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Huaman, J., (2024). Pronóstico de tiempo severo a muy corto plazo (Nowcasting) usando datos del satélite GOES-16 [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/6541
Huaman, J., Pronóstico de tiempo severo a muy corto plazo (Nowcasting) usando datos del satélite GOES-16 []. PE: Universidad Nacional Agraria La Molina; 2024. https://hdl.handle.net/20.500.12996/6541
@misc{renati/249214,
title = "Pronóstico de tiempo severo a muy corto plazo (Nowcasting) usando datos del satélite GOES-16",
author = "Huaman Chinchay, Joao Henry",
publisher = "Universidad Nacional Agraria La Molina",
year = "2024"
}
Title: Pronóstico de tiempo severo a muy corto plazo (Nowcasting) usando datos del satélite GOES-16
Authors(s): Huaman Chinchay, Joao Henry
Advisor(s): Cholan Rodriguez, Edison
Keywords: Nowcasting
OCDE field: https://purl.org/pe-repo/ocde/ford#1.05.09
Issue Date: 2024
Institution: Universidad Nacional Agraria La Molina
Abstract: El presente trabajo de suficiencia profesional (TSP) tiene por objetivo presentar un algoritmo computacional escrito en python, que usa las informaciones del satélite GOES-16 para realizar pronósticos horarios de lluvias moderadas, fuertes y extremas, las cuales son emitidas como avisos de lluvia a muy corto plazo (nowcating) en la página web del Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI). Los pronósticos realizados por este algoritmo son comparados con los datos de las estaciones automáticas del SENAMHI para evaluar el desempeño de estos pronósticos.
The objective of this Professional Sufficiency Work (PSW) is to present a computational algorithm written in Python, which uses information from the GOES-16 satellite to make hourly forecasts of moderate, heavy and extreme rains, which are issued as very short-term rain warnings (nowcating) on the website of the National Meteorology and Hydrology Service of Peru (SENAMHI). The forecasts made by this algorithm are compared with the data from the SENAMHI automatic stations to evaluate the performance of these forecasts.
The objective of this Professional Sufficiency Work (PSW) is to present a computational algorithm written in Python, which uses information from the GOES-16 satellite to make hourly forecasts of moderate, heavy and extreme rains, which are issued as very short-term rain warnings (nowcating) on the website of the National Meteorology and Hydrology Service of Peru (SENAMHI). The forecasts made by this algorithm are compared with the data from the SENAMHI automatic stations to evaluate the performance of these forecasts.
Link to repository: https://hdl.handle.net/20.500.12996/6541
Note: Universidad Nacional Agraria La Molina. Facultad de Ciencias. Departamento Académico de Ingeniería Ambiental, Física y Meteorología
Discipline: Ingeniería Ambiental, Física y Meteorología
Grade or title grantor: Universidad Nacional Agraria La Molina. Facultad de Ciencias
Grade or title: Ingeniero Meteorólogo
Juror: Calle Montes, Victoria Doris; Ibañez Blancas, Alexis Nicolas; Unsihuay Tovar, Franklin Delio
Register date: 4-Jun-2024
This item is licensed under a Creative Commons License