Cloudy Sky Conditions Research Articles

Evaluation of the Surface Downward Longwave Radiation Estimation Models over Land Surface

Surface downward longwave radiation (SDLR) is crucial for maintaining the global radiative budget balance. Due to their ease of practicality, SDLR parameterization models are widely used, making their objective evaluation essential. In this study, against comprehensive ground measurements collected from more than 300 globally distributed sites, four SDLR parameterization models, including three popular existing ones and a newly proposed model, were evaluated under clear- and cloudy-sky conditions at hourly (daytime and nighttime) and daily scales, respectively. The validation results indicated that the new model, namely the Peng model, originally proposed for SDLR estimation at the sea surface and applied for the first time to the land surface, outperformed all three existing models in nearly all cases, especially under cloudy-sky conditions. Moreover, the Peng model demonstrated robustness across various land cover types, elevation zones, and seasons. All four SDLR models outperformed the Global Land Surface Satellite product from Advanced Very High-Resolution Radiometer Data (GLASS-AVHRR), ERA5, and CERES_SYN1de-g_Ed4A products. The Peng model achieved the highest accuracy, with validated RMSE values of 13.552 and 14.055 W/m2 and biases of −0.25 and −0.025 W/m2 under clear- and cloudy-sky conditions at daily scale, respectively. Its superior performance can be attributed to the inclusion of two cloud parameters, total column cloud liquid water and ice water, besides the cloud fraction. However, the optimal combination of these three parameters may vary depending on specific cases. In addition, all SDLR models require improvements for wetlands, bare soil, ice-covered surfaces, and high-elevation regions. Overall, the Peng model demonstrates significant potential for widespread use in SDLR estimation for both land and sea surfaces.

Experimental investigation of the impact of model complexity on indoor daylight spectral simulations

Daylight spectral simulation is crucial for designing functional, healthy spaces and predicting light interactions. It is essential for accurate non-image-forming effects of light calculations. This study addresses the knowledge gap in reproducing indoor daylight spectral conditions in the built environment. Using varying levels of geometry (LOG) and information (LOI), simulation accuracy was assessed by comparing it with experimental data from two offices over three days with cloudy and clear sky conditions. The lowest accuracy was found with high LOI and low LOG simulations. For the highest accuracy, specific material spectral properties are needed, while spectrally-neutral materials at low LOG produced comparable results. Simulations near and facing windows were the most accurate. The study concludes that to reproduce indoor daylight spectral conditions, modelling should use either the lowest or highest geometry and information complexity, depending on available modelling time and required accuracy.

All weather land surface temperature estimation by combining thermal infrared and passive microwave radiometry: a study over India

ABSTRACT Land Surface Temperature (LST) plays a crucial role in water and energy cycle studies. However, clouds pose a significant challenge in obtaining continuous LST time series from Thermal Infrared (TIR) sensors. To overcome this challenge, this study leverages the potential of Passive Microwave Radiometry (PMR), which offers all-weather observation capabilities, albeit at a coarser spatial resolution to estimate all-weather LST over India. In this study, we trained a Random Forest (RF) model using clear sky LST from either Moderate Resolution Spectro Radiometer (MODIS) or Visible Infrared Imaging Radiometer Suite (VIIRS) and passive microwave observations from Advanced Microwave Scanning Radiometer-2 (AMSR2), enabling LST estimation at a 1 km spatial resolution under clear and cloudy conditions. The performance of the models was evaluated by comparing the RF simulated LST with observed LST data from MODIS and VIIRS satellites. The Root Mean Square Error (RMSE) for the RF models was found to be 2.17 K and 2.29 K respectively, with coefficient of determination (R2) values of 0.97 for both the models. Furthermore, comparisons with in-situ observations resulted in RMSE values of 2.24–3.70 K and 2.40–4.07 K for clear sky and cloudy sky LST, respectively, for MODIS. Similarly, for the VIIRS LST prediction model, the RMSE values were 2.61–3.51 K and 2.60–3.97 K for clear and cloudy sky conditions. These findings demonstrate the potential of using passive microwave radiometers to estimate LST and highlight the applicability of the RF model for LST estimation under overcast conditions.

