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| bool | TLM_vs_NLM.saveFigs = True |
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| string | TLM_vs_NLM.date = '20181004' |
| |
| string | TLM_vs_NLM.time = '000000' |
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| list | TLM_vs_NLM.fields_geos = ['ua','va','t','delp','q','qi','ql','o3mr'] |
| |
| list | TLM_vs_NLM.fields_gfs = ['ua','va','T','Ps','sphum','ice_wat','liq_wat','o3mr'] |
| |
| list | TLM_vs_NLM.kind_gfs = ['fv_core','fv_core','fv_core','fv_core','fv_tracer','fv_tracer','fv_tracer','fv_tracer'] |
| |
| | TLM_vs_NLM.nm = len(fields_geos) |
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| string | TLM_vs_NLM.nl_type = 'geos' |
| |
| string | TLM_vs_NLM.nl1 = '../INPUTS/GEOS_c180/H21/GEOS.traj.c180.eta.'+date+'_'+time[0:4]+'z.nc4' |
| |
| string | TLM_vs_NLM.nl2 = '../INPUTS/GEOS_c180/H15/GEOS.traj.c180.eta.'+date+'_'+time[0:4]+'z.nc4' |
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| string | TLM_vs_NLM.tlm_type = 'gfs' |
| |
| string | TLM_vs_NLM.tlm = date+'.'+time+'.linearforecast.final.KIND.res.tileXX.nc' |
| |
| | TLM_vs_NLM.tmp = re.sub("XX", str(1), nl1) |
| |
| | TLM_vs_NLM.fh_nl1 = Dataset(tmp, mode='r') |
| |
| string | TLM_vs_NLM.nl_xid = 'xaxis_1' |
| |
| string | TLM_vs_NLM.nl_yid = 'yaxis_1' |
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| string | TLM_vs_NLM.nl_zid = 'zaxis_1' |
| |
| | TLM_vs_NLM.im = len(fh_nl1.dimensions[nl_xid]) |
| |
| | TLM_vs_NLM.jm = len(fh_nl1.dimensions[nl_yid]) |
| |
| | TLM_vs_NLM.lm = len(fh_nl1.dimensions[nl_zid]) |
| |
| int | TLM_vs_NLM.jm_gfs = jm/6 |
| |
| | TLM_vs_NLM.x_nlm = np.zeros(im*jm*lm*nm).reshape(nm,lm,jm,im) |
| |
| | TLM_vs_NLM.x_tlm = np.zeros(im*jm*lm*nm).reshape(nm,lm,jm,im) |
| |
| list | TLM_vs_NLM.fields = fields_gfs |
| |
| | TLM_vs_NLM.fh_nl2 = Dataset(nl2, mode='r') |
| |
| | TLM_vs_NLM.filetile1 = re.sub("XX", str(tile+1), tlm) |
| |
| | TLM_vs_NLM.filetile = re.sub("KIND", kind_gfs[i], filetile1) |
| |
| | TLM_vs_NLM.fh_tlm = Dataset(filetile, mode = 'r') |
| |
| int | TLM_vs_NLM.js = tile*jm_gfs |
| |
| tuple | TLM_vs_NLM.je = (tile+1)*jm_gfs |
| |
| | TLM_vs_NLM.f |
| |
| | TLM_vs_NLM.ax |
| |
| | TLM_vs_NLM.figsize |
| |
| | TLM_vs_NLM.corr_tlm = np.zeros(lm*nm).reshape(nm,lm) |
| |
| | TLM_vs_NLM.c1 = np.corrcoef(np.reshape(x_tlm[i,j,:,:],(im*jm,)),np.reshape(x_nlm[i,j,:,:],(im*jm,))) |
| |
| int | TLM_vs_NLM.rangeup1 = 0 |
| |
| int | TLM_vs_NLM.rangeup2 = 0 |
| |
| | TLM_vs_NLM.color |
| |
1.8.14