Weatherscope Weatherscope Application Information: Weatherscope Is a Stand-Alone Application That Makes Viewing Weather Data Easier
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University of Oklahoma
UNIVERSITY OF OKLAHOMA GRADUATE COLLEGE INVESTIGATION OF POLARIMETRIC MEASUREMENTS OF RAINFALL AT CLOSE AND DISTANT RANGES A DISSERTATION SUBMITTED TO THE GRADUATE FACULTY in partial fulfillment of the requirements for the degree of Doctor of Philosophy By SCOTT EDWARD GIANGRANDE Norman, Oklahoma 2007 UMI Number: 3291249 UMI Microform 3291249 Copyright 2008 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, MI 48106-1346 INVESTIGATION OF POLARIMETRIC MEASUREMENTS OF RAINFALL AT CLOSE AND DISTANT RANGES A DISSERTATION APPROVED FOR THE SCHOOL OF METEOROLOGY BY ____________________________________ Dr. Michael Biggerstaff ____________________________________ Dr. Alexander Ryzhkov ____________________________________ Dr. Jerry Straka ____________________________________ Dr. Guifu Zhang ____________________________________ Dr. Mark Yeary © Copyright by SCOTT EDWARD GIANGRANDE 2007 All Rights Reserved. ACKNOWLEDGEMENTS I would like to extend my sincerest thanks to the numerous individuals who have helped me complete this work. To begin, this work would not have been possible without the guidance of my primary research advisor, Dr. Alexander Ryzhkov. His leadership and patience were instrumental throughout this process. I would also like to extend my gratitude to the other members of my committee: Drs. Michael Biggerstaff (Co-Chair and primary OU School of Meteorology advisor), Guifu Zhang, Jerry Straka, and Mark Yeary. The reviews performed by these individuals strengthened this work. I also thank the members of the Radar Research and Development Division (RRDD) at the National Severe Storms Laboratory (NSSL), which includes Drs. Douglas Forsyth, Dusan Zrnic, Dick Doviak, Allen Zahrai, Terry Schuur, Pam Heinselman, Valery Melnikov, Sebastian Torres, Pengfei Zhang and Svetlana Bachmann. -
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. -
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. -
MN GIS/Lis2011conference 21St Annual Conference and Workshops
MN GIS/LIS2011Conference 21st Annual Conference and Workshops October 5–7, 2011 Saint Cloud River’s Edge Convention Center www.mngislis.org 1000 Westgate Drive, Suite 252 St. Paul, MN 55114-1067 (651) 203-7242 www.mngislis.org W LCOME Welcome to the 2011 MN GIS/LIS Conference and Workshops E The Minnesota GIS/LIS Board of Directors and Conference Committee first time. Consider attending the student competition on Thursday and welcome you to the 21st annual Minnesota GIS/LIS Conference and welcoming these future GIS professionals. Workshops. This year’s Conference will offer a unique experience to explore geographic information systems and land information systems We have an opportunity to recognize our former and current Polaris in Minnesota and beyond. and Lifetime award winners. Please take a minute to congratulate these committed individuals who are at the heart of GIS/LIS in Minnesota: MN Keynote speakers will bring us to new places, exhibiting how GIS is useful GIS/LIS honors them for their leadership. beyond our world. This year’s keynote speaker, Dr. Scott Mest, a research scientist with NASA, will introduce us to his work using GIS to study the Exhibitors support the conference and offer a variety of GIS products, surface of the moon and Mars. On Friday, we step back for a moment, services and information. The Exhibit hall is open Thursday at 10am. put down our wireless devices and unplug our laptops. Listen to Mr. Don’t forget to stop by the MN GIS/LIS Consortium booth in the exhibit Kenny Salwey, the “Last River Rat,” share his experiences living on the hall. -
2020 Infra Surface Weather Observations
