Analysis of satellite derived solar irradiance in islands with site adaptation techniques for improving the uncertainty

Analysis of Spanish Radiometric Networks with the Novel Bias-Based Quality Control (BQC) Method

“…All of them presented defects in more than 40% of their stations (Figure 3a). Despite this, several studies have been published based on GH measurements from these networks, especially using SIAR stations [4,35,36,37,38,39,40,41,42,43,44,45]. SIAR is an attractive network for research studies in Spain because it freely provides 30-min GH data over a dense network of more than 500 stations covering most of Spain.…”

“…The quality control was deficient in the majority of the studies. It basically consisted of a two-step procedure: (i) discarding stations with too many missing values [38,39,40,41,42,44]; and (ii) discarding samples out of the range of physically possible values that were set based on the extraterrestrial irradiance [4,40,41], the clearness index [35,38], clear-sky models [42,45], or WMO recommendations [44]. However, range QC tests do not detect most of the errors present in the Spanish weather stations as shown in the previous section.…”

Correction of Tropical Rainfall Measuring Missions Satellite Data of Solar Radiation for the High Andean Areas of Peru

“…Global warming and society's demand for electrical energy has intensified in recent decades, generating electrical energy from the sun is one of the challenges in recent decades (Grossi & Coquet, 2017) (Mazorra Aguiar, Polo, Vindel, & Oliver, 2019) the development of applications and research related to renewable energy (Jimenez, Will, & Rodríguez, 2017) are prioritized lines in recent decades, also being necessary the characterization of solar energy resources for renewable energy technologies requires good precision (Jesus Polo et al, 2020), it has an impact on the economy (Stoffel et al, 2000), without data on solar resources we do not advance in research (Yang & Bright, 2020) photovoltaic plants in areas where there are few records of solar radiation, after quality control (J. Polo et al, 2016), the availability of a high quality time and space series of solar radiation in situ is limited, it is about building through satellite images (Ameen et al, 2018) for the purpose of quantifying in regions where there is no climate information, the validation of solar radiation satellite data with respect to observed data is essential for later use in areas with a scarcity of observed data and they are quite similar (Ameen et al, 2018), knowing the exact data of the terrestrial solar radiation is enough to implement photovoltaic systems for the supply of electrical energy as well as for the detection of climate change (Stoffel et al, 2000), multispectral atmospheric correction being necessary to improve satellite data such as MODIS (Cao, Han, Zhang, & Li, 2020), countries such as North Korea and South Korea to alleviate electricity crisis make energy explorations (Yeom et al, 2020), another technique used is in neural networks and mathematical models using climatic variables as input (Jimenez et al, 2017) (Lavorato, Lakkis, & Canziani, 2013), too (Lavado & Condom, 2010) proposes correcting satellite data on precipitation through the use of additive and multiplicative factors, throughout the Peruvian territory there is not enough climate information specifically the climate element solar radiation, local and regional policies are focused on the use of renewable energy , for this it has become essential to know the intensity of radiation and solar energy in time and space, in the high Andean areas of Peru the dehydration of the potato called chuño has been practiced for many generations, the entire process is based on radiation solar, for Andean cultures solar radiation is deity, in recent years chuño is of social and economic interest due to the guarantee of food safety, the objective of this study is to validate TRMM satellite data through data observed from a meteorological station automatic in situ for solar radiation in the period from 2014 to 2017 located in the p central art o...…”

“…coefficients have been determined, the Pearson correlation coefficient shows significant improvements, being r = 0.84 as the slope of the line reaches 0.71 figure3, this without considering clear skies or hours with the presence of clouds that you can overestimate or underestimate(Mazorra Aguiar et al, 2019) satellite solar radiation, the scatter diagram before and after correction shows figure4between observed data and TRMM for a period of 4 years; The methodology used guarantees the suitability of TRMM for high Andean areas as well as other techniques for different satellites(Mazorra Aguiar et al, 2019), Taking into account that TRMM has been from 1980 to the present, the correction coefficients found for a short period of 4 years is applicable for long Published by IDEAS SPREAD periods and places where data records are scarce (JesusPolo et al, 2020) it is sometimes called site adaptation using different techniques.…”

Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure

“…To overcome the inaccuracies introduced by these error sources, a common solution is to post-process the modeled data with coincident and quality assured ground measurements, in order to understand the source of discrepancy and subsequently to improve the accuracy of the resulting time series. In particular, for reliable solar resource assessments at a specific location, the accuracy of satellite-based solar irradiance series is typically enhanced by a short-term ground measurement campaign at the site [17,19,20]. In order to achieve an acceptable small risk level in solar projects, financial institutions typically require the disposal of a coincident period of (at least) one year between solar irradiance measurements and models for the application of this procedure.…”