Operating Instructions Present Weather Sensor Parsivel" (70.200.005.B.E)
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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. -
Operating Instructions Present Weather Sensor Parsivel
Operating instructions Present Weather Sensor Parsivel English We reserve the right to make technical changes! Table of contents 1 Scope of delivery 5 2 Part numbers 5 3 Parsivel Factory Settings 6 4 Safety instructions 7 5 Introduction 8 5.1 Functional principle 8 5.2 Connection Options for the Parsivel 9 6 Installing the Parsivel 10 6.1 Cable Selection 10 6.2 Wiring the Parsivel 11 6.3 Grounding the Parsivel 13 6.4 Installing the Parsivel 14 7 Connecting the Parsivel to a data logger 15 7.1 Connecting the Parsivel to the LogoSens Station Manager via RS-485 interface 15 7.2 Connecting the Parsivel to a Data logger via the SDI-12 Interface 17 7.3 Connecting the Parsivel to a Data Logger with Impulse/Status Input 21 8 Connecting the Parsivel to a PC 23 8.1 Connecting the Parsivel to Interface Converter RS-485/RS-232 (Accessories) 23 8.2 Connecting the Parsivel to the ADAM-4520 Converter RS-485/RS-232 (Accessories) 25 8.3 Connecting the Parsivel to Interface Converter RS-485/USB (Accessories) 26 8.4 Connecting the Parsivel to any RS-485 Interface Converter 27 8.5 Connecting the Parsivel for configuration via the Service-Tool to a PC 27 9 Connecting the Parsivel to a Power Supply (Accessory) 29 10 Heating the Parsivel sensor heads 30 11 Operating Parsivel with a Terminal software 31 11.1 Set up communications between the Parsivel and the terminal program 31 11.2 Measured value numbers 32 11.3 Defining the formatting string 33 11.4 OTT telegram 33 11.5 Updating Parsivel Firmware 34 12 Maintenance 36 12.1 Cleaning the laser’s protective glass -
How to Get Weather and Pest Data?
How to get weather and pest data? François Brun (ACTA) with contributions of the other lecturers IPM CC, October 2016 Which data ? • Weather and Climate – Weather : conditions of the atmosphere over a short period of time – climate : atmosphere behavior over relatively long periods of time. • Pest and Disease data – Effects of conditions : experiments – Epidemiology : observation / monitoring networks Weather and Climate data Past Weather Historical Climate Data – Ground weather station – Average and variability – Satellite,… – Real long time series – Reconstituted long series – Simulated long series (1961- 1990 : reference) Forecast Weather Climate projections – Prediction with model – Prediction with model – Short term : 1h, 3h, 12h, 24, – IPCC report 3 day, 15 day. – 2021-2050 : middle of – Seasonal prediction : 1 to 6 century period months (~ el nino ) – 2071-2100 : end of century period Past Weather data Standard weather station Standard : at 2 m height • Frequent Useful for us – Thermometer : temperature – Anemometer : wind speed – Wind vane : wind direction – Hygrometer : humidity – Barometer : atmospheric pressure • Less frequent – Ceilometer : cloud height – Present weather sensor – Visibility sensor – Rain gauge : liquid-equivalent precipitation – Ultrasonic snow depth sensor for measuring depth of snow © Choi – Pyranometer : solar radiation Past Weather data In field / micro weather observations Wetness duration Temperature and humidity in canopy Water in soil © Choi Past Weather data Where to retrieve them ? • Your own weather -
ICICLE Program Updates (Stephanie Divito, FAA)
In-Cloud ICing and Large-drop Experiment Stephanie DiVito, FAA October 13, 2020 New FAA Flight program: ICICLE In-Cloud ICing and Large-drop Experiment Other Participants: Desert Research Institute (DRI), National Oceanic and Atmospheric Association (NOAA) Earth System Research Laboratory (ESRL), National Aeronautics and Space Administration (NASA) Langley Research Center, Meteo-France, UK Met Office, Deutscher Wetterdienst (German Meteorological Office), Northern Illinois University, Iowa State University, University of Illinois at Urbana-Champaign, and Valparaiso University 10/13/2020 FPAW: ICICLE 2 Flight Program Overview • January 27 – March 8, 2019 • Operations Base: Rockford, Illinois – Domain: 200 nmi radius • NRC Convair-580 aircraft – Owned