scholarly journals FY-4A SATELLITE BASED CLOUD MICROPHYSICAL VARIATION ANALYSIS OF AIRBORNE CLOUD SEEDING OPERATIONS IN SICHUAN BASIN

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 125-131
Author(s):  
D. Lin ◽  
W. Wang ◽  
P. Liu ◽  
G. Liu ◽  
W. Geng
Keyword(s):  
Sichuan Basin ◽  
Near Infrared ◽  
Effective Radius ◽  
Cloud Seeding ◽  
Cloud Droplets ◽  
Cloud Particle ◽  
Microphysical Properties ◽  
Cloud Temperature ◽  
Impact Area ◽  
Small Cloud

Abstract. Based on a satellite retrieval methodology, the cloud microphysical properties of two airborne cloud seeding operations in Sichuan Basin of Southwest China are analyzed in this paper. The methodology for the retrieval of the cloud particle effective radius (Re), cloud temperature (T) and microphysical structure is based on the data from the AGRI onboard the Chinese FY-4A satellite. A microphysical red–green–blue (RGB) composite visualization has been devised to qualitatively highlight the cloud composition. This RGB scheme is displayed by compositing visible 0.65 micron channel, near infrared 2.2 micron channel and infrared 11.0 micron channel. And the vertical structure and development status of the clouds are demonstrated by the T-Re profiles. The results show that after the cloud seeding operation on June 11, 2018, the cloud particle effective radius increases, and the ground observed PM10 and PM2.5 pollutants decrease as well. As for the cloud seeding operation on November, 17, 2018, the satellite inversion shows that the medium and low level clouds are rich in super-cooled water with small cloud particle effective radius. After the cloud seeding operation, the effective radius of the cloud droplets increases significantly. Both of these two cloud seeding operation in Sichuan Basin demonstrate obvious precipitation enhancement results in the seeding impact area.

scholarly journals Droplet Growth in Warm Water Clouds Observed by the A-Train. Part II: A Multisensor View

2010 ◽  
Vol 67 (6) ◽  
pp. 1897-1907 ◽  
Author(s):  
Takashi Y. Nakajima ◽  
Kentaroh Suzuki ◽  
Graeme L. Stephens
Keyword(s):  
Cloud Droplet ◽  
Warm Water ◽  
Droplet Growth ◽  
Growth Processes ◽  
Cloud Droplets ◽  
Cloud Particle ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Small Cloud

Abstract Hydrometeor droplet growth processes are inferred from a combination of Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) cloud particle size observations and CloudSat/Cloud Profiling Radar (CPR) observations of warm water clouds. This study supports the inferences of a related paper (Part I) (i) that MODIS-retrieved cloud droplet radii (CDR) from the 3.7-μm channel (R37) are influenced by the existence of small droplets at cloud top and (ii) that the CDR obtained from 1.6- (R16) and 2.1-μm (R21) channels contain information about drizzle droplets deeper into the cloud as well as cloud droplets. This interpretation is shown to be consistent with radar reflectivities when matched to CDR that were retrieved from MODIS data. This study demonstrates that the droplet growth process from cloud to rain via drizzle proceeds monotonically with the evolution of R16 or R21 from small cloud drops (on the order of 10–12 μm) to drizzle (CDR greater than 14 μm) to rain (CDR greater than 20 μm). Thus, R16 or R21 is an indicator of hydrometeor droplet growth processes whereas R37 does not contain information about coalescence. A new composite analysis, the contoured frequency diagram, is introduced to combine CloudSat/CPR reflectivity profiles and reveals a distinct trimodal population of reflectivities corresponding to cloud, drizzle, and rain modes.

scholarly journals Estrutura microfísica das nuvens em diferentes ecossistemas da América do Sul

2009 ◽  
Vol 32 (2) ◽  
pp. 33-41
Author(s):  
Bruno Muniz Duarte ◽  
José Ricardo de Almeida França
Keyword(s):  
Deep Convection ◽  
Effective Radius ◽  
Atmospheric Models ◽  
Cloud Type ◽  
Synoptic Condition ◽  
Cloud Particle ◽  
Microphysical Properties ◽  
Four Seasons ◽  
Frontal Systems

