Exemplo n.º 1
0
def S1_surface_distribution_different_times():
    """
    Surface distributions at different times to see that distribution comes to an equilibrium
    """

    #load data at several times
    fname = 'SubSurf_y2000_m1_d5_simdays3650_layer0_pos'  #File names, apart from the label of initial grid
    tload = range(0, 730, 73) + [
        729
    ]  #Times when data is loaded (indices, not actual times)
    SurfaceData = ParticleData.from_nc(datadir + 'Layer0/',
                                       fname,
                                       tload=tload,
                                       Ngrids=40)  #Load data

    #for the figure
    fig = plt.figure(figsize=(14, 21))
    gs1 = gridspec.GridSpec(6, 2)
    gs1.update(wspace=0.01, hspace=0.0)

    for i in range(len(tload)):

        #get distribution at specific time
        d = SurfaceData.get_distribution(i, 2.)  #Compute distribution
        d = oceanvector(
            d, ddeg=2.)  #Create oceanvector object from it for plotting
        lon_bins_2d, lat_bins_2d = np.meshgrid(d.Lons_edges, d.Lats_edges)

        #for the plot
        plt.subplot(gs1[i])
        m = Basemap(projection='robin', lon_0=180, resolution='l')
        m.drawparallels([-60, -30, 0, 30, 60],
                        labels=[True, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawmeridians([50, 150, 250, 350],
                        labels=[False, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawcoastlines()
        m.fillcontinents(color='dimgrey')
        xs, ys = m(lon_bins_2d, lat_bins_2d)

        #plot distribution
        plt.pcolormesh(xs,
                       ys,
                       d.V2d,
                       cmap='plasma',
                       norm=colors.LogNorm(),
                       rasterized=True)
        cbar = plt.colorbar(orientation='vertical', shrink=0.5)
        cbar.ax.tick_params(labelsize=7, width=0.03)
        plt.title('Year ' + str(int(round(tload[i] * 5 / 365., 0))), size=10)

    fig.savefig(outdir_paper + 'S1_distribution_surface_in_time.pdf',
                dpi=900,
                bbox_inches='tight')
Exemplo n.º 2
0
    def create_transport_matrix(so_lat=-60, na_lat=65):
        n_matrix = {
        }  #Matrix with entries n_{ij} in paper as a list for each layer

        ddeg = 2.  #Choice of binning, required for the region labels. ddeg=2 has no influence here on the result as we are perfectly on the region boundaries

        for j in range(len(folders_all)):

            if subfolders_all[j] == 'Sim3D':
                pdata = ParticleData.from_nc(folders_all[j] + '/',
                                             filenames_all[j],
                                             tload=[0, 121],
                                             Ngrids=12)
            else:
                pdata = ParticleData.from_nc(folders_all[j] + '/',
                                             filenames_all[j],
                                             tload=[0, -1],
                                             Ngrids=40)

            pdata.remove_nans()  #Remove some Nans

            #Give the particles labels according to the basin they are in at different times
            initial_region = pdata.set_region_labels(ddeg,
                                                     0,
                                                     so_lat=so_lat,
                                                     na_lat=na_lat)
            final_region = pdata.set_region_labels(ddeg,
                                                   -1,
                                                   so_lat=so_lat,
                                                   na_lat=na_lat)

            n = np.zeros((8, 8))  #n-matrix for the specific layer

            for i in range(len(initial_region)):
                n[int(initial_region[i]), int(final_region[i])] += 1

            n_matrix[models_all[j]] = n

        np.save(
            outdir_paper + 'n_matrix_solat_' + str(so_lat) + '_na_lat_' +
            str(na_lat), n_matrix)
Exemplo n.º 3
0
def FIG1_surface_distribution():

    pdir = '/Users/wichmann/Simulations/Proj1_SubSurface_Mixing/Layer0/'  #Data directory
    filename = 'SubSurf_y2000_m1_d5_simdays3650_layer0_pos'

    #load particle data and get distribution
    pdata = ParticleData.from_nc(pdir, filename, tload=[0, -1], Ngrids=40)
    d_full = pdata.get_distribution(t=-1, ddeg=2.).flatten()
    d = oceanvector(d_full, ddeg=2.)
    lon_bins_2d, lat_bins_2d = np.meshgrid(d.Lons_edges, d.Lats_edges)

