Similar to snow covered hills
with its unique view, but also hidden dangers, winter weather for the
operational meteorologists offers a unique concept to handle, quite a different
view in the satellite imagery, and hidden hurdles when it comes to
interpretation of that imagery. Join us for this session and you will hear
satellite application experts talking about:
24 November 2021; 12:00 UTC
This short course offers an introduction to the weather-related satellite data visualization and analysis using Jupyter Notebooks. We show you how you can use the Python scripts to easily open and visualize the data and analyse the weather. In this course you learn how to:
- Access satellite data using Jupyter Notebooks
- Visualize single channels and channel combinations (RGB products)
- Analyse cloud types and basic weather patterns in visualized images
with Ivan Smiljanic and Alen Berta (CGI); Moderator: Natasa Strelec Mahovic (EUMETSAT)
9 November 2021, 12:00 UTC
In the course we will learn some of the most popular machine learning algorithms applied to retrieval and classification of optical remote sensing images (Sentinel-3 OLCI) for Ocean Colour studies.
with Ana Ruescas; Moderator: Mark Higgins (EUMETSAT)
4 November 2021, 12:00 UTC
The ocean is a complex system with processes at various scales interacting among them, from thousands of kilometers down to less than 1 km. Satellite data offer a unique amount of information about the ocean surface, thanks to the high spatial and temporal resolution they provide. However, satellite sensors measuring at the visible and infrared wavebands are affected by the presence of clouds and have therefore a large amount of missing data (clouds cover about 75% of the Earth at any given time). In order to study these multi-scale oceanic processes it is therefore necessary to deal with this missing information. Data interpolation techniques are often used for that, and various approaches have been developed over time.
The GHER (GeoHydrodynamics and Environment Research) of the University of Liege in Belgium works on the development of interpolation techniques for satellite data. In this seminar we will present two approaches. We’ll start with DINEOF - Data Interpolating Empirical Orthogonal Functions- which is a data-driven technique using EOFs to infer missing information in satellite datasets. We will follow with a more recent development, DINCAE - Data Interpolating Convolutional AutoEncoder.
with Aida Alvera Azcarate; Moderator: Hayley Evers-King
19 October 2021, 11:00 UTC
Machine learning has recently been used for nowcasting weather phenomena in several studies and applications. One of these applications is thunderstorm nowcasting, on which several studies have already been published. However, these studies usually make use of only one data source and concentrate on a single thunderstorm hazard. In order to bring these methods to real-world applications, we are working to develop thunderstorm nowcasting methods that make use of multiple sources of data simultaneously and can be trained to create products for different hazards according to the needs of the end user.
with Jussi Leinonen (MeteoSwiss); Moderator: Mark Higgins (EUMETSAT)
6 October 2021, 11:00 UTC
We inform you on the availability of new and modern Data Services at EUMETSAT that you can already employ to access a selection of EUMETSAT data, including the MSG level1.5.
The key new service for existing Data Centre users is the EUMETSAT Data Store. The Data Store and the associated Data Tailor Service provides users with a download and data tailoring service for online data which will eventually replace the ordering service from the Data Centre. Users can discover, apply customisation changes (format transformations, regional sub-setting, file aggregation, etc.) and download data. The service provides access through an online interface (GUI) and additionally for the first time also via Application Programming Interfaces (API). The service is currently in a pilot phase and is planned to go operational in July 2021.
For limited audience only.
Environmental and weather prediction systems rely on an accurate representation of soil moisture (SM). The availability of moisture in the root zone of plants is critical and especially in recent years has become an issue in large areas of Europe, as a series of dry summers have been experienced.
