A Guide for Weather Emergency Communications W5YM University
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NEWSLETTER National Weather Association No
NEWSLETTER National Weather Association No. 10 – 12 December 2010 Tracking the Storms the PLOWS Way Adverse road conditions as- sociated with winter storms are re- sponsible for a large portion of the nearly 7000 deaths, 600,000 inju- Inside This Edition ries and 1 4. million accidents that occur in the United States each Internet Based GIS year . Improving cool season quan- Remote Sensing and Storm titative precipitation forecasting Chasing . .2 depends largely on developing a greater understanding of the me- President’s Message . .3 soscale structure and dynamics of cyclonic weather systems . The Pro- This C-130 Hercules Aircraft flies PLOWS missions. New Learning Opportunities filing of Winter Storms (PLOWS) project is aimed at doing just that. During the 2008- from the EJOM . 4. 2009 and 2009-2010 winter seasons, the University of Illinois (UI), the University of Alabama at Huntsville (UAH) and the University of Missouri (UM) placed teams of Scholarship Fundraising . 4. researchers in the field to study winter cyclones across the Midwestern United States NWA on Twitter and Facebook . .5 as part of the PLOWS project . PLOWS was designed to be a comprehensive field campaign, with complementary National Academy of Sciences to numerical modeling studies, that will address outstanding scientific questions targeted Study NWS . .7 at improving our understanding of precipitation substructures in the northwest and warm frontal quadrants of continental extratropical cyclones. The field strategy Professional Development was designed to answer questions about the mesoscale structure of winter storms Opportunities . .7 including: • What are the predominant spatial patterns of organized precipitation NWA Mission and Vision substructures, such as bands and generating cells, in these quadrants and how Statements . -
Climate Data Sources in Connecticut Patricia A
University of Connecticut OpenCommons@UConn College of Agriculture, Health and Natural Storrs Agricultural Experiment Station Resources 1-1982 Climate Data Sources in Connecticut Patricia A. Palley University of Connecticut - Storrs David R. Miller University of Connecticut - Storrs Follow this and additional works at: https://opencommons.uconn.edu/saes Part of the Climate Commons, Environmental Monitoring Commons, and the Meteorology Commons Recommended Citation Palley, Patricia A. and Miller, David R., "Climate Data Sources in Connecticut" (1982). Storrs Agricultural Experiment Station. 80. https://opencommons.uconn.edu/saes/80 Storrs Agricultural Experiment Station Bulletin 461 Climate Data Sources in Connecticut By Patricia A Palley, Assistant State Climatologist and David R. Miller, Associate Professor of Natural Resources JAN 1982 STORRS AGRICULTURAL EXPERI MENT STATION COLLEGE OF AGRICULTURE AND NATURAL RESOURCES THE UNIVERSITY OF CONNECTICUT, STORRS. CT 06268 TABLE OF CONTENTS Int roduction . 1 Types of Weather Stations 2 Parameters Measur ed 3 Summary of Climate Observations in Connecticu t 5 How to Use the Maps and Site Reports • • • • • 7 Table I Record Lengths, by parameter, of all weather stat ions i n Conn., state summary 8 Table II Record Lengths , by parame ter, of all weather stations in Conn . , by county . 9 Table III Record Lengths, by paramet er, of Nationa l Wea ther Service operat ed and coope rative stations in Conn., by county . • . 10 Table IV Re cord Lengths , by par ameter , of pr ivate data collect ors i n Conn ., by county . • . 11 Figure I Distribution of stations t hat measure rainfall . 12 Figur e II Distribution of stations t hat meas ure s nowf all . -
Handbook for the Meteorological Observation
Handbook for the Meteorological Observation Koninklijk Nederlands Meteorologisch Instituut KNMI September 2000 Contents Chapter 1. Measuring stations – General 1 Introduction 2 Variables 3 Type of observing station 4 Conditions relating to the layout of the measurement site of a weather station 5 Spatial distribution of the measuring stations and the representativeness of the observations 6 Procedures relating to the inspection, maintenance and management of a weather station 6.1 Inspection 6.2 Technical maintenance 6.3 Supervision 1. MEASURING STATIONS - GENERAL 1.1 Introduction The mission statement of the KNMI1 (from their brochure “KNMI, more than just weather” of August 1999) reads: “The KNMI is an agency with approximately five hundred employees that is part of the Ministry of Transport, Public Works and Water Management. From its position as the national knowledge centre for weather, climate and seismology, the institute is targeted entirely