2013
DOI: 10.1016/j.solener.2012.10.007
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Accuracy of the solar irradiance forecasts of the Japan Meteorological Agency mesoscale model for the Kanto region, Japan

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Cited by 40 publications
(24 citation statements)
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“…However, few studies have been focused on the comparison of operational NWP models with satellite-derived data [13,15,[23][24][25][26]. These previous works have shown that, as in the case of reanalysis data, forecast models overestimate R s in general compared to the ground-based measurements.…”
Section: Discussion and Outlookmentioning
confidence: 99%
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“…However, few studies have been focused on the comparison of operational NWP models with satellite-derived data [13,15,[23][24][25][26]. These previous works have shown that, as in the case of reanalysis data, forecast models overestimate R s in general compared to the ground-based measurements.…”
Section: Discussion and Outlookmentioning
confidence: 99%
“…In contrast, [13] found a positive MBE using WRF for the four seasons of the year. Additionally, [25,26] have also obtained a different trend in the MBE statistical score when comparing the summer with the winter seasons, using the Japan Meteorological Agency mesoscale model (MSM). However, although the current study shows an underestimation of the observations using the RAMS model during the winter season, the MSM produces an overestimation of the observations during this season of the year over Japan.…”
Section: Discussion and Outlookmentioning
confidence: 99%
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“…Among the available algorithms, it is worth mentioning the Heliosat-2 method (Raschke et al, 1987;Rigollier et al, 2004;Blanc et al, 2011), the State University of New York (SUNY) model (Perez et al, 2002), the Surface Insolation under Clear and Cloudy skies model (SICCS; Greuell et al, 2013), and more sophisticated radiative transfer models (e.g., Pinker and Laszlo, 1992) and algorithms based on neural network models (e.g., Takenaka et al, 2011;Taylor et al, 2016). Because of its unprecedented temporal resolution (up to 2.5 min), the new Japanese geostationary meteorological satellite Himawari-8 is expected shortly to attain a key position within this framework, drastically improving atmospheric research (Bessho et al, 2016) and forecasts of photovoltaic power generation (e.g., Ohtake et al, 2013Ohtake et al, , 2015.…”
mentioning
confidence: 99%
“…Authors performed a validation of GHI day-ahead forecasts from the JMA NWPs and investigated forecast error characteristics [1,2] in cooperation with the JMA. An estimation of confidence intervals of hourly GHI forecasts has been investigated [3].…”
Section: Introductionmentioning
confidence: 99%