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Example results of MC calculations for a lidar wavelength of 355 nm corresponding to semi-infinite clouds with a cloud-base of 1.0 km for two values of α 100 as a function of R eff,100 for a lidar FOV of 1.0 mrad.
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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....
Context in source publication
Context 1
... return and the associated multiple-scattering contributions. Using Eq. (5) it is possible to interpolate between the MC look-up table entries to examine how the signal and depolarisation ratio profiles behave as a function of R eff,100 while the extinction profile is held constant, thus isolating the effects of MS. Such an example 10 is shown in Fig. 4 where the para., perp. and depolarisation profiles are shown for val- ues of α 100 = 5 km −1 and 10 km −1 (the extinction coefficient at 100 m from cloud-base) as a function of R eff,100 . If MS was not occurring, there would be no variation present in the para profile as R eff,100 changes and practically no perp. signal would exist at ...
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Citations
... Since then, important research papers have been published, leading to better exploitation of MS, especially from space LiDAR data, in particular the Hu equation [11], the work by Hogan et al. [12,13] and the physical model of Sato and al. [14,15]. In parallel, work has been done to better understand the physics of MS and depolarization [16][17][18][19][20][21]. A good review is done in Ref. [21]. ...
Multiple scattering is always present in LiDAR measurements. It is one of the major causes of LiDAR signal depolarization when detecting backscattering from water clouds. For a given probing wavelength, the LiDAR signal is a function of the aerosol size distribution, cloud range, and optical depth, and of the LiDAR field of view (FoV). We present a relatively simple polarimetric multiple scattering model. It uses Poisson statistics to determine the photons’ scattering order distribution at a given optical depth and takes into account the aerosol’s properties as well as the characteristics of the LiDAR. The results are compared with Monte Carlo simulations performed on two types of cumulus clouds and on a moderate water fog. Good agreement is demonstrated for the total LiDAR signal and the depolarization parameter for a FoV of 1 mrad and a large FoV of 12 mrad.
... The simulated lidar profiles corresponding to the given microphysical properties of water clouds were computed using MC simulation and then used as input for the retrieval algorithm. Similar simulations for assessing the performance of retrieving cloud properties also can be found in other works (39,49). In this simulation, r e of the water cloud ranges from 6 to 18 μm, while LWC varies from 0.05 to 0.45 gm −3 to represent various cloud scenarios (homogeneous clouds for the sake of simplicity). ...
Significance
Aerosol–cloud interaction affects the cooling of Earth’s climate, mostly by activation of aerosols as cloud condensation nuclei that can increase the amount of sunlight reflected back to space. But the controlling physical processes remain uncertain in current climate models. We present a lidar-based technique as a unique remote-sensing tool without thermodynamic assumptions for simultaneously profiling diurnal aerosol and water cloud properties with high resolution. Direct lateral observations of cloud properties show that the vertical structure of low-level water clouds can be far from being perfectly adiabatic. Furthermore, our analysis reveals that, instead of an increase of liquid water path (LWP) as proposed by most general circulation models, elevated aerosol loading can cause a net decrease in LWP.
... It is also difficult to find this kind of benchmark results online. More importantly, to our best knowledge, the active lidar Monte Carlo polarized radiative transfer models were developed dominantly for 1D plane-parallel atmospheres [22][23][24][25][26][27][28][29] , rarely for 3D inhomogeneous atmospheres (e.g. the 3DMcPOLID [30,31] and ECSIM [32,33] ...
... For instance, integrate backward algorithm into the Monte Carlo model to add a feature of simulating local and directional polarized radiance under sunlight or thermal illumination [34,35] ; integrate multiple kinds of geometrical and microphysical configurations of atmosphere, surface, source and detector into the model to broaden the scope of passive and active remote sensing applications (see e.g. [30,33,[36][37][38][39] ); embed sophisticated variance reduction techniques into the model to make complex scenario simulations possible in affordable comput ational cost s (see e.g. [19,[40][41][42] ); and etc. ...
... To evaluate lidar polarization simulations, the comparisons with the published results in the scientific literature [31,33] have been Table 1 ). The dashed lines denote the MSCART Scheme SO results and the solid lines denote the I3RC consensus results. ...
This paper extends the theoretical framework of universal forward and backward Monte Carlo radiative transfer modeling for passive and active polarization observation simulations. The framework is built
upon newly derived forward and backward vector scattering order-dependent integral radiative transfer equations (IRTEs). The unified mathematical formalism not only establishes the design of object-oriented software architecture, but also speeds up software development via the reuse of developed scalar code. The polarization simulations are implemented with the addition of the Stokes vector and the Mueller matrix weight tracing schemes. To improve numerical performance order by order, the extension implementation of hybrid scattering order-dependent variance reduction techniques are given detailedly, with a focus on the formulation of scattering phase matrix truncation on the basis of remodeling vector IRTEs. To enrich polarization simulation features, not only scattering operators but also source vector function and detector response matrix function are formulated in unified mathematical forms for the hierarchies
organization of various atmosphere, surface, source and detector classes.
