Validation of direct normal irradiance predictions under arid conditions: A review of radiative models and their turbidity-dependent performance

Gueymard, Christian A.; Ruiz‐Arias, José A.

doi:10.1016/j.rser.2015.01.065

Cited by 84 publications

(37 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The present findings clearly suggest that the modeling of radiative aerosol effects is the most likely cause of discrepancy between modeled predictions, thus confirming previous site-specific evaluations, e.g. [5,7,9].…”

Section: Resultssupporting

confidence: 89%

“…Aerosol optical depth at 500, 469, 670 and 865 nm are retrieved from MACC. The Ångström turbidity coefficient and exponent are calculated from a log-log fit of these spectral AODs to the Ångström formula (see [5] for details). The aerosol optical depths at 550 and 700 nm are derived using the Ångström formula with the Ångström exponent and AOD at 500 and 670 nm, respectively.…”

Section: Data and Clear-sky Solar Radiation Modelsmentioning

confidence: 99%

“…Water vapor can be a key factor over tropical and some coastal areas, but in general aerosols are the dominating factor, particularly over arid regions [5,6]. For STE applications over such regions, the bankability of some existing irradiance datasets has already been questioned [7].…”

Section: Introductionmentioning

confidence: 99%

“…So far, all efforts directed to the performance evaluation of clear-sky solar radiation (CSR) models have hinged upon comparisons against high-quality ground observations [5][6][7][8][9][10][11]. However, two major shortcomings undermine this conventional method: (1) The models' evaluation is done only for the particular climatic conditions at a few test sites, thus strongly limiting the generalization of results; and (2) the cloud-screening procedure that must be applied to the irradiance observations adds uncertainty to the validation process.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Worldwide multi-model intercomparison of clear-sky solar irradiance predictions

Ruiz‐Arias

Gueymard²,

Cebecauer

2017

AIP Conference Proceedings

Self Cite

View full text Add to dashboard Cite

Abstract. Accurate modeling of solar radiation in the absence of clouds is highly important because solar power production peaks during cloud-free situations. The conventional validation approach of clear-sky solar radiation models relies on the comparison between model predictions and ground observations. Therefore, this approach is limited to locations with availability of high-quality ground observations, which are scarce worldwide. As a consequence, many areas of interest for, e.g., solar energy development, still remain sub-validated. Here, a worldwide inter-comparison of the global horizontal irradiance (GHI) and direct normal irradiance (DNI) calculated by a number of appropriate clear-sky solar radiation models is proposed, without direct intervention of any weather or solar radiation ground-based observations. The model inputs are all gathered from atmospheric reanalyses covering the globe. The model predictions are compared to each other and only their relative disagreements are quantified. The largest differences between model predictions are found over central and northern Africa, the Middle East, and all over Asia. This coincides with areas of high aerosol optical depth and highly varying aerosol distribution size. Overall, the differences in modeled DNI are found about twice larger than for GHI. It is argued that the prevailing weather regimes (most importantly, aerosol conditions) over regions exhibiting substantial divergences are not adequately parameterized by all models. Further validation and scrutiny using conventional methods based on ground observations should be pursued in priority over those specific regions to correctly evaluate the performance of clear-sky models, and select those that can be recommended for solar concentrating applications in particular.

show abstract

Section: Resultssupporting

confidence: 89%

Section: Data and Clear-sky Solar Radiation Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Worldwide multi-model intercomparison of clear-sky solar irradiance predictions

Ruiz‐Arias

Gueymard²,

Cebecauer

2017

AIP Conference Proceedings

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, most locations lack long-term accurate radiation, cloudiness, and/or satellite data for many climate stations, which are needed in order to identify and estimate atmospheric attenuation. For example, models such as r.sun [16,17], Solei-32 [17,18] and, ESRA [5,6,8] calculate the overcast radiation from clear sky values and a clear-sky index called Linke (Table 1, [23,24]). The Linke must be derived from one of the three methods: (1) from the ratio between measured global radiation and computed values of clear sky global radiation, (2) from other climatologic data such as cloudiness [23], or (3) directly from shortwave surface irradiance measured by satellites [24].…”

Section: Introductionmentioning

confidence: 99%

A novel time-effective model for daily distributed solar radiation estimates across variable terrain

Mirmasoudi

Byrne

Kroebel³

et al. 2018

Int J Energy Environ Eng

View full text Add to dashboard Cite

Accurate and precisess estimation of spatio-temporal variability of solar radiation is critical. Some commonly used models evaluate this variability using methods in which the data required for estimating atmospheric attenuation may not be easily accessible for some study areas. Here, a daily solar radiation estimation method which uses ambient air temperature, a Digital Elevation Model, time of year, and monthly radiation estimates from Solar Analyst model has been proposed. The objective was to use air temperature-based empirical models for atmospheric transmissivity and diffuse fractions to vary total monthly radiation estimation from Solar Analyst, and then calculate total daily radiation as a fraction of total monthly radiation by applying a daily transmissivity-based ratio, as air temperature data are readily available at most locations on the planet. Results revealed that daily solar radiation can be estimated very well, with Mean Absolute Bias Error of around 40-53 W m −2 or Mean Bias Error of ± 10%, under all sky conditions at seven sites in diverse climate regions, using significantly less input data. The presented method is an improvement over previously used methods with Mean Bias Error of under 10% but more input parameters. Furthermore, the hourly solar radiation values can be calculated using the presented method using the ratio between daily and hourly radiation, for example from literature values and estimated daily insolation. The result also showed that the method is more useful for those stations with substantially higher numbers of sunny days than cloudy or partly cloudy days because the uncertainty of the model decreased from cloudy to sunny sky conditions. The implemented Digital Elevation Models environment of this method makes it applicable in many studies that need spatial estimation of solar radiation, especially for solar energy generation projects. Keywords Solar radiation · Digital elevation model · Solar analyst · Atmospheric transmissivity · Air temperature Abbreviations

show abstract

Clear-Sky Radiation Models and Aerosol Effects

Gueymard¹

2019

Solar Resources Mapping

View full text Add to dashboard Cite

Validation of direct normal irradiance predictions under arid conditions: A review of radiative models and their turbidity-dependent performance

Cited by 84 publications

References 62 publications

Worldwide multi-model intercomparison of clear-sky solar irradiance predictions

Worldwide multi-model intercomparison of clear-sky solar irradiance predictions

A novel time-effective model for daily distributed solar radiation estimates across variable terrain

Clear-Sky Radiation Models and Aerosol Effects

Contact Info

Product

Resources

About