% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/relativehumidity.R
\docType{data}
\name{RelativeHumidity}
\alias{RelativeHumidity}
\title{Monthly Relative Humidity Data}
\format{
A data frame with 312 observations and 11 variables:
\describe{
  \item{date}{Date. Last day of the reference month for the monthly
        measurements (YYYY-MM-DD).}
  \item{rh}{Numeric. Monthly mean relative humidity, originally measured
        in percent and rescaled to the unit interval (0, 1).}
  \item{ins}{Numeric. Monthly total insolation (in hours), contains
        2 missing values.}
  \item{ins2}{Numeric. Monthly total insolation (in hours) with missing
        values imputed via seasonal interpolation.}
  \item{pre}{Numeric. Monthly total precipitation (in mm), contains
        2 missing values.}
  \item{pre2}{Numeric. Monthly total precipitation (in mm) with missing
        values imputed via seasonal interpolation.}
  \item{cld}{Numeric. Monthly mean cloudiness (in tenths).}
  \item{ap}{Numeric. Monthly mean atmospheric pressure (in hPa).}
  \item{tmax}{Numeric. Monthly mean of daily maximum temperature
        (in degrees Celsius).}
  \item{ws}{Numeric. Monthly mean wind speed (in m/s).}
  \item{wd}{Numeric. Monthly predominant wind direction, coded by
        INMET/BDMEP in tens of degrees (e.g., 9 = 90 degrees, East;
        32 = 320 degrees, Northwest). A value of 0 indicates calm
        conditions (no wind or undefined direction). Multiply by 10
        to obtain the direction in degrees (0-360).}
}
}
\source{
Instituto Nacional de Meteorologia (INMET). Banco de Dados
Meteorológicos para Ensino e Pesquisa (BDMEP), Estação de Brasília
(https://bdmep.inmet.gov.br). Data accessed in 2026.
}
\usage{
data(RelativeHumidity)
}
\description{
Monthly meteorological data including relative humidity (rh),
temperature, insolation, precipitation, and wind speed for the
meteorological station of Brasília, Brazil (2000-2025), obtained from
the National Institute of Meteorology (INMET).

The dataset contains two missing observations in the variables \code{ins}
and \code{pre}, corresponding to September 2020 and November 2025. To address
these missing values, imputation was performed via seasonal interpolation using
the \pkg{imputeTS} package, with the imputed versions stored as \code{ins2}
and \code{pre2}.
}
\examples{
# Load the dataset
data(RelativeHumidity)

# View first rows
head(RelativeHumidity)

# Check structure
str(RelativeHumidity)

# Insolation with and without imputation
plot(RelativeHumidity$ins, type = "l", col = "red",
     ylab = "Insolation", main = "Missing values visible as gaps")
points(RelativeHumidity$ins2, type = "l", col = "blue")
}
\keyword{datasets}
