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Auteur Umar Saeed |
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Adaptive estimation of the stable boundary layer height using combined Lidar and microwave radiometer observations / Umar Saeed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
[article]
Titre : Adaptive estimation of the stable boundary layer height using combined Lidar and microwave radiometer observations Type de document : Article/Communication Auteurs : Umar Saeed, Auteur ; Francesc Rocadenbosch, Auteur ; Susanne Crewell, Auteur Année de publication : 2016 Article en page(s) : pp 6895 - 6906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse de données
[Termes IGN] analyse diachronique
[Termes IGN] données lidar
[Termes IGN] radiomètre à hyperfréquence
[Termes IGN] Satellite Microwave RadiometerRésumé : (Auteur) A synergetic approach for the estimation of stable boundary layer height (SBLH) using lidar and microwave radiometer (MWR) data is presented. Vertical variance of the backscatter signal from a ceilometer is used as an indicator of the aerosol stratification in the nocturnal stable boundary layer. This hypothesis is supported by a statistical analysis over one month of observations. Thermodynamic information from the MWR-derived potential temperature is incorporated as coarse estimate of the SBLH. Data from the two instruments are adaptively assimilated by using an extended Kalman filter (EKF). A first test of the algorithm is performed by applying it to collocated Vaisala CT25K ceilometer and humidity and temperature profiler MWR data collected during the HD(CP)2 Observational Prototype Experiment (HOPE) campaign at Jülich, Germany. The application of the algorithm to different atmospheric scenarios reveals the superior performance of the EKF compared to a nonlinear least squares estimator, particularly in nonidealized conditions. Numéro de notice : A2016-920 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2586298 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2586298 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83324
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 6895 - 6906[article]