Clear Sky Conditions Research Articles

Regional Algorithm of Quantitative Assessment of Cyanobacteria Blooms in the Eastern Part of the Gulf of Finland Using Satellite Ocean Color Data

Summer blooms of potentially harmful cyanobacteria are common in the Baltic Sea. Under clear sky conditions, the cyanobacterial blooms are easily detectable from space. We propose a new regional algorithm for cyanobacteria biomass estimation from satellite data in the eastern part of the Gulf of Finland, developed on the basis of field measurements in July–August 2012–2014. The multi-regression equation defines the cyanobacteria biomass as a function of the particle backscattering coefficient and chlorophyll concentration. The use of this equation provides the best performance in comparison to the linear one, which is reflected in both R2 and RMSE values (0.61 and 272 mg m−3 respectively). Unlike other algorithms, which determine only the cyanobacteria bloom area in the Baltic Sea, our algorithm allows the determination of both a bloom area and its intensity. Considering the algorithm errors, the bloom detection threshold has been shifted from the 200 mg m−3 determined by biologists to 300 mg m−3. Based on data from the MODIS-Aqua satellite ocean color scanner, the spatial and temporal variability of cyanobacterial blooms in this region from 2003 to 2022 was analyzed. Significant interannual variability of cyanobacteria biomass was revealed in the central part of the studied region, with minimum values in 2014 and maximum in 2004. The record bloom during the studied period occurred in July 2004 (the average cyanobacteria biomass was 780 mg m−3). The weakest blooms were observed in 2009, 2010, and 2014, when both in July and August, the bloom areas did not exceed 30% of the study region.

EUSO-SPB1 mission and science

The Extreme Universe Space Observatory on a Super Pressure Balloon 1 (EUSO-SPB1) was launched in 2017 April from Wanaka, New Zealand. The plan of this mission of opportunity on a NASA super pressure balloon test flight was to circle the southern hemisphere. The primary scientific goal was to make the first observations of ultra-high-energy cosmic-ray extensive air showers (EASs) by looking down on the atmosphere with an ultraviolet (UV) fluorescence telescope from suborbital altitude (33 km). After 12 days and 4 h aloft, the flight was terminated prematurely in the Pacific Ocean. Before the flight, the instrument was tested extensively in the West Desert of Utah, USA, with UV point sources and lasers. The test results indicated that the instrument had sensitivity to EASs of ⪆3 EeV. Simulations of the telescope system, telescope on time, and realized flight trajectory predicted an observation of about 1 event assuming clear sky conditions. The effects of high clouds were estimated to reduce this value by approximately a factor of 2. A manual search and a machine-learning-based search did not find any EAS signals in these data. Here we review the EUSO-SPB1 instrument and flight and the EAS search.

Assessment of atmospheric emissivity models for clear-sky conditions with reanalysis data

Atmospheric longwave downward radiation (Ld) is one of the significant components of net radiation (Rn), and it drives several essential ecosystem processes. Ld can be estimated with simple empirical methods using atmospheric emissivity (εa) submodels. In this study, eight global models for εa were evaluated, and the best-performing model was calibrated on a global scale using a parametric instability analysis approach. The climatic data were obtained from a dynamically consistent scale resolution of basic atmospheric quantities and computed parameters known as NCEP/NCAR reanalysis (NNR) data. The performance model was evaluated with monthly average values from the NNR data. The Brutsaert equation demonstrated the best performance, and then it was calibrated. The seasonal global trend of the Brutsaert equation calibrated coefficient ranged between 1.2 and 1.4, and the K-means analysis identified five homogeneous zones (clusters) with similar behavior. Finally, the calibrated Brutsaert equation improved the Rn estimation, with an error reduction, at the worldwide scale, of 64%. Meanwhile, the error reduction for each cluster ranged from 18 to 77%. Hence, Brutsaert’s equation coefficient should not be considered a constant value for use in εa estimation, nor in time or location.

