Projected changes in medicanes in the HadGEM3 N512 high-resolution global climate model
- 317 Downloads
Medicanes or “Mediterranean hurricanes” represent a rare and physically unique type of Mediterranean mesoscale cyclone. There are similarities with tropical cyclones with regard to their development (based on the thermodynamical disequilibrium between the warm sea and the overlying troposphere) and their kinematic and thermodynamical properties (medicanes are intense vortices with a warm core and even a cloud-free eye). Although medicanes are smaller and their wind speeds are lower than in tropical cyclones, the severity of their winds can cause substantial damage to islands and coastal areas. Concern about how human-induced climate change will affect extreme events is increasing. This includes the future impacts on medicanes due to the warming of the Mediterranean waters and the projected changes in regional atmospheric circulation. However, most global climate models do not have high enough spatial resolution to adequately represent small features such as medicanes. In this study, a cyclone tracking algorithm is applied to high resolution global climate model data with a horizontal grid resolution of approximately 25 km over the Mediterranean region. After a validation of the climatology of general Mediterranean mesoscale cyclones, changes in medicanes are determined using climate model experiments with present and future forcing. The magnitude of the changes in the winds, frequency and location of medicanes is assessed. While no significant changes in the total number of Mediterranean mesoscale cyclones are found, medicanes tend to decrease in number but increase in intensity. The model simulation suggests that medicanes tend to form more frequently in the Gulf of Lion–Genoa and South of Sicily.
KeywordsMediterranean Medicanes Climate change Cyclone climatology HadGEM3
This research was supported by the PREDIMED (CGL2011-24458) and EXTREMO (CGL2014-52199-R) projects, funded by the Spanish “Ministerio de Ciencia e Innovación”. The leading author visited the University of Reading under Grant EEBB-I-13-07076 from “Ministerio de Educación”. The work was also partially funded by the Government of the Balearic Islands through the project 7/2011 of the Conselleria d’Educació, Cultura i Universitats. The study is based on the UPSCALE data set licensed from the University of Reading which includes material from NERC and the Controller of HMSO & Queen’s Printer. The UPSCALE data set was created by P. L. Vidale, M. Roberts, M. Mizielinski, J. Strachan, M.E. Demory and R. Schiemann using the HadGEM3 model with support from NERC and the Met Office and the PRACE Research Infrastructure resource HERMIT based in Germany at HLSR.
- Campins J, Genovés A, Picornell MA, Jansà A (2011) Climatology of Mediterranean cyclones using the ERA-40 dataset. Int J Climatol 31:1596–1614Google Scholar
- Daloz AS, Camargo SJ, Kossin JP, Emanuel K, Horn M, Jonas JA, Kim D, LaRow T, Lim YK, Patricola CM, Roberts M, Scoccimarro E, Shaevitz D, Vidale PL, Wang H, Wehner M, Zhao M (2015) Cluster analysis of downscaled and explicitly simulated north atlantic tropical cyclone tracks. J Clim 28:574–596CrossRefGoogle Scholar
- Jansà A (2003) Miniciclons a la mediterrània. IX Jornades de Meteorologia Eduard Fontserè, Associació Catalana de Meteorologia (ACAM), Barcelona. ISBN: 84–930328–6–7, 75–85Google Scholar
- Mizielinski MS, Roberts MJ, Vidale PL, Schiemann R, Demory ME, Strachan J, Edwards T, Stephens A, Lawrence BN, Pritchard M, Chiu P, Iwi A, Churchill J, del Cano Novales C, Kettleborough J, Roseblade W, Selwood P, Foster M, Glover M, Malcolm A (2014) High-resolution global climate modelling: the upscale project, a large-simulation campaign. Geosci Model Dev 7:1629–1640CrossRefGoogle Scholar
- Picornell MA, Jansà A, Genovés A, Campins J (2001) Automated database of mesocyclones from the Hirlam(INM)-0.5 analyses in the western mediterranean. Int J Climatol 335–354Google Scholar
- Shaevitz DA, Camargo SJ, Sobel AH, Jonas JA, Kim D, Kumar A, LaRow TE, Lim YK, Murakami H, Reed KA, Roberts MJ, Scoccimarro E, Vidale PL, Wang H, Wehner MF, Zhao M, Henderson N (2014) Characteristics of tropical cyclones in high-resolution models in the present climate. J Adv Model Earth Syst 6:1154–1172CrossRefGoogle Scholar
- Walters DN, Williams KD, Boutle IA, Bushell AC, Edwards JM, Field PR, Lock AP, Morcrette CJ, Stratton RA, Wilkinson JM, Willett MR, Brooks ME, Copsey D, Earnshaw PD, harris CM, Manners JC, MacLachian C, Palmer MD, Roberts MJ, Tennant WJ (2011) Development of an objective scheme to estimate tropical cyclone intensity from digital geostacionary satellite infrared imagery. The Met Office Unified Model Global Atmosphere 4.0 and JULES Global Land 4.0 configurations. Geosci Model Dev 7(1):361–386Google Scholar
- Welch B (1947) The generalization of “student’s” problem when several different population variances are involved. Biometrika 34(1–2):28–35Google Scholar
- Xia L, Zahn M, Hodges KI, Feser F, von Storch H (2012) A comparison of two identification and tracking methods for polar lows. Tellus A 64:17196. doi: 10.3402/tellusa.v64i0.17196