Impact-Based Forecasting Guide
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The Weather Company History on Demand
Solution Brief The Weather Company History on Demand Learn from the past’s data to prepare for the future’s business demands Highlights Anecdotes are great for telling stories, but they lose credibility when your near real-time business decisions depend on – Precision them for actionable data. History on Demand (HoD), from The – Accuracy Weather Company, an IBM Business, provides the historical – Speed of scale context we believe you need to extrapolate relationships and – Competetive pricing make correlations with your past business and operational – 35km grid results to help you predict future business needs and – 5+ years historical data outcomes. HoD offers competitively priced and accurate historical weather information, featuring a 35 km worldwide grid and hourly historical information dating back to July 2011. Make global decisions locally HoD provides a worldwide, consistent dataset of the most important and commonly used weather parameters accessible via web API. You can obtain large historical datasets specific to your geography and time without having to rummage through unorganized public datasets. Couple the historical data with your analysis and our forecast products, and you’ll have the tools to help you manage and minimize significant weather impacts on your business and better plan for them in the future. Convenient access in one package HoD offers a comprehensive dataset spanning July 2011 to the present, and new data is regularly added as it becomes available. HoD contains hourly values for surface temperature, wind speed, wind direction, relative humidity, atmospheric pressure, dewpoint and precipitation rate. Access can be gained by latitude/longitude and is supported for a list of latitudinal/longitudinal points, as well as a bounding box specification. -
Worldwide Marine Radiofacsimile Broadcast Schedules
WORLDWIDE MARINE RADIOFACSIMILE BROADCAST SCHEDULES U.S. DEPARTMENT OF COMMERCE NATIONAL OCEANIC and ATMOSPHERIC ADMINISTRATION NATIONAL WEATHER SERVICE January 14, 2021 INTRODUCTION Ships....The U.S. Voluntary Observing Ship (VOS) program needs your help! If your ship is not participating in this worthwhile international program, we urge you to join. Remember, the meteorological agencies that do the weather forecasting cannot help you without input from you. ONLY YOU KNOW THE WEATHER AT YOUR POSITION!! Please report the weather at 0000, 0600, 1200, and 1800 UTC as explained in the National Weather Service Observing Handbook No. 1 for Marine Surface Weather Observations. Within 300 nm of a named hurricane, typhoon or tropical storm, or within 200 nm of U.S. or Canadian waters, also report the weather at 0300, 0900, 1500, and 2100 UTC. Your participation is greatly appreciated by all mariners. For assistance, contact a Port Meteorological Officer (PMO), who will come aboard your vessel and provide all the information you need to observe, code and transmit weather observations. This publication is made available via the Internet at: https://weather.gov/marine/media/rfax.pdf The following webpage contains information on the dissemination of U.S. National Weather Service marine products including radiofax, such as frequency and scheduling information as well as links to products. A listing of other recommended webpages may be found in the Appendix. https://weather.gov/marine This PDF file contains links to http pages and FTPMAIL commands. The links may not be compatible with all PDF readers and e-mail systems. The Internet is not part of the National Weather Service's operational data stream and should never be relied upon as a means to obtain the latest forecast and warning data. -
Spark and DB2 -- a Perfect Couple
