How to Use and Interpret Doppler Weather Radar
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Chapter-5 Doppler Effect
Chapter-5 Doppler Effect Stationary source Stationary observer Moving source Stationary observer Stationary source Moving observer Moving source Moving observer http://www.astro.ubc.ca/~scharein/a311/Sim/doppler/Doppler.html Doppler Effect The Doppler effect is the apparent change in the frequency of a wave motion when there is relative motion between the source of the waves and the observer. The apparent change in frequency f experienced as a result of the Doppler effect is known as the Doppler shift. The value of the Doppler shift increases as the relative velocity v between the source and the observer increases. The Doppler effect applies to all forms of waves. Doppler Effect (Moving Source) http://www.absorblearning.com/advancedphysics/demo/units/040103.html Suppose the source moves at a steady velocity vs towards a stationary observer. The source emits sound wave with frequency f. From the diagram, we can see that the distance between crests is shortened such that ' vs Since = c/f and = 1/f, We get c c v s f ' f f c vs f ' ( ) f c vs Doppler Effect (Moving Observer) Consider an observer moving with velocity vo toward a stationary source S. The source emits a sound wave with frequency f and wavelength = c/f. The velocity of the sound wave relative to the observer is c + vo. c Doppler Shift Consider a source moving towards an observer, the Doppler shift f is c f f ' f ( ) f f c vs f v s f c v s f v If v <<c, then we get s s f c The above equation also applies to a receding source, with vs taking as negative. -
A Real-Time System to Estimate Weather Conditions at High Resolution
12.1 A Real-Time System to Estimate Weather Conditions at High Resolution Peter P. Neilley1 Weather Services International, Inc. Andover, MA 01810 And Bruce L. Rose The Weather Channel Atlanta, GA the earth’s surface (the so-called current 1. Introduction1 conditions). b) We do not necessarily produce weather The purpose of this paper is to describe an observations on a regular grid, but at an operational system used to estimate current irregular set of arbitrary locations or points weather conditions at arbitrary places in real- that are relevant to the consumers of the time. The system, known as High Resolution information. Assimilation of Data (or HiRAD), is designed to generate synthetic weather observations in a c) In addition to producing quantitative manner equivalent in scope, timeliness and observational elements (e.g. temperature, quality to a arbitrarily dense physical observing pressure and wind speed) our system network. Our approach is, first, to collect produces common, descriptive terminology information from a variety of relevant sources of the sensible weather such as including gridded analyses, traditional surface “Thundershowers”, “Patchy Fog”, and weather reports, radar, satellite and lightning “Snow Flurries”. observations. Then we continuously synthesize these data into weather condition estimates at d) We do not strive to produce a state of the prescribed locations. An operational system atmosphere optimized for fidelity with based on this approach has been built and is Numerical Weather Prediction (NWP) commercially deployed in the United States. models. Instead, the system is optimized to produce the most accurate estimate of the In most regards, our approach is analogous to observed state at the surface that can be modern data assimilation techniques. -
Fire W Eather
Fire Weather Fire Weather Fire weather depends on a combination of wildland fuels and surface weather conditions. Dead and live fuels are assessed weekly from a satellite that determines the greenness of the landscape. Surface weather conditions are monitored every 5-minutes from the Oklahoma Mesonet. This fire weather help page highlights the surface weather ingredients to monitor before wildfires and also includes several products to monitor once wildfires are underway. Fire Weather Ingredients: WRAP While the presence of wildland fuels is one necessary component for wildfires, weather conditions ultimately dictate whether or not a day is primed for wildfires to occur. There are four key fire weather ingredients and they include: high Winds, low Relative humidity, high Air temperature, and no/minimal recent Precipitation (WRAP). High Winds are the second most critical weather ingredient for wildfires. In general, winds of 20 mph or greater 20+ mph winds increase spot fires and make for most of the containment considerably more difficult. state Low Relative humidity is the most 30-40+ critical weather ingredient for wildfires mph winds and is most common in the afternoon when the air temperature is at its warmest. When relative humidity is at or below 20% extreme fire behavior can result and spot fires become freQuent. Watch out for areas of 20% or below relative humidity and 20 mph or higher winds à 20/20 rule! Extremely low relative humidity Warm Air temperatures are another values key weather ingredient for wildfires as warming can lower the relative humidity, reduce moisture for smaller dead fuels, and bring fuels closer to their ignition point. -
