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| = Project description = | = Project results = |
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| The aim of the SMOSIce study is to develop, improve and validate algorithms for sea ice thickness retrieval from the 1.4 GHz (L-band, wavelength=20cm) data of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. SMOS payload is the Microwave Imaging Radiometer Using Aperture Synthesis (MIRAS) measuring the brightness temperature at a range of incidence angles and at different polarizations. | The aim of the SMOSIce study was to develop, improve and validate algorithms for sea ice thickness retrieval from the 1.4 GHz (L-band) data of the European Space Agency's (ESA) [[http://www.esa.int/esaLP/LPsmos.html|Soil Moisture and Ocean Salinity (SMOS) mission]]. SMOS payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) measuring for the first time globally the L-band brightness temperature at a range of incidence angles and at different polarizations. Electromagnetic radiation at L-band wavelengths (about 21cm) emerge from deep inside the sea ice layer. The attenuation mainly depends on the relative brine volume which is a function of ice bulk salinity and temperature. The penetration depth is up to 1.5m for cold low-salinity sea ice and reduces to a few centimeters for saline sea ice at high temperatures. The potential to derive the ice thickness from L-band radiometry mainly depends on sea ice temperature and salinity. |
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| Electromagnetic radiation with wavelengths of 20 cm can emerge from deep inside the sea ice layer. The attenuation mainly depends on the relative brine volume which is a function of ice bulk salinity and temperature. The penetration depth is up to 1.5m for cold low-salinity ice and reduces to a few centimeters for saline sea ice at high temperatures. The potential to derive the ice thickness from L-band radiometry thus depends on sea ice temperature and salinity. | Several different sea ice emissivity models and retrieval algorithms have been developed and assessed using independent ice thickness estimates. The independent ice thickness estimates include electromagnetic induction (EM) measurements, NASA's Operation IceBridge data, MODIS thermal infrared imagery, as well as model simulations. The models used are of different complexity and range from empirical freezing degree-day ice growth parameterisations over one- and two-dimensional thermodynamic sea ice models to advanced coupled dynamic-thermodynamic ocean-ice assimilation systems. |
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| A sea ice emissivity model is an integral part for the retrieval of ice thickness from SMOS measurements. The most simple setup consists of a three layer (ocean-ice-atmosphere) dielectric slab with plane-parallel specular surfaces [[http://www.the-cryosphere.net/4/583/2010/tc-4-583-2010.html|(Kaleschke et al.,2010)]]. The dielectric properties are parameterized as a function of the bulk ice salinity and temperature. One main objective of the SMOSIce study is to define the Algorithm Theoretical Basis Documents (ATBD) for SMOS sea ice retrieval, as well as to generate a SMOS sea ice product. This product is assessed using independent ice thickness measurements mainly from thermal infrared satellite imagery (MODIS) as well as from electromagnetic induction (EM) measurements. | The assessment has shown a clear advantage of a retrieval method that accounts for variations in ice temperature and ice salinity. This retrieval method determines the maximum thickness that can be retrieved. Sensitivity studies as well as comparisons with MODIS ice thickness revealed significantly better performance of the retrieval based on the brightness temperature near nadir in comparison to the difference of vertically and horizonally polarised brightness temperatures in the higher incidence angle range. |
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| = First results = | For the production of a sea ice thickness data product we select an algorithm based on a forward model that includes a sea ice thermodynamic model and a three layer radiation model. During the iterative retrieval ice temperature and salinity are estimated from surface air temperature reanalysis and a weekly climatology of sea surface salinity. The retrieval model accounts for the thermodynamic effect of a snow layer parameterised as a function of ice thickness. The resulting sea ice thickness is corrected for the statistical influence of the thickness distribution function. |
