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Volume 12, issue 3 | Copyright
The Cryosphere, 12, 921-933, 2018
https://doi.org/10.5194/tc-12-921-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Mar 2018

Research article | 14 Mar 2018

Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models

Friedrich Richter1, Matthias Drusch1, Lars Kaleschke3, Nina Maaß3, Xiangshan Tian-Kunze3, and Susanne Mecklenburg2 Friedrich Richter et al.
  • 1European Space Agency, ESA-ESTEC, 2200 AG Noordwijk, the Netherlands
  • 2European Space Agency, ESA-ESRIN, Via Galileo Galilei, casella postale 64 – 00044, Frascati, Italy
  • 3Institute of Oceanography, University of Hamburg, Bundesstraße 53, 20146 Hamburg, Germany

Abstract. Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously.

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L-band (1.4 GHz) brightness temperatures from ESA's Soil Moisture and Ocean Salinity SMOS mission have been used to derive thin sea ice thickness. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems reducing the data latency and providing a more consistent first guess. We studied the forward (observation) operator that translates geophysical sea ice parameters from the ECMWF Ocean ReAnalysis Pilot 5 (ORAP5) into brightness temperatures.
L-band (1.4 GHz) brightness temperatures from ESA's Soil Moisture and Ocean Salinity SMOS...
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