Multiple-Linear-Regression-Correction

In aws.wrfsmn: Data Processing of SMN Hi-Res Weather Forecast from 'AWS'

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

First the package should be loaded:

library(aws.wrfsmn)

The example data to use will be 'eva' and should be call it with data:

data(eva)

head(eva)

A Multiple Linear Regression is made between the predictand (observed evaporation) and the following predictors:

test.predictors <- c('OUT_PREC',
                     'OUT_EVAP',
                     'OUT_RUNOFF',
                     'OUT_BASEFLOW',
                     'OUT_SOIL_MOIST_lyr_1',
                     'OUT_EVAP_CANOP',
                     'OUT_SURF_TEMP')

Using multiple.guidance function to obtain the regression coefficients:

mg <- multiple.guidance(input.data = eva, predictand = 'evapo_obs', predictors = test.predictors)
mg

The evaluation of the correction applied from the mg regression is:

evaluation.eva <- mg.evaluation(input.data = eva, predictand = 'evapo_obs', predictors = test.predictors, var.model = 'OUT_EVAP', lmodel = mg)

head(evaluation.eva)

Finally, the monthly data is calculated to be plot:

ploting(daily2monthly(evaluation.eva[[1]]))

aws.wrfsmn documentation built on Aug. 8, 2025, 6:13 p.m.