Solar and terrestrial radiation dependent on the amount and type of cloud

Kasten, Fritz; Czeplak, Gerhard

doi:10.1016/0038-092x(80)90391-6

Cited by 497 publications

(252 citation statements)

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“…The value of n/N is one on cloudless days, so the clear-sky transmissivity is A a + B a . For time periods and stations where sunshine hours (n) were not available, the Hargreaves method as modified by Supit and Van Kappel (1998) 2) does not explicitly consider the effect of changes in the physical or optical properties of clouds on incoming radiation (Haurwitz, 1946;Kasten and Czeplak, 1980;Rossow and Lacis, 1990). Variability in cloud properties, including over small spatial scales (Rossow, 1989), may preclude the use of a simple relationship between visual cloud cover and incoming solar radiation as assumed in the Hargreaves relation.…”

Section: Angstrom and Hargreaves Equations With Correction For Aerosolsmentioning

confidence: 99%

“…Variability in cloud properties, including over small spatial scales (Rossow, 1989), may preclude the use of a simple relationship between visual cloud cover and incoming solar radiation as assumed in the Hargreaves relation. A full radiative transfer model (Chou and Zhao, 1997) or separate transmissivities by cloud type (Kasten and Czeplak, 1980) could account for cloud physical properties, but the IMD historical data used here cannot reliably predict those properties. The purpose of the present investigation is to test the utility of a simple relationship (Equation 2) appropriate for a given data set in a single river basin, and to use that relationship to leverage historical cloudiness data that do not include detailed cloud property measurements.…”

Section: Angstrom and Hargreaves Equations With Correction For Aerosolsmentioning

confidence: 99%

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Trends in solar radiation due to clouds and aerosols, southern India, 1952–1997

Biggs

Scott

Rajagopalan

et al. 2007

Intl Journal of Climatology

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Abstract:Decadal trends in cloudiness are shown to affect incoming solar radiation (SW SFC ) in the Krishna River basin (13-20°N, 72-82°E), southern India, from 1952 to 1997. Annual average cloudiness at 14 meteorological stations across the basin decreased by 0.09% of the sky per year over 1952-1997. The decreased cloudiness partly balanced the effects of aerosols on incoming solar radiation (SW SFC ), resulting in a small net increase in SW SFC in monsoon months (0.1-2.9 W m −2 per decade). During the non-monsoon, aerosol forcing dominated over trends in cloud forcing, resulting in a net decrease in SW SFC (−2.8 to −5.5 W m −2 per decade). Monthly satellite measurements from the International Satellite Cloud Climatology Project (ISCCP) covering 1983-1995 were used to screen the visual cloudiness measurements at 26 meteorological stations, which reduced the data set to 14 stations and extended the cloudiness record back to 1952. SW SFC measurements were available at only two stations, so the SW SFC record was extended in time and to the other stations using a combination of the Angstrom and Hargreaves-Supit equations. The Hargreaves-Supit estimates of SW SFC were then corrected for trends in aerosols using the literature values of aerosol forcing over India. Monthly values and trends in satellite measurements of SW SFC from National Aeronautics and Space Administration's (NASA's) surface radiation budget (SRB) matched the aerosol-corrected Hargreaves-Supit estimates over 1984-1994 (RMSE = 11.9 W m −2 , 5.2%). We conclude that meteorological station measurements of cloudiness, quality checked with satellite imagery and calibrated to local measurements of incoming radiation, provide an opportunity to extend radiation measurements in space and time. Reports of decreased cloudiness in other parts of continental Asia suggest that the cloud-aerosol trade-off observed in the Krishna basin may be widespread, particularly during the rainy seasons when changes in clouds have large effects on incoming radiation compared with aerosol forcing.