and operated by NRC Flight Research Laboratory – Jointly instrumented by NRC and ECCC – Extensively used in icing research for over 25 years • 120 flight hours (110 for research) • 26 research flights (30 total) 10/13/2020 FPAW: ICICLE 3 Scientific & Technical Objectives • Observe, document, and further characterize a variety of in-flight and surface-level icing conditions – Environmental parameters and particle size distribution for: . Small-drop icing, FZDZ and FZRA – Transitions between those environments & non-icing environments – Synoptic, mesoscale & local effects • Assess ability of operational data, icing tools and products to diagnose and forecast those features – Satellite – GOES-16 – Radar – Individual NEXRADs, MRMS – Surface based – ASOS, AWOS, etc. – Numerical Weather Prediction (NWP) models – Microphysical parameterizations, TLE, etc. – Icing Products - CIP, FIP, other icing tools 10/13/2020 FPAW: ICICLE 4 Sampling Objectives (1/2) • Collect data in a wide variety of icing and non-icing conditions – Small-drop and large-drop . Including those with (& without) FZDZ and FZRA – Null icing environments . -
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 -
Ott Parsivel - Enhanced Precipitation Identifier for Present Weather, Drop Size Distribution and Radar Reflectivity - Ott Messtechnik, Germany
® OTT PARSIVEL - ENHANCED PRECIPITATION IDENTIFIER FOR PRESENT WEATHER, DROP SIZE DISTRIBUTION AND RADAR REFLECTIVITY - OTT MESSTECHNIK, GERMANY Kurt Nemeth1, Martin Löffler-Mang2 1 OTT Messtechnik GmbH & Co. KG, Kempten (Germany) 2 HTW, Saarbrücken (Germany) as a laser-optic enhanced precipitation identifier and present weather sensor. The patented extinction method for simultaneous measurements of particle size and velocity of all liquid and solid precipitation employs a direct physical measurement principle and classification of hydrometeors. The instrument provides a full picture of precipitation events during any kind of weather phenomenon and provides accurate reporting of precipitation types, accumulation and intensities without degradation of per- formance in severe outdoor environments. Parsivel® operates in any climate regime and the built-in heating device minimizes the negative effect of freezing and frozen precipitation accreting critical surfaces on the instrument. Parsivel® can be integrated into an Automated Surface/ Weather Observing System (ASOS/AWOS) as part of the sensor suite. The derived data can be processed and 1. Introduction included into transmitted weather observation reports and messages (WMO, SYNOP, METAR and NWS codes). ® OTT Parsivel : Laser based optical Disdrometer for 1.2. Performance, accuracy and calibration procedure simultaneous measurement of PARticle SIze and VELocity of all liquid and solid precipitation. This state The new generation of Parsivel® disdrometer provides of the art instrument, designed to operate under all the latest state of the art optical laser technology. Each weather conditions, is capable of fulfilling multiple hydrometeor, which falls through the measuring area is meteorological applications: present weather sensing, measured simultaneously for size and velocity with an optical precipitation gauging, enhanced precipitation acquisition cycle of 50 kHz. -
Launching of New RS90-AG Radiosonde Valuable
40813_VaisalaNews_155 7.12.2000 18:29 Sivu 1 155/2001155/2001 After Extensive Field Testing: Launching of New RS90-AG Radiosonde Customer Satisfaction Survey for WOBS Customers: Valuable Customer Feedback Using Product Platforms: Next Generation of Surface Weather Software Products New ROSA Weather Station Generation: Evolution Rather Than Revolution 40813_VaisalaNews_155 7.12.2000 18:29 Sivu 2 Contents President’s Column 3 Serving Better Our Customers 4 Customer Satisfaction Survey for WOBS Customers: Valuable Customer Feedback 6 Next Generation of Surface Weather Software Products 8 Meteorological Data Management System: Aurora’s payload system was MetMan for Multi-purpose Data Collection 10 developed for high altitude dropsonde missions, for use on Compact MAWS301 Automatic Weather Station 12 low speed platforms such as Demanding Tactical Military Needs 14 Pathfinder, Altus