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Avoiding the Risks of Deadly Lightning Strikes
Avoiding the Risks of Deadly Lightning Strikes Lightning is one of the most underrated severe weather hazards, yet ranks as the second-leading weather killer in the United States. More deadly than hurricanes or tornadoes, lightning strikes in America each year kill an average of 73 people and injure 300 others, according to NOAA's National Weather Service. How Lightning Works Lightning is caused by the attraction between positive and negative charges in the atmosphere, resulting in the buildup and discharge of electrical energy. This rapid heating and cooling of the air produces the shock wave that results in thunder. During a storm, raindrops can acquire extra electrons, which are negatively charged. These surplus electrons seek out a positive charge from the ground. As they flow from the clouds, they knock other electrons free, creating a conductive path. This path follows a zigzag shape that jumps between randomly distributed clumps of charged particles in the air. When the two charges connect, current surges through that jagged path, creating the lightning bolt. The Warning Signs High winds, rainfall, and a darkening cloud cover are the warning signs for possible cloud-to- ground lightning strikes. While many lightning casualties happen at the beginning of an approaching storm, more than 50 percent of lightning deaths occur after the thunderstorm has passed. The lightning threat diminishes after the last sound of thunder, but may persist for more than 30 minutes. When thunderstorms are in the area, but not overhead, the lightning threat can exist when skies are clear. Safety Precautions While nothing offers absolute safety from lightning, some actions can greatly reduce your risks. -
Winter Precipitation Liquid–Ice Phase Transitions Revealed with Polarimetric Radar and 2DVD Observations in Central Oklahoma
MAY 2017 B U K O V CICETAL. 1345 Winter Precipitation Liquid–Ice Phase Transitions Revealed with Polarimetric Radar and 2DVD Observations in Central Oklahoma PETAR BUKOVCIC ´ NOAA/National Severe Storms Laboratory, and Cooperative Institute for Mesoscale Meteorological Studies, and School of Meteorology, and Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma DUSAN ZRNIC´ NOAA/National Severe Storms Laboratory, Norman, Oklahoma GUIFU ZHANG School of Meteorology, and Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma (Manuscript received 30 June 2016, in final form 8 November 2016) ABSTRACT Observations and analysis of an ice–liquid phase precipitation event, collected with an S-band polarimetric KOUN radar and a two-dimensional video disdrometer (2DVD) in central Oklahoma on 20 January 2007, are presented. Using the disdrometer measurements, precipitation is classified either as ice pellets or rain/freezing rain. The disdrometer observations showed fast-falling and slow-falling particles of similar size. The vast majority (.99%) were fast falling with observed velocities close to those of raindrops with similar sizes. In contrast to the smaller particles (,1 mm in diameter), bigger ice pellets (.1.5 mm) were relatively easy to distinguish because their shapes differ from the raindrops. The ice pellets were challenging to detect by looking at conventional polarimetric radar data because of the localized and patchy nature of the ice phase and their occurrence close to the ground. Previously published findings referred to cases in which ice pellet areas were centered on the radar location and showed a ringlike structure of enhanced differential reflectivity ZDR and reduced copolar correlation coefficient rhv and horizontal reflectivity ZH in PPI images. -
Downloaded 10/01/21 08:52 PM UTC 186 WEATHER and FORECASTING VOLUME 16
