MPAS Vertex-centered Voronoi plots

This example draws MPAS vertex-centered scalar data on the dual polygons around each vertex with easyclimate.plot.mpas.plot_vertex_voronoi.

If cell-centered data are supplied, the helper can average neighboring cell values to vertices before plotting.

import xarray as xr
import numpy as np
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import easyclimate as ecl

from easyclimate.plot.mpas import plot_vertex_voronoi

Open the sample MPAS output and use a selected relative-vorticity field for the vertex-based examples.

data = ecl.open_tutorial_dataset("mpas_JWwave_T10_nVertLevels10")
data

mpas_JWwave_T10_nVertLevels10.nc ━━━━━━━━ 100.0% • 2.3/2.3  • 20.2     • 0:00:00
                                                   MB         MB/s

<xarray.Dataset> Size: 6MB
Dimensions:                 (nCells: 40962, nVertices: 81920, maxEdges: 10,
                             nEdges: 122880, TWO: 2, vertexDegree: 3)
Coordinates:
  * nCells                  (nCells) int64 328kB 0 1 2 3 ... 40959 40960 40961
    Time                    int64 8B ...
    nVertLevels             int64 8B ...
Dimensions without coordinates: nVertices, maxEdges, nEdges, TWO, vertexDegree
Data variables:
    uReconstructZonal       (nCells) float32 164kB ...
    uReconstructMeridional  (nCells) float32 164kB ...
    vorticity               (nVertices) float32 328kB ...
    divergence              (nCells) float32 164kB ...
    lonCell                 (nCells) float32 164kB ...
    latCell                 (nCells) float32 164kB ...
    lonVertex               (nVertices) float32 328kB ...
    latVertex               (nVertices) float32 328kB ...
    verticesOnCell          (nCells, maxEdges) int32 2MB ...
    nEdgesOnCell            (nCells) int32 164kB ...
    verticesOnEdge          (nEdges, TWO) int32 983kB ...
    cellsOnVertex           (nVertices, vertexDegree) int32 983kB ...
Attributes: (12/180)
    model_name:                             mpas
    core_name:                              atmosphere
    version:                                8.4.0
    source:                                 MPAS
    Conventions:                            MPAS
    git_version:                            v8.4.0
    ...                                     ...
    config_noahmp_iopt_crop:                0
    config_noahmp_iopt_irr:                 0
    config_noahmp_iopt_irrm:                0
    config_noahmp_iopt_infdv:               1
    config_noahmp_iopt_tdrn:                0
    file_id:                                m02zbs7ciw

xarray.Dataset

• Dimensions:
  • nCells: 40962
  • nVertices: 81920
  • maxEdges: 10
  • nEdges: 122880
  • TWO: 2
  • vertexDegree: 3
• Coordinates: (3)
  • nCells
    (nCells)
    int64
    0 1 2 3 ... 40958 40959 40960 40961

    array([    0,     1,     2, ..., 40959, 40960, 40961], shape=(40962,))

  • Time
    ()
    int64
    ...

    [1 values with dtype=int64]

  • nVertLevels
    ()
    int64
    ...

    [1 values with dtype=int64]

• Data variables: (12)
  • uReconstructZonal
    (nCells)
    float32
    ...

    units :

    m s^{-1}

    long_name :

    Zonal component of reconstructed horizontal velocity at cell centers

    [40962 values with dtype=float32]

  • uReconstructMeridional
    (nCells)
    float32
    ...

    units :

    m s^{-1}

    long_name :

    Meridional component of reconstructed horizontal velocity at cell centers

    [40962 values with dtype=float32]

  • vorticity
    (nVertices)
    float32
    ...

    units :

    s^{-1}

    long_name :

    Relative vorticity at vertices

    [81920 values with dtype=float32]

  • divergence
    (nCells)
    float32
    ...

    units :

    s^{-1}

    long_name :

    Horizontal velocity divergence at cell center

    [40962 values with dtype=float32]

  • lonCell
    (nCells)
    float32
    ...

    units :

    rad

    long_name :

    Longitude of cells

    [40962 values with dtype=float32]

  • latCell
    (nCells)
    float32
    ...

    units :

    rad

    long_name :

    Latitude of cells

    [40962 values with dtype=float32]

  • lonVertex
    (nVertices)
    float32
    ...

    units :

    rad

    long_name :

    Longitude of vertices

    [81920 values with dtype=float32]

  • latVertex
    (nVertices)
    float32
    ...

    units :

    rad

    long_name :

    Latitude of vertices

    [81920 values with dtype=float32]

  • verticesOnCell
    (nCells, maxEdges)
    int32
    ...

    units :

    -

    long_name :

    IDs of vertices (corner points) of a cell

    [409620 values with dtype=int32]

  • nEdgesOnCell
    (nCells)
    int32
    ...

    units :

    -

    long_name :

    Number of edges forming the boundary of a cell

    [40962 values with dtype=int32]

  • verticesOnEdge
    (nEdges, TWO)
    int32
    ...

