Commit 41e46aed authored by Pierre Cazenave's avatar Pierre Cazenave

Helper function to do the interpolation of the regularly gridded POLCOMS-ERSEM...

Helper function to do the interpolation of the regularly gridded POLCOMS-ERSEM daily mean model output onto the FVCOM vertical grid
parent 0666a463
function dataz = grid_vert_interp(Mobj, lon, lat, data, depth, mask)
% Child function to interpolate a given 3D array (x by y by sigma) values
% to the unstructured grid vertical layers.
% versions of otherwise constant variables (temperature and salinity only
% for the time being).
% function grid_vert_interp(Mobj, lon, lat, data, depth, mask)
% Interpolate the regularly gridded data described by lon, lat, data
% (whose size should be x by y for the lon and lat arrays, and x by y by
% z for the data array) to the unstructured grid vertical layers defined
% in Mobj.siglayz. The closest unstructured grid node is used for the
% vertical interpolation of each regularly gridded node.
% Mobj = MATLAB mesh structure which must contain:
% - Mobj.siglayz - sigma layer depths for all model
% nodes.
% - Mobj.lon, - node coordinates (long/lat).
% lon, lat = Rectangular arrays of longitude and latitude (see
% meshgrid).
% data, depth = x by y by z (where z is vertical layers) grids of the
% data and water depths to be interpolated onto the vertical grid defined
% by Mobj.siglayz.
% mesh = logical array of positions outside the regularly gridded
% domain (e.g. if the regular data contains NaNs or other undefined
% values, create a logical array of those positions so they can be
% omitted quickly).
% x by y by z array of vertically interpolated values at each regular
% grid location.
% grid_vert_interp(Mobj, lon, lat, data, depth, mask)
% Author(s):
% Pierre Cazenave (Plymouth Marine Laboratory)
% Revision history
% 2013-02-08 First version.
subname = 'grid_vert_interp';
global ftbverbose
if ftbverbose
fprintf(['begin : ' subname '\n'])
if ~isfield(Mobj, 'siglayz')
error('Error: missing required sigma layer depth values for the unstructured grid.')
if ~Mobj.have_lonlat
error('Need spherical coordinates')
if sum(size(lon) ~= size(data(:, :, 1))) ~= 0 || sum(size(lat) ~= size(data(:, :, 1))) ~= 0
error('Size of the longitude or latitude arrays do not match the supplied data array')
[~, fz] = size(Mobj.siglayz);
[nx, ny, ~, ~] = size(data);
% Preallocate the output arrays
dataz = nan(nx, ny, fz);
for xi = 1:nx
% Get all the y and z dimension data for the current x position
% (temperature, salinity and depth). N.B. The POLCOMS data is stored y,
% x, z, t (first two dimensions the wrong way around).
xdata = squeeze(data(xi, :, :));
xdepth = squeeze(depth(xi, :, :));
xmask = mask(xi, :);
% Preallocate the arrays for the inner loop
ydata = nan(ny, fz);
for yi = 1:ny
if xmask(yi)
% Find the nearest sigma layer z values from the unstructured grid.
[md, mi] = min(sqrt((Mobj.lon - lon(xi, yi)).^2 + ( - lat(xi, yi)).^2));
% Skip data point if the closest FVCOM node is more than 10 minutes
% away.
if md > 10 / 60
% if ftbverbose
% fprintf('%s : skipping %f, %f (more than 10 minutes from the nearest unstructured grid node),\n', subname, lon(yi, xi), lat(yi, xi))
% end
% Use the FVCOM node's sigma depths to interpolate this POLCOMS
% position's temperature and salinity data.
% Get the FVCOM depths closest to this POLCOMS grid position.
tfz = Mobj.siglayz(mi, :);
% Now get the POLCOMS depth at this node for the time index
% identified above.
tpz = xdepth(yi, :);
ydata(yi, :) = interp1(tpz, xdata(yi, :), tfz, 'linear', 'extrap');
dataz(xi, :, :) = ydata;
% Tidy up the namespace a bit.
clear ytemp ysalt tfz tpz md mi xtemp xsalt xdepth xi yi zi
if ftbverbose
fprintf(['end : ' subname '\n'])
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