Effects of increasing spatial resolution on the spatial information content and accuracy of downward surface shortwave radiation

Downward Surface Shortwave Radiation (DSSR) plays a crucial role in ecological, hydrological, and solar photovoltaic studies. The estimation of DSSR at higher spatial resolutions is increasingly popular. However, the impact of increasing spatial resolution on spatial information content and accuracy of DSSR estimates is not well understood. Addressing this knowledge gap, an all-sky DSSR dataset at varying spatial resolutions (0.8° to 0.01°) in China was estimated using MODIS top-of-atmosphere reflectance data. Subsequently, the spatial heterogeneity and accuracy of the DSSR dataset as well as its driving factors were analyzed. The results indicate that the magnitude of the increase in spatial heterogeneity varies across different regions as the spatial resolution increases. On the edge of the Qinghai-Tibet Plateau, the spatial heterogeneity experiences the most significant increase. To quantify the factors driving the spatial heterogeneity of DSSR, the Correlation Coefficients (CC) were calculated between the Coefficient Of Variation (COV) of DSSR and the COVs of relevant factors. In cloudy-sky conditions, the CC between the COV of DSSR and cloud optical thickness ranged from 0.54 to 0.62, whereas the CC between DSSR COV and Column Water Vapor (CWV) COV was between 0.72 and 0.78. Under clear-sky conditions, the COV of CWV, aerosol optical depth, and PM2.5 showed more significant correlations with DSSR COV compared to altitude COV. Validation using ground-based measurements revealed that the accuracy of DSSR decreased at coarser spatial resolutions due to the presence of mixed pixel samples. Moreover, it was demonstrated that a spatial resolution of 0.05° offered the highest cost-effectiveness when estimating DSSR. These insights significantly advance our understanding of the role of spatial resolutions in DSSR estimation and are instrumental in guiding the selection of optimal resolutions for such studies.

Elucidating the boundary layer turbulence dissipation rate using high-resolution measurements from a radar wind profiler network over the Tibetan Plateau

Abstract. The planetary boundary layer (PBL) over the Tibetan Plateau (TP) exerts a significant influence on regional and global climate, while its vertical structures of turbulence and evolution features remain poorly understood, largely due to the scarcity of observations. This study examines the vertical profile of and daytime variation in the turbulence dissipation rate (ε) in the PBL and free troposphere over the TP using the high-resolution (6 min and 120 m) measurements from a radar wind profiler (RWP) network, combined with hourly data from ERA5 during the period from 1 September 2022 to 31 October 2023. Observational analyses show that the magnitude of ε below 3 km under all-sky conditions exhibits a large spatial discrepancy over the six RWP stations over the TP. Particularly, the values of ε at Minfeng and Jiuquan over the northern TP and at Dingri (alternately Tingri) over the southern TP are roughly an order of magnitude greater than those at Lijiang, Ganzi (alternately Garzê), and Hongyuan over the eastern TP. This could be partially attributed to the difference in land cover across the six RWP stations. In terms of the diurnal variation, ε rapidly intensifies from 09:00 local standard time (LST) to 14:00 LST and then gradually levels off in the late afternoon. Under clear-sky conditions, both ε and the planetary boundary layer height (zi) are greater compared with cloudy-sky conditions, which could be due to the cooling effect of clouds, which reduces the solar irradiation reaching the surface. In the lower PBL (0.3 ≤ z/zi ≤ 0.5), where z is the height above ground level, the dominant influential factor in the development of turbulence is the surface–air temperature difference (Ts−Ta). By comparison, in the upper PBL (0.6 ≤ z/zi ≤ 1.0), both Ts−Ta and vertical wind shear (VWS) affect the development of turbulence. Above the PBL (1.0 < z/zi ≤ 2.0), the shear production resulting from VWS dominates the variation in turbulence. Under cloudy-sky conditions, the reduced Ts−Ta and weakened surface sensible heat flux tend to inhibit the turbulent motion in the PBL. On the other hand, the strong VWS induced by clouds enhances the turbulence above the PBL. The findings obtained here underscore the importance of the RWP network in revealing the fine-scale structures of the PBL over the TP and gaining new insight into the PBL evolution.