FEBRUARY 2001 NOTES AND CORRESPONDENCE 185 Further Investigation of a Physically Based, Nondimensional Parameter for Discriminating between Locations of Freezing Rain and Ice Pellets ROBERT M. RAUBER,LARRY S. OLTHOFF, AND MOHAN K. RAMAMURTHY Department of Atmospheric Sciences, University of Illinois at Urbana±Champaign, Urbana, Illinois KENNETH E. KUNKEL Midwestern Climate Center, Illinois State Water Survey, Champaign, Illinois 9 December 1999 and 16 August 2000 ABSTRACT The general applicability of an isonomogram developed by Czys and coauthors to diagnose the position of the geographic boundary between freezing precipitation (freezing rain or freezing drizzle) and ice pellets (sleet or snow grains) was tested using a 25-yr sounding database consisting of 1051 soundings, 581 where stations were reporting freezing drizzle, 391 reporting freezing rain, and 79 reporting ice pellets. Of the 1051 soundings, only 306 clearly had an environmental temperature and moisture pro®le corresponding to that assumed for the isonomogram. This pro®le consisted of a three-layer atmosphere with 1) a cold cloud layer aloft that is a source of ice particles, 2) a midlevel layer where the temperature exceeds 08C and ice particles melt, and 3) a surface layer where T , 08C. The remaining soundings did not conform to the pro®le either because 1) the freezing precipitation was associated with the warm rain process or 2) the ice pellets formed due to riming rather than melting and refreezing. For soundings conforming to the pro®le, the isonomogram showed little diagnostic skill. Freezing rain or freezing drizzle occurred about 50% of the time that ice pellets were expected. -
A Winter Forecasting Handbook Winter Storm Information That Is Useful to the Public
A Winter Forecasting Handbook Winter storm information that is useful to the public: 1) The time of onset of dangerous winter weather conditions 2) The time that dangerous winter weather conditions will abate 3) The type of winter weather to be expected: a) Snow b) Sleet c) Freezing rain d) Transitions between these three 7) The intensity of the precipitation 8) The total amount of precipitation that will accumulate 9) The temperatures during the storm (particularly if they are dangerously low) 7) The winds and wind chill temperature (particularly if winds cause blizzard conditions where visibility is reduced). 8) The uncertainty in the forecast. Some problems facing meteorologists: Winter precipitation occurs on the mesoscale The type and intensity of winter precipitation varies over short distances. Forecast products are not well tailored to winter Subtle features, such as variations in the wet bulb temperature, orography, urban heat islands, warm layers aloft, dry layers, small variations in cyclone track, surface temperature, and others all can influence the severity and character of a winter storm event. FORECASTING WINTER WEATHER Important factors: 1. Forcing a) Frontal forcing (at surface and aloft) b) Jetstream forcing c) Location where forcing will occur 2. Quantitative precipitation forecasts from models 3. Thermal structure where forcing and precipitation are expected 4. Moisture distribution in region where forcing and precipitation are expected. 5. Consideration of microphysical processes Forecasting winter precipitation in 0-48 hour time range: You must have a good understanding of the current state of the Atmosphere BEFORE you try to forecast a future state! 1. Examine current data to identify positions of cyclones and anticyclones and the location and types of fronts. -
Weather and Climate: Changing Human Exposures K
CHAPTER 2 Weather and climate: changing human exposures K. L. Ebi,1 L. O. Mearns,2 B. Nyenzi3 Introduction Research on the potential health effects of weather, climate variability and climate change requires understanding of the exposure of interest. Although often the terms weather and climate are used interchangeably, they actually represent different parts of the same spectrum. Weather is the complex and continuously changing condition of the atmosphere usually considered on a time-scale from minutes to weeks. The atmospheric variables that characterize weather include temperature, precipitation, humidity, pressure, and wind speed and direction. Climate is the average state of the atmosphere, and the associated characteristics of the underlying land or water, in a particular region over a par- ticular time-scale, usually considered over multiple years. Climate variability is the variation around the average climate, including seasonal variations as well as large-scale variations in atmospheric and ocean circulation such as the El Niño/Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO). Climate change operates over decades or longer time-scales. Research on the health impacts of climate variability and change aims to increase understanding of the potential risks and to identify effective adaptation options. Understanding the potential health consequences of climate change requires the development of empirical knowledge in three areas (1): 1. historical analogue studies to estimate, for specified populations, the risks of climate-sensitive diseases (including understanding the mechanism of effect) and to forecast the potential health effects of comparable exposures either in different geographical regions or in the future; 2. studies seeking early evidence of changes, in either health risk indicators or health status, occurring in response to actual climate change; 3. -
