[A-AS03] Extreme Events and Mesoscale Weather: Observations and Modeling

[AAS03-15] A case study on a heavy rainfall event in March 2024 in Argentina using high frequency radar data assimilation with LETKF

*Arata Amemiya^1,2,3, Paula Soledad Maldonado⁵, María Eugenia Dillon^4,5, Jorge Gacitúa Gutiérrez^4,6, Gimena Casaretto^4,5,7, Federico Cutraro⁵, Juan Ruiz^4,6,7,8, hirofumi tomita¹, Yoshiyuki Kajikawa¹, Seiya Nishizawa¹, Yanina García Skabar⁵, Takemasa Miyoshi^1,2,3 (1.RIKEN Center for Computational Science, 2.RIKEN Cluster for Pioneering Research, 3.RIKEN interdisciplinary Theoretical and Mathematical Sciences Program, 4.Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina, 5.Servicio Meteorológico Nacional, Buenos Aires, Argentina, 6.Centro de Investigaciones del Mar y la Atmósfera, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, CONICET-UBA, Buenos Aires, Argentina, 7.Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina, 8.CNRS-IRD-CONICET-UBA, Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI), Buenos Aires, Argentina)

Keywords:Data assimilation, Numerical weather prediction, Mesoscale convective system, Weather radar

The National Weather Service of Argentina has long been studying on the use of the Local Ensemble Transform Kalman Filter (LETKF) and recently implemented the LETKF with the Weather Research and Forecasting (WRF) model at a 4-km horizontal grid spacing as their operational probabilistic NWP system. In addition, to provide more accurate and timely forecasts of localized heavy precipitation in urban areas in Argentina, we have developed a prototype of high-resolution and frequent-update LETKF system under a project called PREVENIR, the Japan-Argentina cooperation project for a total package of heavy rain and urban flood disaster prevention. The operational 4-km WRF-LETKF system assimilates conventional observations and radar reflectivity every hour, whereas the high-resolution LETKF system using WRF or Scalable Computing for Advanced Library and Environment regional model (SCALE-RM) assimilates additional automated weather station data every 10 minutes and radar data every 5 minutes. Here we present a case study of heavy rainfall by mesoscale convective systems in Buenos Aires on 19 March 2024. The development of organized convection during the event is captured by the network of Doppler weather radars in Argentina. Panels (a) and (b) in the figure show the synoptic pattern at 0000 UTC of 20 March 2024 represented by the Global Forecasting System (GFS) of the US National Centers for Environmental Prediction (NCEP). Warm and moist air from northern tropical rainforests flows into the urban area of Buenos Aires (red and white rectangles in (a) and (b)) and generates intense mesoscale convective systems. Panels (c) and (d) show the snapshot of the maximum column radar reflectivity observed by Ezeiza radar in Buenos Aires at about 2200 and 2300 UTC, respectively. The preliminary result of the data assimilation experiment with the 4-km WRF-LETKF system (panels (e) and (f)) showed that the analysis maximum column reflectivity field roughly corresponds to the observed reflectivity. Detailed performance assessment of the operational and prototypical high-resolution LETKF systems and the sensitivity to parameter settings will be discussed in the presentation.