Combined SMAP–SMOS thin sea ice thickness retrieval
The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) provide brightness temperature data in the L band (1.4 GHz). At this low frequency the atmosphere is close to transparent and in polar regions the thickness of thin sea ice can be der...
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| Published in | The cryosphere Vol. 13; no. 2; pp. 675 - 691 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Katlenburg-Lindau
Copernicus GmbH
28.02.2019
Copernicus Publications |
| Subjects | |
| Online Access | Get full text |
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| Abstract | The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS)
and Soil Moisture Active Passive (SMAP) provide brightness temperature data
in the L band (1.4 GHz). At this low frequency the atmosphere is close to
transparent and in polar regions the thickness of thin sea ice can be
derived. SMOS measurements cover a large incidence angle range, whereas SMAP
observes at a fixed 40∘ incidence angle. By using brightness
temperatures at a fixed incidence angle obtained directly (SMAP), or through
interpolation (SMOS), thin sea ice thickness retrieval is more consistent as
the incidence angle effects do not have to be taken into account. Here we
transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm)
from SMOS data at 40 to 50∘ incidence angle to the fixed
incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given
incidence angle are estimated using empirical fit functions. SMAP TBs are
calibrated to SMOS to provide a merged SMOS–SMAP sea ice thickness
product. The new merged SMOS–SMAP thin ice thickness product was improved upon in
several ways compared to previous thin ice thickness retrievals. (i) The
combined product provides a better temporal and spatial coverage of the polar
regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was
improved, which results in higher data availability over both ocean and sea
ice areas. (iii) For the intercalibration between SMOS and SMAP brightness
temperatures the root mean square difference (RMSD) was reduced by 30 %
relative to a prior attempt. (iv) The algorithm presented here allows also
for separate retrieval from any of the two sensors, which makes the ice
thickness dataset more resistant against failure of one of the sensors. A new
way to estimate the uncertainty of ice thickness retrieval was implemented,
which is based on the brightness temperature sensitivities. |
|---|---|
| AbstractList | The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS)
and Soil Moisture Active Passive (SMAP) provide brightness temperature data
in the L band (1.4 GHz). At this low frequency the atmosphere is close to
transparent and in polar regions the thickness of thin sea ice can be
derived. SMOS measurements cover a large incidence angle range, whereas SMAP
observes at a fixed 40∘ incidence angle. By using brightness
temperatures at a fixed incidence angle obtained directly (SMAP), or through
interpolation (SMOS), thin sea ice thickness retrieval is more consistent as
the incidence angle effects do not have to be taken into account. Here we
transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm)
from SMOS data at 40 to 50∘ incidence angle to the fixed
incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given
incidence angle are estimated using empirical fit functions. SMAP TBs are
calibrated to SMOS to provide a merged SMOS–SMAP sea ice thickness
product. The new merged SMOS–SMAP thin ice thickness product was improved upon in
several ways compared to previous thin ice thickness retrievals. (i) The
combined product provides a better temporal and spatial coverage of the polar
regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was
improved, which results in higher data availability over both ocean and sea
ice areas. (iii) For the intercalibration between SMOS and SMAP brightness
temperatures the root mean square difference (RMSD) was reduced by 30 %
relative to a prior attempt. (iv) The algorithm presented here allows also
for separate retrieval from any of the two sensors, which makes the ice
thickness dataset more resistant against failure of one of the sensors. A new
way to estimate the uncertainty of ice thickness retrieval was implemented,
which is based on the brightness temperature sensitivities. The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) provide brightness temperature data in the L band (1.4 GHz). At this low frequency the atmosphere is close to transparent and in polar regions the thickness of thin sea ice can be derived. SMOS measurements cover a large incidence angle range, whereas SMAP observes at a fixed 40 ∘ incidence angle. By using brightness temperatures at a fixed incidence angle obtained directly (SMAP), or through interpolation (SMOS), thin sea ice thickness retrieval is more consistent as the incidence angle effects do not have to be taken into account. Here we transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm) from SMOS data at 40 to 50 ∘ incidence angle to the fixed incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given incidence angle are estimated using empirical fit functions. SMAP TBs are calibrated to SMOS to provide a merged SMOS–SMAP sea ice thickness product. The new merged SMOS–SMAP thin ice thickness product was improved upon in several ways compared to previous thin ice thickness retrievals. (i) The combined product provides a better temporal and spatial coverage of the polar regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was improved, which results in higher data availability over both ocean and sea ice areas. (iii) For the intercalibration between SMOS and SMAP brightness temperatures the root mean square difference (RMSD) was reduced by 30 % relative to a prior attempt. (iv) The algorithm presented here allows also for separate retrieval from any of the two sensors, which makes the ice thickness dataset more resistant against failure of one of the sensors. A new way to estimate the uncertainty of ice thickness retrieval was implemented, which is based on the brightness temperature sensitivities. The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) provide brightness temperature data in the L band (1.4 GHz). At this low frequency the atmosphere is close to transparent and in polar regions the thickness of thin sea ice can be derived. SMOS measurements cover a large incidence angle range, whereas SMAP observes at a fixed 40.sup.