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Synchronization of Radar Observations with Multi-Scale Storm Tracking
YANG Hongping,Jian ZHANG,Carrie LANGSTON
Wuhan Institute of Heavy Rain, China Meteorological Administration, Wuhan 430074;Cooperative Institute for Mesoscale Meteorological Studies, The University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, Norman, O.K., U.S.A;Cooperative Institute for Mesoscale Meteorological Studies, The University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, Norman, O.K., U.S.A
Abstract The 3-D radar reflectivity data has become increasingly important for use in data assimilation towards convective scale numerical weather prediction as well as next generation precipitation estimation. Typically, reflectivity data from multiple radars are objectively analyzed and mosaiced onto a regional 3-D Cartesian grid prior to being assimilated into the models. One of the scientific issues associated with the mosaic of multi-radar observations is the synchronization of all the observations. Since radar data is usually rapidly updated (～every 5--10 min), it is common in current multi-radar mosaic techniques to combine multiple radar' observations within a time window by assuming that the storms are steady within the window. The assumption holds well for slow evolving precipitation systems, but for fast evolving convective storms, this assumption may be violated and the mosaic of radar observations at different times may result in inaccurate storm structure depictions. This study investigates the impact of synchronization on storm structures in multiple radar data analyses using a multi-scale storm tracking algorithm.
