Jacob, Marek, Kollias, Pavlos, Ament, Felix, Schemann, Vera and Crewell, Susanne (2020). Multilayer cloud conditions in trade wind shallow cumulus - confronting two ICON model derivatives with airborne observations. Geosci. Model Dev., 13 (11). S. 5757 - 5778. GOTTINGEN: COPERNICUS GESELLSCHAFT MBH. ISSN 1991-9603

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Abstract

Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Non-hydrostatic) model simulations at kilometer and hectometer scales. The clouds were observed by an airborne nadir-pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model output into the observational space for considering instrument-specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10(-7) kg kg(-1) are detectable by the lidar, whereas the radar is primarily sensitive to the rain category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifting condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow stratiform outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are sensed differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at a kilometer scale barely reproduces the cloud modes and shows most cloud tops being slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parameterizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle better represent cloud radiative effects and water cycle.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Jacob, MarekUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kollias, PavlosUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Ament, FelixUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schemann, VeraUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Crewell, SusanneUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-310762
DOI: 10.5194/gmd-13-5757-2020
Journal or Publication Title: Geosci. Model Dev.
Volume: 13
Number: 11
Page Range: S. 5757 - 5778
Date: 2020
Publisher: COPERNICUS GESELLSCHAFT MBH
Place of Publication: GOTTINGEN
ISSN: 1991-9603
Language: English
Faculty: Faculty of Mathematics and Natural Sciences
Divisions: Faculty of Mathematics and Natural Sciences > Department of Geosciences > Institute for Geophysics and Meteorology
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
MICROWAVE RADIOMETER; RADAR; STRATOCUMULUS; AGGREGATION; SIMULATIONS; CONVECTION; ATLANTIC; PACKAGEMultiple languages
Geosciences, MultidisciplinaryMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/31076

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