Calculating wind direction from U and V components of the wind using lapply or ifelse

Question

Averaging scalar wind direction data yields inaccurate values due to the compass headings ranging from 0-360 degrees, so I have converted my list to u and v components from the magnitude and wind direction angles already. In order to back out the proper wind direction, for averaging purposes, I need to develop some sort of apply, ifelse, function for the 3 following scenarios: ``` V > 0...((180 / pi) * atan((Ucomp/Vcomp)) + 180) U and V < 0...((180 / pi) * atan((Ucomp/Vcomp)) + 0) U > 0 and V < 0...((180 / pi) * atan((Ucomp/Vcomp)) + 360) ``` In the data set I am looking to analyze, Ucomp is greater than 0 and Vcomp is less than zero, but there will undoubtedly be scenarios where all 3 will pan out, so I need a function to parse through and calculate iteratively and applying the correct formula for each time step. I have not used lapply or functions before, so me playing around with them has not worked. I provide a sample of data below... ``` DateTime Wind.Spd Wind.Direction Air.Densi…

Accepted Answer

First define the function to do the calculation: ``` windDir <- function(u, v) { if(v > 0) ((180 / pi) * atan(u/v) + 180) if(u < 0 & v < 0) ((180 / pi) * atan(u/v) + 0) if(u > 0 & v < 0) ((180 / pi) * atan(u/v) + 360) } ``` Then apply it to each row. Here I'm using `ddply`, which is a nice "apply" variety for data frames: ``` > library(plyr) > ddply(data, 'DateTime', summarize, windDir=windDir(Ucomp, Vcomp)) DateTime windDir 1 1981 278.0232 2 1982 276.0232 3 1983 280.2760 4 1984 277.1531 5 1985 280.0370 6 1986 279.7517 ```

Calculating wind direction from U and V components of the wind using lapply or ifelse

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