The Experts below are selected from a list of 273 Experts worldwide ranked by ideXlab platform
C Bertrand - One of the best experts on this subject based on the ideXlab platform.
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quality control of solar Radiation Data within the rmib solar measurements network
Solar Energy, 2011Co-Authors: Michel Journee, C BertrandAbstract:Assessment of the solar resource is based upon measured Data, where available. However, with any measurement there exist errors. Consequently, solar Radiation Data do not exhibit necessarily the same reliability and it often happens that users face time series of measurements containing questionable values though preliminary technical control has been done before the Data release. To overcome such a situation, a major effort has been undertaken at the Royal Meteorological Institute of Belgium (RMIB) to develop procedures and software for performing post-measurement quality control of solar Data from the radiometric stations of our in situ solar monitoring network. Moreover, because solar energy applications usually need continuous time series of solar Radiation Data, additional procedures have also been established to fill missing values (Data initially lacking or removed via quality checks).
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Improving the spatio-temporal distribution of surface solar Radiation Data by merging ground and satellite measurements
Remote Sensing of Environment, 2010Co-Authors: Michel Journee, C BertrandAbstract:Appropriate information on solar resources is very important for a variety of technological areas, such as: agriculture, meteorology, forestry engineering, water resources and in particular in the designing and sizing of solar energy systems. However, the availability of observed solar Radiation measurements has proven to be spatially and temporally inadequate for many applications. In this paper we propose to merge the global solar Radiation measurements from the Royal Meteorological Institute of Belgium solar measurements network with the operationally derived surface incoming global short-wave Radiation products from Meteosat Second Generation satellites imageries to improve the spatio-temporal resolution of the surface global solar Radiation Data over Belgium. We evaluate several merging methods with various degrees of complexity (from mean field bias correction to geostatistical merging techniques) together with interpolated ground measurements and satellite-derived values only. The performance of the different methods is assessed by leave-one-out cross-validation.
João C. Carvalho - One of the best experts on this subject based on the ideXlab platform.
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A multilayer perceptron approach for the retrieval of vertical temperature profiles from satellite Radiation Data
Proceedings. 2005 IEEE International Joint Conference on Neural Networks 2005., 1Co-Authors: Elcio Hideiti Shiguemori, J.d.s. Da Silva, H.fd.c. Velho, João C. CarvalhoAbstract:In this paper a multilayer perceptron neural network is used to retrieve vertical atmospheric temperature profiles from satellite Radiation Data. The training set consists of Data provided by the direct model characterized by the radiative transfer equation (RTE) and by real Radiation Data from the NOAA-HIRS/2 (high resolution infrared Radiation) sounder. The retrieved vertical temperature profiles are compared to radiosonde measured Data. The neural network performance is compared to the results of the projects by J.C. Carvalho et al (1999) and by F.M. Ramos et al (1999) who used regularization techniques. Neural network approaches are especially advantageous due to the embed parallelism that may imply in faster vertical temperature profiles retrieving systems.
Elcio Hideiti Shiguemori - One of the best experts on this subject based on the ideXlab platform.
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Amultilayer perceptron approach fortheretrieval of vertical temperature profiles fromsatellite Radiation Data
2005Co-Authors: Elcio Hideiti Shiguemori, S Demisio, Haroldo F. DecamposvelhoAbstract:Inthis paper amulti layer perceptron neural network isused toretrieve vertical atmospheric temperature profiles from satellite Radiation Data. Thetraining setconsists ofData provided bythedirect model characterized bytheRadiative Transfer Equation (RTE)andbyreal Radiation Datafrom theNOAA -HIRS/2 (High Resolution Infrared Radiation) Sounder. Theretrieved vertical temperature profiles are compared toradiosonde measured Data. Theneural network performance iscompared totheresults of[1]and[2] who usedregularization techniques. Neural network approaches areespecially advantageous duetotheembedparallelism thatmayimplyinfaster vertical temperature profiles retrieving systems.
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A multilayer perceptron approach for the retrieval of vertical temperature profiles from satellite Radiation Data
Proceedings. 2005 IEEE International Joint Conference on Neural Networks 2005., 1Co-Authors: Elcio Hideiti Shiguemori, J.d.s. Da Silva, H.fd.c. Velho, João C. CarvalhoAbstract:In this paper a multilayer perceptron neural network is used to retrieve vertical atmospheric temperature profiles from satellite Radiation Data. The training set consists of Data provided by the direct model characterized by the radiative transfer equation (RTE) and by real Radiation Data from the NOAA-HIRS/2 (high resolution infrared Radiation) sounder. The retrieved vertical temperature profiles are compared to radiosonde measured Data. The neural network performance is compared to the results of the projects by J.C. Carvalho et al (1999) and by F.M. Ramos et al (1999) who used regularization techniques. Neural network approaches are especially advantageous due to the embed parallelism that may imply in faster vertical temperature profiles retrieving systems.