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| SMOS provides daily coverage of the polar regions with a resolution of about 35 km and can be used to measure sea ice thickness up to half a meter. The ice thickness derived from SMOS agrees with the ice thickness from thermal infrared MODIS images with 10cm standard deviation. SMOS thickness retrieval is well feasible and practical under ideal cold conditions such as typically encountered during the Arctic freeze-up period. Changes in ice concentration and ice temperature, as well as the snow thickness are the largest uncertainties which are neglected for the first operational prototype of a retrieval algorithm. | A sea ice thickness product including three winter (October 15 to April 15) seasons has been derived from SMOS Level 1C brigthness temperature and is distributed via the Integrated Climate Data Center at the University of Hamburg. The daily updated data products are available at https://icdc.zmaw.de/. The approximate uncertainties of the SMOS ice thickness retrieval are about 20% for ice thickness less than 30 cm and 100% for ice thickness more than half a meter with an ill-constrained upper limit. To determine changes of the total sea ice thickness and volume we recommend to use SMOS and CryoSat-2 data together because of their complementary error characteristics. We expect the greatest benefit of the SMOS data alone during the cold freeze-up periods when extensive areas of thin sea ice control the ocean-atmosphere heat exchange, which is important for weather and climate, as well as for operational marine applications. There is the need for more validation measurements in both hemispheres to further improve the retrieval algorithm. |
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| == Sea ice thickness during the Arctic freeze-up as seen by SMOS == | |
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| {{attachment:ice_thickness_SMOS_Arc_0-40_20101101.png|20101101|width=400}} {{attachment:ice_thickness_SMOS_Arc_0-40_20101115.png|20101115|width=400}} {{attachment:ice_thickness_SMOS_Arc_0-40_20101201.png|20101201|width=400}} |
= Data = |
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| * [[http://icdc.zmaw.de/l3c_smos_sit.html|L3C SMOS Sea Ice Thickness is distributed via the Integrated Climate Data Center]] = Links = * [[http://blogs.esa.int/campaignearth/2014/03/24/smos-ice-first-coincident-flight-from-svalbard-a-success/|SMOS ice campaign 2014: first coincident flight from Svalbard a success]] * [[http://www.esa.int/SPECIALS/smos/SEMK64FRI7H_0.html| ESA satellites looking deeper into sea ice]] * [[http://www.esa.int/esaEO/SEM361BX9WG_index_0.html| SMOS versatility offers sea ice mapping]] |
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| A workshop to present the SMOS ice thickness product, as well as the scientific and technical outcome of the study will take place at the [[http://www.klimacampus.de/klimacamp+M563a176f1a5.html?&L=1|KlimaCampus]] of the University of Hamburg. Potential participants are modelers, sea ice remote sensing and assimilation experts, as well as representatives from operational ice services and international projects (e.g. CliC, CCI) and potential data users. Contributions, conclusions and recommendations from the participants will be compiled in a workshop report. |
A [[http://www.klimacampus.de/631+M5bbd728e1df.html?&L=1|workshop]] to present the new SMOS ice thickness product, as well as the scientific and technical outcome of the ESA SMOSIce study took place at the University of Hamburg. |
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| == Workshop details == * Date: 17 Feb 2012 * Time: 9:00-17:00 * Place: [[https://www.ifm.zmaw.de/|Institute of Oceanography]] at the [[http://www.klimacampus.de/klimacamp+M563a176f1a5.html?&L=1|KlimaCampus]], University of Hamburg * Registration: until 15 Jan, 2012 by email to Dr. Xiangshan Tian-Kunze: <<MailTo(xiangshan DOT tian-kunze AT SPAMFREE zmaw DOT de)>> == Technical programme == * '''The SMOS Mission''': Introduction (Yann Kerr) * '''Validation''': Sea ice thickness measurements in the Baltic Sea and in the Arctic (Stefan Hendricks, Marko Mäkynen) * '''Algorithms''': SMOS sea ice thickness retrieval algorithms (Lars Kaleschke, Georg Heygster) * '''Uncertainties''': SMOS sea ice thickness product validation, sensitivities and uncertainties (Xiangshan Tian-Kunze, Nina Maaß, Rasmus Tonboe) * '''Assimilation ''': Assimilation system for sea ice thickness (Frank Kauker) * '''ESA Climate Change Initiative (CCI)''': User requirements for the Essential Climate Variable (ECV) Sea Ice (Stefan Kern) |
