Turbulent dispersion in cloud-topped boundary layers

Verzijlbergh, Remco; Jonker, Harm J. J.; Heus, Thijs; Arellano, Jordi Vilà‐Guerau de

doi:10.5194/acp-9-1289-2009

Cited by 26 publications

(28 citation statements)

References 35 publications

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“…Furthermore, the radiosonde humidity sensor can introduce systematic errors in clod and dry or cloudy conditions (Seibert et al, 2000;Moradi et al, 2013). Refractivity and specific humidity can be dominated by the water vapour pressure variations at lower altitudes, and they decrease rapidly with height von Engeln and Teixeira, 2013). The breakpoint of the profile usually appears at a low altitude, which leads to the shallow h values using these two methods.…”

Section: Reasons For Discrepancies Among Different Methodsmentioning

confidence: 99%

“…The stable layer within the cloud can act as a turbulence barrier to the air pollution and inhibit turbulence under the stable layer. Nonetheless, clouds can also encourage pollutant dispersion and enhance mixing due to the cloud-venting (Cotton et al, 1995;Verzijlbergh et al, 2009). The vertical motion of pollutants mainly depends on the atmospheric stability in the cloud.…”

Section: Reasons For Discrepancies Among Different Methodsmentioning

confidence: 99%

“…We suggest that the presence of clouds is an important factor that reduces the agreement of different methods. In the presence of clouds, the humidity-based methods may identify the cloud top as the top of mixing layer due to the large negative humidity gradient there (von Engeln and Teixeira, 2013). For example, the RH method combines the temperature and specific humidity to enlarge both gradients (von Engeln and Teixeira, 2013).…”

Section: Reasons For Discrepancies Among Different Methodsmentioning

confidence: 99%

“…cloud or fog) (Ferrero et al, 2010;McGrath-Spangler and Denning, 2012). Many methods have been proposed to estimate h from the temperature and atmospheric composition profiles (Seibert et al, 2000;Basha and Ratnam, 2009;Seidel et al, 2010;Ferrero et al, 2011;Seidel et al, 2012); however, inconsistencies exist among the methods (Seidel et al, 2010;von Engeln and Teixeira, 2013). Seidel et al (2010) compared h values that were derived from the existing methods using radiosonde data and found substantial differences among the various methods.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of atmospheric mixing layer height from radiosonde data

Wang

2014

Atmos. Meas. Tech.

104

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Abstract. Mixing layer height (h) is an important parameter for understanding the transport process in the troposphere, air pollution, weather and climate change. Many methods have been proposed to determine h by identifying the turning point of the radiosonde profile. However, substantial differences have been observed in the existing methods (e.g. the potential temperature (θ ), relative humidity (RH), specific humidity (q) and atmospheric refractivity (N) methods). These differences are associated with the inconsistency of the temperature and humidity profiles in a boundary layer that is not well mixed, the changing measurability of the specific humidity and refractivity with height, the measurement error of humidity instruments within clouds, and the general existence of clouds. This study proposes a method to integrate the information of temperature, humidity and cloud to generate a consistent estimate of h. We apply this method to high vertical resolution (∼ 30 m) radiosonde data that were collected at 79 stations over North America during the period from 1998 to 2008. The data are obtained from the Stratospheric Processes and their Role in Climate Data Center (SPARC). The results show good agreement with those from N method as the information of temperature and humidity contained in N ; however, cloud effects that are included in our method increased the reliability of our estimated h. From 1988 to 2008, the climatological h over North America was 1675 ± 303 m with a strong east-west gradient: higher values (generally greater than 1800 m) occurred over the Midwest US, and lower values (usually less than 1400 m) occurred over Alaska and the US West Coast.

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Section: Reasons For Discrepancies Among Different Methodsmentioning

confidence: 99%

Section: Reasons For Discrepancies Among Different Methodsmentioning

confidence: 99%

Section: Reasons For Discrepancies Among Different Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of atmospheric mixing layer height from radiosonde data

Wang

2014

Atmos. Meas. Tech.

104

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“…1 of Possner et al, 2014). The initial and lateral boundary conditions for the dynamical fields are provided by the ECMWF Interim Reanalysis (Uppala et al, 2005;Dee et al, 2011). For the aerosol tracers, the climatological means for January (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) obtained in ECHAM-HAM simulations are prescribed as initial and lateral boundary conditions.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Real-case simulations of aerosol–cloud interactions in ship tracks over the Bay of Biscay

et al. 2015

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Abstract. Ship tracks provide an ideal test bed for studying aerosol-cloud interactions (ACIs) and for evaluating their representation in model parameterisations. Regional modelling can be of particular use for this task, as this approach provides sufficient resolution to resolve the structure of the produced track including their meteorological environment whilst relying on the same formulations of parameterisations as many general circulation models. In this work we simulate a particular case of ship tracks embedded in an optically thin stratus cloud sheet which was observed by a polar orbiting satellite at 12:00 UTC on 26 January 2003 around the Bay of Biscay.The simulations, which include moving ship emissions, show that the model is indeed able to capture the structure of the track at a horizontal grid spacing of 2 km and to qualitatively capture the observed cloud response in all simulations performed. At least a doubling of the cloud optical thickness was simulated in all simulations together with an increase in cloud droplet number concentration by about 40 cm −3 (300 %) and decrease in effective radius by about 5 µm (40 %). Furthermore, the ship emissions lead to an increase in liquid water path in at least 25 % of the track regions.We are confident in the model's ability to capture key processes of ship track formation. However, it was found that realistic ship emissions lead to unrealistic aerosol perturbations near the source regions within the simulated tracks due to grid-scale dilution and homogeneity.Combining the regional-modelling approach with comprehensive field studies could likely improve our understanding of the sensitivities and biases in ACI parameterisations, and could therefore help to constrain global ACI estimates, which strongly rely on these parameterisations.

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Entrainment and detrainment in cumulus convection: an overview

Rooy

Bechtold

Fröhlich

et al. 2012

Quart J Royal Meteoro Soc

304

256

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Entrainment and detrainment processes have been recognised for a long time as key processes for cumulus convection and have recently witnessed a regrowth of interest mainly due to the capability of large-eddy simulations (LES) to diagnose these processes in more detail. This article has a twofold purpose. Firstly, it provides a historical overview of the past research on these mixing processes, and secondly, it highlights more recent important developments. These include both fundamental process studies using LES aiming to improve our understanding of the mixing process, but also more practical studies targeted toward an improved parametrised representation of entrainment and detrainment in large-scale models. A highlight of the fundamental studies resolves a long-lasting controversy by showing that lateral entrainment is the dominant mixing mechanism in comparison with the cloud-top entrainment in shallow cumulus convection. The more practical studies provide a wide variety of new parametrisations with sometimes conflicting approaches to the way in which the effect of the free tropospheric humidity on the lateral mixing is taken into account. An important new insight that will be highlighted is that, despite the focus in the literature on entrainment, it appears that it is rather the detrainment process that determines the vertical structure of the convection in general and the mass flux especially. Finally, in order to speed up progress and stimulate convergence in future parametrisations, stronger and more systematic use of LES is advocated.

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Turbulent dispersion in cloud-topped boundary layers

Cited by 26 publications

References 35 publications

Estimation of atmospheric mixing layer height from radiosonde data

Estimation of atmospheric mixing layer height from radiosonde data

Real-case simulations of aerosol–cloud interactions in ship tracks over the Bay of Biscay

Entrainment and detrainment in cumulus convection: an overview

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