Investigating the predictability of a Mediterranean tropical-like cyclone using a storm-resolving model

被引:22
|
作者
Cioni, Guido [1 ,2 ]
Cerrai, Diego [3 ]
Klocke, Daniel [2 ,4 ]
机构
[1] Max Planck Inst Meteorol, Bundesstr 53, Hamburg, Germany
[2] Hans Ertel Ctr Weather Res HErZ, Hamburg, Germany
[3] Univ Connecticut, Hydrometeorol & Hydrol Remote Sensing Grp, Storrs, CT USA
[4] Deutsch Wetterdienst, Offenbach, Germany
基金
美国国家航空航天局;
关键词
medicanes; potential vorticity streamers; tropical-like cyclones; POTENTIAL VORTICITY; NOVEMBER; 2014; ECMWF MODEL; SEA; SENSITIVITY; PARAMETERIZATION; SIMULATION; HURRICANE; MEDICANE;
D O I
10.1002/qj.3322
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Predicting the trajectory and structure of Mediterranean tropical-like cyclones (MTLCs) has always been a challenge even within a few hours of verification time, given the inadequacy of numerical weather prediction (NWP) models to resolve the relatively small spatial scale of these systems. In particular, the event of 7-8 November 2014 was poorly predicted by operational NWP models which failed to reproduce the trajectory of the cyclone. Using a state-of-the-art storm-resolving model, we show that simulations with a grid spacing of approximately 1 km are able to reproduce the fine-scale structure of this MTLC. Simulations performed with grid spacing larger than 2.5 km fail to represent the features of the cyclone, while additional nested simulations with very high resolution (300 m) reveal the ability of the model to fully capture the internal structure of the cyclone. Thus, there is a noticeable convergence towards the observed trajectory of the cyclone with increasing resolution. Finally, a potential vorticity (PV) analysis highlights the mutual interaction between a PV streamer and a low-level PV maximum induced by convection. Only convection-resolving simulations, with a grid spacing smaller than 5 km, show a low-level maximum of PV which impacts the redistribution of PV at the higher atmospheric levels.
引用
收藏
页码:1598 / 1610
页数:13
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