Is the summer season losing potential for solar energy applications in South Africa?

Singh, Jyotsna; Kruger, Andries

doi:10.17159/2413-3051/2017/v28i2a1673

Cited by 7 publications

(14 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Positive trends are evident during SON (Figure d) from both the ECMWF and SAWS observations. This is consistent with findings by Singh and Kruger (), who, although using point observations from weather stations across South Africa, use a similar period and found a general decrease in sunshine duration trends, mostly in DJF and MAM, while a maximum increase is recorded in SON. Trends between cloud cover and sunshine duration are largely consistent, with some areas of disagreement.…”

Section: Resultssupporting

confidence: 92%

“…A decrease in sunshine duration from the equator to the subtropics (around latitude 29°S) is evident in DJF (Figure b); however, in JJA (Figure b) a decrease in sunshine duration is evident from the equator to latitude 19°S, thereafter an increase is evident for all lower latitudes. A clear correspondence between trends over the different latitudes compares well with results from Singh and Kruger (), for example, positive trend in sunshine duration south of 30°S but turning negative northwards in DJF and negative trends south of 30°S in JJA.…”

Section: Resultssupporting

confidence: 86%

“…Trends in cloud cover, solar radiation and sunshine duration for various regions have been documented in a number of studies (e.g., Liepert, ; Groisman et al, ; Wang and Key, ). A recent study (Singh and Kruger, ) on sunshine duration trends using point observations from 22 sunshine recording stations across South Africa identified a general decreasing trend for all seasons. However, the decrease was most prominently observed for the summer season.…”

Section: Introductionmentioning

confidence: 96%

See 2 more Smart Citations

Integrated climatology and trends in the subtropical Hadley cell, sunshine duration and cloud cover over South Africa

Ndarana

Grab

Engelbrecht

2018

Intl Journal of Climatology

View full text Add to dashboard Cite

This study uses two methods to diagnose the local Hadley circulation; first the zonally averaged mass stream function, and second the stream function vector method. The two methods have been applied to the ERA-Interim reanalysis data for the period 1979-2015, to calculate both the climatology and trends of the Hadley cell. Both diagnostics advocate downwards mass flux being dominant over the subtropics, particularly over South Africa, yet the strength of Hadley is seasonal. Contrasts have been found between linear trends of the two diagnostics. Zonally symmetric diagnostics indicate strengthening of the Hadley cell, particularly in the subtropics of the Southern Hemisphere in winter and weakening in summer. The zonally asymmetric results indicate maximum strengthening of the Hadley over South Africa to be in spring and weakening in summer. Furthermore, maximum decrease in cloud cover and increase in sunshine duration over South Africa is in spring, implying more opportunities for solar energy generation. K E Y W O R D SHadley circulation, mass flux, streamfunction, sunshine duration, total cloud cover

show abstract

Section: Resultssupporting

confidence: 92%

Section: Resultssupporting

confidence: 86%

Section: Introductionmentioning

confidence: 96%

See 1 more Smart Citation

Integrated climatology and trends in the subtropical Hadley cell, sunshine duration and cloud cover over South Africa

Ndarana

Grab

Engelbrecht

2018

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…Hourly sunshine duration data was obtained by determining the burn made by the sun on a coated card in a Campbell-Stokes sunshine recorder [8]. Hourly data was then summed to get total daily sunshine duration (n).…”

Section: Methodsmentioning

confidence: 99%

“…The data collected from SAWS network help in the validation of satellites as well as the development and verification of empirical models [7]. SAWS also manage a very dense sunshine duration recording network over South Africa to the extent that sunshine duration data has been continuously measured for several years [8]. SAWS GHI stations are sparse, according to [1,2,3,4,5,9].…”

Section: Introductionmentioning

confidence: 99%

The Ångström-Prescott Regression Coefficients for Six Climatic Zones in South Africa

Mabasa¹,

Lysko²,

Tazvinga³

et al. 2020

Preprint

View full text Add to dashboard Cite

The South African Weather Service (SAWS) manages an in-situ solar irradiance radiometric network of 13 stations and a very dense sunshine recording network; located in all six macro-climate zones of South Africa. A sparsely distributed radiometric network and over a landscape with dynamic climate and weather shifts is inadequate for solar energy studies and applications. Therefore, there is a need to develop mathematical models to estimate solar irradiation for a multitude of diverse climates. In this study, the annual regression coefficients, a and b, of the Ångström-Prescott (AP) model that can be used to estimate global horizontal irradiance from observed sunshine hours were calibrated and validated with observed station data. The AP regression coefficients were calibrated and validated for each of the six macro-climate zones of South Africa using the observation data that spans 2013 to 2019. The predictive effectiveness of the calibrated AP model coefficients was evaluated by comparing estimated and observed daily global horizontal irradiance. The maximum annual relative Mean Bias Error (rMBE) was 0.371 %, relative Mean Absolute Error (rMAE) was 0.745 %, relative Root Mean Square Error (rRMSE) was 0.910 % and the worst-case correlation coefficient (R2) was 0.910. The statistical validation metrics results show that there is a strong correlation and linear relation between observed and estimated solar radiation values. The AP model coefficients calculated in this study can be used with quantitative confidence in estimating daily GHI data at locations in South Africa where the daily observation sunshine duration data is available.

show abstract

Evaluating sunshine hour approximation for biometeorological indices

Fitchett,

Roffe,

Prinsloo

2024

Theor Appl Climatol

View full text Add to dashboard Cite

Sunshine influences a range of biometeorological parameters, from human health to the enjoyment of touristic destinations. Sunshine has therefore become an important meteorological variable in biometeorological indices and the causal analysis of the impact of climate on humans. However, ground-based recording of sunshine hours is sparse, particularly in African countries. Methods to estimate sunshine hours from more ubiquitously measured or modelled meteorological parameters offer the prospect to supplement these datasets, and are thus appealing for biometeorological studies. It is therefore important to critically explore and test the validity of these approaches at country-level resolution. In this study, we explore the accuracy of a method to estimate sunshine hours from solar radiation that is used in the Camping Climate Index for the United States, and test the suitability of the substitution for South Africa. We find that for each station in South Africa, at least 65% of the values estimated by this equation are completely erroneous, either returning negative values for sunshine hours or a total of sunshine hours for a day in excess of the duration between sunrise and sunset. Further comparison of the estimated data against measured data reveals that for at least half of the months of the year for each station, the differences in values are statistically significant. We therefore strongly caution against the use of this particular method for estimating sunshine hours in South Africa, and encourage similar tests before applying it elsewhere. More broadly, we advocate for careful ground-truthing of estimated meteorological variables before inputting them into biometeorological indices or models.

show abstract

Is the summer season losing potential for solar energy applications in South Africa?

Abstract: Seasonal trends using in situ sunshine duration (SD)

Cited by 7 publications

References 30 publications

Integrated climatology and trends in the subtropical Hadley cell, sunshine duration and cloud cover over South Africa

Integrated climatology and trends in the subtropical Hadley cell, sunshine duration and cloud cover over South Africa

The Ångström-Prescott Regression Coefficients for Six Climatic Zones in South Africa

Evaluating sunshine hour approximation for biometeorological indices

Contact Info

Product

Resources

About