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

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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. © 2011 Royal Meteorological Society.

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Bielli, S., Grzeschik, M., Richard, E., Flamant, C., Champollion, C., Kiemle, C., … Brousseau, P. (2012). Assimilation of water-vapour airborne lidar observations: Impact study on the COPS precipitation forecasts. Quarterly Journal of the Royal Meteorological Society, 138(667), 1652–1667. https://doi.org/10.1002/qj.1864

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