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Comparison of MODIS-based thin-ice thicknesses with ice draft measurements in the Laptev Sea & Chukchi Sea

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<p>Acquiring information about the thickness of thin Arctic sea-ice is an important aspect of assessing atmosphere – sea-ice – ocean interactions, as the ice thickness directly relates to the magnitude of energy fluxes at the sea-ice interfaces. In winter, these fluxes are linked to sea-ice formation and hence accompanying processes such as physically induced upper-ocean convection and turbulent mixing of the lower atmospheric boundary layer. It remains a big challenge to validate satellite-derived thin-ice thicknesses, first and foremost due to the lack of suitable in-situ data in these remote areas.</p><p>In order to address this issue, we here present the first insight into a comparison between high-resolution (2km) MODIS thermal infrared satellite data (available for 2002/2003 to 2017/2018) and comprehensive time series of ice-draft data obtained from moored Ice Profiling Sonar (IPS) data. The IPS data set comprises winter-seasons 2009/2010 to 2011/2012 in the Chukchi Sea and winter-seasons 2013/2014 to 2014/2015 in the Laptev Sea. For the MODIS data set, a 1D energy balance model serves as the base for deriving thin-ice thicknesses (0 to 50 cm) from ice-surface temperature swath-data and ERA-Interim atmospheric reanalysis data. In order to facilitate the comparison, the 1Hz IPS ice-draft data is first empirically converted to ice thickness and afterwards resampled to 5-minute modal-values to find matching MODIS swath data.</p><p>It shows that the agreement between the MODIS and IPS ice-thickness data largely depends on the thickness of the ice sampled by the IPS. We found the highest agreement for ice thickness values below 20 cm, which tend to appear more frequently at the Chukchi Sea mooring location. More generally, we notice that MODIS seems to overestimate ice thicknesses up to approximately 40 cm. For thicker ice, the limitations of the MODIS ice-thickness retrieval result in an underestimation.</p>
Title: Comparison of MODIS-based thin-ice thicknesses with ice draft measurements in the Laptev Sea & Chukchi Sea
Description:
<p>Acquiring information about the thickness of thin Arctic sea-ice is an important aspect of assessing atmosphere – sea-ice – ocean interactions, as the ice thickness directly relates to the magnitude of energy fluxes at the sea-ice interfaces.
In winter, these fluxes are linked to sea-ice formation and hence accompanying processes such as physically induced upper-ocean convection and turbulent mixing of the lower atmospheric boundary layer.
It remains a big challenge to validate satellite-derived thin-ice thicknesses, first and foremost due to the lack of suitable in-situ data in these remote areas.
</p><p>In order to address this issue, we here present the first insight into a comparison between high-resolution (2km) MODIS thermal infrared satellite data (available for 2002/2003 to 2017/2018) and comprehensive time series of ice-draft data obtained from moored Ice Profiling Sonar (IPS) data.
The IPS data set comprises winter-seasons 2009/2010 to 2011/2012 in the Chukchi Sea and winter-seasons 2013/2014 to 2014/2015 in the Laptev Sea.
For the MODIS data set, a 1D energy balance model serves as the base for deriving thin-ice thicknesses (0 to 50 cm) from ice-surface temperature swath-data and ERA-Interim atmospheric reanalysis data.
In order to facilitate the comparison, the 1Hz IPS ice-draft data is first empirically converted to ice thickness and afterwards resampled to 5-minute modal-values to find matching MODIS swath data.
</p><p>It shows that the agreement between the MODIS and IPS ice-thickness data largely depends on the thickness of the ice sampled by the IPS.
We found the highest agreement for ice thickness values below 20 cm, which tend to appear more frequently at the Chukchi Sea mooring location.
More generally, we notice that MODIS seems to overestimate ice thicknesses up to approximately 40 cm.
For thicker ice, the limitations of the MODIS ice-thickness retrieval result in an underestimation.
</p>.

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