Remove CESM2 table from energy extension

energy/energy/rad_aavg_cesm2.py

-import os
-# import numpy as np
-import numpy.ma as ma
-
-from netCDF4 import Dataset
-
-
-def calculate_area_weighted_averages(cesm_path='/lustre/atlas1/cli115/world-shared/4ue/B_1PAL/'):
-    f_cesm_lnd_climo_jja = os.path.join(cesm_path, 'postproc/lnd/climos/B_1PAL_JJA_climo.nc')
-    f_cesm_lnd_climo_ann = os.path.join(cesm_path, 'postproc/lnd/climos/B_1PAL_ANN_climo.nc')
-
-    # f_cesm_lnd_climo_jja get FLDS (mean downwelling longwave rad),FIRA (mean net IR longwave rad, absorbed)
-    # FLDS(0,:,:), FIRA(0,:,:)
-    # Matrix gris_area(Greenland ice area) has values 0 and none
-
-    # Goal: print out area-weighted average of
-    #   SW_d(268),
-    #   SW_net(61),
-    #   LW_d(235),
-    #   LW_net(-46),
-    #   R_net(15),
-    #   SHF(7),
-    #   LHF(-8),
-    # NOTE: these variables have size[192,288]
-    #   FSDS: atmospheric incident solar radiation
-    #   FSA: absorbed solar radiation
-    #   FLDS: atmospheric longwave radiation
-    #   FIRA: net infrared (longwave) radiation
-    #   FIRE: emitted infrared (longwave) radiation
-    #   FSH: sensible heat
-    #   QSOIL: ground evaporation over ice landunits
-
-    # ---read input_files
-    ncid1 = Dataset(f_cesm_lnd_climo_jja, mode='r')
-    ncid3 = Dataset(f_cesm_lnd_climo_ann, mode='r')
-
-    fsds = ncid1.variables['FSDS'][0, :, :]
-    fsa = ncid1.variables['FSA'][0, :, :]
-    flds = ncid1.variables['FLDS'][0, :, :]
-    fira = ncid1.variables['FIRA'][0, :, :]
-    fsh = ncid1.variables['FSH'][0, :, :]
-    qsoil = ncid1.variables['QSOIL'][0, :, :]
-    rain = ncid3.variables['RAIN'][0, :, :]
-    snow = ncid3.variables['SNOW'][0, :, :]
-    qrunoff = ncid3.variables['QRUNOFF'][0, :, :]
-    # t2m = ncid11.variables['TREFHT'][0,:,:]
-    t2m = ncid1.variables['TSA'][0, :, :]
-
-    # CESM2
-    gris_mask = ncid1.variables['gris_mask'][:, :]
-
-    sw_d = fsds
-    sw_net = fsa
-    lw_d = flds
-    lw_net = -1.0 * fira
-    r_net = fsa - fira
-    shf = -1.0 * fsh
-    lhf = -1.0 * 2.835e6 * qsoil
-    # smb = QICE * 3.1567e7
-    smb = rain + snow - qrunoff - qsoil * 3.1567e7
-    t2m_c = t2m - 273.15
-
-    # ---grid cell area on Greenland. For other regions, the value is 9.999e35.
-    area = ncid1.variables['area'][:]
-
-    ncid1.close()
-    ncid3.close()
-
-    # Option I: use greenland mask to mask the area where the ice sheet fraction is zero
-    #     Note: some non-greenland region has non-zero ice sheet fraction.
-    gris_mask = ma.masked_equal(gris_mask, 0)
-    area_maskice = ma.masked_array(area, mask=gris_mask.mask)
-
-    # Option II: use icesheet fraction mask to mask the area where the ice sheet fraction is zero
-    # ices_mask = ma.masked_equal(ices,0)
-    # area_maskice = ma.masked_array(area, mask=ices_mask.mask)
-
-    # Option III: first multiply area with ices, then use greenland mask to mask the area where the ice sheet
-    #             fraction is zero
-    #       NOTE: this option get the closest results to the Table 1 in the paper.
-    # areaices = np.multiply(area, ices)
-    # gris_mask = ma.masked_equal(gris_mask, 0)
-    # area_maskice = ma.masked_array(areaices, mask=gris_mask.mask)
-
-    aavgs = {
-             'Sw_d': (ma.average(sw_d, weights=area_maskice)),
-             'Sw_net': (ma.average(sw_net, weights=area_maskice)),
-             'Lw_d': (ma.average(lw_d, weights=area_maskice)),
-             'Lw_net': (ma.average(lw_net, weights=area_maskice)),
-             'Rnet': (ma.average(r_net, weights=area_maskice)),
-             'shf': (ma.average(shf, weights=area_maskice)),
-             'lhf': (ma.average(lhf, weights=area_maskice)),
-             'smb': (ma.average(smb, weights=area_maskice)),
-             't2c': (ma.average(t2m_c, weights=area_maskice)),
-             }
-
-    return aavgs
-
-
-if __name__ == '__main__':
-    racmo_aavgs = calculate_area_weighted_averages()
-    for var, net in racmo_aavgs.items():
-        print('RACMO {}: {}'.format(var, net))

energy/energy_cesm.py

@@ -51,7 +51,6 @@ with fn.temp_sys_path(os.path.dirname(__file__)):
     import energy.cesm_racmo23_t2m_ann as t2m_ann
     import energy.cesm_racmo23_t2m_djf as t2m_djf
     import energy.cesm_racmo23_t2m_jja as t2m_jja
-    import energy.rad_aavg_cesm2 as cesm2_rad
     import energy.rad_aavg_model as cesm_rad
     import energy.rad_aavg_racmo as racmo_rad
     import energy.timeseries_trefht as ts_trefht
@@ -77,15 +76,12 @@ def run(name, config):
 
     element_list = []
     cesm_aavg = cesm_rad.calculate_area_weighted_averages()
-    cesm2_aavg = cesm2_rad.calculate_area_weighted_averages()
     racmo_aavg = racmo_rad.calculate_area_weighted_averages()
 
     cesm_aavg_title = """Area weighted averages of CESM's energy balance variables."""
-    cesm2_aavg_title = """Area weighted averages of CESM2's energy balance variables."""
     racmo_aavg_title = """Area weighted averages of RACMO's energy balance variables."""
 
     element_list.append(el.vtable(cesm_aavg_title, cesm_aavg.keys(), cesm_aavg))
-    element_list.append(el.vtable(cesm2_aavg_title, cesm2_aavg.keys(), cesm2_aavg))
     element_list.append(el.vtable(racmo_aavg_title, racmo_aavg.keys(), racmo_aavg))
 
     # PLOTS