Spark and DB2 -- A perfect couple Pallavi Priyadarshini [email protected] Senior Technical Staff Member Spark Technology Center, IBM Session # E11 | Wed, May 25 (1 PM – 2 PM) | Platform: Cross platform Agenda Objective 1: Spark fundamentals relevant to database integration Objective 2: Integration between Spark and IBM data servers through DataFrame API Objective 3: Loading DB2 data into Spark and writing Spark data into DB2 Objective 4: Spark Use Cases Demo Power of data. Simplicity of design. Speed of innovation. Background What is Spark An Apache Foundation open source project. Not a product. An in-memory compute engine that works with data. Not a data store. Enables highly iterative analysis on large volumes of data at scale Unified environment for data scientists, developers and data engineers Radically simplifies process of developing intelligent apps fueled by data. History of Spark . 2002 – MapReduce @ Google . 2004 – MapReduce paper . 2006 – Hadoop @ Yahoo . 2008 – Hadoop Summit . 2010 – Spark paper . 2014 – Apache Spark top-level . 2014 – 1.2.0 release in December Activity for 6 months in 2014 . 2015 – 1.3.0 release in March (from Matei Zaharia – 2014 Spark Summit . 2015 – 1.5 released in Sep ) . 2016 – 1.6 released in Jan . Spark is HOT!!! . Most active project in Hadoop ecosystem . One of top 3 most active Apache projects . Databricks founded by the creators of Spark from UC Berkeley’s AMPLab Why Spark? Spark is open, accelerating community innovation Spark is fast —100x faster than Hadoop MapReduce Spark is about all data for large-scale data processing Spark supports agile data science to iterate rapidly Spark can be integrated with IBM solutions Our partner ecosystem IBM announces major commitment™ - to advance Apache® Spark The Analytics Operating System …the most significant open source project of the next decade. -
NOTICE: This Publication Is Available At
Department of Commerce • National Oceanic & Atmospheric Administration • National Weather Service NATIONAL WEATHER SERVICE INSTRUCTION 10-807 OCTOBER 5, 2017 Operations and Services Aviation Weather Services, NWSPD 10-8 INTERNATIONAL SERVICE AGREEMENTS NOTICE: This publication is available at: http://www.nws.noaa.gov/directives/. OPR: W/AFS24 (M. Graf) Certified by: W/AFS24 (W. Bauman) Type of Issuance: Routine SUMMARY OF REVISIONS: This directive supersedes NWSI 10-807, “International Service Agreements,” dated May 19, 2009. Changes were made to reflect the NWS Headquarters reorganization effective on April 1, 2015. No content changes were made. Signed 9/21/2017 Andrew D. Stern Date Director Analyze, Forecast, and Support Office NWSI 10-807 OCTOBER 5, 2017 International Service Agreements Table of Contents Page 1. Purpose. ..................................................................................................................................... 2 2. Background. ............................................................................................................................... 2 3. Definition of Unique Terms. ................................................................................................................ 3 4. General ............................................................................................................................................ 3 5. Correspondence with Foreign Meteorological Services. ................................................................. 4 6. Services Provided. -
Dealing with Inconsistent Weather Warnings: Effects on Warning Quality and Intended Actions
Research Collection Journal Article Dealing with inconsistent weather warnings: effects on warning quality and intended actions Author(s): Weyrich, Philippe; Scolobig, Anna; Patt, Anthony Publication Date: 2019-10 Permanent Link: https://doi.org/10.3929/ethz-b-000291292 Originally published in: Meteorological Applications 26(4), http://doi.org/10.1002/met.1785 Rights / License: Creative Commons Attribution 4.0 International This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Received: 11 July 2018 Revised: 12 December 2018 Accepted: 31 January 2019 Published on: 28 March 2019 DOI: 10.1002/met.1785 RESEARCH ARTICLE Dealing with inconsistent weather warnings: effects on warning quality and intended actions Philippe Weyrich | Anna Scolobig | Anthony Patt Climate Policy Group, Department of Environmental Systems Science, Swiss Federal In the past four decades, the private weather forecast sector has been developing Institute of Technology (ETH Zurich), Zurich, next to National Meteorological and Hydrological Services, resulting in additional Switzerland weather providers. This plurality has led to a critical duplication of public weather Correspondence warnings. For a specific event, different providers disseminate warnings that are Philippe Weyrich, Climate Policy Group, Department of Environmental Systems Science, more or less severe, or that are visualized differently, leading to inconsistent infor- Swiss Federal Institute of Technology (ETH mation that could impact perceived warning quality and response. So far, past Zurich), 8092 Zurich, Switzerland. research has not studied the influence of inconsistent information from multiple Email: [email protected] providers. This knowledge gap is addressed here. -
