This publication provides guidance on homogenization of instrumental land station data. For beginners, the publication describes prerequisites for homogenization (including data rescue, quality control, metadata, parallel measurements etc), explains homogenization practices in detail and provides an overview of homogenization software packages. For advanced users, the history and mathematical theory of homogenization is introduced.Published by: OMM ; 2020 (Edition 2020)
This publication provides guidance on homogenization of instrumental land station data. For beginners, the publication describes prerequisites for homogenization (including data rescue, quality control, metadata, parallel measurements etc), explains homogenization practices in detail and provides an overview of homogenization software packages. For advanced users, the history and mathematical theory of homogenization is introduced.
Collection(s) and Series: OMM- No. 1245
Language(s): French; Other Languages: English
Format: Digital (Free)
ISBN (or other code): 978-92-63-21245-0This publication provides guidance on homogenization of instrumental land station data. For beginners, the publication describes prerequisites for homogenization (including data rescue, quality control, metadata, parallel measurements etc), explains homogenization practices in detail and provides an overview of homogenization software packages. For advanced users, the history and mathematical theory of homogenization is introduced.Published by: WMO ; 2020 (2020 edition)
Collection(s) and Series: WMO- No. 1245
Language(s): English; Other Languages: French
Format: Digital (Free)
ISBN (or other code): 978-92-63-11245-3Published by: WMO ; 2020 (2020 edition)
Collection(s) and Series: WMO- No. 1246
Format: Digital (Free)
ISBN (or other code): 978-92-63-11246-9Наставление предназначается для следующих целей: a) способствовать сотрудничеству в отношении обработки данных и прогнозирования между странами-членами; b) определить обязанности стран-членов по осуществлению Глобальной системы обработки данных и прогнозирования (ГСОДП) Всемирной службы погоды (ВСП); c) обеспечивать единообразие и стандартизацию практики и процедур при выполнении пунктов (a) и (b) выше.Published by: BMO ; 2019 (Издание 2019 г.)
Наставление по Глобальной системе обработки данных и прогнозирования: Дополнение IV к Техническому регламенту ВМО
Наставление предназначается для следующих целей: a) способствовать сотрудничеству в отношении обработки данных и прогнозирования между странами-членами; b) определить обязанности стран-членов по осуществлению Глобальной системы обработки данных и прогнозирования (ГСОДП) Всемирной службы погоды (ВСП); c) обеспечивать единообразие и стандартизацию практики и процедур при выполнении пунктов (a) и (b) выше.
Collection(s) and Series: BMO- No. 485
Language(s): Russian; Other Languages: English, French, Spanish
Format: Digital (Free)
ISBN (or other code): 978-92-63-40485-5
Archives access: 1992-[...]
Tags: Capacity development ; National Meteorological and Hydrological Service (NMHS) ; Weather forecasting ; Information management ; Manual ; Global Data-processing and Forecasting System (GDPFS) Add tagGCRF African-SWIFT is a programme of research and capability building, led by the National Centre for Atmospheric Science (NCAS), and funded by UK Research and Innovation Global Challenges Research Fund. The project aims to deliver a step change in African weather forecasting capability from hourly to seasonal timescales, and build research capability to continue forecasting improvements in Africa for the foreseeable future.
The GCRF African-SWIFT team works with forecast users across sectors from aviation to agriculture, energy, water and emergency response to understand how to ...Published by: University of Leeds ; 2019
GCRF African-SWIFT is a programme of research and capability building, led by the National Centre for Atmospheric Science (NCAS), and funded by UK Research and Innovation Global Challenges Research Fund. The project aims to deliver a step change in African weather forecasting capability from hourly to seasonal timescales, and build research capability to continue forecasting improvements in Africa for the foreseeable future.
