Overcast Conditions Research Articles

The dominant role of aerosol-cloud interactions in aerosol-boundary layer feedback: Case studies in three megacities in China

Interactions between aerosols and meteorology have received increasing attention in recent decades. Through interactions with radiation, aerosols involve in thermodynamic processes and cause cloud adjustment, referred to as the direct and semi-direct effects respectively. They also involve in cloud microphysical processes by severing as cloud condensation nuclei or ice nuclei, referred to as indirect effect. Aerosol direct effect is found to potentially exacerbate air quality by stabilizing the planetary boundary layer (PBL). However, their impacts through the interaction with clouds, including semi-direct and indirect effect remain unclear. In this study, we conducted model simulations to evaluate the direct, semi-direct and indirect effects of aerosols in PBL structure and surface PM2.5 concentration during three heavy haze events under overcast conditions. Overall, the aerosol-PBL feedback results in a 22%–36% decrease of PBL height and 5%–28% increase of PM2.5 concentration. The indirect effect always has the largest impact on PBL and PM2.5 pollution, accounting for 59%–84% of the changes. The semi-direct effect is the weakest on average, although it can exceed the direct effect at certain times and locations. Black carbon aerosols play the vital role in both the direct and semi-direct effects. Our findings promote the understanding of heavy haze formation, and highlight the dominant role of aerosol-cloud interaction in the feedback process of aerosols to PBL structure and air quality.

Experimental study on the impact of double tilted Venetian blinds on indoor daylight conditions

One of the most important concerns when designing buildings as liveable spaces is the indoor comfort. This depends on different factors, including daylight availability and discomfort glare conditions.The increasing use of glazing areas in the building's envelopes can lead to high energy consumption and problems such as visual discomfort. The use of shading devices stands out as a sustainable design strategy to reduce energy consumption in the buildings. This work presents an experimental analysis of the impact of an innovative shading device, a double-tilted venetian blind (DTVB) with different positions of upper and lower slats, on the indoor daylight conditions. Moreover, discomfort glare evaluation, through DGPs metric, is performed.The experimental campaign was conducted in an outdoor test cell during three periods of the year: summer solstice, winter solstice and autumn equinox. Experiments were carried out with both white and grey DTVBs, for several positions of upper and lower slats, under clear and overcast sky conditions. This comprises the measurement of indoor and outdoor horizontal and vertical illuminances and irradiances and solar and visible transmittance of the fenestration. It was concluded that DTVBs can achieve a higher performance, regarding solar protection, daylighting and glare control, when compared with more traditional venetian blinds systems.

Midnight Sun to Polar Night: A Model of Seasonal Light in the Barents Sea

AbstractArctic marine ecosystems are strongly influenced by the extreme seasonality of light in the region. Accurate determination of light is essential for building a comprehensive understanding of the dynamics of animal and aquatic algae populations. Current approaches to underwater light field parameterisations rely upon shortwave radiation (300–3000 nm) estimates from satellites or surface radiometry measurements to populate full radiative transfer software. Due to the inaccessibility of many regions in the Arctic, measured data is not widely available. This study presents a model of spectrally resolved underwater light in ice‐free conditions in the Barents Sea. Given a location and time, the model accounts for downwelling spectral irradiance in the photosynthetically active radiation (PAR, 400–700 nm) range (ED PAR) at the ocean surface from solar, lunar, and galactic light sources, modulated by local cloud cover. We demonstrate the ability to extend over the full year into the period of Polar Night, validated in both broadband PAR and spectral domains. Using a bio‐optical model of diffuse attenuation developed for the Barents Sea, we show accurate calculations to depth for inhomogeneous water columns over a spatial‐temporal range, validated against time series irradiance data from the ArcLight observatory in Ny‐Ålesund, Svalbard and in‐situ irradiance sensors deployed in the Barents Sea. Finally, in comparison to state‐of‐the‐art radiative transfer models, averaged over the water column we demonstrate a typical mean absolute error of <1 μmol m−2 s−1 in ED PAR for overcast conditions (<6 μmol m−2 s−1 for clear‐sky) and reduced execution time of factor 20.

