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Yves Govaerts - One of the best experts on this subject based on the ideXlab platform.
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Climate Data Records from Meteosat First Generation Part II: Retrieval of the In-Flight Visible Spectral Response
'MDPI AG', 2019Co-Authors: Ralf Quast, Yves Govaerts, Ralf Giering, Frank Rüthrich, Rob RoebelingAbstract:How can the in-flight spectral response functions of a series of decades-old broad band radiometers in Space be retrieved post-flight? This question is the key to developing Climate Data Records from the Meteosat Visible and Infrared Imager on board the Meteosat First Generation (MFG) of geostationary satellites, which acquired Earth radiance images in the Visible (VIS) broad band from 1977 to 2017. This article presents a new metrologically sound method for retrieving the VIS spectral response from matchups of pseudo-invariant calibration site (PICS) pixels with datasets of simulated top-of-atmosphere spectral radiance used as reference. Calibration sites include bright desert, open ocean and deep convective cloud targets. The absolute instrument spectral response function is decomposed into generalised Bernstein basis polynomials and a degradation function that is based on plain physical considerations and able to represent typical chromatic ageing characteristics. Retrieval uncertainties are specified in terms of an error covariance matrix, which is projected from model parameter space into the spectral response function domain and range. The retrieval method considers target type-specific biases due to errors in, e.g., the selection of PICS target pixels and the spectral radiance simulation explicitly. It has been tested with artificial and well-comprehended observational data from the Spinning Enhanced Visible and Infrared Imager on-board Meteosat Second Generation and has retrieved meaningful results for all MFG satellites apart from Meteosat-1, which was not available for analysis
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towards multidecadal consistent Meteosat surface albedo time series
Remote Sensing, 2010Co-Authors: Alexander Loew, Yves GovaertsAbstract:Monitoring of land surface albedo dynamics is important for the understanding of observed climate trends. Recently developed multidecadal surface albedo data products, derived from a series of geostationary satellite data, provide the opportunity to study long term surface albedo dynamics at the regional to global scale. Reliable estimates of temporal trends in surface albedo require carefully calibrated and homogenized long term satellite data records and derived products. The present paper investigates the long term consistency of a new surface albedo product derived from Meteosat First Generation (MFG) geostationary satellites for the time period 1982-2006. The temporal consistency of the data set is characterized. The analysis of the long term homogeneity reveals some discrepancies in the time series related to uncertainties in the characterization of the sensor spectral response of some of the MFG satellites. A method to compensate for uncertainties in the current data product is proposed and evaluated.
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estimation of surface albedo increase during the eighties sahel drought from Meteosat observations
Grid and Pervasive Computing, 2008Co-Authors: Yves Govaerts, Alessio LattanzioAbstract:Abstract The devastating drought in the Sahel during the 70s and the 80s is among the most undisputed and largest recent climate event recognized by the research community. This dramatic climate event has generated numerous sensitivity analyses on land-atmosphere feedback mechanisms with contradicting conclusions on surface albedo response to precipitation changes. Recent improvements in the calibration and quantitative exploitation of archived Meteosat data for the retrieval of surface albedo have permitted to compare surface albedo of 1884, the driest year of the 80s, with year 2003 which had similar precipitation rate than conditions prevailing prior to the 80s drought. This analysis reveals detailed information on the geographical extension and magnitude of the surface albedo increase during from the 80s drought. A mean zonal increase in broadband surface albedo of about 0.06 between 1984 and 2003 has been estimated from the analysis of Meteosat observations. Regions particularly affected by the 1980s drought are essentially located into a narrow band of about 2° width along 16°N running from 18°W up to 20°E. Within this geographical area, surface albedo changes are not homogeneous and largest differences might locally exceed 0.15 whereas other places remained almost unaffected. The variety of previously published results might be explained by these important spatial variations observed around 16°N.
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retrieval error estimation of surface albedo derived from geostationary large band satellite observations application to Meteosat 2 and Meteosat 7 data
Journal of Geophysical Research, 2007Co-Authors: Yves Govaerts, A LattanzioAbstract:[1] The extraction of critical geophysical variables from multidecade archived satellite observations, such as those acquired by the European Meteosat First Generation satellite series, for the generation of climate data records is recognized as a pressing challenge by international environmental organizations. This paper presents a statistical method for the estimation of the surface albedo retrieval error that explicitly accounts for the measurement uncertainties and differences in the Meteosat radiometer characteristics. The benefit of this approach is illustrated with a simple case study consisting of a meaningful comparison of surface albedo derived from observations acquired at a 20 year interval by sensors with different radiometric performances. In particular, it is shown how it is possible to assess the magnitude of minimum detectable significant surface albedo change.
