Clima

Teoría

La información del clima se obtiene del ASOS (*Automated Surface Serving System) ubicados en los aeropuertos de todas las ciudades del mundo.

Instalar paquetes y llamar librerias

#install.packages("riem") # Accesar al ASOS para obtener datos climáticos
library(riem)
#install.packages("tidyverse") #Manipulación de datos
library(tidyverse)

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#install.packages("ggplot2") # Gráficas con mejor diseño que plot
library(ggplot2)
#install.packages("plotly") #Gráficas con mejor calidad
library(plotly)

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Paso.1 Nuscar la red del país (México) y copiar CODE

#view(riem_networks())
# MX__ASOS

Paso.2 Buscar la estación o ciudad (Monterrey) y copiar ID

# view(riem_stations("MX__ASOS"))
#MMMY

Paso.3 Obtener datos del clima

clima_mty <- riem_measures("MMMY")

Ejercicio 1. Obetener datos del clima de Monterrey de febrero 2024

clima_mty_feb <- subset(clima_mty, valid >= as.POSIXct("2024-02-01 00:000") & valid <= as.POSIXct("2024-02-29 00:000"))

Ejercicio 2. Graficar la Humedad Relativa durante Febrero 2024

plot(clima_mty_feb$valid,clima_mty_feb$relh,type="l", main="Humedad Relativa en Monterrey durante Febrero 2024",xlab="Fecha",ylab = "Humedad Relativa(%)")

#Promediar humedad relativa diaria
clima_mty_feb$date <- as.Date(clima_mty_feb$valid)

cmfd <- aggregate(clima_mty_feb, by= list(date = clima_mty_feb$date), FUN=mean)

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plot(cmfd$date,cmfd$relh,type="l", main="Promedio Diario de Humedad Relativa en Monterrey durante Febrero 2024",xlab="Fecha",ylab = "Humedad Relativa(%)")

Ejercicio 3.

# Paso 1. Buscar la red del país (México) y copiar CODE
#View(riem_networks())
# MX__ASOS

# Paso 2. Buscar la estación o ciudad (Puebla) y copiar CODE
#View(riem_stations("MX__ASOS"))
# MMPB

# Paso 3. Obtener datos del clima de la ciudad 
clima_cva <- riem_measures("MMPB")

# Paso 4. Obtener datos del clima de Puebla en febrero
clima_cuerna_feb <- subset(clima_cva, valid >= as.POSIXct("2024-02-01 00:00") & valid <= as.POSIXct("2024-02-29 23:59"))

# Paso 5. Convertir temperatura en farenheit a celcius 
clima_cuerna_feb <- clima_cuerna_feb %>%  mutate(tmpc = (tmpf - 32) * (5/9))

# Promediar la temperatura Celsius por día
promedio_diario <- aggregate(clima_cuerna_feb$tmpc,by = list(date = as.Date(clima_cuerna_feb$valid)), FUN = mean)

plot(promedio_diario$date,promedio_diario$x, type = "l",main = "Promedio Diario de temperatura en Cuernavaca durante Febrero 2024", xlab = "Fecha", ylab = " Temperatura (°C)" )

Conclusión

En R podemos osbervar datos sobre el clima en diferentes ciudades alrededor del mundo, gracias a que en los aeropuertos de cada ciudad hay aparatos llamados ASOS que arrojan información cada 30 min sobre datos meterológicos. Nosotros podemos acceder a estos usando el paquete y libreria riem en el programa R, podemos analizarlos y sacar conclusiones que nos puede ayudar a hacer diferentes estudios.