Evaluation and improvement of parameterization methods for estimating cloudy-sky downwelling surface longwave radiation from geostationary satellite data

ABSTRACT Estimating downwelling surface longwave radiation (DSLR) under cloudy-sky conditions presents a significant challenge, the parameterization methods used to estimate cloudy-sky DSLR may yield disparate results for the same scenario. Hence, it is imperative to undertake a comparative and validation study of these methods to comprehend their applicability. This study compares and validates five parameterized schemes for estimating cloudy-sky DSLR using data from the Fengyun-4A (FY-4A) and Himawari-8 geostationary satellites. Additionally, an improved algorithm for cloudy-sky DSLR estimation is proposed, integrating the radiation effect of the entire cloud layer and a nonlinear parameterization algorithm. The verification results demonstrate that the nonlinear parameterization algorithm exhibits higher accuracy compared to those reliant on cloud-base temperature. Among these, the improved algorithm has high accuracy similar to the nonlinear algorithms in BSRN (Baseline Surface Radiation Network) and TPDC (National Tibetan Plateau Data Center) sites, its RMSE are 29.62 and 30.09 W/m2, respectively. Sensitivity analysis reveals that cloud type and cloud-base temperature exert a pronounced influence on DSLR estimation, particularly within parameterization algorithms based on cloud-base temperature, warranting thorough consideration. Furthermore, the influence of land cover type and surface elevation, especially in high-altitude regions with bare surfaces, should not be disregarded in DSLR estimation.

Understanding the impact of sky diffuse irradiance on curved photovoltaic modules

Modules utilized in vehicle-integrated photovoltaics (VIPV) have particularities that make them differ from standard PV modules. These particularities are related to their curvature and operating conditions (changing locations, orientations, etc.) and they need to be addressed in the characterization. A vital characterization test is the angular response test, which allows obtaining the electrical response of the module under different angles of incidence and orientations. Results from these tests on real commercial modules presented some dispersion, which is related to diffuse irradiance. Two outdoors experiments involving a programmable dual-axis tracker were conducted to verify its impact: the first one was made with a 1D highly curved module under cloudy sky conditions to identify the effect of diffuse irradiance on such modules and the second experiment assessed the angular response of a 2D commercial curved module under clear sky conditions. Based on the findings, recommendations are given to minimize dispersion in outdoors angular response measurements.

Divergent Responses of Summer Terrestrial Evapotranspiration to Cloud Increase in East Asia

AbstractCloud impact on terrestrial evapotranspiration (ET) can be significant, while a fundamental understanding of ET response to cloud change has not been addressed in regional aspects. In this study, seven ET datasets from satellite and land surface models are used to analyze the summer ET in response to low cloud cover (LCC) over East Asia, in combination with satellite microwave and optical vegetation data, as well as ERA5 climatic and surface parameters. In general, all ET datasets present a strong negative relationship with LCC over dense vegetation (e.g., forests), which leads to the ET reduction of more than −0.5 mmday−1 under the large LCC increase, compared with the least cloudy sky conditions. Such reduction is stronger under more humid and denser forests (aridity index AI > 0.5 and enhanced vegetation index EVI > 0.6). In contrast, a positive relationship between ET and LCC presents over arid and sparse lands (AI < 0.2 and EVI < 0.2), accompanied by enhanced ET (>0.2 mmday−1). Analysis shows that under increased LCC conditions, substantial reduction in radiation availability results in the decline in both plant transpiration (ETveg) and soil evaporation (ETsoil) over humid dense vegetation, dominating the overall negative response. The increase of near‐surface relative humidity over arid sparse vegetation may indicate a stronger moisture availability, which promotes ETsoil and partly offsets the negative effect of radiation reduction. The change of vegetation water content, indicated by a satellite microwave vegetation index, is important for ETveg over arid mountainous lands with cloud cover. These findings contribute new insights to the understanding of vegetation‐atmosphere interactions.

