Analysis of Spatial and Temporal Variability of the PAR/GHI Ratio and PAR Modeling Based on Two Satellite Estimates

The main objectives of this work are to address the analysis of the spatial and temporal variability of the ratio between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI), as well as to develop PAR models. The analysis was carried out using data from three stations located in mainland Spain covering three climates: oceanic, standard Mediterranean, and continental Mediterranean. The results of this analysis showed a clear dependence between the PAR/GHI ratio and the location; the oceanic climate showed higher values of PAR/GHI compared with Mediterranean climates. Further, the temporal variability of PAR/GHI was conditioned by the variability of clearness index, so it was also higher in oceanic than in Mediterranean climates. On the other hand, Climate Monitoring Satellite Facility (CM-SAF) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data were used to estimate PAR as a function of GHI over the whole territory. The validation with ground measurements showed better performance of the MODIS-estimates-derived model for the oceanic climate (root-mean-square error (RMSE) around 5%), while the model obtained from CM-SAF fitted better for Mediterranean climates (RMSEs around 2%)This work was funded by the Ministry of Economy, Industry and Competitiveness (MINECO) [Project CGL2016-79284-P AEI/FEDER/UE and F.F.-C. was founded by PhD Contract Number BES-2017-082043]S

Modeling photosynthetically active radiation from satellite-derived estimations over mainland Spain

A model based on the known high correlation between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI) was implemented to estimate PAR from GHI measurements in this present study. The model has been developed using satellite-derived GHI and PAR estimations. Both variables can be estimated using Kato bands, provided by Satellite Application Facility on Climate Monitoring (CM-SAF), and its ratio may be used as the variable of interest in order to obtain the model. The study area, which was located in mainland Spain, has been split by cluster analysis into regions with similar behavior, according to this ratio. In each of these regions, a regression model estimating PAR from GHI has been developed. According to the analysis, two regions are distinguished in the study area. These regions belong to the two climates dominating the territory: an Oceanic climate on the northern edge; and a Mediterranean climate with hot summer in the rest of the study area. The models obtained for each region have been checked against the ground measurements, providing correlograms with determination coefficients higher than 0.99This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) [Project CGL2016-79284-P AEI/FEDER/UE]S

A methodology for probabilistic assessment of solar thermal power plants yield

AIP Conference Proceedings 1850, 140006-1–140006-7A detailed knowledge of the solar resource is a critical point to perform an economic feasibility analysis of Concentrating Solar Power (CSP) plants. This knowledge must include its magnitude (how much solar energy is available at an area of interest over a long time period), and its variability over time. In particular, DNI inter-annual variations may be large, increasing the return of investment risk in CSP plant projects. This risk is typically evaluated by means of the simulation of the energy delivered by the CSP plant during years with low solar irradiation, which are typically characterized by annual solar radiation datasets with high probability of exceedance of their annual DNI values. In this context, this paper proposes the use meteorological years representative of a given probability of exceedance of annual DNI in order to realistically assess the inter-annual variability of energy yields. The performance of this approach is evaluated in the location of Burns station (University of Oregon Solar Radiation Monitoring Laboratory), where a 34- year (from 1980 to 2013) measured data set of solar irradiance and temperature is available

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V

A novel procedure for generating solar irradiance TSYs

AIP Conference Proceeding 1850, 140015-1–140015-8Typical Solar Years (TSYs) are key parameters for the solar energy industry. In particular, TSYs are mainly used for the design and bankability analysis of solar projects. In essence, a TSY intends to describe the expected longterm behavior of the solar resource (direct and/or global irradiance) into a condensed period of one year at the specific location of interest. A TSY differs from a conventional Typical Meteorological Year (TMY) by its absence of meteorological variables other than solar radiation. Concerning the probability of exceedance (Pe) needed for bankability, various scenarios are commonly used, with Pe90, Pe95 or even Pe99 being most usually required as unfavorable scenarios, along with the most widely used median scenario (Pe50). There is no consensus in the scientific community regarding the methodology for generating TSYs for any Pe scenario. Furthermore, the application of two different construction methods to the same original dataset could produce differing TSYs. Within this framework, a group of experts has been established by the Spanish Association for Standardization and Certification (AENOR) in order to propose a method that can be standardized. The method developed by this working group, referred to as the EVA method, is presented in this contribution. Its evaluation shows that it provides reasonable results for the two main irradiance components (direct and global), with low errors in the annual estimations for any given Pe. The EVA method also preserves the long-term statistics when the computed TSYs for a specific Pe are expanded from the monthly basis used in the generation of the TSY to higher time resolutions, such as 1 hour, which are necessary for the precise energy simulation of solar systems