(BOW ECHO and MCV EXPERIMENT) NCAR/ATD -OCTOBER 2002 OFAP MEETING Submitted on 15 June 2002
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Evolution of NOAA's Observing System Integrated Analysis (NOSIA)
Evolution of NOAA’s Observing System Integrated Analysis (NOSIA) Presented to the 13th Symposium on Societal Applications: Policy, Research and Practice (paper 9.1) Louis Cantrell Jr., and D. Helms, R. C. Reining, A. Pratt, B. Priest, and V. Ries 98th Annual Meeting American Meteorological Society Austin, Texas Overview 1 How NOSIA Informs Portfolio Decision Making 2 How NOSIA is Evolving Observing System Portfolio Management 3 System Engineering Measure of Effectiveness Each point on the Efficient Frontier represents an optimum Portfolio of Observing Programs within a Constrained Budget utcomes) O Measure of Effectiveness Measure Effectiveness of (MoE: Cost 4 Capability Improvement Prioritization NOAA Emerging Technologies for Observations Workshop Sponsored by the NOAA Observing Systems Council August 22-23, 2017 - NCWCP Identifying Capability Improvements for the Greatest NOAA -wide Benefit ▪ National Water Level Observation Network ▪ Tropical Atmosphere Ocean Buoy Ocean Profiles ▪ Commercial Fisheries Dependent Data Surveys ▪ ARGO ▪ Integrated Ocean Observing System Regionals ▪ Animal Borne Sensors ▪ National Observer Program (NOP) ▪ Drifting Buoy Network ▪ NEXRAD Precipitation Products ▪ Program-funded Habitat Surveys ▪ Coastal Weather Buoys Atmospheric Surface Observations ▪ Recreational Fish Surveys ▪ Historical Habitat Databases ▪ Chartered Vessels Research ▪ NWS Upper Air Soundings ▪ Coastal-Marine Automated Network ▪ GOES Imagery ▪ NERR_SWMP ▪ Automated Weather Observing System ▪ Global Ocean Observing System Carbon Network -
NCEP Synergy Meeting Highlights: March 27, 2017
NCEP Synergy Meeting Highlights: March 27, 2017 This meeting was led by Mark Klein (WPC) and attended by Steven Earle (NCO); Glenn White (GCWMB); Israel Jirak (SPC); Mike Brennan (NHC) Scott Scallion (MDL); Brian Miretsky (ER); Jack Settelmaier (SR); Andy Edman (WR); John Eise (CR), and Curtis Alexander (ESRL). 1. NOTES FROM NCO (Steven Earle) RTMA/URMA - Implementation delayed until May 2 http://www.nws.noaa.gov/os/notification/scn17-17rtma_urma.htm LMP/GLMP - Implementation scheduled for 3/29 http://www.nws.noaa.gov/os/notification/scn17-22lamp_glmpaaa.htm ECMWF-MOS - Implementation tentatively scheduled for 3/30; Likely to delay at least a week. Internal NWS only NHC Guidance Suite (NHC only) - Scheduled implementation in mid-May http://www.nws.noaa.gov/os/notification/pns17-09chghurche77removal.htm ESTOFS-Atlantic - Feedback due by COB today with implementation April 25 http://www.nws.noaa.gov/os/notification/scn17-34extratropical.htm NWM - 30-day IT stability test scheduled to begin today. Implementation scheduled for early May. SCN to be released soon. GFS - 30-day IT stability test scheduled to begin in May; Implementation scheduled for mid-June. SCN will be released in early May. CMAQ - CONUS only upgrade. Evaluation and IT stability test expected to start at the end of April PETSS/ETSS - NCO began work on the upgrade; Evaluation and IT stability expected to start in early May 2. NOTES FROM EMC 2a. Global Climate and Weather Modeling Branch (GCWMB) (Glenn White): The Office of the Director has approved the implementation of the GFS NEMS. The 30-day IT test is now scheduled for May and implementation is scheduled for mid-June. -
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 -
The Impact of Dropsonde and Extra Radiosonde Observations During NAWDEX in Autumn 2016
