Articles | Volume 15, issue 18
https://doi.org/10.5194/amt-15-5415-2022
https://doi.org/10.5194/amt-15-5415-2022
Research article
 | 
26 Sep 2022
Research article |  | 26 Sep 2022

An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties

Alistair Bell, Pauline Martinet, Olivier Caumont, Frédéric Burnet, Julien Delanoë, Susana Jorquera, Yann Seity, and Vinciane Unger

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Cited articles

Bannister, R. N.: A review of forecast error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast error covariance statistics, Q. J. Roy. Meteor. Soc., 134, 1971–1996, 2008. a
Bauer, P., Lopez, P., Benedetti, A., Salmond, D., and Moreau, E.: Implementation of 1D + 4D-Var assimilation of precipitation-affected microwave radiances at ECMWF. I:  1D-Var, Q. J. Roy. Meteorol. Soc., 132, 2277–2306, 2006. a
Bell, A., Martinet, P., Caumont, O., Vié, B., Delanoë, J., Dupont, J.-C., and Borderies, M.: W-band radar observations for fog forecast improvement: an analysis of model and forward operator errors, Atmos. Meas. Tech., 14, 4929–4946, https://doi.org/10.5194/amt-14-4929-2021, 2021. a, b, c, d, e, f, g, h, i
Borderies, M., Caumont, O., Augros, C., Bresson, É., Delanoë, J., Ducrocq, V., Fourrié, N., Bastard, T. L., and Nuret, M.: Simulation of W-band radar reflectivity for model validation and data assimilation, Q. J. Roy. Meteorol. Soc., 144, 391–403, 2018. a
Bouttier, F. and Courtier, P.: Data assimilation concepts and methods March 1999, Meteorological training course lecture series, ECMWF, 718, 59, https://www.ecmwf.int/sites/default/files/elibrary/2002/16928-data-assimilation-concepts-and-methods.pdf (last access: 8 September 2022), 2002. a, b
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Short summary
Cloud radars and microwave radiometers offer the potential to improve fog forecasts when assimilated into a high-resolution model. As this process can be complex, a retrieval of model variables is sometimes made as a first step. In this work, results from a 1D-Var algorithm for the retrieval of temperature, humidity and cloud liquid water content are presented. The algorithm is applied first to a synthetic dataset and then to a dataset of real measurements from a recent field campaign.
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