ASMET Lessons

 

Recent ASMET lessons are online and on CD. Earlier lessons are available on CD only. To obtain a CD, email ops@eumetsat.int.


ASMET 7 (2013, English with French forthcoming, online and CD)

Three aviation weather case studies aimed at improving aviation forecasting in Africa. The case studies also support COMET's Review of Aeronautical Meteorology – Africa online learning curriculum, which provides training that supports the WMO/ICAO competencies for Aeronautical Meteorological Forecasters. The lessons are intended for aviation forecasters, general weather forecasters interested in aviation meteorology, and meteorological forecasting instructors and students.

Forecasting Fog For Aviation: Kenya Case Study

  • This lesson aims to improve aviation forecasts of fog in the African airspace by teaching forecasters to make more accurate forecasts using satellite imagery, numerical weather prediction, and other available data. A process for diagnosing and forecasting fog is presented and applied to a case over the Nairobi, Kenya region. Learners assume the role of aviation forecaster, analysing various products to determine whether the current Terminal Aerodrome Forecast (TAF) is valid or needs to be amended.

Convective Weather and Aviation in West and Central Africa

  • The hazards associated with convective systems present some of the most dangerous conditions encountered by aircraft and pose many challenges to aviation operations. When convection is forecast to develop, aviation forecasters are required to issue a series of warning messages and other meteorological aeronautical products to various members of the aviation community. This lesson teaches these forecasters how to produce the products, doing so in the context of a case study in which learners assume the role of aeronautical forecaster on duty at the airport in Niamey, Niger on a night when convection develops.

Detecting Clear Air Turbulence: South African Case Study

  • Turbulence is a major concern for the aviation industry. It often goes undetected in cloud-free areas, catching pilots off guard when they fly into it. Turbulence can injure passengers and crew, and cause structural damage to aircraft. This makes it critical for aviation weather forecasters to closely monitor the atmosphere for signs of turbulence and issue special warnings when it is likely to be present. This lesson helps prepare forecasters for these tasks by providing general information about turbulence and showing them how to detect it using satellite imagery, tephigrams, and NWP products. The latter is presented in the form of a case study in which learners assume the role of aviation forecaster at Cape Town International Airport (South Africa), and need to determine if turbulence is likely to be present along a particular flight path.

Basics of Visible and Infrared Remote Sensing, online version of ASMET 1, which was published on CD in 1997, English with French forthcoming, 2014

This lesson presents the scientific and technical basis for using visible and infrared satellite imagery so forecasters can make optimal use of it for observing and forecasting the behaviour of the atmosphere. The concepts and capabilities presented are common to most international geostationary (GEO) and low-Earth orbiting (LEO) meteorological satellites since their inception, and continue to apply to both current and newer satellite constellations. The lesson reviews remote sensing and radiative transfer theory through a series of conceptual models. Discussions contain explanations of the different Meteosat First Generation imager channels and the phenomena that they can monitor individually and in combination. This lesson is an online version of the first ASMET lesson published on CD in 1998, ASMET 1: Satellite Meteorology in Africa. While the images have not been updated, the concepts are fundamental and remain relevant today. Most of the images are from Meteosat and depict weather conditions over Africa, although some GOES imagery is included as well.


ASMET 6 (2011, English and French, online and CD)

Satellite Precipitation Products for Hydrological Management in Southern Africa / Les Produits satellitaires de précipitation pour la gestion de l'hydrologie en Afrique Australe

  • This lesson introduces a variety of meteorology and hydrology products that can improve the quality of heavy rainfall forecasts and assist with hydrological management during extensive precipitation events in Southern Africa. Among the products are the satellite-based hydro-estimator and the ASCAT, SMOS, and ASAR GM soil moisture products. These are presented within the context of a case, the flooding of South Africa's Vaal Dam in 2009/2010.
  • Ce modules montre divers produits météorologiques et hydrologiques susceptibles d’améliorer la qualité des prévisions de fortes précipitations et d’aider à la gestion hydrologique lors des épisodes de précipitations à grande échelle en Afrique Australe. On retrouve parmi ces produits, ceux extraits de ASCAT, SMOS, ceux d’humidité du sol ASAR GM et l’hydro-estimateur. Les produits sont présentés dans le cadre d’une étude de cas sur les inondations dans la région du barrage de Vaal en Afrique du Sud.

Flooding in West Africa / Inondations en Afrique de l'ouest

  • The rainy season in Sahelian West Africa extends from June to September and is tied to the position of the intertropical front. During this period, mesoscale convective systems (MCSs) often produce significant rainfall that can lead to flooding. This lesson examines an extreme flooding event that occurred in Ouagadougou, Burkina Faso from 31 August to 1 September 2009. Learners assume the role of forecaster, assessing meteorological conditions to see if an MCS will develop that can lead to heavy rain and flooding. They follow a forecast process that emphases the use of satellite data, standard surface and upper-air charts, and model output. The forecast process is tied to a conceptual model of the key features that drive convective activities in West Africa.
  • En Afrique de l’ouest, dans la zone sahélienne, la saison des pluies s'étend de juin à septembre et est liée à la position du front intertropical. Au cours de cette période, les systèmes convectifs de moyenne échelle (MCSs) génèrent souvent des précipitations significatives susceptibles de conduire aux inondations. Ce module présente un cas d'inondations graves qui s'est produit à Ouagadougou, Burkina Faso du 31 août au 1er septembre 2009. Au cours de cette étude, l’apprenant jouera le rôle de prévisionniste. Il évaluera les conditions météorologiques pour voir s’il était possible de prévoir le développement d’un MCS à même de conduire aux fortes pluies et aux inondations observées. A cet effet, il suivra une méthode de prévision basée sur l'utilisation des données satellitaires, des cartes standards de surface et d'altitude ainsi que des sorties de modèle. Cette méthode de prévision est liée à un modèle conceptuel des principaux éléments qui gouvernent les activités convectives en Afrique de l'ouest.