An 11-year record of wintertime snow-surface energy balance and sublimation at 4863 m a.s.l. on the Chhota Shigri Glacier moraine (western Himalaya, India)

Abstract. Analysis of surface energy balance (SEB) at the glacier/snow surface is the most comprehensive way to explain the atmosphere–glacier/snow interactions, but that requires extensive data. In this study, we have analysed an 11-year (2009–2020) record of the meteorological dataset from an automatic weather station installed at 4863 ma.s.l. (above sea level) on a lateral moraine of the Chhota Shigri Glacier, western Himalaya. The study was carried out over the winter months (December to April) to understand SEB drivers and snow loses through sublimation. Furthermore, this study examines the role of cloud cover on SEB and turbulent heat fluxes. The turbulent heat fluxes were calculated using the bulk-aerodynamic method, including stability corrections. The net short-wave radiation was the primary energy source. However, the turbulent heat fluxes dissipated a significant amount of energy. The cloud cover plays an important role in limiting the incoming short-wave radiation by about 70 %. It also restricts the turbulent heat fluxes by more than 60 %, resulting in lower snow sublimation. During winter, turbulent latent heat flux contributed the largest proportion (64 %) in the total SEB, followed by net radiation (25 %) and sensible heat flux (11 %). Sublimation rates were 3 times higher in clear-sky than overcast conditions, indicating a strong role of cloud cover in shaping favourable conditions for turbulent latent heat flux by modulating the near-surface boundary layer conditions. Dry air, along with high snow-surface temperature and wind speed, favours sublimation. Besides, we also observed that strong and cold winds, possibly through mid-latitude western disturbances, impede sublimation by bringing high moisture content to the region and cooling the snow surface. The estimated snow sublimation fraction was 16 %–42 % of the total winter snowfall at the study site. This study substantiates that the snow sublimation is an essential variable to be considered in glaciohydrological modelling at the high-mountain Himalayan glacierised catchments.

Detection method for table grape ears and stems based on a far-close-range combined vision system and hand-eye-coordinated picking test

To improve the picking success rate of table grapes in the process of automatic picking, it is important to accurately locate the point picking of grape ears and the cutting point of grape stems. In this research, a set of far-close-range stereoscopic vision systems was constructed to detect grape ears and grape stems. First, identification algorithms for grape ear centroid were proposed. A series of image operations were performed to complete the recognition and feature extraction of far-range grapes, including median filtering, threshold segmentation, morphological operation, executable region marking, and the extraction of the target centroid. Second, a calculation model of the cutting point of grape stems was established. The selected region of interest (ROI) of the close-range grape stem was determined to carry out edge detection and use a cumulative probability Hough transform. The straight line detection and cutting point positioning of the close-range grape stem were completed. Finally, based on LabVIEW software, the measurement and control system of the grape-picking robot was developed. Experiments verified that the identification of grape stems and localization algorithm of the cutting point had higher reliability, with success rates of 92% on sunny days, 82% during sunny backlight and 86% for overcast conditions. The grape-picking tests showed that the grape-picking robot can complete the table grape-picking task within an average time of 53.4 s under the given computer configuration.

Daylight Performance of the Modified Double Light Pipe (MDLP) Through Experimental Analysis on a Reduced Scale Model

This paper is focused on the Modified Double Light Pipe (MDLP), an innovative daylighting system set up by the authors in the Laboratory of Technical Physics of the University “G. D’Annunzio” of Pescara (Italy). It is an evolution of the Double Light Pipe (DLP), designed by the authors to distribute natural light in two underground levels of a building and tested through an experimental activity on a reduced scale model. The MDLP has been designed by modifying the same scale model of the DLP with the goal to solve some problems related to its size and the risk of glare, thanks to its smaller encumbrance, and a light shelf applied around the external tube to prevent the occupants of the room from seeing the upper brightest portion of the device. Furthermore, the light shelf reflects light towards the ceiling spreading it more uniformly on the horizontal work-plan. The technological components of the MDLP are shown demonstrating the possibility of installing it in both new and refurbished buildings. Then, the first results of an experimental activity carried out on the model of the MDLP in winter climatic conditions are shown. Although the unfavorable values of external illuminance, the MDLP contributes to distributing natural light in the passage room both with overcast and clear sky conditions. On sunny days, direct solar radiation hits the measure positions on the corners of the room producing peak illuminance values. The illuminance uniformity is calculated according to the EN 12464-1. The results can be considered satisfactory both in terms of internal illuminance and uniformity of light distribution.