â incidence angle. By using brightness temperatures at a fixed incidence angle obtained directly (SMAP), or through interpolation (SMOS), thin sea ice thickness retrieval is more consistent as the incidence angle effects do not have to be taken into account. Here we transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm) from SMOS data at 40 to 50.sup.â incidence angle to the fixed incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given incidence angle are estimated using empirical fit functions. SMAP TBs are calibrated to SMOS to provide a merged SMOS-SMAP sea ice thickness product. The new merged SMOS-SMAP thin ice thickness product was improved upon in several ways compared to previous thin ice thickness retrievals. (i) The combined product provides a better temporal and spatial coverage of the polar regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was improved, which results in higher data availability over both ocean and sea ice areas. (iii) For the intercalibration between SMOS and SMAP brightness temperatures the root mean square difference (RMSD) was reduced by 30 % relative to a prior attempt. (iv) The algorithm presented here allows also for separate retrieval from any of the two sensors, which makes the ice thickness dataset more resistant against failure of one of the sensors. A new way to estimate the uncertainty of ice thickness retrieval was implemented, which is based on the brightness temperature sensitivities. The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) provide brightness temperature data in the L band (1.4 GHz). At this low frequency the atmosphere is close to transparent and in polar regions the thickness of thin sea ice can be derived. SMOS measurements cover a large incidence angle range, whereas SMAP observes at a fixed 40∘ incidence angle. By using brightness temperatures at a fixed incidence angle obtained directly (SMAP), or through interpolation (SMOS), thin sea ice thickness retrieval is more consistent as the incidence angle effects do not have to be taken into account. Here we transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm) from SMOS data at 40 to 50∘ incidence angle to the fixed incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given incidence angle are estimated using empirical fit functions. SMAP TBs are calibrated to SMOS to provide a merged SMOS–SMAP sea ice thickness product. The new merged SMOS–SMAP thin ice thickness product was improved upon in several ways compared to previous thin ice thickness retrievals. (i) The combined product provides a better temporal and spatial coverage of the polar regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was improved, which results in higher data availability over both ocean and sea ice areas. (iii) For the intercalibration between SMOS and SMAP brightness temperatures the root mean square difference (RMSD) was reduced by 30 % relative to a prior attempt. (iv) The algorithm presented here allows also for separate retrieval from any of the two sensors, which makes the ice thickness dataset more resistant against failure of one of the sensors. A new way to estimate the uncertainty of ice thickness retrieval was implemented, which is based on the brightness temperature sensitivities. |
| Audience | Academic |
| Author | Huntemann, Marcus Heygster, Georg Paţilea, Cătălin Spreen, Gunnar |
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| Cites_doi | 10.1029/2007GL029703 10.1029/2000JC000311 10.1029/2012GL050916 10.1016/j.rse.2016.03.009 10.1109/TGRS.2004.830641 10.1109/36.942551 10.5194/tc-9-1797-2015 10.1109/JPROC.2010.2043918 10.1029/JC083iC07p03646 10.1109/TGRS.2005.856115 10.1007/978-3-319-13865-7_11 10.1109/TGRS.2012.2187666 10.1109/JPROC.2009.2033096 10.1029/2006JC003543 10.1109/IGARSS.2014.6947266 10.5194/tc-4-583-2010 10.1109/TGRS.2008.915543 10.1029/00EO00124 10.5194/tc-8-439-2014 10.1016/j.rse.2016.02.036 10.1109/JSTARS.2014.2336664 10.1016/0270-0255(87)90516-1 10.1007/s00382-008-0493-4 10.1109/IGARSS.2016.7730367 10.1109/TGRS.2004.840458 10.1109/TGRS.2012.2182775 10.14430/arctic3658 10.1109/LGRS.2015.2428653 10.1109/LGRS.2016.2637440 10.1109/LGRS.2015.2437612 10.1109/TGRS.2010.2060729 10.5194/tc-8-997-2014 10.1109/TGRS.2016.2580459 10.1002/9781119028000 10.3390/rs10040553 10.1029/2005JC003384 10.1109/TGRS.2012.2184548 10.1559/152304003100011090 10.1126/science.1076522 10.1109/TGRS.2007.914809 |
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| Snippet | The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS)
and Soil Moisture Active Passive (SMAP) provide brightness temperature data
in the... The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) provide brightness temperature data in the... |
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| SubjectTerms | Algorithms Analysis Brightness Brightness temperature Ice Ice cover Ice thickness Incidence angle Intercalibration Interpolation Meteorological satellites Microwave sensors Oceans Polar environments Polar regions Radio frequency interference Retrieval Salinity Sea ice Sea ice thickness Sensors Soil Soil moisture Soil temperature Surface radiation temperature Temperature Temperature data Thickness |
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| Title | Combined SMAP–SMOS thin sea ice thickness retrieval |
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