2009 Drought in East Africa / La sécheresse en Afrique de l'Est en 2009

  • The lesson examines the 2009 drought in the Greater Horn of Africa (GHA), focusing on conditions in Kenya. The lesson begins by reviewing drought conditions in the years leading up to 2009. From there, it examines the seasonal climate forecast for the beginning of 2009 and sees what it portends. Satellite products are used to study rainfall performance throughout the year and its impact on the drought situation. Finally, the lesson describes the climate oscillations that can impact drought in the GHA and identifies patterns that were present in 2009 and contributed to its severity. By the end of the lesson, weather forecasters and students should have a better understanding of drought and the tools available for its early detection and monitoring.
  • Ce module examine la sécheresse de l’année 2009 dans la Grande Corne de l’Afrique (GCA) en mettant un accent particulier sur les conditions observées au Kenya. Le module commence par un passage en revue des conditions de sécheresse des années précédentes jusqu’à la situation de 2009. La prévision climatique saisonnière pour le début de 2009 est ensuite examinée afin d’en faire ressortir la tendance annoncée. Les produits satellitaires sont utilisés pour étudier l’évolution des précipitations au cours de l’année et son influence sur la sécheresse. Le module décrit en définitive, les oscillations du climat susceptibles d’influencer la sécheresse dans la Grande Corne de l’Afrique. Il identifie donc la situation météorologique observée en 2009, qui a contribué à la sévérité de la sécheresse. A l’issue de l’étude du module, les étudiants et les prévisionnistes auront une meilleure compréhension de la sécheresse et des outils disponibles pour sa détection précoce et sa surveillance.

ASMET 5: Meteosat Second Generation (MSG) Africa Case Studies (2010, English and French, online and CD)

  • Secondary Lows Behind Frontal Systems
  • Duststorms
  • Cloud Clusters

These case studies teach forecasters how to use EUMETSAT Meteosat Second Generation (MSG) satellite data to forecast the development of secondary lows behind frontal systems, duststorms, and cloud clusters over Africa. Each set has a learning case that guides users through the forecast process and a practice case that lets users apply the process to a different set of weather conditions. The cases use ECMWF model data along with MSG data and emphasize the use of RGB products.


ASMET 4: Tropical Cyclones over the Southwest Indian Ocean (2006; English and French, online and CD)

This lesson has two sections:

  • Background information about the genesis and development of tropical disturbances (TDs) in the SouthWest Indian Ocean, including the main features of tropical cyclones that affect that area, the stages of development of TDs, and the conditions conducive for the life cycle of a TD.
  • A case study of Tropical Cyclone Hary, which occurred during the March 2002 tropical cyclone season over the SouthWest Indian Ocean. The lesson presents a process for forecasting the genesis and evolution of a TD using information issued by tropical cyclone forecast centres and guides users through applying it. Both satellite imagery and numerical weather prediction products are used.

ASMET 3: Combining Satellite Imagery and Model Output in Weather Forecasting (2001, English and French, CD only)

This lesson presents a process for combining satellite imagery and model output in weather forecasting.
The process is applied to two cases: one about the ITCZ and the other about easterly waves over Africa.
These features were chosen because of their significant domination of the weather dynamics over tropical Africa. Each case has two sections: a teaching portion, where users learn how to use model output and validate it with satellite imagery, and a practice portion where they apply the technique to a different situation.


ASMET 2: Integrating Satellite Imagery of the ITCZ into Analyses (1998, English and French, CD only)

This lesson presents a process for integrating satellite imagery into the analysis process. Emphasis is placed on the identification of the Intertropical Convergence Zone (ITCZ) and its related features over tropical Africa in visible, infrared, and water vapour imagery. The satellite information is integrated with synoptic observations to construct analyses for surface, low-, mid-, and upper-level synoptic charts. With better initial analyses, forecasters should be able to improve their forecasting skills.


ASMET 1: Satellite Meteorology in Africa (1997, English and French, CD only)

This lesson presents the scientific and technical basis for using satellite imagery so forecasters and other users can develop locally and regionally useful techniques for observing and forecasting the behavior of the atmosphere. The lesson reviews remote sensing and radiative transfer theory through a series of conceptual models. The discussion contains explanations of the different imagery channels (visible, infrared, and water vapor) and the phenomena that the channels can monitor individually and in combination. The lesson contains imagery from EUMETSAT's Meteosat satellite and the U.S. Geostationary Operational Environmental Satellite (GOES) series.