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Daniela Nowak, Dominique Ruffieux, Judith L. Agnew, and Laurent Vuilleumier


The performance of the boundary determination of fog and low stratiform cloud layers with data from a frequency-modulated continuous-wave (FMCW) cloud radar and a Vaisala ceilometer is assessed. During wintertime stable episodes, fog and low stratiform cloud layers often occur in the Swiss Plateau, where the aerological station of Payerne, Switzerland, is located. During the international COST 720 Temperature, Humidity, and Cloud (TUC) profiling experiment in winter 2003/04, both a cloud radar and a ceilometer were operated in parallel, among other profiling instruments. Human eye observations (“synops”) and temperature and humidity profiles from radiosoundings were used as reference for the validation. In addition, two case studies were chosen to demonstrate the possibilities and limitations of such ground-based remote sensing systems in determining low clouds. In these case studies the cloud boundaries determined by ceilometer and cloud radar were furthermore compared with wind profiler signal-to-noise ratio time series. Under dry conditions, cloud-base and -top detection was possible in 59% and 69% of the cases for low stratus clouds and fog situations, respectively. When cases with any form of precipitation were included, performances were reduced with detection rates of 41% and 63%, respectively. The combination of ceilometer and cloud radar has the potential for providing the base and top of a cloud layer with optimal efficiency in the continuous operational mode. The cloud-top height determination by the cloud radar was compared with cloud-top heights detected using radiosounding humidity profiles. The average height difference between the radiosounding and cloud radar determination of the cloud upper boundary is 53 ± 32 m.

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Keith A. Browning, Alan M. Blyth, Peter A. Clark, Ulrich Corsmeier, Cyril J. Morcrette, Judith L. Agnew, Sue P. Ballard, Dave Bamber, Christian Barthlott, Lindsay J. Bennett, Karl M. Beswick, Mark Bitter, Karen E. Bozier, Barbara J. Brooks, Chris G. Collier, Fay Davies, Bernhard Deny, Mark A. Dixon, Thomas Feuerle, Richard M. Forbes, Catherine Gaffard, Malcolm D. Gray, Rolf Hankers, Tim J. Hewison, Norbert Kalthoff, Samiro Khodayar, Martin Kohler, Christoph Kottmeier, Stephan Kraut, Michael Kunz, Darcy N. Ladd, Humphrey W. Lean, Jürgen Lenfant, Zhihong Li, John Marsham, James McGregor, Stephan D. Mobbs, John Nicol, Emily Norton, Douglas J. Parker, Felicity Perry, Markus Ramatschi, Hugo M. A. Ricketts, Nigel M. Roberts, Andrew Russell, Helmut Schulz, Elizabeth C. Slack, Geraint Vaughan, Joe Waight, David P. Wareing, Robert J. Watson, Ann R. Webb, and Andreas Wieser

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model.

A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP.

This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

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