Correction of Tropical Rainfall Measuring Missions Satellite Data of Solar Radiation for the High Andean Areas of Peru
Abstract
The spatial and temporal quantification of climatic elements is necessary in different regions of the world, as mitigation policies against climate change in recent years the use of renewable energies has been promoted, with solar radiation being an important element, the objective is to correct Tropical Rainfall Measuring Missions (TRMM) satellite data series of solar radiation with respect to the data observed through an automatic meteorological station for a short period at a point located in the southern Peruvian Andes, we proceeded to process the observed data and download satellite information, making use of From a mathematical model, the correction coefficients of the satellite data were determined; The multiplicative factor model better corrects the satellite information, the Pearson correlation improved from R = 0.65 to R = 0.84 for monthly solar radiation, in the series of satellite data corrected for 37 years, a trend was determined -0.0006 Watt/m2/month.
References
Cao, H., Han, L., Zhang, T., & Li, L. (2020). An Atmospheric Correction Algorithm for GF-2 Image Based on Radiative Transfer Model. IOP Conference Series: Materials Science and Engineering, 780(3), https://doi.org/10.1088/1757-899X/780/3/032040
Condom, T., Rau, P., & Espinoza, J. C. (2011). Correction of TRMM 3B43 monthly precipitation data over the mountainous areas of Peru during the period 1998-2007. Hydrological Processes, 25(12), 1924–1933. https://doi.org/10.1002/hyp.7949
Grossi, H., & Coquet, E. (2017). La pérdida de datos diarios de irradiación solar global y una evaluación sobre su influencia en los promedios mensuales. Revista de Climatología, 17, 45–57. Retrieved from http://www.climatol.eu/reclim/reclim17e.pdf
Jimenez, V. A., Will, A., & Rodríguez, S. (2017). Estimación de Radiación Solar Horaria Utilizando Modelos Empíricos y Redes Neuronales Artificiales. Ciencia y Tecnología, 1(17), 29. https://doi.org/10.18682/cyt.v1i17.608
Lavado, P. R. A. U., & Condom, T. (2010). Análisis espacio temporal de la precipitación en las zonas de montaña de Spatio-temporal analysis of rainfall in the mountain regions of Peru (1998-2007), 29(2), 16–29.
Lavorato, M. B., Lakkis, S. G., & Canziani, P. O. (2013). Radiación solar : métodos de regresión para datos del 2010-2013 en Buenos Aires Solar radiation: regression methods for data period 2010-2013 in Buenos Aires, 26.
Mazorra Aguiar, L., Polo, J., Vindel, J. M., & Oliver, A. (2019). Analysis of satellite derived solar irradiance in islands with site adaptation techniques for improving the uncertainty. Renewable Energy, 135, 98–107. https://doi.org/10.1016/j.renene.2018.11.099
Polo, J., Wilbert, S., Ruiz-Arias, J. A., Meyer, R., Gueymard, C., Súri, M., … Cebecauer, T. (2016). Preliminary survey on site-adaptation techniques for satellite-derived and reanalysis solar radiation datasets. Solar Energy, 132, 25–37. https://doi.org/10.1016/j.solener.2016.03.001
Polo, Jesus, Fernández-Peruchena, C., Salamalikis, V., Mazorra-Aguiar, L., Turpin, M., Martín-Pomares, L., … Remund, J. (2020). Benchmarking on improvement and site-adaptation techniques for modeled solar radiation datasets. Solar Energy, 201(October 2019), 469–479. https://doi.org/10.1016/j.solener.2020.03.040
Segura, H., Espinoza, J. C., Junquas, C., & Takahashi, K. (2016). Evidencing decadal and interdecadal hydroclimatic variability over the Central Andes. Environmental Research Letters, 11(9). https://doi.org/10.1088/1748-9326/11/9/094016
Stoffel, T. L., Reda, I., Myers, D. R., Renne, D., Wilcox, S., & Treadwell, J. (2000). Current issues in terrestrial solar radiation instrumentation for energy, climate, and space applications. Metrologia, 37(5), 399–402. https://doi.org/10.1088/0026-1394/37/5/11
Yang, D., & Bright, J. M. (2020). Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years. Solar Energy, (April), 1–18. https://doi.org/10.1016/j.solener.2020.04.016
Yeom, J. M., Deo, R. C., Adamwoski, J. F., Chae, T., Kim, D. S., Han, K. S., & Kim, D. Y. (2020). Exploring solar and wind energy resources in North Korea with COMS MI geostationary satellite data coupled with numerical weather prediction reanalysis variables. Renewable and Sustainable Energy Reviews, 119(xxxx), 109570. https://doi.org/10.1016/j.rser.2019.109570
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright for this article is retained by the author(s), with first publication rights granted to the journal.
This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