Improving Lightning and Precipitation Prediction of Severe Convection Using of the Lightning Initiation Locations
PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Improving Lightning and Precipitation Prediction of Severe 10.1002/2017JD027340 Convection Using Lightning Data Assimilation Key Points: With NCAR WRF-RTFDDA • A lightning data assimilation method was developed Haoliang Wang1,2, Yubao Liu2, William Y. Y. Cheng2, Tianliang Zhao1, Mei Xu2, Yuewei Liu2, Si Shen2, • Demonstrate a method to retrieve the 3 3 graupel fields of convective clouds Kristin M. Calhoun , and Alexandre O. Fierro using total lightning data 1 • The lightning data assimilation Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information method improves the lightning and Science and Technology, Nanjing, China, 2National Center for Atmospheric Research, Boulder, CO, USA, 3Cooperative convective precipitation short-term Institute for Mesoscale Meteorological Studies (CIMMS), NOAA/National Severe Storms Laboratory, University of Oklahoma forecasts (OU), Norman, OK, USA Abstract In this study, a lightning data assimilation (LDA) scheme was developed and implemented in the Correspondence to: Y. Liu, National Center for Atmospheric Research Weather Research and Forecasting-Real-Time Four-Dimensional [email protected] Data Assimilation system. In this LDA method, graupel mixing ratio (qg) is retrieved from observed total lightning. To retrieve qg on model grid boxes, column-integrated graupel mass is first calculated using an Citation: observation-based linear formula between graupel mass and total lightning rate. Then the graupel mass is Wang, H., Liu, Y., Cheng, W. Y. Y., Zhao, distributed vertically according to the empirical qg vertical profiles constructed from model simulations. … T., Xu, M., Liu, Y., Fierro, A. O. (2017). Finally, a horizontal spread method is utilized to consider the existence of graupel in the adjacent regions Improving lightning and precipitation prediction of severe convection using of the lightning initiation locations. -
From the Line in the Sand: Accounts of USAF Company Grade Officers In
~~may-='11 From The Line In The Sand Accounts of USAF Company Grade Officers Support of 1 " 1 " edited by gi Squadron 1 fficer School Air University Press 4/ Alabama 6" March 1994 Library of Congress Cataloging-in-Publication Data From the line in the sand : accounts of USAF company grade officers in support of Desert Shield/Desert Storm / edited by Michael P. Vriesenga. p. cm. Includes index. 1. Persian Gulf War, 1991-Aerial operations, American . 2. Persian Gulf War, 1991- Personai narratives . 3. United States . Air Force-History-Persian Gulf War, 1991 . I. Vriesenga, Michael P., 1957- DS79 .724.U6F735 1994 94-1322 959.7044'248-dc20 CIP ISBN 1-58566-012-4 First Printing March 1994 Second Printing September 1999 Third Printing March 2001 Disclaimer This publication was produced in the Department of Defense school environment in the interest of academic freedom and the advancement of national defense-related concepts . The views expressed in this publication are those of the authors and do not reflect the official policy or position of the Department of Defense or the United States government. This publication hasbeen reviewed by security andpolicy review authorities and is clearedforpublic release. For Sale by the Superintendent of Documents US Government Printing Office Washington, D.C . 20402 ii 9&1 gook L ar-dicat£a to com#an9 9zacL orflcF-T 1, #ait, /2ZE4Ent, and, E9.#ECLaL6, TatUlLE. -ZEa¢ra anJ9~ 0 .( THIS PAGE INTENTIONALLY LEFT BLANK Contents Essay Page DISCLAIMER .... ... ... .... .... .. ii FOREWORD ...... ..... .. .... .. xi ABOUT THE EDITOR . ..... .. .... xiii ACKNOWLEDGMENTS . ..... .. .... xv INTRODUCTION .... ..... .. .. ... xvii SUPPORT OFFICERS 1 Madzuma, Michael D., and Buoniconti, Michael A. -
