MSE3 Ch14 Thunderstorms
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CALIFORNIA STATE UNIVERSITY, NORTHRIDGE FORECASTING CALIFORNIA THUNDERSTORMS a Thesis Submitted in Partial Fulfillment of the Re
CALIFORNIA STATE UNIVERSITY, NORTHRIDGE FORECASTING CALIFORNIA THUNDERSTORMS A thesis submitted in partial fulfillment of the requirements For the degree of Master of Arts in Geography By Ilya Neyman May 2013 The thesis of Ilya Neyman is approved: _______________________ _________________ Dr. Steve LaDochy Date _______________________ _________________ Dr. Ron Davidson Date _______________________ _________________ Dr. James Hayes, Chair Date California State University, Northridge ii TABLE OF CONTENTS SIGNATURE PAGE ii ABSTRACT iv INTRODUCTION 1 THESIS STATEMENT 12 IMPORTANT TERMS AND DEFINITIONS 13 LITERATURE REVIEW 17 APPROACH AND METHODOLOGY 24 TRADITIONALLY RECOGNIZED TORNADIC PARAMETERS 28 CASE STUDY 1: SEPTEMBER 10, 2011 33 CASE STUDY 2: JULY 29, 2003 48 CASE STUDY 3: JANUARY 19, 2010 62 CASE STUDY 4: MAY 22, 2008 91 CONCLUSIONS 111 REFERENCES 116 iii ABSTRACT FORECASTING CALIFORNIA THUNDERSTORMS By Ilya Neyman Master of Arts in Geography Thunderstorms are a significant forecasting concern for southern California. Even though convection across this region is less frequent than in many other parts of the country significant thunderstorm events and occasional severe weather does occur. It has been found that a further challenge in convective forecasting across southern California is due to the variety of sub-regions that exist including coastal plains, inland valleys, mountains and deserts, each of which is associated with different weather conditions and sometimes drastically different convective parameters. In this paper four recent thunderstorm case studies were conducted, with each one representative of a different category of seasonal and synoptic patterns that are known to affect southern California. In addition to supporting points made in prior literature there were numerous new and unique findings that were discovered during the scope of this research and these are discussed as they are investigated in their respective case study as applicable. -
Chapter 8 Atmospheric Statics and Stability
Chapter 8 Atmospheric Statics and Stability 1. The Hydrostatic Equation • HydroSTATIC – dw/dt = 0! • Represents the balance between the upward directed pressure gradient force and downward directed gravity. ρ = const within this slab dp A=1 dz Force balance p-dp ρ p g d z upward pressure gradient force = downward force by gravity • p=F/A. A=1 m2, so upward force on bottom of slab is p, downward force on top is p-dp, so net upward force is dp. • Weight due to gravity is F=mg=ρgdz • Force balance: dp/dz = -ρg 2. Geopotential • Like potential energy. It is the work done on a parcel of air (per unit mass, to raise that parcel from the ground to a height z. • dφ ≡ gdz, so • Geopotential height – used as vertical coordinate often in synoptic meteorology. ≡ φ( 2 • Z z)/go (where go is 9.81 m/s ). • Note: Since gravity decreases with height (only slightly in troposphere), geopotential height Z will be a little less than actual height z. 3. The Hypsometric Equation and Thickness • Combining the equation for geopotential height with the ρ hydrostatic equation and the equation of state p = Rd Tv, • Integrating and assuming a mean virtual temp (so it can be a constant and pulled outside the integral), we get the hypsometric equation: • For a given mean virtual temperature, this equation allows for calculation of the thickness of the layer between 2 given pressure levels. • For two given pressure levels, the thickness is lower when the virtual temperature is lower, (ie., denser air). • Since thickness is readily calculated from radiosonde measurements, it provides an excellent forecasting tool. -
Comparison Between Observed Convective Cloud-Base Heights and Lifting Condensation Level for Two Different Lifted Parcels
