scholarly journals Characteristics of Correlation Statistics between Droplet Radius and Optical Thickness of Warm Clouds Simulated by a Three-Dimensional Regional-Scale Spectral Bin Microphysics Cloud Model

2012 ◽  
Vol 69 (2) ◽  
pp. 484-503 ◽  
Author(s):  
Yousuke Sato ◽  
Kentaroh Suzuki ◽  
Takamichi Iguchi ◽  
In-Jin Choi ◽  
Hiroyuki Kadowaki ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Cloud Model ◽  
Regional Scale ◽  
Atmospheric Stability ◽  
Three Dimensional ◽  
Droplet Radius ◽  
Cloud Particle ◽  
Sbm Model ◽  
Bin Microphysics ◽  
Correlation Statistics

Abstract Three-dimensional downscaling simulations using a spectral bin microphysics (SBM) model were conducted to investigate the effects of aerosol amount and dynamical stabilities of the atmosphere on the correlation statistics between cloud droplet effective radius (RE) and cloud optical thickness (COT) of warm clouds off the coast of California. The regeneration process of aerosols was implemented into the SBM and was found to be necessary for simulating the satellite-observed microphysical properties of warm clouds by the SBM model used in this study. The results showed that the aerosol amount changed the correlation statistics in a way that changes the cloud particle number concentration, whereas the inversion height of the boundary layer, which is related to the atmospheric stability and the cloud-top height, changed the correlation statistics in a way that changes the liquid water path. These results showed that the dominant mechanisms that control the correlation statistics are similar to those suggested by previous modeling studies based on two-dimensional idealized simulations. On the other hand, the present three-dimensional modeling was also able to simulate some realistic patterns of the correlation statistics, namely, mixtures of characteristic patterns and the “high-heeled” pattern as observed by satellite remote sensing.

scholarly journals A Study of Microphysical Mechanisms for Correlation Patterns between Droplet Radius and Optical Thickness of Warm Clouds with a Spectral Bin Microphysics Cloud Model

2010 ◽  
Vol 67 (4) ◽  
pp. 1126-1141 ◽  
Author(s):  
Kentaroh Suzuki ◽  
Teruyuki Nakajima ◽  
Takashi Y. Nakajima ◽  
Alexander P. Khain
Keyword(s):  
Optical Thickness ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Particle Growth ◽  
Size Distribution Function ◽  
Droplet Radius ◽  
Liquid Water Path ◽  
Correlation Pattern ◽  
Cloud Particle ◽  
Bin Microphysics

Abstract This study investigates the correlation patterns between cloud droplet effective radius (CDR) and cloud optical thickness (COT) of warm clouds with a nonhydrostatic spectral bin microphysics cloud model. Numerical experiments are performed with the model to simulate low-level warm clouds. The results show a positive and negative correlation pattern between CDR and COT for nondrizzling and drizzling stages of cloud development, respectively, consistent with findings of previous observational studies. Only a positive correlation is simulated when the collection process is switched off in the experiment, whereas both the positive and negative correlations are reproduced in the simulation with collection as well as condensation processes. The positive and negative correlations can also be explained in terms of an evolution pattern of the size distribution function due to condensation and collection processes, respectively. Sensitivity experiments are also performed to examine how the CDR–COT correlation patterns are influenced by dynamical and aerosol conditions. The dynamical effect tends to change the amplitude of the CDR–COT plot mainly through changing the liquid water path, whereas the aerosol amount significantly modifies the correlation pattern between CDR and COT mainly through changing the cloud particle number concentration. These results suggest that the satellite-observed relationships between CDR and COT can be interpreted as being formed through microphysical particle growth processes under various dynamical and aerosol conditions in the real atmosphere.

scholarly journals Conditions for super-adiabatic droplet growth after entrainment mixing

2016 ◽  
Vol 16 (14) ◽  
pp. 9421-9433 ◽  
Author(s):  
Fan Yang ◽  
Raymond Shaw ◽  
Huiwen Xue
Keyword(s):  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Critical Height ◽  
Growth Region ◽  
Cloud Droplets ◽  
Environmental Air ◽  
Bin Microphysics ◽  
Entrainment Mixing

Abstract. Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixed parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. The findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.

