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"SOLAR RADIATION"
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CODE’s new solar radiation pressure model for GNSS orbit determination
The Empirical CODE Orbit Model (ECOM) of the Center for Orbit Determination in Europe (CODE), which was developed in the early 1990s, is widely used in the International GNSS Service (IGS) community. For a rather long time, spurious spectral lines are known to exist in geophysical parameters, in particular in the Earth Rotation Parameters (ERPs) and in the estimated geocenter coordinates, which could recently be attributed to the ECOM. These effects grew creepingly with the increasing influence of the GLONASS system in recent years in the CODE analysis, which is based on a rigorous combination of GPS and GLONASS since May 2003. In a first step we show that the problems associated with the ECOM are to the largest extent caused by the GLONASS, which was reaching full deployment by the end of 2011. GPS-only, GLONASS-only, and combined GPS/GLONASS solutions using the observations in the years 2009–2011 of a global network of 92 combined GPS/GLONASS receivers were analyzed for this purpose. In a second step we review direct solar radiation pressure (SRP) models for GNSS satellites. We demonstrate that only even-order short-period harmonic perturbations acting along the direction Sun-satellite occur for GPS and GLONASS satellites, and only odd-order perturbations acting along the direction perpendicular to both, the vector Sun-satellite and the spacecraft’s solar panel axis. Based on this insight we assess in the third step the performance of four candidate orbit models for the future ECOM. The geocenter coordinates, the ERP differences w. r. t. the IERS 08 C04 series of ERPs, the misclosures for the midnight epochs of the daily orbital arcs, and scale parameters of Helmert transformations for station coordinates serve as quality criteria. The old and updated ECOM are validated in addition with satellite laser ranging (SLR) observations and by comparing the orbits to those of the IGS and other analysis centers. Based on all tests, we present a new extended ECOM which substantially reduces the spurious signals in the geocenter coordinate
z
(by about a factor of 2–6), reduces the orbit misclosures at the day boundaries by about 10 %, slightly improves the consistency of the estimated ERPs with those of the IERS 08 C04 Earth rotation series, and substantially reduces the systematics in the SLR validation of the GNSS orbits.
Journal Article
Sun, wind, and light: architectural design strategies
\"This fully updated Third Edition covers principles of designing buildings that use the sun for heating, wind for cooling, and daylight for natural lighting. Using hundreds of illustrations and companion CD-ROM, this book offers practical strategies that give the designer the tools they need to make energy efficient buildings\"-- Provided by publisher.
Book
Assessment of solar energy potential for Bahir Dar city, Ethiopia
The world’s energy consumption is being replaced by renewable energies in large part because of the depletion of fossil fuels and the acceleration of environmental change. This study reports the amount of inward solar radiation in the date range from January 2018 to December 2022 in the Gregorian Calendar for certain areas in Bahir Dar, Ethiopia: 37°E and 11.6°N. On the horizontal surface of the case area, the month with the highest global radiation (monthly average daily) is March, at approximately 42.56 MJ/m
2
. day; June has the lowest diffuse radiation, at 16.2 MJ/m
2
.day. Furthermore, April had the most global radiation (monthly average hourly) on the horizontal surface, measuring 9.09 MJ/m2.hour, while June had the lowest diffuse radiation, measuring 2.3 MJ/m2.hour. In addition, this study predicts the beam, diffuse, and total radiation on the tilted collector using the total available horizontal radiation on a monthly and hourly basis. According to the research, the output of the radiation on the tilted surface towards the equator in the northern hemisphere, azimuth angle, γ = 0°, shows that the highest possible total radiation (monthly average daily) is 48.3 MJ/m
2
. day (January) and the highest possible total radiation (monthly average hourly) in February, 9.14 MJ/m
2
.hour at 1:00 p.m.