Surface Weather Observations Comparison of Various Observing Systems Scott Landolt & Matthias Steiner National Center for Atmospheric Research [email protected] USHST Infrastructure Summit 12 – 13 March 2020 in Washington, DC © 2020 University Corporation for Atmospheric Research 1 Surface Stations & Reporting Frequency Station Type Frequency of Reports Automated Surface 5 minutes Observing System (ASOS) (limited access to 1 minute data) Automated Weather 20 minutes Observing System (AWOS) 15 minutes (standard), can be Road Weather Information more frequent but varies state to System (RWIS) state and even site to site 5 – 15 minutes, can vary from Mesonet station to station Iowa station network © 2020 University Corporation for Atmospheric Research 2 Reporting Variables Weather Variable ASOS AWOS RWIS Mesonet Temperature X X X X Relative X X X X Humidity/Dewpoint Wind Speed/Direction X X X X Barometric Pressure X X X X Ceiling Height X X X X Visibility X X X X Present Weather X X X X Precipitation X X X X Accumulation Road Condition X X X X X – All Stations Report X – Some Stations Report X – No Stations Report © 2020 University Corporation for Atmospheric Research 3 Station Siting Requirements Station Type Siting Areal Representativeness Automated Surface Miles (varies depending on Airport grounds, unobstructed Observing System (ASOS) local conditions & weather) Automated Weather Miles (varies depending on Airport grounds, unobstructed Observing System (AWOS) local conditions & weather) Next to roadways, can be in canyons, valleys, mountain -
Relative Forecast Impact from Aircraft, Profiler, Rawinsonde, VAD, GPS-PW, METAR and Mesonet Observations for Hourly Assimilation in the RUC
16.2 Relative forecast impact from aircraft, profiler, rawinsonde, VAD, GPS-PW, METAR and mesonet observations for hourly assimilation in the RUC Stan Benjamin, Brian D. Jamison, William R. Moninger, Barry Schwartz, and Thomas W. Schlatter NOAA Earth System Research Laboratory, Boulder, CO 1. Introduction A series of experiments was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied to assess the relative importance of the different data types for short-range (3h-12h duration) wind, temperature, and relative humidity forecasts at different vertical levels. This assessment of the value of 7 different observation data types (aircraft (AMDAR and TAMDAR), profiler, rawinsonde, VAD (velocity azimuth display) winds, GPS precipitable water, METAR, and mesonet) on short-range numerical forecasts was carried out for a 10-day period from November- December 2006. 2. Background Observation system experiments (OSEs) have been found very useful to determine the impact of particular observation types on operational NWP systems (e.g., Graham et al. 2000, Bouttier 2001, Zapotocny et al. 2002). This new study is unique in considering the effects of most of the currently assimilated high-frequency observing systems in a 1-h assimilation cycle. The previous observation impact experiments reported in Benjamin et al. (2004a) were primarily for wind profiler and only for effects on wind forecasts. This new impact study is much broader than that the previous study, now for more observation types, and for three forecast fields: wind, temperature, and moisture. Here, a set of observational sensitivity experiments (Table 1) were carried out for a recent winter period using 2007 versions of the Rapid Update Cycle assimilation system and forecast model. -
Storm Preparedness Kits –By Sparky Smith HELLO
www.mesonet.org Volume 5 — Issue 7 — July 2014 connection Storm Preparedness Kits –by Sparky Smith HELLO. MY NAME IS SPARKY SMITH, and I am an pieces everywhere, but never the complete thing. I compiled Eagle Scout. First I will talk a little bit about myself. Then I all the lists and added a few things I thought were needed will tell you about how I came up with the idea for my project, in every emergency. The best way to get your project and actually show you how to build your own. I will also talk approved is to make it relatively inexpensive with easy to about the constraints and guidelines that I had to deal with obtain materials, and a personal aspect to show that you while doing the project. actually put thought into it. I have always been interested in weather. I went to the very One of the first things I did was go to a graphics design store first Mesonet Weather Camp, where I learned more about and had a nice looking label made to put on the storm kits, what kind of disasters occur and what other dangers they so people would know it was more than a five gallon bucket. bring. A storm kit has to last at least 1 day because many Thankfully, most of the products were donated, including the other dangers can arise after storms. For instance, you label. I made 20 storm kits, which would have cost about could be trapped in your shelter by debris or even have $3000, but it ended up costing about $1000-$1200. -