Clouds directly affect meteorological conditions of the planet, by interacting with electromagnetic radiation from the sun, the earth's surface and the atmosphere. Each cloud type interacts in a particular way, being extremely important that the total set of clouds at any location is well represented in atmospheric models, in order to generate more accurate results. The purpose of this paper is to initiate a characterization of cloud types as a function of their microphysical properties and evaluate the dependence on ecosystem and synoptic condition. The data were obtained through remote sensing, using the MODIS sensor and the variables: cloud particle effective radius, optical thickness, pressure and temperature of the cloud top. Several forms of distributions were found for six different ecosystems for the four seasons. It was noted that narrow and concentrated effective radius spectra are linked to deep convection clouds, while broader distributions can be usually associated to cold frontal systems. The amount of events analyzed was not enough to show clear patterns, although the results can lead to other directions in a future and more focused work.

Post-flight analysis of the aerosol impact on size distributions of warm clouds’ droplets, as determined in situ by cloud and aerosol spectrometers

2020 ◽  
Author(s):  
Denisa Elena Moacă ◽  
Sorin Nicolae Vâjâiac ◽  
Andreea Calcan ◽  
Valeriu Filip
Keyword(s):  
Size Distribution ◽  
Pure Water ◽  
Weather Forecast ◽  
Cloud Microphysics ◽  
Atmospheric Environment ◽  
Size Distributions ◽  
Cloud Droplets ◽  
Cloud Particle ◽  
Microphysical Properties

<p>The influence of aerosol on the various aspects of the atmospheric properties as well as on the energetic balance is widely recognised in the scientific community and this issue is currently subject to worldwide intense investigations. Among the multiple ways aerosol particles are impacting the atmospheric environment, their interference with the phase transformations of the atmospheric water is of particular importance. Cloud microphysics, on the other hand, is one of the key components in weather forecast and, therefore, in pursuing daily domestic activities ranging from agriculture to energy harvesting and aviation. The micro-physical processes taking place in clouds are strongly influenced by the spatiotemporal variation of the size distribution of the cloud droplets. In this context, as in situ investigations of clouds seem appropriate, one of the most useful types of instruments is casted into the generic name of Cloud and Aerosol Spectrometer (CAS) that can be mounted on specialized research aircraft. The CAS working principle relies basically on measuring the forward scattering cross section (FWSCS) of light with a certain wavelength on a cloud particle and comparing it to the FWSCS computed for pure water spheres. The eventual matching of these values leads to assigning a certain value for the measured particle’s diameter. The light wavelength is usually chosen in a range where pure water has virtually no absorption. However, atmospheric aerosol frequently mixes up with cloud droplets (starting even from the nucleation processes) and alters their optical properties. By increasing absorption and/or refractivity with respect to those of pure water, one can easily show that the FWSCS-diameter diagram changes drastically by becoming smoother and with an overall significant decrease in absolute values. This means that a CAS will systematically count “contaminated” cloud droplets in a lower range of diameters, thus distorting their real size distribution. This effect is inherently degrading the objectivity of CAS measurements and should be more pronounced when levels of sub-micrometer sized aerosol increase at the cloud altitude. The present study aims at pointing out such correlation in order to estimate the reliability of size distributions (and of the ensuing cloud microphysical properties) obtained by CAS.</p>

scholarly journals Characterization of Initiation and Growth of Selected Severe Convective Storms over Central Europe with MSG-SEVIRI

2015 ◽  
Vol 54 (1) ◽  
pp. 207-224 ◽  
Author(s):  
Fabian Senf ◽  
Felix Dietzsch ◽  
Anja Hünerbein ◽  
Hartwig Deneke
Keyword(s):  
Cooling Rate ◽  
Central Europe ◽  
Vertical Velocity ◽  
Time Lag ◽  
Growth Period ◽  
Effective Radius ◽  
Cloud Particle ◽  
Initiation Mechanism ◽  
Convective Storms ◽  
Microphysical Properties