Soaring Weather
Chapter 16 SOARING WEATHER While horse racing may be the "Sport of Kings," of the craft depends on the weather and the skill soaring may be considered the "King of Sports." of the pilot. Forward thrust comes from gliding Soaring bears the relationship to flying that sailing downward relative to the air the same as thrust bears to power boating. Soaring has made notable is developed in a power-off glide by a conven contributions to meteorology. For example, soar tional aircraft. Therefore, to gain or maintain ing pilots have probed thunderstorms and moun altitude, the soaring pilot must rely on upward tain waves with findings that have made flying motion of the air. safer for all pilots. However, soaring is primarily To a sailplane pilot, "lift" means the rate of recreational. climb he can achieve in an up-current, while "sink" A sailplane must have auxiliary power to be denotes his rate of descent in a downdraft or in come airborne such as a winch, a ground tow, or neutral air. "Zero sink" means that upward cur a tow by a powered aircraft. Once the sailcraft is rents are just strong enough to enable him to hold airborne and the tow cable released, performance altitude but not to climb. Sailplanes are highly 171 r efficient machines; a sink rate of a mere 2 feet per second. There is no point in trying to soar until second provides an airspeed of about 40 knots, and weather conditions favor vertical speeds greater a sink rate of 6 feet per second gives an airspeed than the minimum sink rate of the aircraft. -
The Observation of the Lightning Induced Variations in Atmospheric Ions
XV International Conference on Atmospheric Electricity, 15-20 June 2014, Norman, Oklahoma, U.S.A. The Observation of the Lightning Induced Variations in Atmospheric Ions Xuemeng Chen1,*, Hanna E. Manninen1,2, Pasi Aalto1, Petri Keronen1, Antti Mäkelä3, Jussi Paatero3, Tuukka Petäjä1 and Markku Kulmala1 1. Department of Physics, University of Helsinki, Helsinki, Finland 2. Institute of Physics, University of Tartu, Estonia 3. Finnish Meteorological Institute, Helsinki, Finland ABSTRACT: Variations in atmospheric ion concentration were studied in a boreal forest in Finland, with emphasis on the effect of lightning. In general, changes in ion concentrations have diurnal and seasonal patterns. Distinct features were found in ions of different size ranges, namely small ions (0.8 – 1.7 nm) and intermediate ions (1.7 – 7 nm). Preliminary results on two case studies of lightning effect are present, one with rain effect and the other not. Bursts in the concentrations of small ions and intermediate ions were observed in both cases. However, different trends in trace gases were observed for the two cases. Further investigation is needed to reveal the nature of lightning ions and the mechanism in their formation. The work is under progress. INTRODUCTION Atmospheric ions, or air ions, refer to electric charge carriers present in the atmosphere. Distinct features exist in their chemical composition, mass, size as well as number of carried charges. According to Tammet [1998], atmospheric ions can be classified into small or cluster ions, intermediate ions, and large ions based on their mobility (Z) in air, being Z > 0.5 cm2V-1s-1, 0.5 cm2V-1s-1 ≤ Z ≥ 0.03 cm2V-1s-1 and Z< 0.03 cm2V-1s-1, respectively. -
911 Communicator Questions to Ask Of
911 Communicator Questions to ask of Severe Weather Spotters 1. Name, home address, and telephone number. 2. Is caller a trained severe weather spotter. 3. Time of call. 4. Time of severe weather event (may be different than call time). 5. Location of severe weather event, which may be different from location where spotter called from. (If spotter doesn’t say 1.2 miles southeast of Anytown, then request names of streets at nearest intersection). 6. Type of Weather Event – (most common to least common order) a. If it’s a wind report, ask if the reported speed is measured or estimated. b. If it’s a wind damage report, ask caller to estimate how many trees are damaged, uprooted, etc., or extent and severity of structural damage. c. If it’s a hail event, ask if the reported size is measured or estimated. (penny, nickel, quarter, golf ball, soft ball, etc.) d. If it’s a flood report, ask caller to estimate depth of water on roads or on lawns, ask if the water is stationary or moving, and extent or severity of damage. e. If it’s a “rotating wall-cloud” report, i. Persistent rotation (usually on backside of storm) = true rotating wall-cloud. ii. No rotation = scary-looking cloud (scud), or a non-rotating wall-cloud. f. If it’s a funnel-cloud report, ask caller if the funnel-shaped cloud is actually rotating. If the caller is too far away from the funnel-cloud they may not be able to see rotation. i. No rotation = just a scary-looking cloud (scud). -