Explainable forecasting of global horizontal irradiance over multiple time steps using temporal fusion transformer

Accurate prediction of solar irradiance is essential for the successful integration of solar power plants into electrical systems. Despite recent advancements in deep learning technology yielding impressive results in solar forecasting, their lack of interpretability has hindered their widespread adoption. In this paper, we propose a novel approach that integrates a Temporal Fusion Transformer (TFT) with a McClear model to achieve accurate and interpretable forecasting performance. The TFT is a deep learning model that provides transparency in its predictions through the use of interpretable self-attention layers for long-term dependencies, recurrent layers for local processing, specialized components for feature selection, and gating layers to suppress extraneous components. The model is capable of learning temporal associations between continuous time-series variables, namely, historical global horizontal irradiance (GHI) and clear sky GHI, accounting for cloud cover variability and clear sky conditions that are often ignored by most machine learning solar forecasters. Additionally, it minimizes a quantile loss during training to produce accurate probabilistic forecasts. In this study, we evaluate the performance of hourly GHI forecasts on eight diverse datasets with varying climates: temperate, cold, arid, and equatorial, for multiple temporal horizons of 2, 3, 6, 12, and 24 h. The model is benchmarked against both climatological persistence for deterministic forecasting and Complete History Persistence Ensemble for probabilistic forecasting. To prove that our model is not location locked, it has been blind tested on four completely different datasets. The results demonstrate that the proposed model outperforms its counterparts across all forecast horizons.

Evaluation of direct beam energy received by convex solar collectors and their optimal orientations

We use analytical and numerical methods to evaluate the daily beam energy received by some convex surfaces. Spherical, hemispherical, cylindrical, and semi-cylindrical convex surfaces with arbitrary tilt angles have been investigated and compared with a flat surface of unit area. Diffusive irradiations (sky and ground) were not considered. For hemispherical and semi-cylindrical surfaces, the optimal orientations at which the received beam energy is maximal were obtained for each day of the year. The dependence of the optimal tilt angle on the day of the year is qualitatively the same as for the flat surface. Clear sky condition has been assumed to hold in this work. It is shown that a flat surface per unit of its area receives highest beam energy among other convex surfaces whereas a sphere receives the least amount. Furthermore, the received daily beam energy per unit of the ground-occupied area has been calculated. In this case, a cylindrical surface with a range of values of radius to height ratio receives the highest amount of energy whereas a flat surface receives the least. This aspect becomes noticeable in places where there are some limits, e.g., land price or any other limitation on the available surface area.

Hourly global solar radiation prediction based on seasonal and stochastic feature

Accurate and detailed solar radiation data play a crucial role in the simulation of building thermal and photovoltaic systems. However, developing a highly precise and dependable solar radiation model using cost-effective data has proven challenging. This work proposes a new attenuation solar radiation model formed by conducting a comprehensive analysis of existing models and gaining new insights into solar radiation's seasonal and stochastic properties. Meanwhile, the model is constructed using easily obtainable surface meteorological parameters. The results demonstrate that the proposed model exhibits good performance in terms of prediction accuracy. Moreover, the majority of existing hourly solar radiation models have been primarily developed for clear-sky conditions. However, there is a growing demand for solar radiation hourly estimations that can uphold a high level of accuracy and reliability even in different weather state. Conversely, the proposed model is developed and validated by more than twenty year's meteorological data encompassing various weather conditions in Japan. It effectively captures the stochastic nature of solar radiation by utilizing turbidity parameters, even on cloudy and rainy days. Additionally, the inclusion of interaction variables significantly enhances its interpretability.

Investigation of Turbulent Dissipation Rate Profiles from Two Radar Wind Profilers at Plateau and Plain Stations in the North China Plain

Turbulence is ubiquitous in the planetary boundary layer (PBL), which is of great importance to the prediction of weather and air quality. Nevertheless, the profiles of turbulence in the whole PBL as observed by radar wind profilers (RWPs) are rarely reported. In this communication, the purpose was to investigate the vertical structures of turbulence dissipation rate (ε) obtained from the Doppler spectrum width measurements from two RWPs at plateau (Zhangbei) and plain (Baoding) stations in the North China Plain for the year 2021, and to tease out the underlying mechanism for the difference of ε between Zhangbei and Baoding. Under clear-sky conditions, the annual mean value of ε in the PBL over the plateau station was found to be higher than that over the plain station throughout the daytime from 0900 to 1700 local standard time. The magnitude of ε at both stations showed significant seasonal variation, with the strongest ε in summer but the weakest in winter. If a larger difference between the 2 m air temperature and surface temperature (Ta−Ts), as a surrogate of sensible heat flux, is observed, the turbulence intensity tends to become stronger. The influence of vertical wind shear on turbulence was also analyzed. Comparison analyses showed that the plateau station of Zhangbei was characterized by larger sensible heat flux and stronger wind shear compared with the plain station of Baoding. This may account for the more intense ε within the PBL of Zhangbei. Moreover, the magnitude of ε in the PBL was positively correlated with the values of both Ta−Ts and vertical wind shear. The findings highlight the urgent need to characterize the vertical turbulence structure in the PBL over a variety of surfaces in China.

