Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method
Research on improving the prediction skill of climate models requires refining the quality of observational data used for initializing and tuning the models. This is especially true in the Polar Regions where uncertainties about the interactions between sea ice, ocean and atmosphere are driving ongo...
Main Authors: | , , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
PANGAEA
2020
|
Subjects: | |
Online Access: | https://doi.pangaea.de/10.1594/PANGAEA.912748 https://doi.org/10.1594/PANGAEA.912748 |
id |
ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.912748 |
---|---|
record_format |
openpolar |
institution |
Open Polar |
collection |
PANGAEA - Data Publisher for Earth & Environmental Science |
op_collection_id |
ftpangaea |
language |
English |
topic |
AMSR2 Arctic CIMR File content File format File size pan-Arctic sea ice concentration Sea ice thickness Time coverage Uniform resource locator/link to file |
spellingShingle |
AMSR2 Arctic CIMR File content File format File size pan-Arctic sea ice concentration Sea ice thickness Time coverage Uniform resource locator/link to file Scarlat, Raul Cristian Huntemann, Marcus Paţilea, Cătălin Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method |
topic_facet |
AMSR2 Arctic CIMR File content File format File size pan-Arctic sea ice concentration Sea ice thickness Time coverage Uniform resource locator/link to file |
description |
Research on improving the prediction skill of climate models requires refining the quality of observational data used for initializing and tuning the models. This is especially true in the Polar Regions where uncertainties about the interactions between sea ice, ocean and atmosphere are driving ongoing monitoring efforts. The Copernicus Imaging Microwave Radiometer (CIMR) is an European Space Agency (ESA) candidate mission which promises to offer high resolution, low uncertainty observation capabilities at the 1.4, 6.9,10.65,18.7 and 36.5 GHz frequencies. To assess the potential impact of CIMR for sea ice parameter retrieval, a comparison is made between retrievals based on present AMSR2 observations and a retrieval using future CIMR equivalent observations over a data set of validated sea ice concentration (SIC) values. An optimal estimation retrieval method (OEM) is used which can use input from different channel combinations to retrieve seven geophysical parameters (sea ice concentration, multi year ice fraction, ice surface temperature, columnar water vapor, liquid water path, over ocean wind speed and sea surface temperature). An advantage of CIMR over existing adiometers is that it would provide higher spatial resolution observations at the lower frequency channels (6.9, 10.65, 18.7 GHz) which are less sensitive to atmospheric influence. This enables the passive microwave based retrieval of SIC and other surface parameters with higher resolution and lower uncertainty than is currently possible. An information content analysis expands the comparison between AMSR2 and CIMR to all retrievable surface and atmospheric parameters. This analysis quantifies the contributions to the observed signal and highlights the differences between different input channel combinations. The higher resolution of the low frequency CIMR channels allow for unprecedented detail to be achieved in Arctic passive microwave sea ice retrievals. The presence of 1.4 GHz channels on board CIMR opens up the possibility for thin sea ice ... |
format |
Dataset |
author |
Scarlat, Raul Cristian Huntemann, Marcus Paţilea, Cătălin |
author_facet |
Scarlat, Raul Cristian Huntemann, Marcus Paţilea, Cătălin |
author_sort |
Scarlat, Raul Cristian |
title |
Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method |
title_short |
Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method |
title_full |
Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method |
title_fullStr |
Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method |
title_full_unstemmed |
Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method |
title_sort |
sea ice concentration and thin sea ice thickness in the arctic retrieved with different configurations of an optimal estimation method |
publisher |
PANGAEA |
publishDate |
2020 |
url |
https://doi.pangaea.de/10.1594/PANGAEA.912748 https://doi.org/10.1594/PANGAEA.912748 |
op_coverage |
LATITUDE: 90.000000 * LONGITUDE: 0.000000 |
long_lat |
ENVELOPE(0.000000,0.000000,90.000000,90.000000) |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_relation |
