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Aggregate Weather Observations to Daily Data

Source: R/aggregate_weather_daily.R
aggregate_weather_daily.Rd

Converts sub-daily weather observations to one row per day, optionally within each site or location. The same statistics style used by the window workflow is supported here: use a character vector to apply the same statistics to every variable, or use a named list to choose different statistics for different variables. The special .conditions entry can be used for multivariable summaries within each daily group.

Usage

aggregate_weather_daily(
  weather,
  id_col = NULL,
  time_col = "time",
  date_col = "date",
  weather_cols = NULL,
  temp_col = "temp",
  rh_col = "rh",
  rain_col = "rain",
  leaf_wetness_col = "leaf_wetness",
  statistics = list(temp = "mean", rh = "mean", rain = "sum", leaf_wetness = "sum"),
  keep_time = TRUE,
  name_prefix = "daily"
)

Arguments

weather

A weather data frame.

id_col

Optional site, location, or series identifier column. If supplied, aggregation is done separately within each ID.

time_col

Name of the timestamp column. Use NULL when the input data already have a day/date column and no separate timestamp column is needed.

date_col

Name of the day/date column. If this column already exists in weather, it is used for daily grouping. If it does not exist, aggregate_weather_daily() derives it from time_col and creates it in the output.

weather_cols

Character vector of weather columns to aggregate. If named, the names are used in the output column names.

temp_col

Name of the temperature column.

rh_col

Name of the relative humidity column.

rain_col

Name of the rainfall column.

leaf_wetness_col

Name of the leaf wetness column.

statistics

Daily statistics to compute. Use a character vector to apply the same statistics to all weather_cols, such as c("mean", "max"). Use a named list to choose statistics by variable or to provide custom named functions. Use .conditions for multivariable condition summaries.

keep_time

If TRUE, include a daily POSIXct time column at midnight. This requires either time_col or an existing date_col.

name_prefix

Prefix used in aggregated weather columns. The default creates names such as daily_mean_temp and daily_sum_rain.

Value

A daily data frame sorted by ID and date.

Examples

hourly <- simulate_weather_series(days = 5, n_series = 2, id_col = "site_id", seed = 1)

aggregate_weather_daily(
  hourly,
  id_col = "site_id",
  statistics = list(temp = c("mean", "max"), rh = "mean", rain = "sum")
)
#>    site_id       date       time daily_mean_temp daily_max_temp daily_mean_rh
#> 1      S01 2024-01-01 2024-01-01        22.51000          28.83      78.49250
#> 2      S01 2024-01-02 2024-01-02        22.96833          30.32      78.89083
#> 3      S01 2024-01-03 2024-01-03        23.64375          31.27      80.01708
#> 4      S01 2024-01-04 2024-01-04        23.65750          29.58      79.76667
#> 5      S01 2024-01-05 2024-01-05        23.27542          29.56      77.87917
#> 6      S02 2024-01-01 2024-01-01        22.55417          29.42      80.02417
#> 7      S02 2024-01-02 2024-01-02        22.77500          29.74      78.78000
#> 8      S02 2024-01-03 2024-01-03        23.02250          30.12      80.48500
#> 9      S02 2024-01-04 2024-01-04        23.52583          30.77      78.79875
#> 10     S02 2024-01-05 2024-01-05        23.15667          29.59      78.78292
#>    daily_sum_rain
#> 1            3.48
#> 2            1.63
#> 3            3.52
#> 4            1.40
#> 5            3.23
#> 6            3.74
#> 7            1.30
#> 8            4.23
#> 9            8.02
#> 10           3.34