at fulfilling public tasks: weather forecasts and warnings monitoring the climate acquisition and supply of meteorological data and infrastructure model development aviation meteorology scientific research public information services” The tasks mentioned above are split across a number of sectors within the KNMI. One of the sectors is WM (Waarnemingen en Modellen = Observations and Models). This particular sector’s mission has been formulated as follows: “The Observations and Models sector (WM) is responsible for making the basic meteorological data available and for provision of climatological information to both internal and external users. The basic meteorological data, both current and historical, contains: - observations made by measurement, visual observation, using remote sensing or acquired from external sources - output from atmospheric and oceanographic models, acquired by processing the sector’s own models of acquired from institutes abroad. -
Lesson 6 Weather: Collecting Data GRADE 3-5 BACKGROUND Meteorologists Collect Weather Data Daily to Make Forecasts
Lesson 6 Weather: Collecting Data GRADE 3-5 BACKGROUND Meteorologists collect weather data daily to make forecasts. With the aid of high altitude weather balloons, weather equipment and gauges, satellites, and computers, accurate daily forecasts can be made. Collecting weather data in just one location and making a forecast requires a great deal of skill. Since air travels from one location to another, it is helpful to know what the approaching weather will be. In this investigation, the students will collect data for two weeks. At this time they will start seeing patterns in each of the areas. They can predict what the weather will be like the next day and for the next few days. They will also write if their predictions were correct from the previous day. Collecting the data for this lesson can be done instead of collecting the data separately in lesson 1-4. BASIC LESSON Objective(s) Students will be able to… Collect data for two weeks and use the information to detect patterns and predict weather around their location. State Science Content Standard(s) Standard 4. Students through the inquiry process, demonstrate knowledge of the composition, structures, processes and interactions of Earth's systems and other objects in space. A. 4.4 Observe and describe the water cycle and the local weather and demonstrate how weather conditions are measured. A. Record temperature B. Display data on a graph C. Interpret trends and patterns of data D. Identify and explain the use of a barometer, weather vane, and anemometer E. Collect, record and chart data from each weather instrument F. -
Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms
atmosphere Article Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms Matthew Van Den Broeke Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, Lincoln, NE 68588, USA; [email protected] Abstract: Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature. Keywords: supercell; nowcasting; tornadogenesis failure; polarimetric radar Citation: Van Den Broeke, M. 1. Introduction Polarimetric Radar Characteristics of Supercell thunderstorms produce most strong tornadoes in North America, moti- Tornadogenesis Failure in Supercell vating study of their radar signatures for the benefit of the operational and research Thunderstorms. Atmosphere 2021, 12, communities. Since the polarimetric upgrade to the national radar network of the United 581. https://doi.org/ States (2011–2013), polarimetric radar signatures of these storms have become well-known, 10.3390/atmos12050581 e.g., [1–5], and many others. -
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. -
Article Usage of Color Scales on Radar Maps
Bryant, B., M. Holiner, R. Kroot, K. Sherman-Morris, W. B. Smylie, L. Stryjewski, M. Thomas, and C. I. Williams, 2014: Usage of color scales on radar maps. J. Operational Meteor., 2 (14), 169179, doi: http://dx.doi.org/10.15191/nwajom.2014.0214. Journal of Operational Meteorology Article Usage of Color Scales on Radar Maps BRITTNEY BRYANT, MATTHEW HOLINER, RACHAEL KROOT, KATHLEEN SHERMAN-MORRIS, WILLIAM B. SMYLIE, LISA STRYJEWSKI, MEAGHAN THOMAS, and CHRISTOPHER I. WILLIAMS Mississippi State University, Mississippi State, Mississippi (Manuscript received 3 October 2013; review completed 14 April 2014) ABSTRACT The visualization of rainfall rates and amounts using colored weather maps has become very common and is crucial for communicating weather information to the public. Little research has been done to investigate which color scales lead to the best understanding of a weather map; however, research has been performed on the general use of color and the theory behind it. Applying color