An Advanced Model for the Estimation of the Surface Solar Irradiance Under All Atmospheric Conditions Using MSG/SEVIRI Data

A new advanced model for estimation of surface solar irradiance from satellite (AMESIS), designed to estimate with better accuracy the incident solar radiation at the surface from the spinning enhanced visible and infrared imager (SEVIRI) satellite measurements, has been developed. The new generations of sensors such as SEVIRI payload on board the geostationary meteosat second generation gives an opportunity to improve the solar irradiance estimation at surface with accuracy as well as the high spatial and time resolution for a large geographical area according to the needs of solar energy applications. The model developed takes into account the effect of aerosol, the overcast and partially cloudy coverage, and provides irradiance solar maps every 15 min both for monitoring purposes and for monthly, annual averages of surface solar irradiance. Cloud and aerosol microphysical parameters are retrieved by using VIS and IR SEVIRI channels, while surface solar irradiance is retrieved through the high-resolution broadband visible channel. Comparisons with the Global Atmosphere Watch station ground-based measurements of incoming solar radiation agree with the values retrieved with AMESIS model. The results show a very good correlation of about 0.99, a root mean square and a bias ranging, respectively, between 1 and 2.7 J/cm2 and -0.6 and 0.4 J/cm2 depending on the station.

[1]  Eva Borbas,et al.  Development of a Global Infrared Land Surface Emissivity Database for Application to Clear Sky Sounding Retrievals from Multispectral Satellite Radiance Measurements , 2008 .

[2]  T. Aoki,et al.  Estimation of the precipitable water from the IR channel of the geostationary satellite , 1982 .

[3]  Didier Tanré,et al.  Remote sensing of aerosols over the oceans using MSG/SEVIRI imagery , 2005 .

[4]  M. Desbois,et al.  The Potential of Infrared Satellite Data for the Retrieval of Saharan-Dust Optical Depth over Africa. , 1989 .

[5]  P. Koepke,et al.  Optical Properties of Aerosols and Clouds: The Software Package OPAC , 1998 .

[6]  Stuart A. Young,et al.  Identification of the Mount Hudson volcanic cloud over SE Australia , 1992 .

[7]  Keith Sharp,et al.  Calculation of monthly average insolation on a shaded surface at any tilt and azimuth , 1982 .

[8]  Richard Perez,et al.  COMPARING SATELLITE REMOTE SENSING AND GROUND NETWORK MEASUREMENTS FOR THE PRODUCTION OF SITE/TIME SPECIFIC IRRADIANCE DATA , 1997 .

[9]  L. Larrabee Strow,et al.  Infrared dust spectral signatures from AIRS , 2006 .

[10]  Larry M. McMillin,et al.  Estimation of sea surface temperatures from two infrared window measurements with different absorption , 1975 .

[11]  Piet Stammes,et al.  Simulation study of the aerosol information content in OMI spectral reflectance measurements , 2007 .

[12]  Lars Klüser,et al.  Remote sensing of mineral dust over land with MSG infrared channels: A new Bitemporal Mineral Dust Index , 2009 .

[13]  Jean-Claude Roger,et al.  Atmospheric correction over land for MERIS , 1999 .

[14]  C. Gautier,et al.  A Simple Physical Model to Estimate Incident Solar Radiation at the Surface from GOES Satellite Data , 1980 .

[15]  J. D. Tarpley Estimating Incident Solar Radiation at the Surface from Geostationary Satellite Data , 1979 .

[16]  Larry M. McMillin,et al.  Retrieval of Precipitable Water from Observations in the Split Window over Varying Surface Temperatures , 1990 .

[17]  S. Ackerman Remote sensing aerosols using satellite infrared observations , 1997 .

[18]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[19]  Alain Chedin,et al.  Dust altitude and infrared optical depth from AIRS , 2004 .

[20]  R. Perez,et al.  Effective Accuracy of Satellite-Derived Hourly Irradiances , 1999 .

