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

Generating a climatology of surface solar radiation over the UK with application to wheat yield prediction

A UK climatology of daily mean Surface Incoming Shortwave (SIS) solar radiation was generated for the period 1983-2010 using a combination of satellite based data from the Climate Data Record (CDR) of SIS provided by the Climate Monitoring Satellite Applications Facility (CMSAF) and by MeteoSwiss. The combined version of these datasets has a 3km spatial resolution and it is currently the best available, long-term homogeneous satellite-based climate data record of daily surface solar radiation. The SIS climatology enabled an investigation of UK inter-annual variability and long term trends. The impact of synoptic scale weather typing on SIS accumulations was analysed using a combination of daily satellite based data from CMSAF and daily weather types from the GrossWetterLagen classification (GWL). Solar radiation drives photosynthesis in crops, highlighting the importance of knowing the spatial and temporal distribution of this valuable resource. Harnessing both state-of-the-art satellite based SIS estimates and model based temperature records enabled an investigation of the contributory effect of the variable radiation climate to the UK ‘yield plateau’ in wheat which has been widely observed over the last twenty years. Trend analyses do not support the theory that the observed yield plateau may be completely explained by solar radiation variability, since the main wheat growing area of England exhibits a general 3-5% increase of SIS accumulations during a fixed grain fill window over the 1994-2010 period. However, analysis performed to quantify the statistical relationship between SIS recorded during grain fill and actual yields from the HGCA Recommended Lists (RL) trial sites reveals encouraging results when controlling for soil type and previous cro

System Vicarious Calibration for Copernicus Ocean Colour Missions: Updated Requirements and Recommendations for a European Site

The Copernicus Program has been established through the Regulation EU No377/2014 with the objective to ensure long-term and sustained provision of accurate and reliable data on environment and security through dedicated services. Among these, the Copernicus Marine Environment Monitoring Service and the marine component of the Climate Change Service, both rely on satellite ocean colour observations to deliver data on water quality and climate relevant quantities such as chlorophyll-a concentration used as a proxy for phytoplankton biomass. Satellite ocean colour missions require in situ highly accurate radiometric measurements for the indirect calibration (so called System Vicarious Calibration (SVC)) of the space sensor. This process is essential to minimize the combined effects of uncertainties affecting the space sensor calibration and those resulting from the inaccuracy of processing algorithms and models applied for the generation of data products. SVC is thus a fundamental element to maximize the return on investments for the Copernicus Program by delivering to the user science community satellite ocean colour data with accuracy granting achievement of target objectives from applications addressing environmental and climate change issues. The long-term Copernicus Program foresees multiple ocean colour missions (i.e., the Sentinel-3 satellites carrying the Ocean and Land Colour Instrument (OLCI)). The need to ensure the highest accuracy to satellite derived data products contributing to the construction of Climate Data Records (CDRs), suggests the realization, deployment and sustain of a European in situ infrastructure supporting SVC for Sentinel-3 missions, fully independent from similar facilities established and maintained by other space agencies (e.g., that operated in the Pacific Ocean by US agencies). It is emphasized that the need to cope with long-term Copernicus objectives on data accuracy, implies very stringent requirements for the in situ infrastructure and location providing reference measurements for SVC. These requirements, in fact, are much higher than those imposed by SVC for a single mission. The content of this Report, which is a revised version of a previous one (Zibordi et al. 2017), builds on the long-standing experience of the JRC on ocean colour radiometry. This experience counts on decadal field and laboratory measurements performed in support of validation and SVC applications, and additionally on activities comprehensively embracing measurement protocols, instruments characterization and the initiation of autonomous measurement infrastructures. Overall, this Report summarizes a number of recent investigations led by the JRC on SVC requirements for the creation of CDRs. The final objective is to consolidate in a single document the elements essential fJRC.D.2-Water and Marine Resource

