Atmospheric Measurements Learning Module
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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. -
Downloaded 09/25/21 08:19 AM UTC 662 JOURNAL of ATMOSPHERIC and OCEANIC TECHNOLOGY VOLUME 15 Mer 1987; Muller and Beekman 1987; Crescenti Et Al
JUNE 1998 BREAKER ET AL. 661 Preliminary Results from Long-Term Measurements of Atmospheric Moisture in the Marine Boundary Layer in the Gulf of Mexico* LAURENCE C. BREAKER National Weather Service, NCEP, NOAA, Washington, D.C. DAVID B. GILHOUSEN National Weather Service, National Data Buoy Center, NOAA, Stennis Space Center, Mississippi LAWRENCE D. BURROUGHS National Weather Service, NCEP, NOAA, Washington, D.C. (Manuscript received 1 April 1997, in ®nal form 18 July 1997) ABSTRACT Measurements of boundary layer moisture have been acquired from Rotronic MP-100 sensors deployed on two National Data Buoy Center (NDBC) buoys in the northern Gulf of Mexico from June through November 1993. For one sensor that was retrieved approximately 8 months after deployment and a second sensor that was retrieved about 14 months after deployment, the pre- and postcalibrations agreed closely and fell within WMO speci®cations for accuracy. A second Rotronic sensor on one of the buoys provided the basis for a detailed comparison of the instruments and showed close agreement. A separate comparison of the Rotronic instrument with an HO-83 hygrometer at NDBC showed generally close agreement over a 1-month period, which included a number of fog events. The buoy observations of relative humidity and supporting data from the buoys were used to calculate speci®c humidity. Speci®c humidities from the buoys were compared with speci®c humidities computed from observations obtained from nearby ship reports, and the correlations were generally high (0.7± 0.9). Uncertainties in the calculated values of speci®c humidity were also estimated and ranged between 0.27% and 2.1% of the mean value, depending on the method used to estimate this quantity. -
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. -
Imet-4 Radiosonde 403 Mhz GPS Synoptic
iMet-4 Radiosonde 403 MHz GPS Synoptic Technical Data Sheet Temperature and Humidity Radiosonde Data Transmission The iMet-4 measures air temperature with a The iMet-4 radiosonde can transmit to an small glass bead thermistor. Its small size effective range of over 250 km*. minimizes effects caused by long and short- wave radiation and ensures fast response times. A 6 kHz peak-to-peak FM transmission maximizes efficiency and makes more channels The humidity sensor is a thin-film capacitive available for operational use. Seven frequency polymer that responds directly to relative selections are pre-programmed - with custom humidity. The sensor incorporates a temperature programming available. sensor to minimize errors caused by solar heating. Calibration Pressure and Height The iMet-4’s temperature and humidity sensors are calibrated using NIST traceable references to As recommended by GRUAN3, the iMet-4 is yield the highest data quality. equipped with a pressure sensor to calculate height at lower levels in the atmosphere. Once Benefits the radiosonde reaches the optimal height, pressure is derived using GPS altitude combined • Superior PTU performance with temperature and humidity data. • Lightweight, compact design • No assembly or recalibration required The pressure sensor facilitates the use of the • GRUAN3 qualified (pending) sonde in field campaigns where a calibrated • Status LED indicates transmit frequency barometer is not available to establish an selection and 3-D GPS solution accurate ground observation for GPS-derived • Simple one-button user interface pressure. For synoptic use, the sensor is bias adjusted at ground level. Winds Data from the radiosonde's GPS receiver is used to calculate wind speed and direction. -
GPS-Based Measurement of Height and Pressure with Vaisala Radiosonde RS41
GPS-Based Measurement of Height and Pressure with Vaisala Radiosonde RS41 WHITE PAPER Table of Contents CHAPTER 1 Introduction ................................................................................................................................................. 4 Executive Summary of Measurement Performance ............................................................................. 5 CHAPTER 2 GPS Technology in the Vaisala Radiosonde RS41 ........................................................................................... 6 Radiosonde GPS Receiver .................................................................................................................. 6 Local GPS Receiver .......................................................................................................................... 6 Calculation Algorithms ..................................................................................................................... 6 CHAPTER 3 GPS-Based Measurement Methods ............................................................................................................... 7 Height Measurement ......................................................................................................................... 7 Pressure Measurement ..................................................................................................................... 7 Measurement Accuracy..................................................................................................................... 8 CHAPTER -
Manual of Aeronautical Meteorological Practice --`,,```,,,,````-`-`,,`,,`,`,,`
Doc 8896 AN/893 Manual of Aeronautical Meteorological Practice --`,,```,,,,````-`-`,,`,,`,`,,`--- Approved by the Secretary General and published under his authority Ninth Edition — 2011 International Civil Aviation Organization Copyright International Civil Aviation Organization Provided by IHS under license with ICAO No reproduction or networking permitted without license from IHS Not for Resale Suzanne --`,,```,,,,````-`-`,,`,,`,`,,`--- Copyright International Civil Aviation Organization Provided by IHS under license with ICAO No reproduction or networking permitted without license from IHS Not for Resale Doc 8896 AN/893 Manual of Aeronautical Meteorological Practice --`,,```,,,,````-`-`,,`,,`,`,,`--- Approved by the Secretary General and published under his authority Ninth Edition — 2011 International Civil Aviation Organization Copyright International Civil Aviation Organization Provided by IHS under license with ICAO No reproduction or networking permitted without license from IHS Not for Resale Published in separate English, French, Russian and Spanish editions by the INTERNATIONAL CIVIL AVIATION ORGANIZATION 999 University Street, Montréal, Quebec, Canada H3C 5H7 For ordering information and for a complete listing of sales agents and booksellers, please go to the ICAO website at www.icao.int Seventh edition 2006 Eighth edition 2008 Ninth edition 2011 ICAO Doc 8896, Manual of Aeronautical Meteorological Practice Order Number: 8896 ISBN 978-92-9231-828-4 © ICAO 2011 All rights reserved. No part of this publication may be reproduced, -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
Unit 11 Sound Speed of Sound Speed of Sound Sound Can Travel Through Any Kind of Matter, but Not Through a Vacuum
Unit 11 Sound Speed of Sound Speed of Sound Sound can travel through any kind of matter, but not through a vacuum. The speed of sound is different in different materials; in general, it is slowest in gases, faster in liquids, and fastest in solids. The speed depends somewhat on temperature, especially for gases. vair = 331.0 + 0.60T T is the temperature in degrees Celsius Example 1: Find the speed of a sound wave in air at a temperature of 20 degrees Celsius. v = 331 + (0.60) (20) v = 331 m/s + 12.0 m/s v = 343 m/s Using Wave Speed to Determine Distances At normal atmospheric pressure and a temperature of 20 degrees Celsius, speed of sound: v = 343m / s = 3.43102 m / s Speed of sound 750 mi/h Speed of light 670 616 629 mi/h c = 300,000,000m / s = 3.00 108 m / s Delay between the thunder and lightning Example 2: The thunder is heard 3 seconds after the lightning seen. Find the distance to storm location. The speed of sound is 345 m/s. distance = v t = (345m/s)(3s) = 1035m Example 3: Another phenomenon related to the perception of time delays between two events is an echo. In a canyon, an echo is heard 1.40 seconds after making the holler. Find the distance to the canyon wall (v=345m/s) distanceround trip = vt = (345 m/s )( 1.40 s) = 483 m d= 484/2=242m Applications: Sonar, Ultrasound, and Medical Imaging • Ultrasound or ultrasonography is a medical imaging technique that uses high frequency sound waves and their echoes. -
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