The Error Is the Feature: How to Forecast Lightning Using a Model Prediction Error [Applied Data Science Track, Category Evidential]
The Error is the Feature: How to Forecast Lightning using a Model Prediction Error [Applied Data Science Track, Category Evidential] Christian Schön Jens Dittrich Richard Müller Saarland Informatics Campus Saarland Informatics Campus German Meteorological Service Big Data Analytics Group Big Data Analytics Group Offenbach, Germany ABSTRACT ACM Reference Format: Despite the progress within the last decades, weather forecasting Christian Schön, Jens Dittrich, and Richard Müller. 2019. The Error is the is still a challenging and computationally expensive task. Current Feature: How to Forecast Lightning using a Model Prediction Error: [Ap- plied Data Science Track, Category Evidential]. In Proceedings of 25th ACM satellite-based approaches to predict thunderstorms are usually SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19). based on the analysis of the observed brightness temperatures in ACM, New York, NY, USA, 10 pages. different spectral channels and emit a warning if a critical threshold is reached. Recent progress in data science however demonstrates 1 INTRODUCTION that machine learning can be successfully applied to many research fields in science, especially in areas dealing with large datasets. Weather forecasting is a very complex and challenging task requir- We therefore present a new approach to the problem of predicting ing extremely complex models running on large supercomputers. thunderstorms based on machine learning. The core idea of our Besides delivering forecasts for variables such as the temperature, work is to use the error of two-dimensional optical flow algorithms one key task for meteorological services is the detection and pre- applied to images of meteorological satellites as a feature for ma- diction of severe weather conditions. -
Wildland Fire Incident Management Field Guide
A publication of the National Wildfire Coordinating Group Wildland Fire Incident Management Field Guide PMS 210 April 2013 Wildland Fire Incident Management Field Guide April 2013 PMS 210 Sponsored for NWCG publication by the NWCG Operations and Workforce Development Committee. Comments regarding the content of this product should be directed to the Operations and Workforce Development Committee, contact and other information about this committee is located on the NWCG Web site at http://www.nwcg.gov. Questions and comments may also be emailed to [email protected]. This product is available electronically from the NWCG Web site at http://www.nwcg.gov. Previous editions: this product replaces PMS 410-1, Fireline Handbook, NWCG Handbook 3, March 2004. The National Wildfire Coordinating Group (NWCG) has approved the contents of this product for the guidance of its member agencies and is not responsible for the interpretation or use of this information by anyone else. NWCG’s intent is to specifically identify all copyrighted content used in NWCG products. All other NWCG information is in the public domain. Use of public domain information, including copying, is permitted. Use of NWCG information within another document is permitted, if NWCG information is accurately credited to the NWCG. The NWCG logo may not be used except on NWCG-authorized information. “National Wildfire Coordinating Group,” “NWCG,” and the NWCG logo are trademarks of the National Wildfire Coordinating Group. The use of trade, firm, or corporation names or trademarks in this product is for the information and convenience of the reader and does not constitute an endorsement by the National Wildfire Coordinating Group or its member agencies of any product or service to the exclusion of others that may be suitable.