    units :

    -

    long_name :

    IDs of the two vertex endpoints of an edge

    [245760 values with dtype=int32]

  • cellsOnVertex
    (nVertices, vertexDegree)
    int32
    ...

    units :

    -

    long_name :

    IDs of the cells that meet at a vertex

    [245760 values with dtype=int32]

• Attributes: (180)

  model_name :

  mpas

  core_name :

  atmosphere

  version :

  8.4.0

  source :

  MPAS

  Conventions :

  MPAS

  git_version :

  v8.4.0

  on_a_sphere :

  YES

  sphere_radius :

  6.371229e+06

  is_periodic :

  NO

  x_period :

  0.0

  y_period :

  0.0

  history :

  mpirun -n 2 ./atmosphere_model

  parent_id :

  obz1o02d1d

  mesh_spec :

  0.0

  config_time_integration :

  SRK3

  config_time_integration_order :

  2

  config_dt :

  450.0

  config_calendar_type :

  gregorian

  config_start_time :

  0000-01-01_00:00:00

  config_stop_time :

  none

  config_run_duration :

  16_00:00:00

  config_split_dynamics_transport :

  NO

  config_number_of_sub_steps :

  6

  config_dynamics_split_steps :

  1

  config_h_mom_eddy_visc2 :

  0.0

  config_h_mom_eddy_visc4 :

  0.0

  config_v_mom_eddy_visc2 :

  0.0

  config_h_theta_eddy_visc2 :

  0.0

  config_h_theta_eddy_visc4 :

  0.0

  config_v_theta_eddy_visc2 :

  0.0

  config_horiz_mixing :

  2d_smagorinsky

  config_les_model :

  none

  config_les_surface :

  none

  config_surface_heat_flux :

  0.0

  config_surface_moisture_flux :

  0.0

  config_surface_drag_coefficient :

  0.0

  config_len_disp :

  120000.0

  config_visc4_2dsmag :

  0.05

  config_mix_scalars :

  NO

  config_del4u_div_factor :

  10.0

  config_w_adv_order :

  3

  config_theta_adv_order :

  3

  config_scalar_adv_order :

  3

  config_u_vadv_order :

  3

  config_w_vadv_order :

  3

  config_theta_vadv_order :

  3

  config_scalar_vadv_order :

  3

  config_scalar_advection :

  NO

  config_positive_definite :

  NO

  config_monotonic :

  NO

  config_coef_3rd_order :

  1.0

  config_smagorinsky_coef :

  0.125

  config_mix_full :

  YES

  config_epssm :

  0.1

  config_smdiv :

  0.1

  config_apvm_upwinding :

  0.5

  config_h_ScaleWithMesh :

  YES

  config_num_halos :

  2

  config_relax_zone_divdamp_coef :

  6.0

  config_zd :

  22000.0

  config_xnutr :

  0.0

  config_mpas_cam_coef :

  0.0

  config_number_cam_damping_levels :

  4

  config_rayleigh_damp_u :

  NO

  config_rayleigh_damp_u_timescale_days :

  5.0

  config_number_rayleigh_damp_u_levels :

  6

  config_epssm_minimum :

  0.1

  config_epssm_maximum :

  0.5

  config_epssm_transition_bottom_z :

  30000.0

  config_epssm_transition_top_z :

  50000.0

  config_apply_lbcs :

  NO

  config_restart_timestamp_name :

  restart_timestamp

  config_pio_num_iotasks :

  0

  config_pio_stride :

  1

  config_block_decomp_file_prefix :

  x1.40962.graph.info.part.

  config_number_of_blocks :

  0

  config_explicit_proc_decomp :

  NO

  config_proc_decomp_file_prefix :

  graph.info.part.

  config_do_restart :

  NO

  config_do_DAcycling :

  NO

  config_print_global_minmax_vel :

  YES

  config_print_detailed_minmax_vel :

  NO

  config_print_global_minmax_sca :

  NO

  config_IAU_option :

  off

  config_IAU_window_length_s :

  21600.0

  config_jedi_da :

  NO

  config_halo_exch_method :

  mpas_halo

  config_gpu_aware_mpi :

  NO

  input_soil_data :

  STAS

  input_soil_temperature_lag :

  140

  num_soil_layers :

  4

  months :

  12

  noznlev :

  59

  naerlev :

  29

  camdim1 :

  4

  config_frac_seaice :

  YES

  config_sfc_albedo :

  YES

  config_sfc_snowalbedo :

  YES

  config_sst_update :

  NO

  config_sstdiurn_update :

  NO

  config_deepsoiltemp_update :

  NO

  config_o3climatology :

  NO

  config_microp_re :

  NO

  config_ysu_pblmix :

  NO

  config_urban_physics :

  NO

  config_n_microp :

  1

  config_microphysics_top :

  45000.0

  config_radtlw_interval :

  00:30:00

  config_radtsw_interval :

  00:30:00

  config_conv_interval :

  none

  config_pbl_interval :

  none

  config_camrad_abs_update :

