scholarly journals A Simple Parameterization Scheme for Subtropical Marine Stratocumulus

SOLA ◽  
2006 ◽  
Vol 2 ◽  
pp. 17-20 ◽  
Author(s):  
Hideaki Kawai ◽  
Toshiro Inoue
Keyword(s):  
Parameterization Scheme ◽  
Marine Stratocumulus

scholarly journals Factors Controlling Rapid Stratocumulus Cloud Thinning

2014 ◽  
Vol 71 (2) ◽  
pp. 655-664 ◽  
Author(s):  
J. J. van der Dussen ◽  
S. R. de Roode ◽  
A. P. Siebesma
Keyword(s):  
Moisture Flux ◽  
Steady State Solution ◽  
Cloud Layer ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Buoyancy Reversal ◽  
Stratocumulus Clouds ◽  
Budget Equation ◽  
Heat And Moisture

Abstract The relationship between the inversion stability and the liquid water path (LWP) tendency of a vertically well-mixed, adiabatic stratocumulus cloud layer is investigated in this study through the analysis of the budget equation for the LWP. The LWP budget is mainly determined by the turbulent fluxes of heat and moisture at the top and the base of the cloud layer, as well as by the source terms due to radiation and precipitation. Through substitution of the inversion stability parameter κ into the budget equation, it immediately follows that the LWP tendency will become negative for increasing values of κ due to the entrainment of increasingly dry air. Large κ values are therefore associated with strong cloud thinning. Using the steady-state solution for the LWP, an equilibrium value κeq is formulated, beyond which the stratocumulus cloud will thin. The Second Dynamics and Chemistry of Marine Stratocumulus field study (DYCOMS-II) is used to illustrate that, depending mainly on the magnitude of the moisture flux at cloud base, stratocumulus clouds can persist well within the buoyancy reversal regime.

scholarly journals Machine Learning Comparison and Parameter Setting Methods for the Detection of Dump Sites for Construction and Demolition Waste Using the Google Earth Engine

2021 ◽  
Vol 13 (4) ◽  
pp. 787
Author(s):  
Lei Zhou ◽  
Ting Luo ◽  
Mingyi Du ◽  
Qiang Chen ◽  
Yang Liu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Google Earth ◽  
Construction And Demolition Waste ◽  
Parameterization Scheme ◽  
Classification Methods ◽  
Demolition Waste ◽  
Optimal Method ◽  
Identification Method ◽  
Google Earth Engine

Machine learning has been successfully used for object recognition within images. Due to the complexity of the spectrum and texture of construction and demolition waste (C&DW), it is difficult to construct an automatic identification method for C&DW based on machine learning and remote sensing data sources. Machine learning includes many types of algorithms; however, different algorithms and parameters have different identification effects on C&DW. Exploring the optimal method for automatic remote sensing identification of C&DW is an important approach for the intelligent supervision of C&DW. This study investigates the megacity of Beijing, which is facing high risk of C&DW pollution. To improve the classification accuracy of C&DW, buildings, vegetation, water, and crops were selected as comparative training samples based on the Google Earth Engine (GEE), and Sentinel-2 was used as the data source. Three classification methods of typical machine learning algorithms (classification and regression trees (CART), random forest (RF), and support vector machine (SVM)) were selected to classify the C&DW from remote sensing images. Using empirical methods, the experimental trial method, and the grid search method, the optimal parameterization scheme of the three classification methods was studied to determine the optimal method of remote sensing identification of C&DW based on machine learning. Through accuracy evaluation and ground verification, the overall recognition accuracies of CART, RF, and SVM for C&DW were 73.12%, 98.05%, and 85.62%, respectively, under the optimal parameterization scheme determined in this study. Among these algorithms, RF was a better C&DW identification method than were CART and SVM when the number of decision trees was 50. This study explores the robust machine learning method for automatic remote sensing identification of C&DW and provides a scientific basis for intelligent supervision and resource utilization of C&DW.

scholarly journals A Modeling Case Study of Mixed-Phase Clouds over the Southern Ocean and Tasmania

2010 ◽  
Vol 138 (3) ◽  
pp. 839-862 ◽  
Author(s):  
Anthony E. Morrison ◽  
Steven T. Siems ◽  
Michael J. Manton ◽  
Alex Nazarov
Keyword(s):  
Southern Ocean ◽  
Supercooled Liquid ◽  
Mixed Phase ◽  
Weather Research And Forecasting ◽  
Marine Stratocumulus ◽  
Cloud Structure ◽  
In Situ Observations ◽  
Cloud Tops ◽  
Mixed Phase Clouds

