Drizzle in Stratiform Boundary Layer Clouds. Part I: Vertical and Horizontal Structure

2005 ◽  
Vol 62 (9) ◽  
pp. 3011-3033 ◽  
Author(s):  
R. Wood
Keyword(s):  
Boundary Layer ◽  
Water Content ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Precipitation Rate ◽  
Cloud Base ◽  
Specific Reference ◽  
Horizontal Structure ◽  
Boundary Layer Clouds ◽  
Droplet Concentration

Abstract Detailed observations of stratiform boundary layer clouds on 12 days are examined with specific reference to drizzle formation processes. The clouds differ considerably in mean thickness, liquid water path (LWP), and droplet concentration. Cloud-base precipitation rates differ by a factor of 20 between cases. The lowest precipitation rate is found in the case with the highest droplet concentration even though this case had by far the highest LWP, suggesting that drizzle can be severely suppressed in polluted clouds. The vertical and horizontal structure of cloud and drizzle liquid water and bulk microphysical parameters are examined in detail. In general, the highest concentration of r > 20 μm drizzle drops is found toward the top of the cloud, and the mean volume radius of the drizzle drops increases monotonically from cloud top to base. The resulting precipitation rates are largest at the cloud base but decrease markedly only in the upper third of the cloud. Below cloud, precipitation rates decrease markedly with distance below base due to evaporation, and are broadly consistent in most cases with the results from a simple sedimentation–evaporation model. Evidence is presented that suggests evaporating drizzle is cooling regions of the subcloud layer, which could result in dynamical feedbacks. A composite power spectrum of the horizontal spatial series of precipitation rate is found to exhibit a power-law scaling from the smallest observable scales to close to the maximum observable scale (∼30 km). The exponent is considerably lower (1.1–1.2) than corresponding exponents for LWP variability obtained in other studies (∼1.5–2), demonstrating that there is relatively more variability of drizzle on small scales. Singular measures analysis shows that drizzle fields are much more intermittent than the cloud liquid water content fields, consistent with a drizzle production process that depends strongly upon liquid water content. The adiabaticity of the clouds, which can be modeled as a simple balance between drizzle loss and turbulent replenishment, is found to decrease if the time scale for drizzle loss is shorter than roughly 5–10 eddy turnover time scales. Finally, the data are compared with three simple scalings derived from recent observations of drizzle in subtropical stratocumulus clouds.

scholarly journals Estimating drizzle drop size and precipitation rate using two-colour lidar measurements

2010 ◽  
Vol 3 (3) ◽  
pp. 671-681 ◽  
Author(s):  
C. D. Westbrook ◽  
R. J. Hogan ◽  
E. J. O'Connor ◽  
A. J. Illingworth
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Drop Size ◽  
Liquid Water Content ◽  
Precipitation Rate ◽  
Infrared Light ◽  
Cloud Base ◽  
Size Spectrum ◽  
Drop Diameter ◽  
Lidar Measurements

Abstract. A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 μm, which leads to a different backscatter cross section for water drops larger than ≈50 μm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio) provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 μm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC) and other moments of the drizzle drop distribution. The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m) profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R) and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here). Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.

scholarly journals Estimating drizzle drop size and precipitation rate using two-colour lidar measurements

2010 ◽  
Vol 3 (2) ◽  
pp. 891-921
Author(s):  
C. D. Westbrook ◽  
R. J. Hogan ◽  
E. J. O'Connor ◽  
A. J. Illingworth
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Drop Size ◽  
Liquid Water Content ◽  
Precipitation Rate ◽  
Infrared Light ◽  
Cloud Base ◽  
Size Spectrum ◽  
Drop Diameter ◽  
Lidar Measurements

Abstract. A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 µm, which leads to a different backscatter cross section for water drops larger than ≈50 µm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio) provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 µm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC) and other moments of the drizzle drop distribution. The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m) profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R) and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here). Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.

scholarly journals Parameterization of Vertical Profiles of Governing Microphysical Parameters of Shallow Cumulus Cloud Ensembles Using LES with Bin Microphysics

2019 ◽  
Vol 76 (2) ◽  
pp. 533-560 ◽  
Author(s):  
Pavel Khain ◽  
Reuven Heiblum ◽  
Ulrich Blahak ◽  
Yoav Levi ◽  
Harel Muskatel ◽  
...  
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Effective Radius ◽  
Cloud Base ◽  
Vertical Profiles ◽  
Droplet Concentration ◽  
Radiation Properties ◽  
Microphysical Parameters ◽  
Bin Microphysics