The framework was fully implemented in Multiple-Scaling-based Cloudy Atmospheric Radiative Transfer (MSCART) model. For passive simulation, it not only can handle all one- and three-dimensional (1D and 3D) test cases in the Phase A and B of the International Polarized Radiative Transfer (IPRT) intercomparison project by simulating area-averaged polarized radiance using forward and backward algorithm, but also can simulate polarized radiance in a specified direction at a specified position using backward
algorithm; For active simulation, lidar backscatter range-resolved signals can be simulated using forward algorithm. The source package is freely available for research purpose from the corresponding author, with online documentation from https://intersharp.gitlab.io/mscart-docs or http://mscart.nuist.edu.cn .
... As suggested by Kim et al., 15 LWC and CDES can be retrieved from the slope of the DLP at the cloud base and the saturated DLP at an infinite altitude. Donovan et al. 16 also proposed that liquid-cloud microphysical properties can be determined using depolarization Lidar, assuming that the clouds exhibit characteristics of (quasi-)linear LWC profiles and (quasi-) constant cloud-droplet number density in the cloud base region. Although substantial progress has been made on theoretical studies of multiple scattering, to the best of our knowledge, very little experimental research has been conducted. ...
Liquid water content (LWC) and cloud droplet effective size (CDES) are important factors affecting atmospheric radiative transfer, and measurement of these parameters in clouds is essential. For homogeneous liquid cloud (constant extinction coefficient) with a gamma size distribution of cloud droplets, we find that LWC and CDES can be retrieved from two parameters obtained from a multiple-field-of-view (MFOV) Lidar: the intercept of the range-corrected Lidar signal (IRCLS) and the slope of the range-corrected Lidar signal (SRCLS) at different sizes of FOV. Monte Carlo simulations reveal that IRCLS at different sizes of FOV varies with both extinction coefficient and CDES while SRCLS varies only with the extinction coefficient, which depends on both LWC and CDES. This means that, after extracting the extinction coefficient using SRCLS, we can easily obtain CDES from IRCLS, and LWC can then be determined using the extinction coefficient. An innovative MFOV Lidar system is constructed to measure the LWC and CDES. A series of experiments is conducted in the northern suburb of Nanjing, China, and the LWC and CDES of homogeneous liquid cloud are obtained. Comparisons among results from the MFOV Lidar, theoretical calculation, and the global precipitation measurement satellite verify our proposed method. © 2018 Society of Photo-Optical Instrumentation Engineers (SPIE).
... Observations from the lidar were pro- cessed using an inversion method which pro- duces estimates of cloud microphysical prop- erties such as the effective radius and cloud droplet number density. This new inversion method is based on Monte Carlo modelling of multiple scattering within idealised semi- adiabatic clouds [3]. The method utilizes the propensity of light to become depolarized when it undergoes multiple scattering within a liq- uid water cloud. ...
Marine stratocumulus clouds are important climate regulators, reflecting sunlight over a dark ocean background. A UV-depolarization lidar on Ascension, a small remote island in the south Atlantic, measured cloud droplet sizes and number concentration using an inversion method based on Monte Carlo (MC) modelling of multiple scattering in idealised semiadiabatic clouds. The droplet size and number concentration weremodulated due to smoke from the African continent, measured by the same instrument.
... To characterize this influence, accurate and simultaneous observations of the microphysical properties of the clouds and of aerosols below the clouds base are needed. Many scientist have attempted to estimate the microphysical properties of liquid clouds by analyzing the multiple scattering effects with lidar [2,3,4,5,6]. ...
... Recently a robust optimal estimation procedure to retrieve this microphysical properties from lidar depolarization measurements was developed [6]. This is an innovative application, carrying on with previous work with the dual FOV techniques developed in the same group. ...
... The same time period was selected to use the depolarization method [6], but the averaging is performed for 3-minute periods to obtain 7 profiles in total. The calibration for the polarization channels was based on a three signal procedure [11]. ...
Since 2010, the Raman dual-FOV lidar system permits the retrieval of microphysical properties of liquid-water clouds during nighttime. A new robust lidar depolarization approach was recently introduced, which permits the retrieval of these properties as well, with high temporal resolution and during daytime. To implement this approach, the lidar system was upgraded, by adding a three channel depolarization receiver. The first preliminary retrieval results and a comparison between both methods is presented.
