Potentials of images from geostationary satellite for the assessment of solar energy parametersReport as inadecuate

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1 CEP-Sophia CEP - Centre Énergétique et Procédés

Abstract : Images taken by meteorological geostationary satellites are currently used to map global radiation. Several methods exist which process these images. Among them, the Heliosat method ranks as one of the most accurate and one of the easiest to use. Typical uncertainties rms. of such assessment are about 10 % for the monthly mean global irradiance on the ground, about 10 % for the daily value, and about 20 % for the hourly value. Use of ground measurements and proper processing e. g. kriging increase the accuracy of the estimates in global radiation. Splitting the global radiation into its direct and diffuse components is not currently made on an operational basis. This requires additional information, such as turbidity in clear skies and geometrical and optical properties of the clouds, which is not available from the current geostationary satellites. However, some methods have been proposed which make use of the sole satellite data and which rely on assumptions replacing the missing information. In assessing the components of the global radiation, one should take care of the space-time scales he is dealing with: they are of paramount importance in designing a method, of its usefulness, as well as in the evaluation of its accuracy. It is emphasized that satellite images are measurements taken by a radiometer and as such obey the theory of signal processing, particularly space-time sampling constraints. The application of such images and of their processing is limited to time scales equal or greater than 1 hour, and to space scale equal or greater than two pixels about 20 km. Therefore, we cannot treat the case of fragmented cloud coverage, unless additional external information is available. An important aspect to be taken into account when satellite-derived and ground-measured information are to be compared, either for calibration or validation, is the fact that satellite information is a snapshot over a large area, while ground information is a time-integrated pinpoint measurement. Of course practical problems to be solved are strongly dependent upon the particular applications, with major effects of space and time samplings. For example, in daylighting for a peculiar building, detailed spatial distribution is required for a very accurate assessment of the luminance. The large size of a pixel prevents from having this information, and the best and most useful that can be got is likely a sky class together with some relevant probabilities. In daylighting as well as in many other applications in solar energy, it is necessary to split the global radiation into its diffuse and direct components in order for example to be able to compute values on tilted surfaces. Keeping in mind the above-mentioned limitations, several works have been made to infer diffuse radiation from satellite images. Some of these works are briefly presented, their principles and their uncertainties. Then future tracks are discussed which rely heavily on numerical models of the radiative transfer within the cloudy or cloud-free atmosphere. The advantages and drawbacks, as well as the pending questions are presented. Such approaches require additional information that are not available by the sole use of the data of the geostationary satellites. The supply of these data, the robustness of the method to these data are discussed, too. It is shown that some properties, such as turbidity, geometrical and optical properties of the clouds, are predominant for the assessment of the diffuse and direct components. These properties are best estimated by some other satellites and it is recommended to use them in order to gain in accuracy. However this leads to a large increase in complexity of the processing chain as well of the fundamental problems to be solved with respect to the space-time characteristics.

Author: Lucien Wald -

Source: https://hal.archives-ouvertes.fr/


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