run_tracers_restored_zarr

MITgcm output from a wind and thermally driven channel with a ridge at 5km resolution and interior restored tracers

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/pangeo-data/pangeo-datastore/master/intake-catalogs/ocean/channel.yaml")
ds  = cat["run_tracers_restored_zarr"].to_dask()

Working with requester pays data

Several of the datasets within the cloud data catalog are contained in requester pays storage buckets. This means that a user requesting data must provide their own billing project (created and authenticated through Google Cloud Platform) to be billed for the charges associated with accessing a dataset. To set up an GCP billing project and use it for authentication in applications:

Create a project on GCP; if this is the first time using GCP, a prompt will appear to choose a Google account to link to all GCP-related activities.
Create a Cloud Billing account associated with the project and enable billing for the project through this account.
Using Google Cloud IAM, add the Service Usage Consumer role to your account, which enables it to make billed requests on the behalf of the project.
Through command line, install the Google Cloud SDK; this can be done using conda:
```
conda install -c conda-forge google-cloud-sdk
```
Initialize the gcloud command line interface, logging into the account used to create the aforementioned project and selecting it as the default project; this will allow the project to be used for requester pays access through the command line:
```
gcloud auth login
gcloud init
```
Finally, use gcloud to establish application default credentials; this will allow the project to be used for requester pays access through applications:
```
gcloud auth application-default login
```

Metadata

time_resolution	3 day snapshots
duration	16.5 years
uploader_github	charlesbluca
uploader_email	charles@ldeo.columbia.edu
tags	['ocean', 'model']

Dataset Contents

xarray.Dataset

Dimensions:
- XC: 400
- XG: 400
- YC: 400
- YG: 400
- Z: 40
- Zl: 40
- Zp1: 41
- Zu: 40
- layer_1TH_bounds: 43
- layer_1TH_center: 42
- layer_1TH_interface: 41
- time: 1980

Coordinates: (32)

Depth

(YC, XC)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: XC YC
long_name :: ocean depth
standard_name :: ocean_depth
units :: m





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

PHrefC

(Z)

float32

dask.array<chunksize=(1,), meta=np.ndarray>

long_name :: Reference Hydrostatic Pressure
standard_name :: cell_reference_pressure
units :: m2 s-2





  
      Array  Chunk 
  
  
     Bytes  160 B   4 B 
     Shape  (40,)   (1,) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

PHrefF

(Zp1)

float32

dask.array<chunksize=(41,), meta=np.ndarray>

long_name :: Reference Hydrostatic Pressure
standard_name :: cell_reference_pressure
units :: m2 s-2





  
      Array  Chunk 
  
  
     Bytes  164 B   164 B 
     Shape  (41,)   (41,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

XC
(XC)
float32
2500.0 7500.0 ... 1997500.0
axis :
X
coordinate :
YC XC
long_name :
x coordinate
standard_name :
plane_x_coordinate
units :
m
```
array([   2500.,    7500.,   12500., ..., 1987500., 1992500., 1997500.],
      dtype=float32)
```
XG
(XG)
float32
0.0 5000.0 ... 1990000.0 1995000.0
axis :
X
c_grid_axis_shift :
-0.5
coordinate :
YG XG
long_name :
x coordinate
standard_name :
plane_x_coordinate_at_f_location
units :
m
```
array([      0.,    5000.,   10000., ..., 1985000., 1990000., 1995000.],
      dtype=float32)
```
YC
(YC)
float32
2500.0 7500.0 ... 1997500.0
axis :
Y
coordinate :
YC XC
long_name :
y coordinate
standard_name :
plane_y_coordinate
units :
m
```
array([   2500.,    7500.,   12500., ..., 1987500., 1992500., 1997500.],
      dtype=float32)
```
YG
(YG)
float32
0.0 5000.0 ... 1990000.0 1995000.0
axis :
Y
c_grid_axis_shift :
-0.5
long_name :
y coordinate
standard_name :
plane_y_coordinate_at_f_location
units :
m
```
array([      0.,    5000.,   10000., ..., 1985000., 1990000., 1995000.],
      dtype=float32)
```