The Twister Sisters, Peggy Willenberg and Melanie Metz Topic
NEWSLETTER TWIN CITIES CHAPTER AMERICAN METEOROLOGICAL SOCIETY September, 2007 Vol. 29 No. 1 The meeting of the Twin Cities Chapter of the AMS will be at 7 PM September 18th, 2007 Twin Cities WFO, Chanhassen, MN Specific directions to the meeting can be found on page 5. AMS chapter members, interested acquaintances and potential members are invited to attend. Featured Speaker: The Twister Sisters, Peggy Willenberg and Melanie Metz Topic: Chasing the Greensburg, KS, tornado of May 4, 2007 “Ok, so we're not actually sisters... but we are true Twister Sisters! We started chasing together in 2001 and have become best of friends. We both enjoy life, like a good glass of wine, think the same way, and have a common desire... to capture the perfect wedge! We always agree on a target and continue to learn more from each successful chase and each bust. Every chase is a new and exciting challenge.” “We both have a Bachelor's Degree in Science and are completed several Meteorology courses at Saint Cloud State University. We also attended a Severe Storm Forecasting class instructed by Tim Vasquez and attended the College of Du Page Severe Storms Forecasting Conference. During the chase season, we work for FOX 9 News, KMSP in Minneapolis, MN and teach basic and advanced Skywarn classes. We have given educational severe weather talks for two consecutive years at a HAM radio fest in St. Paul, MN; The Importance of Boundaries for Severe Storm Initiation and Tornadic vs. Non-Tornadic Wall Clouds. During the summer of 2002, we volunteered as IHOP Mobile Mesonet Operators at the National Severe Storms Laboratory. -
Weather Charts Natural History Museum of Utah – Nature Unleashed Stefan Brems
Weather Charts Natural History Museum of Utah – Nature Unleashed Stefan Brems Across the world, many different charts of different formats are used by different governments. These charts can be anything from a simple prognostic chart, used to convey weather forecasts in a simple to read visual manner to the much more complex Wind and Temperature charts used by meteorologists and pilots to determine current and forecast weather conditions at high altitudes. When used properly these charts can be the key to accurately determining the weather conditions in the near future. This Write-Up will provide a brief introduction to several common types of charts. Prognostic Charts To the untrained eye, this chart looks like a strange piece of modern art that an angry mathematician scribbled numbers on. However, this chart is an extremely important resource when evaluating the movement of weather fronts and pressure areas. Fronts Depicted on the chart are weather front combined into four categories; Warm Fronts, Cold Fronts, Stationary Fronts and Occluded Fronts. Warm fronts are depicted by red line with red semi-circles covering one edge. The front movement is indicated by the direction the semi- circles are pointing. The front follows the Semi-Circles. Since the example above has the semi-circles on the top, the front would be indicated as moving up. Cold fronts are depicted as a blue line with blue triangles along one side. Like warm fronts, the direction in which the blue triangles are pointing dictates the direction of the cold front. Stationary fronts are frontal systems which have stalled and are no longer moving. -
Snow Nowcasting Using a Real-Time Correlation of Radar Reflectivity
20 JOURNAL OF APPLIED METEOROLOGY VOLUME 42 Snow Nowcasting Using a Real-Time Correlation of Radar Re¯ectivity with Snow Gauge Accumulation ROY RASMUSSEN AND MICHAEL DIXON National Center for Atmospheric Research, Boulder, Colorado STEVE VASILOFF National Severe Storms Laboratory, Norman, Oklahoma FRANK HAGE,SHELLY KNIGHT,J.VIVEKANANDAN, AND MEI XU National Center for Atmospheric Research, Boulder, Colorado (Manuscript received 21 November 2001, in ®nal form 13 June 2002) ABSTRACT This paper describes and evaluates an algorithm for nowcasting snow water equivalent (SWE) at a point on the surface based on a real-time correlation of equivalent radar re¯ectivity (Ze) with snow gauge rate (S). It is shown from both theory and previous results that Ze±S relationships vary signi®cantly during a storm and from storm to storm, requiring a real-time correlation of Ze and S. A key element of the algorithm is taking into account snow drift and distance of the radar volume from the snow gauge. The algorithm was applied to a number of New York City snowstorms and was shown to have skill in nowcasting SWE out to at least 1 h when compared with persistence. The algorithm is currently being used in a real-time winter weather nowcasting system, called Weather Support to Deicing Decision Making (WSDDM), to improve decision making regarding the deicing of aircraft and runway clearing. The algorithm can also be used to provide a real-time Z±S relationship for Weather Surveillance Radar-1988 Doppler (WSR-88D) if a well-shielded snow gauge is available to measure real-time SWE rate and appropriate range corrections are made. -