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Consistency of surface anisotropy characterization with Meteosat observations
Advances in Space Research, 2007Co-Authors: Alessio Lattanzio, Yves Govaerts, Bernard PintyAbstract:Abstract The purpose of this paper is to present the results of the evaluation of the Meteosat Surface Albedo (MSA) product, including the effects due to instrument changes and associated calibration uncertainties. To this end, observations acquired by two adjacent geostationary spacecrafts, Meteosat-7 and Meteosat-5 have been processed with the MSA algorithm. These satellites are located, respectively, at 0° and 63° East. Data acquired by these two instruments overlap over a large area encompassing most of Africa and the Arabian peninsula. The consistency of the surface anisotropy retrieval is evaluated through a reconstruction of the Meteosat-5 (-7) observations with the Meteosat-7 (-5) surface anisotropy characterization. Some differences slightly higher than the calibration accuracy have been found. This effect has no significant impact on the albedo retrieval which indicates that MSA is a reliable algorithm to produce albedo datasets.
J. Schmetz - One of the best experts on this subject based on the ideXlab platform.
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Comparisons of Upper Tropospheric Humidity Retrievals from TOVS and Meteosat
2014Co-Authors: C. Escoffier, J. Bates, A. Chsdin, W. B. Rossow, J. SchmetzAbstract:Abstract. Two different methodsfor retrieving Upper TroposphericHumidities (UTH) from the TOVS (TIROS Operational Vertical Sounder) instruments aboard NOAA polar orbiting satellites are presentedand compared. The first one, from the Environmental TechnologyLaboratory, computed by J. Bates and D. Jackson (hereafter BJ method), estimatesUTH from a simplified radiative transfer analysisof the upper tropospheric infrared water vapor channelat wavelengthmeasuredby HIRS (6.3gm). The secondone results from a neural network analysisof the TOVS (HIRS and MSU) data developedat the Laboratoire de MeteorologieDynamique (hereafterthe 3I (Improved Initialization Inversion)method). Although the two methods give very similar retrievals in t,emperateregions(30-60°Nand S), an absolutebias up to 16c7c, appearsin the convectivezoneof the tropics. The two datasetshavealsobeencompared with UTH retrievals from infrared radiancemeasurementsin the 6.3 m channel from the geostationary satellite Meteosat (hereafter MET method). The Meteosat retrievals are systematically drier than the TOVS-based results by an absolute bias between 5 and 25_,. Despite the biases, the spatial and temporal correlations are very good. The purpose of this study is to explain the deviations observed between the three datasets. The sensitivity of UTH to air temperature and humidity profiles is analysed as are the clouds effects. Overall, the comparison of the three retrievals gives an assessement of the current uncertainties in water vapor amounts in the upper troposphere as determined from NOAA and Meteosat satellites. 1
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Technical note: Quantitative monitoring of a Saharan dust event with SEVIRI on Meteosat-8
International Journal of Remote Sensing, 2007Co-Authors: Peng Zhang, J. Schmetz, Timothy J Schmit, W. P. MenzelAbstract:An algorithm has been developed to quantitatively retrieve dust properties (identification, optical thickness, particle radius, and dust density) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard Meteosat-8, the first of the Meteosat Second Generation (MSG). Two SEVIRI thermal infrared (IR) window channels (10.8 µm and 12 µm) were used to monitor the dust event of 3 March 2004 over the Sahara in northern Africa. The identification and evolution of dust are well depicted by SEVIRI data with high spatial resolution (approximately 3 km) and high temporal resolution (15 minutes). This demonstrates the capability of a geostationary advanced imager to monitor dust events over land, their migration and the corresponding air quality.
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Quantitative monitoring of a Saharan dust event with SEVIRI on Meteosat-8
International Journal of Remote Sensing, 2007Co-Authors: Peng Zhang, J. Schmetz, Timothy J Schmit, W. P. MenzelAbstract:An algorithm has been developed to quantitatively retrieve dust properties (identification, optical thickness, particle radius, and dust density) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard Meteosat-8, the first of the Meteosat Second Generation (MSG). Two SEVIRI thermal infrared (IR) window channels (10.8 μm and 12μm) were used to monitor the dust event of 3 March 2004 over the Sahara in northern Africa. The identification and evolution of dust are well depicted by SEVIRI data with high spatial resolution (approximately 3 km) and high temporal resolution (15 minutes). This demonstrates the capability of a geostationary advanced imager to monitor dust events over land, their migration and the corresponding air quality.
