Alistair Adcroft adcroft
adcroft
/ calc_total_TKE.py
Last active
August 29, 2015 13:57
Diagnose total TKE input to internal tide mixing parameterization in MOM6
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| import netCDF4 | |
| import numpy | |
| tkeFile = netCDF4.Dataset('/archive/bls/tikal_mom6_2014.01.17/MOM6z_SIS_025_enstro_newTides/gfdl.ncrc2-intel-prod/history/unpack/19000101.ocean_annual.nc') | |
| TKEi = numpy.ma.array( tkeFile.variables['TKE_itidal'][0], dtype='float64') | |
| TKEf = numpy.ma.array( tkeFile.variables['TKE_tidal'][0], dtype='float64') | |
| staticFile = netCDF4.Dataset('/net2/aja/OWG/ocean_static.nc') | |
| area = numpy.ma.array( staticFile.variables['area_t'][:], dtype='float64') | |
| depth = numpy.ma.array( staticFile.variables['depth_ocean'][:], dtype='float64') |
adcroft
/ demo_plot_MOM6_SST.py
Last active
August 29, 2015 13:57
An example interactive python session to plot SST from MOM6 post-processed files, using just matplotlib and netCDF4
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| # Import necessary modules | |
| import netCDF4 | |
| import matplotlib.pyplot as plt | |
| tFiles = netCDF4.MFDataset('/archive/bls/tikal_201406_mom6_2014.07.01/OM4_SIS_baseline/gfdl.ncrc2-intel-prod/pp/ocean_monthly/ts/monthly/10yr/ocean_monthly.*.temp.nc') | |
| print tFiles | |
| tType = tFiles.variables['temp'] | |
| print tType | |
| print tType.shape |
adcroft
/ demo_zonal_average_T_difference.py
Created
March 31, 2014 16:00
An example of a zonal average plot of potential temperature difference between two runs.
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| import netCDF4 | |
| import numpy | |
| import matplotlib | |
| import matplotlib.pyplot as plt | |
| area = netCDF4.Dataset('/net2/aja/OWG/ocean_static.nc').variables['area_t'][:] | |
| lat = netCDF4.Dataset('/net2/aja/OWG/ocean_static.nc').variables['geolat_c'][:] | |
| T1 = netCDF4.Dataset('/archive/bls/tikal_mom6_2014.01.17/MOM6z_SIS_025_enstro_iTides_1TW/gfdl.ncrc2-intel-prod/pp/ocean_annual/av/annual_20yr/ocean_annual.1900-1919.ann.nc').variables['temp'][0,:] | |
| T2 = netCDF4.Dataset('/archive/bls/tikal_mom6_2014.01.17/MOM6z_SIS_025_enstro_rev5channels/gfdl.ncrc2-intel-prod/pp/ocean_annual/av/annual_20yr/ocean_annual.1900-1919.ann.nc').variables['temp'][0,:] | |
| zInterface = netCDF4.Dataset('/archive/bls/tikal_mom6_2014.01.17/MOM6z_SIS_025_enstro_iTides_1TW/gfdl.ncrc2-intel-prod/pp/ocean_annual/av/annual_20yr/ocean_annual.1900-1919.ann.nc').variables['e'][0,:] |
adcroft
/ plot_zonal_average_T_anomaly.py
Last active
August 29, 2015 13:57
An example of plotting the zonal average T anomaly w.r.t. WOA2005 climatology
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| import netCDF4 | |
| import numpy | |
| import matplotlib | |
| import matplotlib.pyplot as plt | |
| [ny,nx] = netCDF4.Dataset('/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked/ocean_topog.nc').variables['depth'].shape | |
| area = netCDF4.Dataset('/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked/ocean_hgrid.nc').variables['area'][:].reshape(ny,2,nx,2).sum(axis=-1).sum(axis=1) | |
| lat = netCDF4.Dataset('/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked/ocean_hgrid.nc').variables['y'][1::2,1::2] | |
| annualFile = '/archive/bls/tikal_201406_mom6_2014.07.01/OM4_SIS_baseline/gfdl.ncrc2-intel-prod/pp/ocean_annual/av/annual_5yr/ocean_annual.1900-1904.ann.nc' |
adcroft
/ plot_tidal_amplitudes.py
Created
April 1, 2014 12:30
Plots versions of tidal amplitude file
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| import netCDF4 | |
| import numpy | |
| import m6plot | |
| lon = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['x'][::2,::2] | |
| lat = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['y'][::2,::2] | |
| area = netCDF4.Dataset('/net2/aja/OWG/ocean_static.nc').variables['area_t'][:] | |
| U26 = netCDF4.Dataset('/net2/aja/MOM6.workdir/MOM6/tools/python/tideamp/tidal_amplitude.v20140326.nc').variables['tideamp'][:] | |
| U28 = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/INPUT/tidal_amplitude.v20140328.nc').variables['tideamp'][:] |
adcroft
/ demo_yz_section.py
Created
April 15, 2014 20:55
An example of minimal y-z section of temperature at a given longitude.
