Solar Irradiance Variations Research Articles

PAStar : A model for stellar surface from the Sun to active stars

The characterisation of exoplanets requires a good description of the host star. Stellar activity acts as a source of noise, which can alter planet radii as derived from the transit depth or atmospheric characterisation. Here, we propose PAStar a model to describe photospheric activity in the form of spots and faculae, which could be applied to a wide range of stellar observations, from photometric to spectroscopic time series, making it possible to correctly extract planetary and stellar properties. The adopted stellar atmosphere is a combination of three components: the quiet photosphere, spots, and faculae. The model takes into account the effects of star inclination and Doppler shifts due to stellar rotation and limb darkening, which is independent for each component. Several synthetic products have been presented to show the capabilities of the model. The model is able to retrieve the input surface-inhomogeneity configuration through photometric or spectroscopic observations. The model has been validated against optical solar data and compared to alternative stellar surface activity models; for example SOAP code . The Sun is a unique laboratory to test stellar models because of the possibility to unambiguously relate flux variations to surface inhomogeneities' configuration. This validation has been done by analysing a photometric time series from the Variability of Solar Irradiance and Gravity Oscillations (VIRGO) photometer on-board Solar and Heliospheric Observatory (SOHO) mission. Results have been compared to real solar images from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) to confirm the goodness of the results in terms of surface inhomogeneities' positions and dimensions. The description of stellar activity is a fundamental step in several astrophysical contexts and it is covered by the method we present. Our model offers a flexible and valuable tool to describe the activity of stars when it is dominated by spots and faculae.

Solar parking lot capacity: an abundant dual-use alternative to meet demand for the renewable energy transition

Abstract Most utility-scale solar facilities (USSFs) in the United States (US) are planned or installed in grasslands, pastures, agriculture land, and timberland, with aggressive future expansion plans. Investor-owned electricity providers have lobbied aggressively to remove obstacles to approval of USSFs on agricultural lands and for limits on regulations that support distributed solar installation. Rural USSF expansion may have potentially significant local, state, and regional impacts on agricultural production and the economy, property values and affordability, and conservation of habitats, connectivity, and endangered species. The potential use of parking lots in urban and suburban areas for solar development to meet demands is poorly studied and parking lot solar has not gained much traction in the US. The objective of this research was to estimate whether solar PV systems installed in parking lots can meet electricity demands across multiple urban and suburban metropolitan areas within the US. Parking lot data across four municipalities with variation in latitude, solar radiation, and population density was obtained, along with modeled annual electricity demand by sector. Parking lot area and potential generating capacity was calculated for canopy and carport designs using standard and premium efficiency panels, and annual electricity production was estimated using the National Renewable Energy Laboratory’s PVWatts Calculator. Premium efficiency canopy designs can meet ~100% of demand in some large car dependent low to medium density municipalities. High density urban areas may receive marginal direct benefit from parking lot solar development within their boundaries. Dual-use of lands without any ecosystem or productive value can substantially contribute to renewable energy mixes to meet demands.

The capability of 20th‐century reanalyses to reproduce the spatiotemporal variation in surface incident solar radiation over Japan for 1931–2010

AbstractUnderstanding the spatiotemporal variations in surface incident solar radiation (Rs), especially over longer time spans, is crucial for climate modeling and environmental assessment. This study, referring to the century‐long homogenized Rs measurements, comprehensively quantifies the ability of five 20th‐century reanalyses phenomena to estimate Rs over Japan for 1931–2010, and furthermore assesses the contributions of total cloud cover and vapor pressure to the biases in Rs trends. Dominant features revealed that Rs signals boost from the north to the south, which could be captured but is overestimated by all reanalyses. The dominant time evolution of Rs was well captured by CERA20C, followed by ERA20C and 20CRv3, corresponding to their relatively better performance cloud cover. Unfortunately, ERA20CM totally fails to reproduce the spatiotemporal variation in Rs as its procedure does not include an assimilation step. 20CRv2c fails in estimating Rs for 1931–1960, but improves much for 1961–2010 as the quality of assimilated observational variables becomes better. A dimming of −2.76 W·m−2·decade−1 for 1931–1960 was detected in the observed Rs, which could be reproduced by CERA20C and ERA20C. Afterwards, a brightening of 0.88 W·m−2·decade−1 for 1961–2010 was shown in observations, and all reanalyses fail. The trend bias of Rs in CERA20C attributes more to total cloud cover before 1960, and to aerosols or other factors after 1960. Cloud cover contributed more than vapor pressure to the trend bias of Rs for 1931–1960; vapor pressure became more important in regulating Rs for 1961–2010 than for 1931–1960. The combined effects of both factors on Rs are insignificant for 20CRv3 during the entire period, for 20CRv2c for 1931–1960 and for CERA20C for 1961–2010, suggesting other factors, such as aerosols, cloud types, cloud optical depth and their interactions may impact Rs simulations more and this calls for further investigation.