(Z)

float32

-5.0 -15.0 ... -2830.5 -2933.5

axis :: Z
long_name :: vertical coordinate of cell center
positive :: down
standard_name :: depth
units :: m

array([   -5. ,   -15. ,   -25. ,   -36. ,   -49. ,   -64. ,   -81.5,  -102. ,
        -126. ,  -154. ,  -187. ,  -226. ,  -272. ,  -327. ,  -393. ,  -471.5,
        -565. ,  -667.5,  -770.5,  -873.5,  -976.5, -1079.5, -1182.5, -1285.5,
       -1388.5, -1491.5, -1594.5, -1697.5, -1800.5, -1903.5, -2006.5, -2109.5,
       -2212.5, -2315.5, -2418.5, -2521.5, -2624.5, -2727.5, -2830.5, -2933.5],
      dtype=float32)

(Zl)

float32

0.0 -10.0 -20.0 ... -2779.0 -2882.0

axis :: Z
c_grid_axis_shift :: -0.5
long_name :: vertical coordinate of upper cell interface
positive :: down
standard_name :: depth_at_upper_w_location
units :: m

array([    0.,   -10.,   -20.,   -30.,   -42.,   -56.,   -72.,   -91.,  -113.,
        -139.,  -169.,  -205.,  -247.,  -297.,  -357.,  -429.,  -514.,  -616.,
        -719.,  -822.,  -925., -1028., -1131., -1234., -1337., -1440., -1543.,
       -1646., -1749., -1852., -1955., -2058., -2161., -2264., -2367., -2470.,
       -2573., -2676., -2779., -2882.], dtype=float32)

Zp1

(Zp1)

float32

0.0 -10.0 -20.0 ... -2882.0 -2985.0

axis :: Z
c_grid_axis_shift :: [-0.5, 0.5]
long_name :: vertical coordinate of cell interface
positive :: down
standard_name :: depth_at_w_location
units :: m

array([    0.,   -10.,   -20.,   -30.,   -42.,   -56.,   -72.,   -91.,  -113.,
        -139.,  -169.,  -205.,  -247.,  -297.,  -357.,  -429.,  -514.,  -616.,
        -719.,  -822.,  -925., -1028., -1131., -1234., -1337., -1440., -1543.,
       -1646., -1749., -1852., -1955., -2058., -2161., -2264., -2367., -2470.,
       -2573., -2676., -2779., -2882., -2985.], dtype=float32)

(Zu)

float32

-10.0 -20.0 ... -2882.0 -2985.0

axis :: Z
c_grid_axis_shift :: 0.5
long_name :: vertical coordinate of lower cell interface
positive :: down
standard_name :: depth_at_lower_w_location
units :: m

array([  -10.,   -20.,   -30.,   -42.,   -56.,   -72.,   -91.,  -113.,  -139.,
        -169.,  -205.,  -247.,  -297.,  -357.,  -429.,  -514.,  -616.,  -719.,
        -822.,  -925., -1028., -1131., -1234., -1337., -1440., -1543., -1646.,
       -1749., -1852., -1955., -2058., -2161., -2264., -2367., -2470., -2573.,
       -2676., -2779., -2882., -2985.], dtype=float32)

drC

(Zp1)

float32

dask.array<chunksize=(41,), meta=np.ndarray>

long_name :: cell z size
standard_name :: cell_z_size_at_w_location
units :: m





  
      Array  Chunk 
  
  
     Bytes  164 B   164 B 
     Shape  (41,)   (41,) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

drF

(Z)

float32

dask.array<chunksize=(1,), meta=np.ndarray>

long_name :: cell z size
standard_name :: cell_z_size
units :: m





  
      Array  Chunk 
  
  
     Bytes  160 B   4 B 
     Shape  (40,)   (1,) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

dxC

(YC, XG)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YC XG
long_name :: cell x size
standard_name :: cell_x_size_at_u_location
units :: m





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

dxG

(YG, XC)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YG XC
long_name :: cell x size
standard_name :: cell_x_size_at_v_location
units :: m





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

dyC

(YG, XC)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YG XC
long_name :: cell y size
standard_name :: cell_y_size_at_v_location
units :: m





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

dyG

(YC, XG)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YC XG
long_name :: cell y size
standard_name :: cell_y_size_at_u_location
units :: m





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

hFacC

(Z, YC, XC)

float32

dask.array<chunksize=(1, 400, 400), meta=np.ndarray>

long_name :: vertical fraction of open cell
standard_name :: cell_vertical_fraction





  
      Array  Chunk 
  
  
     Bytes  25.60 MB   640.00 kB 
     Shape  (40, 400, 400)   (1, 400, 400) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

hFacS

(Z, YG, XC)

float32

dask.array<chunksize=(1, 400, 400), meta=np.ndarray>

long_name :: vertical fraction of open cell
standard_name :: cell_vertical_fraction_at_v_location