Exergo-Economic and CO2 Emission Analysis of Bi-Symmetrical Web Flow Photovoltaic-Thermal System Under Diurnal Conditions

Abstract The undesired heat evolved in photovoltaic (PV) module during its regular operation must be removed to aspire to reliable power output. PV installations in tropical and sub-tropical regions experience abrupt PV module heating, especially during summer seasons that lead to a hot spot effect. Photovoltaic–thermal (PVT) system has proven to provide module cooling satisfactorily with various working fluids while delivering a higher annual energy yield. In the present study, experiments were carried out on novel web flow channel PVT module at Vellore (12.9165 ° N, 79.1325 ° E), India. The present research was carried out under outdoor conditions with various mass flowrates ranging 0.5– 2 L per minute under sunny and overcast conditions. Water was used as working fluid in the PVT system, and performance results were compared to 335 Wp reference polycrystalline PV module under similar operating conditions. PVT with bi-symmetrical web flow thermal absorber gave maximum overall efficiency of 63.09% obtained at 1.5 LPM mass flowrate of the water. Estimation of CO2 mitigations for PVT system earned 8.2% higher savings than the PV module alone under overcast conditions.

Solar Tracking System for Efficient Power Generation using Image Processing

Abstract: The emerging era is energy demanding and there is a drastic need to shift to more eco-friendly methods for power generation. The non-renewable resources generate 86% of the world's power. Around the world, coal and gas power plants are shutting down due to lack of fuel. With more and more industries and governments joining the Green Movement, the demand for cost effective renewable energy has surged. Solar power can be easily harnessed as compared to other eco-friendly methods, using solar panels and the conventional process of converting solar energy to electrical energy. Even though solar power is used in domestic as well as industrial applications, it is still a long way from making an impact on environmental change. Since solar panels can only be utilized up to their full potential in clear sky and sunny conditions, its usage is affected by geographic location. However, even in conditions of optimal usage, it's not used up to its full potential. As all solar panels are fixed due sunny side, they receive direct sunlight only for half a day. During the other half, the sun is behind the panels and hence, the power generation drops steadily. To rectify this, we introduce the principle used by sunflowers. Sunflowers intake energy by following the sun from sunrise till sunset. Using the same concept, we make the panels follow the sun resulting in significant increase in energy production. We take images of the sun throughout the day, using image processing make sure that the sun is directly incident to the panels, follow this procedure till sunset. This method makes sure that even in conditions of slight to moderate overcast weather, the sun will be directly incident on panels, such is the power of image processing. The status of the device as well as energy generated can be easily visualized using the mobile application provided. The system can further be made cost effective by modifying the existing panels. The concept is simple yet very efficient, robust and scalable. This method can be used for domestic as well as industrial applications. In optimal conditions, this method can generate up to 40% more energy than a conventional solar panel system of the same size. In conclusion, just by learning from nature, using only a gearbox and controller in addition to panels, we can generate significantly more electricity. In addition to this method, using most efficient solar panels that give maximum power output even in overcast conditions can further increase power output.

Application of artificial neural networks in horizontal luminous efficacy modeling

Harnessing daylight for energy-efficient designs requires the availability of daylight illuminance data. In the absence of measured daylight data, deriving daylight using the luminous efficacy model is an alternative. This paper presents an approach for modeling diffuse and global luminous efficacies using accessible measured climatic data. The methodology explored machine learning, sensitivity analysis and empirical modeling approaches. Twelve (12) luminous efficacy models were proposed. These models consisted of six artificial neural networks (ANN) and six empirical models. All models also cover the all-sky, overcast and non-overcast sky conditions. The intent of using ANN lies in the need for more accurate daylight predictions and its ease in explaining complex relationships between complex atmospheric variables. Findings from the study show that diffuse fraction is crucial in global and diffuse luminous efficacy modeling. Furthermore, the performance of all models was statistically assessed, and the results show that all twelve proposed models could offer acceptable predictions of daylight. In particular, the ANN models outperformed the empirical models.

Ultraviolet-visible light compass method based on local atmospheric polarization characteristics in adverse weather conditions

Bionic polarization navigation has attracted extensive attention because of its strong anti-interference performance and no accumulation of errors over time. However, very few studies have fully considered the influence of adverse weather conditions such as cloudy and overcast weather, which play a key role in navigation accuracy. Therefore, we propose an adaptive ultraviolet-visible light compass method based on local atmospheric polarization characteristics applicable to various weather conditions. The proposed method transforms the heading determination problem into a multiclassification problem by using a weather recognition technique. Ultraviolet detection is used to weaken the depolarization effect of cloud particles and to obtain more accurate skylight polarization patterns. Then, on the basis of screening effective data, the sun direction vector is calculated by using the electric vector direction and is finally combined with the astronomical calendar to achieve navigation. The experimental results confirm that, compared to the other methods, the designed algorithm can suppress the interference of clouds better and adapt to complex weather conditions. Under cloudy and overcast conditions, the heading angle error is reduced to less than 2°.