Journal Article
Toward the 1-cm Galileo orbits: challenges in modeling of perturbing forces
Precise orbit determination demands knowledge of perturbing forces acting on the satellites of the Global Navigation Satellite Systems (GNSS). The metadata published by the European GNSS Agency for the Galileo satellites allow for the composition of the analytical box-wing model dedicated for coping with the direct solar radiation pressure (SRP), albedo, and infrared radiation (IR). Based on the box-wing model, we evaluated both the magnitude and the characteristic periods of accelerations caused by all the aforementioned forces. We assess which perturbations can be absorbed by the extended Empirical CODE Orbit Model (ECOM2) and what are the consequences of neglecting higher-order ECOM2 coefficients. In order to evaluate the impact of SRP, albedo, IR, and the navigation antenna thrust, we perform a series of precise Galileo orbit determination strategies for Galileo In-Orbit-Validation (IOV), Full Operational Capability (FOC), and two FOC satellites launched into eccentric orbits. The proposed box-wing model is capable of absorbing approximately 97% of the SRP in the Sun-satellite direction, whereas the rest can be mitigated by an additionally estimated small set of empirical parameters. The purely physical box-wing model does not fully handle satellite misorientation and re-radiation effects, such as
Y
-bias, solar panel rotation lag, that is the misalignment causing a constant acceleration perpendicular to the solar panel axis and the direction to the Sun. However, the box-wing model is especially crucial in terms of the absorption of the higher-order terms of SRP and stabilizes the orbit solutions during the eclipsing periods. Based on the SLR residual analysis, we found a systematic effect at the level up to 50 mm resulting from the omission of the high-order empirical orbit coefficients. We also found that the impact of the albedo, IR, and transmitter antenna thrust on the Galileo orbits reach the level of 5, 14, and 20 mm, respectively. Eventually, we obtain the overall accuracy of the Galileo-FOC orbits at the level of 22.5 mm, even for the eclipsing period for the solution which considers the box-wing model with the estimation of the constant empirical accelerations.
Journal Article
Engineering the climate
Engineering the Climate: The Ethics of Solar Radiation Management discusses the ethical issues associated with deliberately engineering a cooler climate to combat global warming. Climate engineering (also known as geoengineering) has recently experienced a surge of interest given the growing likelihood that the global community will fail to limit the temperature increases associated with greenhouse gases to safe levels. Deliberate manipulation of solar radiation to combat climate change is an exciting and hopeful technical prospect, promising great benefits to those who are in line to suffer most through climate change. At the same time, the prospect of geoengineering creates huge controversy. Taking intentional control of earth’s climate would be an unprecedented step in environmental management, raising a number of difficult ethical questions. One particular form of geoengineering, solar radiation management (SRM), is known to be relatively cheap and capable of bringing down global temperatures very rapidly. However, the complexity of the climate system creates considerable uncertainty about the precise nature of SRM’s effects in different regions. The ethical issues raised by the prospect of SRM are both complex and thorny. They include: 1) the uncertainty of SRM’s effects on precipitation patterns, 2) the challenge of proper global participation in decision-making, 3) the legitimacy of intentionally manipulating the global climate system in the first place, 4) the potential to sidestep the issue of dealing with greenhouse gas emissions, and, 5) the lasting effects on future generations. It has been widely acknowledged that a sustained and scholarly treatment of the ethics of SRM is necessary before it will be possible to make fair and just decisions about whether (or how) to proceed. This book, including essays by 13 experts in the field of ethics of geoengineering, is intended to go some distance towards providing that treatment.
eBook
Solar-Cycle Variability Results from the Solar Radiation and Climate Experiment (SORCE) Mission
The
Solar Radiation and Climate Experiment
(SORCE) was a NASA mission that operated from 2003 to 2020 to provide key climate-monitoring measurements of total solar irradiance (TSI) and solar spectral irradiance (SSI). This 17-year mission made TSI and SSI observations during the declining phase of Solar Cycle 23, during all of Solar Cycle 24, and at the very beginning of Solar Cycle 25. The SORCE solar-variability results include comparisons of the solar irradiance observed during Solar Cycles 23 and 24 and the solar-cycle minima levels in 2008 – 2009 and 2019 – 2020. The differences between these two minima are very small and are not significantly above the estimate of instrument stability over the 11-year period. There are differences in the SSI variability for Solar Cycles 23 and 24, notably for wavelengths longer than 250 nm. Consistency comparisons with SORCE variability on solar-rotation timescales and solar-irradiance model predictions suggest that the SORCE Solar Cycle 24 SSI results might be more accurate than the SORCE Solar Cycle 23 results. The SORCE solar-variability results have been useful for many Sun–climate studies and will continue to serve as a reference for comparisons with future missions studying solar variability.
