scholarly journals A Model Intercomparison of CCN-Limited Tenuous Clouds in the High Arctic

2017 ◽  
Author(s):  
Robin G. Stevens ◽  
Katharina Loewe ◽  
Christopher Dearden ◽  
Antonios Dimitrelos ◽  
Anna Possner ◽  
...  
Keyword(s):  
Water Content ◽  
Size Distribution ◽  
Liquid Water ◽  
Atmospheric Stability ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
High Arctic ◽  
Model Intercomparison ◽  
Cloud Droplet Size Distribution

Abstract. We perform a model intercomparison of summertime high Arctic (> 80 N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm−3. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNC) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts on autoconversion rates. Our results therefore suggest that properly estimating aerosol–cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in-situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN-limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures and atmospheric stability need to be considered for weather and climate predictions in this region.

scholarly journals A model intercomparison of CCN-limited tenuous clouds in the high Arctic

2018 ◽  
Vol 18 (15) ◽  
pp. 11041-11071 ◽  
Author(s):  
Robin G. Stevens ◽  
Katharina Loewe ◽  
Christopher Dearden ◽  
Antonios Dimitrelos ◽  
Anna Possner ◽  
...  
Keyword(s):  
Water Content ◽  
Size Distribution ◽  
Liquid Water ◽  
Atmospheric Stability ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
High Arctic ◽  
Model Intercomparison ◽  
Cloud Droplet Size Distribution

Abstract. We perform a model intercomparison of summertime high Arctic (> 80∘ N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm−3. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts autoconversion rates. Our results therefore suggest that properly estimating aerosol–cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures, and atmospheric stability need to be considered for weather and climate predictions in this region.

scholarly journals The relative dispersion of cloud droplets: its robustness with respect to key cloud properties

2014 ◽  
Vol 14 (8) ◽  
pp. 11153-11176
Author(s):  
E. Tas ◽  
A. Teller ◽  
O. Altaratz ◽  
D. Axisa ◽  
R. Bruintjes ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Thermodynamic Characteristics ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Relative Dispersion ◽  
Distribution Width ◽  
Airborne Measurements ◽  
Cloud Droplet Size Distribution

Abstract. The relative dispersion (ε) of cloud droplet size distribution, defined as the ratio between cloud droplet size distribution width (σ) and cloud droplet average radius (⟨r⟩), is investigated using airborne measurements of warm cumulus clouds. The data is used to study the relation of ε with microphysical and thermodynamic characteristics of the clouds. The results show that ε is constrained with average values in the range of ~0.25–0.35. It is shown that ε is not correlated with the cloud droplet concentration or with the Liquid Water Content (LWC). However, the relative dispersion variance (related to the third moment of the droplets distribution) shows sensitivity to the droplets' concentration and LWC, suggesting smaller ε variability in more adiabatic regions in the clouds. A clear criterion for the usage of the in situ airborne measurements data for statistical moments' calculations is suggested.

Turbulent transport and deposition of fog droplets in the Central Namib

2020 ◽  
Author(s):  
Robert Spirig ◽  
Christian Feigenwinter ◽  
Roland Vogt
Keyword(s):  
Water Content ◽  
Sea Level ◽  
Liquid Water ◽  
Turbulent Transport ◽  
Water Flux ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Field Measurements ◽  
Liquid Water Content ◽  
Fog Water

<p>Regular, nocturnal fog is a defining and seasonally varying feature in the Namib desert. Historical observations were limited to the binary measure of fog occurrence and the concurrent fog water input is quantified only since 2014 via the FogNet using Juvik fog collectors. This installation opened new avenues of research such as the efficiency of the transport mechanism, sampling and spatial variation thereof. An eddy covariance setup of a cloud droplet probe and collocated sonic(s) was installed in turns at the two FogNet stations Vogelfederberg (23.10°S, 15.03°E, 515 m above sea level) and Gobabeb (23.56°S, 15.04°E, 406 m above sea level) for 2 years in the frame of the Namib Fog Life Cycle Analysis Field Measurements (NaFoLiCA-F) project. With this setup, we gathered duration, droplet size distribution, droplet concentration, liquid water content, turbulent liquid water flux and the fog water input via the Juvik fog collector with a total of over 150 fog events. We found that fog appears suddenly and front-like as seen by an increase of droplet numbers by several magnitudes and dissolves more gradually towards the morning. All droplet classes of the resolved range of 2 to 50 µm are present, but at the Vogelfederberg with around 2 to 3 times larger fog water input, the mean and median of the distribution are lower due to comparably fewer large droplets. Liquid water fluxes at both sites resulted in a net gain for the surface but the spatial discrepancy between fog water input recorded by fog collectors and the liquid water content indicates that drizzle, i.e. droplets outside the resolved range, may contribute to the larger total water deposition at Vogelfederberg.</p>

scholarly journals Parametric representation of the cloud droplet spectra for LES warm bulk microphysical schemes

2010 ◽  
Vol 10 (10) ◽  
pp. 4835-4848 ◽  
Author(s):  
O. Geoffroy ◽  
J.-L. Brenguier ◽  
F. Burnet
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Tuning Parameter ◽  
Parametric Function ◽  
Generalized Gamma ◽  
Parametric Functions ◽  
Generalized Gamma Function