A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation

We present a new database of solar radiation at ground level for Eastern Europe and Africa, the Middle East and Asia, estimated using satellite images from the Meteosat East geostationary satellites. The method presented calculates global horizontal (G) and direct normal irradiance (DNI) at hourly intervals, using the full Meteosat archive from 1998 to present. Validation of the estimated global horizontal and direct normal irradiance values has been performed by comparison with high-quality ground station measurements. Due to the low number of ground measurements in the viewing area of the Meteosat Eastern satellites, the validation of the calculation method has been extended by a comparison of the estimated values derived from the same class of satellites but positioned at 0ºE, where more ground stations are available. Results show a low overall mean bias deviation (MBD) of +1.63W/m-2 or +0.73\% for global horizontal irradiance. The mean absolute bias of the individual station MBD is 2.36\%, while the root mean square deviation of the individual MBD values is 3.18\%. For direct normal irradiance the corresponding values are overall MBD of +0.62W/m-2 or +0.62\%, while the mean absolute bias of the individual station MBD is 5.03\% and the root mean square deviation of the individual MBD values is 6.24\%. The resulting database of hourly solar radiation values will be made freely available. These data will also be integrated into the PVGIS web application to allow users to estimate the energy output of photovoltaic (PV) systems not only in Europe and Africa, but now also in Asia.JRC.F.7-Renewables and Energy Efficienc

Surface solar irradiance from SCIAMACHY measurements: algorithm and validation

Broadband surface solar irradiances (SSI) are, for the first time, derived from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) satellite measurements. The retrieval algorithm, called FRESCO (Fast REtrieval Scheme for Clouds from the Oxygen A band) SSI, is similar to the Heliosat method. In contrast to the standard Heliosat method, the cloud index is replaced by the effective cloud fraction derived from the FRESCO cloud algorithm. The MAGIC (Mesoscale Atmospheric Global Irradiance Code) algorithm is used to calculate clear-sky SSI. The SCIAMACHY SSI product is validated against globally distributed BSRN (Baseline Surface Radiation Network) measurements and compared with ISCCP-FD (International Satellite Cloud Climatology Project Flux Dataset) surface shortwave downwelling fluxes (SDF). For one year of data in 2008, the mean difference between the instantaneous SCIAMACHY SSI and the hourly mean BSRN global irradiances is −4 W m<sup>−2</sup> (−1 %) with a standard deviation of 101 W m<sup>−2</sup> (20 %). The mean difference between the globally monthly mean SCIAMACHY SSI and ISCCP-FD SDF is less than −12 W m<sup>−2</sup> (−2 %) for every month in 2006 and the standard deviation is 62 W m<sup>−2</sup> (12 %). The correlation coefficient is 0.93 between SCIAMACHY SSI and BSRN global irradiances and is greater than 0.96 between SCIAMACHY SSI and ISCCP-FD SDF. The evaluation results suggest that the SCIAMACHY SSI product achieves similar mean bias error and root mean square error as the surface solar irradiances derived from polar orbiting satellites with higher spatial resolution

System Vicarious Calibration for Copernicus Ocean Colour Missions: Requirements and Recommendations for a European Site

The Copernicus Program has been established through the Regulation EU No377/2014 with the objective to ensure long-term and sustained provision of accurate and reliable data on environment and security through dedicated services. Among these, the Copernicus Marine Environment Monitoring Service and the marine component of the Climate Change Service, both rely on satellite ocean colour observations to deliver data on water quality and climate relevant quantities such as chlorophyll-a concentration used as a proxy for phytoplankton biomass. Satellite ocean colour missions require in situ highly accurate radiometric measurements for the indirect calibration (so called System Vicarious Calibration (SVC)) of the space sensor. This process is essential to minimize the combined effects of uncertainties affecting the space sensor calibration and those resulting from the inaccuracy of processing algorithms and models applied for the generation of data products. SVC is thus a fundamental element to maximize the return on investments for the Copernicus Program by delivering to the user science community satellite ocean colour data with accuracy granting achievement of target objectives from applications addressing environmental and climate change issues. The long-term Copernicus Program foresees multiple ocean colour missions (i.e., the Sentinel-3 satellites carrying the Ocean and Land Colour Instrument (OLCI)). The need to ensure the highest accuracy to satellite derived data products contributing to the construction of Climate Data Records (CDRs), suggests the realization, deployment and sustain of a European in situ infrastructure supporting SVC for Sentinel-3 missions, fully independent from similar facilities established and maintained by other space agencies (e.g., that operated in the Pacific Ocean by US agencies). It is emphasized that the need to cope with long-term Copernicus objectives on data accuracy, implies very stringent requirements for the in situ infrastructure and location providing reference measurements for SVC. These requirements, in fact, are much higher than those imposed by SVC for a single mission. The content of this Report builds on the long-standing experience of the JRC on ocean colour radiometry. This experience counts on decadal field and laboratory measurements performed in support of validation and SVC applications, and additionally on activities comprehensively embracing measurement protocols, instruments characterization and the initiation of autonomous measurement infrastructures. Overall, this Report summarizes a number of recent investigations led by the JRC on SVC requirements for the creation of CDRs. The final objective is to consolidate in a single document the elements essential for the realization of a European SVC infrastructure in support of the Copernicus Program. Briefly, the various Chapters summarize: • General requirements for a long-term SVC infrastructure, which indicate the need for spatially homogenous oceanic optical properties, seasonal stability of marine and atmospheric geophysical quantities, negligible land perturbations, hyperspectral radiometry, and low measurement uncertainties; • Spectral resolution requirements for in situ SVC hyperspectral measurements as a function of bandwidths and center-wavelengths of most advanced satellite sensors, which specify the need for sub-nanometre resolutions to allow for supporting any scheduled satellite ocean color sensor; • Suitable SVC locations in European Seas showing the fitness of regions in the Eastern Mediterranean Sea to satisfy fundamental requirements.JRC.D.2-Water and Marine Resource