  
      Array  Chunk 
  
  
     Bytes  25.60 MB   640.00 kB 
     Shape  (40, 400, 400)   (1, 400, 400) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

hFacW

(Z, YC, XG)

float32

dask.array<chunksize=(1, 400, 400), meta=np.ndarray>

long_name :: vertical fraction of open cell
standard_name :: cell_vertical_fraction_at_u_location





  
      Array  Chunk 
  
  
     Bytes  25.60 MB   640.00 kB 
     Shape  (40, 400, 400)   (1, 400, 400) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

iter

(time)

int64

dask.array<chunksize=(35,), meta=np.ndarray>

long_name :: model timestep number
standard_name :: timestep





  
      Array  Chunk 
  
  
     Bytes  15.84 kB   280 B 
     Shape  (1980,)   (35,) 
     Count  58 Tasks  57 Chunks 
     Type  int64  numpy.ndarray

layer_1TH_bounds

(layer_1TH_bounds)

float32

-0.2 0.0 0.2 0.4 ... 7.8 8.0 8.2

axis :: 1TH
c_grid_axis_shift :: -0.5
long_name :: boundaries points of layer 1TH
standard_name :: ocean_layer_coordinate_1TH_bounds

array([-0.2,  0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,
        2.2,  2.4,  2.6,  2.8,  3. ,  3.2,  3.4,  3.6,  3.8,  4. ,  4.2,  4.4,
        4.6,  4.8,  5. ,  5.2,  5.4,  5.6,  5.8,  6. ,  6.2,  6.4,  6.6,  6.8,
        7. ,  7.2,  7.4,  7.6,  7.8,  8. ,  8.2], dtype=float32)

layer_1TH_center

(layer_1TH_center)

float32

-0.1 0.1 0.3 0.5 ... 7.7 7.9 8.1

axis :: 1TH
long_name :: center points of layer 1TH
standard_name :: ocean_layer_coordinate_1TH_center

array([-0.1,  0.1,  0.3,  0.5,  0.7,  0.9,  1.1,  1.3,  1.5,  1.7,  1.9,  2.1,
        2.3,  2.5,  2.7,  2.9,  3.1,  3.3,  3.5,  3.7,  3.9,  4.1,  4.3,  4.5,
        4.7,  4.9,  5.1,  5.3,  5.5,  5.7,  5.9,  6.1,  6.3,  6.5,  6.7,  6.9,
        7.1,  7.3,  7.5,  7.7,  7.9,  8.1], dtype=float32)

layer_1TH_interface

(layer_1TH_interface)

float32

0.0 0.2 0.4 0.6 ... 7.4 7.6 7.8 8.0

axis :: 1TH
c_grid_axis_shift :: -0.5
long_name :: interface points of layer 1TH
standard_name :: ocean_layer_coordinate_1TH_interface

array([0. , 0.2, 0.4, 0.6, 0.8, 1. , 1.2, 1.4, 1.6, 1.8, 2. , 2.2, 2.4, 2.6,
       2.8, 3. , 3.2, 3.4, 3.6, 3.8, 4. , 4.2, 4.4, 4.6, 4.8, 5. , 5.2, 5.4,
       5.6, 5.8, 6. , 6.2, 6.4, 6.6, 6.8, 7. , 7.2, 7.4, 7.6, 7.8, 8. ],
      dtype=float32)

maskC

(Z, YC, XC)

bool

dask.array<chunksize=(1, 400, 400), meta=np.ndarray>

long_name :: mask denoting wet point at center
standard_name :: sea_binary_mask_at_t_location





  
      Array  Chunk 
  
  
     Bytes  6.40 MB   160.00 kB 
     Shape  (40, 400, 400)   (1, 400, 400) 
     Count  41 Tasks  40 Chunks 
     Type  bool  numpy.ndarray

maskS

(Z, YG, XC)

bool

dask.array<chunksize=(1, 400, 400), meta=np.ndarray>

long_name :: mask denoting wet point at interface
standard_name :: cell_vertical_fraction_at_v_location





  
      Array  Chunk 
  
  
     Bytes  6.40 MB   160.00 kB 
     Shape  (40, 400, 400)   (1, 400, 400) 
     Count  41 Tasks  40 Chunks 
     Type  bool  numpy.ndarray

maskW

(Z, YC, XG)

bool

dask.array<chunksize=(1, 400, 400), meta=np.ndarray>

long_name :: mask denoting wet point at interface
standard_name :: cell_vertical_fraction_at_u_location