The GCRF African-SWIFT team works with forecast users across sectors from aviation to agriculture, energy, water and emergency response to understand how to tailor the provision and delivery of weather forecasts and to ensure improved response to high-impact events (e.g. onset of rains, heat-waves, dry spells, strong winds); rapid emergency response to extreme events, such as urban flooding and prolonged droughts; and increased resilience, through integration of weather prediction into strategies for response to climate change.
Notes: Primary Author: GCRF African SWIFT
Publisher: University of Leeds
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Format: Digital (Free) (Variable)
Tags: Weather forecasting ; Numerical weather prediction ; Climate services ; Text/ Reading ; Competencies for Provision of Climate Services ; NWP Skills and Knowledge for Operational Meteorologists ; PWS - Personnel Engaged in Operational Forecasting ; PWS - Weather Broadcasters and Communicators ; Satellite Skills and Knowledge for Operational Meteorologists ; PWS - Competency Requirements for Persons Engaged in the Development and Delivery of Products and Services to Meet User Requirements ; Basic Instructional Package for Meteorologists Add tagGCRF African-SWIFT is a programme of research and capability building, led by the National Centre for Atmospheric Science (NCAS), and funded by UK Research and Innovation Global Challenges Research Fund. The project aims to deliver a step change in African weather forecasting capability from hourly to seasonal timescales, and build research capability to continue forecasting improvements in Africa for the foreseeable future.
The GCRF African-SWIFT team works with forecast users across sectors from aviation to agriculture, energy, water and emergency response to understand how to ...PermalinkWorld Meteorological Organization (WMO) ; United Nations Educational, Scientific and Cultural Organization (UNESCO); Intergovernmental Oceanographic Commission (IOC); et al. - WMO, 2019PermalinkThis lesson was developed by meteorologist, Dr. Mick Pope, with sponsorship from the Australian Bureau of Meteorology (BoM). The lesson is a somewhat broad-brush review of the overall forecast process, but with specific application of the forecast funnel approach as used by Australia's Bureau of Meteorology (BoM). The forecast process components include decision support and communication, use of numerical weather prediction, and applying the forecast funnel approach. The forecast funnel is described in detail, along with the forecaster time pyramid, and it is applied using a BoM forecast polic ...PermalinkPermalinkThe Community Earth System Model (CESM) is a fully-coupled, community, global climate model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The CESM Distance Learning Course is based on the CESM Tutorial held annually at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado. This course consists of 12 lectures and 4 practical sessions on simulating the climate system and practical sessions on running Community Earth System Model (CESM), modifying components, and analyzing data. The course is targeted at the graduat ...PermalinkIn this lesson, forecasters will practice using guidance from different convection-allowing models (CAMs) over the short term. As they review and analyze the model guidance they will encounter some of the advantages and limitations of using CAMs for winter weather.PermalinkThis 45-minute lesson provides an overview of the satellite-derived products generated by the Satellite Application Facility on Land Surface Analysis (LSA-SAF) that may provide beneficial information to the agriculture community. Learners will practice reading and interpreting the LSA-SAF products to better understand the characteristics of vegetation. The lesson also discusses the application of satellite-derived products in regression analysis to model agricultural production, and uses a wine production case in the Portuguese Douro Valley to show learners how seasonal crop productions may be ...PermalinkThe current GOES-R and JPSS meteorological satellites have improved capabilities for enhanced fire detection that include more effective monitoring of fire starts, evolution, and smoke. This lesson provides forecasters and others with the opportunity to become more familiar with both GOES-R and JPSS satellite products (including the longwave-shortwave IR difference, Fire Temperature RGB, GeoColor, GOES-R Fire Mask, JPSS Active Fire, and others) during the onset of a large grassland fire event, known as the Rhea Fire, that affected western Oklahoma from April 12-18, 2018. Interactions and quest ...PermalinkThe latest-generation Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-7/COSMIC-2) provides high-resolution observations of Earth's atmosphere, including the ionosphere. In this video, scientists and mission planners introduce the instrumentation used and describe the collaborations that made