import xarray as xrstore = 'https://ncsa.osn.xsede.org/Pangeo/pangeo-forge/cesm-atm-025deg-feedstock/cesm-atm-025deg.zarr'ds = xr.open_dataset(store, engine='zarr', chunks={})
<xarray.Dataset> Size: 2GB Dimensions: (time: 73, lat: 768, lon: 1152, ilev: 31, lev: 30, nbnd: 2) Coordinates: * ilev (ilev) float64 248B 2.255 5.032 10.16 18.56 ... 967.5 985.1 1e+03 * lat (lat) float64 6kB -90.0 -89.77 -89.53 -89.3 ... 89.53 89.77 90.0 * lev (lev) float64 240B 3.643 7.595 14.36 24.61 ... 957.5 976.3 992.6 * lon (lon) float64 9kB 0.0 0.3125 0.625 0.9375 ... 359.1 359.4 359.7 * time (time) object 584B 0078-01-01 00:00:00 ... 0078-03-14 00:00:00 Dimensions without coordinates: nbnd Data variables: (12/35) FLDS (time, lat, lon) float32 258MB dask.array<chunksize=(73, 768, 1152), meta=np.ndarray> FSNS (time, lat, lon) float32 258MB dask.array<chunksize=(73, 768, 1152), meta=np.ndarray> LHFLX (time, lat, lon) float32 258MB dask.array<chunksize=(73, 768, 1152), meta=np.ndarray> P0 float64 8B ... PSL (time, lat, lon) float32 258MB dask.array<chunksize=(73, 768, 1152), meta=np.ndarray> SHFLX (time, lat, lon) float32 258MB dask.array<chunksize=(73, 768, 1152), meta=np.ndarray> ... ... nsteph (time) float64 584B dask.array<chunksize=(73,), meta=np.ndarray> ntrk float64 8B ... ntrm float64 8B ... ntrn float64 8B ... sol_tsi (time) float64 584B dask.array<chunksize=(73,), meta=np.ndarray> time_bnds (time, nbnd) object 1kB dask.array<chunksize=(73, 2), meta=np.ndarray> Attributes: (12/18) Conventions: CF-1.0 TITLE: REMAPPED: UNSET ... Version: $Name$ case: hybrid_v5_rel04_BC5_ne120_t12_pop62 ... creation_date: Fri Sep 19 14:46:57 MDT 2014 host: ys2738 ... ... revision_Id: $Id$ separator1: ------- SOURCE FILE ATTRIBUTES -------- separator2: --------------------------------------- source: CAM title: UNSET ... topography_file: /glade/p/cesm/cseg//inputdata/atm/cam/topo/USGS_gtopo30...
array([ 2.25524 , 5.031692, 10.157947, 18.555317, 30.669123, 45.867477, 63.323483, 80.701418, 94.941042, 111.693211, 131.401271, 154.586807, 181.863353, 213.952821, 251.704417, 296.117216, 348.366588, 409.835219, 482.149929, 567.224421, 652.332969, 730.445892, 796.363071, 845.353667, 873.715866, 900.324631, 924.964462, 947.432335, 967.538625, 985.11219 , 1000. ])
array([-90. , -89.765319, -89.530639, ..., 89.530639, 89.765319, 90. ])
array([ 3.643466, 7.59482 , 14.356632, 24.61222 , 38.2683 , 54.59548 , 72.012451, 87.82123 , 103.317127, 121.547241, 142.994039, 168.22508 , 197.908087, 232.828619, 273.910817, 322.241902, 379.100904, 445.992574, 524.687175, 609.778695, 691.38943 , 763.404481, 820.858369, 859.534767, 887.020249, 912.644547, 936.198398, 957.48548 , 976.325407, 992.556095])
array([0.000000e+00, 3.125000e-01, 6.250000e-01, ..., 3.590625e+02, 3.593750e+02, 3.596875e+02])
array([cftime.DatetimeNoLeap(78, 1, 1, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 2, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 3, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 4, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 5, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 6, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 7, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 8, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 9, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 10, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 11, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 12, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 13, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 14, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 15, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 16, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 17, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 18, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 19, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 20, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 21, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 22, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 23, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 24, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 25, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 26, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 27, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 28, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 29, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 30, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 1, 31, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 1, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 2, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 3, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 4, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 5, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 6, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 7, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 8, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 9, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 10, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 11, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 12, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 13, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 14, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 15, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 16, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 17, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 18, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 19, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 20, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 21, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 22, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 23, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 24, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 25, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 26, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 27, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 2, 28, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 1, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 2, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 3, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 4, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 5, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 6, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 7, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 8, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 9, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 10, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 11, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 12, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 13, 0, 0, 0, 0, has_year_zero=True), cftime.DatetimeNoLeap(78, 3, 14, 0, 0, 0, 0, has_year_zero=True)], dtype=object)
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[1 values with dtype=float64]
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[1 values with dtype=float64]
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[1 values with dtype=float64]
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[1 values with dtype=float64]
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PandasIndex(Index([ 2.255239523947239, 5.031691864132881, 10.15794742852449, 18.55531707406044, 30.66912293434143, 45.86747661232948, 63.3234828710556, 80.70141822099686, 94.94104236364365, 111.69321089982991, 131.4012706279755, 154.5868068933487, 181.8633526563644, 213.95282074809072, 251.70441716909409, 296.11721634864807, 348.3665883541107, 409.8352193832398, 482.14992880821234, 567.22442060709, 652.3329690098763, 730.4458916187286, 796.3630706071854, 845.3536666929722, 873.7158663570881, 900.3246314823627, 924.9644624069333, 947.4323345348239, 967.5386245362461, 985.112190246582, 1000.0], dtype='float64', name='ilev'))
PandasIndex(Index([ -90.0, -89.76531942633638, -89.53063885267275, -89.29595827900913, -89.0612777053455, -88.82659713168188, -88.59191655801826, -88.35723598435463, -88.122555410691, -87.88787483702738, ... 87.88787483702713, 88.12255541069075, 88.35723598435438, 88.591916558018, 88.82659713168162, 89.06127770534525, 89.29595827900887, 89.5306388526725, 89.76531942633612, 90.0], dtype='float64', name='lat', length=768))
PandasIndex(Index([ 3.64346569404006, 7.594819646328688, 14.356632251292467, 24.612220004200935, 38.26829977333546, 54.59547974169254, 72.01245054602623, 87.82123029232025, 103.31712663173676, 121.54724076390266, 142.99403876066208, 168.22507977485657, 197.9080867022276, 232.82861895859241, 273.9108167588711, 322.2419023513794, 379.10090386867523, 445.992574095726, 524.6871747076511, 609.7786948084831, 691.3894303143024, 763.404481112957, 820.8583686500788, 859.5347665250301, 887.0202489197254, 912.644546944648, 936.1983984708786, 957.485479535535, 976.325407391414, 992.556095123291], dtype='float64', name='lev'))
PandasIndex(Index([ 0.0, 0.3125, 0.625, 0.9375, 1.25, 1.5625, 1.875, 2.1875, 2.5, 2.8125, ... 356.875, 357.1875, 357.5, 357.8125, 358.125, 358.4375, 358.75, 359.0625, 359.375, 359.6875], dtype='float64', name='lon', length=1152))
PandasIndex(CFTimeIndex([0078-01-01 00:00:00, 0078-01-02 00:00:00, 0078-01-03 00:00:00, 0078-01-04 00:00:00, 0078-01-05 00:00:00, 0078-01-06 00:00:00, 0078-01-07 00:00:00, 0078-01-08 00:00:00, 0078-01-09 00:00:00, 0078-01-10 00:00:00, 0078-01-11 00:00:00, 0078-01-12 00:00:00, 0078-01-13 00:00:00, 0078-01-14 00:00:00, 0078-01-15 00:00:00, 0078-01-16 00:00:00, 0078-01-17 00:00:00, 0078-01-18 00:00:00, 0078-01-19 00:00:00, 0078-01-20 00:00:00, 0078-01-21 00:00:00, 0078-01-22 00:00:00, 0078-01-23 00:00:00, 0078-01-24 00:00:00, 0078-01-25 00:00:00, 0078-01-26 00:00:00, 0078-01-27 00:00:00, 0078-01-28 00:00:00, 0078-01-29 00:00:00, 0078-01-30 00:00:00, 0078-01-31 00:00:00, 0078-02-01 00:00:00, 0078-02-02 00:00:00, 0078-02-03 00:00:00, 0078-02-04 00:00:00, 0078-02-05 00:00:00, 0078-02-06 00:00:00, 0078-02-07 00:00:00, 0078-02-08 00:00:00, 0078-02-09 00:00:00, 0078-02-10 00:00:00, 0078-02-11 00:00:00, 0078-02-12 00:00:00, 0078-02-13 00:00:00, 0078-02-14 00:00:00, 0078-02-15 00:00:00, 0078-02-16 00:00:00, 0078-02-17 00:00:00, 0078-02-18 00:00:00, 0078-02-19 00:00:00, 0078-02-20 00:00:00, 0078-02-21 00:00:00, 0078-02-22 00:00:00, 0078-02-23 00:00:00, 0078-02-24 00:00:00, 0078-02-25 00:00:00, 0078-02-26 00:00:00, 0078-02-27 00:00:00, 0078-02-28 00:00:00, 0078-03-01 00:00:00, 0078-03-02 00:00:00, 0078-03-03 00:00:00, 0078-03-04 00:00:00, 0078-03-05 00:00:00, 0078-03-06 00:00:00, 0078-03-07 00:00:00, 0078-03-08 00:00:00, 0078-03-09 00:00:00, 0078-03-10 00:00:00, 0078-03-11 00:00:00, 0078-03-12 00:00:00, 0078-03-13 00:00:00, 0078-03-14 00:00:00], dtype='object', length=73, calendar='noleap', freq='D'))