[21]  T. Nakajima,et al.  Wide-Area Determination of Cloud Microphysical Properties from NOAA AVHRR Measurements for FIRE and ASTEX Regions , 1995 .

[22]  Catherine Gautier,et al.  SBDART: A Research and Teaching Software Tool for Plane-Parallel Radiative Transfer in the Earth's Atmosphere. , 1998 .

[23]  Peng Zhang,et al.  Identification and physical retrieval of dust storm using three MODIS thermal IR channels , 2006 .

[24]  Vincenzo Cuomo,et al.  A Technique for Classifying Uncertain MOD35/MYD35 Pixels Through Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager Observations , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[25]  Z. Wan,et al.  Quality assessment and validation of the MODIS global land surface temperature , 2004 .

[26]  A. Ohmura,et al.  First global WCRP shortwave surface radiation budget dataset , 1995 .

[27]  E. Vermote,et al.  Second‐generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance , 2007 .

[28]  V. Cuomo,et al.  Multilayered cloud parameters retrievals from combined infrared and microwave satellite observations , 2007 .

[29]  F. Maignan,et al.  Remote sensing of aerosols over land surfaces from POLDER‐ADEOS‐1 polarized measurements , 2001 .

[30]  G. Leeuw,et al.  AEROSOL RETRIEVALS OVER LAND AND SEA SURFACES USING COMBINED SATELLITE MEASUREMENTS FROM MSG-SEVIRI AND ENVISAT-AATSR , 2007 .

[31]  Daryl R. Myers,et al.  Solar Radiation Modeling and Measurements for Renewable Energy Applications: Data and Model Quality , 2004 .

[32]  A. Louche,et al.  Utilization of meteosat satellite-derived radiation data for integration of autonomous photovoltaic solar energy systems in remote areas , 1998 .

[33]  M. Romaguera,et al.  Land surface temperature retrieval from MSG1-SEVIRI data , 2004 .

[34]  M. Romaguera,et al.  Water‐vapour retrieval from Meteosat 8/SEVIRI observations , 2008 .

[35]  Stefan Heise,et al.  Total water vapor column retrieval from MSG-SEVIRI split window measurements exploiting the daily cycle of land surface temperatures , 2008 .

[36]  Filomena Romano,et al.  Physical and statistical approaches for cloud identification using Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager Data , 2008 .

[37]  H. Guillard,et al.  A method for the determination of the global solar radiation from meteorological satellite data , 1986 .

[38]  E. Carboni GOME aerosol optical depth retrieval over ocean: Correcting for the effects of residual cloud contamination , 2006 .

[39]  A. Lacis,et al.  Near-Global Survey of Effective Droplet Radii in Liquid Water Clouds Using ISCCP Data. , 1994 .

[40]  M. King,et al.  Determination of the optical thickness and effective particle radius of clouds from reflected solar , 1990 .

[41]  W. Wiscombe The Delta–M Method: Rapid Yet Accurate Radiative Flux Calculations for Strongly Asymmetric Phase Functions , 1977 .

[42]  Stefan Wunderle,et al.  Remote sensing of aerosol optical depth over central Europe from MSG-SEVIRI data and accuracy assessment with ground-based AERONET measurements , 2007 .

[43]  E. Vermote,et al.  The MODIS Aerosol Algorithm, Products, and Validation , 2005 .

[44]  Graeme Kelly,et al.  A satellite radiance‐bias correction scheme for data assimilation , 2001 .

[45]  A. Prata Land surface temperatures derived from the advanced very high resolution radiometer and the along‐track scanning radiometer: 1. Theory , 1993 .

[46]  J. Schmetz,et al.  Technical note: Quantitative monitoring of a Saharan dust event with SEVIRI on Meteosat‐8 , 2007 .

[47]  Peter R. J. North,et al.  Aerosol optical depth and land surface reflectance from multiangle AATSR measurements: global validation and intersensor comparisons , 2006, IEEE Transactions on Geoscience and Remote Sensing.