AbstractThe early development of severe convective storms over central Europe was investigated on the basis of nine cases from 2012. Using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) imaging radiometer aboard a geostationary Meteosat Second Generation (MSG) satellite, dynamical and microphysical properties of developing storms were monitored and combined. Several satellite-based storm properties, for example, cloud-top temperature, cloud-top cooling rate, and cloud particle effective radius, were investigated following the storm tracks. A framework for quantification of uncertainties of along-track properties resulting from tracking errors was also introduced. The majority of studied storms show a distinct maximum in cloud-top cooling rate; the corresponding time was used for track synchronization. The cloud growth phase was divided into an initial updraft intensification period before the maximum cooling and a continued growth period afterward. The initial updraft intensification period is variable and strongly depends on the convection initiation mechanism and detection conditions. The continued growth period is more confined, lasting between 30 and 45 min. The change in anvil size and the resulting average anvil edge velocity were determined from infrared satellite images. As a consequence of mass transport, the anvil edge velocity shows its highest correlation with the cloud-top vertical velocity approximately 20–30 min after the maximum in the cloud-top cooling rate. Larger effective radii of ice crystals were observed for vertically slower-growing clouds. The largest anticorrelation between cloud-top vertical velocity and effective radius was found at a time lag of 20 min after the maximum in cloud-top cooling.

scholarly journals Influence of local surface albedo variability and ice crystal shape on passive remote sensing of thin cirrus

2014 ◽  
Vol 14 (4) ◽  
pp. 1943-1958 ◽  
Author(s):  
C. Fricke ◽  
A. Ehrlich ◽  
E. Jäkel ◽  
B. Bohn ◽  
M. Wirth ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Surface Albedo ◽  
Near Infrared ◽  
Effective Radius ◽  
High Spectral Resolution ◽  
Spectral Radiance ◽  
Crystal Shape ◽  
Frequency Distributions ◽  
Airborne Measurements ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Airborne measurements of solar spectral radiance reflected by cirrus are performed with the HALO-Solar Radiation (HALO-SR) instrument onboard the High Altitude and Long Range Research Aircraft (HALO) in November 2010. The data are used to quantify the influence of surface albedo variability on the retrieval of cirrus optical thickness and crystal effective radius. The applied retrieval of cirrus optical properties is based on a standard two-wavelength approach utilizing measured and simulated reflected radiance in the visible and near-infrared spectral region. Frequency distributions of the surface albedos from Moderate resolution Imaging Spectroradiometer (MODIS) satellite observations are used to compile surface-albedo-dependent lookup tables of reflected radiance. For each assumed surface albedo the cirrus optical thickness and effective crystal radius are retrieved as a function of the assumed surface albedo. The results for the cirrus optical thickness are compared to measurements from the High Spectral Resolution Lidar (HSRL). The uncertainty in cirrus optical thickness due to local variability of surface albedo in the specific case study investigated here is below 0.1 and thus less than that caused by the measurement uncertainty of both instruments. It is concluded that for the retrieval of cirrus optical thickness the surface albedo variability is negligible. However, for the retrieval of crystal effective radius, the surface albedo variability is of major importance, introducing uncertainties up to 50%. Furthermore, the influence of the bidirectional reflectance distribution function (BRDF) on the retrieval of crystal effective radius was investigated and quantified with uncertainties below 10%, which ranges below the uncertainty caused by the surface albedo variability. The comparison with the independent lidar data allowed for investigation of the role of the crystal shape in the retrieval. It is found that if assuming aggregate ice crystals, the HSRL observations fit best with the retrieved optical thickness from HALO-SR.

scholarly journals Constraints on interactions between aerosols and clouds on a global scale from a combination of MODIS-CERES satellite data and climate simulations

2010 ◽  
Vol 10 (20) ◽  
pp. 9851-9861 ◽  
Author(s):  
X. Ma ◽  
K. von Salzen ◽  
J. Cole
Keyword(s):  
Liquid Water ◽  
Negative Relationship ◽  
Cloud Droplet ◽  
Global Scale ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Droplets ◽  
Cloud Liquid Water ◽  
Albedo Effect ◽  
Cloud Liquid Water Path