The Microphysics of Ice and Precipitation Development in Tropical Cumulus Clouds

2015 ◽  
Vol 72 (6) ◽  
pp. 2429-2445 ◽  
Author(s):  
R. Paul Lawson ◽  
Sarah Woods ◽  
Hugh Morrison
Keyword(s):  
High Speed ◽  
Cloud Model ◽  
Supercooled Liquid ◽  
High Speed Photography ◽  
Cumulus Clouds ◽  
Cloud Particle ◽  
Ice Particles ◽  
Aircraft Observations ◽  
Bin Microphysics ◽  
Ice Production

Abstract The rapid glaciation of tropical cumulus clouds has been an enigma and has been debated in the literature for over 60 years. Possible mechanisms responsible for the rapid freezing have been postulated, but until now direct evidence has been lacking. Recent high-speed photography of electrostatically suspended supercooled drops in the laboratory has shown that freezing events produce small secondary ice particles. Aircraft observations from the Ice in Clouds Experiment–Tropical (ICE-T), strongly suggest that the drop-freezing secondary ice production mechanism is operating in strong, tropical cumulus updraft cores. The result is the production of small ice particles colliding with large supercooled drops (hundreds of microns up to millimeters in diameter), producing a cascading process that results in rapid glaciation of water drops in the updraft. The process was analyzed from data collected using state-of-the-art cloud particle probes during 54 Learjet penetrations of strong cumulus updraft cores over open ocean in a temperature range from 5° to −20°C. Repeated Learjet penetrations of an updraft core containing 3–5 g m−3 supercooled liquid showed an order-of-magnitude decrease in liquid mass concentration 3 min later at an elevation 1–1.5 km higher in the cloud. The aircraft observations were simulated using a one-dimensional cloud model with explicit bin microphysics. The model was initialized with drop and ice particle size distributions observed prior to rapid glaciation. Simulations show that the model can explain the observed rapid glaciation by the drop-freezing secondary ice production process and subsequent riming, which results when large supercooled drops collide with ice particles.

scholarly journals Correlation Pattern between Effective Radius and Optical Thickness of Water Clouds Simulated by a Spectral Bin Microphysics Cloud Model

SOLA ◽  
2006 ◽  
Vol 2 ◽  
pp. 116-119 ◽  
Author(s):  
Kentaroh Suzuki ◽  
Teruyuki Nakajima ◽  
Takashi Y. Nakajima ◽  
Alexander Khain
Keyword(s):  
Optical Thickness ◽  
Cloud Model ◽  
Effective Radius ◽  
Correlation Pattern ◽  
Bin Microphysics

scholarly journals What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 362 ◽  
Author(s):  
Alexander V. Ryzhkov ◽  
Jeffrey Snyder ◽  
Jacob T. Carlin ◽  
Alexander Khain ◽  
Mark Pinsky
Keyword(s):  
Cloud Model ◽  
Weather Prediction ◽  
Primary Source ◽  
Polarimetric Radar ◽  
Microphysical Process ◽  
Weather Radars ◽  
Cloud Models ◽  
Cloud Modeling ◽  
Bin Microphysics ◽  
The Impact

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

Numerical Simulation of Emergency Release of Liquid Petroleum Gas on a Car Gas Station

2021 ◽  
Vol 23 ◽  
pp. 65-77
Author(s):  
Zdzislaw Salamonowicz ◽  
Malgorzata Majder-Lopatka ◽  
Anna Dmochowska ◽  
Aleksandra Piechota-Polanczyk ◽  
Andrzej Polanczyk
Keyword(s):  
Liquid Surface ◽  
Atmospheric Stability ◽  
Three Dimensional ◽  
Three Dimensional Model ◽  
Liquid Form ◽  
Cfd Simulations ◽  
Danger Zone ◽  
Liquid Petroleum Gas ◽  
Gas Station ◽  
Hazardous Zone

LPG storage tanks may be seriously threatened by a fire coming from nearby fuels or by leakage appearance. The aim of the study was to prepare a three-dimensional model of LPG release on a car gas station under different environmental conditions. CFD simulations of liquid and gas phase release from a tank localized on a car gas station was performed. First, ALOHA software was applied to determine mass flow rate, while Ansys software was used to determine the shape and size of hazardous zone. To reflect real condition atmospheric stability classes were applied. It was observed that for classes A-D the hazardous zone was decreasing. While, for E and F class the range was increased. It was noticed that the location of the leakage affects the extent of the danger zone. For the leaking below the liquid surface analyzed LPG has liquid form. While, for the leaking above the liquid surface analyzed LPG has gas form. Furthermore, for liquid leakage the largest hazard zone of release was observed.

scholarly journals Theory of Time-Dependent Freezing. Part II: Scheme for Freezing Raindrops and Simulations by a Cloud Model with Spectral Bin Microphysics

2015 ◽  
Vol 72 (1) ◽  
pp. 262-286 ◽  
Author(s):  
Vaughan T. J. Phillips ◽  
Alexander Khain ◽  
Nir Benmoshe ◽  
Eyal Ilotoviz ◽  
Alexander Ryzhkov
Keyword(s):  
Water Mass ◽  
Cloud Model ◽  
Critical Diameter ◽  
Time Dependent ◽  
Growth Surface ◽  
Mature Stage ◽  
Liquid Drops ◽  
Thermodynamic Effects ◽  
Bin Microphysics ◽  
Cloud Ice

