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Surface global irradiance assessed by three different methods

Zheng, Pingyun (2018) Surface global irradiance assessed by three different methods. Maestría thesis, Universidad Nacional de Colombia - Sede Bogotá.

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Three methods will be used to evaluate the surface global irradiance: radiative transfer theory, empirical regression, and artificial neural networks (ANN). Radiative transfer is the fundamental theory that describes the propagation of radiation through a medium; empirical regression predicts surface global irradiance in simple parameterizations; artificial neural network, as an artificial intelligence technique, can also be tried to assess the surface global irradiance. These three approaches are studied in the present work. Data from the station “EL IDEAM” were used in the modeling experiments built upon these approaches to evaluate the daily transparency, also known as clearness index. We found out that the optimal inputs for artificial neural networks are extraterrestrial irradiance, surface relative humidity, and a pollution index based on particulate matter of sizes less than 10µm (PM 10 ). Surface relative humidity was suggested in a regression trial under meteorological conditions of “EL IDEAM”. By means of the programming code DISORT for the solution of the radiative transfer equation, daily irradiance characteristics were analyzed, and a hybrid model was created. Our results showed that artificial neural network produces higher scores than the other methods, though advantages and drawbacks are also discussed and compared.

Tipo de documento:Tesis/trabajos de grado - Thesis (Maestría)
Colaborador / Asesor:Pelkowski Goebel, Joaquín
Información adicional:Magíster en Ciencias - Meteorología. Línea de Investigación: Radiación atmosférica, especialmente irradiancia en superficie.
Palabras clave:Surface global irradiance, Clearness index, Linear regression, Artificial neural network, Radiative transfer, DISORT
Temática:5 Ciencias naturales y matemáticas / Science > 51 Matemáticas / Mathematics
5 Ciencias naturales y matemáticas / Science > 53 Física / Physics
5 Ciencias naturales y matemáticas / Science > 55 Ciencias de la tierra / Earth sciences & geology
Unidad administrativa:Sede Bogotá > Facultad de Ciencias > Departamento de Geociencias
Código ID:72996
Enviado por : Pingyun Zheng
Enviado el día :25 Julio 2019 19:46
Ultima modificación:25 Julio 2019 19:46
Ultima modificación:25 Julio 2019 19:46
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