Weather
This module will demonstrate the usefulness of the water vapour channels in forecasting.
Water vapour images have traditionally been used as additional information which tells about the air streams and water vapour content in the upper and middle levels of the troposphere.
Water vapour is a trace gas, that tells about the origin and kinematics of an airmass. In this respect water vapour images can reveal features that Infrared or Visible channel images are not capable of showing.
Since the introduction of RGB techniques in satellite products, water vapour information is been used more and more in these RGB combination images. Water vapour information is particularly important in Airmass and Severe Storms RGB products.
This module takes a closer look at vorticity maxima and minima signatures in satellite imagery.
Vorticity patterns control the circulation of air masses in their vicinity. By doing this they control the location of important meteorological quantities that are essential for an accurate diagnosis and forecast of the atmosphere.
The scale of vorticity patterns in the atmosphere ranges from large-scale synoptic system circulations (low and high pressure centres) to smaller meso-scale circulations (water vapour vortices (sometimes referred as WV eddies or WV eyes). The (anti-)cyclonic rotation in the atmosphere caused by a vorticity maxima is easily seen in satellite imagery. And quite naturally, satellite imagery is the key tool to correctly locate the maximum of cyclonic and anticyclonic vorticity in the atmosphere. Moreover, satellite images are able to show the small-scale vorticity patterns that are easily overlooked and smoothed out by a NWP model.
This training module has been developed to teach you to identify these vorticity centres in Meteosat Second Generation (MSG) satellite imagery. In addition the module will provide you with a firm physical background to help you understand why it is important to do a good diagnosis of satellite images and also provide you with a range of examples and exercises to demonstrate the impact a vorticity centre may have on your weather forecast.
An intensive training module on the operational use of RGBs in the forecasting room.
Technological advances and the increasing sophistication of weather forecasting have created a demand for more frequent and more accurate and higher resolution observations from space. To meet this demand on 28th August 2002 the first of four satellites known as Meteosat Second Generation (MSG) was launched.
MSG transmits more than 20 times the information of its predecessor. The improved resolution of frequency of data significantly contributes to the accuracy of both short-term and medium range weather forecasts. Since 2004, the MSG satellites have been providing full Earth disc images every 15 minutes, in 12 spectral bands.
Twenty times more information is also a challenge for the user to cope with. To present all of this extra data in a understandable way to the user, so-called RGB (red, green and blue) images were developed that allow you to easily make a qualitative analysis. In RGB images the different properties of the twelve spectral bands of MSG are combined in one powerful coloured image.
Fog, snow, atmospheric dust, SO2 clouds from erupting volcanoes, severe updrafts in convective systems, Potential Vorticity (PV) anomalies are just a few keywords and applications that we will teach you to recognise in satellite imagery. On several occasions questions and exercises will help you to test your gained knowledge.
Storm Xynthia developed over the North Atlantic in late February 2010. The ASCAT sensor of EUMETSAT MetOp-A satellite tracked its evolution and provided insight into the life cycle of the storm.
This case study covers the development of storm Xynthia. Xynthia evolved out of a low pressure system which formed east of the Bermuda and lasted for 8 days. The storm was well depicted in satellite imagery and showed strong convective activity over the Atlantic. When approaching Western Europe and crossing Northern Europe, Xynthia was mainly a windstorm with gusts exceeding 150 km/h. The module briefly describes the functional principle of the ASCAT sensor and illustrates how measurement is performed and wind speed is retrieved. A comparison of ASCAT winds with NWP and surface winds is given, showing the benefits and drawbacks of each data source. Chapter 2 of the case study investigates the storms life cycle. In combination with satellite images, ASCAT wind data are plotted revealing deeper insight into the wind circulation close to ocean surface. The detailed analysis of the wind fields shows additional information on the position of the surface fronts and the location of pressure minima. Ongoing measurements of wind speed and direction from ASCAT is compared with NWP data and surface observations. The life cycle of storm Xynthia, from its real beginning over the Atlantic until its filling over the North Sea, is followed. During this time, Xynthia was covered 8 times by overpasses of the ASCAT sensor.
Icing still represents a major threat to aviation. This CAL module focuses on the occurrence of icing in stratiform clouds. A method to detect icing probability from satellite images in combination with radar and radiosonde data is presented.
Ice formation on wings and inside of the jet engine of planes causes around 15% of weather related aircraft accidents. Most icing occurs inside cumulonimbus clouds when supercooled droplets freeze with contact of the aircraft body. But also in stratiform clouds icing represents a major threat to aircrafts during landing and take-off phase. In this CAL module, icing hazards related to stratiform clouds are examined. The introductory chapter focuses on the different types of icing and the physical principles leading to ice formation on aircrafts. Satellite products from geostationary and polar orbiting satellites help differentiating between ice and water clouds. A sample of satellite images and products illustrate this capability. Additional data sources like radiosoundings and radar imagery are useful completions to the satellite data. Interpretation of radiosoundings in view of icing occurrence is the main topic of chapter 4. The usefulness of radar data for detecting ice clouds is demonstrated. Three case studies complement the theoretical part of the training module, showing typical weather situations where severe icing represented a serious threat to aircrafts in the past. These case studies combine the above mentioned data sources in the frame of a practical situation. The CAL module finishes on a suggested procedure for nowcasting icing from stratiform clouds. Exercises offering the possibility to test the acquired knowledge form the end of this module.