Modelling Analysis and Characteristics of Multi-Level Inverter for Integrating Solar PV System to Grid

This paper investigates the implementation of a cascaded H-bridge multi-level inverter in a single-phase grid-connected solar photovoltaic (PV) system to address harmonic distortion challenges in DC-to-AC power conversion. The primary objective is to enhance power quality and system efficiency by leveraging the inverter's ability to reduce harmonics through power sharing and a lower switching frequency. A Simulink model is developed to evaluate the proposed system's performance, incorporating a unipolar Pulse Width Modulation (PWM) control strategy and an LCL filter for effective harmonic mitigation. The system employs Maximum Power Point Tracking (MPPT) based on the Perturb and Observe (P&O) algorithm, combined with Synchronous Reference Frame Theory-Phase Disposition PWM (SRFT-PDPWM) for optimal control. The proposed inverter ensures precise synchronization between the grid and inverter frequencies, achieving a Total Harmonic Distortion (THD) below 5%. Simulation results demonstrate the system's robust responsiveness to variations in solar irradiance, with increased irradiance leading to further reductions in THD and improved power quality. These findings validate the proposed inverter's capability to deliver high-quality, efficient power under varying environmental conditions, aligning with global objectives for integrating clean and sustainable energy into utility networks.

Enhancing solar efficiency in steppe regions: a comprehensive performance evaluation of photovoltaic systems in M’sila, Algeria

This study assesses a 10 kW grid-connected solar PV system in Algeria's harsh steppe climate in M'Sila, characterised by intense solar radiation and considerable temperature variations. High temperatures reduce photovoltaic conversion efficiency and increase thermal stresses, prompting a detailed investigation into PV systems' challenges in such environments. The research reveals that M'Sila's system generates 7,794.8 kWh annually, with an efficiency range of 16%–19.2%, peaking slightly. Unique thermal management techniques are necessary to sustain efficiency, as extreme heat causes efficiency losses of up to 20%. The levelized cost of energy (LCOE) of $0.0138 per kWh makes the system economically viable in these conditions. The investment proves worthwhile, yielding annual savings of $304. The M'Sila solar system also reduces CO₂ emissions by 4.07 tonnes per year. Algeria’s shift toward renewable energy and carbon reduction gains an additional $59.11 annually in “carbon credit” from these emissions reductions. This research supports Algeria’s renewable energy goals by guiding energy companies and decision-makers to improve efficiency and minimise environmental impact in steppe regions like M'Sila.

A Data Storage, Analysis, and Project Administration Engine (TMFdw) for Small- to Medium-Size Interdisciplinary Ecological Research Programs with Full Raster Data Capabilities

Over almost 20 years, a data storage, analysis, and project administration engine (TMFdw) has been continuously developed in a series of several consecutive interdisciplinary research projects on functional biodiversity of the southern Andes of Ecuador. Starting as a “working database”, the system now includes program management modules and literature databases, which are all accessible via a web interface. Originally designed to manage data in the ecological Research Unit 816 (SE Ecuador), the open software is now being used in several other environmental research programs, demonstrating its broad applicability. While the system was mainly developed for abiotic and biotic tabular data in the beginning, the new research program demands full capabilities to work with area-wide and high-resolution big models and remote sensing raster data. Thus, a raster engine was recently implemented based on the Geo Engine technology. The great variety of pre-implemented desktop GIS-like analysis options for raster point and vector data is an important incentive for researchers to use the system. A second incentive is to implement use cases prioritized by the researchers. As an example, we present machine learning models to generate high-resolution (30 m) microclimate raster layers for the study area in different temporal aggregation levels for the most important variables of air temperature, humidity, precipitation, and solar radiation. The models implemented as use cases outperform similar models developed in other research programs.