Abstract. Parametric functions are currently used to represent droplet spectra in clouds and to develop bulk parameterizations of the microphysical processes and of their interactions with radiation. The most frequently used parametric functions are the Lognormal and the Generalized Gamma which have three and four independent parameters, respectively. In a bulk parameterization, two parameters are constrained by the total droplet number concentration and the liquid water content. In the Generalized Gamma function, one parameter is specified a priori, and the fourth one, like the third parameter of the Lognormal function, shall be tuned, for the parametric function to statistically best fit observed droplet spectra. These parametric functions are evaluated here using droplet spectra collected in non-or slightly precipitating stratocumulus and shallow cumulus. Optimum values of the tuning parameters are derived by minimizing either the absolute or the relative error for successively the first, second, fifth, and sixth moments of the droplet size distribution. A trade-off value is also proposed that minimizes both absolute and relative errors for the four moments concomitantly. Finally, a parameterization is proposed in which the tuning parameter depends on the liquid water content. This approach significantly improves the fit for the smallest and largest values of the moments.

scholarly journals Parametric representation of the cloud droplet spectra for LES warm bulk microphysical schemes

2009 ◽  
Vol 9 (4) ◽  
pp. 17633-17663 ◽  
Author(s):  
O. Geoffroy ◽  
J.-L. Brenguier ◽  
F. Burnet
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Tuning Parameter ◽  
Parametric Function ◽  
Generalized Gamma ◽  
Parametric Functions ◽  
Generalized Gamma Function

Abstract. Parametric functions are currently used to represent droplet spectra in clouds and to develop bulk parameterizations of the microphysical processes and of their interactions with radiation. The most frequently used parametric functions are the Lognormal and the Generalized Gamma which have three and four independent parameters, respectively. In a bulk parameterization, two parameters are constrained by the total droplet number concentration and the liquid water content. In the Generalized Gamma function, one parameter is specified a priori, and the fourth one, like the third parameter of the Lognormal function, shall be tuned, for the parametric function to statistically best fit observed droplet spectra. These parametric functions are evaluated here using droplet spectra collected in non-or slightly precipitating stratocumulus and shallow cumulus. Optimum values of the tuning parameters are derived by minimizing either the absolute or the relative error for successively the first, second, fifth, and sixth moments of the droplet size distribution. A trade-off value is also proposed that minimizes both absolute and relative errors for the four moments concomitantly. Finally, a parameterization is proposed in which the tuning parameter depends on the liquid water content. This approach significantly improves the fit for the smallest and largest values of the moments.

scholarly journals The relative dispersion of cloud droplets: its robustness with respect to key cloud properties

2015 ◽  
Vol 15 (4) ◽  
pp. 2009-2017 ◽  
Author(s):  
E. Tas ◽  
A. Teller ◽  
O. Altaratz ◽  
D. Axisa ◽  
R. Bruintjes ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Measurement Data ◽  
Thermodynamic Characteristics ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Relative Dispersion ◽  
Droplet Concentration ◽  
Cloud Droplet Size Distribution

Abstract. Flight data measured in warm convective clouds near Istanbul in June 2008 were used to investigate the relative dispersion of cloud droplet size distribution. The relative dispersion (ϵ), defined as the ratio between the standard deviation (σ) of the cloud droplet size distribution and cloud droplet average radius (⟨r⟩), is a key factor in regional and global models. The relationship between ε and the clouds' microphysical and thermodynamic characteristics is examined. The results show that ε is constrained with average values in the range of ~0.25–0.35. ε is shown not to be correlated with cloud droplet concentration or liquid water content (LWC). However, ε variance is shown to be sensitive to droplet concentration and LWC, suggesting smaller variability of ϵ in the clouds' most adiabatic regions. A criterion for use of in situ airborne measurement data for calculations of statistical moments (used in bulk microphysical schemes), based on the evaluation of ϵ, is suggested.

scholarly journals Fog Droplet Size Distribution and the Interaction between Fog Droplets and Fine Particles during Dense Fog in Tianjin, China

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 258 ◽  
Author(s):  
Qing Liu ◽  
Bingui Wu ◽  
Zhaoyu Wang ◽  
Tianyi Hao
Keyword(s):  
Water Content ◽  
Size Distribution ◽  
Droplet Size ◽  
Liquid Water ◽  
Fine Particles ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Average Spectrum ◽  
Dense Fog ◽  
Scavenging Efficiency