In this CAL module you will learn to detect areas with the risk for Clear Air Turbulence (CAT). This will be done with the help of satellite images, soundings, flight reports and analyses of the airflow.
Clear Air Turbulence is one of the most frequent hazards for civil aviation. It is also one of the biggest challenges for forecasters to detect and warn for possible Clear Air Turbulence occurrence.
In this CAL module you will learn to detect areas with a high risk for Clear Air Turbulence (CAT). This will be done with the help of satellite images, soundings, flight reports and analyses of the airflow. Practical examples will show you how to apply your knowledge.
This CAL module deals with applications of MSG water vapour images in operational forecast departments. It focusses on the analysis of WV imagery in view of turbulence, cyclogenesis, convection and deformation zones.
This training module gives an overview on applications of MSG water vapour channels for operational weather forecasting. It handles the concept of potential vorticity which is a key feature to understand the dynamic processes in the higher Troposphere such as cyclogenesis. The CAL module also shows practical applications of the WV images from the geostationary satellites for locating tropopause foldings, clear air turbulence and deformation zones. It handles the effects of WV boundaries on the initiation of convective processes and finally presents some meteorological products heavily based on WV imagery.
An intensive training module on the operational use of RGBs in the forecasting room.
The new generation satellite data contains more and more information offering increased insight into cloud and air mass characteristics. This poses a challenge: figuring out how to extract, distill and package the data into products that are easy for forecasters to interpret and use.
One might create numerous different kinds of RGB images. Satellite experts developed some optimally tuned RGB types for highlighting specific features. These are the so called standard RGBs recommended by EUMETSAT. The advantage of using standard RGBs is their easy comparability.
The aim of creating RGBs is to provide fast, easily understandable VISUAL information. A 'good' RGB should convey information that would be difficult or time consuming to assess visually from one or more individual single channel images. RGB image should be unambiguous and use intuitive colours to help highlighting important meteorological and surface features. RGBs provide useful information to forecasters, in particular when looking at animated image sequences. They preserve the "natural" look-and-feel of "traditional" satellite images, e.g. they preserve texture, and the patterns are continuous in time.
In this module you will learn more about the EUMETSAT standard RGBs: HRV Fog RGB, Snow RGB, Night Microphysics RGB and the Ash RGB.
This module treats all kinds of atmospheric gravity waves over land and over the oceans.
This module treats all kinds of atmospheric wave phenomena, starting with Lee Waves and ending with Vortex Streets. The physical background of Gravity Waves in general and Lee Waves in special will be highlighted and special cases, such as Foehn clouds, treated in more details. Gravity waves over the oceans build another focal point of this module. At the end of each chapter, exercises will help you to check the acquired knowledge.
The purpose of this training module is to give an overview on the different RGB types created from the AVHRR instrument.
This training module describes MetOp AVHRR (Advanced Very High Resolution Radiometer) RGB schemes that are based on EUMETSAT recommendations. The 'recipes' were tuned to create high quality MetOp/AVHRR RGB images as similar as possible to the SEVIRI RGB schemes recommended by EUMETSAT.
The main aim of the training module is to help the users (weather forecasters and/or other experts) understand and use these RGB types by giving them background information, examples and exercises.
The module takes the following structure:
- The aim of the RGB type
- Physical background
- How to create the given RGB type
- Typical colors
- Examples of interpretation
- Benefits and limitations
- Comparisons with other RGB types and/or single channel images
- Exercise
In this Training Module, the two major mid-latitude cyclone models, the Norwegian cyclone model and the Shapiro-Keyser cyclone model will be explained in detail.
In this module, the two major mid-latitude cyclone models, the Norwegian cyclone model and the Shapiro-Keyser cyclone model, will be explained in detail. The intention of the module is to point out the main differences in the life cycles of cyclones of the Norwegian type and the Shapiro-Keyser (S-K) type. Special focus will be placed on the synoptic preconditions that lead to the formation of cyclones.
Finally, sting jets, which often appear in the context of Shapiro-Keyser cyclones, will be briefly introduced.
In this Training Module you can follow the voyage of the research vessel Polarstern across the Atlantic and observe various atmospheric phenomena.
Follow the voyages of the research vessel Polarstern through different climate zones and weather situations in three oceans - Arctic, Atlantic and Antarctic. Learn more about fog, winds and convection, the globel circulation and climate zones. See how satellite images help you observe the atmospheric phenomena.