AUGUST 2002 NOTES AND CORRESPONDENCE 885 Comparison between Observed Convective Cloud-Base Heights and Lifting Condensation Level for Two Different Lifted Parcels JEFFREY P. C RAVEN AND RYAN E. JEWELL NOAA/NWS/Storm Prediction Center, Norman, Oklahoma HAROLD E. BROOKS NOAA/National Severe Storms Laboratory, Norman, Oklahoma 6 January 2002 and 16 April 2002 ABSTRACT Approximately 400 Automated Surface Observing System (ASOS) observations of convective cloud-base heights at 2300 UTC were collected from April through August of 2001. These observations were compared with lifting condensation level (LCL) heights above ground level determined by 0000 UTC rawinsonde soundings from collocated upper-air sites. The LCL heights were calculated using both surface-based parcels (SBLCL) and mean-layer parcels (MLLCLÐusing mean temperature and dewpoint in lowest 100 hPa). The results show that the mean error for the MLLCL heights was substantially less than for SBLCL heights, with SBLCL heights consistently lower than observed cloud bases. These ®ndings suggest that the mean-layer parcel is likely more representative of the actual parcel associated with convective cloud development, which has implications for calculations of thermodynamic parameters such as convective available potential energy (CAPE) and convective inhibition. In addition, the median value of surface-based CAPE (SBCAPE) was more than 2 times that of the mean-layer CAPE (MLCAPE). Thus, caution is advised when considering surface-based thermodynamic indices, despite the assumed presence of a well-mixed afternoon boundary layer. 1. Introduction dry-adiabatic temperature pro®le (constant potential The lifting condensation level (LCL) has long been temperature in the mixed layer) and a moisture pro®le used to estimate boundary layer cloud heights (e.g., described by a constant mixing ratio. -
Thunderstorm Predictors and Their Forecast Skill for the Netherlands
Atmospheric Research 67–68 (2003) 273–299 www.elsevier.com/locate/atmos Thunderstorm predictors and their forecast skill for the Netherlands Alwin J. Haklander, Aarnout Van Delden* Institute for Marine and Atmospheric Sciences, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands Accepted 28 March 2003 Abstract Thirty-two different thunderstorm predictors, derived from rawinsonde observations, have been evaluated specifically for the Netherlands. For each of the 32 thunderstorm predictors, forecast skill as a function of the chosen threshold was determined, based on at least 10280 six-hourly rawinsonde observations at De Bilt. Thunderstorm activity was monitored by the Arrival Time Difference (ATD) lightning detection and location system from the UK Met Office. Confidence was gained in the ATD data by comparing them with hourly surface observations (thunder heard) for 4015 six-hour time intervals and six different detection radii around De Bilt. As an aside, we found that a detection radius of 20 km (the distance up to which thunder can usually be heard) yielded an optimum in the correlation between the observation and the detection of lightning activity. The dichotomous predictand was chosen to be any detected lightning activity within 100 km from De Bilt during the 6 h following a rawinsonde observation. According to the comparison of ATD data with present weather data, 95.5% of the observed thunderstorms at De Bilt were also detected within 100 km. By using verification parameters such as the True Skill Statistic (TSS) and the Heidke Skill Score (Heidke), optimal thresholds and relative forecast skill for all thunderstorm predictors have been evaluated. -
1 Module 4 Water Vapour in the Atmosphere 4.1 Statement of The
Module 4 Water Vapour in the Atmosphere 4.1 Statement of the General Meteorological Problem D. Brunt (1941) in his book Physical and Dynamical Meteorology has stated, “The main problem to be discussed in connection to the thermodynamics of the moist air is the variation of temperature produced by changes of pressure, which in the atmosphere are associated with vertical motion. When damp air ascends, it must eventually attain saturation, and further ascent produces condensation, at first in the form of water drops, and as snow in the later stages”. This statement of the problem emphasizes the role of vertical ascends in producing condensation of water vapour. However, several text books and papers discuss this problem on the assumption that products of condensation are carried with the ascending air current and the process is strictly reversible; meaning that if the damp air and water drops or snow are again brought downwards, the evaporation of water drops or snow uses up the same amount of latent heat as it