Use of Large-Eddy simulations to design an adaptive sampling strategy to assess cumulus cloud heterogeneities by Remotely Piloted Aircraft

Autor: Fleur Couvreux, Gregory Roberts, Pierre Narvor, Simon Lacroix, Titouan Verdu, Nicolas Maury, Najda Villefranque, Gautier Hattenberger
Přispěvatelé: Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Scripps Institution of Oceanography (SIO), University of California [San Diego] (UC San Diego), University of California-University of California, Ecole Nationale de l'Aviation Civile (ENAC), Équipe Robotique et InteractionS (LAAS-RIS), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, LAboratoire PLasma et Conversion d'Energie (LAPLACE), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Scripps Institution of Oceanography (SIO - UC San Diego), University of California (UC)-University of California (UC), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), ANR-17-CE01-0003,NEPHELAE,Réseaux pour l'étude de l'entrainement et la microphysique des nuages par l'exploration adaptative(2017), Météo France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2021
Předmět:
Zdroj: Atmospheric Measurement Techniques, Vol 15, Pp 335-352 (2022)
Atmospheric Measurement Techniques
Atmospheric Measurement Techniques, 2022, 15 (2), pp.335-352. ⟨10.5194/amt-15-335-2022⟩
ISSN: 1867-1381
1867-8548
DOI: 10.5194/amt-2021-20
Popis: Trade wind cumulus clouds have a significant impact on the Earth's radiative balance due to their ubiquitous presence and significant coverage in subtropical regions. Many numerical studies and field campaigns have focused on better understanding the thermodynamic, microphysical, and macroscopic properties of cumulus clouds with ground-based and satellite remote sensing as well as in situ observations. Aircraft flights have provided a significant contribution, but their resolution remains limited by rectilinear transects and fragmented temporal data for individual clouds. To provide a higher spatial and temporal resolution, remotely piloted aircraft (RPA) can now be employed for direct observations using numerous technological advances to map the microphysical cloud structure and to study entrainment mixing. In fact, the numerical representation of mixing processes between a cloud and the surrounding air has been a key issue in model parameterizations for decades. To better study these mixing processes as well as their impacts on cloud microphysical properties, the paper aims to improve exploration strategies that can be implemented by a fleet of RPA. Here, we use a large-eddy simulation (LES) of shallow maritime cumulus clouds to design adaptive sampling strategies. An implementation of the RPA flight simulator within high-frequency LES outputs (every 5 s) allows tracking individual clouds. A rosette sampling strategy is used to explore clouds of different sizes that are static in time and space. The adaptive sampling carried out by these explorations is optimized using one or two RPA and with or without Gaussian process regression (GPR) mapping by comparing the results obtained with those of a reference simulation, in particular the total liquid water content (LWC) and the LWC distribution in a horizontal cross section. Also, a sensitivity test of length scale for GPR mapping is performed. The results of exploring a static cloud are then extended to a dynamic case of a cloud evolving with time to assess the application of this exploration strategy to study the evolution of cloud heterogeneities. While a single RPA coupled to GPR mapping remains insufficient to accurately reconstruct individual clouds, two RPA with GPR mapping adequately characterize cloud heterogeneities on scales small enough to quantify the variability of important parameters such as total LWC.
Databáze: OpenAIRE
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