Cloud Parameterizations, Cloud Physics, and Their Connections: an Overview
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Exercise 10: Cumulus Cloud with Bulk Cloud Physics
Exercise Hints Tasks Results Exercise 10: Cumulus Cloud With Bulk Cloud Physics PALM group Institute of Meteorology and Climatology, Leibniz Universität Hannover last update: 21st September 2015 PALM group PALM Seminar 1 / 16 I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. I Trigger the cloud by a bubble of rising warm air. I Parameterize condensation using a simple bulk cloud physics scheme. I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: PALM group PALM Seminar 2 / 16 I Trigger the cloud by a bubble of rising warm air. I Parameterize condensation using a simple bulk cloud physics scheme. I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. PALM group PALM Seminar 2 / 16 I Parameterize condensation using a simple bulk cloud physics scheme. I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. I Trigger the cloud by a bubble of rising warm air. PALM group PALM Seminar 2 / 16 I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. -
Exam 2: Cloud Physics April 16, 2008 Physical Meteorology 3440
Name ____________________________ Exam 2: Cloud Physics April 16, 2008 Physical Meteorology 3440 Questions 1-10 are worth 5 points each. Questions 11-15 are worth 10 points each. 1. Rank the concentrations of the following from lowest (1) to highest (3): cloud condensation nuclei (3) cloud droplets (2) raindrops (1) 2. Match the following particles with their typical size cloud condensation nuclei 10 μm cloud droplets 0.1 μm raindrops 1000 μm 3. Why do ice crystals grow at the expense of supercooled water droplets? The saturation vapor pressure over liquid is higher than the saturation vapor pressure over ice. Therefore, the environment will be more supersaturated with respect to ice than with respect to liquid, and the ice crystals will grow more quickly. At some point, the ice crystals may bring S (with respect to ice) down to 1, in which case Sl (with respect to liquid) is less than 1, causing the liquid drops to evaporate. 4. Match the following particles with their most likely means of growth 5 μm cloud drop accretion 5 μm ice crystal aggregation 100 μm dendritic ice crystals in ice cloud depositional growth 500 μm ice crystal in mixed-phase cloud condensational growth 100 μm cloud drop collision-coalescence 5. Fill in the blanks: Not all clouds with temperatures below the freezing point of water contain ice, because of the scarcity of ice nuclei in the atmosphere, and the temperature at which they nucleate ice. As the cloud temperature decreases, the probability of ice increases to the 1 temperature of -40 °C, at which point homogeneous freezing occurs. -
Synoptic Meteorology
Lecture Notes on Synoptic Meteorology For Integrated Meteorological Training Course By Dr. Prakash Khare Scientist E India Meteorological Department Meteorological Training Institute Pashan,Pune-8 186 IMTC SYLLABUS OF SYNOPTIC METEOROLOGY (FOR DIRECT RECRUITED S.A’S OF IMD) Theory (25 Periods) ❖ Scales of weather systems; Network of Observatories; Surface, upper air; special observations (satellite, radar, aircraft etc.); analysis of fields of meteorological elements on synoptic charts; Vertical time / cross sections and their analysis. ❖ Wind and pressure analysis: Isobars on level surface and contours on constant pressure surface. Isotherms, thickness field; examples of geostrophic, gradient and thermal winds: slope of pressure system, streamline and Isotachs analysis. ❖ Western disturbance and its structure and associated weather, Waves in mid-latitude westerlies. ❖ Thunderstorm and severe local storm, synoptic conditions favourable for thunderstorm, concepts of triggering mechanism, conditional instability; Norwesters, dust storm, hail storm. Squall, tornado, microburst/cloudburst, landslide. ❖ Indian summer monsoon; S.W. Monsoon onset: semi permanent systems, Active and break monsoon, Monsoon depressions: MTC; Offshore troughs/vortices. Influence of extra tropical troughs and typhoons in northwest Pacific; withdrawal of S.W. Monsoon, Northeast monsoon, ❖ Tropical Cyclone: Life cycle, vertical and horizontal structure of TC, Its movement and intensification. Weather associated with TC. Easterly wave and its structure and associated weather. ❖ Jet Streams – WMO definition of Jet stream, different jet streams around the globe, Jet streams and weather ❖ Meso-scale meteorology, sea and land breezes, mountain/valley winds, mountain wave. ❖ Short range weather forecasting (Elementary ideas only); persistence, climatology and steering methods, movement and development of synoptic scale systems; Analogue techniques- prediction of individual weather elements, visibility, surface and upper level winds, convective phenomena. -
Twelve Lectures on Cloud Physics
