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Low-Atmosphere Drifting Balloons: Platforms for Environment Monitoring and Forecast Improvement

Abstract : Abstract Balloons are one of the key observing platforms for the atmosphere. Radiosounding is the most commonly used technique and provides over a thousand vertical profiles worldwide every day. These data represent an essential cornerstone of data assimilation for numerical weather prediction systems. Although less common (but equally interesting for the in situ investigation of the atmosphere), drifting boundary layer pressurized balloons (BLPBs) offer rare observational skills. These balloons collect meteorological and/or chemical measurements at isopycnal height as they drift in a quasi-Lagrangian way. The BLPB system presented in this paper was developed by the French Space Agency [Centre National d’Études Spatiales (CNES)] and has been used in field experiments focusing on precipitation in Africa [African Monsoon Multiscale Analysis (AMMA)] and the Mediterranean [Hydrological Cycle in the Mediterranean Experiment (HyMeX)] as well as on air pollution in India [Indian Ocean Experiment (INDOEX)] and the Mediterranean [Transport a Longue Distance et Qualite de l’Air dans le bassin Méditerraneen (TRAQA) and Chemistry–Aerosol Mediterranean Experiment (ChArMeX)]. One important advantage of BLPBs is their capability to explore the lowest layers of the atmosphere above the oceans, areas that remain difficult to access. BLPB had a leading role in a complex adaptive observation system for the forecast of severe precipitation events. These balloons collected data in the marine environment of convective systems, which were assimilated in real time to improve the knowledge of the state of the atmosphere in the numerical prediction models of Météo-France.
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Submitted on : Wednesday, September 29, 2021 - 9:04:17 AM
Last modification on : Wednesday, June 1, 2022 - 3:54:27 AM
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A. Doerenbecher, P Basdevant, P. Drobinski, P. Durand, F Fesquet, et al.. Low-Atmosphere Drifting Balloons: Platforms for Environment Monitoring and Forecast Improvement. Bulletin of the American Meteorological Society, American Meteorological Society, 2016, 97 (9), pp.1583-1599. ⟨10.1175/BAMS-D-14-00182.1⟩. ⟨insu-03357812⟩



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