Michel Journee - One of the best experts on this subject based on the ideXlab platform.
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quality control of solar Radiation Data within the rmib solar measurements network
Solar Energy, 2011Co-Authors: Michel Journee, C BertrandAbstract:Assessment of the solar resource is based upon measured Data, where available. However, with any measurement there exist errors. Consequently, solar Radiation Data do not exhibit necessarily the same reliability and it often happens that users face time series of measurements containing questionable values though preliminary technical control has been done before the Data release. To overcome such a situation, a major effort has been undertaken at the Royal Meteorological Institute of Belgium (RMIB) to develop procedures and software for performing post-measurement quality control of solar Data from the radiometric stations of our in situ solar monitoring network. Moreover, because solar energy applications usually need continuous time series of solar Radiation Data, additional procedures have also been established to fill missing values (Data initially lacking or removed via quality checks).
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Improving the spatio-temporal distribution of surface solar Radiation Data by merging ground and satellite measurements
Remote Sensing of Environment, 2010Co-Authors: Michel Journee, C BertrandAbstract:Appropriate information on solar resources is very important for a variety of technological areas, such as: agriculture, meteorology, forestry engineering, water resources and in particular in the designing and sizing of solar energy systems. However, the availability of observed solar Radiation measurements has proven to be spatially and temporally inadequate for many applications. In this paper we propose to merge the global solar Radiation measurements from the Royal Meteorological Institute of Belgium solar measurements network with the operationally derived surface incoming global short-wave Radiation products from Meteosat Second Generation satellites imageries to improve the spatio-temporal resolution of the surface global solar Radiation Data over Belgium. We evaluate several merging methods with various degrees of complexity (from mean field bias correction to geostatistical merging techniques) together with interpolated ground measurements and satellite-derived values only. The performance of the different methods is assessed by leave-one-out cross-validation.
Lucien Wald - One of the best experts on this subject based on the ideXlab platform.
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Using remotely sensed solar Radiation Data for reference evapotranspiration estimation at a daily time step
Agricultural and Forest Meteorology, 2008Co-Authors: Benjamin Bois, Lucien Wald, Philippe Pieri, Cornelis Van Leeuwen, Frédéric Huard, Jean-pierre Gaudillère, Etienne SaurAbstract:International audienceSolar Radiation is an important climatic variable for assessing reference evapotranspiration (E0), but it is seldom available in weather station records. Meteosat satellite images processed with the Heliosat-2 method provide the HelioClim-1 Database, which displays spatialized solar Radiation Data at a daily time step for Europe and Africa. The aim of the present work was to investigate the interest of satellite-sensed solar Radiation for E0 calculation, where air temperature is the sole local weather Data available. There were two study areas in Southern France. One (Southwest, SW) is characterized by Oceanic climate and the other (Southeast, SE) by Mediterranean climate. A Data set of daily values for 19 weather stations spanning five years (2000–2004) was used. First, a sensitivity analysis of the Penman–Monteith formula to climate input variables was performed, using the Sobol' method. It shows that E0 is mainly governed by solar Radiation during summer, and by wind speed during winter. Uncertainties of HelioClim-1 solar Radiation Data and their repercussions on E0 formulae were evaluated, using the FAO-56 Penman–Monteith formulae (PM) and Radiation-based methods (Turc, TU; Priestley–Taylor, PT and Hargreaves-Radiation, HR). It was shown that HelioClim-1 Data slightly underestimate solar Radiation and provide relative RMSE (root mean square error) of 20% of the mean annual value for SW and 14% for SE. The propagation of HelioClim-1 Data uncertainties is small in PM but considerable in Radiation methods. Four estimation methods were then compared to PM Data: the 1985 Hargreaves formula (HT) based on air temperature only; TU, PT and HR, based on air temperature and satellite-sensed solar Radiation. Radiation methods were more precise and more accurate than HT, with RMSE ranging from 0.52 mm to 0.86 mm against 0.67–0.96 mm. These results suggest that using satellite-sensed solar Radiation may improve E0 estimates for areas where air temperature is the only available record at ground level