Porous polymer bilayer with near-ideal solar reflectance and longwave infrared emittance

Abstract This study explores the optical design of a daytime radiative cooler with near-ideal solar reflectance and longwave infrared (LWIR) emittance through materials selection and nanostructuring. Focusing on polymers as a materials platform, we introduce a bilayer architecture, comprising a porous poly(vinylidene fluoride-co-hexafluoropropene) (P(VdF-HFP)) topcoat that serves as a low-index LWIR emissive effective medium, over a nanofibrous, solar scattering polytetrafluoroethene underlayer. This novel configuration yields a superwhite coating with a near-ideal solar reflectance of >0.99, and a blackbody-like near-normal and hemispherical LWIR emittances of ∼0.98 and ∼0.96 respectively. Under humid and partially cloudy sky conditions unfavorable for radiative heat loss, these values enable the bilayer radiative cooler to achieve a sub-ambient of 2.3 °C. Given that the porous polymer bilayer uses scalable fabrication processes and commercially available materials, it holds significant promise for device-scale, as well as building thermoregulation applications.

Enerji Verimli Aydınlatma Tasarımı: Farklı Pencere Boyutlarında Optimum Gün Işığı Kullanımı Üzerine Bir Araştırma

In recent years, with the frequently discussed concept of sustainability, designers have been increasingly demanded to improve spatial comfort conditions. The growing emphasis on energy efficiency in design has led designers to consider these issues at earlier stages of the design process. Daylight, seen as a clean, uninterrupted energy source and a cost-effective alternative to artificial lighting, also ensures visual comfort for individuals due to its good color rendering. Despite all these well-known benefits, design criteria have not been established to reduce the energy consumption rate caused by artificial lighting while taking into account the factors affecting daylight, an important input. This study presents an investigation aimed at achieving energy savings in lighting by using the ideal window concept and other parameters to optimally benefit from daylight. The study has been applied under cloudy sky and deep room conditions, which represent the worst-case scenarios. As an alternative to time-consuming mathematical calculations, the Velux Daylight Visualizer lighting simulation program was used to create three-dimensional designs for horizontal, vertical, square, and roof windows separately, and the effects of these windows on the daylight factor were analyzed. The impact of different furniture colors in the interior space was also examined. Following the investigations, it was observed that roof windows produced more daylight compared to others. However, since roof windows cannot be used in multi-story buildings, a comparison was made between horizontal, vertical, and square windows, and it was concluded that horizontal windows placed close to the upper wall were more efficient than the others. In addition, it was observed that lighter-colored furniture, among the light and dark furniture, produced more daylight compared to the other.

Trends from 30-Year Observations of Downward Solar Irradiance in Thessaloniki, Greece

The shortwave downward solar irradiance (SDR) is an important factor that drives climate processes and energy production and can affect all living organisms. Observations of SDR at different locations around the world with different environmental characteristics have been used to investigate its long-term variability and trends at different time scales. Periods of positive trends are referred to as brightening periods and of negative trends as dimming periods. In this study we have used 30 years of pyranometer data in Thessaloniki, Greece, to investigate the variability of SDR under three types of sky conditions (clear-, cloudy- and all-sky). The clear-sky data were identified by applying a cloud screening algorithm. We have found a positive trend of 0.38%/year for all-sky, ∼0.1%/year for clear-sky, and 0.41%/year for cloudy conditions. The consistency of these trends, their seasonal variability, and the effect of the solar zenith angle have also been investigated. Under all three sky categories, the SDR trend is stronger in winter, with 0.7, 0.4, and 0.76%/year, respectively, for all-, clear-, and cloudy-sky conditions. The next larger seasonal trends are in autumn—0.42 and 0.19%/year, for all and cloudy skies, respectively. The rest of the seasonal trends are significant smaller, close to zero, with a negative values in summer, for clear and cloudy skies. The SDR trend is increasing with increasing solar zenith angle, except under cloudy skies, where the trend is highly variable and close to zero. Finally, we discuss shorter-term variations in SDR anomalies by examining the patterns of the cumulative sums of monthly anomalies from the climatological mean, both before and after removing the long-term trend.