was liberated by condensation on the upward path of the air. Another assumption is that the drops fall out as the damp air ascends but then the process is not reversible, and Von Bezold (1883) termed it as a pseudo-adiabatic process. It must be pointed out that if the products of condensation are retained in the ascending current, the mathematical treatment is easier in comparison to the pseudo-adiabatic case. There are four stages that can be discussed in connection to the ascent of moist air. (a) The air is saturated; (b) The air is saturated and contains water drops at a temperature above the freezing-point; (c) All the water drops freeze into ice at 0°C; (d) Saturated air and ice at temperatures below 0°C. -
Convective Cores in Continental and Oceanic Thunderstorms: Strength, Width, And
Convective Cores in Continental and Oceanic Thunderstorms: Strength, Width, and Dynamics THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Alexander Michael McCarthy, B.S. Graduate Program in Atmospheric Sciences The Ohio State University 2017 Master's Examination Committee: Jialin Lin, Advisor Jay Hobgood Bryan Mark Copyrighted by Alexander Michael McCarthy 2017 Abstract While aircraft penetration data of oceanic thunderstorms has been collected in several field campaigns between the 1970’s and 1990’s, the continental data they were compared to all stem from penetrations collected from the Thunderstorm Project in 1947. An analysis of an updated dataset where modern instruments allowed for more accurate measurements was used to make comparisons to prior oceanic field campaigns that used similar instrumentation and methodology. Comparisons of diameter and vertical velocity were found to be similar to previous findings. Cloud liquid water content magnitudes were found to be significantly greater over the oceans than over the continents, though the vertical profile of oceanic liquid water content showed a much more marked decrease with height above 4000 m than the continental profile, lending evidence that entrainment has a greater impact on oceanic convection than continental convection. The difference in buoyancy between vigorous continental and oceanic convection was investigated using a reversible CAPE calculation. It was found that for the strongest thunderstorms over the continents and oceans, oceanic CAPE values tended to be significantly higher than their continental counterparts. Alternatively, an irreversible CAPE calculation was used to investigate the role of entrainment in reducing buoyancy for continental and oceanic convection where it was found that entrainment played a greater role in diluting oceanic buoyancy than continental buoyancy. -
Stability Analysis, Page 1 Synoptic Meteorology I
Synoptic Meteorology I: Stability Analysis For Further Reading Most information contained within these lecture notes is drawn from Chapters 4 and 5 of “The Use of the Skew T, Log P Diagram in Analysis and Forecasting” by the Air Force Weather Agency, a PDF copy of which is available from the course website. Chapter 5 of Weather Analysis by D. Djurić provides further details about how stability may be assessed utilizing skew-T/ln-p diagrams. Why Do We Care About Stability? Simply put, we care about stability because it exerts a strong control on vertical motion – namely, ascent – and thus cloud and precipitation formation on the synoptic-scale or otherwise. We care about stability because rarely is the atmosphere ever absolutely stable or absolutely unstable, and thus we need to understand under what conditions the atmosphere is stable or unstable. We care about stability because the purpose of instability is to restore stability; atmospheric processes such as latent heat release act to consume the energy provided in the presence of instability. Before we can assess stability, however, we must first introduce a few additional concepts that we will later find beneficial, particularly when evaluating stability using skew-T diagrams. Stability-Related Concepts Convection Condensation Level The convection condensation level, or CCL, is the height or isobaric level to which an air parcel, if sufficiently heated from below, will rise adiabatically until it becomes saturated. The attribute “if sufficiently heated from below” gives rise to the convection portion of the CCL. Sufficiently strong heating of the Earth’s surface results in dry convection, which generates localized thermals that act to vertically transport energy. -
