Digging the METEOSAT Treasure - 3 Decades of Solar Surface Radiation

Solar surface radiation data of high quality is essential for the appropriate monitoring and analysis of the Earth's radiation budget and the climate system. Further, they are crucial for the efficient planning and operation of solar energy systems. However, well maintained surface measurements are rare in many regions of the world and over the oceans. There, satellite derived information is the exclusive observational source. This emphasizes the important role of satellite based surface radiation data. Within this scope, the new satellite based CM-SAF SARAH (Solar surfAce RAdiation Heliosat) data record is discussed as well as the retrieval method used. The SARAH data are retrieved with the sophisticated SPECMAGIC method, which is based on radiative transfer modeling. The resulting climate data of solar surface irradiance, direct irradiance (horizontal and direct normal) and clear sky irradiance are covering 3 decades. The SARAH data set is validated with surface measurements of the Baseline Surface Radiation Network (BSRN) and of the Global Energy and Balance Archive (GEBA). Comparison with BSRN data is performed in order to estimate the accuracy and precision of the monthly and daily means of solar surface irradiance. The SARAH solar surface irradiance shows a bias of 1.3 \(W/m^2\) and a mean absolute bias (MAB) of 5.5 \(W/m^2\) for monthly means. For direct irradiance the bias and MAB is 1 \(W/m^2\) and 8.2 \(W/m^2\) respectively. Thus, the uncertainty of the SARAH data is in the range of the uncertainty of ground based measurements. In order to evaluate the uncertainty of SARAH based trend analysis the time series of SARAH monthly means are compared to GEBA. It has been found that SARAH enables the analysis of trends with an uncertainty of 1 \(W/m^2/dec\); a remarkable good result for a satellite based climate data record. SARAH has been also compared to its legacy version, the satellite based CM-SAF MVIRI climate data record. Overall, SARAH shows a significant higher accuracy and homogeneity than its legacy version. With its high accuracy and temporal and spatial resolution SARAH is well suited for regional climate monitoring and analysis as well as for solar energy applications.

[1]  Taiping Zhang,et al.  Assessment of BSRN radiation records for the computation of monthly means , 2010 .

[2]  Alexander Loew,et al.  Combined evaluation of MPI‐ESM land surface water and energy fluxes , 2012 .

[3]  C. Brühl,et al.  Intercomparison of Stratospheric Chemistry Models under Polar Vortex Conditions , 2003 .

[4]  Johannes W. Kaiser,et al.  Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System : Forward modeling , 2009 .

[5]  N. Loeb,et al.  Surface Irradiances Consistent With CERES-Derived Top-of-Atmosphere Shortwave and Longwave Irradiances , 2013 .

[6]  Andrew K. Skidmore,et al.  A comparison of data sources for creating a long-term time series of daily gridded solar radiation for Europe , 2014 .

[7]  William B. Rossow,et al.  Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets: 2. Validation and first results , 1995 .

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

[9]  E. Shettle.  Models of aerosols, clouds, and precipitation for atmospheric propagation studies , 1990 .

[10]  R. Pinker,et al.  Modeling Surface Solar Irradiance for Satellite Applications on a Global Scale , 1992 .

[11]  Uwe Pfeifroth,et al.  Towards Optimal Aerosol Information for the Retrieval of Solar Surface Radiation Using Heliosat , 2015 .

[12]  Michel Journée,et al.  Solar resource assessment in the Benelux by merging Meteosat-derived climate data and ground measurements , 2012 .

[13]  Thomas A. Huld,et al.  A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation , 2014, Remote. Sens..

[14]  松山 洋.  「Statistical Methods in the Atmospheric Sciences(2nd edition), International Geophysics Series 91」, Daniel S. Wilks著, Academic Press, 2005年11月, 648頁, $94.95, ISBN978-0-12-751966-1(本だな) , 2010 .

[15]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

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

[17]  Christophe Vernay,et al.  Review of Satellite-based Surface Solar Irradiation Databases for the Engineering, the Financing and the Operating of Photovoltaic Systems☆ , 2014 .

[18]  R. Kuhlemann,et al.  Rethinking satellite-based solar irradiance modelling: The SOLIS clear-sky module , 2004 .

[19]  Martin Wild,et al.  Decadal changes in shortwave irradiance at the surface in the period from 1960 to 2000 estimated from Global Energy Balance Archive Data , 2009 .

[20]  Gary G. Gibson,et al.  A Climatology of Surface Radiation Budget Derived from Satellite Data , 1999 .

[21]  Jan Cornelis,et al.  Spectral Aging Model Applied to Meteosat First Generation Visible Band , 2014, Remote. Sens..

[22]  J. Schmetz,et al.  AN INTRODUCTION TO METEOSAT SECOND GENERATION (MSG) , 2002 .

[23]  R. Mueller,et al.  RETHINKING SATELLITE BASED SOLAR IRRADIANCE MODELLING , 2003 .

[24]  E. Raschke,et al.  Incident Solar Radiation over Europe Estimated from METEOSAT Data. , 1984 .

[25]  A. Belward,et al.  The IGBP-DIS global 1km land cover data set, DISCover: First results , 1997 .

[26]  D. Dee,et al.  Variational bias correction of satellite radiance data in the ERA‐Interim reanalysis , 2009 .

[27]  Thomas R. Loveland,et al.  USING MULTISOURCE DATA IN GLOBAL LAND-COVER CHARACTERIZATION: CONCEPTS, REQUIREMENTS, AND METHODS , 1993 .

[28]  A. Evan,et al.  Arguments against a physical long‐term trend in global ISCCP cloud amounts , 2007 .