FEBRUARY 2020 S C H I N D L E R E T A L . 809 The Impact of Dropsonde and Extra Radiosonde Observations during NAWDEX in Autumn 2016 MATTHIAS SCHINDLER Meteorologisches Institut, Ludwig-Maximilians-Universitat,€ Munich, Germany MARTIN WEISSMANN Hans-Ertel Centre for Weather Research, Deutscher Wetterdienst, Munich, Germany, and Institut fur€ Meteorologie und Geophysik, Universitat€ Wien, Vienna, Austria ANDREAS SCHÄFLER Institut fur€ Physik der Atmosphare,€ Deutsches Zentrum fur€ Luft- und Raumfahrt, Oberpfaffenhofen, Germany GABOR RADNOTI European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom (Manuscript received 2 May 2019, in final form 18 November 2019) ABSTRACT Dropsonde observations from three research aircraft in the North Atlantic region, as well as several hundred additionally launched radiosondes over Canada and Europe, were collected during the international North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) in autumn 2016. In addition, over 1000 dropsondes were deployed during NOAA’s Sensing Hazards with Operational Unmanned Technology (SHOUT) and Reconnaissance missions in the west Atlantic basin, supplementing the conven- tional observing network for several intensive observation periods. This unique dataset was assimilated within the framework of cycled data denial experiments for a 1-month period performed with the global model of the ECMWF. Results show a slightly reduced mean forecast error (1%–3%) over the northern Atlantic and Europe by assimilating these additional observations, with the most prominent error reductions being linked to Tropical Storm Karl, Cyclones Matthew and Nicole, and their subsequent interaction with the midlatitude waveguide. The evaluation of Forecast Sensitivity to Observation Impact (FSOI) indicates that the largest impact is due to dropsondes near tropical storms and cyclones, followed by dropsondes over the northern Atlantic and additional Canadian radiosondes. -
Massively Deployable, Low-Cost Airborne Sensor Motes for Atmospheric Characterization
Wireless Sensor Network, 2020, 12, 1-11 https://www.scirp.org/journal/wsn ISSN Online: 1945-3086 ISSN Print: 1945-3078 Massively Deployable, Low-Cost Airborne Sensor Motes for Atmospheric Characterization Michael Bolt, J. Craig Prather, Tyler Horton, Mark Adams Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA How to cite this paper: Bolt, M., Prather, Abstract J.C., Horton, T. and Adams, M. (2020) Massively Deployable, Low-Cost Airborne A low-cost airborne sensor mote has been designed for deployment en masse Sensor Motes for Atmospheric Characteri- to characterize atmospheric conditions. The designed environmental sensing zation. Wireless Sensor Network, 12, 1-11. mote, or eMote, was inspired by the natural shape of auto-rotating maple https://doi.org/10.4236/wsn.2020.121001 seeds to fall slowly and gather data along its descent. The eMotes measure Received: January 2, 2020 and transmit temperature, air pressure, relative humidity, and wind speed es- Accepted: January 28, 2020 timates alongside GPS coordinates and timestamps. Up to 2080 eMotes can Published: January 31, 2020 be deployed simultaneously with a 1 Hz sampling rate, but the system capac- Copyright © 2020 by author(s) and ity increases by 2600 eMotes for every second added between samples. All Scientific Research Publishing Inc. measured and reported data falls within accuracy requirements for reporting This work is licensed under the Creative with both the World Meteorological Organization (WMO) and the National Commons Attribution International Oceanic and Atmospheric Administration (NOAA). This paper presents the License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ design and validation of the eMote system alongside discussions on the imple- Open Access mentation of a large-scale, low-cost sensor network. -
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. -
Weatherscope Weatherscope Application Information: Weatherscope Is a Stand-Alone Application That Makes Viewing Weather Data Easier