Radiation estimation and crop growth trajectory reconstruction by novel algorithms improve MOD16 evapotranspiration predictability for global multi-site paddy rice ecosystems

Reliable estimations in evapotranspiration (ET) of paddy rice ecosystems by satellite products are critical because of their important roles in regional hydrological processes and climate change. However, the NASA MODIS ET products (MOD16A2) and its derivatives do not have good correlations with all global paddy rice ET observations. In this research, MOD16 model sensitivity analyses and parameter optimization strategies were conducted in order to solve the problem. Results suggested that underestimation of daily net radiation (Rn) in overcast conditions and less satisfactory reconstruction of field-scale leaf area index (LAI) growth trajectory from the start date of field flooding and transplanting (FFTD) to the end of growing seasons by MODIS coarse vegetation index were identified as two major causes. A Light and Temperature-Driven Growth model and a Phenology-based LAI temporal Smoothing method fusion algorithm (LTDG_PhenoS) and an improved Rn estimation method were introducted and evaluated in paddy rice fields in South Korea, Japan, China, Philippines, India, Spain, Italy, and the USA from 2002 to 2019. The LTDG_PhenoS algorithm considers Landsat and MODIS EVI observations and meteorological data as input variables and 30-m LAI daily time series as outcomes. Introducing the global cloudy index algorithm resulted in improved estimations of daily Rn under all-sky conditions, with a significant decrease of root mean square error (RMSE) from 1.87 to 1.11 MJ m−2 day−1. The LTDG_PhenoS algorithm well reconstructed crop LAI growth dynamics from the FFTD to the end of rice growing seasons, with a substantial decline of RMSE from 1.49 to 0.27 m2/m−2. The FFTD estimations by the LTDG_PhenoS algorithm had an R2 of 0.97 and a small RMSE of less than 12-days. Daily ET rates estimated by novel algorithms had a substantial decline in RMSE from 2.88 to 0.90 mm day−1.

Application of Cycle Skipping Modulation in Buck–Boost Photovoltaic Microconverters

Cycle skipping modulation (CSM) was previously demonstrated for efficiency improvement in different converters intended for photovoltaic module-level applications. Currently, galvanically isolated buck–boost converters (IBBCs) have attracted increased attention in these applications due to the uptake of dc microgrids. This article revisits the topic of CSM and applies it to a quasi-Z-source-based IBBC. Two new CSM schemes are proposed for the given converter. Power losses in components are estimated for different CSM schemes to predict efficiency improvement that could be attained. A 300-W prototype was built to verify the efficiency estimation results. The efficiency trends are the same between the theoretical estimations and experimental measurements. Converter operation was studied for two bell-shaped solar irradiance daily profiles using a solar array simulator. The converter demonstrates efficiency improvement during morning and evening hours for a sunny day and during the whole day for overcast sky conditions.

Subjective and physiological responses towards daylit spaces with contemporary façade patterns in virtual reality: Influence of sky type, space function, and latitude

Recent studies have shown that the façade and light patterns in a space are an important factor in the occupants' experience, but little is known about the generalizability of these findings in different lighting conditions, uses of space, or latitudes. This study employed virtual reality to investigate the effects of façade geometry and daylight patterns on space impressions and physiological responses (skin conductance, heart rate, and heart rate variability), while simultaneously examining the effect of sky type, spatial context, and latitude on participant responses. In an experimental study conducted in Switzerland and Greece, 256 participants were exposed to immersive interior scenes with six façade geometry variations with the same perforation ratio, derived from contemporary architecture. Participants evaluated the scenes under different sky types (clear sky with high or low sun angle, or overcast sky) and spatial contexts (working or socializing). The façade geometry influenced both the appraisal (how pleasant, interesting, exciting, or calming the space was perceived) and the visual appearance of the space (how complex, bright, or spacious the space was perceived). Façade geometry also influenced the reported satisfaction with the amount of view, with a façade variation with small, irregularly distributed openings driving this effect. Neither the sky type nor the spatial context influenced space impressions. Results showed a significant effect of country and an interaction between country and façade geometry only for ratings of excitement, with participants in Greece rating specific façade variations as more exciting than participants in Switzerland. Skin conductance level (logΔSCL) decreased under exposure to a social context in clear sky with a low sun angle compared to a working context in overcast sky conditions. No significant effects were found for the other physiological measures. The results of the present study show that façade geometry was the main driver of the participants’ spatial experience, inducing perceptual effects that were robust to variations in sky type and space function and to regional differences (except for excitement). These findings have implications for the built environment, delineating the façade geometry as an important design tool with a high application potential across lighting conditions and space uses, and across latitudes between central and southern Europe.

