Articles | Volume 13, issue 12
Atmos. Meas. Tech., 13, 6593–6611, 2020
https://doi.org/10.5194/amt-13-6593-2020

Special issue: Tropospheric profiling (ISTP11) (AMT/ACP inter-journal SI)

Atmos. Meas. Tech., 13, 6593–6611, 2020
https://doi.org/10.5194/amt-13-6593-2020

Research article 07 Dec 2020

Research article | 07 Dec 2020

Improvement of numerical weather prediction model analysis during fog conditions through the assimilation of ground-based microwave radiometer observations: a 1D-Var study

Pauline Martinet et al.

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Cited articles

Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A., and Xiao, Q.: A three-dimensional variational data assimilation system for MM5: Implementation and initial results, Mon. Weather Rev., 132, 897–914, 2004. a
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Brousseau, P., Berre, L., Bouttier, F., and Desroziers, G.: Background-error covariances for a convective-scale data-assimilation system: AROME–France 3D-Var, Q. J. Roy. Meteor. Soc., 137, 409–422, 2011. a
Brousseau, P., Seity, Y., Ricard, D., and Léger, J.: Improvement of the forecast of convective activity from the AROME-France system, Q. J. Roy. Meteor. Soc., 142, 2231–2243, https://doi.org/10.1002/qj.2822, 2016. a, b
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Short summary
Each year large human and economical losses are due to fog episodes. However, fog forecasts remain quite inaccurate, partly due to a lack of observations in the atmospheric boundary layer. The benefit of ground-based microwave radiometers has been investigated and has demonstrated their capability of significantly improving the initial state of temperature and liquid water content profiles in current numerical weather prediction models, paving the way for improved fog forecasts in the future.