As an H SAF partner, ECMWF is producing scatterometer-derived root zone SM. In this short course you will learn about the retrieval approach and the strengths and limitations of the climate data record.
with David Fairbairn (ECMWF; H SAF) and Christine Traeger Chatterjee
16 June 2021, 12:00 UTC
What is Land Surface Temperature (LST)? How is it measured? What is it used for? Why are there two similar data records of LST offered in the EUMETSAT portfolio? Can we do climate analysis by combing the different LST data? These and more questions will be answered in this short course.
with Anke Duguay-Teztlaff (MeteoSwiss, CM SAF), Joao Martins (LSA SAF, IPMA) and Christine Traeger Chatterjee
19 May 2021, 12:00 UTC
Discover what satellite data is used in convection analysis and try yourself in a hands-on data exercise in a convective case.
with Natasa Strelec Mahovic and Ivan Smiljanic
12 May 2021, 12:00 UTC
Discover Global sea surface temperature data from the SLSTR instrument onboard the Sentinel-3 satellites, including data access, visualization and processing. Tools used in this short course will include CODA, SNAP, and Python Jupyter Notebooks.
with Bob Brewin, Lauren Biermann, Oliver Clements, and Christine Traeger Chatterjee
14 April 2021, 12:00 UTC
Have you ever done case study yourself? What is the case study anyway – is this a nice short story about the event that happened, supported by some scientific variables? Or this is research paper triggered by a certain event that did not go under public or scientific radar? Why and how experts produce case studies, and who needs them anyway?
In this short course webinar we will try to answer aforementioned questions and hint you about the tools and know-how to assist your own potential venture into case studies.
with Ivan Smiljanic and Natasa Strelec Mahovic
17 March 2021, 12:00 UTC
This short course focuses on the ozone dataset from the GOME-2 instrument. We will discuss the basics of the stratospheric ozone science and the observational techniques. Then we will bring participants in working with datasets on an intuitive series of Notebooks to (1) familiarize with data and (2) get ready to make their own analysis and animations.
with Alessandra Cacciari, Julia Wagemann and Federico Fierli
18 Febr 2021, 12:00 UTC
In this short course you will be introduced to R-Instat, its functionalities and how it can be used to compare satellite data with station data. R-Instat is a statistics software, which is very well designed to manage station data and compare and combine station data with satellite data.
Participants will be given time to play with R-Instat, check out the functionalities to compare station data with satellite data. Participants are also invited to join a feedback session on Monday, 8 February 2021.
with Danny Parsons, Steffen Kothe and Christine Träger-Chatterjee
3 Febr 2021, 12:00 UTC
In this short course you will be introduced to the CM SAF R Toolbox and its functionalities. The CM SAF R Toolbox is a software based on R, specifically developed to analyse satellite based climate data records.
Information and support on how to install the CM SAF R Toolbox will be provided. Participants will be invited to play with the visualization and analysis functionalities provided in the software and to join also a feedback / Q&A session on Monday, 25 January 2021
with Christine Traeger Chatterjee, Steffen Kothe and Danny Parsons
20 Jan 2021, 12:00 UTC
Download, plot and explore level 2 data and build a gridded dataset following robust methods using Jupyter Notebooks. The activity is structured into a webinar, self-paced work and a feedback session.
with Alessandra Cacciari and Julia Wagemann9 December 2020, 12:00 UTC
Discover Ocean and Land Colour data from the Instruments (OLCI) onboard the Sentinel-3 satellites, including data access, visualization and processing. Tools will include Python, Jupyter Notebooks & SNAP.
with Hayley Evers-King, Lauren Biermann and Oliver Clements
25 November 2020, 12:00 UTC
Details on the CM SAF SARAH climate data record (available since 1983), focusing on sunshine duration and surface solar radiation, incl. current applications and future developments. In an interactive session you will be able to explore the SARAH data record using the CMSAF R Toolbox and discuss the results.
with Jörg Trentmann, Uwe Pfeifroth, Steffen Kothe and Christine Träger-Chatterjee
28 October 2020, 12:00 UTC
Learn more about fire monitoring with satellites in general and the NRT Sentinel-3 SLSTR Fire Radiative Power (FRP) and Aerosol Optical Depth (AOD) data products in specific.
The course will be accompanied with a practical training where the data and three different examples of recent wildfire events will be introduced. The practical training is based on Jupyter notebooks.
with Federico Fierli, Julien Chimot and Julia Wagemann
Feedback session: 19 Oct 2020, 12:00 UTC
with Mark Higgins
6 October 2020, 13:00 UTC
A formula-free approach to remote sensing based on images from GOES and Meteosat satellites. How to twist radiance readings at the satellite into air temperatures and soil characteristics. Guided exercises on viewers will try to make you familiar with
satellite data.
with Jose Prieto
30 September 2020, 12:00 UTC
