Browsing by Subject "MM5"

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Assimilation of ground-based and airborne lidar data into the MM5 4D-Var system
(2010) Grzeschik, Matthias; Wulfmeyer, Volker
This work investigates the impact of assimilating water vapor Light Detection and Ranging (lidar) data into mesoscale Numerical Weather Prediction (NWP) models. Two cases from the field campaigns International H20 Project 2002 (IHOP_2002) and International Lindenberg Campaign for Assessment of Humidity- and Cloud-Profiling Systems and its Impact on High-Resolution Modelling 2005 (LAUNCH-2005) are presented. In the first case, airborne water vapor Differential Absorption Lidar (DIAL) data are used for an assimilation for 24 May 2002, where convection occurred along an eastward moving dryline in western Texas and Oklahoma south of a triple point that formed in western Oklahoma. In the second case, a network of three ground based water vapor Raman lidars, operated behind a sharp frontal rain band with a northwesterly flow, are used. The method employed, Four-Dimensional Variational Data Assimilation (4D-Var), is described in relation to other methods and the implementation is given in detail. The data assimilation results in a large modification of the initial fields. The assimilation into the preconvective conditions changed not only the water vapor field but also the location of convergence lines, causing positive modification of Convective Initiation (CI). In the LAUNCH-2005 case a strong correction of the vertical structure and the absolute values of the initial water-vapor field of the order of 1g/kg was found. This occurred mainly upstream of the lidar systems within an area that was comparable with the domain covered by the lidar systems. The correction of the water-vapor field was validated using independent Global Positioning System (GPS) sensors. Much better agreement with GPS zenith wet path delay was achieved with the initial water-vapor field after 4D-Var. Furthermore, the impact of the assimilation and its temporal evolution was investigated with introduced measures. The results demonstrate the high value of accurate vertically resolved mesoscale water vapor observations and advanced data assimilation systems for short-range weather forecasting.