Twelve Lectures on Cloud Physics Bjorn Stevens Winter Semester 2010-2011 Contents 1 Lecture 1: Clouds–An Overview3 1.1 Organization...........................................3 1.2 What is a cloud?.........................................3 1.3 Why are we interested in clouds?................................4 1.4 Cloud classification schemes..................................5 2 Lecture 2: Thermodynamic Basics6 2.1 Thermodynamics: A brief review................................6 2.2 Variables............................................8 2.3 Intensive, Extensive, and specific variables...........................8 2.3.1 Thermodynamic Coordinates..............................8 2.3.2 Composite Systems...................................8 2.3.3 The many variables of atmospheric thermodynamics.................8 2.4 Processes............................................ 10 2.5 Saturation............................................ 10 3 Lecture 3: Droplet Activation 11 3.1 Supersaturation over curved surfaces.............................. 12 3.2 Solute effects.......................................... 14 3.3 The Kohler¨ equation and its properties............................. 15 4 Lecture 4: Further Properties of an Isolated Drop 16 4.1 Diffusional growth....................................... 16 4.1.1 Temperature corrections................................ 18 4.1.2 Drop size effects on droplet growth.......................... 20 4.2 Terminal fall speeds of drops and droplets........................... 20 5 Lecture 5: Populations of Particles 22 5.1 -
Lightning Dr
ESCI 340 - Cloud Physics and Precipitation Processes Lesson 12 - Lightning Dr. DeCaria References: The Lightning Discharge, Uman The Electrical Nature of Storms, MacGorman and Rust Fundamentals of Lightning, Rakov `Runaway Breakdown and the Mysteries of Lightning', Gurevich and Zybin, Physics Today, 2005 Mechanisms of Charge Separation • The top of a thunderstorm (cumulonimbus) cloud becomes positively charged, while the middle-to-lower portions of the cloud becomes negatively charged. • Often there is also a smaller pocket of positive charge near the bottom of the cloud. • The reason for this charge separation is not completely understood, but some of the more prominent theories are described below. • Those mechanisms requiring a preexisting electric field are called inductive charging mechanisms, while those not requiring a preexisting electric field are called nonin- ductive charging mechanisms. Inductive ion capture: In a preexisting electrical field, there will be a separation of charge across a hydrometeor. As the hydrometeor falls, gaseous ions will either be attracted or repelled from the underside of the hydrometeor, depending on their sign. Thus, the hydrometeor will gain an increasing charge of whatever sign it has on its topside. In Fig. 1 the positive ions are repelled as the hydrometeor falls, but the negative ions are attracted. Thus, the hydrometeor gains a net negative charge as it falls. Figure 1: Inductive ion capture. 1 Ion capture may play a role in weakly electrified storms, but cannot be used to explain the amount of charge separation seen in a thunderstorm without the presence of other mechanisms. Inductive particle rebound: Two hydrometeors in a preexisting electric field, falling at different speeds, will exchange charge during collision as shown in Fig. -
SUBSIDENCE in MARITIME AIR OVER the COLUMBIA and SNAKE RIVER BASINS by ARCHERB
JANUARY1936 MONTHLY WEATRER REVIEW 9 SUBSIDENCE IN MARITIME AIR OVER THE COLUMBIA AND SNAKE RIVER BASINS By ARCHERB. CARPENTER [Weather Bureau, Portland, Oreg., October 18361 The Columbia and Snake River Basins arc surrounded direction of movement is favorable to development of by theRocky Mountains to the northeast, east, and south- stagnation in the drainage areas of the Columbia and east; a high plateau to the south; and the Cmcade Range Snake Rivers. The air mass that followed was charac- to the west. In addition to this almost continuous rim teristically polar Pacific (PP),with showers over Washing- that surrounds the combined basins, there is the ridge of ton and parts of Oregon for several days. No airplane the Blue Mountains between them. The most notablc observations were available in this air mass to further and most effective outlet for this great area is the Co- identify it. Surface radiation and air drainage in the lumhia River Gorge. Columbia River Basin produced the first patches of fog The period co\--ered in the present study extended from and low clouds on the east, slope of the Cascade Range on January 19 to February 10, 1935; and the problem inves- the morning of January 34. These fog patches increased tigated is that of subsidence in the maritime air associated with low stratus clouds and fog. This type of stagnation is not uncommon in the Columbia River Basin east of the Cascade Range, but it is less common for the effects of this stagnation to reach over into the Snake River Basin, and to be persistent for such a long period. -
Cloud Microphysics