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an introduction to Meteosat second generation msg
Bulletin of the American Meteorological Society, 2002Co-Authors: J. Schmetz, Stephen Tjemkes, Sergio Rota, Paolo Pili, Dieter Just, Jochen Kerkmann, Alain RatierAbstract:This paper introduces the new generation of European geostationary meteorological satellites, Meteosat Second Generation (MSG), scheduled for launch in summer 2002. MSG is spin stabilized, as is the current Meteosat series, however, with greatly enhanced capabilities. The 12-channel imager, called the Spinning Enhanced Visible and Infrared Imager (SEVIRI), observes the full disk of the earth with an unprecedented repeat cycle of 15 min. SEVIRI has eight channels in the thermal infrared (IR) at 3.9,6.2,7.3, 8.7, 9.7, 10.8, 12.0, and 13.4 μum; three channels in the solar spectrum at 0.6, 0.8, and 1.6 μm; and a broadband high-resolution visible channel. The high-resolution visible channel has a spatial resolution of 1.67 km at nadir; pixels are oversampled with a factor of 1.67 corresponding to a sampling distance of 1 km at nadir. The corresponding values for the eight thermal IR and the other three solar channels are 4.8-km spatial resolution at nadir and an oversampling factor of 1.6, which corresponds to...
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Comparison of upper tropospheric humidity retrievals from TOVS and Meteosat
Journal of Geophysical Research: Atmospheres, 2001Co-Authors: C. Escoffier, W. B. Rossow, John J. Bates, A Chedin, J. SchmetzAbstract:Two different methods for retrieving upper tropospheric humidity (UTH) from the TIROS Operational Vertical Sounder (TOVS) instruments aboard NOAA polar orbiting satellites are presented and compared. The first one, from the Environmental Technology Laboratory, computed by J. J. Bates and D. L. Jackson, estimates UTH from a simplified radiative transfer analysis of the upper tropospheric infrared water vapor channel at 6.7 μm wavelength measured by High-resolution Infrared Radiation Sounder (HIRS). The second one results from a neural network analysis of the TOVS (HIRS and Microwave Sounding Unit (MSU)) data developed at the Laboratoire de Meteorologie Dynamique. Although the two methods give very similar retrievals in temperate regions (30°–60°N and S), the latter is larger by up to 16% in the tropics. The two data sets have also been compared with the UTH retrievals from infrared radiance measurements at 6.3 μm wavelength from the geostationary satellite Meteosat. These products are taken from the archive without any reprocessing that would take care of known biases. Since the Meteosat UTH in 1989 was confined to clear-sky areas, it has a dry bias. The differences observed among the three data sets can be explained. UTH computation is sensitive to assumed air temperature and humidity profiles. Despite the biases the spatial and temporal correlations are very good. Overall, the comparison of the two TOVS retrievals provides an assessment of the UTH uncertainties, about 15–25% (relative). With regard to the Meteosat UTH it is concluded that the archived product performs well in depicting spatial and temporal changes. For future quantitative analyses, a reprocessing of the Meteosat UTH is suggested.
R. Mullen - One of the best experts on this subject based on the ideXlab platform.
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Meteosat seviri fire radiative power frp products from the land surface analysis satellite applications facility lsa saf part 1 algorithms product contents and analysis
Atmospheric Chemistry and Physics, 2015Co-Authors: Martin J Wooster, P. H. Freeborn, R. Beeby, G. Roberts, Y. Govaerts, A Lattanzio, R. MullenAbstract: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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LSA SAF Meteosat FRP products-Part 1: Algorithms, product contents, and analysis
Atmospheric Chemistry and Physics, 2015Co-Authors: Martin J Wooster, P. H. Freeborn, R. Beeby, D Fisher, Jian He, G. Roberts, Alessio Lattanzio, Y. Govaerts, R. MullenAbstract: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).
Martin J Wooster - One of the best experts on this subject based on the ideXlab platform.
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Meteosat seviri fire radiative power frp products from the land surface analysis satellite applications facility lsa saf part 1 algorithms product contents and analysis
Atmospheric Chemistry and Physics, 2015Co-Authors: Martin J Wooster, P. H. Freeborn, R. Beeby, G. Roberts, Y. Govaerts, A Lattanzio, R. MullenAbstract: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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LSA SAF Meteosat FRP products-Part 1: Algorithms, product contents, and analysis
Atmospheric Chemistry and Physics, 2015Co-Authors: Martin J Wooster, P. H. Freeborn, R. Beeby, D Fisher, Jian He, G. Roberts, Alessio Lattanzio, Y. Govaerts, R. MullenAbstract: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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Fire Detection and Fire Characterization Over Africa Using Meteosat SEVIRI
IEEE Transactions on Geoscience and Remote Sensing, 2008Co-Authors: Gareth J. Roberts, Martin J WoosterAbstract:Africa is the single largest continental source of biomass burning emissions and one where emission source strengths are characterized by strong diurnal and seasonal cycles. This paper describes the development of a fire detection and characterization algorithm for generating high temporal resolution African pyrogenic emission data sets using data from the geostationary spinning enhanced visible and infrared imager (SEVIRI). The algorithm builds on a prototype approach tested previously with preoperational SEVIRI data and utilizes both spatial and spectral detection methods whose thresholds adapt contextually within and between imaging slots. Algorithm validation is carried out via comparison to data from ~800 temporally coincident moderate resolution imaging spectroradiometer (MODIS) scenes, and performance is significantly improved over the prior algorithm version, particularly in terms of detecting low fire radiative power (FRP) signals. On a per-fire basis, SEVIRI shows a good agreement with MODIS in terms of FRP measurement, with a small (3.7 MW) bias. In comparison to regional-scale total FRP derived from MODIS, SEVIRI underestimates this by, on average, 40% to 50% due to the nondetection of many low-intensity fire pixels (FRP < 50 MW). Frequency-magnitude analysis can be used to adjust fire radiative energy estimates for this effect, and taking this and other adjustments into account, SEVIRI-derived fuel consumption estimates for southern Africa from July to October 2004 are 259-339 Tg, with emission intensity peaking after midday and reducing by more than an order of magnitude each night.