Abstract Shallow convection is a subgrid process in cloud-resolving models for which their grid box is larger than the size of small cumulus clouds (Cu). At the same time such Cu substantially affect radiation properties and thermodynamic parameters of the low atmosphere. The main microphysical parameters used for calculation of radiative properties of Cu in cloud-resolving models are liquid water content (LWC), effective droplet radius, and cloud fraction (CF). In this study, these parameters of fields of small, warm Cu are calculated using large-eddy simulations (LESs) performed using the System for Atmospheric Modeling (SAM) with spectral bin microphysics. Despite the complexity of microphysical processes, several fundamental properties of Cu were found. First, despite the high variability of LWC and droplet concentration within clouds and between different clouds, the volume mean and effective radii per specific level vary only slightly. Second, the values of effective radius are close to those forming during adiabatic ascent of air parcels from cloud base. These findings allow for characterization of a cloud field by specific vertical profiles of effective radius and of mean liquid water content, which can be calculated using the theoretical profile of adiabatic liquid water content and the droplet concentration at cloud base. Using the results of these LESs, a simple parameterization of cloud-field-averaged vertical profiles of effective radius and of liquid water content is proposed for different aerosol and thermodynamic conditions. These profiles can be used for calculation of radiation properties of Cu fields in large-scale models. The role of adiabatic processes in the formation of microstructure of Cu is discussed.

scholarly journals Scaling Analysis of Temperature and Liquid Water Content in the Marine Boundary Layer Clouds during POST

2017 ◽  
Vol 74 (12) ◽  
pp. 4075-4092 ◽  
Author(s):  
Yong-Feng Ma ◽  
Szymon P. Malinowski ◽  
Katarzyna Karpińska ◽  
Hermann E. Gerber ◽  
Wojciech Kumala
Keyword(s):  
Boundary Layer ◽  
Water Content ◽  
Liquid Water ◽  
Marine Boundary Layer ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Scaling Analysis ◽  
Scaling Exponents ◽  
Near Surface ◽  
Scale Break

AbstractThe authors have analyzed the scaling behavior of marine boundary layer (MBL) clouds using high-resolution temperature (T) and liquid water content (LWC) fluctuations from aircraft measurements collected over the Pacific Ocean during the Physics of Stratocumulus Top (POST) research campaign in summer of 2008. As an extension of the past studies for scale-invariant properties of MBL clouds, the authors studied the variability of scaling exponents with height. The results showed that both LWC and T have two distinct scaling regimes: the first one displays scale invariance over a range from about 1–5 m to at least 7 km, and the second one goes from about 0.1–1 to 1–5 m. For the large-scale regime (r > 1–5 m), turbulence in MBL clouds is multifractal, while scale break and scaling exponents vary with height, most significantly in the cloud-top region. For example, LWC spectral exponent β increases from 1.42 at cloud base to 1.58 at cloud top, while scale break decreases from ~5 m at cloud base to 0.8 m at cloud top. The bifractal parameters (H1, C1) for LWC increase from (0.14, 0.02) at cloud base to (0.33, 0.1) at cloud top while maintaining a statistically significant linear relationship C1 ≈ 0.4H1 − 0.04 in MBL clouds. From near surface to cloud top, (H1, C1) for T also increase with height, but above cloud top H1 increases and C1 decreases with height. The results suggest the existence of three turbulence regimes: near the surface, in the middle of the boundary layer, and in the cloud-top region, which need to be distinguished.

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 Why Does Deep Convection Have Different Sensitivities to Temperature Perturbations in the Lower versus Upper Troposphere?