Development of a novel multifunctional superconducting device for performance enhancement of DC microgrids

DC microgrids have become an important infrastructure for increasing the integration of renewable energy sources in power grids. However, these DC microgrids suffer from inherent fluctuations from renewable energy sources as well as high fault currents during grid disturbances. Addressing these challenges simultaneously with a single device is a significant technical issue. This paper proposes a novel Multifunctional Superconducting Device (MSCD) with dual functionality to overcome these challenges. The MSCD can operate as a Superconducting Magnetic Energy Storage (SMES) system during normal operation, providing mitigation of renewable energy fluctuations through its shunt connection. During grid faults, the MSCD transits to operate as a Superconducting Fault Current Limiter (SFCL) in series with the grid, limiting the fault current. The proposed MSCD has only an additional controlled switch to the conventional power electronic converter of SMES. The dual functionality of the proposed MSCD has been evaluated using the PSCAD/EMTCD computer package under various operating conditions, validating its ability to seamlessly transition between SMES and SFCL modes. The proposed MSCD could effectively smooth DC bus voltage fluctuations caused by variations in wind speed and solar radiation and could significantly limit the fault current contribution from the DC microgrid under fault conditions. Furthermore, a superconducting coil with a pancake structure has been built and integrated with a control circuit to experimentally validate the functionality of the MSCD. Two experimental case studies were conducted - the first testing the charging and discharging behavior, and the second evaluating the current limiting capability of the MSCD prototype.

Intelligent fuzzy-PSO based grid connected solar EV charging station for electric buses to enhance stability and energy management

Abstract Modern power networks are relying more and more on Distributed Generation (DG) and solar energy-powered Electric Bus (EB) charging stations; nevertheless, controlling the charging process under situations of peak EB load and variable solar irradiation presents considerable hurdles. This study presents a coordinated control approach that maximizes energy distribution for solar (PV)-based EB charging stations by using an intelligent energy management system (IEMS). Through the analysis of load demand and meteorological data in real time, the IEMS optimizes PV generation and grid power consumption, thereby halving peak power demand, minimizing system losses, and easing distribution grid stress. In order to enable dynamic modifications to the energy flow between PV power, the grid, and battery storage, the method integrates an adaptive neuro-based fuzzy control system that anticipates solar energy generation and predicts EB load demands. Furthermore, to balance power distribution between battery and ultracapacitor systems and control energy storage in ultracapacitors, a fuzzy inference system optimized using Particle Swarm Optimization (PSO) is utilized. This prolongs battery life and guarantees effective energy management. The overall performance of the IEMS is improved by the fuzzy logic controller, which produces output signals that specify the best power distribution for any energy storage system. Digital simulations and a real-time hardware-in-loop experimental setup are used to validate the effectiveness of the proposed system, which shows notable gains in energy management, grid stability, and system efficiency. In order to improve intelligent energy management in grid-connected solar-powered systems, this study offers a viable method for incorporating renewable energy sources into EB charging stations.

A Novel EPSO Algorithm Based on Shifted Sigmoid Function Parameters for Maximizing the Energy Yield from Photovoltaic Arrays: An Experimental Investigation

This paper presents a new method for maximizing the energy production of photovoltaic (PV) arrays, utilizing the Enhanced Particle Swarm Optimization (EPSO) algorithm. In contrast with the classical PSO, the proposed EPSO algorithm employs shifted sigmoid functions in order to adapt the acceleration coefficients and the inertia weight instead of using constant coefficients. The EPSO algorithm proves its effectiveness even in challenging either condition, such as abrupt variations in solar irradiance or instances of partial shading conditions (PSCs). The proposed EPSO-based Maximum Power Point Tracking (MPPT) controller has undergone testing and a comparative analysis alongside well-known metaheuristic algorithms, which include the PSO, Bat Algorithm (BAT), Grasshopper Optimization Algorithm (GOA), and Grey Wolf Optimizer (GWO). The results obtained through simulations consistently demonstrate that the EPSO-based MPPT method surpasses other metaheuristic approaches in terms of energy yield and the speed at which it tracks the Maximum Power Point (MPP) under PSCs. In addition, the proposed EPSO algorithm demonstrates robustness, maintaining consistent tracking of the MPP during sudden solar radiation changes. Experimental validation on a real PV system affirms these findings, demonstrating that the EPSO algorithm surpasses its counterparts by achieving a high MPPT efficiency of approximately 99.19% in a fast-tracking time of 2.4 s while maintaining minimal power oscillations of around 2.04 %.

