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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ftuniaarhuspubl:oai:pure.atira.dk:publications/37764fc1-0017-4ba6-a20c-f50de6413b54 2024-06-23T07:47:21+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 https://pure.au.dk/portal/en/publications/37764fc1-0017-4ba6-a20c-f50de6413b54 https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 eng eng https://pure.au.dk/portal/en/publications/37764fc1-0017-4ba6-a20c-f50de6413b54 info:eu-repo/semantics/openAccess Wang , X , An , L , Langen , P L & Li , R 2024 , ' Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica ' , International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives , vol. 48 , no. 1 , pp. 691-696 . https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 Antarctic brightness temperature evaluation firn densification model firn temperature profiles contributionToPeriodical 2024 ftuniaarhuspubl https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 2024-06-11T14:22:51Z 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. Article in Journal/Newspaper Antarc* Antarctic Antarctica Ice Sheet Aarhus University: Research Antarctic The Antarctic The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1-2024 691 696 |
institution |
Open Polar |
collection |
Aarhus University: Research |
op_collection_id |
ftuniaarhuspubl |
language |
English |
topic |
Antarctic brightness temperature evaluation firn densification model firn temperature profiles |
spellingShingle |
Antarctic brightness temperature evaluation firn densification model firn temperature profiles 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 |
topic_facet |
Antarctic brightness temperature evaluation firn densification model firn temperature profiles |
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 |
Article in Journal/Newspaper |
author |
Wang, Xiaofeng An, Lu Langen, Peter L. Li, Rongxing |
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://pure.au.dk/portal/en/publications/37764fc1-0017-4ba6-a20c-f50de6413b54 https://doi.org/10.5194/isprs-archives-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 |
Wang , X , An , L , Langen , P L & Li , R 2024 , ' Comparing firn temperature profile retrieval based on the firn densification model and microwave data over the Antarctica ' , International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives , vol. 48 , no. 1 , pp. 691-696 . https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024 |
op_relation |
https://pure.au.dk/portal/en/publications/37764fc1-0017-4ba6-a20c-f50de6413b54 |
op_rights |
info:eu-repo/semantics/openAccess |
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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1802651444153679872 |