Tornado Events Associated With Supercells and Quasi- linear Convective Systems Sara Jupin EAS4480 4/28/2011 Sara Jupin EAS4480 4/28/2011.

Slides:

Advertisements

Similar presentations

Radar Climatology of Tornadoes in High Shear, Low CAPE Environments in the Mid-Atlantic and Southeast Jason Davis Matthew Parker North Carolina State University.

Advertisements

Chapter 14, part D Statistical Significance. IV. Model Assumptions The error term is a normally distributed random variable and The variance of  is constant.

Thunderstorms & Tornadoes Chapter 10 Meteorology 1010 Professor Bunds Utah Valley University.

APPENDIX B S OME B ASIC T ESTS IN S TATISTICS Organization of appendix in ISSO –Standard one-sample test P-values Confidence intervals –Basic two-sample.

1 Chapter 2 Simple Linear Regression Ray-Bing Chen Institute of Statistics National University of Kaohsiung.

Super Tuesday Tornado Outbreak Presented by: Catherine Smith, Colleen Smith, Trevor Smith, Andrew Smith.

April 2011 Tornado Outbreak. From noaa.gov 312 tornadoes from 4/ EDT to 4/ EDT About 340 killed in this time period The Tuscaloosa-Birmingham.

Forecasting Thunderstorms in Terminal Aerodrome Forecasts (TAFs) Some new insights Steven Thompson National Weather Service (NWS) La Crosse, WI.

Department of Civil Engineering University of Washington Quantitative Safety Analysis for Intersections on Washington State Two-lane Rural Highways Master’s.

A Study on Convective Modes Associated with Tornadoes in Central New York and Northeast Pennsylvania Timothy W. Humphrey 1 Michael Evans 2 1 Department.

Dr. Scott M. Rochette Department of the Earth Sciences The College at Brockport.

UNDERSTANDING RESEARCH RESULTS: STATISTICAL INFERENCE.

Statistics. Overview 1. Confidence interval for the mean 2. Comparing means of 2 sampled populations (or treatments): t-test 3. Determining the strength.

6.4 One and Two-Sample Inference for Variances. Example - Problem 26 – Page 435  D. Kim did some crude tensile strength testing on pieces of some nominally.

Lecture 24: Thurs. Dec. 4 Extra sum of squares F-tests (10.3) R-squared statistic (10.4.1) Residual plots (11.2) Influential observations (11.3,

Chapter Topics Types of Regression Models

11 Comparison of Two Means Tests involving two samples – comparing variances, F distribution TOH - x A = x B ? Step 1 - F-test  s A 2 = s B 2 ? Step.

Independent Samples t-Test What is the Purpose?What are the Assumptions?How Does it Work?What is Effect Size?

Getting Started with Hypothesis Testing The Single Sample.

Downbursts and dust storms. Review of last lecture 1.3 stages of supercell tornado formation. 2.2 types of non-supercell tornado formation. 3.Tornado.

Statistical Hypothesis Testing. Suppose you have a random variable X ( number of vehicle accidents in a year, stock market returns, time between el nino.

1 © Lecture note 3 Hypothesis Testing MAKE HYPOTHESIS ©

Means Tests Hypothesis Testing Assumptions Testing (Normality)

PowerPoint presentation to accompany Research Design Explained 6th edition ; ©2007 Mark Mitchell & Janina Jolley Chapter 7 Introduction to Descriptive.

Chapter 9 Hypothesis Testing and Estimation for Two Population Parameters.

An Evaluation of Mortality Rates Within the Path of Well-Warned Significant Tornadoes National Weather Service WFO Detroit, Michigan Joseph V Clark

Measures of Dispersion CUMULATIVE FREQUENCIES INTER-QUARTILE RANGE RANGE MEAN DEVIATION VARIANCE and STANDARD DEVIATION STATISTICS: DESCRIBING VARIABILITY.

Learning Objectives In this chapter you will learn about the t-test and its distribution t-test for related samples t-test for independent samples hypothesis.

EQT 373 Chapter 3 Simple Linear Regression. EQT 373 Learning Objectives In this chapter, you learn: How to use regression analysis to predict the value.

Chapter 12 Tests of a Single Mean When σ is Unknown.