Year-long ground-based observations of bromine oxide over Bharati Station, Antarctica

Bromine chemistry plays an important role in tropospheric ozone depletion events in polar regions. Autocatalytic reactions lead to bromine explosion events, causing ozone depletion to near-zero levels in the polar troposphere. Bromine chemistry over Antarctica is not fully understood, and ground-based observations are scarce. This work presents year-long observations of bromine oxide (BrO) over the Bharati station (69.41°S, 76.19°E) using Multi-axis Differential Optical Absorption Spectroscopy (MAX-DOAS) from December 2018 to February 2020. The results show that elevated BrO mixing ratios were found during spring (September), with a maximum value of 10.21 ± 4.38 pptv for clear sky conditions and 33.15 ± 2.23 pptv for cloudy conditions. BrO was not observed above the detection limit (∼3 × 1013 molecule cm−2) outside spring on clear days. In general, lower mixing ratios were observed on clear days over Bharati compared to stations in West Antarctica. This indicates a different source strength over East Antarctica compared to West Antarctica. BrO vertical column densities were high during spring, with a maximum value of 1.34 ± 0.35 × 1014 molecule cm−2. The vertical profiles of the BrO mixing ratios show a peak at the surface during spring (average of 6.5 ± 1.91 pptv), decreasing sharply with altitude. Back trajectories show that air masses passing over the first year ice showed higher BrO, although factors such as meteorology play an important role in determining the absolute levels. Using a box model, we show that bromine chemistry can deplete as much as 2.15 ppb of ozone in a day at the Bharati Station on clear days, which shows that it does not lead to complete ozone depletion events over Bharati.

Photoluminescence imaging of field-installed photovoltaic modules in diffuse irradiance

Photoluminescence imaging under sunlight excitation has in the recent years been proposed as a promising inspection technique of field-installed photovoltaic modules. Virtually, all studies have been conducted in full sunlight and clear sky conditions. A study in which photoluminescence images had been acquired at an irradiance level below 100 W m−2 using the lock-in technique has shown the potential of these images with respect to defect analysis. Additionally, as on-site measurement techniques are subject to weather conditions, it would be favorable to extend the applicability of photoluminescence imaging to a wider range of irradiance levels. A method for photoluminescence imaging which does not use the lock-in technique for the purpose of filtering of sunlight was proposed recently. The present study extends the application of this approach to diffuse irradiance conditions. We demonstrate that the method gives valuable information about the modules also in the case of image acquisition under diffuse global in-plane irradiance as low as 40 W m−2. Photoluminescence images acquired under low irradiance are comparable to electroluminescence images acquired at 10% of short-circuit current. Photoluminescence imaging has also been conducted successfully from the rear of bifacial modules in these illumination conditions.

Physics constraint Deep Learning based radiative transfer model.

Deep Learning (DL) open sources libraries such as TensorFlow, Keras, and PyTorch have been widely and successfully applied for many applications in a forward model. We have developed the DL radiative transfer model over Oceans under a clear-sky condition. However, the derived physical model from the DL forward model has difficulties in predicting physical properties such as the Jacobian, because multiple solutions can fit the forward model results during the deep learning training process. The Jacobian model in a radiative transfer can calculate radiance sensitivities on geophysical parameters, which are required by satellite radiance assimilation in support of weather forecasts and for retrieving environmental data records. In this study, we introduce a physics constraint into our deep learning training for deriving the forward model that retains right physics. With this physics constraint, the radiance sensitivities are well captured by this new DL radiative transfer.

Thermal and CFD Analyses of Sustainable Heat Storage-Based Passive Greenhouse Dryer Operating in No-Load Condition

