Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

Tonttila, Juha; O’Connor, Ewan; Niemelä, Sami; Räisänen, Petri; Järvinen, Heikki

doi:10.5194/acp-11-9207-2011

Cited by 26 publications

(18 citation statements)

References 39 publications

(48 reference statements)

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“…The range of σ w shown in Fig. 4 is in good agreement with in situ measurements of vertical velocity at cloud base in marine stratocumulus (Peng et al, 2005;Guo et al, 2008), and continental regions (Fountoukis et al, 2007;Tonttila et al, 2011), showing σ w mostly between 0.2 and 1 m s −1 . However, global measurements of σ w have not been reported.…”

Section: Subgrid-scale Vertical Velocitysupporting

confidence: 71%

Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing System Model (GEOS-5)

et al. 2014

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Abstract. This work presents the development of a twomoment cloud microphysics scheme within version 5 of the NASA Goddard Earth Observing System (GEOS-5). The scheme includes the implementation of a comprehensive stratiform microphysics module, a new cloud coverage scheme that allows ice supersaturation, and a new microphysics module embedded within the moist convection parameterization of GEOS-5. Comprehensive physically based descriptions of ice nucleation, including homogeneous and heterogeneous freezing, and liquid droplet activation are implemented to describe the formation of cloud particles in stratiform clouds and convective cumulus. The effect of preexisting ice crystals on the formation of cirrus clouds is also accounted for. A new parameterization of the subgrid-scale vertical velocity distribution accounting for turbulence and gravity wave motion is also implemented. The new microphysics significantly improves the representation of liquid water and ice in GEOS-5. Evaluation of the model against satellite retrievals and in situ observations shows agreement of the simulated droplet and ice crystal effective radius, the ice mass mixing ratio and number concentration, and the relative humidity with respect to ice. When using the new microphysics, the fraction of condensate that remains as liquid follows a sigmoidal dependency with temperature, which is in agreement with observations and which fundamentally differs from the linear increase assumed in most models. The performance of the new microphysics in reproducing the observed total cloud fraction, longwave and shortwave cloud forcing, and total precipitation is similar to the operational version of GEOS-5 and in agreement with satellite retrievals. The new microphysics tends to underestimate the coverage of persistent low-level stratocumulus. Sensitivity studies showed that the simulated cloud properties are robust to moderate variation in cloud microphysical parameters. Significant sensitivity remains to variation in the dispersion of the ice crystal size distribution and the critical size for ice autoconversion. Despite these issues, the implementation of the new microphysics leads to a considerably improved and more realistic representation of cloud processes in GEOS-5, and allows the linkage of cloud properties to aerosol emissions.

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Section: Subgrid-scale Vertical Velocitysupporting

confidence: 71%

Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing System Model (GEOS-5)

et al. 2014

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“…However, the complexity of the vertical velocity structure in convective clouds makes the parameterization non-straightforward (Wang and Zhang, 2014). Observations show that in most of convective clouds the vertical velocity is highly variable, and consequently the detailed structure of convection cannot be resolved in many models (Kollias and Albrecht, 2010;Tonttila et al, 2011). Additionally, using the same parameterization of vertical velocity for different grid resolutions may result in different cloud and precipitation properties (Khairoutdinov et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Airborne volumetric Doppler radars have also been used to study the dynamic structure of convective clouds (e.g., Jorgensen and Smull, 1993;Hildebrand et al, 1996;Jorgensen et al, 2000). Remote sensing has the advantage of being able to measure the vertical velocity at different heights simultaneously (Tonttila et al, 2011), and some of the techniques can detect the strongest updraft cores in convective clouds (Heymsfield et al, 2010;Collis et al, 2013). Volumetric radars can also provide three-dimensional (3-D) structure of air motion in convective clouds Nicol et al, 2015;Jorgensen et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

“…In order to reasonably simulate convective clouds, the vertical air velocity must be parameterized reliably in numerical weather prediction models (NWPMs) and global circulation models (GCMs) (Donner et al, 2001;Tonttila et al, 2011;Wang and Zhang, 2014). However, the complexity of the vertical velocity structure in convective clouds makes the parameterization non-straightforward (Wang and Zhang, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Characteristics of vertical air motion in isolated convective clouds

et al. 2016

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Abstract. The vertical velocity and air mass flux in isolated convective clouds are statistically analyzed using aircraft in situ data collected from three field campaigns: High-Plains Cumulus (HiCu) conducted over the midlatitude High Plains, COnvective Precipitation Experiment (COPE) conducted in a midlatitude coastal area, and Ice in Clouds Experiment-Tropical (ICE-T) conducted over a tropical ocean. The results show that small-scale updrafts and downdrafts ( < 500 m in diameter) are frequently observed in the three field campaigns, and they make important contributions to the total air mass flux. The probability density functions (PDFs) and profiles of the observed vertical velocity are provided. The PDFs are exponentially distributed. The updrafts generally strengthen with height. Relatively strong updrafts (> 20 m s −1 ) were sampled in COPE and ICE-T. The observed downdrafts are stronger in HiCu and COPE than in ICE-T. The PDFs of the air mass flux are exponentially distributed as well. The observed maximum air mass flux in updrafts is of the order 10 4 kg m −1 s −1 . The observed air mass flux in the downdrafts is typically a few times smaller in magnitude than that in the updrafts. Since this study only deals with isolated convective clouds, and there are many limitations and sampling issues in aircraft in situ measurements, more observations are needed to better explore the vertical air motion in convective clouds.

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“…Shallow mixed-phase cloud layers (altocumulus, stratocumulus) have been used repeatedly for the study of the interaction between aerosols, cloud droplets, and in-cloud dynamics on the basis of in-situ or remote-sensing measurements (Fleishauer et al, 2002;Ansmann et al, 2009;Tonttila et al, 2011;Zhang et al, 2010a;Bühl et al, 2016) and extensive modeling studies (Korolev and Field, 2008;Pinsky et al, 2015). Their potential impact on Earth's climate has recently been as-30 sessed by Bourgeois et al (2016).…”

mentioning

confidence: 99%

Statistics of vertical velocities in supercooled cloud layers over Leipzig and Praia measured with Doppler lidar

Bühl

Seifert

Engelmann

et al. 2017

Preprint

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Abstract. This study presents statistics of vertical air velocity at the bases of supercooled shallow cloud layers separately for mixed-phase and liquid-only clouds. For the first time, this statistics is compared for clouds observed over a sub-tropical site at Cape Verde (14.9 • N, 26 Standard deviation of the vertical velocities at both sites was found to be 0.4 m s −1 and was also the same in pure-liquid and mixed-phase layers. Skewness groups around -0.4 for both sites, pointing to radiative cooling as the driver for the cloud turbulence. Occasionally, positive skewness in some 10 cloud layers indicated external drivers, e.g., gravity waves, for the turbulence. From the observed similarity in the vertical-velocity statistics derived at the base of supercooled liquid cloud layers at Praia and Leipzig it can be concluded that other factors besides cloud dynamics are responsible for the differences in ice formation efficiency reported previously for both sites.1 Atmos. Chem. Phys. Discuss.,

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Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations

Cited by 26 publications

References 39 publications

Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing System Model (GEOS-5)

Development of two-moment cloud microphysics for liquid and ice within the NASA Goddard Earth Observing System Model (GEOS-5)

Characteristics of vertical air motion in isolated convective clouds

Statistics of vertical velocities in supercooled cloud layers over Leipzig and Praia measured with Doppler lidar

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