Comparison of Pond Depth and Ice Thickness Retrieval Algorithms for Summer Arctic Sea Ice

In order to satisfy the demand of key sea ice parameters, including melt pond depth Hp and underlying ice thickness Hi, in studies of Arctic sea ice change in summer, four algorithms of retrieving Hp and Hi were compared and validated by using optical data of melt ponds from field observations. The Malinka18 algorithm stood out as the most accurate algorithm for the retrieval of Hp. For the retrieval of Hi, Malinka18 and Zhang21 algorithms could also provide reasonable results and both can be applied under clear and overcast sky conditions, while retrievals under clear sky conditions are more accurate. The retrieval results of Hi for Lu18 agreed better with field measurements for thin ice (Hi < 1 m) than that for thick ice, but those results of Hp were not satisfactory. The König20 algorithm was only suitable for clear sky conditions, and underestimated Hp, while showing a good agreement with Hp < 0.15 m. For Arctic applications, Malinka18 and Zhang21 algorithms provided a basis and reference for the satellite optical data such as WoeldView2 to retrieve Hp and Hi. Malimka18 also showed the ability to retrieve Hi, except for the Lu18 algorithm if pond color captured by helicopters and unmanned aerial vehicles were available. This study identifies the optimal algorithm for retrieval of Hp and Hi under different conditions, which have the potential to provide necessary data for numerical simulations of Arctic sea ice changes in summer.

Simple low-light image enhancement based on Weber–Fechner law in logarithmic space

In an environment with poor illumination, such as indoor, night, and overcast conditions, the image information can be seriously lost, which affects the visual effect and degrades the performance of machine systems. However, existing methods such as retinex-based method, dehazing model-based method, and machine learning-based method usually have high computational complexity or are prone to color distortion, noise amplification, and halo artifacts. To balance the enhancement effect and processing speed, this paper applies the Weber–Fechner law to the grayscale mapping in logarithmic space and proposed an adaptive and simple color image enhancement method based on the improved logarithmic transformation. In the framework, the brightness component is extracted from the scene of the low-light image using Gaussian filtering after color space conversion. The image is logarithmically transformed by adaptively adjusting the parameters of the illumination distribution to improve the brightness of the image. The color saturation is hence compensated. The proposed algorithm adaptively reduces the impact of non-uniform illumination on the image, and the enhanced image is clear and natural. Our experimental results demonstrate improved performance to the existing image enhancement approaches.

Investigation and analysis of actual atmospheric scattered radiance and slant visibility by two-wavelength Raman-Mie lidar

Considering the necessity of lidar for atmospheric scattered radiance measurement, and the application scenario in civil aviation airports, an eye-safe two-wavelength Raman-Mie lidar is proposed for slant visibility measurements, which differs from the existing Mie-scattering slant visibility lidar. Lidar system is to provide atmospheric aerosol parameters for SBDART model, so as to solve the calculation of actual atmospheric scattered radiance. The obtained information including the total irradiance, the scattered radiance, and the atmospheric transparency are combined to calculate the contrast ratio between the object and the background.Lidar experiments were carried out over Xi'an University of Technology, China (34.233°N, 108.911°E), and two cases conducted under overcast and haze conditions are investigated. Using the 33-layer atmospheric aerosol list by vertical lidar detection, the 33-layer actual atmospheric scattered radiance and the total solar irradiance are obtained by SBDART model. The atmospheric transparency is further obtained by slant scanning detection. Taking the playground runway and the grassland as the object and the background, the contrast ratio curves can be calculated with consideration of actual atmospheric scattered radiance and atmospheric transparency, and the slant visibility distances can be thus obtained at any slant directions under the contrast ratio of 0.05. The results under overcast condition showed that, the obtained slant visibility is at the distance of 9 km and 11.2 km at a zenith angle of 50° and 70°, with the statistical measurement error of 12.5% and 6.54%. The results under haze weather condition also differs at slant directions, the slant visibility distances varied ranging from 4.4 km to 6.51 km, and the statistical measurement errors are approximately of 10.21% and 8.89%. The results demonstrated the developed two-wavelength Raman-Mie lidar provides a new solution to actual atmospheric scattered radiance measurements, and also validated its feasibility and reliability for accurate slant visibility measurements.