This article presents a comprehensive study on thermal and computational fluid dynamics (CFD) analysis of an innovative greenhouse dryer designed for passive operation under a no-load condition. The dryer incorporates hybrid thermal storage at the floor and a reflective mirror with thermocoal as the north wall, transforming a classical even-span greenhouse dryer into an efficient and effective system. The experimentation was conducted under clear sky conditions, with variations in global solar radiation (GSR) ranging from 166.6 to 1209 W/m2, resulting in an average value of 875.9 W/m2. The variations in GSR influenced other ambient parameters, including ambient temperature (28.7 °C to 35.6 °C), ambient relative humidity (33.2% to 45.7%), and ambient wind speed (0.1 to 1.02 m/s). Indoor parameters of the proposed dryer, such as inside temperature (31 °C to 47.35 °C), inside relative humidity (31.1% to 39.1%), ground temperature (44.2 °C to 70.6 °C), and outlet temperature (29 °C to 45.35 °C), were measured hourly. The average values of these parameters were 41.25 °C, 35.31%, 61.65 °C, and 39.25 °C, respectively. Quantitative parameters, including heat loss, overall heat transfer coefficient, coefficient of diffusion, and instantaneous efficiency, were calculated to evaluate the dryer’s performance. The proposed dryer exhibited an improved range of overall heat transfer coefficients (3.87 to 5.03 W/m2 K) compared to the modified greenhouse dryer under passive mode and the conventional greenhouse under passive mode. CFD analysis provided temperature distribution plots showing a progressively increasing range of temperatures near the trays, ranging from 310 K to 335 K, suitable for natural convection drying. The findings highlight the superior performance of the innovative dryer compared to contemporary systems. This research contributes to the advancement of drying technology and holds potential for applications in the agriculture and food processing industries.

How solar panels work, in theory and in practice

We present an analysis of the functionality of an array of monocrystalline silicon solar panels over a 22 month period. For simple geometrical reasons, one expects the solar power produced to be linearly proportional to the cosine of the incidence angle of the Sun’s light on the panels. This can be demonstrated with high accuracy (root-mean-square scatter of less than one percent), but one must first correct the measured solar power for the dimming effect of the Earth’s atmosphere as a function of the atmospheric path length that the Sun’s light traverses. We elaborate a simple and robust method for determining the atmospheric extinction term on days with clear sky conditions. There are two situations under which the extinction-corrected data deviate from the linear relation. One is due to the heating of the panels during daylight hours, resulting in their being less efficient. The other is manifested as an increase of power that occurs when the sky is partially filled with reflective clouds. This is the phenomenon of cloud enhancement.

Evaluation of the hourly ERA5 radiation product and its relationship with aerosols over China

Surface solar radiation (SSR) and its components are important parameters in studies of land, hydrology and the atmosphere. However, the SSR of ECMWF Reanalysis 5 (ERA5) rather than observations is often used in related research fields due to the sparse and uneven spatial distribution of observations. Therefore, understanding the deviation from observations and the attribution is essential for the appropriate use of reanalysis SSR. Based on station observations in China for 2014–2020, this study evaluates the ERA5 SSR products including global radiation (Rs), direct radiation (Rdir) and diffuse radiation (Rdif) under various PM2.5 concentrations to explore the influence of aerosols on ERA5 radiation. Overall, Rs from ERA5 has higher accuracy than Rdir and Rdif. The ERA5 product generally overestimates (underestimates) Rdir (Rdif), and this overestimate (underestimate) increases with the intensification of particle pollution. Under the influence of biomass burning (BB) events, the Rdir (Rdif) of ERA5 exhibits overestimation (underestimation) similar to that under the heaviest particle pollution. In terms of the time series, the deviations of Rdir and Rdif from ERA5 in 1999–2020 still vary with the local aerosol optical depth (AOD). The diurnal variation in Rdir (Rdif) from ERA5 also shows larger deviations under air pollution conditions than under clean conditions, especially at the hours around noon. Furthermore, the misrepresentation of aerosols also causes large deviations in the Rdif/Rdir of ERA5 from observations, especially at stations in eastern China. Similar changes in the deviation of ERA5 radiation from observations with increasing aerosol loading are found under both all sky and clear sky conditions. The high association with aerosol pollution found here indicates that ERA5 SSR products should be used with caution in the presence of atmospheric particle pollution.

Closing the Reactive Carbon Flux Budget: Observations From Dual Mass Spectrometers Over a Coniferous Forest

