Description Usage Arguments Value
Run Daily Weather Simulation
1 2 3 4 5 6 | wgen_daily(obs_day, n_year, start_month = 10, start_water_year = 2000,
include_leap_days = FALSE, n_knn_annual = 100, dry_wet_threshold = 0.3,
wet_extreme_quantile_threshold = 0.8, adjust_annual_precip = TRUE,
annual_precip_adjust_limits = c(0.9, 1.1), dry_spell_changes = 1,
wet_spell_changes = 1, prcp_mean_changes = 1, prcp_cv_changes = 1,
temp_mean_changes = 0)
|
obs_day |
daily historical observation dataset as |
n_year |
number of simulation years |
start_month |
initial month of the water year |
start_water_year |
initial water year of simulation |
include_leap_days |
include leap days in simulation time series |
n_knn_annual |
number of years used in knn sampling algorithm |
dry_wet_threshold |
threshold precipitation amount for dry/wet states |
wet_extreme_quantile_threshold |
threshold quantile for wet/extreme states |
adjust_annual_precip |
flag to adjust simulated daily precip to match simulated annual precip |
annual_precip_adjust_limits |
range of maximum annual precip adjustment factors |
dry_spell_changes |
adjustment factor(s) for dry spell durations (single value, or vector of length 12 for monthly) |
wet_spell_changes |
adjustment factor(s) for wet spell durations (single value, or vector of length 12 for monthly) |
prcp_mean_changes |
adjustment factor(s) for mean precip (single value, or vector of length 12 for monthly) |
prcp_cv_changes |
adjustment factor(s) for precip CV (single value, or vector of length 12 for monthly) |
temp_mean_changes |
adjustment factor(s) for mean temp (single value, or vector of length 12 for monthly) |
a named list containing:
|
the historical observation dataset used to train the simulation |
|
monthly precipitation thresholds for defining Markov states based on the historical dataset |
|
monthly transition matrices based on the historical dataset |
|
monthly state equilibria probabilities |
|
a data frame of the simulated daily weather |
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