    #plot figure
    fig = plt.figure(figsize=(12, 8))
    m = Basemap(projection='robin', lon_0=180, resolution='l')
    m.drawparallels([-60, -30, 0, 30, 60],
                    labels=[True, False, False, True],
                    linewidth=1.2,
                    size=10)
    m.drawmeridians([50, 150, 250, 350],
                    labels=[False, False, False, True],
                    linewidth=1.2,
                    size=10)
    m.drawcoastlines(linewidth=0.4)
    m.fillcontinents(color='dimgrey')
    xs, ys = m(lon_bins_2d, lat_bins_2d)
    plt.pcolormesh(xs,
                   ys,
                   d.V2d,
                   cmap='plasma',
                   norm=colors.LogNorm(),
                   rasterized=True)
    cbar = plt.colorbar(orientation='vertical', shrink=0.5)
    cbar.ax.tick_params(labelsize=10, width=0.05)
    cbar.set_label('Particles per bin', size=10)
    fig.savefig(outdir_paper + 'F1_surface_distribution.pdf',
                dpi=900,
                bbox_inches='tight')
Exemplo n.º 4
0
def S4_basintransport_other():

    filenames = [
        'SubSurf_y2000_m1_d5_simdays3650_layer2_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer4_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer7_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer10_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer13_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer19_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer22_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer23_pos'
    ]
    folders = [
        'Layer2', 'Layer4', 'Layer7', 'Layer10', 'Layer13', 'Layer19',
        'Layer22', 'Layer23'
    ]
    folders = [
        '/Users/wichmann/Simulations/Proj1_SubSurface_Mixing/' + f
        for f in folders
    ]
    labels = [
        'a) z = ' + str(nemo_depth[2]) + ' m',
        'b) z = ' + str(nemo_depth[4]) + ' m',
        'c) z = ' + str(nemo_depth[7]) + ' m',
        'd) z = ' + str(nemo_depth[10]) + ' m',
        'e) z = ' + str(nemo_depth[13]) + ' m',
        'f) z = ' + str(nemo_depth[19]) + ' m',
        'g) z = ' + str(nemo_depth[22]) + ' m',
        'h) z = ' + str(nemo_depth[23]) + ' m'
    ]  #figure titles

    #for the figure
    fig = plt.figure(figsize=(14, 18))
    gs1 = gridspec.GridSpec(5, 2)
    gs1.update(wspace=0.1, hspace=0.)

    #get region names and constrain to the subtropical basins
    _, region_names = regions(2.)
    region_names = region_names[0:5]
    basin_regions = [1, 2, 3, 4, 5]

    for j in range(len(folders)):

        #load particle data
        filename = filenames[j]
        pdata = ParticleData.from_nc(folders[j] + '/',
                                     filename,
                                     tload=[0, -1],
                                     Ngrids=40)
        pdata.remove_nans()
        region_label = pdata.set_region_labels(2., -1)

        #select the particles in the basins, and label the particles according to their final basin
        selection = [
            k for k in range(len(region_label))
            if region_label[k] in basin_regions
        ]
        lons = pdata.lons[selection]
        lats = pdata.lats[selection]
        region_label = [
            region_label[i] for i in range(len(region_label))
            if region_label[i] in basin_regions
        ]

        #plot
        plt.subplot(gs1[j])
        m = Basemap(projection='robin', lon_0=180, resolution='l')
        m.drawcoastlines()
        m.drawmapboundary(fill_color='lightgray')
        m.drawparallels([-60, -30, 0, 30, 60],
                        labels=[True, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawmeridians([50, 150, 250, 350],
                        labels=[False, False, False, True],
                        linewidth=.8,
                        size=7)
        m.fillcontinents(color='dimgray')
        xs, ys = m(lons[:, 0], lats[:, 0])
        cmap = plt.get_cmap('jet', 5)
        scat = m.scatter(xs,
                         ys,
                         marker='.',
                         s=1,
                         c=region_label,
                         cmap=cmap,
                         rasterized=True)
        plt.title(labels[j], size=10, y=1.0)

