RSS CCMP_RT V2.1 derived surface winds (Level 3.0)

read_ccmp(
  date,
  time.resolution = c("6hourly"),
  xylim = NULL,
  lon180 = FALSE,
  magonly = FALSE,
  dironly = FALSE,
  uonly = FALSE,
  vonly = FALSE,
  nobsonly = FALSE,
  latest = TRUE,
  returnfiles = FALSE,
  ...,
  inputfiles = NULL
)

Arguments

date

date or dates of data to read, see Details

time.resolution

time resolution (6hourly)

xylim

spatial extents to crop from source data, can be anything accepted by extent, see Details

magonly

return just the magnitude from the U and V components

dironly

return just the direction from the U and V, in degrees N=0, E=90, S=180, W=270

uonly

return just the U component of velocity

vonly

return just the V component of velocity components, in degrees (0 north, 90 east, 180 south, 270 west)

latest

if TRUE (and date not supplied) return the latest time available, otherwise the earliest

returnfiles

ignore options and just return the file names and dates

...

passed to brick, primarily for filename

Details

CCMP wind data is read from files managed by ccmp_files. Dates are matched to file names by finding the nearest match in time within a short duration. By default only one time step is returned with both U and V components. Multiple dates can be returned for magnitude or direction, U or V only or N-obs only.

This is the " RSS VAM 6-hour analyses starting from the NCEP GFS wind analyses"

See References.

See also

icefiles for details on the repository of data files, raster for the return value

Examples

## read a single time slice, direction only
x <- read_ccmp(dironly = TRUE)


## get a local extent for a zoom plot and plot the directions [0,360) as an image with arrows
e <- extent(projectExtent(raster(extent(130, 150, -50, -30), crs = "+proj=longlat"), projection(x)))
x <- crop(read_ccmp(), e)
crds <- coordinates(x)
scale <- 0.05
vlen <- function(x) sqrt(x[[1]]^2 + x[[2]]^2)
plot(vlen(crop(x, e)))
x1 <- crds[,1]
y1 <- crds[,2]
x2 <- crds[,1] + values(x[[1]]) * scale
y2 <- crds[,2] + values(x[[2]]) * scale
arrows(x1, y1, x2, y2, length = 0.02)


## faster if we get the file list first
ccfiles <- ccmp_files()
earliest <- read_ccmp(ccfiles$date[1:16], xylim = e, magonly = TRUE, inputfiles = ccfiles)
plot(earliest, col = hcl.colors(64), zlim = c(0, 20))