Variations in boundary layer stability across Antarctica: a comparison between coastal and interior sites

Abstract. The range of boundary layer stability profiles, from the surface to 500 m a.g.l. (above ground level), present in radiosonde observations from two continental-interior (South Pole Station and Dome Concordia Station) and three coastal (McMurdo Station, Georg von Neumayer Station III, and Syowa Station) Antarctic sites, is examined using the self-organizing maps (SOMs) neural network algorithm. A wide range of potential temperature profiles is revealed, from shallow boundary layers with strong near-surface stability to deeper boundary layers with weaker or near-neutral stability, as well as profiles with weaker near-surface stability and enhanced stability aloft, above the boundary layer. Boundary layer regimes were defined based on the range of profiles revealed by the SOM analysis; 20 boundary layer regimes were identified to account for differences in stability near the surface as well as above the boundary layer. Strong, very strong, or extremely strong stability, with vertical potential temperature gradients of 5 to in excess of 30 K per 100 m, occurred more than 80 % of the time at South Pole and Dome Concordia in the winter. Weaker stability was found in the winter at the coastal sites, with moderate and strong stability (vertical potential temperature gradients of 1.75 to 15 K per 100 m) occurring 70 % to 85 % of the time. Even in the summer, moderate and strong stability is found across all five sites, either immediately near the surface or aloft, just above the boundary layer. While the mean boundary layer height at the continental-interior sites was found to be approximately 50 m, the mean boundary layer height at the coastal sites was deeper, around 110 m. Further, a commonly described two-stability-regime system in the Arctic associated with clear or cloudy conditions was applied to the 20 boundary layer regimes identified in this study to understand if the two-regime behavior is also observed in the Antarctic. It was found that moderate and strong stability occur more often with clear- than cloudy-sky conditions, but weaker stability regimes occur almost equally for clear and cloudy conditions.

A novel atmospheric segmentation model for improving the accuracy of radiative cooling potential prediction

Radiative cooling offers a wide range of potential applications in the current promotion of clean energy. However, the radiative cooling potential is generally underestimated, accounting for ignoring the effect of aerosols on atmospheric longwave downward radiation. This paper proposes an atmospheric segmentation model to improve the accuracy of radiative cooling potential prediction. The heat transfer on the radiative cooling surface is analyzed, and the accuracy of the proposed atmospheric segmentation model is verified with experiments and compared with the models in existing studies. Then, the effects of aerosol optical depth, precipitable water vapor, and relative humidity on the radiative cooling potential are discussed in detail based on the atmospheric segmentation model. Finally, the map of radiative cooling potential in China is also derived from the proposed atmospheric segmentation model. The results show that the relative error of radiative cooling power between the atmospheric segmentation model prediction and experiment is only 2.4%. Furthermore, the measured and calculated atmospheric longwave downward radiations match well with each other, in which the Pearson correlation coefficients and root mean square errors are 0.9834 and 11.34 W/m2 under clear sky conditions and 0.94211 and 21.32 W/m2 under cloudy sky conditions.