    #color bar on the right
    fig.subplots_adjust(right=0.8)
    cbar_ax = fig.add_axes([0.822, 0.43, 0.015, 0.3])
    cbar = fig.colorbar(scat, cax=cbar_ax, ticks=[1, 2, 3, 4, 5])
    cbar.ax.tick_params(labelsize=10)
    tick_locs = 1 + 0.4 * np.array([1, 3, 5, 7, 9])
    cbar.set_ticks(tick_locs)
    cbar.set_ticklabels(region_names)

    #save figure
    fig.savefig(outdir_paper + 'S4_transport_basins_scatter_other.pdf',
                dpi=900,
                bbox_inches='tight')
    plt.close()
Exemplo n.º 5
0
def S3_distributions_different_models():

    filenames = [
        'SubSurf_y2000_m1_d5_simdays3650_layer2_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer4_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer7_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer13_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer22_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer23_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer25_pos'
    ]
    folders = [
        'Layer2', 'Layer4', 'Layer7', 'Layer13', 'Layer22', 'Layer23',
        'Layer25'
    ]
    folders = [
        '/Users/wichmann/Simulations/Proj1_SubSurface_Mixing/' + f
        for f in folders
    ]
    labels = [
        'a) z = ' + str(nemo_depth[2]) + ' m',
        'b) z = ' + str(nemo_depth[4]) + ' m',
        'c) z = ' + str(nemo_depth[7]) + ' m',
        'd) z = ' + str(nemo_depth[13]) + ' m',
        'e) z = ' + str(nemo_depth[22]) + ' m',
        'f) z = ' + str(nemo_depth[23]) + ' m',
        'g) z = ' + str(nemo_depth[25]) + ' m'
    ]  #figure titles

    #for the figure
    fig = plt.figure(figsize=(14, 14))
    gs1 = gridspec.GridSpec(4, 2)
    gs1.update(wspace=0.01, hspace=0.0)

    for i in range(len(folders)):

        #load particle data
        filename = filenames[i]
        pdata = ParticleData.from_nc(folders[i] + '/',
                                     filename,
                                     tload=[0, -1],
                                     Ngrids=40)

        #create subplot
        plt.subplot(gs1[i])
        m = Basemap(projection='robin', lon_0=180, resolution='l')
        m.drawparallels([-60, -30, 0, 30, 60],
                        labels=[True, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawmeridians([50, 150, 250, 350],
                        labels=[False, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawcoastlines()
        m.fillcontinents(color='dimgrey')

        #get distribution
        d_full = pdata.get_distribution(t=-1, ddeg=2.).flatten()
        d = oceanvector(d_full, ddeg=2.)
        lon_bins_2d, lat_bins_2d = np.meshgrid(d.Lons_edges, d.Lats_edges)
        xs, ys = m(lon_bins_2d, lat_bins_2d)

        #plot distribution
        plt.pcolormesh(xs,
                       ys,
                       d.V2d,
                       cmap='plasma',
                       norm=colors.LogNorm(),
                       rasterized=True)
        cbar = plt.colorbar(orientation='vertical', shrink=0.5)
        cbar.ax.tick_params(labelsize=7, width=0.03)
        plt.title(labels[i], size=10, y=1.)

        fig.savefig(outdir_paper + 'S3_distributions_other_scenarios.pdf',
                    dpi=900,
                    bbox_inches='tight')
Exemplo n.º 6
0
def FIG4_scatter_final_poles():

    subfolders = ['Layer0', 'Layer16', 'Layer25', 'UniMix', 'KukMix', 'Sim3D']
    folders = [
        '/Users/wichmann/Simulations/Proj1_SubSurface_Mixing/' + f
        for f in subfolders
    ]
    labels = [
        'a) z = ' + str(nemo_depth[0]) + ' m',
        'b) z = ' + str(nemo_depth[16]) + ' m',
        'c) z = ' + str(nemo_depth[25]) + ' m', 'd) Uniform',
        'e) Kukulka mixing', 'f) 3D simulation'
    ]  #figure titles
    filenames = [
        'SubSurf_y2000_m1_d5_simdays3650_layer0_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer16_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer25_pos',
        'Uniform_y2000_m1_d5_simdays3650_layer0_pos',
        'Kukulka_y2000_m1_d5_simdays3650_layer0_pos',
        'Run13D_y2000_m1_d5_simdays3650_pos'
    ]

    #for the figure
    fig = plt.figure(figsize=(14, 11))
    gs1 = gridspec.GridSpec(3, 2)
    gs1.update(wspace=0.06, hspace=0.0)

    #binning for the regions defining functions. this does not affect the result, as the region boundaries are a multiple of 2
    ddeg = 2.

