(This article was first published on

**long time ago...**, and kindly contributed to R-bloggers)Hi all!

A researcher asked me last week about how to compute wind average for an area using rWind. I wrote a simple function to do this using dplyr library (following the advice of my friend Javier Fajardo). The function will be added to rWind package as soon as possible. Meanwhile, you can test the results… enjoy!

` # First, charge the new function `

library(dplyr)

wind.region <- function (X){

X[,3] <- X[,3] %% 360

X[X[,3]>=180,3] <- X[X[,3]>=180,3] - 360

avg<-summarise_all(X[,-1], .funs = mean)

wind_region <- cbind(X[1,1],avg)

return(wind_region)

}

Once you have charged the function, let’s do some example

` # Get some wind data and convert it into a raster to be plotted later `

library(rWind)

library(raster)

wind_data<-wind.dl(2015,2,12,0,-10,5,35,45)

wind_fitted_data <- wind.fit(wind_data)

r_speed <- wind2raster(wind_fitted_data, type="speed")

Now, you can use the new function to obtain wind average in the study area:

` myMean <- wind.region(wind_data) `

myMean

` # Now, you can use wind.fit to get wind speed and direction. `

myMean_fitted <- wind.fit(myMean)

myMean_fitted

` # Finally, let's plot the results! `

library(rworldmap)

library(shape)

plot(r_speed)

lines(getMap(resolution = "low"), lwd=4)

alpha <- arrowDir(myMean_fitted)

Arrowhead(myMean_fitted$lon, myMean_fitted$lat, angle=alpha,

arr.length = 2, arr.type="curved")

text(myMean_fitted$lon+1, myMean_fitted$lat+1,

paste(round(myMean_fitted$speed,2), "m/s"), cex = 2)

To

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