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Solar surface radiation data of high quality is essential for the appropriate monitoring and analysis of the Earth's radiation budget and the climate system. Further, they are crucial for the efficient planning and operation of solar energy systems. However, well maintained surface measurements are rare in many regions of the world and over the oceans. There, satellite derived information is the exclusive observational source. This emphasizes the important role of satellite based surface radiation data. Within this scope, the new satellite based CM-SAF SARAH (Solar surfAce RAdiation Heliosat) data record is discussed as well as the retrieval method used. The SARAH data are retrieved with the sophisticated SPECMAGIC method, which is based on radiative transfer modeling. The resulting climate data of solar surface irradiance, direct irradiance (horizontal and direct normal) and clear sky irradiance are covering 3 decades. The SARAH data set is validated with surface measurements of the Baseline Surface Radiation Network (BSRN) and of the Global Energy and Balance Archive (GEBA). Comparison with BSRN data is performed in order to estimate the accuracy and precision of the monthly and daily means of solar surface irradiance. The SARAH solar surface irradiance shows a bias of 1.3 \\(W/m^2\\) and a mean absolute bias (MAB) of 5.5 \\(W/m^2\\) for monthly means. For direct irradiance the bias and MAB is 1 \\(W/m^2\\) and 8.2 \\(W/m^2\\) respectively. Thus, the uncertainty of the SARAH data is in the range of the uncertainty of ground based measurements. In order to evaluate the uncertainty of SARAH based trend analysis the time series of SARAH monthly means are compared to GEBA. It has been found that SARAH enables the analysis of trends with an uncertainty of 1 \\(W/m^2/dec\\); a remarkable good result for a satellite based climate data record. SARAH has been also compared to its legacy version, the satellite based CM-SAF MVIRI climate data record. Overall, SARAH shows a significant higher accuracy and homogeneity than its legacy version. With its high accuracy and temporal and spatial resolution SARAH is well suited for regional climate monitoring and analysis as well as for solar energy applications.

A brief summary of the various observations and constraints that underlie solar dynamo research are presented. The arguments that indicate that the solar dynamo is an alpha-omega dynamo of the Babcock-Leighton type are then shortly reviewed. The main open questions that remain are concerned with the subsurface dynamics, including why sunspots emerge at preferred latitudes as seen in the familiar butterfly wings, why the cycle is about 11 years long, and why the sunspot groups emerge tilted with respect to the equator (Joy’s law). Next, we turn to magnetic helicity, whose conservation property has been identified with the decline of large-scale magnetic fields found in direct numerical simulations at large magnetic Reynolds numbers. However, magnetic helicity fluxes through the solar surface can alleviate this problem and connect theory with observations, as will be discussed.

Due to the integration of fluctuating weather-dependent energy sources into the grid, the importance of weather and power forecasts grows constantly. This paper describes the implementation of a short-term forecast of solar surface irradiance named SESORA (seamless solar radiation). It is based on the the optical flow of effective cloud albedo and available for Germany and parts of Europe. After the clouds are shifted by applying cloud motion vectors, solar radiation is calculated with SPECMAGIC NOW (Spectrally Resolved Mesoscale Atmospheric Global Irradiance Code), which computes the global irradiation spectrally resolved from satellite imagery. Due to the high spatial and temporal resolution of satellite measurements, solar radiation can be forecasted from 15 min up to 4 h or more with a spatial resolution of 0.05 ∘ . An extensive validation of this short-term forecast is presented in this study containing two different validations based on either area or stations. The results are very promising as the mean RMSE (Root Mean Square Error) of this study equals 59 W/m 2 (absolute bias = 42 W/m 2 ) after 15 min, reaches its maximum of 142 W/m 2 (absolute bias = 97 W/m 2 ) after 165 min, and slowly decreases after that due to the setting of the sun. After a brief description of the method itself and the method of the validation the results will be presented and discussed.

