Tutorial Datasets

The module melodies_monet.tutorial enables automatic downloading and caching of small1 versions of the tutorial datasets. This functionality requires pooch, an optional dependency.

import xarray as xr

import melodies_monet as mm

mm.tutorial.example_ids

['wrfchem:racm_esrl',
 'wrfchem:racm_esrl_vcp',
 'airnow:2019-09',
 'airnow:2019-08',
 'airnow:2019-07',
 'camchem:fv',
 'camchem:se',
 'camchem:se_scrip',
 'aeronet:2019-09',
 'aeronet:2019-08',
 'csn:2019_daily',
 'improve:2019_daily',
 'ncore:2019_daily']

The example IDs above can be used inside a control file to specify to use that dataset, downloading if necessary but otherwise loading from the pooch cache.

For example:

model:
  cam-chem:
    files: 'example:camchem:fv'

(for model)

obs:
  airnow:
    filename: 'example:airnow:2019-09'

(for obs)

Note that you can also use melodies_monet.tutorial.fetch_example() to load data directly.

fp = mm.tutorial.fetch_example("camchem:fv")
xr.open_dataset(fp)

<xarray.Dataset>
Dimensions:    (time: 36, lev: 1, lat: 192, lon: 288, ilev: 2, nbnd: 2)
Coordinates:
  * ilev       (ilev) float64 985.0 1e+03
  * lat        (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0
  * lev        (lev) float64 992.5
  * lon        (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8
  * time       (time) datetime64[ns] 2019-09-01T06:00:00 ... 2019-09-10
Dimensions without coordinates: nbnd
Data variables:
    O3         (time, lev, lat, lon) float32 ...
    P0         float64 1e+05
    PM25       (time, lev, lat, lon) float32 ...
    PS         (time, lat, lon) float32 ...
    date       (time) int32 20190901 20190901 20190901 ... 20190909 20190910
    datesec    (time) int32 21600 43200 64800 0 21600 ... 0 21600 43200 64800 0
    hyai       (ilev) float64 4.805e-05 0.0
    hyam       (lev) float64 2.402e-05
    hybi       (ilev) float64 0.985 1.0
    hybm       (lev) float64 0.9925
    time_bnds  (time, nbnd) datetime64[ns] 2019-09-01 ... 2019-09-10
Attributes:
    Conventions:       CF-1.0
    source:            CAM
    case:              fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02
    logname:           buchholz
    host:              cheyenne3
    initial_file:      /glade/p/cesmdata/cseg/inputdata/atm/cam/inic/fv/f.e20...
    topography_file:   /glade/p/cesmdata/cseg/inputdata/atm/cam/met/MERRA2/0....
    model_doi_url:     https://doi.org/10.5065/D67H1H0V
    time_period_freq:  hour_6
    history:           Mon Feb 28 16:25:23 2022: ncks -7 -L 1 --baa=4 --ppc d...
    NCO:               netCDF Operators version 5.0.6 (Homepage = http://nco....

xarray.Dataset

• Dimensions:
  • time: 36
  • lev: 1
  • lat: 192
  • lon: 288
  • ilev: 2
  • nbnd: 2
• Coordinates: (5)
  • ilev
    (ilev)
    float64
    985.0 1e+03

    long_name :

    hybrid level at interfaces (1000*(A+B))

    units :

    hPa

    positive :

    down

    standard_name :

    atmosphere_hybrid_sigma_pressure_coordinate

    formula_terms :

    a: hyai b: hybi p0: P0 ps: PS

    array([ 985.000021, 1000.      ])

  • lat
    (lat)
    float64
    -90.0 -89.06 -88.12 ... 89.06 90.0

    long_name :

    latitude

    units :

