Assessing characteristics of Mediterranean explosive cyclones for different data resolution

作者:Kouroutzoglou John; Flocas Helena A*; Simmonds Ian; Keay Kevin; Hatzaki Maria
来源:Theoretical and Applied Climatology, 2011, 105(1-2): 263-275.
DOI:10.1007/s00704-010-0390-8

摘要

A comparison of two objective climatologies of explosive cyclones in the Mediterranean region is performed. The results are derived from two different mean sea-level pressure reanalysis data resolutions, but from the same assimilation model, in order to quantify the pure impact of higher resolution on the identification and characteristics of explosive cyclones, when the assimilation model is the same. The explosive cyclones were identified with the aid of the Melbourne University automatic cyclone finding and tracking scheme over a 40-year period, using the 6-hourly analyses of ERA-40 mean sea-level pressure (MSLP) on: (a) 2.5 x 2.5 and (b) 1 x 1 latitude-longitude grid. The comparison of the two datasets revealed the significant role of the increase in spatial resolution of MSLP data on the identification and tracking process, and the number of the explosive cyclones in the high-resolution dataset is almost four times greater than the respective one in the lower resolution dataset. However, the comparison of explosive cyclone characteristics, including spatial and temporal variations of explosive deepening, revealed differences in the geographical distribution of the location of the maximum explosive deepening and average explosive cyclone Laplacian of the central pressure. These differences are due to the identification in the higher resolution set of smaller scale and secondary explosives along the strongly baroclinic northern Mediterranean boundaries, south of the Alps and the Pyrenees. Explosive deepening appears a bias to the daytime period from 12 to 18 Coordinated Universal Time (UTC) for both datasets, which is more prominent in the LR dataset. Statistically significant difference of pressure tendency between the two datasets appear for the daytime period from 06 to 12 UTC, accounting for better representation of orographic forcing in the HR dataset.

  • 出版日期2011-8