Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica
The firn temperature is a crucial parameter for understanding firn densification processes of the Antarctic Ice Sheet (AIS). Simulations with firn densification models (FDM) can be conceptualized as a function that relies on forcing data, comprising temperature and surface mass balance, together wit...
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ftcopernicus:oai:publications.copernicus.org:isprs-archives120164 2024-06-23T07:47:01+00:00 Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica Wang, Xiaofeng An, Lu Langen, Peter L. Li, Rongxing 2024-05-11 application/pdf https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 https://isprs-archives.copernicus.org/articles/XLVIII-1-2024/691/2024/ eng eng doi:10.5194/isprs-archives-XLVIII-1-2024-691-2024 https://isprs-archives.copernicus.org/articles/XLVIII-1-2024/691/2024/ eISSN: 2194-9034 Text 2024 ftcopernicus https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 2024-06-13T01:24:45Z The firn temperature is a crucial parameter for understanding firn densification processes of the Antarctic Ice Sheet (AIS). Simulations with firn densification models (FDM) can be conceptualized as a function that relies on forcing data, comprising temperature and surface mass balance, together with tuning parameters determined based on measured depth-density profiles from different locations. The simulated firn temperature is obtained in the firn densification models by solving the one-dimensional heat conduction equation. Microwave satellite data on brightness temperature at different frequencies can also provide remote sensing monitoring of firn temperature variations across the AIS (i.e., the L-band up to 1500 meters). The firn temperature can be estimated by the microwave emission model and the regression method, but these two methods need more observations of temperature profiles for correction and validation. Therefore, we compiled a dataset with temperature profiles and temperature observations with depth around 10 meters. In this work, two methods were used to simulate/retrieve firn temperature across the Antarctic ice sheet. One method estimated the temperature profiles by solving the one-dimensional heat conduction equation driven by reanalyses and regional climate models, which are used in the simulation of FDMs. The other one established a relationship between the multi-frequency brightness temperature data from microwave remote sensing satellites and the firn temperature. Text Antarc* Antarctic Antarctica Ice Sheet Copernicus Publications: E-Journals Antarctic The Antarctic The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1-2024 691 696 |
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Copernicus Publications: E-Journals |
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English |
description |
The firn temperature is a crucial parameter for understanding firn densification processes of the Antarctic Ice Sheet (AIS). Simulations with firn densification models (FDM) can be conceptualized as a function that relies on forcing data, comprising temperature and surface mass balance, together with tuning parameters determined based on measured depth-density profiles from different locations. The simulated firn temperature is obtained in the firn densification models by solving the one-dimensional heat conduction equation. Microwave satellite data on brightness temperature at different frequencies can also provide remote sensing monitoring of firn temperature variations across the AIS (i.e., the L-band up to 1500 meters). The firn temperature can be estimated by the microwave emission model and the regression method, but these two methods need more observations of temperature profiles for correction and validation. Therefore, we compiled a dataset with temperature profiles and temperature observations with depth around 10 meters. In this work, two methods were used to simulate/retrieve firn temperature across the Antarctic ice sheet. One method estimated the temperature profiles by solving the one-dimensional heat conduction equation driven by reanalyses and regional climate models, which are used in the simulation of FDMs. The other one established a relationship between the multi-frequency brightness temperature data from microwave remote sensing satellites and the firn temperature. |
format |
Text |
author |
Wang, Xiaofeng An, Lu Langen, Peter L. Li, Rongxing |
spellingShingle |
Wang, Xiaofeng An, Lu Langen, Peter L. Li, Rongxing Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica |
author_facet |
Wang, Xiaofeng An, Lu Langen, Peter L. Li, Rongxing |
author_sort |
Wang, Xiaofeng |
title |
Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica |
title_short |
Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica |
title_full |
Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica |
title_fullStr |
Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica |
title_full_unstemmed |
Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica |
title_sort |
comparing firn temperature profile retrieval based on the firn densification model and microwave data over the antarctica |
publishDate |
2024 |
url |
https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 https://isprs-archives.copernicus.org/articles/XLVIII-1-2024/691/2024/ |
geographic |
Antarctic The Antarctic |
geographic_facet |
Antarctic The Antarctic |
genre |
Antarc* Antarctic Antarctica Ice Sheet |
genre_facet |
Antarc* Antarctic Antarctica Ice Sheet |
op_source |
eISSN: 2194-9034 |
op_relation |
doi:10.5194/isprs-archives-XLVIII-1-2024-691-2024 https://isprs-archives.copernicus.org/articles/XLVIII-1-2024/691/2024/ |
op_doi |
https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 |
container_title |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
container_volume |
XLVIII-1-2024 |
container_start_page |
691 |
op_container_end_page |
696 |
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1802650230614654976 |