Incorporating Variational Local Analysis and Prediction System (vLAPS) Analyses with Nudging Data Assimilation: Methodology and Initial Results

2017 
Abstract : The potential value of combining 2 data assimilation methodologies to improve mesoscale meteorological model predictions is investigated using a case day with strong convection. The variational version of the Local Analysis and Prediction System (vLAPS) and both analysis and observation nudging data assimilation are applied both separately and together. The combination of methods is designed to combine the benefits of the gradual and persistent application of the effects of observations during a pre-forecast gained from nudging with the ability to assimilate a wide variety of observation types gained from vLAPS. Multiple cycles of 1-km horizontal grid spacing forecasts of the Advanced Research version of the Weather Research and Forecasting model were completed for 20 May 2013 over the southern Great Plains. The results suggest potential value in this combination data assimilation system, but further analysis of this case is required as well as application of the technique to additional case days.
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