scholarly journals Parameterization of the Autoconversion Process. Part II: Generalization of Sundqvist-Type Parameterizations

2006 ◽  
Vol 63 (3) ◽  
pp. 1103-1109 ◽  
Author(s):  
Yangang Liu ◽  
Peter H. Daum ◽  
R. McGraw ◽  
R. Wood
Keyword(s):  
Critical Radius ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Smooth Transition ◽  
Relative Dispersion ◽  
Droplet Concentration ◽  
Single Function ◽  
Cloud Droplet Size Distribution ◽  
Part Structure

Abstract Existing Sundqvist-type parameterizations, which only consider dependence of the autoconversion rate on cloud liquid water content, are generalized to explicitly account for the droplet concentration and relative dispersion of the cloud droplet size distribution as well. The generalized Sundqvist-type parameterization includes the more commonly used Kessler-type parameterization as a special case, unifying the two different types of parameterizations for the autoconversion rate. The generalized Sundqvist-type parameterization is identical with the Kessler-type parameterization presented in Part I beyond the autoconversion threshold, but exhibits a more realistic, smooth transition in the vicinity of the autoconversion threshold (threshold behavior) in contrast to the discontinuously abrupt transition embodied in the Kessler-type parameterization. A new Sundqvist-type parameterization is further derived by applying the expression for the critical radius derived from the kinetic potential theory to the generalized Sundqvist-type parameterization. The new parameterization eliminates the need for defining the driving radius and for prescribing the critical radius associated with Kessler-type parameterizations. The two-part structure of the autoconversion process raises questions regarding model-based empirical parameterizations obtained by fitting simulation results from detailed collection models with a single function.

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 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.

scholarly journals An Observational Study on Cloud Spectral Width in North China

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 109 ◽  
Author(s):  
Yuan Wang ◽  
Shengjie Niu ◽  
Chunsong Lu ◽  
Yangang Liu ◽  
Jingyi Chen ◽  
...  
Keyword(s):  
Size Range ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Spectral Width ◽  
Relative Dispersion ◽  
Cloud Base ◽  
Cloud Droplets ◽  
Factors Affecting ◽  
Cloud Droplet Size Distribution ◽  
Stratiform Clouds

Cloud droplet size distribution (CDSD) is a critical characteristic for a number of processes related to clouds, considering that cloud droplets are formed in different sizes above the cloud-base. This paper analyzes the in-situ aircraft measurements of CDSDs and aerosol concentration ( N a ) performed in stratiform clouds in Hebei, China, in 2015 to reveal the characteristics of cloud spectral width, commonly known as relative dispersion ( ε , ratio of standard deviation (σ) to mean radius (r) of the CDSD). A new algorithm is developed to calculate the contributions of droplets of different sizes to ε . It is found that small droplets with the size range of 1 to 5.5 μm and medium droplets with the size range of 5.5 to 10 μm are the major contributors to ε, and the medium droplets generally dominate the change of ε. The variation of ε with N a can be well explained by comparing the normalized changes of σ and r ( k σ / σ and k r / r ), rather than k σ and k r only ( k σ is Δσ/Δ N a and k r is Δr/Δ N a ). From the perspective of external factors affecting ε change, the effects of N a and condensation are examined. It is found that ε increases initially and decreases afterward as N a increases, and “condensational broadening” occurs up to 1 km above cloud-base, potentially providing observational evidence for recent numerical simulations in the literature.

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 Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

2022 ◽  
Vol 22 (1) ◽  
pp. 319-333
Author(s):  
Ian Boutle ◽  
Wayne Angevine ◽  
Jian-Wen Bao ◽  
Thierry Bergot ◽  
Ritthik Bhattacharya ◽  
...  
Keyword(s):  
Large Eddy Simulation ◽  
Weather Prediction ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Radiation Fog ◽  
Eddy Simulation ◽  
Cloud Droplet Size Distribution ◽  
Large Eddy ◽  
Single Column ◽  
Les Model

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.

scholarly journals Demistify: an LES and SCM intercomparison of radiation fog

2021 ◽  
Author(s):  
Ian Boutle ◽  
Wayne Angevine ◽  
Jian-Wen Bao ◽  
Thierry Bergot ◽  
Ritthik Bhattacharya ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Radiation Fog ◽  
Eddy Simulation ◽  
Cloud Droplet Size Distribution ◽  
Single Column ◽  
Research Grade ◽  
Model Variability ◽  
Les Model

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the LANFEX field campaign. 7 of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst 3 are research-grade SCMs designed for fog simulation, and the LES are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality, and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number (CDNC) conditions. The main SCM bias appears to be toward over-development of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP-SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parametrization, as it is to the underlying aerosol or CDNC.

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.

scholarly journals Investigation of aerosol indirect effects on monsoon clouds using ground-based measurements over a high-altitude site in Western Ghats

2016 ◽  
Author(s):  
V. Anil Kumar ◽  
G. Pandithurai ◽  
P. P. Leena ◽  
K. K. Dani ◽  
P. Murugavel ◽  
...  
Keyword(s):  
High Altitude ◽  
Indirect Effects ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Number Concentration ◽  
Effective Radius ◽  
Aerosol Indirect Effects ◽  
Cloud Droplet Number Concentration ◽  
Aerosol Effects

Abstract. The effect of aerosols on cloud droplet number concentration and droplet effective radius are investigated from ground-based measurements over a high-altitude site where in clouds pass over the surface. First aerosol indirect effect AIE estimates were made using i) relative changes in cloud droplet number concentration (AIEn) and ii) relative changes in droplet effective radius (AIEs) with relative changes in aerosol for different LWC values. AIE estimates from two different methods reveal that there is systematic overestimation in AIEn as compared to that of AIEs. Aerosol indirect effects (AIEn and AIEs) and Dispersion effect (DE) at different liquid water content (LWC) regimes ranging from 0.05 to 0.50 gm-3 were estimated. The analysis demonstrates that there is overestimation of AIEn as compared to AIEs which is mainly due to DE. Aerosol effects on spectral dispersion in droplet size distribution plays an important role in altering Twomey’s cooling effect and thereby changes in climate. This study shows that the higher DE in the medium LWC regime which offsets the AIE by 30%.

Sign in / Sign up

Export Citation Format

Share Document