cesm_racmo23_lwsn.py 8.58 KB
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import os
import Ngl
import numpy as np
import numpy.ma as ma

from netCDF4 import Dataset

from livvkit.util import elements as el


describe = """CESM_RACMO23_lwsn plot."""


def make_plot(config=None, out_path='.',
              racmo_path='/lustre/atlas1/cli115/world-shared/4ue/racmo23_GRN_monthly/',
              cism_path='/lustre/atlas1/cli115/world-shared/4ue/',
              cesm_path='/lustre/atlas1/cli115/world-shared/4ue/b.e10.BG20TRCN.f09_g16.002/'):
    # ---------------- Data source in TITAN ------------------------
    f_cism = os.path.join(cism_path, 'Greenland_5km_v1.1_SacksRev_c110629.nc')
    f_cesm_lnd_climo_jja = os.path.join(cesm_path,
                                        'postproc/lnd/climos/b.e10.BG20TRCN.f09_g16.002_JJA_196006_200508_climo.nc')
    f_racmo_lwsn_jja = os.path.join(racmo_path, 'climos/racmo23_GRN_monthly.lwsn.1980-1999.JJA.nc')
    f_racmo_lwsn_jja_remapped = os.path.join(racmo_path,
                                             'remapped_racmo/racmo23_GRN_monthly.lwsn.1980-1999.remap2cesm.JJA.nc')
    f_racmo_mask = os.path.join(racmo_path, 'RACMO23_masks_ZGRN11.nc')

    img_list = []

    # --------------------------------------------------------------
    # f_cism get the following, matrixsize[301,561]
    # usrf(0,:,:), lat(0,:,:), lon(0,:,:)
    #
    # f_cesm_lnd_climo_jja get FSDS (mean downwelling solar flux),FSA (mean net  solar flux, absorbed)
    # FSR (the mean net solar flux, reflected)
    # FSDS(0,:,:), FSA(0,:,:), FSR(0,:,:)

    # Goal: plot 3 figures, radiation overlaying on elevation usrf

    # read f_cism, elevation of 5km CESM
    # adding the [:] transform the variable to type numpy.ndarray
    ncid0 = Dataset(f_cism)
    usrf = ncid0.variables['usrf'][0, :, :]
    lat = ncid0.variables['lat'][0, :, :]
    lon = ncid0.variables['lon'][0, :, :]

    # read f_cesm_lnd_climo_jja, CESM variables
    ncid1 = Dataset(f_cesm_lnd_climo_jja)
    fira = ncid1.variables['FIRA'][0, :, :]
    lat1 = ncid1.variables['lat'][:]
    lon1 = ncid1.variables['lon'][:]

    fira = -1 * fira

    # use gris as a mask to mask fira array
    gris_mask = ncid1.variables['gris_mask'][0, :, :]
    gris_mask = ma.masked_equal(gris_mask, 0)

    fira_mask = ma.masked_array(fira, mask=gris_mask.mask)
    fira = fira_mask

    # read f_racmo_lwsn_jja, RACMO variables
    ncid2 = Dataset(f_racmo_lwsn_jja)
    lwsn = ncid2.variables['lwsn'][0, :, :]
    # lat2 = ncid2.variables['lat'][:]
    # lon2 = ncid2.variables['lon'][:]

    # read f_racmo_mask, the lat/lon for RACMO data
    ncid4 = Dataset(f_racmo_mask)
    lat4 = ncid4.variables['lat'][:]
    lon4 = ncid4.variables['lon'][:]
    racmo_elev = ncid4.variables['Topography'][0, 0, :, :]

    # Use gris as a mask to mask fira array.
    gris_mask = ncid4.variables['GrIS_mask'][:]
    gris_mask = ma.masked_equal(gris_mask, 0)

    lwsn_mask = ma.masked_array(lwsn, mask=gris_mask.mask)
    lwsn = lwsn_mask

    # read f_racmo_lwsn_jja_remapped, the remapped RACMO file to calculate difference
    ncid3 = Dataset(f_racmo_lwsn_jja_remapped)
    remap_lwsn = ncid3.variables['lwsn'][0, :, :]

    diff = fira - remap_lwsn

    # print(np.max(diff))
    # print(np.min(diff))

    # ------- PLOT --------
    #  Open a workstation for drawing the plots
    wkres = Ngl.Resources()
    # wkres.wkColorMap = "matlab_jet"
    wkres.wkColorMap = "BlueWhiteOrangeRed"
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    # wkres.wkOrientation = "portrait"  # "portrait" or "landscape"
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    wks_type = "png"
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    wks_img = str(os.path.join(out_path, "CESM_RACMO23_lwsn_JJA"))
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    wks = Ngl.open_wks(wks_type, wks_img, wkres)

    # --- for the map -------
    # Define plotting area, Greenland
    mres = Ngl.Resources()
    mres.nglDraw = False  # Don't draw individual plots
    mres.nglFrame = False  # Don't advance frame.

    mres.pmTickMarkDisplayMode = "Never"  # Turn off map tickmarks.
    mres.mpGridAndLimbOn = False  # Turn off grid and limb lines.
    mres.mpProjection = "Aitoff"
    mres.mpLimitMode = "LatLon"  # limit map via lat/lon, to zoom in
    mres.mpCenterLatF = 70.  # map area
    mres.mpCenterLonF = -44.
    mres.mpMinLatF = 57.
    mres.mpMaxLatF = 85.
    mres.mpMinLonF = -55.
    mres.mpMaxLonF = -30.
    mres.mpOutlineOn = False
    mres.mpFillOn = False
    mres.mpPerimOn = True  # add box around map

