Predicting the Weather Lesson Plans
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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. -
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 -
A Study on Snow Density Variations at Different Elevations
Brian Miretzky 1 A Study on Snow Density Variations at Different Elevations and the Related Consequences; Especially to Forecasting. Brian J. Miretzky Senior Undergrad at the University of Wisconsin- Madison ABSTRACT With observations becoming more common and forecasting becoming more accurate snow density research has increased. These new observations can be correlated with current knowledge to develop reasons for snow density variations. Currently there is still no specific consensus on what are the important characteristics in snow density variations. There are many points of general agreement such as that temperature and relative humidity are key factors. How to incorporate these into snowfall prediction is the key. Once there is more substantiated knowledge, more accurate forecasts can be made. Finally, the last in the chain of events is that society can plan accordingly to this new data. Better prediction means less work, less time, and less money spent. This study attempts to determine if elevation is an important characteristic in snow density variations. It also looks at computer models and how snow density is used in conjunction with these models to make snowfall projections. The results seem to show elevation is not an important characteristic. The results also show that model accuracy is more important than snow density variations when using models to make snowfall projections. 1. Introduction volume of the sample. Snow densities are typically on an order of 70 to 150 kg The density of snow is a m-3, but can be lower or higher in some very important topic in winter weather. cases. This is because the density of snow The fact that snow densities can helps determine characteristics of a vary makes them one of the most given snowfall. -
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. -
Evaluation of the Hotplate Snow Gauge
Evaluation of the Hotplate Snow Gauge http://aurora-program.org Aurora Project 2004-01 Final Report July 2005 Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No. Aurora Project 2004-01 4. Title and Subtitle 5. Report Date Evaluation of the Hotplate Snow Gauge July 2005 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Jack Stickel, Bill Maloney, Curt Pape, Dennis Burkheimer 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) Center for Transportation Research and Education Iowa State University 11. Contract or Grant No. 2711 South Loop Drive, Suite 4700 Ames, IA 50010-8664 12. Sponsoring Organization Name and Address 13. Type of Report and Period Covered Aurora Program Iowa State University 14. Sponsoring Agency Code 2711 South Loop Drive, Suite 4700 Ames, IA 50010-8664 15. Supplementary Notes Visit www.ctre.iastate.edu for color PDF files of this and other research reports. 16. Abstract Winter precipitation (e.g., snow, ice, freezing rain) is poorly measured by current National Weather Service (NWS), Federal Aviation Administration (FAA), and State Departments of Transportation (SDOT) automated weather observation systems. The lack of accurate winter precipitation measurements, particularly snow, negatively impacts the ability of winter maintenance personnel to conduct snow and ice control operations. The inability to accurately measure winter precipitation is an ongoing problem that is well recognized by the meteorological community as well as organizations and industries dependent on accurate quantitative precipitation information. The FAA recognized this limitation and its impact on the ability to conduct aircraft deicing operations, and began a research program in the 1990s to improve decision support for aircraft deicing. -
Measurement of Precipitation
CHAPTER CONTENTS Page CHAPTER 6. MEASUREMENT OF PRECIPITATION ..................................... 186 6.1 General ................................................................... 186 6.1.1 Definitions ......................................................... 186 6.1.2 Units and scales ..................................................... 186 6.1.3 Meteorological and hydrological requirements .......................... 187 6.1.4 Measurement methods .............................................. 187 6.1.4.1 Instruments ................................................ 187 6.1.4.2 Reference gauges and intercomparisons ........................ 188 6.1.4.3 Documentation. 188 6.2 Siting and exposure ........................................................ 189 6.3 Non-recording precipitation gauges .......................................... 190 6.3.1 Ordinary gauges .................................................... 190 6.3.1.1 Instruments ................................................ 190 6.3.1.2 Operation. 192 6.3.1.3 Calibration and maintenance ................................. 192 6.3.2 Storage gauges ..................................................... 192 6.4 Precipitation gauge errors and corrections ..................................... 193 6.5 Recording precipitation gauges .............................................. 196 6.5.1 Weighing-recording gauge ........................................... 196 6.5.1.1 Instruments ................................................ 196 6.5.1.2 Errors and corrections. 197 6.5.1.3 Calibration -