the COSMIC-2 mission possible. These experts describe how COSMIC uses a technique called radio occultation—making use of existing navigation satellite signals passing through the atmosphere to provide detailed measurements of temperature, pressure, and water vapor. They ex ...PermalinkWant to know about COSMIC, and how satellite signals can provide information about Earth's atmosphere? This video provides anyone interested in the topic with a brief overview of the Constellation Observing System for Meteorology, Ionosphere, and Climate, called COSMIC. Targeted to students and teachers in Grades 5-9 but accessible to anyone, the video introduces the latest COSMIC mission (COSMIC-2), which uses satellites orbiting near Earth to measure how the atmosphere affects signals from global positioning system (GPS) satellites high above the surface. This technique is called radio occul ...PermalinkThe U.S. National Weather Service (NWS) National Blend of Models (NBM) is scheduled to be upgraded to version 3.2 in November 2019. It includes the first probabilistic blended guidance for temperature, precipitation, snow, and ice. There are more blended forecast products for aviation, marine, water resources, fire weather, winter weather, and tropical weather. Version 3.2 uses more model components to improve guidance, and introduces a new Guam domain. For a transcript, see What’s New in NBM v3.2. (https://www.meted.ucar.edu/nwp/blend_v32_video/NBM_v32_script.pdf)PermalinkNWP is one of the most important forecasting tools in our toolbox. Yet identifying when/where it isn’t capturing reality is difficult. In the short-term forecasting range, it is important as a forecaster to identify when/where NWP output isn’t matching reality. Then you can make appropriate changes to the forecast output. To find those mismatches anywhere in the world, one of the best tools is satellite imagery. In this lesson, we will focus on a few cases using satellite imagery to help identify mismatched features/processes between the satellite imagery and the NWP. Anyone trying to add valu ...PermalinkAnother way to try to find mismatches between observed weather and NWP output is by using total-column variables. There are a few of them to choose from, and they make for a relatively simple comparison method for finding correctable mismatches. In this lesson, we'll address appropriate methods for making these comparisons and build to a point where we will focus on bigger picture atmospheric processes. This is the second in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts.PermalinkYou know what PV is, yet aren't quite sure how to modify it to make a better forecast. In this short lesson, we will discuss how to modify the PV surface to match water vapour imagery and how those adjustments affect the surface sensible weather. This is the fifth in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts. Pre-requisite Knowledge: Satellite Water Vapour Interpretation -- Short CoursePermalinkThis 45-minute lesson briefly introduces learners to the benefits of using probabilistic forecast information to assess weather and communicate forecast uncertainties. Learners will explore a winter weather event in Germany and practice synthesizing deterministic and probabilistic forecast guidance to better understand forecast uncertainties based on lead-time. Also, learners will decide how to best communicate the potential weather threats and impacts to local end users. The lesson is another component of the Forecast Uncertainty: EPS Products, Interpretation, and Communication distance learn ...PermalinkThe Satellite Foundational Course for JPSS (SatFC-J) is a series of short lessons focused on topics related to microwave remote sensing and Joint Polar Satellite System instruments and capabilities. Hosted by the Cooperative Institute for Research in the Atmosphere (CIRA), this resource provides access to the full set of course lessons, which were developed specifically for National Weather Service (NWS) forecasters. The lessons provide foundational training to help forecasters and decision makers maximize the utility of the U.S.’ new-generation polar-orbiting environmental satellites. The cou ...PermalinkIn this lesson, we start by investigating the different types of fronts that are commonly analyzed. Next, we address two different types of cold fronts: classic (stacked), and katabatic. Then, we identify the main characteristics of these frontal types and what sets them apart from each other in conceptual models and in water vapour imagery. This is the first lesson in a two part series that addresses three different types of cold fronts and how to diagnose them.PermalinkThe Geostationary Lightning Mapper (GLM) aboard the GOES-R series satellites provides continuous lightning detection from space, giving forecasters a unique tool to monitor developing thunderstorms. This 45 minute lesson introduces learners to the benefits of using GLM gridded products, primarily