Abstract. Satellite-based cloud top effective radius retrieved by the CERES Science Team were combined with simulated aerosol concentrations from CCCma CanAM4 to examine relationships between aerosol and cloud that underlie the first aerosol indirect (cloud albedo) effect. Evidence of a strong negative relationship between sulphate, and organic aerosols, with cloud top effective radius was found for low clouds, indicating both aerosol types are contributing to the first indirect effect on a global scale. Furthermore, effects of aerosol on the cloud droplet effective radius are more pronounced for larger cloud liquid water paths. While CanAM4 broadly reproduces the observed relationship between sulphate aerosols and cloud droplets, it does not reproduce the dependency of cloud top droplet size on organic aerosol concentrations nor the dependency on cloud liquid water path. Simulations with a modified version of the model yield a more realistic dependency of cloud droplets on organic carbon. The robustness of the methods used in the study are investigated by repeating the analysis using aerosol simulated by the GOCART model and cloud top effective radii derived from the MODIS Science Team.

scholarly journals FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

2014 ◽  
Vol 7 (11) ◽  
pp. 3873-3890 ◽  
Author(s):  
C. K. Carbajal Henken ◽  
R. Lindstrot ◽  
R. Preusker ◽  
J. Fischer
Keyword(s):  
Optical Thickness ◽  
Single Layer ◽  
Cloud Water ◽  
Effective Radius ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Microphysical Property ◽  
Resolution Imaging ◽  
Cloud Optical Thickness ◽  
Cloud Water Path

Abstract. A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years 2007–2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 μm and −0.18 g m−2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds.

scholarly journals Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign

2021 ◽  
Vol 14 (6) ◽  
pp. 4755-4771
Author(s):  
William G. K. McLean ◽  
Guangliang Fu ◽  
Sharon P. Burton ◽  
Otto P. Hasekamp
Keyword(s):  
Refractive Index ◽  
Effective Radius ◽  
High Spectral Resolution ◽  
Imaginary Component ◽  
The Real ◽  
Microphysical Properties ◽  
Lidar Measurements ◽  
Fine Mode ◽  
Truth Value ◽  
Real Refractive Index

Abstract. This study presents an investigation of aerosol microphysical retrievals from high spectral resolution lidar (HSRL) measurements. Firstly, retrievals are presented for synthetically generated lidar measurements, followed by an application of the retrieval algorithm to real lidar measurements. Here, we perform the investigation for an aerosol state vector that is typically used in multi-angle polarimeter (MAP) retrievals, so that the results can be interpreted in relation to a potential combination of lidar and MAP measurements. These state vectors correspond to a bimodal size distribution, where column number, effective radius, and effective variance of both modes are treated as fit parameters, alongside the complex refractive index and particle shape. The focus is primarily on a lidar configuration based on that of the High Spectral Resolution Lidar-2 (HSRL-2), which participated in the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined project between NASA and SRON (Netherlands Institute for Space Research). The measurement campaign took place between October and November 2017, over the western region of the USA. Six different instruments were mounted on the aeroplane: four MAPs and two lidar instruments, HSRL-2 and the Cloud Physics Lidar (CPL). Most of the flights were carried out over land, passing over scenes with a low aerosol load. One of the flights passed over a prescribed forest fire in Arizona on 9 November, with a relatively higher aerosol optical depth (AOD), and it is the data from this flight that are focussed on in this study. A retrieval of the aerosol microphysical properties of the smoke plume mixture was attempted with the data from HSRL-2 and compared with a retrieval from the MAPs carried out in previous work pertaining to the ACEPOL data. The synthetic HSRL-2 retrievals resulted for the fine mode in a mean absolute error (MAE) of 0.038 (0.025) µm for the effective radius (with a mean truth value of 0.195 µm), 0.052 (0.037) for the real refractive index, 0.010 (7.20×10-3) for the imaginary part of the refractive index, 0.109 (0.071) for the spherical fraction, and 0.054 (0.039) for the AOD at 532 nm, where the retrievals inside brackets indicate the MAE for noise-free retrievals. For the coarse mode, we find the MAE is 0.459 (0.254) µm for the effective radius (with a mean truth value of 1.970 µm), 0.085 (0.075) for the real refractive index, 2.06×10-4 (1.90×10-4) for the imaginary component, 0.120 (0.090) for the spherical fraction, and 0.051 (0.039) for the AOD. A study of the sensitivity of retrievals to the choice of prior and first guess showed that, on average, the retrieval errors increase when the prior deviates too much from the truth value. These experiments revealed that the measurements primarily contain information on the size and shape of the aerosol, along with the column number. Some information on the real component of the refractive index is also present, with the measurements providing little on absorption or on the effective variance of the aerosol distribution, as both of these were shown to depend heavily on the choice of prior. Retrievals using the HSRL-2 smoke-plume data yielded, for the fine mode, an effective radius of 0.107 µm, a real refractive index of 1.561, an imaginary component of refractive index of 0.010, a spherical fraction of 0.719, and an AOD at 532 nm of 0.505. Additionally, the single-scattering albedo (SSA) from the HSRL-2 retrievals was 0.940. Overall, these results are in good agreement with those from the Spectropolarimeter for Planetary Exploration (SPEX) and Research Scanning Polarimeter (RSP) retrievals.