User Guide - Macintosh http://earthstorm.ocs.ou.edu WeatherScope WeatherScope Application Information: WeatherScope is a stand-alone application that makes viewing weather data easier. To run WeatherScope, Mac OS X version 10.3.7, a minimum of 512MB of RAM, and an accelerated graphics card with 32MB of VRAM are required. WeatherScope is distributed freely for noncommercial and educational use and can be used on both Apple Macintosh and Windows operating systems. How do I Download WeatherScope? To download the application, go to http://earthstorm.ocs.ou.edu, select Data, Software, Download, or go to http://www. ocs.ou.edu/software. There will be three options: WeatherBuddy, WeatherScope, and WxScope Plugin. You will want to choose WeatherScope. There are two options under the application: Macintosh or Windows. Choose Macintosh to download the application. The installation wizard will automatically save to your desktop. Go to your desktop and double click on the icon that says WeatherScope- x.x.x.pkg. Several dialog messages will appear. The fi rst message will inform you that you are about to install the application. The next message tells you about computer system requirements in order to download the application. The following message is the Software License Agreement. It is strongly suggested that you read this agreement. If you agree, click Agree. If you do not agree, click Disagree and the software will not be installed onto your computer. The next message asks you to select a destination drive (usually your hard drive). The setup will run and install the software on your computer. You may then press Close. -
Driftsondes Providing in Situ Long-Duration Dropsonde Observations Over Remote Regions
DRIFTSONDES Providing In Situ Long-Duration Dropsonde Observations over Remote Regions BY STEPHEN A. COHN, TERRY HOCK, PHILIPPE COCQUEREZ, JUNHONG WANG, FLORENCE RABIER, DAVID PARSONS, PATRICK HARR, CHUN-CHIEH WU, PHILIPPE DROBINSKI, FATIMA KARBOU, STÉPHANIE VÉNEL, ANDRÉ VARGas, NadIA FOURRIÉ, NATHALIE SAINT-RAMOND, VINCENT GUIdaRD, ALEXIS DOERENBECHER, HUANG-HSIUNG HSU, PO-HSIUNG LIN, MING-DAH CHOU, JEAN-LUC REDELSPERGER, CHARLIE MARTIN, JacK FOX, NICK POTTS, KATHRYN YOUNG, AND HAL COLE A field-tested, balloon-borne dropsonde platform fills an important gap in in-situ research measurement capabilities by delivering high-resolution, MIST dropsondes to remote locations from heights unobtainable by research aircraft. igh-quality in situ measure- ments from radiosondes and H dropsondes are the gold stan- dard for vertical profiles of funda- mental atmospheric measurements such as wind, temperature (T), and relative humidity (RH). Satellite- borne remote sensors provide much- needed global, long-term coverage; however, they do not match the ability of sondes to capture sharp transitions and fine vertical struc- ture, and have significant perfor- mance limitations (e.g., the inability of infrared sounders to penetrate clouds, poor accuracy in the bound- ary layer). Sondes are also a trusted FIG. 1. The driftsonde system concept. means to calibrate and validate remote sensors. However, it is challenging to launch understanding the development of tropical cyclones radiosondes from remote locations such as the ocean to validating satellite retrievals in Antarctica. surface or the interior of Antarctica. Aircraft release The driftsonde is a unique balloonborne in- dropsondes above such locations but are limited by strument that releases dropsondes to provide the range and endurance of the aircraft. -
Global Hawk Dropsonde Observations of the Arctic Atmosphere Obtained During the Winter Storms and Pacific Atmospheric Rivers (WISPAR) field Campaign