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| import netCDF4 | |
| import numpy | |
| import matplotlib.pyplot as plt | |
| rootDir = '/archive/bls/tikal_201403_mom6_2014.04.03/MOM6z_SIS_025_PPMh4/gfdl.ncrc2-intel-prod/' | |
| # Read nominal longitudes (to find the section) | |
| xh = netCDF4.Dataset(rootDir+'history/unpack/19300101.ocean_annual.nc').variables['xh'][:] | |
| # Find the index of longitude=-30.0 | |
| iSect = numpy.abs(xh + 30.0).argmin() |
adcroft
/ demo_ssh_blue_marble.py
Last active
August 29, 2015 14:00
Demo of SSH using a basemap projection and "blue marble" image for land
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| import netCDF4 | |
| import matplotlib.pyplot as plt | |
| import numpy | |
| from mpl_toolkits.basemap import Basemap | |
| lon = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['x'][::2,::2] | |
| lat = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['y'][::2,::2] | |
| ssh = netCDF4.Dataset('/archive/aja/awg/tikal_201403/MOM6z_SIS_025_c192L48_am4a1_2000climo_bergs/gfdl.ncrc2-intel-prod-openmp/history/unpack/00040301.ocean_daily.nc').variables['ssh'][1] |
adcroft
/ demo_animate_ssh_blue_marble.py
Last active
August 29, 2015 14:00
Animated SSH on blue marble
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| import netCDF4 | |
| import matplotlib.pyplot as plt | |
| import numpy | |
| from mpl_toolkits.basemap import Basemap | |
| lon = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['x'][::2,::2] | |
| lat = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['y'][::2,::2] | |
| dailyFiles = '/archive/aja/awg/tikal_201403/CM4_c192L48_am4a1_2000/gfdl.ncrc2-intel-prod-openmp/history/unpack/000[3456]0101.ocean_daily.nc' | |
| ssh = netCDF4.MFDataset(dailyFiles).variables['ssh'] |
adcroft
/ demo_animate_relative_vortcitiy.py
Last active
August 29, 2015 14:00
Animate surface relative vorticity on blue marble earth
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| import netCDF4 | |
| import matplotlib.pyplot as plt | |
| import numpy | |
| from mpl_toolkits.basemap import Basemap | |
| import math | |
| lon = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['x'][1::2,1::2] | |
| lat = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['y'][1::2,1::2] | |
| dx = netCDF4.Dataset('/archive/gold/datasets/MOM6z_SIS_025/siena/mosaic.unpacked/ocean_hgrid.nc').variables['dx'][:] | |
| dx = dx[1::2,1::2]+numpy.roll(dx,-1,axis=-1)[1::2,1::2] |
adcroft
/ dens_write_eos.py
Created
May 12, 2014 15:07
Density of sea-water using Wright et al. 1997, equation of state
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| def dens_wright_eos(T, S, p): | |
| """ | |
| Equation of state for sea water given by Wright, 1997, J. Atmos. Ocean. Tech., 14, 735-740. | |
| Units: T[degC],S[PSU],p[Pa] | |
| Returns density [kg m-3] | |
| """ | |
| a0 = 7.057924e-4; a1 = 3.480336e-7; a2 = -1.112733e-7 | |
| b0 = 5.790749e8; b1 = 3.516535e6; b2 = -4.002714e4; b3 = 2.084372e2; b4 = 5.944068e5; b5 = -9.643486e3 | |
| c0 = 1.704853e5; c1 = 7.904722e2; c2 = -7.984422; c3 = 5.140652e-2; c4 = -2.302158e2; c5 = -3.079464 |
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