Quantitative Interpretation of Laser Ceilometer Intensity Profiles
396 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 14 Quantitative Interpretation of Laser Ceilometer Intensity Pro®les R. R. ROGERS AND M.-F. LAMOUREUX Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada L. R. BISSONNETTE Defence Research Establishment Valcartier, Courcelette, Quebec, Canada R. M. PETERS Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania (Manuscript received 23 July 1996, in ®nal form 28 October 1996) ABSTRACT The authors have used a commercially available laser ceilometer to measure vertical pro®les of the optical extinction in rain. This application requires special signal processing to correct the raw data for the effects of receiver noise, high-pass ®ltering, and the incomplete overlap of the transmitted beam with the receiver ®eld of view at close range. The calibration constant of the ceilometer, denoted by C, is determined from the pro®le of the corrected returned power in conditions of moderate attenuation in which the power is completely extin- guished over a distance on the order of 1 km. In this determination, the value of the backscatter-to-extinction ratio k of the scattering medium must be speci®ed and an allowance made for the effects of multiple scattering. These requirements impose an uncertainty on C that can amount to 650%. An alternative to determining the calibration constant is explained, which does not require specifying k, although it assumes that k is constant with height. Using this alternative approach, the authors have estimated many extinction pro®les in rain and compared them with radar re¯ectivity pro®les measured with a UHF boundary layer wind pro®ler. -
The Montague Doppler Radar, an Overview June 2018
ISSUE PAPER SERIES The Montague Doppler Radar, An Overview June 2018 NEW YORK STATE TUG HILL COMMISSION DULLES STATE OFFICE BUILDING · 317 WASHINGTON STREET · WATERTOWN, NY 13601 · (315) 785-2380 · WWW.TUGHILL.ORG The Tug Hill Commission Technical and Issue Paper Series are designed to help local officials and citizens in the Tug Hill region and other rural parts of New York State. The Tech- nical Paper Series provides guidance on procedures based on questions frequently received by the Commis- sion. The Issue Paper Series pro- vides background on key issues facing the region without taking advocacy positions. Other papers in each se- ries are available from the Tug Hill Commission. Please call us or vis- it our website for more information. The Montague Doppler Weather Radar, An Overview Table of Contents Introduction .................................................................................................................................................. 1 Who owns the Montague radar? ................................................................................................................. 1 Who uses the Montague radar? .................................................................................................................. 1 How does the radar system work? .............................................................................................................. 2 How does the radar predict lake-effect snowstorms? ................................................................................ 2 How does the -
Weather Observations
Operational Weather Analysis … www.wxonline.info Chapter 2 Weather Observations Weather observations are the basic ingredients of weather analysis. These observations define the current state of the atmosphere, serve as the basis for isoline patterns, and provide a means for determining the physical processes that occur in the atmosphere. A working knowledge of the observation process is an important part of weather analysis. Source-Based Observation Classification Weather parameters are determined directly by human observation, by instruments, or by a combination of both. Human-based Parameters : Traditionally the human eye has been the source of various weather parameters. For example, the amount of cloud that covers the sky, the type of precipitation, or horizontal visibility, has been based on human observation. Instrument-based Parameters : Numerous instruments have been developed over the years to sense a variety of weather parameters. Some of these instruments directly observe a particular weather parameter at the location of the instrument. The measurement of air temperature by a thermometer is an excellent example of a direct measurement. Other instruments observe data remotely. These instruments either passively sense radiation coming from a location or actively send radiation into an area and interpret the radiation returned to the instrument. Satellite data for visible and infrared imagery are examples of the former while weather radar is an example of the latter. Hybrid Parameters : Hybrid observations refer to weather parameters that are read by a human observer from an instrument. This approach to collecting weather data has been a big part of the weather observing process for many years. Proper sensing of atmospheric data requires proper siting of the sensors. -