    degrees_north

    array([-90.      , -89.057592, -88.115183, -87.172775, -86.230366, -85.287958,
           -84.34555 , -83.403141, -82.460733, -81.518325, -80.575916, -79.633508,
           -78.691099, -77.748691, -76.806283, -75.863874, -74.921466, -73.979058,
           -73.036649, -72.094241, -71.151832, -70.209424, -69.267016, -68.324607,
           -67.382199, -66.439791, -65.497382, -64.554974, -63.612565, -62.670157,
           -61.727749, -60.78534 , -59.842932, -58.900524, -57.958115, -57.015707,
           -56.073298, -55.13089 , -54.188482, -53.246073, -52.303665, -51.361257,
           -50.418848, -49.47644 , -48.534031, -47.591623, -46.649215, -45.706806,
           -44.764398, -43.82199 , -42.879581, -41.937173, -40.994764, -40.052356,
           -39.109948, -38.167539, -37.225131, -36.282723, -35.340314, -34.397906,
           -33.455497, -32.513089, -31.570681, -30.628272, -29.685864, -28.743455,
           -27.801047, -26.858639, -25.91623 , -24.973822, -24.031414, -23.089005,
           -22.146597, -21.204188, -20.26178 , -19.319372, -18.376963, -17.434555,
           -16.492147, -15.549738, -14.60733 , -13.664921, -12.722513, -11.780105,
           -10.837696,  -9.895288,  -8.95288 ,  -8.010471,  -7.068063,  -6.125654,
            -5.183246,  -4.240838,  -3.298429,  -2.356021,  -1.413613,  -0.471204,
             0.471204,   1.413613,   2.356021,   3.298429,   4.240838,   5.183246,
             6.125654,   7.068063,   8.010471,   8.95288 ,   9.895288,  10.837696,
            11.780105,  12.722513,  13.664921,  14.60733 ,  15.549738,  16.492147,
            17.434555,  18.376963,  19.319372,  20.26178 ,  21.204188,  22.146597,
            23.089005,  24.031414,  24.973822,  25.91623 ,  26.858639,  27.801047,
            28.743455,  29.685864,  30.628272,  31.570681,  32.513089,  33.455497,
            34.397906,  35.340314,  36.282723,  37.225131,  38.167539,  39.109948,
            40.052356,  40.994764,  41.937173,  42.879581,  43.82199 ,  44.764398,
            45.706806,  46.649215,  47.591623,  48.534031,  49.47644 ,  50.418848,
            51.361257,  52.303665,  53.246073,  54.188482,  55.13089 ,  56.073298,
            57.015707,  57.958115,  58.900524,  59.842932,  60.78534 ,  61.727749,
            62.670157,  63.612565,  64.554974,  65.497382,  66.439791,  67.382199,
            68.324607,  69.267016,  70.209424,  71.151832,  72.094241,  73.036649,
            73.979058,  74.921466,  75.863874,  76.806283,  77.748691,  78.691099,
            79.633508,  80.575916,  81.518325,  82.460733,  83.403141,  84.34555 ,
            85.287958,  86.230366,  87.172775,  88.115183,  89.057592,  90.      ])

  • lev
    (lev)
    float64
    992.5

    long_name :

    hybrid level at midpoints (1000*(A+B))

    units :

    hPa

    positive :

    down

    standard_name :

    atmosphere_hybrid_sigma_pressure_coordinate

    formula_terms :

    a: hyam b: hybm p0: P0 ps: PS

    array([992.500011])

  • lon
    (lon)
    float64
    0.0 1.25 2.5 ... 356.2 357.5 358.8

    long_name :

    longitude

    units :

    degrees_east

    array([  0.  ,   1.25,   2.5 , ..., 356.25, 357.5 , 358.75])

  • time
    (time)
    datetime64[ns]
    2019-09-01T06:00:00 ... 2019-09-10

    long_name :

    time

    bounds :

    time_bnds

    cell_methods :

    time: mean

    array(['2019-09-01T06:00:00.000000000', '2019-09-01T12:00:00.000000000',
           '2019-09-01T18:00:00.000000000', '2019-09-02T00:00:00.000000000',
           '2019-09-02T06:00:00.000000000', '2019-09-02T12:00:00.000000000',
           '2019-09-02T18:00:00.000000000', '2019-09-03T00:00:00.000000000',
           '2019-09-03T06:00:00.000000000', '2019-09-03T12:00:00.000000000',
           '2019-09-03T18:00:00.000000000', '2019-09-04T00:00:00.000000000',
           '2019-09-04T06:00:00.000000000', '2019-09-04T12:00:00.000000000',
           '2019-09-04T18:00:00.000000000', '2019-09-05T00:00:00.000000000',
           '2019-09-05T06:00:00.000000000', '2019-09-05T12:00:00.000000000',
           '2019-09-05T18:00:00.000000000', '2019-09-06T00:00:00.000000000',
           '2019-09-06T06:00:00.000000000', '2019-09-06T12:00:00.000000000',
           '2019-09-06T18:00:00.000000000', '2019-09-07T00:00:00.000000000',
           '2019-09-07T06:00:00.000000000', '2019-09-07T12:00:00.000000000',
           '2019-09-07T18:00:00.000000000', '2019-09-08T00:00:00.000000000',
           '2019-09-08T06:00:00.000000000', '2019-09-08T12:00:00.000000000',
           '2019-09-08T18:00:00.000000000', '2019-09-09T00:00:00.000000000',
           '2019-09-09T06:00:00.000000000', '2019-09-09T12:00:00.000000000',
           '2019-09-09T18:00:00.000000000', '2019-09-10T00:00:00.000000000'],
          dtype='datetime64[ns]')