... The technique has been used for a long time to monitor and investigate cirrus cloud systems (e.g., Sassen, 1991Sassen, , 2005Reichardt et al., 2002Reichardt et al., , 2008 and polar stratospheric cloud evolution (see, e.g., Browell et al., 1990;Achtert and Tesche, 2014). The method is well suited to study heterogeneous ice formation in mixed-phased clouds (e.g., Sassen et al., 2003;Ansmann et al., 2005Ansmann et al., , 2008Ansmann et al., 2009a;Seifert et al., , 2011 and liquidwater cloud developments (e.g., Bissonnette, 2005;Donovan et al., 2015). Meanwhile, polarization lidars are intensively used to explore aerosol mixtures and to identify soil, desert, and volcanic dust (e.g., McNeil and Carswell, 1975;Iwaska and Hayashida, 1981;Winker and Osborn, 1992;Gobbi, 1998;Murayama et al., 1999Murayama et al., , 2004Cairo et al., 1999;Gobbi et al., 2000;Sakai et al., 2003;Sassen et al., 2007;Freudenthaler et al., 2009;Ansmann et al., 2010;Ansmann et al., 2011a;Groß et al., 2012;Miffre et al., 2012;Amiridis et al., 2013;Nisantzi et al., 2014). ...
We applied the recently introduced polarization lidar–photometer
networking (POLIPHON) technique for the first time to triple-wavelength
polarization lidar measurements at 355, 532, and 1064 nm. The lidar
observations were performed at Barbados during the Saharan Aerosol Long-Range
Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) in the summer
of 2014. The POLIPHON method comprises the traditional lidar technique to
separate mineral dust and non-dust backscatter contributions and the new,
extended approach to separate even the fine and coarse dust backscatter
fractions. We show that the traditional and the advanced method are
compatible and lead to a consistent set of dust and non-dust profiles at
simplified, less complex aerosol layering and mixing conditions as is the
case over the remote tropical Atlantic. To derive dust mass concentration
profiles from the lidar observations, trustworthy extinction-to-volume
conversion factors for fine, coarse, and total dust are needed and obtained
from an updated, extended Aerosol Robotic Network sun photometer data
analysis of the correlation between the fine, coarse and total dust volume
concentration and the respective fine, coarse, and total dust extinction
coefficient for all three laser wavelengths. Conversion factors (total volume
to extinction) for pure marine aerosol conditions and continental
anthropogenic aerosol situations are presented in addition. As a new feature
of the POLIPHON data analysis, the Raman lidar method for particle extinction
profiling is used to identify the aerosol type (marine or anthropogenic) of
the non-dust aerosol fraction. The full POLIPHON methodology was successfully
applied to a SALTRACE case and the results are discussed. We conclude that
the 532 nm polarization lidar technique has many advantages in comparison to
355 and 1064 nm polarization lidar approaches and leads to the most
robust and accurate POLIPHON products.
... Such methods are currently under investigation by different groups, e.g., Maschwitz et al. (2013). An alternative approach may be LWP measurements with depolarization lidar (Hu et al., 2010;Donovan et al., 2015). ...
An analysis of the Cloudnet data set collected at Leipzig, Germany, with
special focus on mixed-phase layered clouds is presented. We derive liquid- and ice-water content together with vertical motions of ice particles falling
through cloud base. The ice mass flux is calculated by combining measurements
of ice-water content and particle Doppler velocity. The efficiency
of heterogeneous ice formation and its impact on cloud lifetime is estimated
for different cloud-top temperatures by relating the ice mass flux and the
liquid-water content at cloud top. Cloud radar measurements of polarization
and Doppler velocity indicate that ice crystals formed in mixed-phase
cloud layers with a geometrical thickness of less than 350 m are mostly
pristine when they fall out of the cloud.
This paper presents a novel mathematical framework to interpret the polarized lidar backscattering pattern for 1D water clouds. The framework is based on the multiple scattering of the lidar signals within small-angle range. An approximation is made that both the outgoing and returning trajectories are assumed to be along nearly planar forward scattering sequences. For lidar axial symmetrical system, a quasi-linear mathematical relationship is built between the observed reduced Mueller matrix and the backscattering phase matrix, and can be generalized to arbitrary scattering orders. For validation, we extend the radiative transfer model MSCART to simulate linearly- and circularly-polarized lidar signals. Meanwhile, we propose the azimuthal Fourier expansion to extract the reduced Mueller matrix results from the MSCART simulation. The numerical evaluation experiments demonstrate that our derived mathematical expressions could extend the polar-angle dependence of the reduced Mueller matrix from second-order to higher-order multiple scatterings. The relation can serve as a useful tool in understanding lidar polarization observations and designing a CCD polarized lidar instrument.
