Pronóstico de tiempo severo a muy corto plazo (Nowcasting) usando datos del satélite GOES-16
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Authors
Huaman Chinchay, Joao Henry
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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.
Description
Universidad Nacional Agraria La Molina. Facultad de Ciencias. Departamento Académico de Ingeniería Ambiental, Física y Meteorología
Keywords
Nowcasting
Citation
Date
2024
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