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% |
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% $Id: average_ML.m,v 1.3 2006/02/11 05:15:28 edhill Exp $ |
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% |
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% Ed Hill |
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% |
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% Generate the APE ML01--ML07 and ME01--ME07 fields: |
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% |
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% For all facets: |
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% For all time steps: |
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% For all variables: |
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% Create a mask based on THETA == 0.0 |
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% For all variables: |
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% compute partial sum wrt mask |
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% compute number contributing wrt mask |
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% Compute the averages from the partial sums & num contrib |
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% Write netCDF output for this facet: |
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% |
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|
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%====================================================================== |
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|
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ML_files |
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|
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vars = { ... |
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{'u','UVEL','masku'} ... |
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{'v','VVEL','maskv'} ... |
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{'w','WVEL','mask'} ... |
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{'phi','PHIHYD','mask'} ... |
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{'q','SALT','mask'} ... |
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{'rh','RELHUM','mask'} ... |
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{'th','THETA','mask'} ... |
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}; |
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|
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%====================================================================== |
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% |
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% Interpolate to the reference pressure levels and then compute the |
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% derived fields and the temporal sums of all fields on the original |
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% MITgcm grid |
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% |
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disp('Computing Sums') |
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|
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itile = 1; |
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for itile = 1:6 |
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|
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it0 = 0; |
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for iv = 1:length(vars) |
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eval(sprintf('clear %s', vars{iv}{1} )); |
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end |
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|
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fi = 1; |
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for fi = [ 1:length(files) ] |
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|
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fib = 0; |
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|
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fname = sprintf(files{fi}{1},itile); |
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disp([ ' fname = "' fname '"' ]); |
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nc = netcdf(fname, 'nowrite'); |
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times = nc{'T'}(:); |
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|
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it = 1; |
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for it = 1:length(times) |
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|
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for iv = 1:length(vars) |
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eval(sprintf('%s = squeeze(nc{ ''%s'' }(it,:,:,:));', ... |
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vars{iv}{1},vars{iv}{2})); |
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eval(sprintf('mr = max(abs(%s(:)));', vars{iv}{1})); |
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if mr > 1e10 |
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% error('values heading out of range!!!'); |
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fib = 1; |
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end |
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end |
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|
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mask = double(th ~= 0.0); |
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masku = ones(size(th) + [0 0 1]); |
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masku(:,:,1:(end-1)) = masku(:,:,1:(end-1)) .* mask; |
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masku(:,:,2:end ) = masku(:,:,2:end ) .* mask; |
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maskv = ones(size(th) + [0 1 0]); |
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maskv(:,1:(end-1),:) = maskv(:,1:(end-1),:) .* mask; |
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maskv(:,2:end, :) = maskv(:,2:end, :) .* mask; |
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|
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if it0 == 0 |
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it0 = 1; |
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for iv = 1:length(vars) |
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eval(sprintf('%s_ave = zeros(size(%s));', ... |
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vars{iv}{1},vars{iv}{1})); |
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end |
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mask_sum = zeros(size(mask)); |
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masku_sum = zeros(size(masku)); |
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maskv_sum = zeros(size(maskv)); |
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end |
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for iv = 1:length(vars) |
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eval(sprintf('%s_ave = %s_ave + (%s .* %s);', ... |
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vars{iv}{1}, vars{iv}{1}, ... |
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vars{iv}{3}, vars{iv}{1})); |
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end |
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mask_sum = mask_sum + mask; |
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masku_sum = masku_sum + masku; |
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maskv_sum = maskv_sum + maskv; |
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|
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end |
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|
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if fib == 1 |
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disp([ 'BAD :: "' fname '"' ]); |
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end |
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|
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nc = close(nc); |
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|
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end |
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|
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for iv = 1:length(vars) |
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eval(sprintf('%s_ave = %s_ave ./ %s_sum;', ... |
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vars{iv}{1}, vars{iv}{1}, vars{iv}{3} )); |
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end |
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|
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nc = netcdf(sprintf('ML_ave_%d.nc',itile), 'clobber'); |
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|
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nc('T') = 0; |
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nc('Z') = 17; |
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nc('X') = 32; nc('Xp1') = 33; |
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nc('Y') = 32; nc('Yp1') = 33; |
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|
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for iv = 1:length(vars) |
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switch vars{iv}{3} |
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case 'mask' |
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nc{ vars{iv}{2} } = ncdouble( 'T', 'Z', 'Y', 'X' ); |
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case 'masku' |
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nc{ vars{iv}{2} } = ncdouble( 'T', 'Z', 'Y', 'Xp1' ); |
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case 'maskv' |
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nc{ vars{iv}{2} } = ncdouble( 'T', 'Z', 'Yp1', 'X' ); |
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end |
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eval(sprintf('nc{ vars{iv}{2} }(1,:,:,:) = %s_ave;',vars{iv}{1})); |
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end |
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nc{ 'mask_sum' } = ncdouble( 'T', 'Z', 'Y', 'X' ); |
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nc{ 'mask_sum' }(1,:,:,:) = mask_sum; |
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nc{ 'masku_sum' } = ncdouble( 'T', 'Z', 'Y', 'Xp1' ); |
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nc{ 'masku_sum' }(1,:,:,:) = masku_sum; |
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nc{ 'maskv_sum' } = ncdouble( 'T', 'Z', 'Yp1', 'X' ); |
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nc{ 'maskv_sum' }(1,:,:,:) = maskv_sum; |
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nc = close(nc); |
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|
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end |
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