A Method for Sky-Condition Classification from Ground-Based Solar Radiation Measurements

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

doi:10.1175/1520-0450(2001)040<2193:amfscc>2.0.co;2

Cited by 43 publications

(27 citation statements)

References 12 publications

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“…The method we have chosen to assess the sky condition is a cluster supervised classification technique using a maximum likelihood criterion (Calbó et al, 2001). This technique is often used for pattern recognition in satellite imagery.…”

Section: Classifiermentioning

confidence: 99%

“…Feature V AR 4 is directly related to the difference between the length of the actual K n vs. time curve and the length of an horizontal curve, which corresponds to a cloudless sky. The more variable the global irradiance (and correspondingly, K n ) is in a given period, the higher this feature (Calbó et al, 2001).…”

Section: Classifiermentioning

confidence: 99%

“…The methodology was already introduced by Calbó et al (2001), and is synthetically explained in Sect. 2, along with the database used to apply the method, and the tools used to test it.…”

Section: Introductionmentioning

confidence: 99%

“…2, along with the database used to apply the method, and the tools used to test it. Calbó et al (2001) used total and diffuse irradiance measurements with a 5 minute resolution to retrieve sky conditions representative of 1 h intervals. They suggested an automatic cluster classification technique with a maximum likelihood criterion; they tested the method for distinguishing different number of clusters, and compared the results with non-collocated visual observations.…”

Section: Introductionmentioning

confidence: 99%

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Using routine meteorological data to derive sky conditions

2003

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Abstract. Sky condition is a matter of interest for public and weather predictors as part of weather analyses. In this study, we apply a method that uses total solar radiation and other meteorological data recorded by an automatic station for deriving an estimation of the sky condition. The impetus of this work is the intention of the Catalan Meteorological Service (SMC) to provide the public with real-time information about the sky condition. The methodology for deriving sky conditions from meteorological records is based on a supervised classification technique called maximum likelihood method.

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Section: Classifiermentioning

confidence: 99%

Section: Classifiermentioning

confidence: 99%

“…The methodology was already introduced by Calbó et al (2001), and is synthetically explained in Sect. 2, along with the database used to apply the method, and the tools used to test it.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using routine meteorological data to derive sky conditions

2003

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“…Calbo et al (2001) applied classical maximum likelihood method for clustering clouds. They used ground-based solar radiation measurements.…”

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confidence: 99%

A fuzzy neural network model to forecast the percent cloud coverage and cloud top temperature maps

Tulunay¹,

Şenalp²,

Öz³

et al. 2008

Ann. Geophys.

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Abstract. Atmospheric processes are highly nonlinear. A small group at the METU in Ankara has been working on a fuzzy data driven generic model of nonlinear processes. The model developed is called the Middle East Technical University Fuzzy Neural Network Model (METU-FNN-M). The METU-FNN-M consists of a Fuzzy Inference System (METU-FIS), a data driven Neural Network module (METU-FNN) of one hidden layer and several neurons, and a mapping module, which employs the Bezier Surface Mapping technique. In this paper, the percent cloud coverage (%CC) and cloud top temperatures (CTT) are forecast one month ahead of time at 96 grid locations. The probable influence of cosmic rays and sunspot numbers on cloudiness is considered by using the METU-FNN-M.

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Carbon dioxide exchange and canopy conductance of two coniferous forests under various sky conditions

Dengel

Grace

2010

Oecologia

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Sky conditions play an important role in the Earth's climate system and CO(2) uptake by plants. We used eddy covariance and meteorological data, including global and diffuse photosynthetic photon flux density (PPFD), recorded over the 2008 and 2009 growing season at two Sitka spruce [Picea sitchensis (Bong.) Carr.] forest sites in northern Britain, in order to establish relationships between physiological properties under diverse sky conditions, i.e. (1) sunny, (2) cloudy, and (3) overcast, and several canopy activity-related properties. These properties are: (1) response to PPFD, (2) photosynthetic light use efficiency, and (3) canopy stomatal conductance. We found that Sitka spruce forests utilise PPFD in a more efficient way when solar radiation is dominated by diffuse radiation. Furthermore, our results show that diffuse radiation enhances canopy stomatal conductance, an effect which may be the result of both blue light enrichment within the canopy and the reduction in vapour pressure deficit during cloudy and overcast weather. Diffuse radiation does not only influence short-term (hourly, daily, monthly) canopy activity but also long-term forest growth.

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A Method for Sky-Condition Classification from Ground-Based Solar Radiation Measurements

Cited by 43 publications

References 12 publications

Using routine meteorological data to derive sky conditions

Using routine meteorological data to derive sky conditions

A fuzzy neural network model to forecast the percent cloud coverage and cloud top temperature maps

Carbon dioxide exchange and canopy conductance of two coniferous forests under various sky conditions

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