79 lines
3.7 KiB
Python
79 lines
3.7 KiB
Python
def get_data_woa2009(variables):
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# get_data_woa2009(variables) ############################################################
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# written by : Gabriel Wolf, g.a.wolf@reading.ac.uk
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# adapted from get_woa2009_data.m of Remi Tailleux
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# last modified : 13.09.2018
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# Content/Description ####################################################################
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# Loading data from the 2009 version of the Levitus World Ocean Atlas
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# References:
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# - for temperature: Locarnini, R. A., A. V. Mishonov, J. I. Antonov, T. P. Boyer, H. E.
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# Garcia, O. K. Baranova, M. M. Zweng, and D. R. Johnson, 2010: World
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# Ocean Atlas 2009, Volume 1: Temperature. S. Levitus, Ed. NOAA Atlas
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# NESDIS 68, 184 pp.
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# -> PDF : https://www.nodc.noaa.gov/OC5/indpub.html#woa09
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# - for salinity : Antonov, J. I., D. Seidov, T. P. Boyer, R. A. Locarnini, A. V.
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# Mishonov, H. E. Garcia, O. K. Baranova, M. M. Zweng, and D. R.
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# Johnson, 2010: World Ocean Atlas 2009, Volume 2: Salinity. S. Levitus,
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# Ed. NOAA Atlas NESDIS 69, 184 pp.
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# -> PDF : https://www.nodc.noaa.gov/OC5/indpub.html#woa09
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# #######################################################################################
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print 'Use of get_data_woa2009 in get_data.py'
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dir_data = '/glusterfs/inspect/users/xg911182/data/WOA2009/'
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grid_names = ('lon','lat','depth','time',)
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# import modules
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import numpy as np
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from netCDF4 import Dataset # to read netcdf files
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from mydata_classes import Grid
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# Allocation
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data = {}
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grd = []
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list_allkeys = variables.keys()
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# Read grid information (for all variables identical)
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print 'Check if all WOA data is using the same grid'
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if 'grd' in list_allkeys:
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fn = dir_data + 'temperature_annual_1deg.nc'
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nc_fid = Dataset(fn,'r')
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LON = np.array(nc_fid.variables[grid_names[0]])
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LAT = np.array(nc_fid.variables[grid_names[1]])
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Z = np.array(nc_fid.variables[grid_names[2]])
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TIME = nc_fid.variables[grid_names[3]]
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Ulon = nc_fid.variables[grid_names[0]].units
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Ulat = nc_fid.variables[grid_names[1]].units
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Uz = nc_fid.variables[grid_names[2]].units
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Ut = nc_fid.variables[grid_names[3]].units
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grd = Grid(LON,LAT,Z,TIME,len(LON),len(LAT),len(Z),len(TIME), Ulon, Ulat, Uz, Ut)
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# Read temperature data
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if 'temp' or 'theta' in list_allkeys:
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print 'Load temperature data'
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fn = dir_data + 'temperature_annual_1deg.nc'
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nc_fid = Dataset(fn,'r')
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# read temperature data
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DATA_d = nc_fid.variables['t_an']
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if 'temp' in list_allkeys:
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varname = 'temp'
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data[varname] = {}
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data[varname]['val'] = np.array(DATA_d)
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data[varname]['units'] = DATA_d.units
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data[varname]['fill_value'] = DATA_d._FillValue
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if 'theta' in list_allkeys:
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print 'MISSING: Calculate pot. temp. from temperature data'
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# read salinity data
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if 's' in list_allkeys:
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print 'Load salinity data'
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fn = dir_data + 'salinity_annual_1deg.nc'
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nc_fid = Dataset(fn,'r')
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# read salinity data
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DATA_d = nc_fid.variables['s_an']
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varname = 's'
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data[varname] = {}
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data[varname]['val'] = np.array(DATA_d)
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data[varname]['units'] = DATA_d.units
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data[varname]['fill_value'] = DATA_d._FillValue
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# return data
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if 'grd' in list_allkeys:
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return grd, data
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else:
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return data
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