Cyril Moulin - One of the best experts on this subject based on the ideXlab platform.
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toms and Meteosat satellite records of the variability of saharan dust transport over the atlantic during the last two decades 1979 1997
Geophysical Research Letters, 2002Co-Authors: Isabelle Chiapello, Cyril MoulinAbstract:[1] We combined aerosol observations of TOMS/Nimbus-7 (1979–1993) and Meteosat/VIS (1984–1997) to investigate the variability of Saharan dust transport over the Atlantic over nearly 20 years. We first used three years (1986–1988) of coincident daily Meteosat images over the northern tropical Atlantic (15–30°N, 5–30°W) to convert the TOMS semi-quantitative index into dust optical thickness by means of two (“winter” and “summer”) linear relationships. We then processed the whole TOMS/Nimbus-7 archive and found that both seasonal and interannual variability of the mean dust optical thickness over the Atlantic retrieved by TOMS and Meteosat are consistent. This consistency offers an unique opportunity to monitor the export of Saharan dust over the Atlantic during the last two decades. This analysis provides the first evidence of the high year-to-year variability of dust transport during winter, and confirms the importance of meteorological factors, through the North Atlantic Oscillation, in affecting its occurrence at this season.
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long term daily monitoring of saharan dust load over ocean using Meteosat isccp b2 data 1 methodology and preliminary results for 1983 1994 in the mediterranean
Journal of Geophysical Research, 1997Co-Authors: Cyril Moulin, Francois Dulac, F Guillard, Claude LambertAbstract:In this paper we describe a method to perform an accurate long-term monitoring of the optical thickness and mass column density of airborne desert dust over the Atlantic and the Mediterranean using Meteosat wideband solar (visible (VIS) plus near infrared) sensor. The dust load is retrieved using aerosol models and an Earth-atmosphere radiative transfer model. The method focuses on multiyear (from 1983 to 1994) daily retrieval of the atmospheric dust load using Meteosat low-resolution images prepared for the International Satellite Cloud Climatology Project (B2 format). We account for the variable calibrations, radiometric sensitivities, and spectral bands of the successive sensors (Meteosat 2 to Meteosat 5) as well as for the presence of marine background and stratospheric aerosols. We discuss the sensitivity of the method to different factors, and its accuracy is assessed in a companion paper. The results obtained include the daily geographical distribution of the dust load and the temporal variation of the dust load over marine areas. We illustrate and briefly discuss the results for the western Mediterranean and particularly for the Dynamique des Flux Atmospheriques en Mdditerrande (DYFAMED) marine station in the Ligurian Sea. The dust transport mainly takes place during summer in this area. More than half a million metric tons of suspended dusts are occasionally observed over the western Mediterranean, and we observed an average of 16 dust events per year. At DYFAMED station the 11.5-year mean dust optical thickness is 0.11, with annual means ranging from 0.055 in 1985 to 0.19 in 1992.
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long term 1983 1994 calibration of the Meteosat solar vis channel using desert and ocean targets
International Journal of Remote Sensing, 1996Co-Authors: Cyril Moulin, Claude Lambert, J Poitou, Francois DulacAbstract:Abstract The successive operational Meteosat solar (VIS) sensors have shown significant variations of their spectral band which affected their relative sensitivities to the light scattering by aerosols, molecules and Earth surface. This paper provides a calibration of the various Meteosat VIS sensors used between June 1983, the beginning of data archiving for the International Satellite Cloud Climatology Project (ISCCP), and December 1994, taking into account the characteristics of their individual spectral band thanks to an atmospheric radiative transfer model. The method is based on a monitoring of the reflectance of desert and ocean targets free of clouds and aerosols, and relies on the absolute vicarious calibration of Meteosat-2 performed in late 1981. We find different sensitivities and temporal evolutions for Meteosat-2, -3, -4, and -5, and our results compare well with other more limited calibration studies
