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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 6
Atmos. Meas. Tech., 7, 1619–1628, 2014
https://doi.org/10.5194/amt-7-1619-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 7, 1619–1628, 2014
https://doi.org/10.5194/amt-7-1619-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Jun 2014

Research article | 06 Jun 2014

An integrated approach toward the incorporation of clouds in the temperature retrievals from microwave measurements

F. Navas-Guzmán, O. Stähli, and N. Kämpfer F. Navas-Guzmán et al.
  • Institute of Applied Physics (IAP), University of Bern, Bern, Switzerland

Abstract. In this paper, we address the characterization of clouds and its inclusion in microwave retrievals in order to study its effect on tropospheric temperature profiles measured by TEMPERA radiometer. TEMPERA is the first ground-based microwave radiometer that makes it possible to obtain temperature profiles in the troposphere and stratosphere at the same time. In order to characterize the clouds a multi-instrumental approach has been adopted. Cloud base altitudes were detected using ceilometer measurements while the integrated liquid water was measured by TROWARA radiometer. Both instruments are co-located with TEMPERA in Bern (Switzerland). Using this information and a constant Liquid Water Content value inside the cloud a liquid profile is provided to characterize the clouds in the inversion algorithm. Microwave temperature profiles have been obtained incorporating this water liquid profile in the inversion algorithm and also without considering the clouds, in order to assess its effect on the retrievals. The results have been compared with the temperature profiles from radiosondes which are launched twice a day at the aerological station of MeteoSwiss in Payerne (40 km W of Bern). Almost 1 year of data have been analysed and 60 non-precipitating cloud cases were studied. The statistical analysis carried out over all the cases evidenced that temperature retrievals improved in most of the cases when clouds were incorporated in the inversion algorithm.

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