NEXRAD Product Improvement Program Update
NEXRAD Product Improvement Program Update Greg Cate OS&T/PPD MARCH 2006 1 TOPICS ORDA • Dual Polarization • Super-Resolution – Recommendation to proceed • FAA Radar Data Ingest •CASA 2 ORDA • ORDA subsystem replaces the current WSR-88D Radar Data Acquisition subsystem to improve: – Receiver and signal processing hardware – User interface – Signal processing and diagnostic software – Reliability, maintainability and availability • ORDA improvements critical to meeting strategic goals for severe weather 3 RDA Status • Began production deployment November 2005 – Five Contractor install teams – Technical Support by RSIS Engineering and ROC – Five Installs/Week • 57 of 158 sites installed • Target completion date – September 2006 • Maintenance Training ongoing • Focus on Transition to O&M 4 5 ORDA Website http://www.orda.roc.noaa.gov/ 6 Dual Polarization 7 Acquisition Strategy Outline • Develop Performance Requirements – Leverage NSSL Experience – Include ROC and Agency Stakeholders • Continue Emphasis on Commercial Solutions • ORDA SIGMET Supports Dual Pol Modification • Performance-based acquisition – Development – Production – Deployment • Utilize NSSL work in Dual Pol Algorithm Development • Align with Current NEXRAD Maintenance Concept • Administer in OS&T/NPI 8 Dual Pol Program Activities • Issue – Contracting Officer is key member of Acquisition Team – NOAA Contracts support is constrained by limited resources – Alternative Contracting Services organization identified • FAA RESULTS Acquisition Group • Located at Mike Monroney Aeronautical Center in Oklahoma City 9 Dual Pol Program Activities (cont.) • Complete NOAA/FAA Inter-Agency Agreement with RESULTS Input • Coordinate Acquisition Plan and Inter- Agency Agreement with NOAA Acquisitions • Brief DOC Acquisition Review Board • Coordinate with RESULTS on: – Pre-Solicitation Activities – Evaluation Plan 10 Dual Pol Technical Activities • Tasking to NSSL – Hardware Analysis and Prototyping – Requirements Development – Polarimetric algorithm development (precip and HCA) – Support RFI/RFP evaluation. -
An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform
aerospace Article An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform Xining Yu 1,*, Yan Zhang 1, Ankit Patel 1, Allen Zahrai 2 and Mark Weber 2 1 School of Electrical and Computer Engineering, University of Oklahoma, 3190 Monitor Avenue, Norman, OK 73019, USA; [email protected] (Y.Z.); [email protected] (A.P.) 2 National Severe Storms Laboratory, National Oceanic and Atomospheric Administration, Norman, OK 73072, USA; [email protected] (A.Z.); [email protected] (M.W.) * Correspondence: [email protected]; Tel.: +1-405-325-2871 Academic Editor: Konstantinos Kontis Received: 22 July 2016; Accepted: 2 September 2016; Published: 9 September 2016 Abstract: This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of general purpose digital signal processors. First, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on a Micro Telecom Computing Architecture (MTCA) chassis using the Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebones design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including the Open Computing Language. Keywords: phased array radar; embedded computing; serial RapidIO; MPAR 1. Introduction 1.1. Real-Time, Large-Scale, Phased Array Radar Systems In [1], we had introduced the real-time phased array radar (PAR) processing based on the Micro Telecom Computing Architecture (MTCA) chassis. -
Gauge and Radarradargauge
GaGaugugeeaandndRRaadadarr PPaaoo--LLiaiangngChaChangng CentCentrarallWWeaeattherherBBurureaeau,u,TTaaiwiwaann A Training Course on Quantitative Precipitation Estimation/Forecasting (QPE/QPF) Crowne Plaza Manila Galleria, Quezon City, Philippines 27-30 March 2012 OOuutlitlinnee RaRadadarraandndGGaaugugeeNetNetwwoorkrkininTTaaiwiwaann RaRadadarrDaDattaaQQCCususingingRefReflectlectivivitityyaandnd RaRainfinfaallllClimClimaattoolologgyy RaRadadarrQQPPEEaandndGGaaugugee--cocorrrrectectededQQPPEE OOututloloookk 2 OOppeerratiationonalalRRadadararNNeetwtwororkkiinnTTaiaiwwanan RRCCWWFF RRCCCCKK RRCCHHLL RRCCMMKK RRCCCCGG RRCCKKTT CCWBWB::RRCCWFWF,,RRCCHHLL,,RRCCKKTT,,RRCCCCGG((DDopoppplleerr,,wwaveavelleenngtgthh::10c10cmm)) AAiirrFFororccee::RRCCCCKK,,RRCCMMKK((dduualal--ppololarariizzatatiionon,,wwaveavelleenngtgthh::5c5cmm)) Taiwan operational radar network basic information RCWF RCHL RCCG RCKT RCCK RCMK Observation Range (km) 460,230 460,230 460,230 460,230 460,160 460,160 (Z,Vr) Gematronik Gematronik Gematronik Gematronik Gematronik Type WSR-88D 1500S 1500S 1500S 1500C 1500C Height (m) 766 63 38 42 203 48 Wavelength (cm) 10 10 10 10 5 5 Polarization Single Single Single Single Dual Dual Max. Unambiguous 26.55 21.15 21.15 49.5 49.5 49.5 Velocity (m/s) GGaaugugeeStStaattioionsns inin TTaaiwiwaann Data from CWB and Gov. agencies (WRA, SWCB,TPC,..) •All Gauge stations ~570 stations •Overland ~560 stations MMeaeannGGaaugugeeSpaSpacingcing ffrroommCWBCWBSitSiteses((dadattaainin22000077)) Number of Gauges CoConceptnceptooffRefReflectlectivivitityyClimClimaattoolologgyy