The Static Atmsophere Equation of State, Hydrostatic Balance, and the Hypsometric Equation
The Static Atmsophere Equation of State, Hydrostatic Balance, and the Hypsometric Equation Equation of State The atmosphere at any point can be described by its temperature, pressure, and density. These variables are related to each other through the Equation of State for dry air: pα = Rd T v (1) Where α is the specific volume (1/ρ), p = pressure, Tv = virtual temperature (K), and R is the gas constant for dry air (R = 287 J kg-1 K-1). The virtual temperature is the temperature air would have if we account for the moisture content of it. Above the surface, where moisture is scarce, Tv and T are nearly equal. Near the surface you can use the following equation to calculate Tv: TTv = (1+ 0.6078q) where q = specific humidity (T must be in K, q must be dimensionless). More on virtual temperature a little later….. We can also write the equation of state as: p= ρ Rd T v (2) The equation of state is also known as the “Ideal Gas Law”. The atmosphere is treated as an “Ideal Gas”, meaning that the molecules are considered to be of negligible size so that they exert no intermolecular forces. Hydrostatic Equation Except in smaller-scale systems such as an intense squall line, the vertical pressure gradient in the atmosphere is balanced by the gravity force. We call this the hydrostatic balance. dp = −ρg (3) dz Integrating (3) from a height z to the top of the atmosphere yields: ∞ p() z= ∫ ρ gdz (4) z This says that the pressure at any point in the atmosphere is equal to the weight of the air above it. -
M.Sc. in Meteorology Physical Meteorology Part 2 Atmospheric
M.Sc. in Meteorology Physical Meteorology Part 2 Prof Peter Lynch Atmospheric Thermodynamics Mathematical Computation Laboratory Dept. of Maths. Physics, UCD, Belfield. 2 Atmospheric Thermodynamics Outline of Material Thermodynamics plays an important role in our quanti- • 1 The Gas Laws tative understanding of atmospheric phenomena, ranging from the smallest cloud microphysical processes to the gen- • 2 The Hydrostatic Equation eral circulation of the atmosphere. • 3 The First Law of Thermodynamics The purpose of this section of the course is to introduce • 4 Adiabatic Processes some fundamental ideas and relationships in thermodynam- • 5 Water Vapour in Air ics and to apply them to a number of simple, but important, atmospheric situations. • 6 Static Stability The course is based closely on the text of Wallace & Hobbs • 7 The Second Law of Thermodynamics 3 4 We resort therefore to a statistical approach, and consider The Kinetic Theory of Gases the average behaviour of the gas. This is the approach called The atmosphere is a gaseous envelope surrounding the Earth. the kinetic theory of gases. The laws governing the bulk The basic source of its motion is incoming solar radiation, behaviour are at the heart of thermodynamics. We will which drives the general circulation. not consider the kinetic theory explicitly, but will take the thermodynamic principles as our starting point. To begin to understand atmospheric dynamics, we must first understand the way in which a gas behaves, especially when heat is added are removed. Thus, we begin by studying thermodynamics and its application in simple atmospheric contexts. Fundamentally, a gas is an agglomeration of molecules. -
An R Package for Atmospheric Thermodynamics
An R package for atmospheric thermodynamics Jon S´aenza,b,∗, Santos J. Gonz´alez-Roj´ıa, Sheila Carreno-Madinabeitiac,a, Gabriel Ibarra-Berastegid,b aDept. Applied Physics II, Universidad del Pa´ısVasco-Euskal Herriko Unibertsitatea (UPV/EHU), Barrio Sarriena s/n, 48940-Leioa, Spain bBEGIK Joint Unit IEO-UPV/EHU, Plentziako Itsas Estazioa (PIE, UPV/EHU), Areatza Pasealekua, 48620 Plentzia, Spain cMeteorology Area, Energy and Environment Division, TECNALIA R&I, Basque Country, Spain. dDept. Nuc. Eng. and Fluid Mech., Universidad del Pa´ısVasco-Euskal Herriko Unibertsitatea (UPV/EHU), Alameda Urquijo s/n, 48013-Bilbao, Spain. Abstract This is a non-peer reviewed preprint submitted to EarthArxiv. It is the authors' version initially submitted to Computers and Geo- sciences corresponding to