Arctic warming by abundant fine sea salt aerosols from blowing snow

The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. However, the mechanisms of sea salt aerosol production remain unclear. Sea salt aerosols are typically thought to be relatively large in size but low in number concentration, implying that their influence on cloud condensation nuclei population and cloud properties is generally minor. Here we present observational evidence of abundant sea salt aerosol production from blowing snow in the central Arctic. Blowing snow was observed more than 20% of the time from November to April. The sublimation of blowing snow generates high concentrations of fine-mode sea salt aerosol (diameter below 300 nm), enhancing cloud condensation nuclei concentrations up to tenfold above background levels. Using a global chemical transport model, we estimate that from November to April north of 70° N, sea salt aerosol produced from blowing snow accounts for about 27.6% of the total particle number, and the sea salt aerosol increases the longwave emissivity of clouds, leading to a calculated surface warming of +2.30 W m−2 under cloudy sky conditions.

IMPLEMENTASI DIGITAL IMAGE PROCESSING SEBAGAI PENDETEKSI POSISI MATAHARI PADA PERANCANGAN DUAL AXIS SOLAR TRACKER

One of the uses of new renewable energy (EBT) in Indonesia which has great potential is solar panels. Solar panels are electrical devices that are used to convert solar energy into electrical energy. The limited surface area of the panels requires users to be able to pay attention to the work efficiency of solar panels. The aspect that has the most influence on optimizing the efficiency of solar panel performance is the placement of the surface of the solar panel against incoming solar radiation. Therefore, it is necessary to have a method to detect the position of the sun to provide input to the actuator so that the surface of the solar panel is positioned in the direction of the sun's rays. This study describes the accuracy of detecting the position of the sun using digital image processing methods. This process needs to be done as a reference in designing a dual axis solar tracker. Detection of the sun's position using this method gets 100% accurate results in cloudless sky conditions and gets 80% success results in cloudy sky conditions.

Generation of global 1-km daily top-of-atmosphere outgoing longwave radiation product from 2000 to 2021 using machine learning

ABSTRACT Top-of-atmosphere (TOA) outgoing longwave radiation (OLR), a key component of the Earth’s energy budget, serves as a diagnostic of the Earth’s climate system response to incoming solar radiation. However, existing products are typically estimated using broadband sensors with coarse spatial resolutions. This paper presents a machine learning method to estimate TOA OLR by directly linking Moderate Resolution Imaging Spectroradiometer (MODIS) TOA radiances with TOA OLR determined by Clouds and the Earth’s Radiant Energy System (CERES) and other information, such as the viewing geometry, land surface temperature and cloud top temperature determined by Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). Models are built separately under clear- and cloudy-sky conditions using a gradient boosting regression tree. Independent test results show that the root mean square errors (RMSEs) of the clear-sky and cloudy-sky models for estimating instantaneous values are 4.1 and 7.8 W/m2, respectively. Real-time conversion ratios derived from CERES daily and hourly OLR data are used to convert the instantaneous MODIS OLR to daily results. Inter-comparisons of the daily results show that the RMSE of the estimated MODIS OLR is 8.9 W/m2 in East Asia. The developed high resolution dataset will be beneficial in analyzing the regional energy budget.

Low-cost, open-hardware shadow band system for diffuse irradiance measurements

In this work, we present the design, implementation, and test of a low-cost, open-hardware shadow band system that enables a pyranometer to measure global and diffuse irradiance. This system was implemented in Lima, Peru, and experimentally tested by contrasting it with a commercial reference system consisting of two pyranometers, one blocked by a shadow ring. The developed shadow band system automatically opens and closes to measure the global and diffuse irradiance consecutively, respectively, without requiring regular, manual adjustments of the shadow ring position as in the reference system. Thus, it potentially saves costs on equipment to characterize de irradiance components. Initial measurements in Lima indicate 100% and at least 23% of diffuse irradiance under cloudy and clear sky conditions, respectively.