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Section: Angstrom and Hargreaves Equations With Correction For Aerosolsmentioning

confidence: 99%

Section: Angstrom and Hargreaves Equations With Correction For Aerosolsmentioning

confidence: 99%

Trends in solar radiation due to clouds and aerosols, southern India, 1952–1997

Biggs

Scott

Rajagopalan

et al. 2007

Intl Journal of Climatology

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“…It provides a first distinction of cloud radiative effects using the available data base (Foyo-Moreno et al, 2001). Different studies have followed similar procedures in their analysis of the cloud radiative effect over the whole solar spectrum, over UV and over photosynthetically active radiation (Kasten and Czeplak, 1980;Blumthaler et al, 1994;Davies, 1995;Alados et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Influence of cloudiness over the values of erythemal radiation in Valencia, Spain

Esteve

Marı́n

Tena

et al. 2009

Intl Journal of Climatology

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The influence of cloudiness over experimental UV erythemal radiation (UVER) has been studied. This influence has been analysed considering total cloudiness and low clouds. The measurements of cloudiness correspond to the daily values registered at 13 : 00 GMT at the Meteorological Centre of Valencia, which is part of the State Agency of Meteorology of Spain (AEMET). The UVER measurements were made using a YES UVB-1 radiometer located on the roof terrace of the Physics Faculty at the Burjassot Campus, Valencia (latitude 39.508°, longitude −0.418°, 60 m above sea level). First, a statistical analysis of cloudiness at 13 : 00 GMT in Valencia was carried out, confirming that the situation is mainly clear skies or very few clouds. Next, the influence of cloudiness on experimental UVER values was analysed, for both total cloudiness and low clouds. The experimental UVER values decrease as cloudiness increases for all solar zenith angles (SZA), and this reduction increases with the zenith angle. Next, the cloud modification factor (CMF) has been defined to reduce the influence of the zenith angle and ozone over the UVER. In order to quantify the relationship between CMF and the degree of cloudiness in oktas, linear, quadratic and potential regressions for both total cloudiness and low clouds have been calculated. Transmissivity due to total cloudiness and for overcast skies reaches 40%. On the other hand, the analysis of the influence over the zenith angle shows that CMF reduces as the zenith angle increases in the case of both total cloudiness and low clouds. With regard to the low cloud CMF, the results are comparable to those proposed by the COST-713 Action "UV-B Forecasting" for partially cloudy or cloudy skies (70% and 50%, respectively). Finally, the relationship between the CMF and the clearness index (k T ) has been analysed, as both parameters are simple indicators of cloudiness. It has been proved that such relationship is close to unity for zenith angles in the mid-range, while the CMF is greater than k T for lower SZA and is less than k T for high SZA, which indicates a certain dependence of these two parameters on the zenith angle.

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“…Cloud cover parameters was calculated from the empirical formula proposed by Kasten and Czeplak [4]. Cc = 1 0.75(N/8) 3.4 (1) Where N is a parameter describing the daily average cloudiness of the sky.…”

Section: Atmospheric Turbidity Factormentioning

confidence: 99%

The method of assessment of solar potential for selected area with use Geographical Information Systems

Pietras

Netzel

2012

EPJ Web of Conferences

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Abstract. This paper describes a method for analyse the spatial distribution of solar energy potential based on calculated solar irradiation with use of GIS (Geographical Information System). Program GIS GRASS gives opportunity to create spatial distribution of solar radiation which is taking into account such important elements like: terrain, atmosphere, pollutants, water and aerosol in atmosphere, clouds. The use of GIS GRASS module -named r.sun gives opportunity to generate spatial distribution of solar radiation on Lower Silesia (south -west part of Poland). In this work the analyse of solar potential to obtain hot water in the individual household were done. This analyse was based on the amount of total solar radiation monthly sums generated by r.sun module. Spatial distribution of solar potential was used to classify the Lower Silesia region in terms of work efficiency solar installations. It is very usefully because it gives people information about the date of the return of the funds invested in the purchase of the solar collectors.

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Solar and terrestrial radiation dependent on the amount and type of cloud

Cited by 497 publications

References 16 publications

Trends in solar radiation due to clouds and aerosols, southern India, 1952–1997

Trends in solar radiation due to clouds and aerosols, southern India, 1952–1997

Influence of cloudiness over the values of erythemal radiation in Valencia, Spain

The method of assessment of solar potential for selected area with use Geographical Information Systems

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