Specialization of a new flux-based approach to thermal problems. Numerical study of glass façades of buildings with cast shadows

Uneven temperature distributions in the glass panes of building façades can induce thermal stresses exceeding material strength, a critical condition usually referred to as “thermal shock”. Here, we specialize in architectural glazing a recently-proposed flux-based variational approach to thermal problems, by considering heat exchanges resulting from climatic actions, in particular the variability of environmental temperatures and solar radiation, influenced by the shielding of cast shadows. The finite element implementation is facilitated because the unknown field is the heat displacement, whose time derivative is the heat flux, which is much smoother than the temperature field, on which the classical approach via Fourier’s law is based. A custom in-house-made FEM code is used to determine the effect of size and shape of cast shadows on temperature distribution in monolithic and laminated glass panes, also coupled in insulating glass units. We find that the temperature difference between irradiated and shadowed regions is only mildly influenced by the shape and size of the shadows, but the glass thickness determines the width of the transition zone and, hence, the temperature gradient. Practical rules for the design of glass façades are tentatively proposed.

Clearness index cluster analysis for photovoltaic weather classification based on solar irradiation measurement data: Theory and application

With the rapid expansion of photovoltaic (PV) power generation, accurately predicting and evaluating PV power output remains a critical challenge due to the inherent variability of solar irradiation. This paper proposes a novel weather classification approach based on the clearness index (CI), derived from solar irradiation data collected in Zhangbei, China, a region abundant in solar resources. Three clustering methods, which are Gaussian Mixture Model, K-Means, and Fuzzy C-Means (FCM), were applied to classify weather into three types: sunny, semi-cloudy, and cloudy. Our findings indicate that FCM consistently outperformed the other methods, particularly under variable conditions. By employing the classified data, short-term PV power forecasting is significantly enhanced. A hybrid CNN-LSTM model trained on the weather-clustered data achieved superior prediction accuracy compared to models trained without weather classification. Integrating weather classification into PV power prediction can notably reduce prediction errors and improve grid management. The proposed approach is recommended for future evaluations of solar applications in Zhangbei and other regions with similar climatic characteristics.

Techno-economic analysis and experimental validation of solar-assisted low-temperature water electrolysis for green hydrogen production: Insights from Afyonkarahisar

This study explores green hydrogen production via low-temperature water electrolysis powered by regional solar energy. A comprehensive techno-economic analysis was conducted to evaluate hydrogen production flow rate and unit costs using computational models developed in the Engineering Equation Solver (EES) and Aspen Plus software. Experimental setups at Afyon Kocatepe University’s energy laboratories were designed to validate these models, showing close alignment between computational and experimental results. Key findings demonstrate the feasibility of solar-assisted hydrogen production, with energy requirements reduced to 52.12 kWh/kg H2 by preheating water to 360 K. The small-scale prototype achieved a maximum hydrogen production rate of 1.829 × 10−6 kg/s, with energy and exergy efficiencies of 64.0 % and 62.46 %, respectively. The calculated levelized cost of hydrogen (LCOH) was 5.84 $/kg H2, with a payback period of 6.9 years, indicating long-term economic viability. This research also introduced novel electrode configurations and fluid variations, optimizing system efficiency under an average solar irradiance of 600 W/m2. This study supports the technical and economic feasibility of solar-driven hydrogen production in the Afyon region by assessing energy, exergy, and techno-economic parameters. It underscores its potential to reduce energy costs and contribute to Turkey’s energy security. The study highlights limitations, including the challenges of scaling up and solar irradiance variability, and suggests avenues for future research to optimize further and expand this technology.