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Using remotely sensed solar Radiation Data for reference evapotranspiration estimation at a daily time step
Agricultural and Forest Meteorology, 2007Co-Authors: Benjamin Bois, Lucien Wald, Philippe Pieri, Cornelis Van Leeuwen, Frédéric Huard, Jean-pierre Gaudillère, Etienne SaurAbstract:Solar Radiation is an important climatic variable for assessing reference evapotranspiration (E0), but it is seldom available in weather station records. Meteosat satellite images processed with the Heliosat-2 method provide the HelioClim-1 Database, which displays spatialized solar Radiation Data at a daily time step for Europe and Africa. The aim of the present work was to investigate the interest of satellite-sensed solar Radiation for E0 calculation, where air temperature is the sole local weather Data available. There were two study areas in Southern France. One (Southwest, SW) is characterized by Oceanic climate and the other (Southeast, SE) by Mediterranean climate. A Data set of daily values for 19 weather stations spanning five years (2000–2004) was used. First, a sensitivity analysis of the Penman–Monteith formula to climate input variables was performed, using the Sobol' method. It shows that E0 is mainly governed by solar Radiation during summer, and by wind speed during winter. Uncertainties of HelioClim-1 solar Radiation Data and their repercussions on E0 formulae were evaluated, using the FAO-56 Penman–Monteith formulae (PM) and Radiation-based methods (Turc, TU; Priestley–Taylor, PT and Hargreaves-Radiation, HR). It was shown that HelioClim-1 Data slightly underestimate solar Radiation and provide relative RMSE (root mean square error) of 20% of the mean annual value for SW and 14% for SE. The propagation of HelioClim-1 Data uncertainties is small in PM but considerable in Radiation methods. Four estimation methods were then compared to PM Data: the 1985 Hargreaves formula (HT) based on air temperature only; TU, PT and HR, based on air temperature and satellite-sensed solar Radiation. Radiation methods were more precise and more accurate than HT, with RMSE ranging from 0.52 mm to 0.86 mm against 0.67–0.96 mm. These results suggest that using satellite-sensed solar Radiation may improve E0 estimates for areas where air temperature is the only available record at ground level.
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ENERGYSPECIFIC SOLAR Radiation Data FROM MSG: THE HELIOSAT3 PROJECT
2006Co-Authors: M. Schroedter, Detlev Heinemann, Hermann Mannstein, Lucien WaldAbstract:Solar energy technologies such as photovoltaics, solar thermal power plants, passive solar heating/cooling systems and day lighting in buildings are expected to continue their very rapid growth. In this context the availability of reliable solar Radiation Data is of high economic value both for planning and operating these systems. HELIOSAT-3 aims the quantification of surface solar irradiance in cloud free and cloudy situations and additional energy-specific parameters as direct normal and diffuse irradiance over Europe and Africa using the enhanced capabilities of MSG. Emphasis is laid on clouds, water vapor, aerosols and ozone and their influence on surface solar irradiance. Several projects as e.g. the HELIOSAT-3 and PVSAT-2 European Commission FP5 and the ENVISOLAR (ESA Earth Observation Market Development Program) projects made profit from the Data access and additional MSG product information obtained through the RAO program. The paper focuses on results obtained during the RAO project based on funding in HELIOSAT-3, PVSAT-2 and ENVISOLAR projects.
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Energy-specific solar Radiation Data from MSG: The Heliosat-3 project
2006Co-Authors: Marion Schroedter Homscheidt, Jethro Betcke, Hanne Breitkreuz, Annette Hammer, Detlev Heinnemann, Sybille Petrack, Thomas Holzer-popp, Lucien WaldAbstract:Solar energy technologies such as photovoltaics, solar thermal power plants, passive solar heating/cooling systems and day lighting in buildings are expected to continue their very rapid growth. In this context the availability of reliable solar Radiation Data is of high economic value both for planning and operating these systems. HELIOSAT-3 aims the quantification of surface solar irradiance in cloud free and cloudy situations and additional energy-specific parameters as direct normal and diffuse irradiance over Europe and Africa using the enhanced capabilities of MSG. Emphasis is laid on clouds, water vapor, aerosols and ozone and their influence on surface solar irradiance. Several projects as e.g. the HELIOSAT-3 and PVSAT-2 European Commission FP5 and the ENVISOLAR (ESA Earth Observation Market Development Program) projects made profit from the Data access and additional MSG product information obtained through the RAO program. The paper focuses on results obtained during the RAO project based on funding in HELIOSAT-3, PVSAT-2 and ENVISOLAR projects.
