Abstract:The control of the quality of irradiation data is often a prerequisite to their further processing. Though data are usually controlled by meteorological offices, the sources are so numerous that the user often faces time-series of measurements containing questionable values. As customers of irradiation data, we established our own procedures to screen time-series of measurements. Since this problem of quality
“…The quality of the ground data measurements of the global irradiation was controlled by the means of a Web tool in order to remove suspicious data (see at www.helioclim.net, Geiger et al, 2002). We follow the ISO standard (1995) to assess the quality of HC-1, or HC-3, versus ground-based measurements.…”
“…The quality of the ground data measurements of the global irradiation was controlled by the means of a Web tool in order to remove suspicious data (see at www.helioclim.net, Geiger et al, 2002). We follow the ISO standard (1995) to assess the quality of HC-1, or HC-3, versus ground-based measurements.…”
“…Thirty-five stations are available for Africa, covering four years, spanning from January 1994 to December 1997 (Table 3). The quality of the ground data measurements of the global irradiation was controlled by the means of a Web tool in order to remove suspicious data (see at www.helioclim.net, Geiger et al, 2002). Following the ISO standard (1995), we compute the difference: estimated-measured for each day, and summarize these differences by the bias, the root mean square difference (RMSD) and the correlation coefficient.…”
Section: Comparing Ground Measurements To Satellite-derived Assessmentsmentioning
“…The data span the period 1994-1998, that is 5 years, except for Mersa Matruh, Egypt, where the period is 1995-1998 (4 years) and Tamanrasset, Algeria, with a period 1995-1999 (5 years). The quality of these measurements was controlled by the means of the Web tool described by Geiger et al (2003). It performs a likelihood control of the data and checks the plausibility of the measurements.…”
This work is a first attempt to propose a map of the solar radiation climate in Africa. Such a map is very useful for preliminary assessment and modeling of solar energy systems. Following the approach adopted for Europe, a data set of monthly means of the daily clearness index has been assembled for 62 sites. A cluster analysis was applied to create 20 classes that were reported on a map of Africa. These classes were geographically extended,
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