Reading Mesonet Rain Maps
Oklahoma’s Weather Network Lesson 2 - Rain Maps Reading Mesonet Rain Maps Estimated Lesson Time: 30 minutes Introduction Every morning when you get ready for school, you decide what you are going to wear for the day. Often you might ask your parents what the weather is like or check the weather yourself before getting dressed. Then you can decide if you will wear a t-shirt or sweater, flip-flops or rain boots. The Oklahoma Mesonet, www.mesonet.org, is a weather and climate network covering the state. The Mesonet collects measurements such as air tempera- ture, rainfall, wind speed, and wind direction, every five minutes . These mea- surements are provided free to the public online. The Mesonet has 120 remote weather stations across the state collecting data. There is at least one in every county which means there is one located near you. Our data is used by people across the state. Farmers use our data to grow their crops, and firefighters use it to help put out a fire. Emergency managers in your town use it to warn you of tornadoes, and sound the town’s sirens. Mesonet rainfall data gives a statewide view, updated every five minutes. When reading the Mesonet rainfall accumulation maps, notice each Mesonet site displays accumulated rainfall. The map also displays the National Weather Service (NWS) River Forecast Center’s rainfall estimates (in color) across Oklahoma based on radar (an instrument that can locate precipitation and its motion). For example, areas in blue have lower rainfall than areas in red or purple. -
Multifunction Phased Array Radar
MULTIFUNCTION PHASED ARRAY RADAR PROGRAM STATUS AND POTENTIAL SERVICE IMPROVEMENTS Prepared by: Working Group for Multifunction Phased Array Radar (WG/MPAR) August 2009 Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM) 8455 Colesville Road, Suite 1500 Silver Spring, MD 20910 Foreword Weather radar has proven its value to the Nation since the installation of the current weather surveillance network began in 1990. In 2020, the WSR-88D radars forming this NEXRAD network will be 23 to 30 years old. In about the same time frame, most of the Nation’s aircraft surveillance radars will be nearing the end of their design life. Decisions on replacing or repairing and upgrading these National radar assets must be made over the next 10 to 15 years. We are now on the threshold of a revolution in civilian radar capability, enabled by the adaptation of established military radar technology to existing civilian applications, plus new capabilities beyond what current systems can provide. The Working Group for Multifunction Phased Array Radar (WG/MPAR) is coordinating an interagency initiative to investigate the feasibility of applying the capabilities of phased array technology to perform weather and aircraft surveillance simultaneously. This paper presents a snapshot of the status of that initiative and projects potential service improvements that would be derived from the operational application of phased array radar to aircraft and weather surveillance. I wish to thank the members of WG/MPAR—especially Dr. James (Jeff) Kimpel, Director of the National Severe Storms Laboratory (NOAA) and Mr. William Benner, Weather Processors Group Manager (FAA)—as well as the OFCM staff, especially Mr. -
The Effect of Climatological Variables on Future UAS-Based Atmospheric Profiling in the Lower Atmosphere