2018 ◽  
Vol 76 (1) ◽  
pp. 27-41 ◽  
Author(s):  
Yang Tian ◽  
Zhiming Kuang
Keyword(s):  
Water Content ◽  
Vertical Velocity ◽  
Liquid Water ◽  
Deep Convection ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Base Temperature ◽  
Upper Troposphere ◽  
Convective Parameterization ◽  
Parameterization Schemes

Abstract Previous studies have documented that deep convection responds more strongly to above-the-cloud-base temperature perturbations in the lower troposphere than to those in the upper troposphere, a behavior that is important to the dynamics of large-scale moist flows, such as convectively coupled waves. A number of factors may contribute to this differing sensitivity, including differences in buoyancy, vertical velocity, and/or liquid water content in cloud updrafts in the lower versus upper troposphere. Quantifying the contributions from these factors can help to guide the development of convective parameterization schemes. We tackle this issue by tracking Lagrangian particles embedded in cloud-resolving simulations within a linear response framework. The results show that both the differences in updraft buoyancy and vertical velocity play a significant role, with the vertical velocity being the more important, and the effect of liquid water content is only secondary compared to the other two factors. These results indicate that cloud updraft vertical velocities need to be correctly modeled in convective parameterization schemes in order to properly account for the differing convective sensitivities to temperature perturbations at different heights of the free troposphere.

scholarly journals Parameterizing cloud top effective radii from satellite retrieved values, accounting for vertical photon transport: quantification and correction of the resulting bias in droplet concentration and liquid water path retrievals

2018 ◽  
Vol 11 (7) ◽  
pp. 4273-4289 ◽  
Author(s):  
Daniel P. Grosvenor ◽  
Odran Sourdeval ◽  
Robert Wood
Keyword(s):  
Penetration Depth ◽  
Optical Depth ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Percentage Error ◽  
Time Variability ◽  
Liquid Water Path ◽  
Water Path ◽  
Droplet Concentration

Abstract. Droplet concentration (Nd) and liquid water path (LWP) retrievals from passive satellite retrievals of cloud optical depth (τ) and effective radius (re) usually assume the model of an idealized cloud in which the liquid water content (LWC) increases linearly between cloud base and cloud top (i.e. at a fixed fraction of the adiabatic LWC). Generally it is assumed that the retrieved re value is that at the top of the cloud. In reality, barring re retrieval biases due to cloud heterogeneity, the retrieved re is representative of smaller values that occur lower down in the cloud due to the vertical penetration of photons at the shortwave-infrared wavelengths used to retrieve re. This inconsistency will cause an overestimate of Nd and an underestimate of LWP (referred to here as the “penetration depth bias”), which this paper quantifies via a parameterization of the cloud top re as a function of the retrieved re and τ. Here we estimate the relative re underestimate for a range of idealized modelled adiabatic clouds using bispectral retrievals and plane-parallel radiative transfer. We find a tight relationship between gre=recloud top/reretrieved and τ and that a 1-D relationship approximates the modelled data well. Using this relationship we find that gre values and hence Nd and LWP biases are higher for the 2.1 µm channel re retrieval (re2.1) compared to the 3.7 µm one (re3.7). The theoretical bias in the retrieved Nd is very large for optically thin clouds, but rapidly reduces as cloud thickness increases. However, it remains above 20 % for τ<19.8 and τ<7.7 for re2.1 and re3.7, respectively. We also provide a parameterization of penetration depth in terms of the optical depth below cloud top (dτ) for which the retrieved re is likely to be representative. The magnitude of the Nd and LWP biases for climatological data sets is estimated globally using 1 year of daily MODIS (MODerate Imaging Spectroradiometer) data. Screening criteria are applied that are consistent with those required to help ensure accurate Nd and LWP retrievals. The results show that the SE Atlantic, SE Pacific and Californian stratocumulus regions produce fairly large overestimates due to the penetration depth bias with mean biases of 32–35 % for re2.1 and 15–17 % for re3.7. For the other stratocumulus regions examined the errors are smaller (24–28 % for re2.1 and 10–12 % for re3.7). Significant time variability in the percentage errors is also found with regional mean standard deviations of 19–37 % of the regional mean percentage error for re2.1 and 32–56 % for re3.7. This shows that it is important to apply a daily correction to Nd for the penetration depth error rather than a time–mean correction when examining daily data. We also examine the seasonal variation of the bias and find that the biases in the SE Atlantic, SE Pacific and Californian stratocumulus regions exhibit the most seasonality, with the largest errors occurring in the December, January and February (DJF) season. LWP biases are smaller in magnitude than those for Nd (−8 to −11 % for re2.1 and −3.6 to −6.1 % for re3.7). In reality, and especially for more heterogeneous clouds, the vertical penetration error will be combined with a number of other errors that affect both the re and τ, which are potentially larger and may compensate or enhance the bias due to vertical penetration depth. Therefore caution is required when applying the bias corrections; we suggest that they are only used for more homogeneous clouds.

