Methods for automatized detection of rapid changes in lateral boundary condition fields for NWP limited area models

Abstract

Abstract. Three hourly temporal resolution of lateral boundary data can be too low to properly resolve rapidly moving storms. This problem is expected to be worse with increasing horizontal resolution. In order to detect intensive disturbances in surface pressure moving rapidly through the model domain, a filtered surface pressure field (MCUF) is computed operationally in the ARPEGE global model of Météo France. The field is distributed in the coupling files along with conventional meteorological fields used for lateral boundary conditions (LBCs) for the operational forecast using limited area model ALADIN in the Meteorological and hydrological service of Croatia (DHMZ). Here an analysis is performed of the MCUF field for the LACE coupling domain for the period since 23 January 2006, when it became available, until 15 November 2014. The MCUF field is a good indicator of rapidly moving pressure disturbances (RMPDs). Its spatial and temporal distribution can be associated to the usual cyclone tracks and areas known to be supporting cyclogenesis. Other global models do not compute such field. Alternative set of coupling files from IFS operational run in ECMWF is also available operationally in DHMZ with 3 hourly temporal resolution but the MCUF field is not available. Here, several methods are tested that detect RMPDs in surface pressure a posteriori from the IFS model fields provided in the coupling files. MCUF is computed by running ALADIN on the coupling files from IFS. The error function is computed using one time step integration of ALADIN on the coupling files without initialization, initialized with DFI or SSDFI. Finally, the amplitude of changes in the mean sea level pressure is computed from the fields in the coupling files. The results are compared to the MCUF field of ARPEGE and the results of same methods applied to the coupling files from ARPEGE. Most methods give a signal for the rapidly moving pressure disturbances (RMPDs), but DFI reduces the storms too much to be detected. Error function without filtering and amplitude have more noise, but the signal of a RMPD is also stronger. The methods are tested for NWP LAM, but could be applied to and benefit the performance of climate LAMs.