Flash Extent Density (FED). Learners will explore several North American convective events and use Flash Extent Density, in combination with other satellite and radar data, to diagnose convective initiation, storm intensification, and areal extent of lightning activity. Helpful hints to keep in mind w ...PermalinkSurface observations are usually the first place we go when trying to find mismatches between observed weather and NWP output. We'll talk in this lesson about appropriate methods for making those comparisons and build to a point where we will focus on bigger picture atmospheric processes. This is the first in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts.PermalinkIf there were a way to make direct comparisons between satellite imagery and NWP output, that would appear to be the best possible way to find mismatches between the observed weather and NWP output. In this lesson, we'll address possible methods for making direct comparisons, starting with pseudo or synthetic satellite imagery and building to a point where we focus on a relatively unused NWP output. This is the third in a series of video lessons that introduces three different methods for modifying NWP output to add human value to forecasts. Pre-requisite Knowledge: Satellite Water Vapour Inte ...PermalinkThis 45-minute lesson briefly introduces learners to the benefits of using probabilistic forecast information to assess the weather and communicate forecast uncertainties. Learners will explore a heat wave event in Spain and practice interpreting EPS forecast products effectively to determine various forecast parameters based on lead-time. Also, learners will decide how to best communicate the potential weather threats and impacts information to local end users.PermalinkIntended for U.S. National Weather Service forecasters, this short video describes changes to the NWS National Blend of Models when it was updated to v3.1. These changes include: More global, mesoscale, and ensemble components; Increased spatial resolution of some components; New and improved weather elements for aviation, QPF, winter, fire, and marine weather forecasting; Significant wave height for offshore waters and the Great Lakes; Improved bias correction; MOS-like text products; Shortened NBM forecast projections delivered at 19 UTC. For an illustrated transcript, see What’s New in NBM ...PermalinkThis lesson introduces the capabilities of NOAA’s next-generation infrared and microwave sounders, the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Both fly on board the Suomi NPP satellite mission and constitute the foundation for NOAA’s operational space-based sounding capability on the next-generation JPSS polar-orbiting satellites. In addition to their complementary sounding duties, CrIS and ATMS provide capabilities and improvements for a variety of environmental products essential to weather forecasting and environmental monitoring. Some of th ...PermalinkThe National Weather Service National Blend of Models (NBM) was updated to version 3.0 on 27 July 2017. Changes include: Eight new components for the contiguous U.S. (CONUS) and Alaska, including four deterministic models, two ensemble systems, and two post-processed statistical components Five new components for Hawaii and Puerto Rico Expanded forecast domains for the CONUS and Alaska A “Time of Day” (ToD), rather than NWP model, initial time concept Hourly NBM forecasts, with short, day 2-4, and extended forecasts Updated NBM guidance available 50-60 minutes after hourly run time New weather ...PermalinkThis listing of multilingual training materials for the GOES-R series includes both foundational lessons and quick guides developed by various partners at the request of the U.S. National Weather Service and NESDIS. The selections included here represent materials translated to Spanish and Portuguese. Training contributors include COMET, RAMMB/CIRA, CIMSS, and SPoRT. Translation contributors/reviewers include the Servicio Meteorológico Nacional (SMN) in Argentina and the University of São Paulo in Brazil.PermalinkThis lesson discusses errors associated with the use of inconsistent terrain in the analyses in the Real-Time and the Un-Restricted Mesoscale Analyses (RTMA and URMA, respectively), and in downscaling numerical weather prediction model data to the resolution of the U.S. National Weather Service National Blend of Models (NBM). The sources of these inconsistencies are examined, and the errors that result are discussed. A solution is to use a unified, consistent terrain in the analyses and the NBM. This solution is only partial however, as resolution of small, meteorologically significant feature ...PermalinkSatellite data are important tools for analyses and short-term forecasts of surface floodwater. This lesson will highlight the August 2017 flooding associated with Hurricane Harvey in southeastern Texas, one of the most costly weather disasters in U.S. history. Through the use of interactive