4.6 Article

Comparison of a Manual and an Automated Tracking Method for Tibetan Plateau Vortices

期刊

ADVANCES IN ATMOSPHERIC SCIENCES
卷 35, 期 8, 页码 965-980

出版社

SCIENCE PRESS
DOI: 10.1007/s00376-018-7278-4

关键词

Tibetan Plateau Vortices; Yearbook of TPVs; TRACK; mesoscale cyclones; manual tracking; automated tracking

资金

  1. UK-China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China, Newton Fund [P100195]
  2. NERC [ncas10003] Funding Source: UKRI

向作者/读者索取更多资源

Tibetan Plateau vortices (TPVs) are mesoscale cyclones originating over the Tibetan Plateau (TP) during the extended summer season (April-September). Most TPVs stay on the TP, but a small number can move off the TP to the east. TPVs are known to be one of the main precipitation-bearing systems on the TP and moving-off TPVs have been associated with heavy precipitation and flooding downstream of the TP (e.g., in Sichuan province or over the Yangtze River Valley). Identifying and tracking TPVs is difficult because of their comparatively small horizontal extent (400-800 km) and the limited availability of soundings over the TP, which in turn constitutes a challenge for short-term predictions of TPV-related impacts and for the climatological study of TPVs. In this study k](i) manual tracking (MT) results using radiosonde data from a network over and downstream of the TP are compared with (ii) results obtained by an automated tracking (AT) algorithm applied to ERA-Interim data. Ten MT-TPV cases are selected based on method (i) and matched to and compared with the corresponding AT-TPVs identified with method (ii). Conversely k]ten AT-TPVs are selected and compared with the corresponding MT-TPVs. In general k]the comparison shows good results in cases where the underlying data are in good agreement k]but considerable differences are also seen in some cases and explained in terms of differences in the tracking methods k]data availability/coverage and disagreement between sounding and ERA-Interim data. Recommendations are given for future efforts in TPV detection and tracking k]including in an operational weather forecasting context.

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