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

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.

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

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.


2016 ◽  
Author(s):  
Sami Romakkaniemi ◽  
Zubair Maalick ◽  
Antti Hellsten ◽  
Antti Ruuskanen ◽  
Olli Väisänen ◽  
...  

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.


2018 ◽  
Vol 76 (1) ◽  
pp. 27-41 ◽  
Author(s):  
Yang Tian ◽  
Zhiming Kuang

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.


2018 ◽  
Vol 11 (7) ◽  
pp. 4273-4289 ◽  
Author(s):  
Daniel P. Grosvenor ◽  
Odran Sourdeval ◽  
Robert Wood

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.


2005 ◽  
Vol 62 (9) ◽  
pp. 3011-3033 ◽  
Author(s):  
R. Wood

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 &gt; 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.


2013 ◽  
Vol 30 (7) ◽  
pp. 1337-1353 ◽  
Author(s):  
Tetsu Sakai ◽  
David N. Whiteman ◽  
Felicita Russo ◽  
David D. Turner ◽  
Igor Veselovskii ◽  
...  

Abstract This paper describes recent work in the Raman lidar liquid water cloud measurement technique. The range-resolved spectral measurements at the National Aeronautics and Space Administration Goddard Space Flight Center indicate that the Raman backscattering spectra measured in and below low clouds agree well with theoretical spectra for vapor and liquid water. The calibration coefficients of the liquid water measurement for the Raman lidar at the Atmospheric Radiation Measurement Program Southern Great Plains site of the U.S. Department of Energy were determined by comparison with the liquid water path (LWP) obtained with Atmospheric Emitted Radiance Interferometer (AERI) and the liquid water content (LWC) obtained with the millimeter wavelength cloud radar and water vapor radiometer (MMCR–WVR) together. These comparisons were used to estimate the Raman liquid water cross-sectional value. The results indicate a bias consistent with an effective liquid water Raman cross-sectional value that is 28%–46% lower than published, which may be explained by the fact that the difference in the detectors' sensitivity has not been accounted for. The LWP of a thin altostratus cloud showed good qualitative agreement between lidar retrievals and AERI. However, the overall ensemble of comparisons of LWP showed considerable scatter, possibly because of the different fields of view of the instruments, the 350-m distance between the instruments, and the horizontal inhomogeneity of the clouds. The LWC profiles for a thick stratus cloud showed agreement between lidar retrievals and MMCR–WVR between the cloud base and 150 m above that where the optical depth was less than 3. Areas requiring further research in this technique are discussed.


2010 ◽  
Vol 3 (3) ◽  
pp. 671-681 ◽  
Author(s):  
C. D. Westbrook ◽  
R. J. Hogan ◽  
E. J. O'Connor ◽  
A. J. Illingworth

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.


Author(s):  
Zeinab Takbiri ◽  
Lisa Milani ◽  
Clement Guilloteau ◽  
Efi Foufoula-Georgiou

Falling snow alters its own microwave signatures when it begins to accumulate on the ground making retrieval of precipitation challenging. This paper investigates the effects of snow-cover depth and cloud liquid water content on microwave signatures of terrestrial snowfall using reanalysis data and multi-annual measurements by the Global Precipitation Measurement (GPM) core satellite with particular emphasis on the 89 and 166 GHz channels. It is found that over snow cover shallower than 10 cm and low values of cloud liquid water path (LWP &le;125gm&minus;2), the scattering of light snowfall (&amp;lt;0.5mmh&minus;1) is detectable only at frequency 166 GHz while for higher intensities the signal can be also detected at 89 GHz. However, when snow depth exceeds &sim;20 cm and the LWP is greater than &sim;125gm&minus;2 , the emission from the increased liquid water content in snowing clouds becomes the only surrogate microwave signal of snowfall that is stronger at frequency 89 GHz than 166 GHz. The results also reveal that over high latitudes above 60∘ N where the snow cover is thicker than 20 cm and LWP is lower than 125 gm&minus;2 the microwave snowfall signal could not be detected with GPM. Our results provide quantitative insights for improving retrieval of snowfall in particular over snow-covered terrain.


2009 ◽  
Vol 137 (12) ◽  
pp. 4369-4381 ◽  
Author(s):  
Ronald M. Thorkildson ◽  
Kathleen F. Jones ◽  
Maggie K. Emery

Abstract On 24 November 2005, 11 lattice steel towers of a high-voltage electrical transmission line running along the edge of an escarpment were damaged by an accumulation of rime on overhead ground wires. Cold air pooling in the Columbia basin of eastern Washington several days before the failure led to the formation of low-level fog and low clouds with temperatures below freezing at the elevation of the transmission line. The liquid water content profile of the cloud formed by air rising over Badger Mountain north of Wenatchee, Washington, is estimated using the air temperature, dewpoint temperature, and air pressure as measured at Wenatchee in the Columbia River valley below the line. Cloud median volume droplet diameters are estimated using typical droplet concentrations. The validity of the computed liquid water content is determined by comparing the measured cloud-base heights at Wenatchee with the calculated cloud-base heights. The mass and density of ice accreted on the ground wires and conductors of the transmission line are modeled using assumed wind speeds at the top of the escarpment with the estimated cloud properties. Results are compared with the density and mass of an ice sample retrieved from the field. This event is compared with other modeled in-cloud icing events from 1973 to 2007 using the period of record of Wenatchee weather data. This paper illustrates an approach for estimating the severity of in-cloud icing on the wires of transmission lines subject to cloud liquid water contents that have been enhanced by the local terrain.


2019 ◽  
Vol 19 (3) ◽  
pp. 1413-1437 ◽  
Author(s):  
Yajuan Duan ◽  
Markus D. Petters ◽  
Ana P. Barros

Abstract. A new cloud parcel model (CPM) including activation, condensation, collision–coalescence, and lateral entrainment processes is used to investigate aerosol–cloud interactions (ACIs) in cumulus development prior to rainfall onset. The CPM was applied with surface aerosol measurements to predict the vertical structure of cloud development at early stages, and the model results were evaluated against airborne observations of cloud microphysics and thermodynamic conditions collected during the Integrated Precipitation and Hydrology Experiment (IPHEx) in the inner region of the southern Appalachian Mountains (SAM). Sensitivity analysis was conducted to examine the model response to variations in key ACI physiochemical parameters and initial conditions. The CPM sensitivities mirror those found in parcel models without entrainment and collision–coalescence, except for the evolution of the droplet spectrum and liquid water content with height. Simulated cloud droplet number concentrations (CDNCs) exhibit high sensitivity to variations in the initial aerosol concentration at cloud base, but weak sensitivity to bulk aerosol hygroscopicity. The condensation coefficient ac plays a governing role in determining the evolution of CDNC, liquid water content (LWC), and cloud droplet spectra (CDS) in time and with height. Lower values of ac lead to higher CDNCs and broader CDS above cloud base, and higher maximum supersaturation near cloud base. Analysis of model simulations reveals that competitive interference among turbulent dispersion, activation, and droplet growth processes modulates spectral width and explains the emergence of bimodal CDS and CDNC heterogeneity in aircraft measurements from different cloud regions and at different heights. Parameterization of nonlinear interactions among entrainment, condensational growth, and collision–coalescence processes is therefore necessary to simulate the vertical structures of CDNCs and CDSs in convective clouds. Comparisons of model predictions with data suggest that the representation of lateral entrainment remains challenging due to the spatial heterogeneity of the convective boundary layer and the intricate 3-D circulations in mountainous regions.


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