scholarly journals Discrimination of water, ice and aerosols by light polarisation in the CLOUD experiment

2015 ◽  
Vol 15 (21) ◽  
pp. 31433-31469 ◽  
Author(s):  
L. Nichman ◽  
C. Fuchs ◽  
E. Järvinen ◽  
K. Ignatius ◽  
N. F. Höppel ◽  
...  
Keyword(s):  
General Circulation ◽  
Simultaneous Detection ◽  
Organic Aerosol ◽  
General Circulation Models ◽  
Mixed Phase ◽  
Cloud Formation ◽  
Potential Contribution ◽  
Particle Size Range ◽  
Cloud Particle ◽  
Small Cloud

Abstract. Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather and General Circulation Models (GCMs). The simultaneous detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud-particle size range below 50 μm, remains challenging in mixed phase, often unstable ice-water phase environments. The Cloud Aerosol Spectrometer with Polarisation (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure their effects on the backscatter polarisation state. Here we operate the versatile Cosmics-Leaving-OUtdoor-Droplets (CLOUD) chamber facility at the European Organisation for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water and ice particles. In this paper, optical property measurements of mixed phase clouds and viscous Secondary Organic Aerosol (SOA) are presented. We report observations of significant liquid – viscous SOA particle polarisation transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarisation ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulphate, and volcanic ash. Finally, we discuss the benefits and limitations of this classification approach for atmospherically relevant concentration and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to Tropical Troposphere Layer (TTL) analysis.

scholarly journals Monte Carlo-based subgrid parameterization of vertical velocity and stratiform cloud microphysics in ECHAM5.5-HAM2

2013 ◽  
Vol 13 (2) ◽  
pp. 5477-5507
Author(s):  
J. Tonttila ◽  
P. Räisänen ◽  
H. Järvinen
Keyword(s):  
Monte Carlo ◽  
Vertical Velocity ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Radiative Effects ◽  
Cloud Droplets ◽  
Microphysical Properties ◽  
Cloud Radiative Effects ◽  
Cloud Activation ◽  
The Impact

Abstract. A new method for parameterizing the subgrid variations of vertical velocity and cloud droplet number concentration (CDNC) is presented for GCMs. These parameterizations build on top of existing parameterizations that create stochastic subgrid cloud columns inside the GCM grid-cells, which can be employed by the Monte Carlo independent column approximation approach for radiative transfer. The new model version adds a description for vertical velocity in individual subgrid columns, which can be used to compute cloud activation and the subgrid distribution of the number of cloud droplets explicitly. This provides a consistent way for simulating the cloud radiative effects with two-moment cloud microphysical properties defined in subgrid-scale. The primary impact of the new parameterizations is to decrease the CDNC over polluted continents, while over the oceans the impact is smaller. This promotes changes in the global distribution of the cloud radiative effects and might thus have implications on model estimation of the indirect radiative effect of aerosols.

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