Using routine meteorological data to derive sky conditions

Pagès, David; Calbó, Josep; González, Josep‐Abel

doi:10.5194/angeo-21-649-2003

Cited by 14 publications

(9 citation statements)

References 9 publications

(12 reference statements)

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“…Calbo, Gonzales, and Page used clearness index, diffuse fraction, and the variability of GHI and diffuse to classify clouds into nine categories using supervised classification techniques [90][91][92]. Harrison, Chalmers, and Hogan used GHI and diffuse to determine cloud amount and discriminate between stratiform and convective cloud types [93].…”

Section: Introductionmentioning

confidence: 99%

Global horizontal irradiance clear sky models : implementation and analysis.

Stein¹,

Hansen²,

Reno³

2012

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Clear sky models estimate the terrestrial solar radiation under a cloudless sky as a function of the solar elevation angle, site altitude, aerosol concentration, water vapor, and various atmospheric conditions. This report provides an overview of a number of global horizontal irradiance (GHI) clear sky models from very simple to complex. Validation of clear-sky models requires comparison of model results to measured irradiance during clear-sky periods. To facilitate validation, we present a new algorithm for automatically identifying clear-sky periods in a time series of GHI measurements. We evaluate the performance of selected clear-sky models using measured data from 30 different sites, totaling about 300 site-years of data. We analyze the variation of these errors across time and location. In terms of error averaged over all locations and times, we found that complex models that correctly account for all the atmospheric parameters are slightly more accurate than other models, but, primarily at low elevations, comparable accuracy can be obtained from some simpler models. However, simpler models often exhibit errors that vary with time of day and season, whereas the errors for complex models vary less over time.4

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Section: Introductionmentioning

confidence: 99%

Global horizontal irradiance clear sky models : implementation and analysis.

Stein¹,

Hansen²,

Reno³

2012

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“…The additional scattering that light undergoes for slant paths is associated with increased image brightness, evident for large z. While recent sky imaging work neglects it (Forster et al, 2017), such correction is consistent with sky observations (Volz, 1987;Patat, 2003). In this context we will be assuming single scattering approximation, as justified by co-located non-cloud-screened AERONET measurements showing op- tical thickness < 1.…”

Section: Air Mass Correctionmentioning

confidence: 73%

“…When no other sky observations are available and attenuation of solar irradiance due to aerosol can be measured or accounted for, a method previously implemented for solar irradiance time series from pyranometer measurements can be used for cloud classification (Duchon and O'Malley, 1999). This can be achieved by accounting for the standard deviation of the scaled observed irradiance and the ratio of the former to the scaled clear-sky irradiance (Duchon and O'Malley, 1999) or, as a cheap and relatively easy-to-use alternative, by combining observed total irradiance, temperature and relative humidity (Pagès et al, 2003). In the future these cirrus discrimination methods should be compared to techniques such as microwave radiometry or lidar, which would allow us to assess their relative merit.…”

Section: Discussionmentioning

confidence: 99%

Halo ratio from ground-based all-sky imaging

et al. 2019

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The halo ratio (HR) is a quantitative measure characterizing the occurrence of the 22 • halo peak associated with cirrus. We propose to obtain it from an approximation to the scattering phase function (SPF) derived from allsky imaging. Ground-based fisheye cameras are used to retrieve the SPF by implementing the necessary image transformations and corrections. These consist of geometric camera characterization by utilizing positions of known stars in a camera image, transforming the images from the zenithcentred to the light-source-centred system of coordinates and correcting for the air mass and for vignetting, the latter using independent measurements from a sun photometer. The SPF is then determined by averaging the image brightness over the azimuth angle and the HR by calculating the ratio of the SPF at two scattering angles in the vicinity of the 22 • halo peak. In variance from previous suggestions we select these angles to be 20 and 23 • , on the basis of our observations. HR time series have been obtained under various cloud conditions, including halo cirrus, non-halo cirrus and scattered cumuli. While the HR measured in this way is found to be sensitive to the halo status of cirrus, showing values typically > 1 under halo-producing clouds, similar HR values, mostly artefacts associated with bright cloud edges, can also be occasionally observed under scattered cumuli. Given that the HR is an ice cloud characteristic, a separate cirrus detection algorithm is necessary to screen out non-ice clouds before deriving reliable HR statistics. Here we propose utilizing sky brightness temperature from infrared radiometry: both its absolute value and the magnitude of fluctuations obtained through detrended fluctuation analysis. The brightness temperature data permit the detection of cirrus in most but not all instances.

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“…Then a question arises about the classification of sky conditions. In this study sky conditions are used as in [12], and four sky conditions are taken into account; First of all sequential frames are taken into account with predetermined sample periods. Then a wavelet enhancement technique is used for increasing object detection possibility.…”

Section: Introductionmentioning

confidence: 99%