AbstractWe use observations from dual high‐resolution mass spectrometers to characterize ecosystem‐atmosphere fluxes of reactive carbon across an extensive range of volatile organic compounds (VOCs) and test how well that exchange is represented in current chemical transport models. Measurements combined proton‐transfer reaction mass spectrometry (PTRMS) and iodide chemical ionization mass spectrometry (ICIMS) over a Colorado pine forest; together, these techniques have been shown to capture the majority of ambient VOC abundance and reactivity. Total VOC mass and associated OH reactivity fluxes were dominated by emissions of 2‐methyl‐3‐buten‐2‐ol, monoterpenes, and small oxygenated VOCs, with a small number of compounds detected by PTRMS driving the majority of both net and upward exchanges. Most of these dominant species are explicitly included in chemical models, and we find here that GEOS‐Chem accurately simulates the net and upward VOC mass and OH reactivity fluxes under clear sky conditions. However, large upward terpene fluxes occurred during sustained rainfall, and these are not captured by the model. Far more species contributed to the downward fluxes than are explicitly modeled, leading to a major underestimation of this key sink of atmospheric reactive carbon. This model bias mainly reflects missing and underestimated concentrations of depositing species, though inaccurate deposition velocities also contribute. The deposition underestimate is particularly large for assumed isoprene oxidation products, organic acids, and nitrates—species that are primarily detected by ICIMS. Net ecosystem‐atmosphere fluxes of ozone reactivity were dominated by sesquiterpenes and monoterpenes, highlighting the importance of these species for predicting near‐surface ozone, oxidants, and aerosols.

First Light Demonstration of Red Solar Induced Fluorescence for Harmful Algal Bloom Monitoring

AbstractThe risks harmful algal blooms (HAB) pose to aquatic ecosystems, public health, and coastal economies necessitate supplementation of current observation strategies. Herein, we explore the use of red solar induced fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI), a remote sensing measurement retrievable in variable cloud conditions, for Karenia brevis detection. Along the West Florida Shelf from 2018 to 2020, we compare red SIF with normalized fluorescence line height (nFLH) from MODIS‐Aqua, a standard remote sensing HAB indicator limited to clear sky days. A strong positive linear relationship is found between nFLH and red SIF during severe bloom conditions in 2018 (N = 33,376, r‐value = 0.79, R2 = 0.63) permitting direct comparison. Red SIF provided nearly double the amount of spatiotemporal fluorescence information than nFLH. This work presents the first application of TROPOMI's red SIF for HAB monitoring and illuminates an approach for bolstering early warning systems for HABs beyond clear sky conditions.

Radiative controls by clouds and thermodynamics shape surface temperatures and turbulent fluxes over land

Land surface temperatures (LSTs) are strongly shaped by radiation but are modulated by turbulent fluxes and hydrologic cycling as the presence of water vapor in the atmosphere (clouds) and at the surface (evaporation) affects temperatures across regions. Here, we used a thermodynamic systems framework forced with independent observations to show that the climatological variations in LSTs across dry and humid regions are mainly mediated through radiative effects. We first show that the turbulent fluxes of sensible and latent heat are constrained by thermodynamics and the local radiative conditions. This constraint arises from the ability of radiative heating at the surface to perform work to maintain turbulent fluxes and sustain vertical mixing within the convective boundary layer. This implies that reduced evaporative cooling in dry regions is then compensated for by an increased sensible heat flux and buoyancy, which is consistent with observations. We show that the mean temperature variation across dry and humid regions is mainly controlled by clouds that reduce surface heating by solar radiation. Using satellite observations for cloudy and clear-sky conditions, we show that clouds cool the land surface over humid regions by up to 7 K, while in arid regions, this effect is absent due to the lack of clouds. We conclude that radiation and thermodynamic limits are the primary controls on LSTs and turbulent flux exchange which leads to an emergent simplicity in the observed climatological patterns within the complex climate system.

Thermodynamic structure of the atmospheric boundary layer over a coastal station in India for contrasting sky conditions during different seasons

The thermodynamic structure of the atmospheric boundary layer for contrasting sky conditions over Chennai, a coastal station in the Indian subcontinent, is investigated through conserved variable analysis of equivalent potential temperature and specific humidity. Simultaneous radiosonde and micropulse lidar measurements undertaken in 2018 constitute the primary database in this investigation. One of the most prominent features of this analysis is a consistent occurrence of a double mixed layer structure during the clear-sky and cloudy conditions throughout the year. The occurrence frequency of the double mixing lines is higher during the pre-monsoon season compared with the winter and northeast (NE) monsoon seasons. The advection mainly dominates the formation of double mixing lines during the winter and pre-monsoon seasons. In contrast, convection and advection dominate during the southwest (SW) and NE monsoon seasons. The frequent double mixing lines over Chennai occur mainly from the restratification of the convective boundary layer (CBL) due to the sea-breeze onset and the cloud layer. Occasionally, a triple mixing line structure is also observed during the fair-weather boundary layer (FWBL) of the pre-monsoon and SW monsoon seasons. Among the 355 total observations collected during 2018, the first, second, and third mixing lines occurred 100%, 70%, and 14%, respectively. The thermal internal boundary layer (TIBL), CBL, and FWBL occur ∼50%, ∼97%, and ∼ 30%, respectively. The first mixing line is represented by both the TIBL and CBL, and CBL and FWBL represent the second mixing line, whereas the third mixing line is represented solely by the FWBL. The first and second mixing line shows strong seasonal variations with lower altitudes during the pre-monsoon season and higher altitudes in the SW monsoon season, almost in the same phase as the CBL variation but in the opposite phase of the TIBL variations. The CBL height attains a minimum during the winter season and maximum during the SW monsoon season, while TIBL becomes minimum during the pre-monsoon and SW monsoon seasons and maximum during winter and NE monsoon seasons.

