A new operational model for satellite-derived irradiances: description and validation

Perez, Richard; Ineichen, Pierre; Moore, Kathy; Kmiecik, Marek; Chain, Cyril; George, R.; Vignola, Frank

doi:10.1016/s0038-092x(02)00122-6

Cited by 547 publications

(230 citation statements)

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“…A detailed discussion of these data sets would be out of the scope of this publication and interested readers are referred to the respective review article [15]. Various algorithms have been developed to generate surface solar radiation data sets covering different approaches (e.g., [14,[16][17][18][19][20][21][22][23]). To the knowledge of the authors SARAH is currently the only climate data record which is retrieved by application of a method that treats the radiation spectrally resolved based on a eigenvector hybrid approach [24].…”

Section: Introductionmentioning

confidence: 99%

Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation

et al. 2015

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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.

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Section: Introductionmentioning

confidence: 99%

Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation

et al. 2015

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“…The strategy for determining ρ g is rather important to the CSU. A better description of its behavior over time as proposed by Hammer (2000), Perez et al (2002), Zelenka (2003) …”

Section: Discussionmentioning

confidence: 99%

“…The uncertainty in z is particularly easy to reduce with the aid of geographic information systems, which are increasingly accurate and compatible with all information systems. The uncertainty in ρ g comes from the difficulty in assessing it from a time-series of reflectances for mixed cases of clear and cloudy skies (Cano et al, 1986;Diabaté et al, 1988;Stuhlmann et al 1990;Perez et al, 2002;Rigollier et al, 2004). In addition, the assessment strategy plays a role in the uncertainty, as discussed by Lefèvre et al (2007), who select only one ρ g per month, although this can vary more rapidly (Diabaté et al, 1989a).…”

Section: Combined Standard Uncertainty Of Heliosat-2mentioning

confidence: 99%

“…Geostationary meteorological satellites, which record several images of the same terrestrial zone per hour, provide a very good means of estimating SSI (e.g., Perez et al, 2002 for the GOES satellite; Beyer et al, 1996;Rigollier et al, 2004 for Meteosat). The Heliosat method is one of the most precise methods for estimating SSI from satellite data (Grüter et al, 1986;Raschke et al, 1991).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the influences of uncertainties in input variables on the outcomes of the Heliosat-2 method

et al. 2009

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The Heliosat-2 method, which employs satellite images to assess solar irradiance at ground level, is one of the most accurate among the available operational methods. Its input variables have uncertainties which impact on the final result. The General Law of Uncertainty Propagation is employed to analyze the impact of these uncertainties on a single pixel with Meteosat-7 inputs in various stages, beginning with the sensitivity coefficients and the changes induced in the clear-sky index (KC) by each independent variable. Once these coefficients are known, the partial combined standard uncertainty (CSU) is calculated for KC from each independent variable and albedo. Finally, the total CSU of KC is calculated.All of the results are in agreement and show that the most influential variables in the uncertainty of estimation of cloudy skies are, in this order, the Linke turbidity factor (54% of KC value), terrain elevation (33%), the calibration coefficient of the satellite sensor (13%) and the ground albedo (5%). What causes the initial uncertainty in the ground albedo is its variation over time and the difficulty in assessing it from a reflectance time-series for mixed clear and cloudy skies. The Linke turbidity factor is the most influential variable on the width of the uncertainty interval, not only because of its own uncertainty (17% in this study), but because it is also used in numerous intermediate calculations. For clear skies, the partial CSUs are considerably lower, except for ground albedo (5% also). Total irradiance in the visible channel of the satellite sensor (W m -2 ), which is the result of the convolution of the spectral distribution of the solar constant by the radiometer spectral sensitivity curve Keywords

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“…A number of models have been developed to estimate DSSR distributions on Earth using polar-orbiting or geostationary satellites on horizontal surfaces at various spatial resolutions (Journee and Bertrand, 2010). Three different approaches are available to estimate solar radiation from satellite data: (i) statistical modeling, such as the HELISOAT model for the Meteosat satellite (Rigollier et al, 2004) and the cloud index deriving based model (Perez et al, 2002); (ii) physical modeling using a complicated radiative transfer model (Kim and Liang, 2010); and (iii) parameterized radiative transmittance model (Yang et al, 2006b). Most satellite radiation models can generate daily irradiation with relatively high accuracy compared to ground-based pyranometer data.…”

Section: Introductionmentioning

confidence: 99%

Estimating global solar radiation using a hybrid parametric model from MODIS data over the Tibetan Plateau

Zhang

Xin

et al. 2015

Solar Energy

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The Tibetan Plateau plays an important role in global atmospheric circulation with its complex terrain. The downward surface shortwave radiation (DSSR) can be obtained from remote sensing data because of its sparse observations and rugged surface. In this paper, a satellite-based scheme is presented to retrieve all-sky downward surface shortwave radiation, which links a look-up table algorithm and satellite images. The look-up table for clear sky and cloudy sky was created separately using a comprehensive 1D physically based radiative transfer model SBDART to achieve a higher computational accuracy and efficiency compared to the comprehensive radiative transfer model. The estimated DSSR was validated using one year pyranometer measurements from 8 stations in the Tibetan Plateau and compared with GEWEX-SRB data with 1°spatial resolution. The result shows that the largest root mean square error was 60 W/m 2 (32%) at Guoluo station, and the least root mean square error was 13 W/m 2 (13%) at Golmud station. The bias was larger in summer and smaller in winter, which may be caused by uncertainties in the assumption from the 1D radiative transfer model and MODIS cloud properties product for broken and inhomogeneous clouds. The algorithm we proposed can be applied globally without local calibration because it is independent of climate and the surface elevation.

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A new operational model for satellite-derived irradiances: description and validation

Cited by 547 publications

References 10 publications

Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation

Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation

Analysis of the influences of uncertainties in input variables on the outcomes of the Heliosat-2 method

Estimating global solar radiation using a hybrid parametric model from MODIS data over the Tibetan Plateau

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