Drizzle in Stratiform Boundary Layer Clouds. Part II: Microphysical Aspects

2005 ◽  
Vol 62 (9) ◽  
pp. 3034-3050 ◽  
Author(s):  
R. Wood
Keyword(s):  
Boundary Layer ◽  
Size Distribution ◽  
Large Scale ◽  
Cloud Droplet ◽  
Horizontal Structure ◽  
Boundary Layer Clouds ◽  
Droplet Concentration ◽  
Warm Rain ◽  
Lognormal Size Distribution ◽  
Accretion Rates

Abstract This is the second of two observational papers examining drizzle in stratiform boundary layer clouds. Part I details the vertical and horizontal structure of cloud and drizzle parameters, including some bulk microphysical variables. In this paper, the focus is on the in situ size-resolved microphysical measurements, particularly of drizzle drops (r &gt; 20 μm). Layer-averaged size distributions of drizzle drops within cloud are shown to be well represented using either a truncated exponential or a truncated lognormal size distribution. The size-resolved microphysical measurements are used to estimate autoconversion and accretion rates by integration of the stochastic collection equation (SCE). These rates are compared with a number of commonly used bulk parameterizations of warm rain formation. While parameterized accretion rates agree well with those derived from the SCE initialized with observed spectra, the autoconversion rates seriously disagree in some cases. These disagreements need to be addressed in order to bolster confidence in large-scale numerical model predictions of the aerosol second indirect effect. Cloud droplet coalescence removal rates and mass and number fall rate relationships used in the bulk microphysical schemes are also compared, revealing some potentially important discrepancies. The relative roles of autoconversion and accretion are estimated by examination of composite profiles from the 12 flights. Autoconversion, although necessary for the production of drizzle drops, is much less important than accretion throughout the lower 80% of the cloud layer in terms of the production of drizzle liquid water. The SCE calculations indicate that the autoconversion rate depends strongly upon the cloud droplet concentration Nd such that a doubling of Nd would lead to a reduction in autoconversion rate of between 2 and 4. Radar reflectivity–precipitation rate (Z–R) relationships suitable for radar use are derived and are shown to be significantly biased in some cases by the undersampling of large (r &gt; 200 μm) drops with the 2D-C probe. A correction based upon the extrapolation to larger sizes using the exponential size distribution changes the Z–R relationship, leading to the conclusion that consideration should be given to sampling issues when examining higher moments of the drop size distribution in drizzling stratiform boundary layer clouds.

scholarly journals Stratocumulus Liquid Water Content from Dual-Wavelength Radar

2005 ◽  
Vol 22 (8) ◽  
pp. 1207-1218 ◽  
Author(s):  
Robin J. Hogan ◽  
Nicolas Gaussiat ◽  
Anthony J. Illingworth
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Wave Attenuation ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Radar Signal ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Atmospheric Radiation Measurement ◽  
The Difference

Abstract A technique is described to retrieve stratocumulus liquid water content (LWC) using the differential attenuation measured by vertically pointing radars at 35 and 94 GHz. Millimeter-wave attenuation is proportional to LWC and increases with frequency, so LWC can be derived without the need to make any assumptions on the nature of the droplet size distribution. There is also no need for the radars to be well calibrated. A significant advantage over many radar techniques in stratocumulus is that the presence of drizzle drops (those with a diameter larger than around 50 μm) does not affect the retrieval, even though such drops may dominate the radar signal. It is important, however, that there are not significant numbers of drops larger than 600 μm, which scatter outside of the Rayleigh regime at 94 GHz. A lidar ceilometer is used to locate the cloud base in the presence of drizzle falling below the cloud. An accuracy of around 0.04 g m−3 is achievable with averaging over 1 min and 150 m (two range gates), but for the previously suggested frequency pair of 10 and 35 GHz, the corresponding accuracy would be considerably worse at 0.34 g m−3. First, the retrieval of LWC is simulated using aircraft-measured size spectra taken from a profile through marine stratocumulus. Results are then presented from two case studies—one using two cloud radars at Chilbolton in southern United Kingdom, and another using the Cloud Profiling Radar System at the Atmospheric Radiation Measurement site in Oklahoma. The liquid water path from the technique was found to be in good agreement with the values that were obtained from microwave radiometers, with the difference between the two being close to the accuracy of the radiometer retrieval. In the case of well-mixed stratocumulus, the profiles were close to adiabatic.

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