Meteosat SEVIRI Fire Radiative Power (FRP) Products from the Land Surface Analysis Satellite Applications Facility (LSA SAF): Part 1 - Algorithms, Product Contents & Analysis

Characterising 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 minutes in both near real-time and archived form. These products map the location of actively burning fires and characterise their rates of thermal radiative energy release (fire radiative power; FRP), which is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL Product contains the full spatio-temporal resolution FRP dataset derivable from the SEVIRI 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 under-detection 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 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 are algorithms used to generate many other 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, whilst 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 Service (CAMS).