Description
Description
Basic Satellite Course Introduction
The
course aims to give an overview on the basics of satellite meteorology:
image analysis i.e. the interpretation of patterns in satellite images
that are related to various meteorological phenomena. During the course
you will read, watch and answer questions about various surface features
like vegetated ares, urban areas, difference between sea and land, you
will identify cloud types and analyze their characteristics and you will
learn to interpret atmospheric phenomena, like for example: dust
storms, smoke and fires from satellite data.
The course is asynchronous, which means that you can take it at your
own pace as all the lectures are pre-prepared. Quizzes are made for
youto check your level of understanding.
This Module Atmospheric Phenomena
This module teaches you how to use satellite data to observe and
analyse atmospheric phenomena. It will show you which products can be
used to identify dust storms, smoke, fires, precipitation, etc.
Expected Learning Outcomes
At the end of this module students should be able to identify and locate the following:
- Dust and sand storms and plumes and areas of raised dust.
- Fires and smoke.
- Moisture features, precipitation types and amounts.
- Volcanic ash particulates, Sulfur Dioxide (SO2) and other chemical emissions.
- Aerosol and particulate pollution.
- Features indicating regions of clear air turbulence.
Target Audience
The primary audience for the training are forecasters in shifts who
have access to different satellite (and model) products, though limited
time or knowledge because of their schedule and the lack of training.
Secondary audience are any other meteorologists and geoscientists that
are working with satellite data in training, research, etc.
WMO Competency Framework:
Satellite Skills and Knowledge for Operational Meteorologists
Format:
Online lesson/guide
Language:
English
Link to resource: https://eumetcal.eu/en/ui#/catalog/course/ff1e8528-4a7a-4da0-a394-bbacabcdb42f
Author of resource: EUMeTrain
Copyright: CC BY-SA
Contact: info@eumetcal.eu
Added by Tomislav Marekovic on 5 Nov 2024 (last modified on 14 Nov 2024)