Carbon dioxide measurements above a wheat crop. II CO2 flux density and the effects of diffuse radiation

The relationships between the daytime CO2 flux density above a wheat crop and both solar irradiance and evapotranspiration are investigatedusing physical and biophysical measurements made in 1971 in Australia. Well-established flux‒gradient relations are used to estimate the hourly CO2flux density using the measured CO2 concentration at heights of 1 m and 2 m above the crop.Principal component regression identifies four key environmental variables (diffuse and beam shortwave irradiance, leaf-area index, humidity deficit) whose variations together explain almost 80% of the variations in the hourly CO2 flux. For the diffuse ratio Sd/Sg ≈ 0.9 (generally overcast skies), where Sd and Sg are the observed diffuse and global broadband shortwave irradiances (wavelength range 285 nm to 2800 nm), respectively, both light-use and water-use efficiencies are found to be around double those for Sd/Sg ≈ 0.1 (sunny skies). For a given value of Sg this doubling in the water-use efficiency is primarily due to the sensitivity of the CO2 flux to the diffuse ratio.Profile measurements of narrowband (350 to 950 nm) irradiance within the canopy confirm that the increase in light-use efficiency is primarily due to the greater interception of radiation in the canopy under an increased diffuse ratio, up to 15 percent in overcast conditions.

Anthropogenic Illumination as Guiding Light for Nocturnal Bird Migrants Identified by Remote Sensing

Migrant birds rely on environmental and celestial cues for navigation and orientation during their journeys. Adverse weather, such as heavy rain or fog, but also thick layers of low-level clouds, affect visibility and can challenge birds’ ability to orientate. Therefore, birds typically favour certain meteorological conditions for migration. Photopollution from artificial lights outdoors and radiated from buildings is known to negatively affect nocturnal migrants’ flight behaviour and trajectories, which may lead to collisions with human infrastructure. Positive effects of artificial light have been identified in some stationary birds, e.g., for extended foraging hours, though not during migration. In the present study, we show the effect of artificial light on the concentration and flight directions of migrating birds during overcast conditions in the peri-urban woodland in Southern Finland. Overcast conditions, by low-level clouds, prompted birds to migrate at low altitudes. Instead of spatially homogenous large-scale migration patterns, birds were observed to adapt their flight directions, in accordance with the artificial lights of the urbanized area. By using dual- and single-polarisation weather radar data we were able to study small-scale patterns of bird movements under the influence of low-level cloud layers. These cases show the remarkable capability of the existing weather radar networks to study bird migration.

Biased Maximum Power Extraction from a PV during Low Irradiation and a Highly Stiffed Grid Condition

Growing electrical demand is to be met dynamically through conventional and nonconventional power sources. PV power generation plays a vital role. Because of low irradiation and overcast weather condition, the installed PV sources are not fully utilized. Many research papers were presented to extract maximum power from PV using various MPPT techniques. This paper presents a new idea of implementing a biased transformer to extract maximum power during the above condition. The proposed method uses three winding transformers to give sufficient biased voltage and current. The biased current and voltage were obtained from the grid that is fed to the primary winding—two of the three winding transformers through the controller. A 10 kW panel is checked for low irradiation and overcast weather condition using the biased MPPT technique. The proposed method is compared with the conventional incremental conductance method with power, cost, and efficiency analysis. Simulation was carried out in MATLAB/Simulink software and experimentally evaluated through a suitable hardware setup.

Extension of PAR Models under Local All-Sky Conditions to Different Climatic Zones

Four models for predicting Photosynthetically Active Radiation (PAR) were obtained through MultiLinear Regression (MLR) and an Artificial Neural Network (ANN) based on 10 meteorological indices previously selected from a feature selection algorithm. One model was developed for all sky conditions and the other three for clear, partial, and overcast skies, using a sky classification based on the clearness index (kt). The experimental data were recorded in Burgos (Spain) at ten-minute intervals over 23 months between 2019 and 2021. Fits above 0.97 and Root Mean Square Error (RMSE) values below 7.5% were observed. The models developed for clear and overcast sky conditions yielded better results. Application of the models to the seven experimental ground stations that constitute the Surface Radiation Budget Network (SURFRAD) located in different Köppen climatic zones of the USA yielded fitted values higher than 0.98 and RMSE values less than 11% in all cases regardless of the sky type.