From November 2016 to January 2017, there were large-scale dense fog processes in Tianjin area on the west coast of Bohai Bay, China, even strong dense fog with visibility less than 50 m occurred. Based on the observation data of fog droplet spectrum monitor, visibility sensor, environmental particle monitoring equipment and meteorological automatic station, the characteristics of fog droplet size distribution and the interaction between the fog droplets and fine particles during dense fog events were analyzed. The results show following characteristics: (1) The average concentration of fog droplets (Na), the average liquid water content (La) and the maximum liquid water content (Lmax) in the strong dense fog process are larger than those in the dense fog. The average spectrum of fog droplet size distribution conforms to Junge distribution, and they are all broad-spectrum fog with a spectrum width of about 45 μm. The average spectrum is similar to the dense fog of heavily industrialized inland in the world. (2) The maximum of fog droplet diameter during the formation stage have a good indication for the outbreak of strong dense fog. (3) The mass concentration of PM2.5 (CPM2.5) is ranged from 121–375 μg/m3, and the interaction between fog droplets and fine particles is analyzed. During the formation, development and maturity stages, fog process can scavenge atmospheric fine particles, and the scavenging efficiency of PM2.5 is more remarkable than PM10. When CPM2.5 does not exceed 350 μg/m3, the increase in the concentration of fine particles is conducive to the rapid growth of fog droplets and the sharp drop of visibility. However, when CPM2.5 exceeds the critical value, the increase has a negative feedback effect on the development of the fog process. More investigations and cases are necessary to fully assess the mechanisms related to the dense fog events in Tianjin area and further analysis will be done.

scholarly journals A depolarisation lidar based method for the determination of liquid-cloud microphysical properties

2014 ◽  
Vol 7 (9) ◽  
pp. 9917-9992 ◽  
Author(s):  
D. P. Donovan ◽  
H. Klein Baltink ◽  
J. S. Henzing ◽  
S. R. de Roode ◽  
A. P. Siebesma
Keyword(s):  
Water Content ◽  
Multiple Scattering ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Optimal Estimation ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Base Region ◽  
Large Eddy Simulation Model ◽  
Inversion Procedure

Abstract. The fact that polarisation lidars measure a depolarisation signal in liquid clouds due to the occurrence of multiple-scattering is well-known. The degree of measured depolarisation depends on the lidar characteristics (e.g. wavelength and receiver field-of-view) as well as the cloud macrophysical (e.g. liquid water content) and microphysical (e.g. effective radius) properties. Efforts seeking to use depolarisation information in a quantitative manner to retrieve cloud properties have been undertaken with, arguably, limited practical success. In this work we present a retrieval procedure applicable to clouds with (quasi-)linear liquid water content (LWC) profiles and (quasi-)constant cloud droplet number density in the cloud base region. Thus limiting the applicability of the procedure allows us to reduce the cloud variables to two parameters (namely the derivative of the liquid water content with height and the extinction at a fixed distance above cloud-base). This simplification, in turn, allows us to employ a fast and robust optimal-estimation inversion using pre-computed look-up-tables produced using extensive lidar Monte-Carlo multiple-scattering simulations. In this paper, we describe the theory behind the inversion procedure and successfully apply it to simulated observations based on large-eddy simulation model output. The inversion procedure is then applied to actual depolarisation lidar data corresponding to a range of cases taken from the Cabauw measurement site in the central Netherlands. The lidar results were then used to predict the corresponding cloud-base region radar reflectivities. In non-drizzling condition, it was found that the lidar inversion results can be used to predict the observed radar reflectivities with an accuracy within the radar calibration uncertainty (2–3 dBZ). This result strongly supports the accuracy of the lidar inversion results. Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud droplet number densities are also presented and discussed. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements.

scholarly journals Aerosol-landscape-cloud interaction: Signatures of topography effect on cloud droplet formation

2016 ◽  
Author(s):  
Sami Romakkaniemi ◽  
Zubair Maalick ◽  
Antti Hellsten ◽  
Antti Ruuskanen ◽  
Olli Väisänen ◽  
...  
Keyword(s):  
Liquid Water ◽  
Measurement Data ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Droplet Formation ◽  
Cloud Base ◽  
Topography Effect ◽  
Boreal Environment ◽  
The Hill

Abstract. Long-term in situ measurements of aerosol-cloud interactions are usually performed in measurement stations residing on hills, mountains, or high towers. In such conditions, the surface topography of the surrounding area can affect the measured cloud droplet distributions by increasing turbulence or causing orographic flows and thus the observations might not be representative for a larger scale. The objective of this work is to analyse, how the local topography affects the observations at Puijo measurement station, which is located in the 75 m high Puijo tower, which itself stands on a 150 m high hill. The analysis of the measurement data shows that the observed cloud droplet number concentration mainly depends on the CCN concentration. However, when the wind direction aligns with the direction of the steepest slope of the hill, a clear topography effect is observed. This finding was further analysed by simulating 3D flow fields around the station and by performing trajectory ensemble modelling of aerosol- and wind-dependent cloud droplet formation. The results showed that in typical conditions, with geostrophic winds of about 10 m s−1, the hill can cause updrafts of up to 1 m s−1 in the air parcels arriving at the station. This is enough to produce in-cloud supersaturations higher than typically found at the cloud base (SS of ~ 0.2 %), and thus additional cloud droplets may form inside the cloud. In the observations, this is seen in the form of a bi-modal cloud droplet size distribution. The effect is strongest with high winds across the steepest slope of the hill and with low liquid water contents, and its relative importance quickly decreases as these conditions are relaxed. We therefore conclude that, after careful screening for wind speed and liquid water content, the observations at Puijo measurement station can be considered representative for clouds in a boreal environment.

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