Northern hemisphere mid-latitudes as a key region for reconciling the Holocene temperature conundrum

The classical Holocene temperature reconstruction indicates a cooling trend following the mid-Holocene thermal maximum. However, significant discrepancies exist between the temperature changes predicted by climate models and those derived from proxy data. Proxy sites are predominantly concentrated in the Northern Hemisphere mid-latitudes, where temperature variations align closely with global climate trends. Notably, in the Northern Hemisphere mid-latitudes, the differences between climate model simulations and proxy data are most pronounced. As such, the Northern Hemisphere mid-latitudes represent a crucial region for reconciling Holocene climate dynamics and addressing the Holocene temperature conundrum. Through an analysis of the latitudinal variation in solar radiation and its impact on temperature, this study underscores the pivotal role of this region in temperature reconstructions, particularly in resolving the ongoing discrepancies in Holocene temperature trends.

Advanced Control Scheme Optimization for Stand-Alone Photovoltaic Water Pumping Systems

This study introduces a novel method for controlling an autonomous photovoltaic pumping system by integrating a Maximum Power Point Tracking (MPPT) control scheme with variable structure Sliding Mode Control (SMC) alongside Perturb and Observe (P&O) algorithms. The stability of the proposed SMC method is rigorously analyzed using Lyapunov’s theory. Through simulation-based comparisons, the efficacy of the SMC controller is demonstrated against traditional P&O methods. Additionally, the SMC-based system is experimentally implemented in real time using dSPACE DSP1104, showcasing its robustness in the presence of internal and external disturbances. Robustness tests reveal that the SMC controller effectively tracks Maximum Power Points (MMPs) despite significant variations in load and solar irradiation, maintaining optimal performance even under challenging conditions. The results indicate that the SMC system can achieve up to a 70% increase in water flow rates compared with systems without MPPT controllers. Furthermore, SMC demonstrated high sensitivity to sudden changes in environmental conditions, ensuring efficient power extraction from the photovoltaic panels. This study highlights the advantages of integrating SMC into Photovoltaic Water Pumping Systems (PV-WPSs), providing enhanced control capabilities and optimizing system performance. The findings contribute to the development of sustainable water supply solutions, particularly in remote areas with limited access to the electrical grid.

Effect of overheating on the efficiency of solar panels - study of temperature above 480C

The impact of heat exposure on solar panels can be very significant, not only in terms of energy losses but also in terms of the reliability of systems in the short and long term. The main PV performance parameter can be reduced; how low the power output is due to heat-induced efficiency degradation depends on the specific microclimate as well as the temperature response of the individual unit. In this paper, experiments are conducted in the laboratory of Adrar University on a monocrystalline panel with a power of 200 watts. Exposed to variable solar radiation at different times of the day. The voltage and current are measured through all stages of experimentation according to regular standards. The results show that the efficiency of the panel decreases between 4% to 10% when the amount of solar radiation increases from 572 W/m2 to 780W/m2. This corresponds to a rise in temperature between 35C0 and 49C0. These results give researchers a general picture of the changes that occur in the solar panel when it is in similar conditions.

Design and PIL Implementation of Fuzzy Logic-based MPPT Control for Symmetrical Multilevel Boost Converter

This paper aims to introduce a fuzzy logic adaptive MPPT controller to control a symmetrical multilevel converter in a standalone PV system. The system is evaluated under fixed and variable solar radiation with 15 V as the input voltage 60 V as the required output voltage and 50 kHz as the switching frequency. Results prove that by using the controller, the system successfully tracks the MPPT point for constant and variable radiation without oscillation around the maximum power point. In addition, the overshoot and time response is reduced while the voltage ripples are eliminated. The proposed controller is verified through practical implementation in Arduino mega board to test the accuracy of results. The practical finding via a processor in the loop test validates the simulation results.

Nonlinear Control of Photovoltaic (PV) Solar-Powered Centrifugal Pump for Irrigation System: A Case Study of Fadak Farm in Karbala

Abstract In both the agricultural and industrial sectors, pumping water is essential. Due to its arid climate, our Saharan area has a substantial solar energy resource, making constructing a PV solar irrigation system possible. Given solar resources' unpredictable and intermittent nature, it is imperative to set up a system that permits optimal usage. This study aims to design and simulate a solar pumping system's effective nonlinear direct torque command. A solar generator provides an asynchronous three-phase machine coupled to a centrifugal pump as part of the system. MPPT monitors the boost converter via duty cycle. The solar generator's functioning at full power will be ensured. The first uses PSO in the MPPT system to supply the motor pump with three phases of power. The second one employs direct torque command (DTC) to regulate the operation of a centrifugal pump coupled with an induction machine. More advancements will be made to the DTC scenario. The proposed mathematical model of the solar irrigation system was simulated using a MATLAB simulation environment, adopting accurate data provided by Fadak Farm. The maximum power extracted from PV tends to peak at 280 Wp with the assistance of particle swarm optimization that energizes the use of the centrifugal pump for the proposed irrigation system. It is evident from numerical simulation results based on accurate input data that the power extracted from PV solar is positively affected by solar radiation and surface temperature variations. It is clear from simulation results that the speed of three–phase I.M motor converges to 22.5 rad/sec, and water flow pumping by centrifugal is decreased and increased, converging to 7.5 *10-8 m/s with the variation of solar irradiance.

