Takes a data frame containing daily records (minimum and maximum temperatures) and expands it into an hourly data frame (24 rows per day) using a sine-exponential reconstruction model. Returns a clean time-series data frame with combined datetime.
Usage
daily_to_hourly_temp(
data,
date_col,
t_min_col,
t_max_col,
lat_col,
lon_col = NULL,
tz = NULL
)Arguments
- data
A data frame containing the daily weather records.
- date_col
Unquoted name of the column containing the Date object.
- t_min_col
Unquoted name of the column containing the current day's minimum temperature (°C).
- t_max_col
Unquoted name of the column containing the current day's maximum temperature (°C).
- lat_col
Unquoted name of the column containing the latitude (decimal degrees).
- lon_col
Optional unquoted name of the column containing the longitude (decimal degrees). Default is
NULL.- tz
Optional numeric value indicating the time zone offset from UTC in hours (e.g., -3). Default is
NULL.
Value
A tibble (data frame) expanded to hourly resolution (24 rows per original daily row)
with two columns: datetime (POSIXct) and temperature_hourly (°C).
Examples
# Sample daily dataset representing 5 continuous days
daily_series <- tibble::tibble(
date = as.Date("2026-06-01") + 0:4,
lat = rep(-27.3, 5),
lon = rep(-50.6, 5),
tmin = c(12.0, 13.5, 11.0, 10.5, 14.0),
tmax = c(22.0, 24.5, 21.0, 19.5, 23.0)
)
# Standard usage (solar time)
daily_to_hourly_temp(daily_series, date, tmin, tmax, lat)
#> # A tibble: 120 × 2
#> datetime temperature_hourly
#> <dttm> <dbl>
#> 1 2026-06-01 00:00:00 14.7
#> 2 2026-06-01 01:00:00 14.2
#> 3 2026-06-01 02:00:00 13.9
#> 4 2026-06-01 03:00:00 13.5
#> 5 2026-06-01 04:00:00 13.3
#> 6 2026-06-01 05:00:00 13.1
#> 7 2026-06-01 06:00:00 12.9
#> 8 2026-06-01 07:00:00 12.7
#> 9 2026-06-01 08:00:00 12.6
#> 10 2026-06-01 09:00:00 13.1
#> # ℹ 110 more rows
# With longitude, time zone, and custom alpha parameter via ...
daily_to_hourly_temp(
daily_series, date, tmin, tmax, lat,
lon_col = lon, tz = -3
)
#> # A tibble: 120 × 2
#> datetime temperature_hourly
#> <dttm> <dbl>
#> 1 2026-06-01 00:00:00 14.9
#> 2 2026-06-01 01:00:00 14.4
#> 3 2026-06-01 02:00:00 14.0
#> 4 2026-06-01 03:00:00 13.6
#> 5 2026-06-01 04:00:00 13.4
#> 6 2026-06-01 05:00:00 13.1
#> 7 2026-06-01 06:00:00 12.9
#> 8 2026-06-01 07:00:00 12.8
#> 9 2026-06-01 08:00:00 12.7
#> 10 2026-06-01 09:00:00 12.6
#> # ℹ 110 more rows