and Perseus B. Due to funding cuts, the Vaisala Technology for the U.S. Air Force 17 dropsonde payload was not Military Exhibition EUROSATORY 2000 in France 18 permitted to be deployed and Climatological Conditions on the My Thuan Bridge 19 operated from Pathfinder. Nevertheless, Aurora tested and Major Contract from the U.S. qualified the payload for flight, National Weather Service 20 using its high altitude test Using L and S-Band Boundary Layer Radars and a chambers. Vaisala’s dropsondes were an integral part of this Millimeter-wave Doppler Radar with Vaisala MAWS: scientific experiment. Weather Observations 20 Researchers are using dropson- Royal Botanic Gardens Melbourne: des to get a more accurate pic- Fostering Plant Conservation 24 ture of hurricanes. Fire RAWS Unit on the Bircher Burned Over 26 Launching of RS90-AG Radiosonde 29 Vaisala’s MAWS301 Automatic Global Positioning System 31 Weather Station is a new gener- ation weather station especially Significant Radiosonde Order designed for applications where from Met Service Canada 32 no commercial power or com- Vaisala’s Next Generation munication networks are avail- 32 able or economically installed. -
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1182 MONTHLY WEATHER REVIEW VOLUME 141 Drop-Size Distributions in Thunderstorms Measured by Optical Disdrometers during VORTEX2 KATJA FRIEDRICH AND EVAN A. KALINA University of Colorado, Boulder, Colorado FORREST J. MASTERS AND CARLOS R. LOPEZ University of Florida, Gainesville, Florida (Manuscript received 13 April 2012, in final form 22 October 2012) ABSTRACT When studying the influence of microphysics on the near-surface buoyancy tendency in convective thun- derstorms, in situ measurements of microphysics near the surface are essential and those are currently not provided by most weather radars. In this study, the deployment of mobile microphysical probes in con- vective thunderstorms during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) is examined. Microphysical probes consist of an optical Ott Particle Size and Velocity (PARSIVEL) disdrometer that measures particle size and fall velocity distributions and a surface obser- vation station that measures wind, temperature, and humidity. The mobile probe deployment allows for targeted observations within various areas of the storm and coordinated observations with ground-based mobile radars. Quality control schemes necessary for providing reliable observations in severe environ- ments with strong winds and high rainfall rates and particle discrimination schemes for distinguishing be- tween hail, rain, and graupel are discussed. It is demonstrated how raindrop-size distributions for selected cases can be applied to study size-sorting and microphysical processes. The study revealed that the raindrop-size distribution changes rapidly in time and space in convective thunderstorms. Graupel, hailstones, and large raindrops were primarily observed close to the updraft region of thunderstorms in the forward- and rear-flank downdrafts and in the reflectivity hook appendage. -
Observation of Present and Past Weather; State of the Ground
CHAPTER CONTENTS Page CHAPTER 14. OBSERVATION OF PRESENT AND PAST WEATHER; STATE OF THE GROUND .. 450 14.1 General ................................................................... 450 14.1.1 Definitions ......................................................... 450 14.1.2 Units and scales ..................................................... 450 14.1.3 Meteorological requirements ......................................... 451 14.1.4 Observation methods. 451 14.2 Observation of present and past weather ...................................... 451 14.2.1 Precipitation. 452 14.2.1.1 Objects of observation ....................................... 452 14.2.1.2 Instruments and measuring devices: precipitation type ........... 452 14.2.1.3 Instruments and measuring devices: precipitation intensity and character ............................................... 454 14.2.1.4 Instruments and measuring devices: multi-sensor approach ....... 455 14.2.2 Atmospheric obscurity and suspensoids ................................ 455 14.2.2.1 Objects of observation ....................................... 455 14.2.2.2 Instruments and measuring devices for obscurity and suspensoid characteristics .................................... 455 14.2.3 Other weather events ................................................ 456 14.2.3.1 Objects of observation ....................................... 456 14.2.3.2 Instruments and measuring devices. 457 14.2.4 State of the sky ...................................................... 457 14.2.4.1 Objects of observation ...................................... -