    #get region names and constrain to the subtropical basins
    _, region_names = regions(ddeg)
    region_names = region_names[5:]
    basin_regions = [6, 7]

    for j in range(len(folders)):

        #load particle data
        filename = filenames[j]

        if subfolders[j] == 'Sim3D':
            pdata = ParticleData.from_nc(folders[j] + '/',
                                         filename,
                                         tload=[0, 121],
                                         Ngrids=12)
        else:
            pdata = ParticleData.from_nc(folders[j] + '/',
                                         filename,
                                         tload=[0, -1],
                                         Ngrids=40)

        pdata.remove_nans()
        region_label = pdata.set_region_labels(ddeg, -1)

        #select the particles in the basins, and label the particles according to their final basin
        selection = [
            k for k in range(len(region_label))
            if region_label[k] in basin_regions
        ]
        lons = pdata.lons[selection]
        lats = pdata.lats[selection]
        region_label = [
            region_label[i] for i in range(len(region_label))
            if region_label[i] in basin_regions
        ]

        #plot
        plt.subplot(gs1[j])
        m = Basemap(projection='robin', lon_0=180, resolution='l')
        m.drawcoastlines()
        m.drawmapboundary(fill_color='lightgray')
        m.drawparallels([-60, -30, 0, 30, 60],
                        labels=[True, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawmeridians([50, 150, 250, 350],
                        labels=[False, False, False, True],
                        linewidth=.8,
                        size=7)
        m.fillcontinents(color='dimgray')
        xs, ys = m(lons[:, 0], lats[:, 0])
        cmap = plt.get_cmap('jet', 2)
        scat = m.scatter(xs,
                         ys,
                         marker='.',
                         s=1,
                         c=region_label,
                         cmap=cmap,
                         rasterized=True)
        plt.title(labels[j], size=10, y=1.)

    #color bar on the right
    fig.subplots_adjust(right=0.8)
    cbar_ax = fig.add_axes([0.822, 0.4, 0.015, 0.2])
    cbar = fig.colorbar(scat, cax=cbar_ax, ticks=[6, 7])
    cbar.ax.tick_params(labelsize=10)
    tick_locs = 6 + 0.25 * np.array([1, 3])
    cbar.set_ticks(tick_locs)
    cbar.set_ticklabels(region_names)

    #save figure
    fig.savefig(outdir_paper + 'F4_transport_poles_scatter.pdf',
                dpi=900,
                bbox_inches='tight')
Exemplo n.º 7
0
def S6_depth_distribution():

    folder = '/Users/wichmann/Simulations/Proj1_SubSurface_Mixing/Sim3D/'
    filename = 'Run13D_y2000_m1_d5_simdays3650_pos'

    pdata = ParticleData.from_nc_3d(folder,
                                    filename,
                                    tload=[0, 121],
                                    Ngrids=12)
    pdata.remove_nans()

    f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 6), sharey=True)

    #Figure Atlantic
    basin_regions = [1, 3]
    region_label = pdata.set_region_labels(2., -1)

    #select the particles in the basins, and label the particles according to their final basin
    selection = [
        k for k in range(len(region_label)) if region_label[k] in basin_regions
    ]
    lats = pdata.lats[selection, -1]
    depths = pdata.depths[selection, -1]

    ax1.invert_yaxis()
    hist = ax1.hist2d(lats,
                      depths,
                      bins=50,
                      norm=colors.LogNorm(),
                      vmin=1,
                      vmax=10000,
                      cmap='inferno')
    ax1.set_xlabel('Latitude [deg]')
    ax1.set_ylabel('Depth [m]')
    ax1.set_title('a) Pacific')

    #Figure Pacific
    basin_regions = [2, 4]