List of Participants
WMO Sypmposium on Impact Based Forecasting and Warning Services Met Office, United Kingdom 2-4 December 2019 LIST OF PARTICIPANTS Name Organisation 1 Abdoulaye Diakhete National Agency of Civil Aviation and Meteorology 2 Angelia Guy National Meteorological Service of Belize 3 Brian Golding Met Office Science Fellow - WMO HIWeather WCRP Impact based Forecast Team, Korea Meteorological 4 Byungwoo Jung Administration 5 Carolina Gisele Cerrudo National Meteorological Service Argentina 6 Caroline Zastiral British Red Cross 7 Catalina Jaime Red Cross Climate Centre Directorate for Space, Security and Migration Chiara Proietti 8 Disaster Risk Management Unit 9 Chris Tubbs Met Office, UK 10 Christophe Isson Météo France 11 Christopher John Noble Met Service, New Zealand 12 Dan Beardsley National Weather Service NOAA/National Weather Service, International Affairs Office 13 Daniel Muller 14 David Rogers World Bank GFDRR 15 Dr. Frederiek Sperna Weiland Deltares 16 Dr. Xu Tang Weather & Disaster Risk Reduction Service, WMO National center for hydro-meteorological forecasting, Viet Nam 17 Du Duc Tien 18 Elizabeth May Webster South African Weather Service 19 Elizabeth Page UCAR/COMET 20 Elliot Jacks NOAA 21 Gerald Fleming Public Weather Service Delivery for WMO 22 Germund Haugen Met No 23 Haleh Kootval World Bank Group 24 Helen Bye Met Office, UK 25 Helene Correa Météo-France Impact based Forecast Team, Korea Meteorological 26 Hyo Jin Han Administration Impact based Forecast Team, Korea Meteorological 27 Inhwa Ham Administration Meteorological Service -
HURRICANE TEDDY (AL202020) 12–23 September 2020
r d NATIONAL HURRICANE CENTER TROPICAL CYCLONE REPORT HURRICANE TEDDY (AL202020) 12–23 September 2020 Eric S. Blake National Hurricane Center 28 April 2021 NASA TERRA MODIS VISIBLE SATELLITE IMAGE OF HURRICANE TEDDY AT 1520 UTC 22 SEPTEMBER 2020. Teddy was a classic, long-lived Cape Verde category 4 hurricane on the Saffir- Simpson Hurricane Wind Scale. It passed northeast of the Leeward Islands and became extremely large over the central Atlantic, eventually making landfall in Nova Scotia as a 55-kt extratropical cyclone. There were 3 direct deaths in the United States due to rip currents. Hurricane Teddy 2 Hurricane Teddy 12–23 SEPTEMBER 2020 SYNOPTIC HISTORY Teddy originated from a strong tropical wave that moved off the west coast of Africa on 10 September, accompanied by a large area of deep convection. The wave was experiencing moderate northeasterly shear, but a broad area of low pressure and banding features still formed on 11 September a few hundred n mi southwest of the Cabo Verde Islands. Convection decreased late that day, as typically happens in the evening diurnal minimum period, but increased early on 12 September. This convection led to the development of a well-defined surface center, confirmed by scatterometer data, and the formation of a tropical depression near 0600 UTC 12 September about 500 n mi southwest of the Cabo Verde Islands. The “best track” chart of the tropical cyclone’s path is given in Fig. 1, with the wind and pressure histories shown in Figs. 2 and 3, respectively. The best track positions and intensities are listed in Table 1.1 After the depression formed, further development was slow during the next couple of days due to a combination of northeasterly shear, dry air in the mid-levels and the large size and radius of maximum winds of the system. -
Papua New Guinea Meteorological Service Country Report