Coastal Weather Program
Commandant 2100 Second Street, S.W. United States Coast Guard Washington, DC 20593-0001 (202) 267-1450 COMDTINST 3140.3D 13 JAN 1988 COMMANDANT INSTRUCTION 3140.3D Subj: Coastal Weather Program 1. PURPOSE. To set forth policy for weather observation, reporting, and dissemination from Coast Guard shore units and offshore light stations; and, to direct the coordination with the National Weather Service (NWS) for these activities. 2. DIRECTIVES AFFECTED. Commandant Instruction 3140.3C is canceled. 3. PROGRAM OBJECTIVES. To support the National Weather Service in conducting its federally-mandated weather forecasting and dissemination program by: a. Designating those stations and units required to report weather observations. b. Ensuring that weather reports are made in the suitable format as prescribed by the NWS. c. Ensuring that uniform and timely communication procedures and methods are used to convey this information to the NWS. d. Providing procedures for units not participating in a regular weather reporting program which may be required to make weather observations in support of NWS special programs. 4. POLICY. Title 14 Section 147 of the U.S. Code authorizes the Commandant to procure, maintain, and make available facilities and assistance for observing, investigating, and communicating weather phenomena and for disseminating weather data, forecasts and warnings in cooperation with the Director of the National Weather Service. To this end the Commandant supports a program to ensure the high quality and quantity of weather observations for NWS marine weather forecasts. The Coast Guard, as a user, depends upon high quality forecasts for our missions in the marine environment. COMDTINST 3140.3D 13 JAN 1988 5. -
Allianz Risk Barometer
ALLIANZ GLOBAL CORPORATE & SPECIALTY ALLIANZ RISK BAROMETER IDENTIFYING THE MAJOR BUSINESS RISKS FOR 2021 The most important corporate perils for the next 12 months and beyond, based on the insight of 2,769 risk management experts from 92 countries and territories. About Allianz Global Corporate & Specialty Allianz Global Corporate & Specialty (AGCS) is a leading global corporate insurance carrier and a key business unit of Allianz Group. We provide risk consultancy, Property-Casualty insurance solutions and alternative risk transfer for a wide spectrum of commercial, corporate and specialty risks across 10 dedicated lines of business. Our customers are as diverse as business can be, ranging from Fortune Global 500 companies to small businesses, and private individuals. Among them are not only the world’s largest consumer brands, tech companies and the global aviation and shipping industry, but also wineries, satellite operators or Hollywood film productions. They all look to AGCS for smart answers to their largest and most complex risks in a dynamic, multinational business environment and trust us to deliver an outstanding claims experience. Worldwide, AGCS operates with its own teams in 31 countries and through the Allianz Group network and partners in over 200 countries and territories, employing over 4,450 people. As one of the largest Property-Casualty units of Allianz Group, we are backed by strong and stable financial ratings. In 2019, AGCS generated a total of €9.1 billion gross premium globally. www.agcs.allianz.com/about-us/about-agcs.html METHODOLOGY CONTENTS The 10th Allianz Risk Barometer is the biggest yet, incorporating the views of a record 2,769 respondents from 92 countries and territories. -
260-2510 Standard Rain and Snow Gauge