Reconstruction of the Total Solar Irradiance During the Last Millennium

Solar irradiance variations across various timescales, from minutes to centuries, represent a potential natural driver of past regional and global climate cold phases. To accurately assess the Sun’s effect on climate, particularly during periods of exceptionally low solar activity, known as grand minima, an accurate reconstruction of solar forcing is essential. While direct measurements of the total solar irradiance (TSI) only began in the late 1970s, with the advent of space radiometers, indirect evidence from various historical proxies suggests that the Sun’s magnetic activity has undergone possible significant fluctuations over much longer timescales. Employing diverse and independent methods for TSI reconstruction is essential to gaining a comprehensive understanding of this issue. This study employs a semi-empirical model to reconstruct TSI over the past millennium. Our approach uses an estimated open solar magnetic field (F o ), derived from cosmogenic isotope data, as a proxy for solar activity. We reconstruct the cyclic variations of TSI, due to the solar surface magnetic features, by correlating F o with the parameter of active region functional form. We obtain the long-term TSI trend by applying the empirical mode decomposition algorithm to the reconstructed F o to filter out the 11 yr and 22 yr solar variability. We prepare a reconstructed TSI record, spanning 971 to 2020 CE. The estimated departure from modern TSI values occurred during the Spörer minimum (around 1400 CE), with a decrease of approximately 2.3 Wm−2. A slightly smaller decline of 2.2 Wm−2 is reported during the Maunder minimum, between 1645 and 1715 CE.

Smartphone Light Sensors as an Innovative Tool for Solar Irradiance Measurements.

In recent years, the teaching of experimental science and engineering has been revolutionized by the integration of smartphone sensors, which are widely used by a large portion of the population. Concurrently, interest in solar energy has surged. This raises the important question of how smartphone sensors can be harnessed to incorporate solar energy studies into undergraduate education. We provide comprehensive guidelines for using smartphone sensors in various conditions, along with detailed instructions on how to calibrate them with widely accessible clear-sky satellite data. This smartphone-based method is also compared with professional reference measurements to ensure consistency. This experiment can be easily conducted with most smartphones, basic materials, and a clear, open location over a few hours (methods). The findings demonstrate that smartphones, combined with simple resources, can accurately measure solar irradiance and support experiments on solar radiation physics, atmospheric interactions, and variations in solar energy across locations, cloud cover, and time scales. This approach provides a practical and accessible tool for studying solar energy, offering an innovative and engaging method for measuring solar resources.

Correlation analysis of the long-term interplay of cosmic rays, solar activity, and solar irradiance

Abstract This study presents a comprehensive analysis of the interplay between solar irradiance variability, solar activity, and cosmic rays over an extensive period from 1950 to 2023, well beyond the scope of previous research that focused on fewer solar cycles. Besides, using a robust dataset, we investigated the correlation between solar activity, represented by sunspot numbers, and the total solar irradiance, alongside the influence of cosmic rays. In this respect, our methodology incorporated sophisticated statistical techniques, including correlation analysis and linear regression, in order to elucidate the complex relationships among these variables. We identified a strong positive correlation between solar activity and total solar irradiance r ≈ + 0.95 , together with a significant anti-correlation between solar activity and cosmic rays r ≈ − 0.72 as well as cosmic rays and total solar irradiance r ≈ − 0.67 . As a consequence, the results of this study offer new insights into the long-term solar influence on climate through cosmic rays, enhancing our understanding of the Sun-Earth dynamic over prolonged periods. Likewise, the extended time series and the analytical framework developed in this study pave the way for further research into related phenomena, including the effects of cloud cover and potential links between cosmic rays and climate change.