exercises the learner will become familiar with use and interpretation of satellite imagery in regions with surface flooding. The lesson will use data from both the S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) and the GOES-16 Advanced Baseline Imager (ABI). The satellite-derived flood map and th ...PermalinkThis lesson provides an introduction to the benefits, important input (forcing data), and key products of the National Water Model. Both official and evolving products are presented. The lesson uses the flooding associated with Hurricane Harvey in August 2017 to demonstrate key products.PermalinkThis short lesson describes the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the next-generation polar-orbiting satellite platforms. AMSR2’s primary mission is to improve scientists’ understanding of climate by providing estimates of precipitation, water vapor, cloud water, wind velocity, sea surface temperature, sea ice concentration, snow depth, and soil moisture. AMSR2 also advances weather forecasting through real-time imagery, value-added products, and input to numerical weather prediction. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).PermalinkThis lesson introduces the VIIRS imager on board the Suomi NPP and JPSS satellites. The lesson briefly describes the capabilities, improvements, and benefits that VIIRS brings to operational meteorology. Numerous images are shown that demonstrate a variety of applications available in the AWIPS weather display system. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).PermalinkThis lesson presents a brief overview of NOAA's operational low Earth orbiting satellites, focusing on how their orbits define observational coverage and how ground receiving capabilities impact data latency from the observation time to product availability. This lesson is part of the Satellite Foundational Course for JPSS (SatFC-J).PermalinkThis lesson introduces the capabilities and benefits of rapid scan imaging from geostationary meteorological satellites with a special focus on the current Meteosat Second Generation satellites. The lesson begins with an overview of current rapid scan imaging strategies and the products made from those observations. It then addresses nowcasting applications that benefit from these products with a focus on convection and its evolution. Other application areas that benefit from rapid scan observation are mentioned including the monitoring of fog and low stratus, wildfires, tropical cyclones, and ...PermalinkThis 45-minute lesson provides an opportunity to use ensemble prediction system products to evaluate uncertainty in the forecast and then communicate that information effectively to a public audience. The lesson places learners in the role of a Meteorological Service of Canada forecaster who must assess forecast uncertainty and then issue early warning notifications to decision-makers regarding the winter storm. In a subsequent work shift during the event, the learner must effectively deliver forecast information via social media and respond to questions from the general public. The lesson is ...PermalinkThis resource demonstrates the variety of satellite imagery and products accessible through the Community Satellite Processing Package (CSPP). Two videos, the first focused on imagery applications and the second on microwave applications, provide an overview of the types of weather and environmental information available through CSPP. Using CSPP, forecasters and others needing timely access to data can download and display imagery and products from Joint Polar Satellite System (JPSS) instruments. The resource provides some background information for obtaining and using the CSPP software, which ...PermalinkThis lesson introduces the innovative Day/Night Band (DNB). Producing both daytime and nighttime visible images, the unique aspect of the DNB is its nocturnal low-light imaging capability. It views reflected moonlight from clouds and Earth's surface, surface light emissions from various natural sources (such as fires) and anthropogenic sources (such as city lights and gas flares), and even from certain atmospheric light emissions such as the aurora, airglow, and lightning flashes. The lesson describes the capabilities and benefits of the DNB, in particular using the Near-Constant Contrast (NCC ...PermalinkThe Geostationary Lightning Mapper (GLM) flies aboard the GOES-R series satellites and provides lightning detection data at a quality and resolution not previously available from space. The GLM's continuous lightning monitoring capability is a valuable asset to detecting and monitoring developing thunderstorms 24 hours a day. This 30 minute lesson introduces learners to the benefits of using Geostationary Lightning Mapper (GLM) observations in assessing convection. Learners will explore a severe weather event near Buenos Aires, Argentina, and practice using GLM observations to determine initia ...PermalinkAgriculture