Assessment of Several Empirical Relationships for Deriving Daily Means of UV-A Irradiance from Meteosat-Based Estimates of the Total Irradiance

International audienceDaily estimates of the solar UV-A radiation (315–400 nm) at the surface, anywhere, anytime, are needed in many epidemiology studies. Satellite-derived databases of solar total irradiance, combined with empirical relationships converting totals into daily means of UV-A irradiance I UV , are a means to satisfy such needs. Four empirical relationships are applied to three different databases: HelioClim-3 (versions 4 and 5) and CAMS Radiation Service—formerly known as MACC-RAD—derived from Meteosat images. The results of these combinations are compared to ground-based measurements located in mid-latitude Europe, mostly in Belgium. Whatever the database, the relationships of Podstawczynska (2010) and of Bilbao et al. (2011) exhibit very large underestimation and RMSE on the order of 40%–50% of the mean I UV. Better and more acceptable results are attained with the relationships proposed by Zavodska and Reichrt (1985) and that of Wald (2012). The relative RMSE is still large and in the range 10%–30% of the mean I UV. The correlation coefficients are large for all relationships. Each of them captures most of the variability contained in the UV measurements and can be used in studies where correlation plays a major role

Desing and optimization of artificial neural network models for solar resource assessment

[ES]El objetivo de la tesis es desarrollar varios modelos basados en redes neuronales artificiales para evaluar el recurso solar a nivel diario y horario, generando estimaciones fiables de GHI y de DNI en zonas geográficas extensas. Como variables de entrada se utilizan imágenes de satélite y productos globales de reanálisis, que cubren todo el globo o áreas geográficas muy extensas. Los dos primeros modelos generan estimaciones diarias de GHI. El primero utiliza como variables de entrada datos de los reanálisis ERA-Interim del ECMWF. El segundo modelo utiliza imágenes del satélite Meteosat 9, que tienen una mayor resolución espacial y temporal. Los otros dos modelos son ensambles de redes neuronales optimizadas para generar estimaciones horarias de GHI y DNI respectivamente, a partir de los 11 canales espectrales del satélite Meteosat 9. Ambos modelos han sido evaluados en una región muy extensa (casi toda Europa y parte de África y Oriente Medio).[EN]The aim of the thesis is the design and development of artificial neural network models for solar resource assessment, deriving reliable GHI and DNI estimates over large areas. Satellite imagery and reanalysis products, covering the whole globe or extensive areas, are used as input variables. The first two models generate daily GHI estimates. The first one uses ECMWF ERA-Interim data as input variables. The second one uses Meteosat-9 images, with better spatial and temporal resolution. The other two models are artificial neural network ensemble models for estimating hourly GHI and DNI respectively, using eleven Meteosat-9 spectral channels. Both models have been validated in a large region, covering mainly Europe and part of Africa and Middle East.Tesis Univ. Jaén. Departamento de Física, leída el 7 de julio de 201