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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 8
Geosci. Model Dev., 9, 2721–2739, 2016
https://doi.org/10.5194/gmd-9-2721-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 2721–2739, 2016
https://doi.org/10.5194/gmd-9-2721-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 19 Aug 2016

Development and technical paper | 19 Aug 2016

RTTOV-gb – adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations

Francesco De Angelis et al.

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Blumberg, W. G., Turner, D. D., Löhnert, U., and Castleberry, S.: Ground-Based Temperature and Humidity Profiling Using Spectral Infrared and Microwave Observations. Part II: Actual Retrieval Performance in Clear-Sky and Cloudy Conditions, J. Appl. Meteorol. Clim., 54, 2305–2319, https://doi.org/10.1175/JAMC-D-15-0005.1, 2015.
Boukabara S. A., Clough, S. A., Moncet, J.-L., Krupnov, A. F., Tretyakov, M. Yu., and Parshin, V. V.: Uncertainties in the Temperature Dependence of the Line-Coupling Parameters of the Microwave Oxygen Band: Impact Study, IEEE T. Geosci. Remote Sens., 43, 1109–1114, https://doi.org/10.1109/TGRS.2004.839654, 2005.
Brousseau, P., Berre, L., Bouttier, F., and Desroziers, G.: Background error covariances for a convective scale data assimilation system: AROME 3D-Var, Q. J. Roy. Meteor. Soc., 137, 409–422, 2011.
Brunel, P. and Hocking, J.: RTTOV v11 Test Suite, Met Office Doc ID: NWPSAF-MO-TV-031, 2014.
Buehler, S. A., Eriksson, P., Kuhn, T., von Engeln, A., and Verdes, C.: ARTS, the Atmospheric Radiative Transfer Simulator, J. Quant. Spectrosc. Ra., 91, 65–93, https://doi.org/10.1016/j.jqsrt.2004.05.051, 2005.
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Ground-based microwave radiometers (MWRs) offer to bridge the observational gap in the atmospheric boundary layer. Currently MWRs are operational at many sites worldwide. However, their potential is largely under-exploited, partly due to the lack of a fast radiative transfer model (RTM) suited for data assimilation into numerical weather prediction models. Here we propose and test an RTM, building on satellite heritage and adapting for ground-based MWRs, which addresses this shortage.
Ground-based microwave radiometers (MWRs) offer to bridge the observational gap in the...
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