Ice crystal number concentration estimates ...
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation
Author(s) :
Sourdeval, Odran [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Leipziger Institut für Meteorologie [LIM]
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]
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Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Leipziger Institut für Meteorologie [LIM]
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]
Journal title :
Atmospheric Chemistry and Physics
Abbreviated title :
Atmos. Chem. Phys.
Volume number :
18
Pages :
14327-14350
Publisher :
Copernicus GmbH
Publication date :
2018-10-09
ISSN :
1680-7324
HAL domain(s) :
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
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
European Project :
Administrative institution(s) :
Université de Lille
CNRS
CNRS
Collections :
Research team(s) :
Interactions Rayonnement Nuages (IRN)
Submission date :
2023-01-06T12:54:55Z
2023-01-17T15:00:15Z
2023-01-17T15:00:15Z
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