    # --- for the lwsn contour of CESM -------
    res1 = Ngl.Resources()
    res1.nglDraw = False  # Don't draw individual plots
    res1.nglFrame = False  # Don't advance frame.
    res1.cnLineLabelsOn = False
    res1.cnFillOn = True
    res1.cnLinesOn = False
    res1.cnLineLabelsOn = False
    res1.cnFillMode = "RasterFill"
    res1.cnLevelSelectionMode = "ExplicitLevels"
    res1.cnLevels = np.arange(-70, -20, 5)
    res1.lbLabelBarOn = True  # Turn on labelbar.
    res1.lbLabelFontHeightF = 0.04
    # res1.pmLabelBarOrthogonalPosF = -0.05

    res1.sfXArray = lon1
    res1.sfYArray = lat1

    # --- for the lwsn contour of RACMO -------
    res2 = Ngl.Resources()
    res2.nglDraw = False  # Don't draw individual plots
    res2.nglFrame = False  # Don't advance frame.
    res2.cnLineLabelsOn = False
    res2.cnFillOn = True
    res2.cnLinesOn = False
    res2.cnLineLabelsOn = False
    res2.cnFillMode = "RasterFill"
    res2.cnLevelSelectionMode = "ExplicitLevels"
    res2.cnLevels = np.arange(-70, -20, 5)
    res2.lbLabelBarOn = True  # Turn on labelbar.
    res2.lbOrientation = "Vertical"  # Verticle labelbar
    # res2.pmLabelBarHeightF    = 0.5         # Change height of labelbar
    # res2.pmLabelBarWidthF     = 0.2           # Change width of labelbar
    # res2.pmLabelBarOrthogonalPosF = -0.02      # Move labelbar closer to plot
    res2.lbLabelFontHeightF = 0.04  # Make fonts smaller.

    res2.sfXArray = lon4
    res2.sfYArray = lat4

    # --- for the lwsn contour of CESM-RACMO -------
    res3 = Ngl.Resources()
    res3.nglDraw = False  # Don't draw individual plots
    res3.nglFrame = False  # Don't advance frame.
    res3.cnLineLabelsOn = False
    res3.cnFillOn = True
    res3.cnLinesOn = False
    res3.cnLineLabelsOn = False
    res3.cnFillMode = "RasterFill"
    res3.cnLevelSelectionMode = "ExplicitLevels"
    res3.cnLevels = np.arange(-30, 40, 10)
    res3.lbLabelBarOn = True  # Turn on labelbar.
    res3.lbOrientation = "Vertical"  # Verticle labelbar
    res3.lbLabelFontHeightF = 0.04  # Make fonts smaller.

    res3.sfXArray = lon1
    res3.sfYArray = lat1

    # ---- for the elevation -------
    sres = Ngl.Resources()
    sres.nglDraw = False  # Don't draw individual plots
    sres.nglFrame = False  # Don't advance frame.
    sres.cnFillOn = False
    sres.cnLinesOn = True
    sres.cnLineLabelsOn = False
    sres.cnLevelSelectionMode = "ExplicitLevels"
    sres.cnLevels = [0, 1000, 2000, 3000]
    sres.sfXArray = lon
    sres.sfYArray = lat

    # ---- for the elevation of RACMO -------
    sres1 = Ngl.Resources()
    sres1.nglDraw = False  # Don't draw individual plots
    sres1.nglFrame = False  # Don't advance frame.
    sres1.cnFillOn = False
    sres1.cnLinesOn = True
    sres1.cnLineLabelsOn = False
    sres1.cnLevelSelectionMode = "ExplicitLevels"
    sres1.cnLevels = [0, 1000, 2000, 3000]
    sres1.sfXArray = lon4
    sres1.sfYArray = lat4

    # ---- Overlay plots, each one has its own ID
    # overlay ice on base map, and then overlay elevation on ice
    # usrf is elevation of 5km CESM, racmo_elev is elevation of RACMO
    usrf_plot1 = Ngl.contour(wks, usrf, sres)
    usrf_plot2 = Ngl.contour(wks, racmo_elev, sres1)
    usrf_plot3 = Ngl.contour(wks, usrf, sres)

    fira_plot = Ngl.contour(wks, fira, res1)
    lwsn_plot = Ngl.contour(wks, lwsn, res2)
    diff_plot = Ngl.contour(wks, diff, res3)

    # Creat multiple figures and draw, which now contains the elevation and radiation
    # "[1,3]" indicates 1 row, 3 columns.
    map_title = ["CESM, LW~B3~net", "RACMO, LW~B3~net", "CESM-RACMO, LW~B3~net"]

    nmap = 3
    plot = []
    for i in range(nmap):
        mres.tiMainString = map_title[i]
        plot.append(Ngl.map(wks, mres))

    # Overlay everything on the map plot.
    Ngl.overlay(plot[0], fira_plot)
    Ngl.overlay(plot[0], usrf_plot1)

    Ngl.overlay(plot[1], lwsn_plot)
    Ngl.overlay(plot[1], usrf_plot2)

    Ngl.overlay(plot[2], diff_plot)
    Ngl.overlay(plot[2], usrf_plot3)

    Ngl.panel(wks, plot, [1, nmap])

    img_link = os.path.join(os.path.basename(out_path),
                            os.path.basename(wks_img + '.' + wks_type))
    img_elem = el.image('CESM_RACMO23_lwsn',
                        ' '.join(describe.split()),
                        img_link)
    if config:
        img_elem['Height'] = config['image_height']
    img_list.append(img_elem)

    return img_list


if __name__ == '__main__':
    make_plot()