Earthquakes: Increasing Over Time? By: Dan Arrington EAS 4480 Spring 2012 Image obtained from:

Thunderstorms and Tornadoes Last Lecture: We looked at severe weather events in the lower latitudes Principal weather event is the formation and movement.

A Study on the Environments Associated with Significant Tornadoes Occurring Within the Warm Sector versus Those Occurring Along Boundaries Jonathan Garner.

Biostatistics Class 6 Hypothesis Testing: One-Sample Inference 2/29/2000.

Statistical Hypotheses & Hypothesis Testing. Statistical Hypotheses There are two types of statistical hypotheses. Null Hypothesis The null hypothesis,

Improving the Forecasting of High Shear, Low CAPE Severe Weather Environments Keith Sherburn and Jason Davis Department of Marine, Earth, and Atmospheric.

Improving the Forecasting of High Shear, Low CAPE Severe Weather Environments Keith Sherburn and Jason Davis Department of Marine, Earth, and Atmospheric.

Kinematics of Super Tuesday Storms Todd Murphy and Kevin Knupp University of Alabama in Huntsville.

Histograms and Distributions Experiment: Do athletes have faster reflexes than non-athletes? Questions: - You go out and 1st collect the reaction time.

Simple Linear Regression ANOVA for regression (10.2)

Testing Differences in Population Variances

Section A Confidence Interval for the Difference of Two Proportions Objectives: 1.To find the mean and standard error of the sampling distribution.

Do Now 2/11/13 1. ________ is any form of condensed water vapor in the atmosphere falling back to Earth. 2. Name the global winds that blow from east to.

NWS Tornado Operations DIA Control Tower Discussion August 21, 2014 NWS Tornado Operations DIA Control Tower Discussion August 21, 2014 Mt Evans Tornado.

Inferential Statistics. The Logic of Inferential Statistics Makes inferences about a population from a sample Makes inferences about a population from.

 Descriptive Methods ◦ Observation ◦ Survey Research  Experimental Methods ◦ Independent Groups Designs ◦ Repeated Measures Designs ◦ Complex Designs.

Thunder storms: you can hear them a mile away!!!!!!! Zach Aldridge ScienceMr.Shepard.

Updated Radar-Based Techniques for Tornado Warning Guidance in the Northeastern United States Brian J. Frugis & Thomas A. Wasula NOAA/NWS Albany, New York.

Quasi-Linear Convective System Tornado Warnings

Non-parametric Tests e.g., Chi-Square. When to use various statistics n Parametric n Interval or ratio data n Name parametric tests we covered Tuesday.

Hypothesis Testing Errors. Hypothesis Testing Suppose we believe the average systolic blood pressure of healthy adults is normally distributed with mean.

BP-31 Updated Radar-Based Techniques for Tornado Warning Guidance in the Northeastern United States Brian J. Frugis and Thomas A. Wasula NOAA/National.

Tornado Warning Skill as a Function of Environment National Weather Service Sub-Regional Workshop Binghamton, New York September 23, 2015 Yvette Richardson.

2. Basic Characteristics and Forecast The 500-hPa pattern for this event featured a deep low centered over Idaho. A composite analysis of past tornado.

Inference for regression - More details about simple linear regression IPS chapter 10.2 © 2006 W.H. Freeman and Company.

Severe Weather What creates it, what it means, and how to stay safe.

Hypothesis Testing. Suppose we believe the average systolic blood pressure of healthy adults is normally distributed with mean μ = 120 and variance σ.

Jump to first page Inferring Sample Findings to the Population and Testing for Differences.

Introduction to Inference Tests of Significance. Wording of conclusion revisit If I believe the statistic is just too extreme and unusual (P-value < 

Lec. 19 – Hypothesis Testing: The Null and Types of Error.

Statistical Inference for the Mean Objectives: (Chapter 8&9, DeCoursey) -To understand the terms variance and standard error of a sample mean, Null Hypothesis,

Statistical Inferences for Variance Objectives: Learn to compare variance of a sample with variance of a population Learn to compare variance of a sample.

MARCH 18, 2014 DATA ANALYSIS. WHAT TO DO WITH DATA Take a look at your data Histogram Descriptive statistics Mean, mode, range, standard deviation/standard.