  
      Array  Chunk 
  
  
     Bytes  6.40 MB   160.00 kB 
     Shape  (40, 400, 400)   (1, 400, 400) 
     Count  41 Tasks  40 Chunks 
     Type  bool  numpy.ndarray

(YC, XC)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YC XC
long_name :: cell area
standard_name :: cell_area
units :: m2





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

rAs

(YG, XC)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

long_name :: cell area
standard_name :: cell_area_at_v_location
units :: m2





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

rAw

(YC, XG)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YG XC
long_name :: cell area
standard_name :: cell_area_at_u_location
units :: m2





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

rAz

(YG, XG)

float32

dask.array<chunksize=(400, 400), meta=np.ndarray>

coordinate :: YG XG
long_name :: cell area
standard_name :: cell_area_at_f_location
units :: m





  
      Array  Chunk 
  
  
     Bytes  640.00 kB   640.00 kB 
     Shape  (400, 400)   (400, 400) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

time

(time)

timedelta64[ns]

61023 days ... 66960 days

axis :: T
calendar :: gregorian
long_name :: Time
standard_name :: time

array([5272387200000000000, 5272646400000000000, 5272905600000000000, ...,
       5784825600000000000, 5785084800000000000, 5785344000000000000],
      dtype='timedelta64[ns]')

Data variables: (27)

Eta

(time, YC, XC)

float32

dask.array<chunksize=(35, 400, 400), meta=np.ndarray>

long_name :: Surface Height Anomaly
standard_name :: ETAN
units :: m





  
      Array  Chunk 
  
  
     Bytes  1.27 GB   22.40 MB 
     Shape  (1980, 400, 400)   (35, 400, 400) 
     Count  58 Tasks  57 Chunks 
     Type  float32  numpy.ndarray

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Hydrostatic Pressure Pot.(p/rho) Anomaly
standard_name :: sea_water_dynamic_pressue
units :: m2 s-2





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PHL

(time, YC, XC)

float32

dask.array<chunksize=(35, 400, 400), meta=np.ndarray>

long_name :: Bottom Pressure Pot.(p/rho) Anomaly
standard_name :: sea_water_dynamic_pressure_at_sea_floor
units :: m2 s-2





  
      Array  Chunk 
  
  
     Bytes  1.27 GB   22.40 MB 
     Shape  (1980, 400, 400)   (35, 400, 400) 
     Count  58 Tasks  57 Chunks 
     Type  float32  numpy.ndarray

PTRACER01

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER01
standard_name :: PTRACER01_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER02

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER02
standard_name :: PTRACER02_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER03

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER03
standard_name :: PTRACER03_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER04

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER04
standard_name :: PTRACER04_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER05

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER05
standard_name :: PTRACER05_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER06

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER06
standard_name :: PTRACER06_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER07

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER07
standard_name :: PTRACER07_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER08

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER08
standard_name :: PTRACER08_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER09

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER09
standard_name :: PTRACER09_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER10

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER10
standard_name :: PTRACER10_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER11

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER11
standard_name :: PTRACER11_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER12

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER12
standard_name :: PTRACER12_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER13

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER13
standard_name :: PTRACER13_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER14

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER14
standard_name :: PTRACER14_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER15

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER15
standard_name :: PTRACER15_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER16

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER16
standard_name :: PTRACER16_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER17

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER17
standard_name :: PTRACER17_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER18

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER18
standard_name :: PTRACER18_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER19

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER19
standard_name :: PTRACER19_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

PTRACER20

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Concentration of PTRACER20
standard_name :: PTRACER20_concentration
units :: kg m-3





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

(time, Z, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Potential Temperature
standard_name :: sea_water_potential_temperature
units :: degree_Celcius





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

(time, Z, YC, XG)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Zonal Component of Velocity
mate :: V
standard_name :: sea_water_x_velocity
units :: m s-1





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

(time, Z, YG, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Meridional Component of Velocity
mate :: U
standard_name :: sea_water_y_velocity
units :: m s-1





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

(time, Zl, YC, XC)

float32

dask.array<chunksize=(35, 1, 400, 400), meta=np.ndarray>

long_name :: Vertical Component of Velocity
standard_name :: sea_water_z_velocity
units :: m s-1





  
      Array  Chunk 
  
  
     Bytes  50.69 GB   22.40 MB 
     Shape  (1980, 40, 400, 400)   (35, 1, 400, 400) 
     Count  2281 Tasks  2280 Chunks 
     Type  float32  numpy.ndarray

Attributes: (0)