The increasing use of renewable energies as a source of electricity has led to a fundamental transition of the power supply system. The integration of fluctuating weather-dependent energy sources into the grid already has a major impact on its load flows. As a result, the interest in forecasting wind and solar radiation with a sufficient accuracy over short time periods (<4 h) has grown. In this study, the short-term forecast of the effective cloud albedo based on optical flow estimation methods is investigated. The optical flow method utilized here is TV-L1 from the open source library OpenCV. This method uses a multi-scale approach to capture cloud motions on various spatial scales. After the clouds are displaced, the solar surface radiation will be calculated with SPECMAGIC NOW, which computes the global irradiation spectrally resolved from satellite imagery. Due to the high temporal and spatial resolution of satellite measurements, the effective cloud albedo and thus solar radiation can be forecasted from 5 min up to 4 h with a resolution of 0.05°. The validation results of this method are very promising, and the RMSE of the 30-min, 60-min, 90-min and 120-min forecast equals 10.47%, 14.28%, 16.87% and 18.83%, respectively. The paper gives a brief description of the method for the short-term forecast of the effective cloud albedo. Subsequently, evaluation results will be presented and discussed.

Spicules are rapidly evolving fine-scale jets of magnetized plasma in the solar chromosphere. It remains unclear how these prevalent jets originate from the solar surface and what role they play in heating the solar atmosphere. Using the Goode Solar Telescope at the Big Bear Solar Observatory, we observed spicules emerging within minutes of the appearance of opposite-polarity magnetic flux around dominant-polarity magnetic field concentrations. Data from the Solar Dynamics Observatory showed subsequent heating of the adjacent corona. The dynamic interaction of magnetic fields (likely due to magnetic reconnection) in the partially ionized lower solar atmosphere appears to generate these spicules and heat the upper solar atmosphere.

The rooftop solar photovoltaic system is one of the potential methods vastly adopted to harness the abundant solar energy and to overcome land limitation. In our previous study, the rooftop solar energy potential has been investigated with a case study of buildings in the University of Bengkulu using drone technology. The estimation results of the study show that all buildings have the potential to be developed as the installation area of solar panels. Moreover, the optimum solar harvest is affected by the inclination of the rooftop. However, the results obtained were estimated power under ideal conditions. Therefore, in this research, the solar mapping potential results were examined using solar panels and current sensors. In the measurement system, the ability of the system to harvest solar energy was evaluated by placing a solar panel on miniature buildings. The placement of the solar panels was adjusted relative to the inclination and orientation of the building rooftop. This experiment was carried out for 24 h to obtain the optimum value for each tilt of the rooftop and orientation of the solar panel surface. The examination results show that the energy harvesting capacity of each solar panel is strongly influenced by the inclination of the rooftop and the orientation of the solar panel surface towards the sun. Solar panels with a smaller tilt angle are able to produce larger average power. Furthermore, the cloud coverage also affects the performance of solar panels in produce electricity.

Estimates of solar irradiance at the earth’s surface from satellite observations are useful for planning both the deployment of distributed photovoltaic systems and their integration into electricity grids. In order to use surface solar irradiance from satellites for these purposes, validation of its accuracy against ground observations is needed. In this study, satellite estimates of surface solar irradiance from Geostationary Operational Environmental Satellite (GOES) are compared with ground observations at two sites, namely the main campus of the University of Texas at San Antonio (UTSA) and the Alamo Solar Farm of San Antonio (ASF). The comparisons are done mostly on an hourly timescale, under different cloud conditions classified by cloud types and cloud layers, and at different solar zenith angle intervals. It is found that satellite estimates and ground observations of surface solar irradiance are significantly correlated (p < 0.05) under all sky conditions (r: 0.80 and 0.87 on an hourly timescale and 0.94 and 0.91 on a daily timescale, respectively for the UTSA and ASF sites); on the hourly timescale, the correlations are 0.77 and 0.86 under clear-sky conditions, and 0.74 and 0.84 under cloudy conditions, respectively for the UTSA and ASF sites, and mostly >0.60 under different cloud types and layers for both sites. The correlations under cloudy-sky conditions are mostly stronger than those under clear-sky conditions at different solar zenith angles. The correlation coefficients are mostly the smallest with solar zenith angle in the range of 75–90° under all sky, clear-sky and cloudy-sky conditions. At the ASF site, the overall bias of GOES surface solar irradiance is small (+1.77 Wm−2) under all sky while relatively larger under clear-sky (−22.29 Wm−2) and cloudy-sky (+40.31 Wm−2) conditions. The overall good agreement of the satellite estimates with the ground observations underscores the usefulness of the GOES surface solar irradiance estimates for solar energy studies in the San Antonio area.

