R/summarise_weather.R

In cvoter/isoH2Obudget: Lake Water Budget Using Stable Isotopes

#' Monthly Weather
#'
#' Summarizes sub-monthly weather at a monthly timestep.
#'
#' @inheritParams summarise_inputs
#' @param timeseries a list with dates (POSIXct) to analyze, and intervals
#'                 (lubridate interval) covering the month before each analysis
#'                 date.
#'
#' @return monthly_weather, a data frame with the following columns:
#' \describe{
#' \item{date}{first of the month for each monthly observation}
#' \item{atmp_K}{mean monthly air temperature (K)}
#' \item{RH_pct}{mean monthly relative humidity (percent)}
#' \item{P_mm}{monthly precipitaiton (mm)}
#' \item{ET_mm}{monthly lake evaporation (mm)}
#' }
#'
#' @importFrom magrittr %>%
#' @importFrom dplyr group_by summarise
#' @importFrom rlang .data
#' @importFrom lubridate floor_date
#' @importFrom NISTunits NISTdegCtOk NISTdegTOradian
#' @importFrom CSLSevap CSLS_daily_met
#'
#' @export
summarise_weather <- function(weather, timeseries, lake){

  # Get lake evaporation
  # In the process converts hourly weather to daily
  # (atmp -> min/max daily atmp and RH -> min/max daily RH)
  daily_weather <- CSLSevap::CSLS_daily_met(method = "McJannet",
                                            lakename = lake)

  # Summarize weather at a monthly timestep
  monthly_weather <- NULL
  for (i in 1:length(timeseries$intervals)) {
    this_weather <- daily_weather %>%
                    filter(.data$date %within% timeseries$intervals[i])

    atmp_min <- mean(this_weather$atmp_min, na.rm = TRUE)
    atmp_max <- mean(this_weather$atmp_max, na.rm = TRUE)
    RH_min   <- mean(this_weather$RH_min, na.rm = TRUE)
    RH_max   <- mean(this_weather$RH_max, na.rm = TRUE)

    monthly_weather$date[i]      <- timeseries$dates[i]
    monthly_weather$atmp_degC[i] <- mean(c(atmp_min, atmp_max))
    monthly_weather$atmp_K[i]    <- NISTdegCtOk(monthly_weather$atmp_degC[i])
    monthly_weather$RH_pct[i]    <- mean(c(RH_min, RH_max))
    monthly_weather$P_mm[i]      <- sum(this_weather$P)
    monthly_weather$E_mm[i]      <- sum(this_weather$E)
  }
  monthly_weather$date <- as_datetime(monthly_weather$date)
  monthly_weather      <- as.data.frame(monthly_weather)

  return(monthly_weather)
}