Abstract The cloud structure associated with two frontal passages over the Southern Ocean and Tasmania is investigated. The first event, during August 2006, is characterized by large quantities of supercooled liquid water and little ice. The second case, during October 2007, is more mixed phase. The Weather Research and Forecasting model (WRFV2.2.1) is evaluated using remote sensed and in situ observations within the post frontal air mass. The Thompson microphysics module is used to describe in-cloud processes, where ice is initiated using the Cooper parameterization at temperatures lower than −8°C or at ice supersaturations greater than 8%. The evaluated cases are then used to numerically investigate the prevalence of supercooled and mixed-phase clouds over Tasmania and the ocean to the west. The simulations produce marine stratocumulus-like clouds with maximum heights of between 3 and 5 km. These are capped by weak temperature and strong moisture inversions. When the inversion is at temperatures warmer than −10°C, WRF produces widespread supercooled cloud fields with little glaciation. This is consistent with the limited in situ observations. When the inversion is at higher altitudes, allowing cooler cloud tops, glaciated (and to a lesser extent mixed phase) clouds are more common. The simulations are further explored to evaluate any orographic signature within the cloud structure over Tasmania. No consistent signature is found between the two cases.

scholarly journals Impact of Gravity Waves on Marine Stratocumulus Variability

2012 ◽  
Vol 69 (12) ◽  
pp. 3633-3651 ◽  
Author(s):  
Qingfang Jiang ◽  
Shouping Wang
Keyword(s):  
Gravity Waves ◽  
Vertical Motion ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Large Eddy Simulation Model ◽  
Cloud Albedo ◽  
Eddy Simulation ◽  
Aerosol Number Concentration ◽  
Wave Induced ◽  
The Impact

Abstract The impact of gravity waves on marine stratocumulus is investigated using a large-eddy simulation model initialized with sounding profiles composited from the Variability of American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-Rex) aircraft measurements and forced by convergence or divergence that mimics mesoscale diurnal, semidiurnal, and quarter-diurnal waves. These simulations suggest that wave-induced vertical motion can dramatically modify the cloud albedo and morphology through nonlinear cloud–aerosol–precipitation–circulation–turbulence feedback. In general, wave-induced ascent tends to increase the liquid water path (LWP) and the cloud albedo. With a proper aerosol number concentration, the increase in the LWP leads to enhanced precipitation, which triggers or strengthens mesoscale circulations in the boundary layer and accelerates cloud cellularization. Precipitation also tends to create a decoupling structure by weakening the turbulence in the subcloud layer. Wave-induced descent decreases the cloud albedo by dissipating clouds and forcing a transition from overcast to scattered clouds or from closed to open cells. The overall effect of gravity waves on the cloud variability and morphology depends on the cloud property, aerosol concentration, and wave characteristics. In several simulations, a transition from closed to open cells occurs under the influence of gravity waves, implying that some of the pockets of clouds (POCs) observed over open oceans may be related to gravity wave activities.

Can Marine Cloud Brightening Reduce Sea-Surface Temperatures to Moderate Extreme Hurricanes and Typhoons?

2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Salter SH ◽  
Keyword(s):  
Boundary Layer ◽  
Marine Boundary Layer ◽  
Sea Water ◽  
Cloud Condensation Nuclei ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Marine Stratocumulus ◽  
Surface Temperatures ◽  
Stratocumulus Clouds ◽  
Cloud Tops

Elevated sea-surface temperatures are a necessary but not sufficient requirement for the formation of hurricanes and typhoons. This paper suggests a way to exploit this. Twomey [1] showed that cloud reflectivity depends on the size-distribution of cloud drops, with a large number of small drops reflecting more than a smaller number of larger ones. Mid-ocean air is cleaner than over land. Latham [2-4] suggested that reflectivity of marine stratocumulus clouds could be increased by releasing a submicron spray of filtered sea water into the bottom of the marine boundary layer. The salt residues left after evaporation would be mixed by turbulence through the full depth of the marine boundary layer and would be ideal cloud condensation nuclei. Those that reached a height where the air had a super-saturation above 100% by enough to get over the peak of the Köhler curve would produce an increased number of cloud drops and so trigger the Twomey effect. The increase in reflection from cloud tops back out to space would cool sea-surface water. We are not trying to increase cloud cover; we just want to make existing cloud tops whiter. The spray could be produced by wind-driven vessels cruising chosen ocean regions. The engineering design of sea-going hardware is well advanced. This paper suggests a way to calculate spray quantities and the number and cost of spray vessels to achieve a hurricane reduction to a more acceptable intensity. It is intended to show the shape of a possible calculation with credible if not exact assumptions. Anyone with better assumptions should be able to follow the process.

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