Journal article

Preliminary signs of the initiation of deep convection by GNSS

Brenot H, Nem??ghaire J, Delobbe L, Clerbaux N, De Meutter P, Deckmyn A, Delcloo A, Frappez L, Van Roozendael M ...see all

Atmospheric Chemistry and Physics, vol. 13, issue 11 (2013) pp. 5425-5449

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Abstract

This study reports on the exploitation of GNSS (Global Navigation Satellite System) and a new potential application for weather forecasts and nowcasting. We focus on GPS observations (post-processing with a time resolution of 5 and 15 min and fast calculations with a time resolution of 5 min) and try to establish typical configurations of the water vapour field which characterise convective systems and particularly which supply precursors of their initiation are associated with deep convection. We show the critical role of GNSS horizontal gradients of the water vapour content to detect small scale structures of the troposphere (i. e. convective cells), and then we present our strategy to obtain typical water vapour configurations by GNSS called "H2O alert". These alerts are based on a dry/wet contrast taking place during a 30 min time window before the initiation of a convective system. GNSS observations have been assessed for the rainfall event of 28-29 June 2005 using data from the Belgian dense network (baseline from 5 to 30 km). To validate our GNSS H2O alerts, we use the detection of precipitation by C-band weather radar and thermal infrared radiance (cloud top temperature) of the 10.8-micrometers channel [Ch09] of SEVIRI instrument on Meteosat Second Generation. Using post-processed measurements, our H2O alerts obtain a score of about 80%. Final and ultra-rapid IGS (International GNSS Service) orbits have been tested and show equivalent results. Fast calculations (less than 10 min) have been processed for 29 June 2005 with a time resolution of 5 min. The mean bias (and standard deviation) between fast and reference post-processed ZTD (zenith total delay) and gradients are, respectively, 0.002 (± 0.008) m and 0.001 (± 0.004) m. The score obtained for the H2O alerts generated by fast calculations is 65%. © 2013 Author(s).

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Authors

  • H. Brenot

  • J. Nem??ghaire

  • L. Delobbe

  • N. Clerbaux

  • P. De Meutter

  • A. Deckmyn

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