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Discussion papers
https://doi.org/10.5194/nhess-2018-314
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2018-314
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Nov 2018

Research article | 12 Nov 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Impact of airborne cloud radar reflectivity data assimilation on kilometre-scale NWP analyses and forecasts of heavy precipitation events

Mary Borderies1, Olivier Caumont1, Julien Delanoë2, Véronique Ducrocq1, Nadia Fourrié1, and Pascal Marquet1 Mary Borderies et al.
  • 1CNRM UMR 3589, Université de Toulouse, Météo-France, CNRS, Toulouse, France
  • 2LATMOS, IPSL, Université Versailles St-Quentin, CNRS, UPMC, Guyancourt, France

Abstract. This article investigates the potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area. The 1D+3DVar assimilation method, operationally employed to assimilate ground-based precipitation radar data in the Météo-France kilometre-scale NWP model AROME, has been adapted to assimilate the W-band reflectivity measured by the airborne cloud radar RASTA during a two-month period over the Mediterranean area. After applying a bias correction, vertical profiles of relative humidity are first derived via a 1D Bayesian retrieval, and then used as relative humidity pseudo-observations in the 3DVar assimilation system of AROME. The efficiency of the 1D Bayesian method in retrieving humidity fields is assessed using independent in-flight humidity measurements. To complement this study, the benefit brought by consistent thermodynamic and dynamic cloud conditions has been investigated by assimilating separately and jointly in the 3h 3DVar assimilation system of AROME the W-band reflectivity and horizontal wind measurements collected by RASTA.

The data assimilation experiments are conducted for a single heavy precipitation event, and then for 32 cases. Results indicate that the W-band reflectivity has a larger impact on the humidity, temperature and pressure fields in the analyses, compared to the assimilation of RASTA wind data alone. Besides, the analyses get closer to independent humidity observations if the W-band reflectivity is assimilated alone or jointly with RASTA wind data. Nonetheless, the impact of the W-band reflectivity decreases more rapidly as the forecast range increases, compared to the assimilation of RASTA wind data alone. Generally, the assimilation of the W-band reflectivity jointly with wind data results in the best improvement of the rainfall precipitation forecasts. Consequently, results of this study indicate that consistent thermodynamic and dynamic cloud conditions in the analysis leads to an improvement of both model initial conditions and forecasts. Even though to a less extent, the assimilation of the W-band reflectivity alone also results in a slight improvement of the rainfall precipitation forecasts.

Mary Borderies et al.
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The potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area is investigated. The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometer-scale NWP model AROME. The results suggest that the joint assimilation of W-band reflectivity and horizontal wind profiles lead to a slight improvement of moisture analyses and rainfall precipitation forecasts.
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