The University of Southampton
University of Southampton Institutional Repository

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

LSA SAF Meteosat FRP products-Part 1: Algorithms, product contents, and analysis
LSA SAF Meteosat FRP products-Part 1: Algorithms, product contents, and analysis
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).

13217-13239
Wooster, M.J.
4b91034b-d585-49ec-85b2-0729f9bca9dc
Roberts, G
fa1fc728-44bf-4dc2-8a66-166034093ef2
Freeborn, P.H.
232c8991-6d80-4aaf-824a-57ee9fb1e36f
Govaerts, Y.
69a0a19d-b4f6-425a-9c5a-817386fb123e
Beeby, R.
a212a579-0b30-4967-9702-4ce2d3f3c3af
He, J.
4e574b72-f610-4522-8df2-41be455328cc
Lattanzia, A.
8d382d59-cb3a-4ef4-bf90-00fa9b528bb0
Mullen, R.
fb4e1950-543b-4e9b-8c1e-ff46404df8d9
Wooster, M.J.
4b91034b-d585-49ec-85b2-0729f9bca9dc
Roberts, G
fa1fc728-44bf-4dc2-8a66-166034093ef2
Freeborn, P.H.
232c8991-6d80-4aaf-824a-57ee9fb1e36f
Govaerts, Y.
69a0a19d-b4f6-425a-9c5a-817386fb123e
Beeby, R.
a212a579-0b30-4967-9702-4ce2d3f3c3af
He, J.
4e574b72-f610-4522-8df2-41be455328cc
Lattanzia, A.
8d382d59-cb3a-4ef4-bf90-00fa9b528bb0
Mullen, R.
fb4e1950-543b-4e9b-8c1e-ff46404df8d9

Wooster, M.J., Roberts, G, Freeborn, P.H., Govaerts, Y., Beeby, R., He, J., Lattanzia, A. and Mullen, R. (2015) LSA SAF Meteosat FRP products-Part 1: Algorithms, product contents, and analysis. [in special issue: Monitoring Atmospheric Composition and Climate Research of the Copernicus/GMES Atmospheric Service] Atmospheric Chemistry and Physics, 15 (22), 13217-13239. (doi:10.5194/acp-15-13217-2015).

Record type: Article

Abstract

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).

Text
Wooster et al 2015_accepted.pdf - Other
Download (3MB)
Text
__userfiles.soton.ac.uk_Users_slb1_mydesktop_acp-15-13217-2015.pdf - Other
Available under License Other.
Download (8MB)

More information

Accepted/In Press date: 11 November 2015
Published date: 30 November 2015
Organisations: Global Env Change & Earth Observation

Identifiers

Local EPrints ID: 379917
URI: http://eprints.soton.ac.uk/id/eprint/379917
PURE UUID: 22082af6-8a2e-4ae7-91dc-376fe54666af
ORCID for G Roberts: ORCID iD orcid.org/0009-0007-3431-041X

Catalogue record

Date deposited: 07 Dec 2015 10:20
Last modified: 15 Mar 2024 03:39

Export record

Altmetrics

Contributors

Author: M.J. Wooster
Author: G Roberts ORCID iD
Author: P.H. Freeborn
Author: Y. Govaerts
Author: R. Beeby
Author: J. He
Author: A. Lattanzia
Author: R. Mullen

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×