Atmos. Meas. Tech., 7, 3917–3926, 2014 www.atmos-meas-tech.net/7/3917/2014/ doi:10.5194/amt-7-3917-2014 © Author(s) 2014. CC Attribution 3.0 License. Global Hawk dropsonde observations of the Arctic atmosphere obtained during the Winter Storms and Pacific Atmospheric Rivers (WISPAR) field campaign J. M. Intrieri1, G. de Boer1,2, M. D. Shupe1,2, J. R. Spackman1,3, J. Wang4,6, P. J. Neiman1, G. A. Wick1, T. F. Hock4, and R. E. Hood5 1NOAA, Earth System Research Laboratory, 325 Broadway, Boulder, CO 80305, USA 2Cooperative Institute for Research in the Environmental Sciences, University of Colorado at Boulder, Box 216 UCB, Boulder, CO 80309, USA 3Science and Technology Corporation, Boulder, CO 80305, USA 4National Center for Atmospheric Research, 1850 Table Mesa Dr., Boulder, CO 80305, USA 5NOAA, Unmanned Aircraft Systems Program, 1200 East West Highway, Silver Spring, MD 20910, USA 6University at Albany, SUNY, Department of Atmospheric & Environmental Sciences, Albany, NY 12222, USA Correspondence to: J. M. Intrieri ([email protected]) Received: 20 February 2014 – Published in Atmos. Meas. Tech. Discuss.: 23 April 2014 Revised: 15 September 2014 – Accepted: 20 October 2014 – Published: 25 November 2014 Abstract. In February and March of 2011, the Global Hawk Comparison of dropsonde observations with atmospheric re- unmanned aircraft system (UAS) was deployed over the Pa- analyses reveal that, for this day, large-scale structures such cific Ocean and the Arctic during the Winter Storms and as the polar vortex and air masses are captured by the re- Pacific Atmospheric Rivers (WISPAR) field campaign. The analyses, while smaller-scale features, including low-level WISPAR science missions were designed to (1) improve our jets and inversion depths, are mischaracterized. -
Singapore Changi Airport Dropsonde for Weather
41621Y_Vaisala156 6.4.2001 10:05 Sivu 1 156/2001156/2001 Extensive AWOS System: Singapore Changi Airport 2000 NWS Isaac Cline Meteorology Award: Dropsonde for Weather Reconnaissance Short-Term Weather Predictions in Urban Zones: Urban Forecast Issues and Challenges The 81st AMS Annual Meeting: Precipitation Extremes and Climate Variability 41621Y_Vaisala156 6.4.2001 10:05 Sivu 2 Contents President’s Column 3 Vaisala’s high-quality customer Upper Air Obsevations support aims to offer complete solutions for customers’ AUTOSONDE Service and Maintenance measurement needs. Vaisala Contract for Germany 4 and DWD (the German Dropsonde for Weather Reconnaissance in the USA 6 Meteorological Institute) have signed an AUTOSONDE Service Ballistic Meteo System for the Dutch Army 10 and Maintenance Contract. The service benefits are short GPS Radiosonde Trial at Camborne, UK 12 turnaround times, high data Challenge of Space at CNES 14 availability and extensive service options. Surface Weather Observations World Natural Heritage Site in Japan 16 The First MAWS Shipped to France for CNES 18 Finland’s oldest and most Aviation Weather experienced helicopter operator Copterline Oy started scheduled The Extesive AWOS System to route traffic between Helsinki Singapore Changi Airport 18 and Tallinn in May 2000. Accurate weather data for safe The New Athens International Airport 23 journeys and landings is Fast Helicopter Transportation Linking Two Capitals 24 provided by a Vaisala Aviation Weather Reporter AW11 system, European Gliding Champs 26 serving at both ends of the route. Winter Maintenance on Roads Sound Basis for Road Condition Monitoring in Italy 28 Fog Monitoring Along the River Seine 30 The French Air and Space Academy has awarded its year Additional Features 2000 “Grand Prix” to the SAFIR system development teams of Urban Forecast Issues and Challenges 30 Vaisala and ONERA (the The 81st AMS Annual Meeting: French National Aerospace Precipitation Extremes and Climate Variability 38 Research Agency). -
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. -
Technical Characteristics and Performance Criteria for Systems in the Meteorological Aids Service in the 403 Mhz and 1 680 Mhz Bands
Recommendation ITU-R RS.1165-3 (12/2018) Technical characteristics and performance criteria for systems in the meteorological aids service in the 403 MHz and 1 680 MHz bands RS Series Remote sensing systems ii Rec. ITU-R RS.1165-3 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Annex 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http://www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also available online at http://www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1.