Cloud microphysics Claudia Emde Meteorological Institute, LMU, Munich, Germany WS 2011/2012 Overview of cloud physics lecture Atmospheric thermodynamics gas laws, hydrostatic equation 1st law of thermodynamics moisture parameters adiabatic / pseudoadiabatic processes stability criteria / cloud formation Microphysics of warm clouds nucleation of water vapor by condensation growth of cloud droplets in warm clouds (condensation, fall speed of droplets, collection, coalescence) formation of rain, stochastical coalescence Microphysics of cold clouds homogeneous nucleation heterogeneous nucleation contact nucleation crystal growth (from water phase, riming, aggregation) formation of precipitation Observation of cloud microphysical properties Parameterization of clouds in climate and NWP models Cloud microphysics November 24, 2011 2 / 35 Growth rate and size distribution growing droplets consume water vapor faster than it is made available by cooling and supersaturation decreases haze droplets evaporate, activated droplets continue to grow by condensation growth rate of water droplet dr 1 = G S dt l r smaller droplets grow faster than larger droplets sizes of droplets in cloud become increasingly uniform, approach monodisperse distribution Figure from Wallace and Hobbs Cloud microphysics November 24, 2011 3 / 35 Size distribution evolution q 2 r = r0 + 2Gl St 0.8 1.4 t=0 t=0 0.7 t=10 t=10 1.2 t=30 t=30 0.6 t=50 t=50 1.0 0.5 0.8 0.4 0.6 0.3 n [normalized] n [normalized] 0.4 0.2 0.2 0.1 0.0 0.0 0 2 4 6 8 10 12 14 16 0 2 4 6 8 10 12 14 16 radius [arbitrary units] radius [arbitrary units] Cloud microphysics November 24, 2011 4 / 35 Growth by collection growth by condensation alone does not explain formation of larger drops other mechanism: growth by collection Cloud microphysics November 24, 2011 5 / 35 Terminal fall speed r 40µ . -
Microbursts As an Aviation Wind Shear Hazard TT Fujita, University Of
0 AIAA-81-0386 Microbursts as an Aviation Wind Shear Hazard T. T. Fujita, University of Ch ica go , 111. '· AIAA 19th AEROSPACE SCIENCES MEETl'NG January12-15, 1981/St. Louis, Missouri .for permission to copy or republish, contact the American Institute of Aeron1ut1cs and Astronautlc.s • 1290 Avenue of the Americas, New Yark, N.Y. 10104 .. NOTES •• MICROBURSTS AS AN AVIATION WIND SHEAR HAZARD T. Theodore Fujita* The University of Chicago Chicago, Illinois Introduction Aircraft operations, for both comfort and ABSTRACT safety , are closely related to the weather situ ations along the flight path. High pressure Since the Eastern 66 accident in 1975 at regions {anticyclones) are generally dominated JFK International Airport, downburst-related by fine weather, while turbulent weather occurs accidents or near-miss cases of jet aircraft in or near the frontal zone. Nonetheless, we have been occurring at the rate of once or cannot always generalize these simple relation twice a year. A microburst with its field, ships irrespective of the scales of atmospheric comparable to the length of runways, could disturbances. induce a wind shear that endan9ers landing or l ift-off aircraft. Latest near-miss landing The high pressure vs. fine weather relation {go around) of a 727 aircraft at Atlanta, Ga., ship is no longer valid in mesoscale high on 22 August 1979 implied that some micro pressure systems, cal led the "pressure dome" by bursts are so smal l that they may not trigger Byers and Braham (1949). They also defined the the warnina device of the anemometer network "pressure nose" to be a sma ll mesoscale high installed and operated at major U.S. -
Variability of Marine Fog Along the California Coast
VARIABILITY OF MARINE FOG ALONG THE CALIFORNIA COAST Maria K. Filonczuk, Daniel R. Cayan, and Laurence G. Riddle Climate Research Division Scripps Institution of Oceanography University of California, San Diego La Jolla, California 92093-0224 SIO REFERENCE NO. 95-2 July 1995 Table of Contents 1. Introduction ......................................................................1 2 . Climatological and Topographic Influences ................................2 2.1. General Climatology ...................................................2 2.2. Topography .............................................................3 3 . Background and Objectives ...................................................5 3.1 . Fog Mechanisms .......................................................5 3 .2. Objectives ...............................................................6 4 . Data .............................................................................6 5 . Climatology of West Coast Fog .............................................13 5.1. Seasonal Variability .................................................. 13 5.1.1. Coastal Station Fog Climatology .................................. 13 5.1.2. Marine Fog Climatology .............................................16 5.2. Interannual Variability ...............................................21 5.2.1. Coastal Stations .......................................................21 5.2.2. Marine Observations .................................................31 6 . Local Connections with Marine Fog ...................................... -
Thunderstorm Anatomy and Dynamics
