Details

Autor(en) / Beteiligte

• Price, J. D.
• Vosper, S.
• Brown, A.
• Ross, A.
• Clark, P.
• Davies, F.
• Horlacher, V.
• Claxton, B.
• McGregor, J. R.
• Hoare, J. S.
• Jemmett-Smith, B.
• Sheridan, P.

Titel

COLPEX: Field and Numerical Studies over a Region of Small Hills

Ist Teil von

• Bulletin of the American Meteorological Society, 2011-12, Vol.92 (12), p.1636-1650

Ort / Verlag

Boston: American Meteorological Society

Erscheinungsjahr

2011

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• During stable nighttime periods, large variations in temperature and visibility often occur over short distances in regions of only moderate topography. These are of great practical significance and yet pose major forecasting challenges because of a lack of detailed understanding of the processes involved and because crucial topographic variations are often not resolved in current forecast models. This paper describes a field and numerical modeling campaign, Cold-Air Pooling Experiment (COLPEX), which addresses many of the issues. The observational campaign was run for 15 months in Shropshire, United Kingdom, in a region of small hills and valleys with typical ridge–valley heights of 75–150 m and valley widths of 1–3 km. The instrumentation consisted of three sites with instrumented flux towers, a Doppler lidar, and a network of 30 simpler meteorological stations. Further instrumentation was deployed during intensive observation periods including radiosonde launches from two sites, a cloud droplet probe, aerosol monitoring equipment, and an instrumented car. Some initial results from the observations are presented illustrating the range of conditions encountered. The modeling phase of COLPEX includes use of the Met Office Unified Model at 100-m resolution, and some brief results for a simulation of an intensive observation period are presented showing the model capturing a cold-pool event. As well as aiding interpretation of the observations, results from this study are expected to inform the design of future generations of operational forecasting systems