Journal Article
Clustered ANFIS network using fuzzy c-means, subtractive clustering, and grid partitioning for hourly solar radiation forecasting
In this paper, an improved clustered adaptive neuro-fuzzy inference system (ANFIS) to forecast an hour-ahead solar radiation data for 915 h is introduced. First, we have classified the history data of solar radiation time series to decrease the input sample size using clustering methods. Three methods are used, namely, fuzzy c-means (FCM), subtractive clustering, and grid partitioning. These methods allow classifying the input data into groups; each group has similar properties that help to understand the correlation between the data and by consequence simplify the forecasting process. Second, we designed an ANFIS structure that takes both advantages of fuzzy theory to describe the uncertain phenomena of the data and artificial neural network algorithm, which has a self-learning ability. Finally, by combining clustered data and ANFIS model, an hour-ahead forecasting is achieved, and it was validated using measured data. The advantage of the proposed method is that provides the ability to use implicitly the information associated with the forecasting problem, without a priori knowledge of the relationships between the different variables solar radiation. The comparison results show that the ANFIS with FCM clustering model gives the best results with RMSE equals to 112 W/m2 and high values of FS.
Journal Article
Estimation of solar radiation in data-scarce subtropical region using ensemble learning models based on a novel CART-based feature selection
Solar radiation estimation is essential with increasing energy demands for industrial and agricultural purposes to create a cleaner environment, negotiate climate change impacts, and attain sustainable development. However, the maintenance and operation of solar radiation measurements are costly due to the lack of pyranometers or their failure; hence, obtaining reliable solar radiation data is challenging in many subtropical regions. Despite its importance, a few studies use machine learning algorithms for solar radiation estimation in Bangladesh. To this end, this study contributes to filling the gap twofold. First, we presented the potentials of ensemble models, such as Bagging-REPT (reduced error pruning tree), random forest (RF), and Bagging-RF, which were compared to three standalone models, namely, Gaussian process regression (GPR), artificial neural network (ANN), and support vector machine (SVM), for estimating daily global solar radiation in three Bangladeshi regions. Second, we explore the optimal input parameters influencing solar radiation change at the regional scale using a classification and regression tree (CART)-based feature selection tool. Satellite-derived ERA5 reanalysis and NASA POWER project datasets were used as input parameters. The performance of the models was compared using performance evaluation metrics like correlation coefficient (
r
), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), index of agreement (IA), and Taylor diagram. Results suggested that the RF model performed 5.47–37.22% better than the standalone models in estimating daily solar radiation at Chuadanga in terms of RMSE. Besides, the other ensemble model Bagging-RF showed 14.9–25.03% and 11.46–30.97% greater performances in Dinajpur and Satkhira than the conventional models in RMSE metric. Besides, this study may provide knowledge to the policymakers to make critical judgments on future energy yield, efficiency, productivity, and operation, which are essential elements for investments and solar energy conversion applications in the subtropical areas of the world.
Journal Article
Evaluation and estimation of daily global solar radiation from the estimated direct and diffuse solar radiation
There are various empirical models used in the estimation of global solar radiation; however, knowledge of direct and diffuse solar radiation is insufficient. Global solar radiation is the sum of direct and diffuse solar radiation, and a method that calculates global solar radiation from the estimated direct and diffuse solar radiation was further proposed in this study. The observed daily solar radiation and meteorological data from 97 stations during 1993–2016 were used for the analysis, and the results indicated that the concave-shaped relationship with relative sunshine duration was more obvious for direct solar radiation than for global solar radiation, while an inverted u-shaped relationship was found for diffuse solar radiation. Generally, the performances of empirical models in estimating direct and diffuse solar radiation were worse than the estimation of global solar radiation. However, because the bias of estimated direct and diffuse solar radiation was partially offset, the results in this study indicated that global solar radiation can be better calculated from the estimated direct and diffuse solar radiation when compared with the best performed empirical model, especially in data-scarce regions. The results of this study will aid in better estimations and understanding of the variations in global solar radiation, as well as direct and diffuse solar radiation.
Journal Article