• Data variables: (11)
  • O3
    (time, lev, lat, lon)
    float32
    ...

    mdims :

    1

    units :

    mol/mol

    long_name :

    O3 concentration

    cell_methods :

    time: mean

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    [1990656 values with dtype=float32]

  • P0
    ()
    float64
    ...

    long_name :

    reference pressure

    units :

    Pa

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    array(100000.)

  • PM25
    (time, lev, lat, lon)
    float32
    ...

    mdims :

    1

    units :

    kg/m3

    long_name :

    PM2.5 concentration

    cell_methods :

    time: mean

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    [1990656 values with dtype=float32]

  • PS
    (time, lat, lon)
    float32
    ...

    units :

    Pa

    long_name :

    Surface pressure

    cell_methods :

    time: mean

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    [1990656 values with dtype=float32]

  • date
    (time)
    int32
    ...

    long_name :

    current date (YYYYMMDD)

    cell_methods :

    time: mean

    array([20190901, 20190901, 20190901, 20190902, 20190902, 20190902, 20190902,
           20190903, 20190903, 20190903, 20190903, 20190904, 20190904, 20190904,
           20190904, 20190905, 20190905, 20190905, 20190905, 20190906, 20190906,
           20190906, 20190906, 20190907, 20190907, 20190907, 20190907, 20190908,
           20190908, 20190908, 20190908, 20190909, 20190909, 20190909, 20190909,
           20190910])

  • datesec
    (time)
    int32
    ...

    long_name :

    current seconds of current date

    cell_methods :

    time: mean

    array([21600, 43200, 64800,     0, 21600, 43200, 64800,     0, 21600, 43200,
           64800,     0, 21600, 43200, 64800,     0, 21600, 43200, 64800,     0,
           21600, 43200, 64800,     0, 21600, 43200, 64800,     0, 21600, 43200,
           64800,     0, 21600, 43200, 64800,     0])

  • hyai
    (ilev)
    float64
    ...

    long_name :

    hybrid A coefficient at layer interfaces

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    array([4.804879e-05, 0.000000e+00])

  • hyam
    (lev)
    float64
    ...

    long_name :

    hybrid A coefficient at layer midpoints

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    array([2.40244e-05])

  • hybi
    (ilev)
    float64
    ...

    long_name :

    hybrid B coefficient at layer interfaces

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    array([0.984955, 1.      ])

  • hybm
    (lev)
    float64
    ...

    long_name :

    hybrid B coefficient at layer midpoints

    QuantizeGranularBitRoundNumberOfSignificantDigits :

    5

    array([0.992477])

  • time_bnds
    (time, nbnd)
    datetime64[ns]
    ...

    long_name :

    time interval endpoints

    cell_methods :

