model_racmo23_t2m_djf.py 8.28 KB
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# coding=utf-8

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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


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describe = """
Average of the 2-meter air temperature (°C) over Greenland for every winter 
(December-January-Feburary; DJF)  from 1980--1999 for CESM (left) and RACMO 2.3 (middle), and the 
difference between them (right; CESM - RACMO 2.3). The black solid lines denote 
the 0, 1000, 2000, and 3000 meter Greenland ice sheet elevation contours as seen
by the models (CESM's contours shown in the difference plot). 
"""
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title = "Winter 2-meter air temperature"

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def make_plot(config, out_path='.'):
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    # ---------------- Data source in TITAN ------------------------
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    f_cism = os.path.join(config['cism_data'], 'Greenland_5km_v1.1_SacksRev_c110629.nc')
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    f_model_lnd_climo_djf = os.path.join(config['model_lnd_climos'], 'b.e10.BG20TRCN.f09_g16.002_DJF_climo.nc')
    f_model_atm_climo_djf = os.path.join(config['model_atm_climos'], 'b.e10.BG20TRCN.f09_g16.002_DJF_climo.nc')
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    f_racmo_t2m_djf = os.path.join(config['racmo_data'], 'racmo23_GRN_monthly.t2m.1980-1999.DJF.nc')
    f_racmo_t2m_djf_remapped = os.path.join(config['racmo_data'],
                                            'racmo23_GRN_monthly.t2m.1980-1999.remap2cesm.DJF.nc')
    f_racmo_mask = os.path.join(config['racmo_data'], 'RACMO23_masks_ZGRN11.nc')
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    # --------------------------------------------------------------

    img_list = []

    # read f_cism, the elevation data
    ncid0 = Dataset(f_cism)
    usrf = ncid0.variables['usrf'][0, :, :]
    lat = ncid0.variables['lat'][0, :, :]
    lon = ncid0.variables['lon'][0, :, :]

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    # read f_model_atm_climo_djf and file2, CESM variable
    ncid1 = Dataset(f_model_atm_climo_djf)
    w_model = ncid1.variables['TREFHT'][0, :, :]
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    lat1 = ncid1.variables['lat'][:]
    lon1 = ncid1.variables['lon'][:]

    # --- original RACMO data without remapping [312,306]
    ncid2 = Dataset(f_racmo_t2m_djf)
    w_racmo_l = ncid2.variables['t2m'][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, :, :]

    # RACMO data after remapping [192,288]
    ncid22 = Dataset(f_racmo_t2m_djf_remapped)
    w_racmo = ncid22.variables['t2m'][0, :, :]
    lat22 = ncid22.variables['lat'][:]
    lon22 = ncid22.variables['lon'][:]

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    w_model = w_model - 273.15  # convert to celcius
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    w_racmo = w_racmo - 273.15
    w_racmo_l = w_racmo_l - 273.15
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    diff = w_model - w_racmo
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    # locate the greenland area using the GreenLand mask
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    ncid8 = Dataset(f_model_lnd_climo_djf)
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    gris_mask = ncid8.variables['gris_mask'][0, :, :]
    gris_mask = ma.masked_equal(gris_mask, 0)

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    # mask out non RACMO regions, icemask var in f_model_lnd_climo_djf
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    diff_mask = ma.masked_array(diff, mask=gris_mask.mask)

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

    # ------- PLOT --------
    # Open a workstation for drawing the plots
    wkres = Ngl.Resources()
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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_t2m_DJF"))
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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 CESM contour -------
    res1 = Ngl.Resources()
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    res1.cnFillPalette = "WhiteBlue"
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    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.trGridType = "TriangularMesh"
    res1.cnLevelSelectionMode = "ExplicitLevels"
    res1.cnLevels = np.arange(-44, 12, 4)
    res1.lbLabelBarOn = True  # Turn on labelbar.
    res1.lbLabelFontHeightF = 0.04

    res1.sfXArray = lon1
    res1.sfYArray = lat1

    # --- for the RACMO contour -------
    res2 = Ngl.Resources()
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    res2.cnFillPalette = "WhiteBlue"
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    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.trGridType = "TriangularMesh"
    res2.cnLevelSelectionMode = "ExplicitLevels"
    res2.cnLevels = np.arange(-44, 12, 4)
    res2.lbLabelBarOn = True  # Turn on labelbar.
    res2.lbOrientation = "Vertical"  # Verticle labelbar
    res2.lbLabelFontHeightF = 0.04  # Make fonts smaller.

    res2.sfXArray = lon4
    res2.sfYArray = lat4

    # --- for the diff=CESM-Remapped_RACMO contour -------
    res22 = Ngl.Resources()
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    res22.cnFillPalette = "BlueWhiteOrangeRed"
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    res22.nglDraw = False  # Don't draw individual plots
    res22.nglFrame = False  # Don't advance frame.
    res22.cnLineLabelsOn = False
    res22.cnFillOn = True
    res22.cnLinesOn = False
    res22.cnLineLabelsOn = False
    res22.cnFillMode = "RasterFill"
    res22.trGridType = "TriangularMesh"
    res22.cnLevelSelectionMode = "ExplicitLevels"
    res22.cnLevels = np.arange(-12, 12, 2)
    res22.lbLabelBarOn = True  # Turn on labelbar.
    res22.lbOrientation = "Vertical"  # Verticle labelbar
    res22.lbLabelFontHeightF = 0.04  # Make fonts smaller.

    res22.sfXArray = lon22
    res22.sfYArray = lat22

    # ---- 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_plot1 = Ngl.contour(wks, usrf, sres)
    usrf_plot2 = Ngl.contour(wks, racmo_elev, sres1)
    usrf_plot3 = Ngl.contour(wks, usrf, sres)

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    t2mw_plot = Ngl.contour(wks, w_model, res1)
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    t2ms_l_plot = Ngl.contour(wks, w_racmo_l, res2)
    diff_plot = Ngl.contour(wks, diff_mask, res22)
    # diff_plot = Ngl.contour(wks,w_racmo,res2)  #Remapped RACMO

    # Creat multiple figures and draw, which now contains the elevation and temperature
    # "[1,3]" indicates 1 row, 3 columns.
    map_title = ["CESM T(~S1~o C )", "RACMO T(~S1~o C )", "CESM-RACMO T(~S1~o C )"]

    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], t2mw_plot)
    Ngl.overlay(plot[0], usrf_plot1)
    Ngl.overlay(plot[1], t2ms_l_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))
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    img_elem = el.image(title,
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                        ' '.join(describe.split()),
                        img_link)
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    img_elem['Height'] = config['image_height']
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    img_list.append(img_elem)

    return img_list