Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic
We present experiences in using an integrated retrieval method for atmospheric and surface parameters in the Arctic using passive microwave data from the AMSR-E radiometer. The core of the method is a forward model which can ingest bulk data for seven geophysical parameters to reproduce the brightne...
Published in: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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ftdtupubl:oai:pure.atira.dk:publications/5eb83186-3860-458b-8731-538c3971d095 2023-08-27T04:06:42+02:00 Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic Scarlat, Raul Cristian Heygster, Georg Pedersen, Leif Toudal 2017 application/pdf https://orbit.dtu.dk/en/publications/5eb83186-3860-458b-8731-538c3971d095 https://doi.org/10.1109/JSTARS.2017.2739858 https://backend.orbit.dtu.dk/ws/files/190319119/jstars_2739858_pp.pdf eng eng info:eu-repo/semantics/openAccess Scarlat , R C , Heygster , G & Pedersen , L T 2017 , ' Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic ' , I E E E Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 10 , no. 9 , pp. 3934-3947 . https://doi.org/10.1109/JSTARS.2017.2739858 Arctic regions Atmospheric measurements Remote sensing Sea ice article 2017 ftdtupubl https://doi.org/10.1109/JSTARS.2017.2739858 2023-08-02T22:57:38Z We present experiences in using an integrated retrieval method for atmospheric and surface parameters in the Arctic using passive microwave data from the AMSR-E radiometer. The core of the method is a forward model which can ingest bulk data for seven geophysical parameters to reproduce the brightness temperatures observed by a passive microwave radiometer. The retrieval method inverts the forward model and produces ensembles of the seven parameters, wind speed, integrated water vapor, liquid water path, sea and ice temperature, sea ice concentration and multiyear ice fraction. The method is constrained using numerical weather prediction data in order to retrieve a set of geophysical parameters that best fit the measurements. A sensitivity study demonstrates the method is robust and that the solution it provides is not dependent on initialization conditions. The retrieval parameters have been compared with the Arctic Systems Reanalysis model data as well as columnar water vapor retrieved from satellite microwave sounders and the Remote Sensing Systems AMSR-E ocean retrieval product in order to determine the feasibility of using the same setup over pure surface with 100% and 0% sea ice cover, respectively. Sea ice concentration retrieval shows good skill for pure surface cases. Ice types retrieval is in good agreement with scatterometer backscatter data. Deficiencies have been identified in using the forward model over sea ice for retrieving atmospheric parameters, that are connected to the treatment of surface emissivity and surface temperature. The retrieval agrees well with legacy atmospheric retrieval products in open ocean areas. Article in Journal/Newspaper Arctic Arctic Sea ice Technical University of Denmark: DTU Orbit Arctic IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 9 3934 3947 |
institution |
Open Polar |
collection |
Technical University of Denmark: DTU Orbit |
op_collection_id |
ftdtupubl |
language |
English |
topic |
Arctic regions Atmospheric measurements Remote sensing Sea ice |
spellingShingle |
Arctic regions Atmospheric measurements Remote sensing Sea ice Scarlat, Raul Cristian Heygster, Georg Pedersen, Leif Toudal Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic |
topic_facet |
Arctic regions Atmospheric measurements Remote sensing Sea ice |
description |
We present experiences in using an integrated retrieval method for atmospheric and surface parameters in the Arctic using passive microwave data from the AMSR-E radiometer. The core of the method is a forward model which can ingest bulk data for seven geophysical parameters to reproduce the brightness temperatures observed by a passive microwave radiometer. The retrieval method inverts the forward model and produces ensembles of the seven parameters, wind speed, integrated water vapor, liquid water path, sea and ice temperature, sea ice concentration and multiyear ice fraction. The method is constrained using numerical weather prediction data in order to retrieve a set of geophysical parameters that best fit the measurements. A sensitivity study demonstrates the method is robust and that the solution it provides is not dependent on initialization conditions. The retrieval parameters have been compared with the Arctic Systems Reanalysis model data as well as columnar water vapor retrieved from satellite microwave sounders and the Remote Sensing Systems AMSR-E ocean retrieval product in order to determine the feasibility of using the same setup over pure surface with 100% and 0% sea ice cover, respectively. Sea ice concentration retrieval shows good skill for pure surface cases. Ice types retrieval is in good agreement with scatterometer backscatter data. Deficiencies have been identified in using the forward model over sea ice for retrieving atmospheric parameters, that are connected to the treatment of surface emissivity and surface temperature. The retrieval agrees well with legacy atmospheric retrieval products in open ocean areas. |
format |
Article in Journal/Newspaper |
author |
Scarlat, Raul Cristian Heygster, Georg Pedersen, Leif Toudal |
author_facet |
Scarlat, Raul Cristian Heygster, Georg Pedersen, Leif Toudal |
author_sort |
Scarlat, Raul Cristian |
title |
Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic |
title_short |
Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic |
title_full |
Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic |
title_fullStr |
Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic |
title_full_unstemmed |
Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic |
title_sort |
experiences with an optimal estimation algorithm for surface and atmospheric parameter retrieval from passive microwave data in the arctic |
publishDate |
2017 |
url |
https://orbit.dtu.dk/en/publications/5eb83186-3860-458b-8731-538c3971d095 https://doi.org/10.1109/JSTARS.2017.2739858 https://backend.orbit.dtu.dk/ws/files/190319119/jstars_2739858_pp.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic Sea ice |
genre_facet |
Arctic Arctic Sea ice |
op_source |
Scarlat , R C , Heygster , G & Pedersen , L T 2017 , ' Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic ' , I E E E Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 10 , no. 9 , pp. 3934-3947 . https://doi.org/10.1109/JSTARS.2017.2739858 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1109/JSTARS.2017.2739858 |
container_title |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
container_volume |
10 |
container_issue |
9 |
container_start_page |
3934 |
op_container_end_page |
3947 |
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1775347519127027712 |