    time: mean

    array([['2019-09-01T00:00:00.000000000', '2019-09-01T06:00:00.000000000'],
           ['2019-09-01T06:00:00.000000000', '2019-09-01T12:00:00.000000000'],
           ['2019-09-01T12:00:00.000000000', '2019-09-01T18:00:00.000000000'],
           ['2019-09-01T18:00:00.000000000', '2019-09-02T00:00:00.000000000'],
           ['2019-09-02T00:00:00.000000000', '2019-09-02T06:00:00.000000000'],
           ['2019-09-02T06:00:00.000000000', '2019-09-02T12:00:00.000000000'],
           ['2019-09-02T12:00:00.000000000', '2019-09-02T18:00:00.000000000'],
           ['2019-09-02T18:00:00.000000000', '2019-09-03T00:00:00.000000000'],
           ['2019-09-03T00:00:00.000000000', '2019-09-03T06:00:00.000000000'],
           ['2019-09-03T06:00:00.000000000', '2019-09-03T12:00:00.000000000'],
           ['2019-09-03T12:00:00.000000000', '2019-09-03T18:00:00.000000000'],
           ['2019-09-03T18:00:00.000000000', '2019-09-04T00:00:00.000000000'],
           ['2019-09-04T00:00:00.000000000', '2019-09-04T06:00:00.000000000'],
           ['2019-09-04T06:00:00.000000000', '2019-09-04T12:00:00.000000000'],
           ['2019-09-04T12:00:00.000000000', '2019-09-04T18:00:00.000000000'],
           ['2019-09-04T18:00:00.000000000', '2019-09-05T00:00:00.000000000'],
           ['2019-09-05T00:00:00.000000000', '2019-09-05T06:00:00.000000000'],
           ['2019-09-05T06:00:00.000000000', '2019-09-05T12:00:00.000000000'],
           ['2019-09-05T12:00:00.000000000', '2019-09-05T18:00:00.000000000'],
           ['2019-09-05T18:00:00.000000000', '2019-09-06T00:00:00.000000000'],
           ['2019-09-06T00:00:00.000000000', '2019-09-06T06:00:00.000000000'],
           ['2019-09-06T06:00:00.000000000', '2019-09-06T12:00:00.000000000'],
           ['2019-09-06T12:00:00.000000000', '2019-09-06T18:00:00.000000000'],
           ['2019-09-06T18:00:00.000000000', '2019-09-07T00:00:00.000000000'],
           ['2019-09-07T00:00:00.000000000', '2019-09-07T06:00:00.000000000'],
           ['2019-09-07T06:00:00.000000000', '2019-09-07T12:00:00.000000000'],
           ['2019-09-07T12:00:00.000000000', '2019-09-07T18:00:00.000000000'],
           ['2019-09-07T18:00:00.000000000', '2019-09-08T00:00:00.000000000'],
           ['2019-09-08T00:00:00.000000000', '2019-09-08T06:00:00.000000000'],
           ['2019-09-08T06:00:00.000000000', '2019-09-08T12:00:00.000000000'],
           ['2019-09-08T12:00:00.000000000', '2019-09-08T18:00:00.000000000'],
           ['2019-09-08T18:00:00.000000000', '2019-09-09T00:00:00.000000000'],
           ['2019-09-09T00:00:00.000000000', '2019-09-09T06:00:00.000000000'],
           ['2019-09-09T06:00:00.000000000', '2019-09-09T12:00:00.000000000'],
           ['2019-09-09T12:00:00.000000000', '2019-09-09T18:00:00.000000000'],
           ['2019-09-09T18:00:00.000000000', '2019-09-10T00:00:00.000000000']],
          dtype='datetime64[ns]')

• Attributes: (11)

  Conventions :

  CF-1.0

  source :

  CAM

  case :

  fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02

  logname :

  buchholz

  host :

  cheyenne3

  initial_file :

  /glade/p/cesmdata/cseg/inputdata/atm/cam/inic/fv/f.e20.FCSD.f09_f09_mg17.cesm2.1-exp002.001.cam.i.2005-01-01-00000_c180801.nc

  topography_file :

  /glade/p/cesmdata/cseg/inputdata/atm/cam/met/MERRA2/0.9x1.25/fv_0.9x1.25_nc3000_Nsw042_Nrs008_Co060_Fi001_ZR_sgh30_24km_GRNL_MERRA2_c171218.nc

  model_doi_url :

  https://doi.org/10.5065/D67H1H0V

  time_period_freq :

  hour_6

  history :

  Mon Feb 28 16:25:23 2022: ncks -7 -L 1 --baa=4 --ppc default=5 -d lev,-1 -d ilev,-2,-1 CAM_chem_merra2_FCSD_1deg_QFED_world_201909-01-09_small.nc -o CAM_chem_merra2_FCSD_1deg_QFED_world_201909-01-09_small_sfc.nc Fri Feb 25 15:19:44 2022: ncrcat /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-01-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-02-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-03-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-04-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-05-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-06-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-07-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-08-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-09-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.cam.h1.201909.nc Fri Feb 25 15:19:30 2022: ncks -v date,datesec,time,lat,lon,hyam,hybm,hyai,hybi,P0,PS,O3,PM25 /glade/campaign/acom/acom-da/CAM_chem_output/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02/atm/boundary_conditions/2019/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-01-21600.nc /glade/scratch/buchholz/tmp/fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02.cam.h1.2019-09-01-21600.nc

  NCO :

  netCDF Operators version 5.0.6 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)

---

1

Only a few variables included, levels limited to surface or near-surface, NCO compression applied. Full versions are also available via https://csl.noaa.gov/groups/csl4/modeldata/melodies-monet/.