THUNDERSTORM ANATOMY AND DYNAMICS An Overview Prepared by LCDR Bill Nisley MR 3421 • Cloud Physics Naval Postgraduate School • Monterey, California [email protected] Photo credits: Thunderstorm Cell and Mammatus Clouds by: Michael Bath; Tornado by Daphne Zaras / NSSL; Supercell Thunderstorm by: AMOS; Wall Cloud by: Greg Michels 1. Introduction The purpose of this paper is to present a broad overview of the various cloud structures displayed during the life cycle of a thunderstorm and the atmospheric dynamics associated with each. Knowledge of atmospheric dynamics provides for a keener understanding of the physical processes related to the “why and how” certain cloud features form. Accordingly, observation of cloud features presents visual queuing of changes in the atmosphere. 2. Thunderstorm Formation and Stages of Development Thunderstorm development is dependent on three basic components: moisture, instability, and some form of lifting mechanism. 2.1 Moisture – As air near the surface is lifted higher in the atmosphere and cooled, available water vapor condenses into small water droplets which form clouds. As condensation of water vapor occurs, latent heat is released making the rising air warmer and less dense than its surroundings (figure 1). The added heat allows the air (parcel) to continue to rise and form an updraft within the developing cloud structure. 2.1.1 In general1, low level moisture increases instability simply by making more latent heat available to the lower atmosphere. Increasing mid level moisture can decrease instability in the atmosphere because moist air is less dense than dry air and therefor is unable to evaporate • Figure 1 – Positive buoyancy / instability as a result of precipitation and cloud droplets as condensation and release of latent heat. -
Charge Accumulation in Thunderstorm Clouds: Fractal Dynamic Model
E3S Web of Conferences 127, 01001 (2019) https://doi.org/10.1051/e3sconf /201912701001 Solar-Terrestrial Relations and Physics of Earthquake Precursors Charge accumulation in thunderstorm clouds: fractal dynamic model Tembulat Kumykov* Institute of Applied Mathematics and Automation KBSC RAS, 360004 st. Shortanova, 89-а Nalchik, Russia Abstract. The paper considers a fractal dynamic charge accumulation model in thunderstorm clouds in view of the fractal dimension. Analytic solution to the model equation has been found. Using numerical calculations we have shown the relationship between the charge accumulation and the medium with the fractal structure. A comparative study of thunderstorm electrification mechanisms have been performed. 1 Introduction Convective clouds inside which thunderstorm processes mainly develop are natural objects with nontrivial fractal structure [1]. One of the most important thunderstorm parameters is the electric field intensity. Once a lightning strike have occurred, the electric field weakens and then recovers. The process of restoring neutralized charges and respectively the electric field after the thunderstorm discharge is the matter of animated debate among scientists. As is known, a central place in thunderstorm electricity occupies charge generation and separation processes inside convective clouds. About two dozen current mechanisms are known that result in charges generation inside the thunderclouds [2]. They can be divided into two groups. The first group is associated with elementary processes in the clouds:, the electrification within the ionic environment, the electrification caused by frictional contact between two icicles, the electrification accompanying the freezing of water and its solutions, the electrification upon destruction of crystallizing droplets, etc., The second group includes the induction electrification mechanism stipulated by the electric field, whose origin is not yet clear. -
Evaluation of ISKA Forecast Performance
Evaluation of ISKA forecast performance An investigation on binary and probabilistic forecast skill scores Björn Claremar, PhD Department of Earth Sciences Uppsala University Villavägen 16 SE-75236 Uppsala Sweden Uppsala, 12 March 2019 ii Evaluation of ISKA forecast performance Abstract The company Ignitia provides rainfall forecasts through SMS to subscribers in Ghana, Mali and some other countries in the West African region south of Sahara. Their ensemble-based probabilistic forecast product iska, based on the high-resolution weather model WRF with modifications, has been developed to better simulate tropical conditions where rainfall is driven by convection. This external investigation determined the forecast skill of iska by validating against NOAA satellite rainfall product. As comparison, rainfall probability forecasts from the global model GFS and from Weather Underground were evaluated. The iska forecasts outperformed the GFS forecasts and the Weather Underground forecasts in terms of accuracy. The statistical skill decreased towards the Sahel region and also towards the coast, the latter probably an artefact of the NOAA product having problems in identifying local warm-cloud rain, meaning that the forecast skill by the coast might be better than indicated. Keywords: West Africa, Ghana, Mali, Tropical weather, Weather forecast, Meteorology, WRF, rainfall, forecast skill, probabilistic, statistics, iska iii Executive summary Background Ignitia was seeking to evaluate the performance of its daily probabilistic rainfall forecasts through external party. The validation included making a comparison against baseline forecasts from NCEP (GFS), which is the most widely used source due to its free and public availability for commercial use, as well as data from a common online provider; forecasts from Weather Underground which is a subsidiary of The Weather Company, owned by IBM.