theory specifically to weather maps, we designed this project to see if there was a statistically significant difference in an individual’s interpretation of weather data presented in two different color scales. We used a radar map and a storm-total precipitation map, each presented in both a rainbow scale and a monochromatic green scale, for a total of four images. A survey based on these images was distributed online to students at Mississippi State University. After analyzing the results, we found that people who received the radar image with the green scale were more likely to answer questions associated with that image correctly. However, there was no significant difference in accuracy between the two color scales on the storm-total precipitation map. -
Rigid Wing Sailboats: a State of the Art Survey Manuel F
Ocean Engineering 187 (2019) 106150 Contents lists available at ScienceDirect Ocean Engineering journal homepage: www.elsevier.com/locate/oceaneng Review Rigid wing sailboats: A state of the art survey Manuel F. Silva a,b,<, Anna Friebe c, Benedita Malheiro a,b, Pedro Guedes a, Paulo Ferreira a, Matias Waller c a Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, Portugal b INESC TEC, Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal c Åland University of Applied Sciences, Neptunigatan 17, AX-22111 Mariehamn, Åland, Finland ARTICLEINFO ABSTRACT Keywords: The design, development and deployment of autonomous sustainable ocean platforms for exploration and Autonomous sailboat monitoring can provide researchers and decision makers with valuable data, trends and insights into the Wingsail largest ecosystem on Earth. Although these outcomes can be used to prevent, identify and minimise problems, Robotics as well as to drive multiple market sectors, the design and development of such platforms remains an open challenge. In particular, energy efficiency, control and robustness are major concerns with implications for autonomy and sustainability. Rigid wingsails allow autonomous boats to navigate with increased autonomy due to lower power consumption and increased robustness as a result of mechanically simpler control compared to traditional sails. These platforms are currently the subject of deep interest, but several important research problems remain open. In order to foster dissemination and identify future trends, this paper presents a survey of the latest developments in the field of rigid wing sailboats, describing the main academic and commercial solutions both in terms of hardware and software. -
A Preliminary Investigation of Derecho-Producing Mcss In
P 3.1 TROPICAL CYCLONE TORNADO RECORDS FOR THE MODERNIZED NWS ERA Roger Edwards1 Storm Prediction Center, Norman, OK 1. INTRODUCTION and BACKGROUND since 1954 was attributable to the weakest (F0) bin of damage rating (Fig. 1). This is the very class of Tornadoes from tropical cyclones (hereafter TCs) tornado that is most common in TC records, and most pose a specialized forecast challenge at time scales difficult to detect in the damage above that from the ranging from days for outlooks to minutes for concurrent or subsequent passage of similarly warnings (Spratt et al. 1997, Edwards 1998, destructive, ambient TC winds. As such, it is possible Schneider and Sharp 2007, Edwards 2008). The (but not quantifiable) that many TC tornadoes have fundamental conceptual and physical tenets of gone unrecorded even in the modern NWS era, due midlatitude supercell prediction, in an ingredients- to their generally ephemeral nature, logistical based framework (e.g., Doswell 1987, Johns and difficulties of visual confirmation, presence of swaths Doswell 1992), fully apply to TC supercells; however, of sparsely populated near-coastal areas (i.e., systematic differences in the relative magnitudes of marshes, swamps and dense forests), and the moisture, instability, lift and shear in TCs (e.g., presence of damage inducers of potentially equal or McCaul 1991) contribute strongly to that challenge. greater impact within the TC envelope. Further, there is a growing realization that some TC tornadoes are not necessarily supercellular in origin (Edwards et al. 2010, this volume). Several major TC tornado climatologies have been published since the 1960s (e.g., Pearson and Sadowski 1965, Hill et al. -
Reducing the Risk Runway Excursions
