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The probability density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

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Advances in Atmospheric Sciences 2024年第1期41卷 173-187页

作者： Lei ZHU Chunsong LU Xiaoqi XU Xin HE Junjun LI Shi LUO Yuan WANG Fan WANG Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)and Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science and TechnologyNanjing 210044China Nanjing Joint Institute for Atmospheric Sciences Nanjing 210019China College of Aviation Meteorology Civil Aviation Flight University of ChinaGuanghan 618307China Collaborative Innovation Center for Western Ecological Safety Lanzhou UniversityLanzhou 730000China Department of Geography Hong Kong Baptist UniversityHong Kong SAR 999077China

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus *** obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization *** this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy *** results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved *** probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous *** analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the *** results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

关键词： large-eddy simulation cumulus clouds entrainment rate probability density functions spatial and temporal distribution

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Probabilistic modeling of soil moisture dynamics in a revegetated desert area

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Research in Cold and Arid Regions 2013年第2期5卷 205-210页

作者： Lei Huang ZhiShan Zhang YongLe Chen Shapotou Desert Research and Experiment Station Cold and Arid Regions Environmental and Engineering Research Institute Chinese Academy of Sciences

Soil moisture is the key link between land hydrological and ecological processes which plays an important role in the terrestrial water cycle. As extreme weather events have increased in recent years, the stochastic simulation of soil moisture has gradually become the focus of ecohydrology research. Based on continuous monitoring of soil moisture data from 2008 to 2011, and histor- ical precipitation data from 199l to 2011, combined with the Rodriguez-Iturbe soil moisture dynamic stochastic model, soil mois- ture dynamics and its probability density fimction in a revegetated desert area was simulated. Results show that annual soil mois- ture dynamic changes of the revegetated desert area during the growing season complied with rainfall distribution; soil moisture probability presents a single-peak distribution in the plant rhizosphere layer （0-60 cm）. The peak width in the 20 cm topsoil was wider than in other soils, and the distribution presented the strong fluctuations and multiple aggregates. The peak widths of 40 cm and 60 cm soil moisture probability distribution were small, which are in accordance with simulated results of the Rodri- guez-lturbe model. This confrms that the Rodriguez-Imrbe model has good applicability and can well simulate the statistical characteristics of soil moisture in an arid revegetated desert area.

关键词： revegetated desert area soil moisture Rodriguez-Iturbe model probability density functions

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Recent Advances on Stochastic Distribution Control:probability density Function Control

Recent Advances on Stochastic Distribution Control:Probabili...

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2009中国控制与决策会议

作者： Aiping Wang~1,Hong Wang~2 and Lei Guo~3 1.Institute of Computer Sciences,Anhui University,Hefei,P R China 2.Control Systems Centre,the University of Manchester,Manchester,England,UK 3.School of Instrumentation and Opto-Electronics Engineering,Beihang University,P R China

＜正＞This semi-plenary paper presents a brief and selected survey on the advances on stochastic distribution control,where the purpose of the controller design is to control the shape of output probability density functions（pdf） of non-Gaussian and general stochastic *** research was motivated through the requirement of distribution shape control of a number of practical systems in *** the developments since 1996,much research has been performed internationally and journal special issues and invited session at major conferences have been seen since 2001. It is expected that this survey will provide readers with some up-to-date information on this new area.

关键词： probability density functions stochastic systems control systems design

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