  06:00:00

  config_greeness_update :

  24:00:00

  config_bucket_update :

  none

  config_physics_suite :

  none

  config_microp_scheme :

  off

  config_convection_scheme :

  off

  config_lsm_scheme :

  off

  config_pbl_scheme :

  off

  config_gwdo_scheme :

  off

  config_ngw_scheme :

  NO

  config_knob_ugwp_tauamp :

  0.00013

  config_ugwp_diags :

  NO

  config_radt_cld_scheme :

  off

  config_radt_lw_scheme :

  off

  config_radt_sw_scheme :

  off

  config_sfclayer_scheme :

  off

  config_radt_cld_overlap :

  maximum_random

  config_radt_cld_dcorrlen :

  constant

  config_gfconv_closure_deep :

  0

  config_gfconv_closure_shallow :

  8

  config_mynn_tkeadvect :

  NO

  config_mynn_tkebudget :

  0

  config_mynn_closure :

  2.5

  config_mynn_cloudpdf :

  2

  config_mynn_mixlength :

  2

  config_mynn_stfunc :

  1

  config_mynn_topdown :

  0

  config_mynn_scaleaware :

  1

  config_mynn_dheat_opt :

  1

  config_mynn_edmf :

  1

  config_mynn_edmf_dd :

  0

  config_mynn_edmf_mom :

  0

  config_mynn_edmf_tke :

  0

  config_mynn_edmf_output :

  0

  config_mynn_mixscalars :

  1

  config_mynn_mixclouds :

  1

  config_mynn_mixqt :

  0

  config_bucket_radt :

  1e+09

  config_bucket_rainc :

  100.0

  config_bucket_rainnc :

  100.0

  config_oml1d :

  NO

  config_oml_hml0 :

  30.0

  config_oml_gamma :

  0.14

  config_oml_relaxation_time :

  864000.0

  config_sounding_interval :

  none

  config_noahmp_iopt_dveg :

  4

  config_noahmp_iopt_crs :

  1

  config_noahmp_iopt_btr :

  1

  config_noahmp_iopt_runsrf :

  3

  config_noahmp_iopt_runsub :

  3

  config_noahmp_iopt_sfc :

  1

  config_noahmp_iopt_frz :

  1

  config_noahmp_iopt_inf :

  1

  config_noahmp_iopt_rad :

  3

  config_noahmp_iopt_alb :

  1

  config_noahmp_iopt_snf :

  1

  config_noahmp_iopt_tksno :

  1

  config_noahmp_iopt_tbot :

  2

  config_noahmp_iopt_stc :

  1

  config_noahmp_iopt_gla :

  1

  config_noahmp_iopt_rsf :

  4

  config_noahmp_iopt_soil :

  1

  config_noahmp_iopt_pedo :

  1

  config_noahmp_iopt_crop :

  0

  config_noahmp_iopt_irr :

  0

  config_noahmp_iopt_irrm :

  0

  config_noahmp_iopt_infdv :

  1

  config_noahmp_iopt_tdrn :

  0

  file_id :

  m02zbs7ciw

Draw vertex dual polygons over a broad region.

plot_vertex_voronoi(
    data,
    data.vorticity,
    lon_min=130,
    lon_max=320,
    lat_min=10,
    lat_max=80,
)

<matplotlib.collections.PolyCollection object at 0x7a8797572540>

The helper can also draw on an existing Cartopy axes.

fig, ax = plt.subplots(subplot_kw= {"projection": ccrs.PlateCarree(-120)})

plot_vertex_voronoi(
    data,
    data.vorticity,

    ax = ax,
    transform = ccrs.PlateCarree(),

    lon_min=130,
    lon_max=320,
    lat_min=10,
    lat_max=80,

    cbar_kwargs = {'location': 'bottom', 'aspect': 60}
)

ax.set_title("JW Wave Relative Vorticity (plot_vertex_voronoi)")
ax.coastlines(resolution="110m", linewidth=0.6, color = "b")
ax.gridlines(draw_labels=True, alpha = 0)

<cartopy.mpl.gridliner.Gridliner object at 0x7a8793f56e40>

Show polygon edges in a smaller region to inspect the dual mesh structure.

fig, ax = plt.subplots(subplot_kw= {"projection": ccrs.PlateCarree(160)})

plot_vertex_voronoi(
    data,
    data.vorticity,

    transform = ccrs.PlateCarree(),
    ax = ax,

    lon_min=200,
    lon_max=270,
    lat_min=30,
    lat_max=70,

    linewidth = 0.1,
    edgecolor="grey",

    cbar_kwargs = {'location': 'bottom', 'aspect': 60}
)

ax.set_title("Local JW Wave Relative Vorticity (plot_cell_voronoi)")
ax.coastlines(resolution="50m", linewidth=0.6, color = "r")
ax.gridlines(draw_labels=True, alpha = 0)

<cartopy.mpl.gridliner.Gridliner object at 0x7a8796f66000>