Assimilation of water-vapour airborne lidar observations: Impact study on the COPS precipitation forecasts

S. Bielli, M. Grzeschik, E. Richard, C. Flamant, C. Champollion, C. Kiemle, M. Dorninger, P. Brousseau

Veröffentlichungen: Beitrag in FachzeitschriftArtikelPeer Reviewed

Abstract

The Convective and Orographically-driven Precipitation Study (COPS) carried out in summer 2007 over northeastern France and southwestern Germany provided a fairly comprehensive description of the low-troposphere water-vapour field, thanks in particular to the deployment of two airborne differential absorption lidar systems. These lidar observations were assimilated using the 3D-Var assimilation system of the Application of Research to Operations at MEsoscale (AROME) numerical weather prediction mesoscale model. The assimilation was carried out for the period 4 July-3 August by running a three-hour forward intermittent assimilation cycle. First, the impact of the lidar observations was assessed by comparing the analyses with a set of more than 200 independent soundings. The lidar observations were found to have a positive impact on the analyses by reducing the dry bias in the first 500 m above ground level and by diminishing the root-mean-square error by roughly 15% in the first km. Then the impact of the lidar observations was assessed by comparing the precipitation forecasts (obtained with and without the lidar observations for the period 15 July-2 August) with the gridded precipitation observations provided by the Vienna Enhanced Resolution Analysis. In general, the impact was found to be positive but not significant for the 24 h precipitation and positive and significant for the 6 h precipitation, with an improvement lasting up to 24 h. Some selected case studies show that the improvement was obtained through a better depiction of convection initiation or through a more accurate positioning of the precipitation systems.

OriginalspracheEnglisch
Seiten (von - bis)1652-1667
Seitenumfang16
FachzeitschriftQuarterly Journal of the Royal Meteorological Society
Jahrgang138
Ausgabenummer667
Frühes Online-Datum21 Dez. 2011
DOIs
PublikationsstatusVeröffentlicht - 1 Juli 2012

ÖFOS 2012

  • 105206 Meteorologie

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