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Convective destabilization by a tropopause fold diagnosed using potential‐vorticity inversion

 

作者: Morwenna Griffiths,   Alan J. Thorpe,   Keith A. Browning,  

 

期刊: Quarterly Journal of the Royal Meteorological Society  (WILEY Available online 2000)
卷期: Volume 126, issue 562  

页码: 125-144

 

ISSN:0035-9009

 

年代: 2000

 

DOI:10.1002/qj.49712656207

 

出版商: John Wiley&Sons, Ltd

 

关键词: Convection;Potential instability;Potential‐vorticity inversion;Tropopause fold

 

数据来源: WILEY

 

摘要:

AbstractThere is observational evidence to suggest that at the time tropopause folds in extra‐tropical cyclones are descending into the mid troposphere there is frequently a destablization of the lower troposphere to moist convection. Here we consider the dynamical reasons for such a linkage using so‐called potential vorticity (PV) attribution concepts. In particular PV inversion is used to find the wind shear attributable to the tropopause fold itself. Then this shear is used to quantify the tendency to generate regions of potential instability. For an observed case of a modest tropopause fold it is found that the PV anomaly contained in the tropopause fold contributed substantially to the instantaneous convective destabilization in the sense of increasing the potential instability. Indeed, at some locations, it overcame a tendency to stabilize by the atmosphere without the fold. On the other hand, only a fraction of the region with increased potential instability experienced sufficient large‐scale ascent to lead to convection and it remains to be seen whether folds in general make a significant contribution to the generation of potential instability that can actually be realized. The importance of tropopause folds, or indeed of tropopause depressions in general in the context of convection, is that their small horizontal scale has the potential to focus and amplify any convective destabilization locally. This may account for the localization of outbreaks of severe convective weather which it is important to forecast accurately. Currently numerical weather‐prediction models often do not handle these small scales very acc

 

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