PAPUA NEW GUINEA METEOROLOGICAL SERVICE COUNTRY REPORT Reporting on National Priority Actions of the Pacific Islands Meteorological Strategy (PIMS) 2012-2021 This Report is presented to the Fourth Pacific Meteorological Council (PMC-4) Meeting held in Honiara from 14-18 August 2017 SAMUEL MAIHA [email protected] Table of Contents 1.0 Summary .................................................................................................................................................................................................................. 3 2.0 Background Information .......................................................................................................................................................................................... 5 2.1 Institutional Setup ................................................................................................................................................................................................ 5 [This subsection will cover an UPDATE of the brief on the institutional arrangement of the NMHS as well as its linkages to the Ministry. Make mention of the legislation or any Acts to support the NMS.] .................................................................................................................................... 5 2.2 Staffing ................................................................................................................................................................................................................. 8 -
Objective Mixed and Manually Controlled Data Base OMG
EMS Annual Meeting Abstracts, 9th UROPEAN EMS Annual Meeting 9TH E ON Vol. 6, EMS2009-115, 2009 CONFERENCE Applications of Meteorology 9th EMS / 9th ECAM High resolution meteorology © Author(s) 2009 - applications and services Objective Mixed and Manually Controlled Data Base OMG T. Kratzsch and Dr. M. Rohn German National Weather Service, Deutscher Wetterdienst (DWD), Offenbach, Germany ([email protected], 069-8062 2254 Many customers of Deutscher Wetterdienst get forecast products (different deterministic meteorological pa- rameters) as so-called Point-Time-Prognoses (PTPs). There’s the need for data of high resolution in space (several kilometers, cities) and time (hourly up to forecast-day 7, updated each hour). Those interpretations of the numerical models have been designed by different methods, called DMO, Model Output Statistics (MOS), Kalman filtering. Because of different model results and different methods there are between five and ten different PTPs for the same location. While a forecaster, based on his experience, can choose between that different interpretations, an automatic customers supply can’t do so. Because updates of those interpretations are only available for each new model run, there’s also the need for more actual forecast data, using nowcasting methods as well as controlling and modifying mechanisms for the forecasters. A process “Objective Optimization” has been implemented which automatically combines the available PTP data, nowcasting products and observations at all required locations. A frequent update of this optimization process every 30 minutes ensures that the OOG is based on the latest available model, nowcasting, and observational information. The resulting so-called “Objectively Optimized Guidance” (OOG) passes an interactive quality control step to produce a “Man Modified output” (MMO). -
Ogeorgia's Economy
GEORGIA’S CREA TIVE OECONOMY Creative Industries GEORGIA’S 1 Establishments: 11,426 Jobs: 116,5771 Wages: $8.4 billion1 Self-Employed: 58,9592 Earnings: $1.6 billion2 CREA Revenue: $29 billion3 Economic Impact: $48 billion4 Sources: 1EMSI 2013 2Nonemployer Statistics 2012, TIVE 3Creative Industries in the South 2012 4ACPSA Issue Brief #5: ECONOMY The Impact of New Demand for Arts and Culture Film and Television Combined Productions: 158 Direct Spend of Productions: $1.4 billion Direct Jobs: 23,500 Direct and Indirect Jobs: 77,900 Direct and Indirect Wages: $3.8 billion Economic Impact: $5.1 billion Source: Georgia Entertainment Industry Profile FY14 2 Music Direct and Indirect Jobs: 26,2211 Direct and Indirect Wages: $1.1 billion1 Total Revenues to State and Local Governments: $314 million2 1 Economic Impact: $3.6 billion Source: 1Estimated Economic Impact of the Music Industry on Georgia’s Metropolitan Areas and the State, 2014 2Source: Economic and Fiscal Impact Analysis of the Music Industry in Georgia, 2011 Digital Entertainment Direct Jobs: 1,824 Direct and