Ice crystal number concentration estimates ...
Type de document :
Article dans une revue scientifique: Article original
URL permanente :
Titre :
Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation
Auteur(s) :
Sourdeval, Odran [Auteur]
Leipziger Institut für Meteorologie [LIM]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Gryspeerdt, Edward [Auteur]
Krämer, Martina [Auteur]
Goren, Tom [Auteur]
Delanoë, Julien [Auteur]
Afchine, Armin [Auteur]
Hemmer, Friederike [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Quaas, Johannes [Auteur]
Leipziger Institut für Meteorologie [LIM]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Gryspeerdt, Edward [Auteur]
Krämer, Martina [Auteur]
Goren, Tom [Auteur]
Delanoë, Julien [Auteur]
Afchine, Armin [Auteur]
Hemmer, Friederike [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Quaas, Johannes [Auteur]
Titre de la revue :
Atmospheric Chemistry and Physics
Nom court de la revue :
Atmos. Chem. Phys.
Numéro :
18
Pagination :
14327-14350
Éditeur :
Copernicus GmbH
Date de publication :
2018-10-09
ISSN :
1680-7324
Discipline(s) HAL :
Planète et Univers [physics]/Sciences de la Terre/Météorologie
Planète et Univers [physics]/Sciences de la Terre/Climatologie
Planète et Univers [physics]/Sciences de la Terre/Météorologie
Planète et Univers [physics]/Océan, Atmosphère
Planète et Univers [physics]/Sciences de la Terre/Climatologie
Planète et Univers [physics]/Sciences de la Terre/Météorologie
Planète et Univers [physics]/Océan, Atmosphère
Résumé en anglais : [en]
The number concentration of cloud particles is a key quantity for understanding aerosol–cloud interactions and describing clouds in climate and numerical weather prediction models. In contrast with recent advances for ...
Lire la suite >The number concentration of cloud particles is a key quantity for understanding aerosol–cloud interactions and describing clouds in climate and numerical weather prediction models. In contrast with recent advances for liquid clouds, few observational constraints exist regarding the ice crystal number concentration (Ni). This study investigates how combined lidar–radar measurements can be used to provide satellite estimates of Ni, using a methodology that constrains moments of a parameterized particle size distribution (PSD). The operational liDAR–raDAR (DARDAR) product serves as an existing base for this method, which focuses on ice clouds with temperatures Tc<−30 ∘C. Theoretical considerations demonstrate the capability for accurate retrievals of Ni, apart from a possible bias in the concentration in small crystals when Tc≳−50 ∘C, due to the assumption of a monomodal PSD shape in the current method. This is verified via a comparison of satellite estimates to coincident in situ measurements, which additionally demonstrates the sufficient sensitivity of lidar–radar observations to Ni. Following these results, satellite estimates of Ni are evaluated in the context of a case study and a preliminary climatological analysis based on 10 years of global data. Despite a lack of other large-scale references, this evaluation shows a reasonable physical consistency in Ni spatial distribution patterns. Notably, increases in Ni are found towards cold temperatures and, more significantly, in the presence of strong updrafts, such as those related to convective or orographic uplifts. Further evaluation and improvement of this method are necessary, although these results already constitute a first encouraging step towards large-scale observational constraints for Ni. Part 2 of this series uses this new dataset to examine the controls on Ni.Lire moins >
Lire la suite >The number concentration of cloud particles is a key quantity for understanding aerosol–cloud interactions and describing clouds in climate and numerical weather prediction models. In contrast with recent advances for liquid clouds, few observational constraints exist regarding the ice crystal number concentration (Ni). This study investigates how combined lidar–radar measurements can be used to provide satellite estimates of Ni, using a methodology that constrains moments of a parameterized particle size distribution (PSD). The operational liDAR–raDAR (DARDAR) product serves as an existing base for this method, which focuses on ice clouds with temperatures Tc<−30 ∘C. Theoretical considerations demonstrate the capability for accurate retrievals of Ni, apart from a possible bias in the concentration in small crystals when Tc≳−50 ∘C, due to the assumption of a monomodal PSD shape in the current method. This is verified via a comparison of satellite estimates to coincident in situ measurements, which additionally demonstrates the sufficient sensitivity of lidar–radar observations to Ni. Following these results, satellite estimates of Ni are evaluated in the context of a case study and a preliminary climatological analysis based on 10 years of global data. Despite a lack of other large-scale references, this evaluation shows a reasonable physical consistency in Ni spatial distribution patterns. Notably, increases in Ni are found towards cold temperatures and, more significantly, in the presence of strong updrafts, such as those related to convective or orographic uplifts. Further evaluation and improvement of this method are necessary, although these results already constitute a first encouraging step towards large-scale observational constraints for Ni. Part 2 of this series uses this new dataset to examine the controls on Ni.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Projet Européen :
Établissement(s) :
Université de Lille
CNRS
CNRS
Collections :
Équipe(s) de recherche :
Interactions Rayonnement Nuages (IRN)
Date de dépôt :
2023-01-06T12:54:55Z
2023-01-17T15:00:15Z
2023-01-17T15:00:15Z
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- Sourdeval-2018aa.pdf
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