LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis

• Published in: Atmospheric chemistry and physics Vol. 15; no. 22; pp. 13217 - 13239
• Main Authors: Wooster, M. J, Roberts, G, Freeborn, P. H, Xu, W, Govaerts, Y, Beeby, R, He, J, Lattanzio, A, Fisher, D, Mullen, R
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 30.11.2015; Copernicus Publications
• Subjects: Aerosol Robotic Network; Algorithms; Atmosphere; Atmospheric composition; Atmospheric correction; Atmospheric models; Atmospheric monitoring; Bias; Biomass; Biomass burning; Burning; Burning rate; Case studies; Cloud cover; Clouds; Computer simulation; Data; Detection; Earth observations (from space); Emission; Emissions; Fire detection; Fires; Geosynchronous orbits; Image detection; Image enhancement; Infrared imaging; Meteorological satellites; METEOSAT; MODIS; Monitoring; Optical analysis; Performance evaluation; Pixels; Plumes; Qualitative analysis; Real time; Remote sensing; Resolution; Satellite imagery; Satellite observation; Satellites; Sensors; Smoke; Surface analysis (chemical); Synchronous satellites; Temporal resolution; Trace gases; Weather forecasting; Wildfires; South America; Europe; Africa
• ISSN: 1680-7324; 1680-7316; 1680-7324
• DOI: 10.5194/acp-15-13217-2015

Characterizing changes in landscape fire activity at better than hourly temporal resolution is achievable using thermal observations of actively burning fires made from geostationary Earth Observation (EO) satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from geostationary EO data, often with the aim of supporting biomass burning fuel consumption and trace gas and aerosol emission calculations. Such Fire Radiative Power (FRP) products are generated operationally from Meteosat by the Land Surface Analysis Satellite Applications Facility (LSA SAF) and are available freely every 15 min in both near-real-time and archived form. These products map the location of actively burning fires and characterize their rates of thermal radiative energy release (FRP), which is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the full spatio-temporal resolution FRP data set derivable from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) imager onboard Meteosat at a 3 km spatial sampling distance (decreasing away from the west African sub-satellite point), whilst the FRP-GRID product is an hourly summary at 5° grid resolution that includes simple bias adjustments for meteorological cloud cover and regional underestimation of FRP caused primarily by underdetection of low FRP fires. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA) detection algorithm used to deliver these products and detail the methods used to generate the atmospherically corrected FRP and per-pixel uncertainty metrics. Using SEVIRI scene simulations and real SEVIRI data, including from a period of Meteosat-8 "special operations", we describe certain sensor and data pre-processing characteristics that influence SEVIRI's active fire detection and FRP measurement capability, and use these to specify parameters in the FTA algorithm and to make recommendations for the forthcoming Meteosat Third Generation operations in relation to active fire measures. We show that the current SEVIRI FTA algorithm is able to discriminate actively burning fires covering down to 10−4 of a pixel and that it appears more sensitive to fire than other algorithms used to generate many widely exploited active fire products. Finally, we briefly illustrate the information contained within the current Meteosat FRP-PIXEL and FRP-GRID products, providing example analyses for both individual fires and multi-year regional-scale fire activity; the companion paper (Roberts et al., 2015) provides a full product performance evaluation and a demonstration of product use within components of the Copernicus Atmosphere Monitoring Service (CAMS).