A Simple Low-cost Method for Accurate Canopy Density Evaluation of Citrus

The use of canopy density for crop production is a useful tool for evaluating management practices for informed decision-making and predicting crop yields. Traditional methods for analyzing canopy density include expensive equipment that requires advanced software and costly repairs, such as leaf area index analyzers, or equipment that can only be used during optimal weather conditions, such as light meters, that quantify photosynthetically active radiation (PAR), thus making it difficult for researchers to maximize the time needed for field research evaluations and data collection. Digital image analyses using technologically advanced cameras, such as smartphone cameras, have allowed new ways of collecting data without the need to purchase specialized instruments. Using a combination of smartphone cameras and ImageJ software, canopy density can be measured in any weather conditions for a much lower cost than that of traditional equipment. This low-cost, digital image analysis method was compared with traditional PAR measurements for ‘Valencia’ sweet orange [Citrus sinensis (L.) Osb.] trees with varying levels of canopy density. A strong positive correlation between the digital image analysis method and standard canopy density measurement method using PAR measurements (r = 0.79; P<0.0001) was found, indicating that this method can be used as an alternative to the PAR method. The digital image analysis method was also consistent when used during different weather conditions, whereas the PAR method was highly variable when quantifying the canopy when clouds were present in comparison with clear sky conditions. This novel method provides researchers and growers with an easy, flexible, consistent, and low-cost option for analyzing canopy density.

Variation in albedo and other vegetation characteristics in non-forested northern ecosystems: the role of lichens and mosses

Vegetation has a profound impact on climate through complex interactions and feedback loops, where especially regulation of albedo, the ratio of reflected to incoming solar radiation, is important at high latitudes. How vegetation albedo varies along environmental gradients in tundra ecosystems is still not well understood, particularly for ecosystems dominated by nonvascular vegetation. We studied broadband shortwave albedo of open boreal, arctic, and alpine ecosystems over a 2000 km long latitudinal gradient (60° N–79° N) and contrasted this against species composition, vegetation greenness (normalised difference vegetation index—NDVI), momentary ecosystem CO2 fluxes and reindeer (Rangifer tarandus) grazing pressure. High cover of pale terricolous fruticose lichens was the single most important predictor for vegetation albedo, which had a maximum value of 0.389 under clear sky conditions and solar zenith angle 60°. To our knowledge, this is the highest broadband albedo recorded for a vegetated surface. NDVI was negatively correlated to lichen biomass (rs = −0.56), and albedo (rs = −0.19). Gross primary production and ecosystem respiration varied considerably less between plots and vegetation types than albedo. While it is well-known that Rangifer affects climate-relevant aboveground biomass, we here show that its regulation of surface albedo in northern ecosystems may also be of high importance for land-atmosphere interactions. The data presented here thus advocate for an increased understanding of the important and complex role of herbivores and lichen cover in climate-vegetation interactions.

The Solar Energy Potential of Greece for Flat-Plate Solar Panels Mounted on Double-Axis Systems

The aim of the present work is to investigate the efficiency of flat-plate solar panels in Greece for delivering solar energy. In this study, the solar panels are mounted on a two-axis tracker, which follows the daily path of the sun. In this context, the annual energy sums are estimated on such surfaces from hourly solar horizontal radiation values at forty-three locations, covering all of Greece. The solar horizontal radiation values are embedded in the typical meteorological years of the sites obtained from the PVGIS tool. All calculations use near-real surface-albedo values for the sites, and isotropic and anisotropic models are used to estimate the diffuse-inclined radiation. The analysis provides non-linear regression expressions for the energy sums as a function of time (month, season). The annual energy sums are found to vary between 2247 kWhm−2 and 2878 kWhm−2 under all-sky conditions with the anisotropic transposition model. Finally, maps of Greece showing the distribution of the annual and seasonal solar energy sums under all- and clear-sky conditions are derived for the first time, and these maps constitute the main innovation of this work.