Convective processes in high resolution models: Impact of the lead time of the simulation

• Lavin-Gullon, Alvaro ^[1] ; Fernandez, Jesus ^[2] ; Cardoso, Rita M. ^[3] ; Goergen, Klaus ^[7] ; Knist, Sebastian ^[4] ; Lorenz, Torge ^[8] ; Milovac, Josipa ^[5] ; Soares, Pedro M. M. ^[3] ; Sobolowski, Stefan ^[8] ; Truhetz, Heimo ^[6] ; Warrach-Sagi, Kirsten ^[5]
  1. [1] Instituto de Física de Cantabria

     Instituto de Física de Cantabria

     Santander, España

     
  2. [2] Universidad de Cantabria

     Universidad de Cantabria

     Santander, España

     
  3. [3] Universidade de Lisboa

     Universidade de Lisboa

     Socorro, Portugal

     
  4. [4] University of Bonn

     University of Bonn

     Kreisfreie Stadt Bonn, Alemania

     
  5. [5] University of Hohenheim

     University of Hohenheim

     Stadtkreis Stuttgart, Alemania

     
  6. [6] University of Graz

     University of Graz

     Graz, Austria

     
  7. [7] Institute of Bio-and Geosciences (IBG-3), Research Centre Jülich, Jülich. Centre for High-Performance Scientific Computing in Terrestrial Systems, Geoverbund ABC/J, Jülich
  8. [8] Uni Research Climate, Bjerknes Centre for Climate Research, Bergen

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• Localización: Acta de las Jornadas Científicas de la Asociación Meteorológica Española, ISSN-e 2605-2199, Nº. 35, 2018 (Ejemplar dedicado a: XXXV Jornadas Científicas de la AME - 19º Encuentro hispano-luso de Meteorología)
• Idioma: español
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• Resumen

  • Most heavy precipitation events occurring in the world are associated with convective processes. As these phenomena produce severe economic and societal impacts, it is crucial to get to know their behaviour and their evolution in a future climate. For this reason, the international project CORDEX (Coordinated Regional climate Downscaling Experiment) proposed the Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean, focused on the study of convection in Europe. In this initiative, multi-model and multi-physics results and uncertainties of regional climate models (RCMs) are explored by means of ensembles of simulations. In this work, we additionally explore the role of internal variability to explain the differences found in the results by different model configurations.