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| Titel |
LSA SAF Meteosat FRP products – Part 1: Algorithms, product contents, and analysis |
| VerfasserIn |
M. J. Wooster, G. Roberts, P. H. Freeborn, W. Xu, Y. Govaerts, R. Beeby, J. He, A. Lattanzio, D. Fisher, R. Mullen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 22 ; Nr. 15, no. 22 (2015-11-30), S.13217-13239 |
| Datensatznummer |
250120193
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| Publikation (Nr.) |
 copernicus.org/acp-15-13217-2015.pdf |
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| Zusammenfassung |
| 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). |
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