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Adding a new example analysis script.
- EddyKineticEnergy.py calculates the surface eddy kinetic energy annual mean - Required adding a logarithmic color plot option to 6plot.xyplot - Serves as an example analysis script that can be called inside the refineDiag script to be done annually - Motivated by the plot in http://www.gfdl.noaa.gov/cms-filesystem-action/user_files/kd/pdf/c37_dixon_th85b.pdf - Unaware of the scientific value, just an example.
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#!/usr/bin/env python | ||
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import netCDF4 | ||
import matplotlib.pyplot as plt | ||
import numpy | ||
import m6plot | ||
import math | ||
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try: import argparse | ||
except: raise Exception('This version of python is not new enough. python 2.7 or newer is required.') | ||
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parser = argparse.ArgumentParser(description='''Script for plotting annual-average SST bias.''') | ||
parser.add_argument('annual_file', type=str, help='''Annually-averaged file contained 3D temp.''') | ||
parser.add_argument('-l','--label', type=str, default='', help='''Label to add to the plot.''') | ||
parser.add_argument('-o','--outdir', type=str, default='.', help='''Directory in which to place plots.''') | ||
parser.add_argument('-g','--gridspec', type=str, | ||
default='/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked', | ||
help='''Directory containing mosaic/grid-spec files (ocean_hgrid.nc and ocean_mask.nc).''') | ||
cmdLineArgs = parser.parse_args() | ||
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rootGroup = netCDF4.Dataset( cmdLineArgs.annual_file ) | ||
if 'ssu' not in rootGroup.variables: raise Exception('Could not find "ssu" in file "%s"'%(cmdLineArgs.annual_file)) | ||
if 'ssv' not in rootGroup.variables: raise Exception('Could not find "ssv" in file "%s"'%(cmdLineArgs.annual_file)) | ||
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x = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][::2,::2] | ||
y = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][::2,::2] | ||
msk = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_mask.nc').variables['mask'][:] | ||
area = msk*netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) | ||
msk = numpy.ma.array(msk, mask=(msk==0)) | ||
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#Tobs = netCDF4.Dataset( '/archive/gold/datasets/MOM6z_SIS_025/siena/obs/WOA05_ptemp_salt_annual_v1.nc' ).variables['temp'][1] | ||
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ssu = rootGroup.variables['ssu'] | ||
ssu_mean = ssu[:].mean(axis=0) | ||
ssv = rootGroup.variables['ssv'] | ||
ssv_mean = ssv[:].mean(axis=0) | ||
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eke = ((ssu[:] - ssu_mean)**2 + (ssv[:] - ssv_mean)**2)/2 | ||
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eke_mean = 10000 * eke[:].mean(axis=0) | ||
#eke_mean = numpy.log10(eke_mean[:]) | ||
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ci=m6plot.pmCI(0.0,0.5,0.1) | ||
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m6plot.xyplot( eke_mean , x, y, area=area, | ||
suptitle=rootGroup.title+' '+cmdLineArgs.label, title='Eddy Kinetic Energy annual mean [(cm/s)^2]', | ||
clim=ci, logscale=True, | ||
save=cmdLineArgs.outdir+'/EKE_mean.png') | ||
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#m6plot.xycompare( temp, Tobs , x, y, area=area, | ||
# suptitle=rootGroup.title+' '+cmdLineArgs.label, | ||
# title1='SST [$\degree$C]', | ||
# title2='WOA\'05 SST [$\degree$C]', | ||
# clim=m6plot.linCI(-2,29,.5), colormap='dunneRainbow', extend='max', | ||
# dlim=ci, dcolormap='dunnePM', dextend='both', centerDCB=True, | ||
# save=cmdLineArgs.outdir+'/SST_bias_WOA05.3_panel.png') |
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