Tools for ROMS model output.

Description

Facilities for easy access to Regional Ocean Modeling System (ROMS) output.

Details

Antarctica simple coastline.

Description

Taken from "rnaturalearth::countries110"

Create SpatialPoints.

Description

Convenience wrapper around SpatialPoints for a two layer brick with longitude and latitude coordinate arrays.

Usage

coords_points(x, ...)

Arguments

Value

SpatialPoints

Examples

## library(raadtools)
##coords_points(romscoords(cpolarfiles()$fullname[1]))

pts <- coords_points(ice_coords)

Crop a ROMS layer

Description

Crop a ROMS data layer from romsdata with a raster extent.

Usage

croproms(x, ext, ...)

Arguments

Details

The spatial crop is performed in the coordinate space of roms data.

Examples

## notice that extent is in long-lat, but ice_local is in the grid
## space of ice_coords
ice_local <- croproms(ice_coords, extent(100, 120, -75, -60))
plot(ice_coords[[2]], col = grey(seq(0, 1, length  = 20)))
plot(crop(ice_fake, ice_local), add = TRUE)

Fake model data.

Description

ice_coords and ice_fake are generated from a projected map of southern Ocean sea ice data.

Details

The coords layer is the longitude and latitude values for the centres of the polar cells. This is veyr loosely analogous to the coordinate arrays used by ROMS data, included here for working examples, illustration and code tests.

The proper metadata for these layers is "-3950000, 3950000, -3950000, 4350000 (xmin, xmax, ymin, ymax)"

"+proj=stere +lat_0=-90 +lat_ts=-70 +lon_0=0 +k=1 +x_0=0 +y_0=0 +a=6378273 +b=6356889.449 +units=m +no_defs"

Read the variable as is

Description

Read the variable as is

Usage

rawdata(x, varname)

Arguments

Boundary polygon from raster of coordinates.

Description

Create a boundary polygon by tracking around coordinates stored in a RasterStack.

Usage

romsboundary(cds)

Arguments

Details

The first layer in the stack is treated as the X coordinate, second as Y.

Examples

ice_grid_boundary <- romsboundary(ice_coords)
plot(antarctica)
## does not make sense in this space
plot(ice_grid_boundary, add = TRUE, border = "grey")

## ok in this one
#library(rgdal)
#   proj4string(ice_grid_boundary) <- CRS("+init=epsg:4326")
# pweird <- "+proj=laea +lon_0=147 +lat_0=-42 +ellps=WGS84"
#  laea_world <- spTransform(antarctica, pweird)
#  plot(extent(laea_world) + 8e6, type = "n", asp = 1)
#  plot(laea_world, add = TRUE)
#  plot(spTransform(ice_grid_boundary, pweird), add  = TRUE, border = "darkgrey")

Extract coordinate arrays from ROMS.

Description

Returns a RasterStack of the given variable names.

Usage

romscoords(x, spatial = c("lon_u", "lat_u"), ncdf = TRUE,
  transpose = FALSE, ...)

Arguments

Details

The two layers from the model output are used to define the real-world space. This is used to create a boundary romsboundary, to map real-world objects into grid space romscoords and to generate graticules for mapping into the grid space with graphics::contour.

Value

RasterStack with two layers of the 2D-variables

Examples

## Not run: 
  coord <- romscoord("roms.nc")

## End(Not run)
## with in-built fake data
plot(ice_fake, asp = 0.5)
contour(ice_coords[[1]], add = TRUE, levels = seq(-165, 165, by = 15))
contour(ice_coords[[2]], add = TRUE)

ROMS single slice 2D layer Extract a data layer from ROMS by name and 4-D slice.

Description

romsdata always works in the first two dimensions (x-y), the more specialist functions will work in the space indicated by their name roms_xy, roms_xt and so on.

Usage

roms_xy(x, varname, slice = c(1L, 1L), transpose = TRUE, ...)

roms_xz(x, varname, slice = c(1L, 1L), transpose = TRUE, ...)

roms_xt(x, varname, slice = c(1L, 1L), transpose = TRUE, ...)

roms_yz(x, varname, slice = c(1L, 1L), transpose = TRUE, ...)

roms_yt(x, varname, slice = c(1L, 1L), transpose = TRUE, ...)

roms_zt(x, varname, slice = c(1L, 1L), transpose = TRUE, ...)

romsdata(x, varname, slice = c(1L, 1L), ncdf = TRUE, transpose = TRUE,
  ...)

Arguments

Value

RasterLayer

Examples

#x <- raadtools:::cpolarfiles()$fullname[1]
#plot(roms_xy(x, "u"))
#plot(roms_xz(x, "u", slice = c(392L,1L)), asp = NA)
#plot(roms_xt(x, "u", slice = c(392L,1L)), asp = NA)

#plot(roms_yz(x, "u"))
#plot(roms_yt(x, "u", slice = c(1L,1L)), asp = NA)
#plot(roms_zt(x, "u", slice = c(1L, 392L)), asp = NA)

Coordinates at depth

Description

Extract the multi-layer 'h'eight grid with S-coordinate stretching applied

Usage

romshcoords(x, S = "Cs_r", depth = "h")

Arguments

Details

S and h are the names of the appropriate variables

Value

RasterStack with a layer for every depth

Remap an object to the ROMS grid.

Description

Find the nearest-neighbour coordinates of x in the coordinate arrays of coords.

Usage

romsmap(x, ...)

## S3 method for class 'SpatialPolygonsDataFrame'
romsmap(x, coords, crop = FALSE,
  lonlat = TRUE, ...)

## S3 method for class 'SpatialLinesDataFrame'
romsmap(x, coords, crop = FALSE,
  lonlat = TRUE, ...)

## S3 method for class 'SpatialPointsDataFrame'
romsmap(x, coords, crop = FALSE,
  lonlat = TRUE, ...)

Arguments

Details

The input coords is a assumed to be a 2-layer RasterStack or RasterBrick and using nabor::knn the nearest matching position of the coordinates of x is found in the grid space of coords. The motivating use-case is the curvilinear longitude and latitude arrays of ROMS model output.

No account is made for the details of a ROMS cell, though this may be included in future. We tested only with the "lon_u" and "lat_u" arrays.

Value

input object with coordinates transformed to space of the coords

Note

Do not use this for extraction purposes without checking the output, this is best used for exploration and visualization. Re-mapping ROMS data is better done by looking up the coords_points within spatial objects, and transferring via the grid index.

Examples

ant_ice_coords <- romsmap(antarctica, ice_coords)
plot(ice_fake, main = "sea ice in pure grid space")
plot(ant_ice_coords, add = TRUE)