Estimation of Instantaneous Air Temperature under All-Weather Conditions Based on MODIS Products in North and Southwest China

Air temperature (Ta) is a common meteorological element involved in many fields, such as surface energy exchange and water circulation. Consequently, accurate Ta estimation is essential for the establishment of hydrological, climate, and environmental models. Unlike most studies concerned with the estimation of daily Ta from land surface temperature, this study focused on the estimation of instantaneous Ta from Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric profile products aboard the Terra and Aqua satellites. The applicability of various estimation methods was examined in two regions with different geomorphological and climate conditions, North and Southwest China. Specifically, the spatiotemporal trend of Ta under clear sky conditions can be reflected by the atmospheric profile extrapolation and average methods. However, the accuracy of Ta estimation was poor, with root mean square error (RMSE) ranging from 3.5 to 5.2 °C for North China and from 4.0 to 7.7 °C for Southwest China. The multiple linear regression model significantly improved the accuracy of Ta estimation by introducing auxiliary data, resulting in RMSE of 1.6 and 1.5 °C in North China and RMSE of 2.2 and 2.3 °C in Southwest China for the Terra and Aqua datasets, respectively. Since atmospheric profile products only provide information under clear sky conditions, a new multiple linear regression model was established to estimate the instantaneous Ta under cloudy sky conditions independently from atmospheric profile products, resulting in RMSE of 1.9 and 1.9 °C in North China and RMSE of 2.5 and 2.8 °C in Southwest China, for the Terra and Aqua datasets, respectively. Finally, instantaneous Ta products with high accuracy were generated for all-weather conditions in the study regions to analyze their Ta spatial patterns. The accuracy of Ta estimation varies depending on MODIS datasets, regions, elevation, and land cover types.

Overirradiance conditions and their impact on the spectral distribution at low- and mid-latitude sites

Lately, the photovoltaics community has shown an increased interest in overirradiance conditions as there is the possibility that such conditions might lead to malfunctions in photovoltaic systems. Varying irradiance levels, recurrence, and duration of such conditions have been reported worldwide, but experimental studies on the spectral distribution of overirradiance conditions are still scarce. This work analyses measured spectral irradiance of overirradiance conditions along with spectra under clear and cloudy sky conditions in three different sites at low- (Lima-Peru) and mid-latitudes (Madrid-Spain and Berlin-Germany) collected for two years. The Average Photon Energy (APE) was used as a representative index of the spectral distribution. For each site, taking the APE under clear sky into account as a reference, it could be shown that the spectra under cloudy skies are blue-shifted, and the overirradiance spectra are red-shifted independently of the location. The red-shift is proportional to the irradiance enhancement intensity. In addition, all sites have different degrees of blue–shift for cloudy skies, with Lima, Madrid, and Berlin exhibiting a difference in APE compared to clear sky conditions of 17 meV, 38 meV, and 43 meV on average, respectively. This difference in APE for the overirradiance conditions compared to clear sky conditions is also independent of the location with a mean value of (8 ± 1)meV. These spectral shift observations experimentally confirm prior assumptions that overirradiance conditions predominantly cause an enhancement of the direct spectral irradiance.

Lowest-threshold solar laser operation under cloudy sky condition

Classical solar-pumped lasers often demand a significant amount of concentrated solar power for laser emission, which is only attainable under clear sky condition, limiting their applicability. In this research, we report the first solar laser emission at very low threshold solar power under cloudy sky condition by end-side-pumping a 2.5 mm diameter, 25 mm length Ce:Nd:YAG rod at the focus of a parabolic mirror concentrator. The Ce:Nd:YAG solar laser performance was also evaluated under clear sky condition for comparison. Low threshold pump power of 32.4 W for continuous-wave solar-pumped laser was obtained under clear sky condition, being two times lower than the previous record. However, the cloud-filtered infrared sunlight enabled notable improvements in the solar laser performance by lessening the thermal lensing effects in the laser medium. The threshold pump power was further reduced to 29.2 W and maximum solar laser output of 14 W was successfully measured. This nearly doubled the focal slope efficiency from 4.03% during clear weather to 7.71% under a cloudy sky. The solar-to-laser conversion efficiency of 6.32% was nearly tripled compared to the 2.32% on a clear sky, while the solar laser conversion efficiency of 21.47 W/m2 was nearly twice the value of 12.62 W/m2 obtained on a clear day. This demonstrates that a cloudy environment could be an asset for solar laser research.