RegionGrids.jl

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Unstructured Grids for Data Extraction ​

There are also RegionGrid types without an actual grid, maybe there are a set of coordinates and geometries that define the corners or the centres of a mesh, such as:

Basically, for each of these datasets, the data is given in such a way that the coordinates of the grid can be expressed via:

  • A Vector of Point2 types, with each Point2 type containing (lon,lat)
julia
using GeoRegions
using RegionGrids
using CairoMakie

Creating Unstructured Grids ​

A Unstructured Grid can be created as follows:

ggrd = RegionGrid(geo,Point2.(lon,lat))

where geo is a GeoRegion of interest that is found within the domain defined by the longitude and latitude grid vectors.

julia
lon = collect(10:20:360); nlon = length(lon)
lat = collect(-80:20:90); nlat = length(lat)

glon = zeros(nlon,nlat); glon .= lon;  glon = glon[:]
glat = zeros(nlon,nlat); glat .= lat'; glat = glat[:]

plon = glon .+ 14rand(nlon*nlat) .- 7
plat = glat .+ 14rand(nlon*nlat) .- 7

geo = GeoRegion([10,100,-80,10],[50,10,-40,50])

iggrd = RegionGrid(geo,Point2.(glon,glat))
pggrd = RegionGrid(geo,Point2.(plon,plat))
The VectorMask Grid type has the following properties:
    Indices             (ipoint) : [51, 70, 71, 72, 73, 74, 75, 89, 90, 91, 92, 93, 94, 108, 109, 110]
    Longitude Points       (lon) : [-73.77791981848617, -56.935678198618064, -35.65020155832315, -16.40735918219866, 9.796008030811326, 34.71431766979874, 48.00688551954834, -30.092138437940093, -3.4753868996899655, 8.406297959567416, 32.30763283618734, 52.226290013433314, 68.14205158455948, -8.17917768734469, 15.084602148364837, 29.347909554580326]
    Latitude Points        (lat) : [-36.130946628631435, -19.05825358692594, -13.278007038207098, -16.932994914090678, -5.726761952704724, 6.898844542284953, 3.8803770612262625, -6.08658296962939, -5.288787380439857, 15.157694505652255, 13.863055663676352, 21.409432966629357, 15.426830046054672, 20.88112359699238, 37.756847233489836, 34.386369360944556]
    Rotated X Coordinates    (X)
    Rotated Y Coordinates    (Y)
    Rotation (°)             (θ) : 0.0
    RegionGrid Weights (weights)
    RegionGrid Size 			  : (16,) points

The API for creating a Unstructured Grid can be found here

What is in a Unstructured Grid? ​

RegionGrids.UnstructuredGrid Type
julia
UnstructuredGrid <: RegionGrid

A UnstructuredGrid is a RegionGrid that is created based on an unstructured grid often used in cubed-sphere or unstructured-mesh grids.

All UnstructuredGrid type will contain the following fields:

  • lon - A Vector of Floats, defining the longitudes for each point in the RegionGrid that describe the region.

  • lat - A Vector of Floats, defining the latitude for each point in the RegionGrid that describe the region.

  • ipoint - A Vector of Ints, defining the indices of the valid points from the original unstructured grid that were extracted into the RegionGrid.

  • weights - A Vector of Floats, defining the latitude-weights of each valid point in the grid. Will be NaN if outside the bounds of the GeoRegion used to define this RectilinearGrid.

  • X - A Vector of Floats, defining the X-coordinates (in meters) of each point in the "derotated" RegionGrid about the centroid for the shape of the GeoRegion.

  • Y - A Vector of Floats, defining the Y-coordinates (in meters) of each point in the "derotated" RegionGrid about the centroid for the shape of the GeoRegion.

  • θ - A Float storing the information on the angle (in degrees) about which the data was rotated in the anti-clockwise direction. Mathematically, it is rotation - geo.θ.

source

We see that in a UnstructuredGrid type, we have the lon and lat vectors that defined the longitude and latitude points that are within the GeoRegion.

@example
ggrd.lon
@example
ggrd.lat

An example of using Unstructured Grids ​

Say we have some sample data, here randomly generated.

julia
data = rand(nlon,nlat)[:]
162-element Vector{Float64}:
 0.9457759119324752
 0.1518450296836532
 0.8848205114529575
 0.7611622983588391
 0.1324997596879074
 0.49753679501673065
 0.5254648932992327
 0.6930924114377638
 0.03941107355510687
 0.24611440839810406
 ⋮
 0.6127362166551712
 0.403170351642994
 0.20613773203763297
 0.5843149057953531
 0.6675419110248055
 0.200981273333655
 0.4652938616522969
 0.16424651525609069
 0.5632079382532902

We extract the valid data within the GeoRegion of interest that we defined above:

julia
ndata = extract(data,iggrd)
pdata = extract(data,pggrd)
16-element Vector{Float64}:
 0.3094304723775425
 0.4899831710273427
 0.049615059744586465
 0.30981189086819416
 0.4775625939578432
 0.3595670117751075
 0.7626980372458837
 0.03274982213044719
 0.9943711636684206
 0.7101732729748955
 0.09414220864561118
 0.7236528788202466
 0.3649091073380065
 0.8049559425661069
 0.06173091573212974
 0.8465393145953215

And now let us visualize the results.

julia
slon,slat = coordinates(geo) # extract the coordinates
fig = Figure()

ax1 = Axis(
    fig[1,1],width=450,height=150,
    limits=(-180,360,-90,90)
)
scatter!(ax1,glon,glat,color=:lightgrey)
scatter!(ax1,plon,plat,color=data)
lines!(ax1,slon,slat,color=:black,linewidth=2)
lines!(ax1,slon.+360,slat,color=:black,linewidth=2,linestyle=:dash)

hidexdecorations!(ax1,ticks=false,grid=false)

ax2 = Axis(
    fig[2,1],width=450,height=150,
    limits=(-180,360,-90,90)
)
scatter!(ax2,iggrd.lon,iggrd.lat,color=:lightgrey)
scatter!(ax2,pggrd.lon,pggrd.lat,color=pdata)
lines!(ax2,slon,slat,color=:black,linewidth=2)

Label(fig[3,:],"Longitude / º")
Label(fig[:,0],"Latitude / º",rotation=pi/2)

resize_to_layout!(fig)
fig