    #select the particles in the basins, and label the particles according to their final basin
    selection = [
        k for k in range(len(region_label)) if region_label[k] in basin_regions
    ]
    lats = pdata.lats[selection, -1]
    depths = pdata.depths[selection, -1]

    hist = ax2.hist2d(lats,
                      depths,
                      bins=50,
                      norm=colors.LogNorm(),
                      vmin=1,
                      vmax=10000,
                      cmap='inferno')
    ax2.set_xlabel('Latitude [deg]')
    ax2.set_title('b) Atlantic')

    f.subplots_adjust(bottom=0.15)
    cbar_ax = f.add_axes([0.15, 0.01, 0.45, 0.05])
    cbar = f.colorbar(hist[3], cax=cbar_ax, orientation='horizontal')
    cbar.ax.tick_params(labelsize=10, width=0.05)
    cbar.set_label('# particles per bin', size=12)

    depths = pdata.depths[:, -1]
    depths = depths[depths >= 0]
    ax3.hist(depths,
             bins=50,
             orientation="horizontal",
             normed=True,
             color='darkred')
    ax3.invert_yaxis()
    ax3.set_title('c) Total vertical distribution')
    ax3.xaxis.set_ticks([0, 0.001, 0.002, 0.003, 0.004])
    ax3.grid(True)

    f.savefig(outdir_paper + 'S6_vertical_distribution.pdf',
              dpi=900,
              bbox_inches='tight')
Exemplo n.º 8
0
def FIG2_distributions_different_models():

    subfolders = ['Layer10', 'Layer16', 'Layer19', 'UniMix', 'KukMix', 'Sim3D']
    folders = [
        '/Users/wichmann/Simulations/Proj1_SubSurface_Mixing/' + f
        for f in subfolders
    ]
    labels = [
        'a) z = ' + str(nemo_depth[10]) + ' m',
        'b) z = ' + str(nemo_depth[16]) + ' m',
        'c) z = ' + str(nemo_depth[19]) + ' m', 'd) Uniform',
        'e) Kukulka mixing', 'f) 3D simulation'
    ]  #figure titles
    filenames = [
        'SubSurf_y2000_m1_d5_simdays3650_layer10_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer16_pos',
        'SubSurf_y2000_m1_d5_simdays3650_layer19_pos',
        'Uniform_y2000_m1_d5_simdays3650_layer0_pos',
        'Kukulka_y2000_m1_d5_simdays3650_layer0_pos',
        'Run13D_y2000_m1_d5_simdays3650_pos'
    ]

    fig = plt.figure(figsize=(14, 11))
    gs1 = gridspec.GridSpec(3, 2)
    gs1.update(wspace=0.06, hspace=0.0)

    for i in range(len(folders)):

        #load particle data and get distribution
        filename = filenames[i]

        if subfolders[i] == 'Sim3D':
            pdata = ParticleData.from_nc(folders[i] + '/',
                                         filename,
                                         tload=[0, 121],
                                         Ngrids=12)
        else:
            pdata = ParticleData.from_nc(folders[i] + '/',
                                         filename,
                                         tload=[0, -1],
                                         Ngrids=40)

        d_full = pdata.get_distribution(t=-1, ddeg=2.).flatten()
        d = oceanvector(d_full, ddeg=2.)
        lon_bins_2d, lat_bins_2d = np.meshgrid(d.Lons_edges, d.Lats_edges)

        #create subplot
        plt.subplot(gs1[i])
        m = Basemap(projection='robin', lon_0=180, resolution='l')
        m.drawparallels([-60, -30, 0, 30, 60],
                        labels=[True, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawmeridians([50, 150, 250, 350],
                        labels=[False, False, False, True],
                        linewidth=.8,
                        size=7)
        m.drawcoastlines()
        m.fillcontinents(color='dimgrey')
        xs, ys = m(lon_bins_2d, lat_bins_2d)
        p = plt.pcolormesh(xs,
                           ys,
                           d.V2d,
                           cmap='plasma',
                           norm=colors.LogNorm(),
                           vmin=1,
                           vmax=10000,
                           rasterized=True)
        plt.title(labels[i], size=10, y=1.)

    fig.subplots_adjust(right=0.8)
    cbar_ax = fig.add_axes([0.85, 0.35, 0.015, 0.4])
    cbar = fig.colorbar(p, cax=cbar_ax)
    cbar.ax.tick_params(labelsize=11)
    cbar.set_label('# particles per bin', size=12)

    fig.savefig(outdir_paper + 'F2_distributions_different_models.pdf',
                dpi=900,
                bbox_inches='tight')