final paper "Analysis of atmospheric ther- modynamics using the R package aiRthermo", published in Com- puters and Goesciences after substantial changes during the review process with doi: http://doi.org/10.1016/j.cageo.2018.10.007, which the readers are encouraged to cite. In this paper the publicly available R package aiRthermo is presented. It allows the user to process information relative to atmospheric thermodynam- ics that range from calculating the density of dry or moist air and converting between moisture indices to processing a full sounding, obtaining quantities such as Convective Available Potential Energy, additional instability indices or adiabatic evolutions of particles. It also provides the possibility to present the information using customizable St¨uve diagrams. Many of the functions are writ- ten inside a C extension so that the computations are fast. The results of an application to five years of real soundings over the Iberian Peninsula are also shown as an example. -
Metar Abbreviations Metar/Taf List of Abbreviations and Acronyms
METAR ABBREVIATIONS http://www.alaska.faa.gov/fai/afss/metar%20taf/metcont.htm METAR/TAF LIST OF ABBREVIATIONS AND ACRONYMS $ maintenance check indicator - light intensity indicator that visual range data follows; separator between + heavy intensity / temperature and dew point data. ACFT ACC altocumulus castellanus aircraft mishap MSHP ACSL altocumulus standing lenticular cloud AO1 automated station without precipitation discriminator AO2 automated station with precipitation discriminator ALP airport location point APCH approach APRNT apparent APRX approximately ATCT airport traffic control tower AUTO fully automated report B began BC patches BKN broken BL blowing BR mist C center (with reference to runway designation) CA cloud-air lightning CB cumulonimbus cloud CBMAM cumulonimbus mammatus cloud CC cloud-cloud lightning CCSL cirrocumulus standing lenticular cloud cd candela CG cloud-ground lightning CHI cloud-height indicator CHINO sky condition at secondary location not available CIG ceiling CLR clear CONS continuous COR correction to a previously disseminated observation DOC Department of Commerce DOD Department of Defense DOT Department of Transportation DR low drifting DS duststorm DSIPTG dissipating DSNT distant DU widespread dust DVR dispatch visual range DZ drizzle E east, ended, estimated ceiling (SAO) FAA Federal Aviation Administration FC funnel cloud FEW few clouds FG fog FIBI filed but impracticable to transmit FIRST first observation after a break in coverage at manual station Federal Meteorological Handbook No.1, Surface -
Moist Potential Vorticity Generation in Extratropical Cyclones Zuohao
Moist Potential Vorticity Generation in Extratropical Cyclones bv Zuohao Cao A thesis submitted in conformity with the requirements for the Degree o f Doctor o f Philosophy in the Department o f Physics o f the University o f Toronto © Copyright by Zuohao Cao 1995 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission For my parents Mr. Jie Cao and Mrs. Sujuan Vang Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Moist Potential Vorticity Generation in Extratropical Cyclones Zuohao Cao, Ph.D. 1995 Department of Physics, University of Toronto Abstract The mechanism o f moist potential vorticity (M PV) generation in a three- dimensional moist adiabatic and frictionless flow is investigated. It is found that MPV generation is governed by baroclinic vectors and moisture gradients. Negative (positive) M PV can be generated in the region where baroclinic vectors have a component along (against) the direction o f moisture gradients. Numerical simulations of extratropical cyclones with different moisture distributions show that at the different stages of cvclogenesis, negative MPV usually appears in the warm sector near the north part o f the cold front, the bent-back warm front, the warm core and the cold front. The effects o f the Boussinesq approximation on the distribution of vorticity and M PV are examined. The Boussinesq approximation neglects several components o f the ^olenoidal term in the vorticity equation. As a result, it underestimates the thermally direct circulations in the cold front and the bent-back warm front by 25% to 30%. This effect is more pronounced when latent heat release is taken into account.