The fast solar wind that fills the heliosphere originates from deep within regions of open magnetic field on the Sun called ‘coronal holes’. The energy source responsible for accelerating the plasma is widely debated; however, there is evidence that it is ultimately magnetic in nature, with candidate mechanisms including wave heating 1 , 2 and interchange reconnection 3 – 5 . The coronal magnetic field near the solar surface is structured on scales associated with ‘supergranulation’ convection cells, whereby descending flows create intense fields. The energy density in these ‘network’ magnetic field bundles is a candidate energy source for the wind. Here we report measurements of fast solar wind streams from the Parker Solar Probe (PSP) spacecraft 6 that provide strong evidence for the interchange reconnection mechanism. We show that the supergranulation structure at the coronal base remains imprinted in the near-Sun solar wind, resulting in asymmetric patches of magnetic ‘switchbacks’ 7 , 8 and bursty wind streams with power-law-like energetic ion spectra to beyond 100 keV. Computer simulations of interchange reconnection support key features of the observations, including the ion spectra. Important characteristics of interchange reconnection in the low corona are inferred from the data, including that the reconnection is collisionless and that the energy release rate is sufficient to power the fast wind. In this scenario, magnetic reconnection is continuous and the wind is driven by both the resulting plasma pressure and the radial Alfvénic flow bursts. Measurements of fast solar wind streams from the Parker Solar Probe spacecraft provide strong evidence for the interchange reconnection mechanism being responsible for accelerating the fast solar wind.

Solar flares sometimes lead to coronal mass ejections that directly affect Earth's environment. However, a large fraction of flares, including on solar-type stars, are confined flares. What are the differences in physical properties between confined and eruptive flares? For the first time, we quantify the thermodynamic and magnetic properties of hundreds of confined and eruptive flares of GOES class C5.0 and above, 480 flares in total. We first analyze large flares of GOES class M1.0 and above observed by the Solar Dynamics Observatory, 216 flares in total, including 103 eruptive and 113 confined flares, from 2010 until 2016 April; we then look at the entire data set of 480 flares above class C5.0. We compare GOES X-ray thermodynamic flare properties, including peak temperature and emission measure, and active-region (AR) and flare-ribbon magnetic field properties, including reconnected magnetic flux and peak reconnection rate. We find that for fixed peak X-ray flux, confined and eruptive flares have similar reconnection fluxes; however, for fixed peak X-ray flux confined flares have on average larger peak magnetic reconnection rates, are more compact, and occur in larger ARs than eruptive flares. These findings suggest that confined flares are caused by reconnection between more compact, stronger, lower-lying magnetic fields in larger ARs that reorganizes a smaller fraction of these regions’ fields. This reconnection proceeds at faster rates and ends earlier, potentially leading to more efficient flare particle acceleration in confined flares.

Using time–distance local helioseismology flow maps within 1 Mm of the solar photosphere, we detect inflows toward activity belts that contribute to solar-cycle scale variations in the near-surface meridional flow. These inflows stretch out as far as 30° away from the active region centroids. If active region neighborhoods are excluded, the solar-cycle-scale variation in the background meridional flow diminishes to below 2 m s−1, but still shows systematic variations in the absence of active regions between sunspot cycles 24 and 25. We therefore propose that the near-surface meridional flow is a three-component flow made up of a constant baseline flow profile that can be derived from quiet-Sun regions, variations due to inflows around active regions, and solar-cycle-scale variation of about 2 m s−1. Torsional oscillation, on the other hand, is found to be a global phenomenon, i.e., exclusion of active region neighborhoods does not significantly affect its magnitude or phase. This nonvariation in torsional oscillation with distance away from active regions and the three-component breakdown of the near-surface meridional flow serve as vital constraints for solar dynamo models and surface flux-transport simulations.