remote sensing Article The Effect of Climatological Variables on Future UAS-Based Atmospheric Profiling in the Lower Atmosphere Ariel M. Jacobs 1,2 , Tyler M. Bell 1,2,3,4 , Brian R. Greene 1,2,5 and Phillip B. Chilson 1,2,5,* 1 School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd, Ste 5900, Norman, OK 73072, USA; [email protected] (A.M.J.); [email protected] (T.M.B.); [email protected] (B.R.G.) 2 Center for Autonomous Sensing and Sampling, University of Oklahoma, 120 David L. Boren Blvd., Ste 4600, Norman, OK 73072, USA 3 Cooperative Institute for Mesoscale Meteorological Studies, 120 David L. Boren Blvd., Ste 2100, Norman, OK 73072, USA 4 NOAA/OAR National Severe Storms Laboratory, 120 David L. Boren Blvd., Norman, OK 73072, USA 5 Advanced Radar Research Center, University of Oklahoma, 3190 Monitor Ave., Norman, OK 73019, USA * Correspondence: [email protected] Received: 7 August 2020; Accepted: 9 September 2020; Published: 11 September 2020 Abstract: Vertical profiles of wind, temperature, and moisture are essential to capture the kinematic and thermodynamic structure of the atmospheric boundary layer (ABL). Our goal is to use weather observing unmanned aircraft systems (WxUAS) to perform the vertical profiles by taking measurements while ascending through the ABL and subsequently descending to the Earth’s surface. Before establishing routine profiles using a network of WxUAS stations, the climatologies of the flight locations must be studied. This was done using data from the North American Regional Reanalysis (NARR) model. To begin, NARR data accuracy was verified against radiosondes. -
Alternative Earth Science Datasets for Identifying Patterns and Events
https://ntrs.nasa.gov/search.jsp?R=20190002267 2020-02-17T17:17:45+00:00Z Alternative Earth Science Datasets For Identifying Patterns and Events Kaylin Bugbee1, Robert Griffin1, Brian Freitag1, Jeffrey Miller1, Rahul Ramachandran2, and Jia Zhang3 (1) University of Alabama in Huntsville (2) NASA MSFC (3) Carnegie Mellon Universityv Earth Observation Big Data • Earth observation data volumes are growing exponentially • NOAA collects about 7 terabytes of data per day1 • Adds to existing 25 PB archive • Upcoming missions will generate another 5 TB per day • NASA’s Earth observation data is expected to grow to 131 TB of data per day by 20222 • NISAR and other large data volume missions3 Over the next five years, the daily ingest of data into the • Other agencies like ESA expect data EOSDIS archive is expected to grow significantly, to more 4 than 131 terabytes (TB) of forward processing. NASA volumes to continue to grow EOSDIS image. • How do we effectively explore and search through these large amounts of data? Alternative Data • Data which are extracted or generated from non-traditional sources • Social media data • Point of sale transactions • Product reviews • Logistics • Idea originates in investment world • Include alternative data sources in investment decision making process • Earth observation data is a growing Image Credit: NASA alternative data source for investing • DMSP and VIIRS nightlight data Alternative Data for Earth Science • Are there alternative data sources in the Earth sciences that can be used in a similar manner? • -
The Center for Analysis and Prediction of Storms
CAPS Mission Statement • The Center for Analysis and Prediction of Storms (CAPS) was established at the University of Oklahoma in 1989 as one of the first 11 National Science Foundation Science and Technology Center. Its mission was, and remains the development of techniques for the computer-based prediction of high-impact local weather, such as individual spring and winter storms, with the NEXRAD (WSR-88D) Doppler radar serving as a key data source. 1 Forecast Funnel • Large Scale - provide synoptic flow patterns and boundary conditions to the Large Scale regional scale flow. • Regional Forecast - provide improved resolution for predicting regional scale Regional Scale events (large thunderstorm complexes, squall lines, heavy precipitation events) • Storm Scale - predict individual thunderstorm and groups of Storm Scale thunderstorms as well as initiation of convection. 2 ARPS System Lateral boundary conditions from large-scale models ARPS Data Assimilation System (ARPSDAS) Gridded first guess Mobile Mesonet Data Acquisition Parameter Retrieval and 4DDA Rawinsondes & Analysis Single-Doppler Velocity • AddACARS adas slide here…... CLASS ARPS Data Analysis Retrieval (SDVR) System (ADAS) SAO 4-D Variational Vel- data Satellite – Ingest Profilers – Quality control Variational ocity Adjustment Incoming – Objective analysis ASOS/AWOS Data & Thermo- – Archival Oklahoma Mesonet Assimilation dynamic Retrieval WSR-88D Wideband Product Generation and DataData SupportSupport SystemSystem ForecastForecast GenerationGeneration ARPSPLT andARPSV IEW