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Open AccessArticle

Nowcasting Surface Solar Irradiance with AMESIS via Motion Vector Fields of MSG-SEVIRI Data

1
Institute of Methodologies for Environmental Analysis, National Research Council (IMAA/CNR), 85100 Potenza, Italy
2
School of Engineering, University of Basilicata, 85100 Potenza, Italy
3
Center of Excellence Telesensing of Environment and Model Prediction of Severe events (CETEMPS), University of L’Aquila, 67100 L’Aquila, Italy
4
Institute for Archaeological and Monumental Heritage, National Research Council (IBAM/CNR), 85100 Potenza, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 845; https://doi.org/10.3390/rs10060845
Received: 3 May 2018 / Revised: 25 May 2018 / Accepted: 27 May 2018 / Published: 29 May 2018
(This article belongs to the Special Issue Solar Radiation, Modelling and Remote Sensing)
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Abstract

In this study, we compare different nowcasting techniques based upon the calculation of motion vector fields derived from spectral channels of Meteosat Second Generation—Spinning Enhanced Visible and InfraRed Imager (MSG-SEVIRI). The outputs of the nowcasting techniques are used as inputs to the Advanced Model for Estimation of Surface solar Irradiance from Satellite (AMESIS), for predicting surface solar irradiance up to 2 h in advance. In particular, the first part of the methodology consists in projecting the time evolution of each MSG-SEVIRI channel (for every pixel in the spatial domain) through extrapolation of a displacement vector field obtained by matching similar patterns within two successive MSG-SEVIRI data images. Different ways to implement the above method result in substantial differences in the predicted trajectory, leading to different performances depending on the time interval of interest. All the nowcasting techniques considered here systematically outperform the simple persistence method for all MSG-SEVIRI channels and for each case study used in this work; importantly, this occurs across the entire 2 h period of the forecast. In the second part of the algorithm, the predicted irradiance maps computed with AMESIS from the forecasted radiances, are shown to be in good agreement with irradiances derived from MSG measured radiances and improve on numerical weather model predictions, thus providing a feasible alternative for nowcasting surface solar radiation. The results show that the mean values for correlation, bias, and root mean square error vary across the time interval, ranging between 0.94, −1 W/m 2 , 61 W/m 2 after 15 min, and 0.73, −18 W/m 2 , 147 W/m 2 after 2 h, respectively. View Full-Text
Keywords: solar irradiance; nowcasting; AMESIS; MSG; SEVIRI; radiance; brightness temperature; motion vector field solar irradiance; nowcasting; AMESIS; MSG; SEVIRI; radiance; brightness temperature; motion vector field
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Gallucci, D.; Romano, F.; Cersosimo, A.; Cimini, D.; Di Paola, F.; Gentile, S.; Geraldi, E.; Larosa, S.; Nilo, S.T.; Ricciardelli, E.; Viggiano, M. Nowcasting Surface Solar Irradiance with AMESIS via Motion Vector Fields of MSG-SEVIRI Data. Remote Sens. 2018, 10, 845.

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