Abstract The time-dependent process of raindrop freezing is described in a general form, including thermodynamic effects from the accretion of cloud liquid and cloud ice. Freezing drops (FDs) larger than 80 μm (and their water mass) are represented explicitly in a cloud model with spectral bin microphysics. FDs consist of interior water covered by ice initially. Possibilities of both dry (icy surface) and wet growth (surface covered by liquid) of FDs are accounted for. Schemes of time-dependent freezing for rain (discussed in this paper) and wet growth of hail and graupel (discussed in Part I) were implemented in a spectral bin microphysics cloud model. The model predicted that accretion of liquid produces giant FDs of 0.5–2 cm in diameter, far larger than purely liquid drops can become. This growth of FDs is promoted by recirculation from the downdraft back into the updraft and by cessation of internal freezing from some accreted liquid remaining unfrozen (wet growth of FDs). Significant contents of FDs reach a height level of 7 km (−29°C) in the simulated storm. After FDs finish freezing and become hailstones, wet growth may resume. The critical diameter separating wet- and dry-growth regimes is predicted to increase with height for FDs and is more vertically uniform for hail. A sensitivity test shows that time-dependent freezing initially delays the formation of hail but later in the mature stage of the storm boosts it. Convection is invigorated. Hail and freezing drops are upwelled to higher levels, causing hail to grow to sizes up to 100% larger than without time-dependent freezing.

scholarly journals GEOREFERENCING AND REPROJECTION ERROR INVESTIGATION ON IMAGE BASED 3D DIGITIZATION AND MAPPING OF HISTORICAL BUILDINGS

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 71-75
Author(s):  
C. Altuntas
Keyword(s):  
Point Cloud ◽  
Large Scale ◽  
Cloud Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Control Points ◽  
Historical Buildings ◽  
Reprojection Error ◽  
Dense Point ◽  
Point Cloud Model

<p><strong>Abstract.</strong> Image based dense point cloud creation is easy and low-cost application for three dimensional digitization of small and large scale objects and surfaces. It is especially attractive method for cultural heritage documentation. Reprojection error on conjugate keypoints indicates accuracy of the model and keypoint localisation in this method. In addition, sequential registration of the images from large scale historical buildings creates big cumulative registration error. Thus, accuracy of the model should be increased with the control points or loop close imaging. The registration of point point cloud model into the georeference system is performed using control points. In this study historical Sultan Selim Mosque that was built in sixteen century by Great Architect Sinan was modelled via photogrammetric dense point cloud. The reprojection error and number of keypoints were evaluated for different base/length ratio. In addition, georeferencing accuracy was evaluated with many configuration of control points with loop and without loop closure imaging.</p>

Using emissions derived from atmospheric observations to inform the reported UK inventory

2021 ◽  
Author(s):  
Alistair Manning ◽  
Alison Redington ◽  
Simon O'Doherty ◽  
Dickon Young ◽  
Dan Say ◽  
...  
Keyword(s):  
Best Practice ◽  
Dispersion Model ◽  
Regional Scale ◽  
Atmospheric Dispersion ◽  
Three Dimensional ◽  
Ghg Emissions ◽  
Atmospheric Observations ◽  
Emission Modelling ◽  
National Inventory Report ◽  
The Uk

&lt;p align=&quot;justify&quot;&gt;Verification of the nationally reported greenhouse gas (GHG) inventories using inverse modelling and atmospheric observations is considered to be best practice by the United Nations Framework Convention on Climate Change (UNFCCC). It allows for an independent assessment of the nationally reported GHG emissions using a comprehensively different approach to the inventory methods. Significant differences in the emissions estimated using the two approaches are a means of identifying areas worthy of further investigation.&lt;/p&gt;&lt;p align=&quot;justify&quot;&gt;&amp;#160;&lt;/p&gt;&lt;p align=&quot;justify&quot;&gt;&lt;span&gt;An inversion methodology called Inversion Technique for Emission Modelling (InTEM) has been developed that uses a non-negative least squares minimisation technique to determine the emission magnitude and distribution that most accurately reproduces the observations. By estimating the underlying &lt;/span&gt;&lt;span&gt;&lt;em&gt;baseline&lt;/em&gt;&lt;/span&gt;&lt;span&gt; time series, atmospheric concentrations where the short-term impact of regional pollution has been removed, and by modelling where the air has passed over on route to the observation stations on a regional scale, estimates of UK emissions are made. &lt;/span&gt;In this study we use an extensive network of observations with six stations across the UK and six more in neighbouring countries&lt;span&gt;. InTEM uses information from a&lt;/span&gt; Lagrangian dispersion model NAME (Numerical Atmospheric dispersion Modelling Environment), driven by three-dimensional, modelled meteorology, to understand how the air mixes during transport from the emission sources to observation points. &lt;span&gt;The InTEM inversion results are submitted annually by the UK as part of their National Inventory Report to the UNFCCC. They are used within the UK inventory team to highlight areas for investigation and have led to significant improvements to the submitted UK inventory. The latest UK comparisons will be shown along with examples of how the inversion results have informed the inventory.&lt;/span&gt;&lt;/p&gt;

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