[29]  K. Stamnes,et al.  Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. , 1988, Applied optics.

[30]  R. A. Roebeling,et al.  Estimating surface solar irradiance from METEOSAT SEVIRI-derived cloud properties , 2008 .

[31]  M. Razinger,et al.  Aerosol analysis and forecast in the European Centre for Medium‐Range Weather Forecasts Integrated Forecast System: 2. Data assimilation , 2009 .

[32]  L. Wald,et al.  The method Heliosat-2 for deriving shortwave solar radiation from satellite images , 2004 .

[33]  H. Beyer,et al.  Solar energy assessment using remote sensing technologies , 2003 .

[34]  Robert Pitz-Paal,et al.  Direct normal irradiance related definitions and applications: The circumsolar issue , 2014 .

[35]  B. McArthur,et al.  Baseline surface radiation network (BSRN/WCRP) New precision radiometry for climate research , 1998 .

[36]  Nancy A. Ritchey,et al.  Seasonal variation of surface radiation budget derived from International Satellite Cloud Climatology Project C1 data , 1992 .

[37]  Michael G. Bosilovich,et al.  Intercomparison of water and energy budgets for five Mississippi subbasins between ECMWF reanalysis (ERA‐40) and NASA Data Assimilation Office fvGCM for 1990–1999 , 2003 .

[38]  Charles N. Long,et al.  An Automated Quality Assessment and Control Algorithm for Surface Radiation Measurements , 2008 .

[39]  Annette Hammer,et al.  A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands , 2012, Remote. Sens..

[40]  Christine Träger-Chatterjee,et al.  Brief Accuracy Assessment of Aerosol Climatologies for the Retrieval of Solar Surface Radiation , 2014, ATMOS 2014.

[41]  R. Dickinson.  Land Surface Processes and Climate—Surface Albedos and Energy Balance , 1983 .

[42]  R. Roebeling,et al.  Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF) , 2008 .

[43]  Bernhard Mayer,et al.  Atmospheric Chemistry and Physics Technical Note: the Libradtran Software Package for Radiative Transfer Calculations – Description and Examples of Use , 2022 .

[44]  F. Kasten,et al.  An operational estimate of global solar irradiance at ground level from METEOSAT data: results from 1985 to 1987 , 1988 .

[45]  R. Hollmann,et al.  The CM-SAF operational scheme for the satellite based retrieval of solar surface irradiance - a LUT based eigenvector hybrid approach. , 2009 .

[46]  W. Collins,et al.  An AeroCom Initial Assessment - Optical Properties in Aerosol Component Modules of Global Models , 2005 .

[47]  B. Bonnel,et al.  Thermal Impact of Saharan Dust over Land. Part I: Simnulation , 1992 .

[48]  E. Shettle,et al.  Models of the atmospheric aerosols and their optical properties , 1976 .

[49]  James K. B. Bishop,et al.  Spatial and temporal variability of global surface solar irradiance , 1991 .

[50]  Johannes Quaas,et al.  Estimates of aerosol radiative forcing from the MACC re-analysis , 2012 .

[51]  Yves M. Govaerts,et al.  Operational calibration of the Meteosat radiometer VIS band , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[52]  Jörg Trentmann,et al.  Remote sensing of solar surface radiation for climate monitoring — the CM-SAF retrieval in international comparison , 2012 .

[53]  Christian A. Gueymard,et al.  Temporal variability in direct and global irradiance at various time scales as affected by aerosols , 2012 .

[54]  J. Olseth,et al.  An hourly diffuse fraction model with correction for variability and surface albedo , 1998 .

[55]  Lucien Wald,et al.  Simulating Meteosat-7 broadband radiances using two visible channels of Meteosat-8 , 2006 .

[56]  Richard Müller,et al.  The Role of the Effective Cloud Albedo for Climate Monitoring and Analysis , 2011, Remote. Sens..

[57]  P. Ineichen,et al.  A new operational model for satellite-derived irradiances: description and validation , 2002 .

[58]  Richard Müller,et al.  Spatial and Temporal Homogeneity of Solar Surface Irradiance across Satellite Generations , 2011, Remote. Sens..

[59]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[60]  M. Wild,et al.  Spatial representativeness of ground‐based solar radiation measurements , 2013 .

[61]  K. Moffett,et al.  Remote Sens , 2015 .

[62]  Kai Zhang,et al.  MAC‐v1: A new global aerosol climatology for climate studies , 2013 .

[63]  Flurin Babst,et al.  Verification of NCEP Reanalysis Shortwave Radiation With Mesoscale Remote Sensing Data , 2008, IEEE Geoscience and Remote Sensing Letters.

[64]  Martin Wild,et al.  Validation and stability assessment of the monthly mean CM SAF surface solar radiation dataset over Europe against a homogenized surface dataset (1983–2005) , 2013 .

[65]  Steven Dewitte,et al.  The satellite application facility on climate monitoring , 2002 .

[66]  Mark A. Liniger,et al.  A surface radiation climatology across two Meteosat satellite generations , 2013 .

[67]  J. Schmetz,et al.  Supplement to An Introduction to Meteosat Second Generation (MSG): SEVIRI CALIBRATION , 2002 .

[68]  A. Kazantzidis,et al.  The aerosol effect on direct normal irradiance in Europe under clear skies , 2014 .

[69]  E. Clothiaux,et al.  The k-distribution method and correlated-k approximation for a shortwave radiative transfer model. , 1999 .

[70]  R. Müller,et al.  A new solar radiation database for estimating PV performance in Europe and Africa , 2012 .

[71]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .