Meteosat LSA SAF DIDSSF Ürününün Türkiye İçin Tutarlılığının Değerlendirilmesi

Yıl 2020, Cilt: 1 Sayı: 2, 85 - 96, 30.09.2020

Kazım Kaba Derya Öztürk Çetni Mustafa Kandırmaz

Öz

Yeryüzüne gelen güneş radyasyonu, iklim, tarım, hidroloji ve enerji uygulamaları için büyük öneme sahiptir. Bu konularda yapılan çalışmalar için enerji değerlerinin zamansal ve alansal dağılımının bilinmesi dünya genelinde ihtiyaç duyulan bir bilgidir. Genel olarak güneş enerjisi ölçümleri meteoroloji istasyonlarında noktasal olarak gerçekleştirilmektedir. Son yıllarda yapılan çalışmalar göstermiştirki yüzeye gelen güneş enerjisi değerleri uydu verileri kullanılarak başarıyla tahmin edilebilmektedir. Meteosat uyduları Türkiye’yi de kapsayacak şekilde Avrupa ve Afrika’ya ait görüntüler kaydetmektedir. Bu kayıtlardan LSA SAF birimi tarafından yeryüzüne ait çeşitli parametreler tahmin edilmektedir. Bu parametrelerden biri olan yüzeye gelen günlük kısa dalga enerjinin tahmin edildiği DIDSSF verisidir. Bu çalışmanın amacı Türkiye için DIDSSF ürünün yer ölçümleri ile kıyaslayarak doğruluğunu belirlemektir. DIDSSF ürününün doğruluğu ülke coğrafyasına olabildiğince homojen dağılmış olan 46 adet MGM istasyonu ile ölçülen global güneş radyasyonu değerleri ile test edilmiştir. İstasyonlardan gelen değerler tek tek incelendiğinde, belirleme katsayısı olan R2’nin 0,7129 ila 0,9585 arasında değişim gösterdiği tespit edilmiştir. 46 adet istasyondan elde edilen ortalama R2 değeri ise 0,9058 olarak bulunmuştur.

Anahtar Kelimeler

Güneş radyasyonu, DIDSSF, Meteosat, Türkiye, Validasyon

Evaluation of the Accuracy of Meteosat LSA SAF DIDSSF Product for Turkey

Öz

The solar radiation that reaches to the surface of the Earth is of great importance for many applications such as climate, agriculture, hydrology and energy. Having knowledge on the temporal and spatial distribution of energy values is a worldwide need for the studies on these topics. Measurement of the solar radiation is generally carried out in a pointwise manner in meteorological stations. Recent studies show that solar radiation over large areas can be estimated successfully using satellite images. The Meteosat satellites record images of Europe and Africa, covering also Turkey. Using these records, the LSA SAF unit predicts various parameters that belongs to Earth. One of these parameters is the DIDSSF (daily downward surface short-wave flux), which predicts the daily short-wave radiation reaching to the Earth surface. This study aimed to evaluate the accuracy of the DIDSSF estimation for Turkey by comparing it against terrestrial measurements. The accuracy of the DIDSSF product was tested through the use of global solar radiation values measured at 46 MGM stations which were homogeneously distributed over the whole country as much as possible. Examination of the stations one by one revealed that the determination coefficient R2 varied between 0.7129 and 0.9585. The average R2 value obtained from 46 stations was found to be 0.9058.