Scarlat, Raul Cristian; Spreen, Gunnar; Heygster, Georg; Huntemann, Marcus; Paţilea, Cătălin; Pedersen, Leif Toudal; Saldo, Roberto (accepted): Sea Ice and Atmospheric Parameter Retrieval From Satellite Microwave Radiometers: Synergy of AMSR2 and SMOS Compared With the CIMR Candidate Mission. Journal of Geophysical Research: Oceans, https://doi.org/10.1029/2019JC015749 Heygster, Georg; Huntemann, Marcus; Ivanova, N; Saldo, Roberto; Pedersen, Leif Toudal (2014): Response of passive microwave sea ice concentration algorithms to thin ice. IEEE Geoscience and Remote Sensing Symposium. IEEE, https://doi.org/10.1109/IGARSS.2014.6947266 Scarlat, Raul Cristian; Heygster, Georg; Pedersen, Leif Toudal (2017): Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(9), 3934-3947, https://doi.org/10.1109/JSTARS.2017.2739858 https://doi.pangaea.de/10.1594/PANGAEA.912748 https://doi.org/10.1594/PANGAEA.912748 |
op_rights |
CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1594/PANGAEA.91274810.1029/2019JC01574910.1109/IGARSS.2014.694726610.1109/JSTARS.2017.2739858 |
_version_ |
1810293865912991744 |
spelling |
ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.912748 2024-09-15T17:51:51+00:00 Sea Ice Concentration and thin Sea Ice Thickness in the Arctic retrieved with different configurations of an Optimal Estimation Method Scarlat, Raul Cristian Huntemann, Marcus Paţilea, Cătălin LATITUDE: 90.000000 * LONGITUDE: 0.000000 2020 text/tab-separated-values, 10 data points https://doi.pangaea.de/10.1594/PANGAEA.912748 https://doi.org/10.1594/PANGAEA.912748 en eng PANGAEA Scarlat, Raul Cristian; Spreen, Gunnar; Heygster, Georg; Huntemann, Marcus; Paţilea, Cătălin; Pedersen, Leif Toudal; Saldo, Roberto (accepted): Sea Ice and Atmospheric Parameter Retrieval From Satellite Microwave Radiometers: Synergy of AMSR2 and SMOS Compared With the CIMR Candidate Mission. Journal of Geophysical Research: Oceans, https://doi.org/10.1029/2019JC015749 Heygster, Georg; Huntemann, Marcus; Ivanova, N; Saldo, Roberto; Pedersen, Leif Toudal (2014): Response of passive microwave sea ice concentration algorithms to thin ice. IEEE Geoscience and Remote Sensing Symposium. IEEE, https://doi.org/10.1109/IGARSS.2014.6947266 Scarlat, Raul Cristian; Heygster, Georg; Pedersen, Leif Toudal (2017): Experiences With an Optimal Estimation Algorithm for Surface and Atmospheric Parameter Retrieval From Passive Microwave Data in the Arctic. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(9), 3934-3947, https://doi.org/10.1109/JSTARS.2017.2739858 https://doi.pangaea.de/10.1594/PANGAEA.912748 https://doi.org/10.1594/PANGAEA.912748 CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess AMSR2 Arctic CIMR File content File format File size pan-Arctic sea ice concentration Sea ice thickness Time coverage Uniform resource locator/link to file dataset 2020 ftpangaea https://doi.org/10.1594/PANGAEA.91274810.1029/2019JC01574910.1109/IGARSS.2014.694726610.1109/JSTARS.2017.2739858 2024-07-24T02:31:34Z Research on improving the prediction skill of climate models requires refining the quality of observational data used for initializing and tuning the models. This is especially true in the Polar Regions where uncertainties about the interactions between sea ice, ocean and atmosphere are driving ongoing monitoring efforts. The Copernicus Imaging Microwave Radiometer (CIMR) is an European Space Agency (ESA) candidate mission which promises to offer high resolution, low uncertainty observation capabilities at the 1.4, 6.9,10.65,18.7 and 36.5 GHz frequencies. To assess the potential impact of CIMR for sea ice parameter retrieval, a comparison is made between retrievals based on present AMSR2 observations and a retrieval using future CIMR equivalent observations over a data set of validated sea ice concentration (SIC) values. An optimal estimation retrieval method (OEM) is used which can use input from different channel combinations to retrieve seven geophysical parameters (sea ice concentration, multi year ice fraction, ice surface temperature, columnar water vapor, liquid water path, over ocean wind speed and sea surface temperature). An advantage of CIMR over existing adiometers is that it would provide higher spatial resolution observations at the lower frequency channels (6.9, 10.65, 18.7 GHz) which are less sensitive to atmospheric influence. This enables the passive microwave based retrieval of SIC and other surface parameters with higher resolution and lower uncertainty than is currently possible. An information content analysis expands the comparison between AMSR2 and CIMR to all retrievable surface and atmospheric parameters. This analysis quantifies the contributions to the observed signal and highlights the differences between different input channel combinations. The higher resolution of the low frequency CIMR channels allow for unprecedented detail to be achieved in Arctic passive microwave sea ice retrievals. The presence of 1.4 GHz channels on board CIMR opens up the possibility for thin sea ice ... Dataset Arctic Sea ice PANGAEA - Data Publisher for Earth & Environmental Science ENVELOPE(0.000000,0.000000,90.000000,90.000000) |