Precipitation 260-2510 Standard Rain and Snow Gauge The 260-2510 Standard Rain and Snow Gauge is a National Weather Service type all-aluminum rain gauge with a total capacity of 20" of rainfall. The gauge includes a funnel, measuring tube, overflow can and measuring stick with English and metric markings. The tripod support is sold separately. The upper portion of the funnel is cylindrical in shape and is turned to a fine edge. Rainwater falling into the funnel is delivered into a measuring tube. The cross- section area of the tube is one-tenth the cross-section area of the funnel. Therefore, when 1 inch of rain falls into the funnel, it fills the measuring tube to a depth of 10 inches. The scale on the measuring stick is expanded 10 times, and since the scale is graduated to hundredths of an inch, the correct rainfall depth of water in the tube is read directly to hundredths from the stick. The capacity of the measuring tube is 2" of rainfall. Any excess overflows into the outer chamber. The overflow water must be transferred to the empty measuring tube for direct measurement with the stick. In winter, the funnel and measuring tube are removed so that rain/sleet/snow/hail are collected by the outer chamber. The amount of precipitation is measured by melting the ice and then pouring the water into the measuring tube. 260-2510 Rain Gauge Features with 260-2510S Tripod National Weather Service Type Rain and Snow Gauge Total capacity 20 inches (500 mm) English / metric measuring stick included Optional tripod support stand Specifications -
The Measurement Factors in Estimating Snowfall Derived from Snow Cover Surfaces Using Acoustic Snow Depth Sensors
MARCH 2011 F I S C H E R 681 The Measurement Factors in Estimating Snowfall Derived from Snow Cover Surfaces Using Acoustic Snow Depth Sensors ALEXANDRE P. FISCHER Observing Systems and Engineering, Weather and Environmental Monitoring, Environment Canada, Toronto, Ontario, Canada (Manuscript received 8 October 2009, in final form 14 October 2010) ABSTRACT At three Canadian test locations during the cold seasons of 2006 and 2007/08, snowfall measurements are derived from changes in the total depth of snow on the ground using multiple Campbell Scientific, Inc., SR50 ultrasonic ranging sensors over very short (minute–hour) time scales. Data analysis reveals that, because of the interplay of numerous essential factors that influence snow cover levels, the measurements exhibit a strong dependence on the time interval between consecutive measurements used to generate the snowfall value. This finding brings into question the reasonable accuracy of snowfall measurements that are derived from the snow cover surface using automated methods over very short time scales. In this study, two math- ematical methods are developed to assist in quantifying the magnitude of the snowfall measurement error. From time-series analysis, the suggested characteristics of the snowdrift signal in the snow depth time series is shown by using measurements taken by FlowCapt Snowdrift acoustic sensors. Furthermore, the use of three collocated SR50s shows that repeated snow depth measurements represent three pairwise essentially dif- ferent time series. These results question the reasonable accuracy of snowfall measurements derived using only a single ultrasonic ranging sensor, especially in cases in which the snow cover is redistributed by the wind and in which snow depth spatial variability is prominent. -
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DECEMBER 2007 C H E R R Y E T A L . 1243 Development of the Pan-Arctic Snowfall Reconstruction: New Land-Based Solid Precipitation Estimates for 1940–99 J. E. CHERRY International Arctic Research Center, and Arctic Region Supercomputing Center, University of Alaska Fairbanks, Fairbanks, Alaska L.-B. TREMBLAY Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada M. STIEGLITZ School of Civil and Environmental Engineering, and School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia G. GONG Department of Earth and Environmental Engineering, Columbia University, New York, New York S. J. DÉRY Environmental Science and Engineering Program, University of Northern British Columbia, Prince George, British Columbia, Canada (Manuscript received 24 April 2006, in final form 5 January 2007) ABSTRACT A new product, the Pan-Arctic Snowfall Reconstruction (PASR), is developed to address the problem of cold season precipitation gauge biases for the 1940–99 period. The method used to create the PASR is different from methods used in other large-scale precipitation data products and has not previously been employed for estimating pan-arctic snowfall. The NASA Interannual-to-Seasonal Prediction Project Catch- ment Land Surface Model is used to reconstruct solid precipitation from observed snow depth and surface air temperatures. The method is tested at four stations in the United States and Canada where results are examined in depth. Reconstructed snowfall at Dease Lake, British Columbia, and Barrow, Alaska, is higher than gauge observations. Reconstructed snowfall at Regina, Saskatchewan, and Minot, North Dakota, is lower than gauge observations, probably because snow is transported by wind out of the Prairie region and enters the hydrometeorological cycle elsewhere.