generate_TmaxTmin: Generate maximum and minimum daily temperature from daily...

In wxgenR: A Stochastic Weather Generator with Seasonality

Generate maximum and minimum daily temperature from daily average temperature

Description

Estimate maximum and minimum temperature from 'wx' simulation results of daily average temperature. This function uses quantile mapping to develop a relationship between daily average temperature and daily maximum temperature. Average and maximum temperature can be contained in your training data for example. Then, the relationship between average and maximum temperature is applied to the simulated daily average temperature output by 'wx' to estimate a simulated daily maximum temperature. Daily minimum temperature is then estimated using the standard equation Tavg = 0.5(Tmax + Tmin).

Quantile mapping is trained and applied separately by calendar month. The quantile mapping function comes from the 'qmap' R package, specifically using empirical quantiles.

You will likely need to post-process the 'wx' function output in order to process each simulation trace since the 'wx' output is in wide format by trace and this function is best applied in long format. Code examples for processing both the training data and simulated data to put into suitable format for the 'generate_TmaxTmin' function are available here:

https://github.com/dwoodson-usbr/wxgenR/tree/master/vignettes

Usage

generate_TmaxTmin(df.train, df.sim)

Arguments

df.train	A dataframe containing the daily training data used to develop the relationship between average and maximum temperature. At a minimum should contain variables named 'tmax', 'temp', and 'month' which represent maximum temperature, average temperature, and numeric month in which the daily observation exists, respectively.
df.sim	A dataframe containing the daily simulation results from the 'wx' function in long format. At a minimum should contain variables named 'sim_temp' and 'month' which respectively represent the simulated daily average temperature from 'wx' and the numeric month in which each data point resides.

Value

Returns a list containing results and metadata from the multisite shuffling in 'long' format for easy analysis and visualization.

• df.sim - Dataframe containing simulated maximum and minimum temperature generated from daily average temperature.

• qmap.monthly - List of dataframes containing fitted quantile mapping models for each calendar month.

References

Gudmundsson L (2025). qmap: Statistical transformations for post-processing climate model output. R package version 1.0-6.

Gudmundsson L, Bremnes JB, Haugen JE, Engen-Skaugen T (2012). “Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations - a comparison of methods.” Hydrology and Earth System Sciences, 16(9), 3383–3390. doi:10.5194/hess-16-3383-2012.

Examples

# Example with toy data
df.train = data.frame(
  temp = runif(10, 50, 70),
  tmax = runif(10, 60, 80),
  month = rep(1:2, each = 5)
)

df.sim = data.frame(
  sim_temp = runif(10, 50, 70),
  month = rep(1:2, each = 5)
)

result = generate_TmaxTmin(df.train, df.sim)
head(result$df.sim)

wxgenR documentation built on April 15, 2025, 1:10 a.m.