is the largest employer in the world and is probably the most dependent on the climate of all human activities. In recent years there have been events that have put in evidence the vulnerability of global food security to major meteorological phenomena, both in global agricultural markets and the world economy. The food price crisis and the subsequent economic crisis reduced the purchasing power of large segments of the population in many developing countries, which seriously reduced their access to food and thus undermined their food security. During the years 2009 and 2010 in Ven ...PermalinkThe purpose of this publication is to describe and recommend procedures for the verification of operational probabilistic seasonal forecasts, including those from the Regional Climate Outlook Forums (RCOFs), National Meteorological and Hydrological Services and other forecasting centres. The recommendations are meant to complement the WMO Commission for Basic Systems Standardized Verification System for Long-range Forecasts (SVSLRF). SVSLRF defines standards for verifying model outputs from Global Producing Centres (GPCs), and so includes procedures for measuring the quality of ensemble predic ...PermalinkThis is the report on the project to create the Seasonal Climate Forecast - Course Package T.O.P. The goal of this online course package is to allow the transfer of seasonal climate forecast knowledge to improve and increase the operational capabilities of the targeted users. The package provides both a theoretical and a practical set of knowledge on seasonal forecast and predictability models, climate and data analysis, forecast verification, and specific application of seasonal forecast for agriculture and water management.PermalinkThis document describes the underpinning skills that support the WMO competencies that relate to the use of satellite data by operational meteorologists.PermalinkServicio Meteorológico Nacional (SMN) de Argentina ; National Oceanic and Atmospheric Administration (NOAA) - Servicio Meteorológico Nacional (SMN) de ArgentinaAquí encontrará los materiales del taller de GOES-16. El objetivo del taller es reforzar los conceptos adquiridos en el curso virtual desarrollado entre agosto y octubre de 2017 en el marco del "Programa de Entrenamiento para la Nueva Generación de Satélites Geoestacionarios" llevado adelante por el Servicio Meteorológico Nacional, y aplicarlo al análisis de casos de estudio de interés en la región. Mayor información sobre este taller presencial en el documento informativo del taller.PermalinkThis lesson teaches the basics of satellite image interpretation to forecasters, meteorology students, and other interested learners, with an emphasis on the African region. It begins by briefly describing visible, infrared, and water vapour channels, as well as RGBs and derived products. From there, it teaches learners how to interpret clouds and surface features using various channels and products. This sets the stage for the final section, where learners practice identifying features using assorted imagery and products. The lesson uses Meteosat Second Generation imagery over Africa and, to ...PermalinkThese free training resources include video tutorials as well as case studies with accompanying data and imagery. The resources introduce the new generation of aerosol products available from the JPSS series of polar-orbiting satellites (SNPP/VIIRS) and the GOES-R series of geostationary satellites (GOES-16/ABI). Users will learn about the types of satellite aerosol products available, including aerosol optical depth/thickness (AOD/AOT) and aerosol detection (smoke/dust masks), as well as complimentary satellite products, such as fire radiative power (FRP) hotspots and visible color imagery (R ...PermalinkThis lesson introduces users to the statistics used in generating the various weather element forecasts included in version 2 and 3 of the U.S. National Weather Service (NWS) National Blend of Global Models (NBM). This Level 3 lesson is intended for forecasters and users of NWS forecast products; some prior knowledge of numerical weather prediction and statistics is useful. Learners will be introduced to the analysis of record used to calibrate the NBM’s bias and error estimates. Learners will also explore the bias correction, weighting, and post-processing procedures used to produce the forec ...PermalinkThis video provides an introduction to the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC), including information about the COSMIC-2 mission. COSMIC uses a technique called radio occultation to profile temperature, water vapor, and ionospheric information within Earth's atmosphere. The high-quality, high-resolution data contribute to improvements in numerical weather prediction, hurricane forecasts, climate studies, and ionospheric analyses. This full video resource covering COSMIC data and science is hosted on COMET's YouTube Channel. A short video highlightin ...Permalink