. We validated the model using 49 in situ melt pond spectra and corresponding depths from shallow ponds on dark and bright ice. Retrieved pond depths are accurate (root mean square error, RMSE=2.81 cm n RMSE=16 %) and highly correlated with in situ measurements ( r =0.89 <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi>p</mi><mo>=</mo><mn mathvariant="normal">4.34</mn><mo>×</mo><msup><mn mathvariant="normal">10</mn><mrow><mo>-</mo><mn mathvariant="normal">17</mn></mrow></msup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="81pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="e889bc451f3575818ff1fb9c7014edd0"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-14-2567-2020-ie00001.svg" width="81pt" height="15pt" src="tc-14-2567-2020-ie00001.png"/></svg:svg> ). The model further explains a large portion of the variation in pond depth ( R 2 =0.74 ). Our results ... |
format |
Article in Journal/Newspaper |
author |
M. König N. Oppelt |
author_facet |
M. König N. Oppelt |
author_sort |
M. König |
title |
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data |
title_short |
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data |
title_full |
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data |
title_fullStr |
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data |
title_full_unstemmed |
A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data |
title_sort |
linear model to derive melt pond depth on arctic sea ice from hyperspectral data |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/tc-14-2567-2020 https://doaj.org/article/49d417fc272b4f61b4268a6bba87e6a0 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
albedo Arctic Sea ice The Cryosphere |
genre_facet |
albedo Arctic Sea ice The Cryosphere |
op_source |
The Cryosphere, Vol 14, Pp 2567-2579 (2020) |
op_relation |
https://tc.copernicus.org/articles/14/2567/2020/tc-14-2567-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-2567-2020 1994-0416 1994-0424 https://doaj.org/article/49d417fc272b4f61b4268a6bba87e6a0 |
op_doi |
https://doi.org/10.5194/tc-14-2567-2020 |
container_title |
The Cryosphere |
container_volume |
14 |
container_issue |
8 |
container_start_page |
2567 |
op_container_end_page |
2579 |
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1766248479281119232 |