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Climate Dynamics

, Volume 51, Issue 3, pp 1041–1057 | Cite as

Simulation of medicanes over the Mediterranean Sea in a regional climate model ensemble: impact of ocean–atmosphere coupling and increased resolution

  • Miguel Ángel Gaertner
  • Juan Jesús González-Alemán
  • Raquel Romera
  • Marta Domínguez
  • Victoria Gil
  • Enrique Sánchez
  • Clemente Gallardo
  • Mario Marcello Miglietta
  • Kevin J. E. Walsh
  • Dmitry  V. Sein
  • Samuel Somot
  • Alessandro Dell’Aquila
  • Claas Teichmann
  • Bodo Ahrens
  • Erasmo Buonomo
  • Augustin Colette
  • Sophie Bastin
  • Erik van Meijgaard
  • Grigory Nikulin
Article

Abstract

Medicanes are cyclones over the Mediterranean Sea having a tropical-like structure but a rather small size, that can produce significant damage due to the combination of intense winds and heavy precipitation. Future climate projections, performed generally with individual atmospheric climate models, indicate that the intensity of the medicanes could increase under climate change conditions. The availability of large ensembles of high resolution and ocean–atmosphere coupled regional climate model (RCM) simulations, performed in MedCORDEX and EURO-CORDEX projects, represents an opportunity to improve the assessment of the impact of climate change on medicanes. As a first step towards such an improved assessment, we analyze the ability of the RCMs used in these projects to reproduce the observed characteristics of medicanes, and the impact of increased resolution and air-sea coupling on their simulation. In these storms, air-sea interaction plays a fundamental role in their formation and intensification, a different mechanism from that of extra-tropical cyclones, where the baroclinic instability mechanism prevails. An observational database, based on satellite images combined with high resolution simulations (Miglietta et al. in Geophys Res Lett 40:2400–2405, 2013), is used as a reference for evaluating the simulations. In general, the simulated medicanes do not coincide on a case-by-case basis with the observed medicanes. However, observed medicanes with a high intensity and relatively long duration of tropical characteristics are better replicated in simulations. The observed spatial distribution of medicanes is generally well simulated, while the monthly distribution reveals the difficulty of simulating the medicanes that first appear in September after the summer minimum in occurrence. Increasing the horizontal resolution has a systematic and generally positive impact on the frequency of simulated medicanes, while the general underestimation of their intensity is not corrected in most cases. The capacity of a few models to better simulate the medicane intensity suggests that the model formulation is more important than reducing the grid spacing alone. A negative intensity feedback is frequently the result of air-sea interaction for tropical cyclones in other basins. The introduction of air-sea coupling in the present simulations has an overall limited impact on medicane frequency and intensity, but it produces an interesting seasonal shift of the simulated medicanes from autumn to winter. This fact, together with the analysis of two contrasting particular cases, indicates that the negative feedback could be limited or even absent in certain situations. We suggest that the effects of air-sea interaction on medicanes may depend on the oceanic mixed layer depth, thus increasing the applicability of ocean–atmosphere coupled RCMs for climate change analysis of this kind of cyclones.

Keywords

Mediterranean cyclones Medicanes Regional climate models High resolution Ocean–atmosphere coupling 

Notes

Acknowledgements

This work is part of the Med-CORDEX initiative (www.medcordex.eu) supported by the HyMeX programme (www.hymex.org). Part of the data used in this work have been downloaded from the Med-CORDEX database (www.medcordex.eu). The authors like to thank the coordination and participating institutes of the EURO-CORDEX initiative (www.euro-cordex.net). The work of UCLM group has been funded by the grant CGL2010-18013 (Spanish Ministry of Science and Innovation) and grant CGL2013-47261-R (Spanish Ministry of Economy and Competitivity). These grants have been co-funded by the European Regional Development Fund. AWI simulations were performed at the German Climate Computing Center (DKRZ). The work of Dmitry Sein was supported by the German Federal Ministry of Education and Research (BMBF) under the project SPACES-AGULHAS (research Grant 03G0835B). The REMO (GERICS) simulations were supported by BMBF and performed under the ‘‘Konsortial’’ share at the German Climate Computing Centre (DKRZ). Bodo Ahrens acknowledges support from Senckenberg BiK-F. The calculations for WRF IPSL-INERIS were made in collaboration with R. Vautard (IPSL/CNRS) using the TGCC super computers under the GENCI time allocation GEN6877. The work of Sophie Bastin has received funding from the French National Research Agency (ANR) projects REMEMBER (Contract ANR-12-SENV-001) and  granted access to the HPC resources of IDRIS (under allocation i2011010227). The KNMI-RACMO2 simulations were supported  by the Dutch Ministry of Infrastructure and the Environment. Part of the SMHI contribution was carried out in the Swedish Mistra-SWECIA programme founded by Mistra (the Foundation for Strategic Environmental Research).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Miguel Ángel Gaertner
    • 1
  • Juan Jesús González-Alemán
    • 1
  • Raquel Romera
    • 1
  • Marta Domínguez
    • 1
  • Victoria Gil
    • 1
  • Enrique Sánchez
    • 1
  • Clemente Gallardo
    • 1
  • Mario Marcello Miglietta
    • 2
  • Kevin J. E. Walsh
    • 3
  • Dmitry  V. Sein
    • 4
  • Samuel Somot
    • 5
  • Alessandro Dell’Aquila
    • 6
  • Claas Teichmann
    • 7
  • Bodo Ahrens
    • 8
  • Erasmo Buonomo
    • 9
  • Augustin Colette
    • 10
  • Sophie Bastin
    • 11
  • Erik van Meijgaard
    • 12
  • Grigory Nikulin
    • 13
  1. 1.Universidad de Castilla-La ManchaToledoSpain
  2. 2.Institute of Atmospheric Sciences and Climate - National Research Council (ISAC-CNR)LecceItaly
  3. 3.University of MelbourneParkvilleAustralia
  4. 4.Alfred Wegener InstituteBremerhavenGermany
  5. 5.CNRM UMR 3589, Météo-France/CNRSToulouseFrance
  6. 6.ENEA, SSPT-MET-CLIMRomeItaly
  7. 7.Climate Service Center Germany (GERICS)HamburgGermany
  8. 8.Institute for Atmospheric and Environmental Sciences, Goethe-University FrankfurtFrankfurt am MainGermany
  9. 9.Met Office-Hadley CentreExeterUnited Kingdom
  10. 10.Institut National de l′Environnement Industriel et des Risques (INERIS)Verneuil-en-HalatteFrance
  11. 11.LATMOS/IPSL, CNRS/INSU, UVSQ Université Paris‑Saclay, UPMC Univ. Paris 06GuyancourtFrance
  12. 12.Royal Netherlands Meteorological Institute (KNMI)De BiltThe Netherlands
  13. 13.Rossby Centre, Swedish Meteorological and Hydrological InstituteNorrköpingSweden

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