MAIN MENU Report . Reducing the Risk of Runway Excursions: Report of the Runway Safety Initiative . Appendixes Reducing the Risk of RUNWAY EXCURSIONS REPORT OF THE RUNWAY SAFETY INITIATIVE This information is not intended to supersede operators’ or manufacturers’ policies, practices or requirements, and is not intended to supersede government regulations. Reducing the Risk of RUNWAY EXCURSIONS REPORT OF THE RUNWAY SAFETY INITIATIVE Contents 1. Introduction 4 1.1 Definitions 4 2. Background 5 3. Data 6 Reducing the Risk of 4.0 Common Risk Factors inRunway Excursion Events 9 RUNWAY EXCURSIONS 4.1 Flight Operations 9 4.1.1 Takeoff Excursion Risk Factors 9 REPORT OF THE RUNWAY SAFETY INITIATIVE 4.1.2 Landing Excursion Risk Factors 9 4.2 Air Traffic Management 9 TABLE OF CONTENTS 4.3 Airport 9 1. Introduction .......................................................................................................................................................................... 4 1.1 Definitions ................................................................................................................................................................. 4 4.4 Aircraft Manufacturers 9 2. Background .......................................................................................................................................................................... 5 4.5 Regulators 9 3. Data ................................................................................................................................................................................... -
Three-Body Scatter Spike
RADAR OBSERVATIONS OF A RARE “TRIPLE” THREE-BODY SCATTER SPIKE Phillip G. Kurimski NOAA/National Weather Service Detroit/Pontiac, Michigan Weather Forecast Office Abstract afternoon and evening across northeast Wisconsin. The hail storms were responsible forOn 1over July 10.3 2006, million several dollars supercell of damage. thunderstorms The most produced intense storm significant produced hail during hail up the to late 4 in. in diameter that damaged over 100 cars and numerous homes in Oconto County, Wisconsin. This storm exhibited a rare, triple three-body scatter spike (TBSS) and a very long, impressive 51 mile TBSS. This paper will diagnose the structure and character of the paperhail cores will responsibleconnect the forunusually the multiple large TBSSscattering using angle several associated different with tools, the illustrating 51 mile longthat TBSSTBSS areto the 3-D increased features thatscattered are not energy confined responsible to a single for elevation the long TBSS.slice. In addition, Corresponding Author: Phillip G. Kurimski NOAA/ National Weather Service, 9200 White Lake Road, White Lake, Michigan 48386-1126 E-mail: [email protected] Kurimski 1. Introduction Since the early days of weather radar, radar operators three distinct TBSS signatures in a single volume scan andsignatures elevation has angle been is observed a phenomenon (Stan-Sion that haset al. yet 2007), to be result from large hail in a thunderstorm (Wilson and Reum documented and is the main motivation for this paper. The 1988).have noticed When athe “flare radar echo” beam down encounters the radial large believed hailstones to with a coating of liquid water, power from the radar is throughout this paper. -
Forensic Analysis
FORENSIC ANALYSIS CLAIM Location: 123 Sample Road, Brooklyn Center, MN Event Date(s): June 29, 2015 Prepared for: Sample PLLC Scope: Determine the possibility of severe, damaging hail impacting the Property on June 29, 2015. All data, observations and conclusions included in this report are based on the following data and materials: ● Watches, warnings and storm reports issued by the National Weather Service (NWS) in the Twin Cities accessed via Iowa Environmental Mesonet (IEM) ● Historical KMPX Doppler Radar located in Chanhassen, MN accessed via GR2Analyst ● National Weather Service (NWS) hourly reporting stations accessed via the Iowa Environmental Mesonet (IEM) ● Archived social media reports via Twitter ● Eye witness reports and photographs (Sample PLLC) ● Sample Engineering Report (Sample PLLC) 6569 City West Parkway, Eden Prairie, MN 55344 (952) 401 1005 www.praedictix.com 1 | Page FORENSIC ANALYSIS OVERVIEW Sample PLLC has requested a professional meteorological analysis of strong thunderstorms and subsequent hail damage that occurred at their Property located at or around 123 Sample Road, Brooklyn Center, Minnesota. We refer to this location as “the Property” in this report. We have been asked to review the weather conditions on June 29, 2015. Based on our analysis, the Property was subject to a severe thunderstorm on the evening of June 29, 2015. A series of strong storms impacted the north Minneapolis metro late that afternoon/evening with multiple Severe Thunderstorm Warnings in the region. Large, damaging hail was confirmed with these thunderstorms as a sequence of storm damage reports recorded by trained weather spotters (Figure 1). The Property was grazed by a core of large hail produced by a severe thunderstorm between 7:14 PM and 7:19 PM on June 29, 2015.