Indirect Jobs: 8,719 Wages: $528 million Revenue: $758 million State Tax Revenue: $49 million Exports: $47 million Economic Impact: $1.9 billion Source: Georgia’s Digital Entertainment Industry, 2012 3 Arts & Culture Organizations: 2,3911 Jobs: 24,2282 Wages: $478 million2 Revenue: $1.1 billion3 Assets: $2.5 billion4 Economic Impact: $1.8 billion5 Source: 1National Center for Charitable Statistics, 2013 2Economic Census, 2007 and Nonemployer Statistics, 2012 3National Center for Charitable Statistics, 2013 and Nonemployer Statistics, 2012 4National Center for Charitable Statistics, 2013 5ACPSA Issue Brief #5: The Impact of New Demand for Arts and Culture 4 GEORGIA COUNCIL FOR THE ARTS A division of the Georgia Department of Economic Development, Georgia Council for the Arts (GCA) empowers the arts industry in Georgia and artists around the state to cultivate healthy, vibrant communities that are rich in civic participation, cultural experiences, and economic prosperity. -
Service Assessment Hurricane Irene, August
Service Assessment Hurricane Irene, August 21–30, 2011 U.S. DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration National Weather Service Silver Spring, Maryland Cover Photographs: Top Left - NOAA GOES 13 visible image of Hurricane Irene taken at 12:32 UTC (8:32 a.m. EDT) on August 27, 2011, as it was moving northward along the east coast. Map of total storm rainfall for Hurricane Irene (NCEP/HPC) overlaid with photos of Hurricane Irene’s impacts. Clockwise from top right: • Damage to bridge over the Pemigewasset River/East Branch in Lincoln, NH (NH DOT) • Trees across road and utility lines in Guilford, CT (CT DEP) • Damage to homes from storm surge at Cosey Beach, East Haven, CT (CT DEP) • Flooding of Delaware River closes Rt. 29 in Trenton, NJ (State of New Jersey, Office of the Governor) • Damage from storm surge on North Carolina’s Outer Banks (USGS) • Damage to home from an EF1 tornado in Lewes, DE (Sussex County, DE EOC) • River flooding on Schoharie Creek near Lexington, NY (USGS) • Flood damage to historic covered bridge and road in Quechee, VT (FEMA) ii Service Assessment Hurricane Irene, August 21–30, 2011 September 2012 National Oceanic and Atmospheric Administration Dr. Jane Lubchenco, Administrator National Weather Service Laura Furgione, Acting Assistant Administrator for Weather Services iii Preface On August 21-29, 2011, Hurricane Irene left a devastating imprint on the Caribbean and U.S. East Coast. The storm took the lives of more than 40 people, caused an estimated $6.5 billion in damages, unleashed major flooding, downed trees and power lines, and forced road closures, evacuations, and major rescue efforts. -
IBM Services ISMS / PIMS Products / Pids in Scope
1H 2021 Certified Product List IBM services ISMS/PIMS Product/Service Offerings/PIDs in scope The following is a list of products associated with the offering bundles in scope of the IBM services information security management system (ISMS). The Cloud services ISMS has been certified on: ISO/IEC 27001:2013 ISO/IEC 27017:2015 ISO/IEC 27018:2019 ISO/IEC 27701:2019 As well as the IBM Cloud Services STAR Self-Assessment found here: This listing is current as of 07/20/2021 IBM Cloud Services STAR Self-Assessment Cloud Controls Matrix v3.0.1 https://cloudsecurityalliance.org/registry/ibm-cloud/ To find out more about IBM Cloud compliance go to: https://www.ibm.com/cloud/compliance/global type groupNameproductName pids ISO Group AccessHub-at-IBM Offering AccessHub-at-IBM N/A ISO Group AI Applications - Maximo and TRIRIGA Offering IBM Enterprise Asset Management Anywhere on Cloud (Maximo) 5725-Z55 Offering IBM Enterprise Asset Management Anywhere on Cloud (Maximo) Add-On 5725-Z55 Offering IBM Enterprise Asset Management on Cloud (Maximo) Asset Configuration Manager Add-On 5725-P73 Offering IBM Enterprise Asset Management on Cloud (Maximo) Aviation Add-On 5725-P73 Offering IBM Enterprise Asset Management on Cloud (Maximo) Calibration Add-On 5725-P73 Offering IBM Enterprise Asset Management on Cloud (Maximo) for Managed Service Provider Add-On 5725-P73 Offering IBM Enterprise Asset Management on Cloud (Maximo) Health, Safety and Environment Manager Add-On 5725-P73 Offering IBM Enterprise Asset Management on Cloud (Maximo) Life Sciences Add-On