Radar Artifacts and Associated Signatures, Along with Impacts of Terrain on Data Quality
Radar Artifacts and Associated Signatures, Along with Impacts of Terrain on Data Quality 1.) Introduction: The WSR-88D (Weather Surveillance Radar designed and built in the 80s) is the most useful tool used by National Weather Service (NWS) Meteorologists to detect precipitation, calculate its motion, estimate its type (rain, snow, hail, etc) and forecast its position. Radar stands for “Radio, Detection, and Ranging”, was developed in the 1940’s and used during World War II, has gone through numerous enhancements and technological upgrades to help forecasters investigate storms with greater detail and precision. However, as our ability to detect areas of precipitation, including rotation within thunderstorms has vastly improved over the years, so has the radar’s ability to detect other significant meteorological and non meteorological artifacts. In this article we will identify these signatures, explain why and how they occur and provide examples from KTYX and KCXX of both meteorological and non meteorological data which WSR-88D detects. KTYX radar is located on the Tug Hill Plateau near Watertown, NY while, KCXX is located in Colchester, VT with both operated by the NWS in Burlington. Radar signatures to be shown include: bright banding, tornadic hook echo, low level lake boundary, hail spikes, sunset spikes, migrating birds, Route 7 traffic, wind farms, and beam blockage caused by terrain and the associated poor data sampling that occurs. 2.) How Radar Works: The WSR-88D operates by sending out directional pulses at several different elevation angles, which are microseconds long, and when the pulse intersects water droplets or other artifacts, a return signal is sent back to the radar. -
Observation of Cloud Base Height and Precipitation Characteristics at a Polar Site Ny-Ålesund, Svalbard Using Ground-Based Remote Sensing and Model Reanalysis
remote sensing Article Observation of Cloud Base Height and Precipitation Characteristics at a Polar Site Ny-Ålesund, Svalbard Using Ground-Based Remote Sensing and Model Reanalysis Acharya Asutosh 1,2,*, Sourav Chatterjee 1,3 , M.P. Subeesh 1, Athulya Radhakrishnan 1 and Nuncio Murukesh 1 1 National Centre for Polar and Ocean Research, Ministry of Earth Sciences, Goa 403804, India; [email protected] (S.C.); [email protected] (M.P.S.); [email protected] (A.R.); [email protected] (N.M.) 2 Indian Institute of Technology, Bhubaneswar, Odisha 752050, India 3 School of Earth, Ocean, and Atmospheric Sciences, Goa University, Goa 403206, India * Correspondence: [email protected] Abstract: Clouds play a significant role in regulating the Arctic climate and water cycle due to their impacts on radiative balance through various complex feedback processes. However, there are still large discrepancies in satellite and numerical model-derived cloud datasets over the Arctic region due to a lack of observations. Here, we report observations of cloud base height (CBH) characteristics measured using a Vaisala CL51 ceilometer at Ny-Ålesund, Svalbard. The study highlights the monthly and seasonal CBH characteristics at the location. It is found that almost 40% of the lowest Citation: Asutosh, A.; Chatterjee, S.; CBHs fall within a height range of 0.5–1 km. The second and third cloud bases that could be detected Subeesh, M.P.; Radhakrishnan, A.; by the ceilometer are mostly concentrated below 3 km during summer but possess more vertical Murukesh, N. Observation of Cloud spread during the winter season. Thin and low-level clouds appear to be dominant during the Base Height and Precipitation summer.