Evaluación de variables meteorológicas modeladas para determinar el clima de ciudades costeras argentinas
; Bustos, María Luján
; Perillo, Gerardo Miguel E.
; Piccolo, Maria Cintia 
Otros responsables
Fecha
2021-05-19
Editorial
Universidad de Alicante
Revista
Investigaciones Geográficas
Título del libro
Nombre del evento
Fecha del evento
Institución organizadora
ISSN
0213-4691
eISSN
1989-9890
ISBN
Idioma
Español
Tipo del evento
Clasificación temática
Palabras clave
Resumen
El conocimiento del clima de las ciudades costeras es importante para el ordenamiento del espaciourbano. Para su estudio, se necesitan series superiores a 30 a os que suelen ser escasas o inconsistentes. En este contexto, los modelos numéricos favorecen la generación de datos meteorológicos. Por ello, el objetivo de este estudio fue evaluar la precisión y ajuste entre datos de temperatura del aire, humedad relativa y precipitación obtenidos con el Reanalysis NCEP/NCAR y observaciones in situ para ocho ciudades costeras marinas y fluviales de Argentina localizadas en distintas regiones climáticas. Para ello, se compararon series meteorológicas del período 1960-2019 y las provenientes del Reanalysis. Ambas se evaluaron considerando distintas escalas espacio-temporales, utilizando diferentes m todos estadísticos.Los mismos favorecieron el conocimiento del ajuste entre las series en periodos normales, pero también se analizaron los valores extremos de las series a partir de una regresión por cuartiles. La temperatura del aire se ajustó mejor en las escalas climática (60 años), mensual y modelada. La humedad relativa tuvo más correlación en la escala estacional, en invierno y otoño, excepto para las ciudades de clima cálido y húmedo. Finalmente, en las precipitaciones el ajuste fue mejor en todas las escalas temporales para los climas templados y áridos. Los resultados generados representan una base de datos esencial para la toma de decisiones orientada a mejorar la calidad de vida de la población y el ambiente costero.
An understanding of the climate of coastal cities is crucial for orientating urban land management. For this reason, it is essential to have access to long series of meteorological information with periods greater than 30 years. A lack of information or inconsistency can make climate study difficult. Numerical models are a suitable tool for the generation of climate data. For these reasons, this study aims to assess the precision and accuracy of temperature, relative humidity, and precipitation obtained in situ and derived from the Reanalysis NCEP/NCAR in eight coastal cities in different climates of Argentina. To do so, we studied the climatic series for the 1960-2019 period and those generated with the Reanalysis. Both series were statistically compared, considering diverse time scales and applying statistical methods. Time series were analysed using the quantile regression method to assess the study of the extremes in all the variables. The temperature presented a good agreement in climatic (60 years), monthly, and model scales. Relative humidity had higher results on the seasonal scale (mainly in winter and autumn), except for the cities located in warm and humid climates. Finally, rainfall registered good agreement in all temporal scales studied for cities located in temperate and arid climates. Results represent an essential database to orientate management plans and improve the quality of life and the coastal environment.
An understanding of the climate of coastal cities is crucial for orientating urban land management. For this reason, it is essential to have access to long series of meteorological information with periods greater than 30 years. A lack of information or inconsistency can make climate study difficult. Numerical models are a suitable tool for the generation of climate data. For these reasons, this study aims to assess the precision and accuracy of temperature, relative humidity, and precipitation obtained in situ and derived from the Reanalysis NCEP/NCAR in eight coastal cities in different climates of Argentina. To do so, we studied the climatic series for the 1960-2019 period and those generated with the Reanalysis. Both series were statistically compared, considering diverse time scales and applying statistical methods. Time series were analysed using the quantile regression method to assess the study of the extremes in all the variables. The temperature presented a good agreement in climatic (60 years), monthly, and model scales. Relative humidity had higher results on the seasonal scale (mainly in winter and autumn), except for the cities located in warm and humid climates. Finally, rainfall registered good agreement in all temporal scales studied for cities located in temperate and arid climates. Results represent an essential database to orientate management plans and improve the quality of life and the coastal environment.
Colecciones
Aprobación
Revisión
Complementado por
Referenciado por
Licencia Creative Commons
Excepto donde se indique lo contrario, la licencia de este ítem se describe como by