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* [[http://www.the-cryosphere.net/8/997/2014/tc-8-997-2014.html|Tian-Kunze, X., Kaleschke, L., Maaß, N., Mäkynen, M., Serra, N., Drusch, M., and Krumpen, T.: SMOS-derived thin sea ice thickness: algorithm baseline, product specifications and initial verification, The Cryosphere, 8, 997-1018, doi:10.5194/tc-8-997-2014, 2014.]] * [[http://www.the-cryosphere.net/7/1971/2013/tc-7-1971-2013.pdf|Maaß, N., Kaleschke, L., Tian-Kunze, X., and Drusch, M.: Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data, The Cryosphere, 7, 1971-1989, doi:10.5194/tc-7-1971-2013, 2013.]] * [[http://www.the-cryosphere.net/8/439/2014/tc-8-439-2014.html|Huntemann, M., Heygster, G., Kaleschke, L., Krumpen, T., Mäkynen, M., and Drusch, M.: Empirical sea ice thickness retrieval during the freeze-up period from SMOS high incident angle observations, The Cryosphere, 8, 439-451, doi:10.5194/tc-8-439-2014, 2014.]] * [[attachment:Kaleschke_SMOS_GRL_2012.pdf|Kaleschke, L., X. Tian-Kunze, N. Maaß, M. Mäkynen, and M. Drusch (2012), Sea ice thickness retrieval from SMOS brightness temperatures during the Arctic freeze-up period, Geophys. Res. Lett., doi:10.1029/2012GL050916]] |
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---- * [[ https://icdc.zmaw.de/fileadmin/user_upload/icdc_Dokumente/SMOSICE_FinalReport_2013.pdf|Kaleschke, L., X. Tian-Kunze, N. Maaß, G. Heygster, M. Huntemann, H. Wang, S. Hendricks, T. Krumpen, R. Tonboe, M. Mäkynen, C. Haas: SMOS Sea Ice Retrieval Study (SMOSIce)", ESA Support To Science Element (STSE), Final Report ESA ESTEC Contract No.: 4000101476/10/NL/CT, 380 pages, Univ. Hamburg, Institute of Oceanography, 2013]] |
Project results
The aim of the SMOSIce study was to develop, improve and validate algorithms for sea ice thickness retrieval from the 1.4 GHz (L-band) data of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. SMOS payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) measuring for the first time globally the L-band brightness temperature at a range of incidence angles and at different polarizations. Electromagnetic radiation at L-band wavelengths (about 21cm) emerge from deep inside the sea ice layer. The attenuation mainly depends on the relative brine volume which is a function of ice bulk salinity and temperature. The penetration depth is up to 1.5m for cold low-salinity sea ice and reduces to a few centimeters for saline sea ice at high temperatures. The potential to derive the ice thickness from L-band radiometry mainly depends on sea ice temperature and salinity.
Several different sea ice emissivity models and retrieval algorithms have been developed and assessed using independent ice thickness estimates. The independent ice thickness estimates include electromagnetic induction (EM) measurements, NASA's Operation IceBridge data, MODIS thermal infrared imagery, as well as model simulations. The models used are of different complexity and range from empirical freezing degree-day ice growth parameterisations over one- and two-dimensional thermodynamic sea ice models to advanced coupled dynamic-thermodynamic ocean-ice assimilation systems.
The assessment has shown a clear advantage of a retrieval method that accounts for variations in ice temperature and ice salinity. This retrieval method determines the maximum thickness that can be retrieved. Sensitivity studies as well as comparisons with MODIS ice thickness revealed significantly better performance of the retrieval based on the brightness temperature near nadir in comparison to the difference of vertically and horizonally polarised brightness temperatures in the higher incidence angle range.
For the production of a sea ice thickness data product we select an algorithm based on a forward model that includes a sea ice thermodynamic model and a three layer radiation model. During the iterative retrieval ice temperature and salinity are estimated from surface air temperature reanalysis and a weekly climatology of sea surface salinity. The retrieval model accounts for the thermodynamic effect of a snow layer parameterised as a function of ice thickness. The resulting sea ice thickness is corrected for the statistical influence of the thickness distribution function.
A sea ice thickness product including three winter (October 15 to April 15) seasons has been derived from SMOS Level 1C brigthness temperature and is distributed via the Integrated Climate Data Center at the University of Hamburg. The daily updated data products are available at https://icdc.zmaw.de/. The approximate uncertainties of the SMOS ice thickness retrieval are about 20% for ice thickness less than 30 cm and 100% for ice thickness more than half a meter with an ill-constrained upper limit. To determine changes of the total sea ice thickness and volume we recommend to use SMOS and CryoSat-2 data together because of their complementary error characteristics. We expect the greatest benefit of the SMOS data alone during the cold freeze-up periods when extensive areas of thin sea ice control the ocean-atmosphere heat exchange, which is important for weather and climate, as well as for operational marine applications. There is the need for more validation measurements in both hemispheres to further improve the retrieval algorithm.
Data
Links
SMOSIce User Workshop
A workshop to present the new SMOS ice thickness product, as well as the scientific and technical outcome of the ESA SMOSIce study took place at the University of Hamburg.
References