Weather
Maria Putsay discusses convective clouds that form over wildfires, focusing on Pyrocumulonimbus clouds and their detection in satellite imagery.
Pyrocumulonimbus (pyro-Cb) clouds can form above wildfires. These are fire-aided or fire-caused convective clouds with considerable vertical development. Large amounts of smoke particles are injected into these clouds. The increased number of condensation nuclei causes extremely small ice crystals on the cloud tops. That is why the typical colors of these clouds vary in several RGBs. The cloud top color may help to identify pyro-Cb clouds, which might be dangerous by causing extreme low-level winds, and hence increasing fire spread.
Pedro Venâncio introduces the Portuguese Rural Fire Information System (SIFOR) and demonstrates how the GeoSIFOR WebGIS enables users to easily access, visualise and interpret available data.
SIFOR is an integrated application ecosystem designed to centralize and share technical information across Portugal’s Integrated Rural Fire Management System (SGIFR). Within this ecosystem, GeoSIFOR acts as a user-friendly Geographic Information Viewer (WebGIS) that allows users without specialized knowledge in GIS or remote sensing to easily leverage geographic and satellite data. Through its agile interface, non-expert users can access complex information, for instance, from the Copernicus Data Space Ecosystem (CDSE), Eumetsat, LSA-SAF, NASA, as well as satellite-derived products processed by other public entities such as DGT and IPMA.
Francesca Di Giuseppe discusses ECMWF fire prediction systems and the advantages of SPARKY, a new data-driven system for predicting fire activity and burned area.
Traditional fire danger indices estimate environmental conditions conducive to fire but do not directly predict when and where fires will occur. This presentation introduces a shift toward fire activity forecasting, using data-driven approaches that integrate weather, fuel conditions, and ignition sources. By leveraging machine learning and Earth observation data, these systems provide probabilistic forecasts of actual fire occurrence and spread. The approach improves early warning capabilities, reduces false alarms in fuel-limited regions, and offers actionable information for fire management, supporting more effective preparedness, response, and long-term risk mitigation strategies.
Ivan Smiljanić presents the evolution of RGB composites used for fire detection, with a final focus on the MTG Day Land Cloud Fire RGB composite and its advantages.
The Day Land Cloud/Fire RGB (full name) is a composite designed to enhance the detection of surface features and clouds, in addition to wildfires. Compared to other fire-focused composites, it provides a more balanced depiction of smoke, vegetation, and burn scars in a single product, though with reduced ability to discriminate fire intensity or even cloud phase. It renders active fires more vividly in red while preserving a near-natural background appearance. It is particularly effective for integrated situational awareness rather than specialized analysis.
Rita Durão explains the FRP's potential as an early smoke indicator and shows the connection with higher air pollutant emissions.
The intensity of a wildfire can be assessed by integrating fire radiative power (FRP) measurements over time. Since FRP is proportional to the amount of burned biomass, higher FRP values are associated with more severe fires, with higher smoke levels and, consequently, higher air pollutant emissions. Thus, the goal of this work is to assess FRP's potential as an early smoke indicator, leveraging the very high-resolution MTG data (10-minute temporal resolution). PMx and CO emitted during the August 2025 wildfires in Iberia are analyzed to illustrate the relationship between air pollutant levels and fire intensity over the affected areas.
Bruno Café introduces satellite products used by operational forecasters for fire detection and monitoring, using the 2025 Portugal fire event as a case study.
This presentation explores the enhanced capabilities of the Flexible Combined Imager (FCI) sensor on board Meteosat-12 (MTG) for forest fire detection and monitoring. By leveraging better spectral, temporal, and spatial resolutions, we demonstrate how new RGB composites, specifically Fire Temperature and True Color RGBs, provide critical advantages in identifying hotspots, smoke plumes, and burn scars.
Sven-Erik Enno introduces the LI instrument and its use for fire detection, while Andrea Meraner provides a data analysis example of a fire related to lightning.
The Meteosat Third Generation (MTG) Lightning Imager (LI), declared operational on October 31, 2024, is a new European Instrument devoted to the real-time monitoring and characterization of lightning activity over Europe, Africa, the eastern part of South America, and a large portion of the Atlantic Ocean. This presentation will demonstrate LI's observational capabilities from hemispherical climatological statistics to local-scale forest fire events. In addition, we show examples of lightning-ignited fires as observed by LI and FCI, the multispectral imager onboard MTG.
Edouard Martins gives a brief introduction on the work of EUMETSAT and then focuses on monitoring thermal hotspots with Sentinel satellites.
EUMETSAT Central Facility (CF) is entrusted by the European Commission for the operational detection and monitoring of high thermal spots (wildfires, gas flares, volcanoes) from the Sentinel-3 (S3) satellites in Near Real Time (NRT), with emergency timeliness. The Copernicus S3 NRT Fire Radiative Power (FRP) observes global wildfires between 500 m and 1 km resolution, both at night and during the day. The public product is today under testing by the two Copernicus services dedicated to atmosphere monitoring and emergency management (CAMS and CEMS). Additionally, it is being completed by NRT quantification of pollutant observation from the Sentinel Constellation (S3 currently, S4 and S5 later on).
Martin Wooster discusses the LSA SAF Fire Radiative Power (FRP) product derived from geostationary satellite imagery and the improvements in active fire detection offered by MTG compared with MSG.
The session will cover the Geostationary FRP products from the EUMETSAT LSA-SAF that provide a record of active fire detections, fire radiative power (FRP) and smoke and carbon emissions over Europe, Africa and parts of South America, most recently from MTG with significant performance improvements compared to MSG. The methods used, the available products, and their performance will be reviewed in this session.
Have you ever wondered what an Atmospheric River is or how to recognize it in model or satellite data? The freshly released training module will assist you by guiding you step by step through the identification process.
First you will learn some basic facts on Atmospheric Rivers; how and where they are created, their typical characteristics and their appearance in satellite and model data. Step by step, you will then be guided through the identification process until you are certain that you are dealing with the phenomenon that is called an Atmospheric River.
Later stages of Atmospheric Rivers are sometimes tricky to identify as they are often merged with mid-latitude frontal systems. But here again, model fields and the timely evolution can give a precise answer whether there is an embedded AR or not.
And finally, it is well invested time going through this training module as ARs are responsible for many floods and heavy precipitation in Western Europe once they make a landfall.
The purpose of this Training Module is to provide step-by-step instructions for identifying Atmospheric Rivers.
This mini-module is part of a series of MTG mini modules produced by EUMETSAT/EUMeTrain with the aim of providing quick and useful learning experience about the new satellite products.
In this exercise you are giving forecast for a shipment route that could be affected by a convective event.
Enter the mini-module.
This mini-module is part of a series of MTG mini modules produced by EUMETSAT/EUMeTrain with the aim of providing quick and useful learning experience about the new satellite products.
In this exercise you will learn how to use LI data together with ground based measurements.
Enter the mini-module.