Thursday, June 25, 2026

x̄ - > MTG-FCI Warning System

Implementing a Warning System Using MTG-FCI Data

Environmental Monitoring and Early Warning Framework Using MTG-FCI Products

MTG-FCI Satellite Monitoring

Overview

To support near-real-time hazard monitoring, a warning system was developed using Meteosat Third Generation – Flexible Combined Imager (MTG-FCI) products. The goal was to automatically identify critical environmental conditions such as wildfires and severe atmospheric activity by analyzing relevant RGB products.

Metadata Investigation and Product Discovery

Metadata Investigation

Metadata inspection workflow showing digitalTransfers, thumbnails, href references, and nested JSON structures.

The initial investigation focused on identifying:

  • Severe Convection products
  • Fire Temperature products

These products were expected to be referenced within the digitalTransfers metadata field. Early inspection revealed that the list of monitoring URLs was empty, suggesting the products were stored differently within the metadata structure.

Diagnostic steps included:

  • Inspection of digitalTransfers records
  • Examination of thumbnail metadata
  • Analysis of href references
  • Inspection of nested JSON structures

Key Findings

Data Access

The MTG-FCI Africa dataset is primarily disseminated through EUMETCast Africa. Rather than direct GeoTIFF download links, metadata contains subscription and access information linked through the EO Portal.

Product Identification

Product-specific dissemination tags were discovered within GeoTIFF filename definitions through the typicalFilename metadata field.

Fire Temperature Product

Fire Temperature (FIRET)

Cloud Phase Product

Cloud Phase (CPHAS)

Product Dissemination Tag
Fire Temperature FIRET
Cloud Phase CPHAS

These tags provide a reliable mechanism for identifying and classifying incoming MTG-FCI products.

Warning System Logic

Warning Dashboard

Real-time threshold monitoring and alert generation dashboard.

A threshold-based alerting function, check_warning_threshold(), was implemented to evaluate incoming pixel values and determine whether warning conditions exist.

Configured Thresholds

Product Threshold
Fire Temperature (FIRET) 310 K
Cloud Phase (CPHAS) 200 K
def check_warning_threshold(product, value):
    thresholds = {
        "FIRET": 310,
        "CPHAS": 200
    }

    if value > thresholds.get(product, float("inf")):
        return f"ALERT: {product} threshold exceeded! Value: {value}K"
    else:
        return f"Normal: {value}K"

Simulation Results

Input

Product: FIRET
Value: 325 K
Threshold: 310 K
Output

ALERT: Fire Temperature threshold exceeded!
Value: 325 K (Limit: 310 K)

The warning system successfully detected the anomaly and generated the appropriate alert notification.

Future Enhancements

  • Integration with live EUMETCast data streams
  • Automated GeoTIFF ingestion and processing
  • Spatial hotspot clustering for wildfire detection
  • Severe convection monitoring using additional MTG-FCI RGB products
  • Real-time dashboard visualization and alert dissemination
Wildfire Monitoring Severe Convection Monitoring GeoTIFF Processing

Conclusion

Through detailed metadata inspection, operational MTG-FCI monitoring products were identified using dissemination tags embedded in GeoTIFF filenames. The resulting threshold-based warning framework demonstrates how MTG-FCI observations can be transformed into actionable alerts for environmental monitoring, wildfire detection, and severe weather early-warning applications.

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