Parameter Estimation.

Data Analysis and Interpretation

CAE Tornado Cases Hunter Coleman Anthony Petrolito Michael Cammarata

Hiding under a freeway overpass will protect me from a tornado.

Northeast Regional Operational Workshop XVII 3 November 2016

Hypothesis tests in linear regression

Presentation transcript:

Tornado Events Associated With Supercells and Quasi- linear Convective Systems Sara Jupin EAS4480 4/28/2011 Sara Jupin EAS4480 4/28/2011

Introduction  Supercell: thunderstorm characterized by the presence of a mesocyclone.  Quasi-linear Convective System (QLCS): line of thunderstorms that form along or ahead of a cold front.  Both can produce tornadoes, however Supercell tornadoes are the most common, and often the most dangerous.  Issuing warnings for QLCS tornodoes is more problematic. Don’t have the strong precursor signatures seen with SC tornadoes.  Objective: Compare data between SC and QLCS data in order to increase future knowledge of QLCS tornadoes.  Supercell: thunderstorm characterized by the presence of a mesocyclone.  Quasi-linear Convective System (QLCS): line of thunderstorms that form along or ahead of a cold front.  Both can produce tornadoes, however Supercell tornadoes are the most common, and often the most dangerous.  Issuing warnings for QLCS tornodoes is more problematic. Don’t have the strong precursor signatures seen with SC tornadoes.  Objective: Compare data between SC and QLCS data in order to increase future knowledge of QLCS tornadoes.

Methodology  GA, AL, TN, MS tornado events from 11/15/2007-4/25/2010.  Probability of detection for QLCS vs. SC tornado events.  T-test and F-test to determine if effects of SC vs. QLCS tornadoes are statistically significant.  Magnitude, Deaths, Injuries, Property Damage(K), Path Length(Miles), Path Width(Yards), and Lead Time (Hours).  Determine any correlations between factors for each type of event.  GA, AL, TN, MS tornado events from 11/15/2007-4/25/2010.  Probability of detection for QLCS vs. SC tornado events.  T-test and F-test to determine if effects of SC vs. QLCS tornadoes are statistically significant.  Magnitude, Deaths, Injuries, Property Damage(K), Path Length(Miles), Path Width(Yards), and Lead Time (Hours).  Determine any correlations between factors for each type of event.

Background Info Supercells  65 events (71%)  59 warned, 6 unwarned  POD: 0.91  Deaths: 0.82  Injuries: 7.08  Damage Cost: 16,521  Path Length:  Path Width:  Lead Time: 3:05 Supercells  65 events (71%)  59 warned, 6 unwarned  POD: 0.91  Deaths: 0.82  Injuries: 7.08  Damage Cost: 16,521  Path Length:  Path Width:  Lead Time: 3:05 QLCS’s  26 events (29%)  21 warned, 5 unwarned  POD: 0.81  Deaths: 0.23  Injuries: 1.88  Damage Cost: 1,975  Path Length: 8.11  Path Width:  Lead Time: 3:11 QLCS’s  26 events (29%)  21 warned, 5 unwarned  POD: 0.81  Deaths: 0.23  Injuries: 1.88  Damage Cost: 1,975  Path Length: 8.11  Path Width:  Lead Time: 3:11 91 Total Events

Student’s T-test Results Null hypothesis: means of the two distributions are identical

F-Test Results Null hypothesis: variances of the two distributions are identical

Correlation Results

Conclusions  SC vs. QLCS results were not statistically significant at 5% convidence interval. Majority of the data did not have identical means or variances.  Not enough evidence in the correlations to suggest a difference between SC vs. QLCS causality.  Tornadoes from SC and QLCS have different results. Therefore, need to research how atmospheric conditions are different between the two. Very long and tedious task.  SC vs. QLCS results were not statistically significant at 5% convidence interval. Majority of the data did not have identical means or variances.  Not enough evidence in the correlations to suggest a difference between SC vs. QLCS causality.  Tornadoes from SC and QLCS have different results. Therefore, need to research how atmospheric conditions are different between the two. Very long and tedious task.

Sources  NWS verification website  MATLAB  NWS verification website  MATLAB