Anahtar Kelimeler

Solar radiation, DIDSSF, Meteosat, Turkey, Validation

Kaynakça

• Angstrom, A. (1924). Solar and terrestrial radiation. Report to the international commission for solar research on actinometric investigations of solar and atmospheric radiation. Quarterly Journal of the Royal Meteorological Society, 50(210), 121-126.
• Behrang, M. A., Assareh, E., Ghanbarzadeh, A., & Noghrehabadi, A. R. (2010). The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data. Solar Energy, 84(8), 1468-1480.
• Cogliani, E., Ricchiazzi, P., & Maccari, A. (2007). Physical model SOLARMET for determinating total and direct solar radiation by meteosat satellite images. Solar Energy, 81(6), 791-798.
• Cristóbal, J., & Anderson, M. C. (2013). Validation of a Meteosat Second Generation solar radiation dataset over the northeastern Iberian Peninsula. Hydrol. Earth Syst. Sci., 17, 163–175, 2013.
• Deniz, A., Toros, H., & Incecik, S. (2011). Spatial variations of climate indices in Turkey. International Journal of climatology, 31(3), 394-403.
• EUMETSAT LSA SAF, (2011). Product User Manual – Down-welling Surface Shortwave Flux (DSSF). Retrieved from https://nextcloud.lsasvcs.ipma.pt/s/bXEkdAKRJJGSn3S#pdfviewer.
• EUMETSAT LSA SAF, (2020). Daily Downward Surface Shortwave Flux (DIDSSF, LSA-203). Retrieved from https://landsaf.ipma.pt/en/products/longwave-shortwave-radiation/didssf/.
• Feng, Y., Hao, W., Li, H., Cui, N., Gong, D., & Gao, L. (2020). Machine learning models to quantify and map daily global solar radiation and photovoltaic power. Renewable and Sustainable Energy Reviews, 118, 109393, doi: 10.1016/j.rser.2019.109393
• Gautier, C., Diak, G., & Masse, S. (1980). A simple physical model to estimate incident solar radiation at the surface from GOES satellite data. Journal of Applied Meteorology, 19(8), 1005-1012.
• Iyigun, C., Türkeş, M., Batmaz, İ., Yozgatligil, C., Purutçuoğlu, V., Koç, E. K., & Öztürk, M. Z. (2013). Clustering current climate regions of Turkey by using a multivariate statistical method. Theoretical and applied climatology, 114(1-2), 95-106.
• Kaba, K., Sarıgül, M., Avcı, M., & Kandırmaz, H. M. (2018). Estimation of daily global solar radiation using deep learning model. Energy, 162, 126-135.
• Moreno, A., Gilabert, M. A., Camacho, F., & Martínez, B. (2013). Validation of daily global solar irradiation images from MSG over Spain. Renewable Energy, 60, 332-342.
• Quesada-Ruiz, S., Linares-Rodríguez, A., Ruiz-Arias, J. A., Pozo-Vázquez, D., & Tovar-Pescador, J. (2015). An advanced ANN-based method to estimate hourly solar radiation from multi-spectral MSG imagery. Solar Energy, 115, 494-504.
• Rusen, S. E., Hammer, A., & Akinoglu, B. G. (2013). Estimation of daily global solar irradiation by coupling ground measurements of bright sunshine hours to satellite imagery. Energy, 58, 417-425.
• Sahin, S. (2012). An aridity index defined by precipitation and specific humidity. Journal of Hydrology, 444, 199-208.
• Sahin, S., & Cigizoglu, H. K. (2012). The sub-climate regions and the sub-precipitation regime regions in Turkey. Journal of Hydrology, 450, 180-189.
• Shamshirband, S., Mohammadi, K., Tong, C. W., Zamani, M., Motamedi, S., & Ch, S. (2016). A hybrid SVM-FFA method for prediction of monthly mean global solar radiation. Theoretical and Applied Climatology, 125(1-2), 53-65.
• Trigo, I. F., Dacamara, C. C., Viterbo, P., Roujean, J. L., Olesen, F., Barroso, C., ... & Geiger, B. (2011). The satellite application facility for land surface analysis. International Journal of Remote Sensing, 32(10), 2725-2744.
• Wu, L., Huang, G., Fan, J., Zhang, F., Wang, X., & Zeng, W. (2019). Potential of kernel-based nonlinear extension of Arps decline model and gradient boosting with categorical features support for predicting daily global solar radiation in humid regions. Energy Conversion and Management, 183, 280-295.