GFDL_CM2_6_grid

GFDL CM2.6 climate model ocean grid

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/pangeo-data/pangeo-datastore/master/intake-catalogs/ocean/GFDL_CM2.6.yaml")
ds  = cat["GFDL_CM2_6_grid"].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

url	https://www.gfdl.noaa.gov/cm2-6/
tags	['ocean', 'model']

Dataset Contents

xarray.Dataset

Dimensions:
- st_edges_ocean: 51
- st_ocean: 50
- sw_edges_ocean: 51
- sw_ocean: 50
- xt_ocean: 3600
- xu_ocean: 3600
- yt_ocean: 2700
- yu_ocean: 2700

Coordinates: (27)

area_t

(yt_ocean, xt_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: tracer cell area
units :: m^2
valid_range :: [0.0, 999999986991104.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

area_u

(yu_ocean, xu_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: velocity cell area
units :: m^2
valid_range :: [0.0, 999999986991104.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

dxt

(yt_ocean, xt_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: width of T_cell
units :: m





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

dxu

(yu_ocean, xu_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: width of C_cell
units :: m





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

dyt

(yt_ocean, xt_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: height of T_cell
units :: m





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

dyu

(yu_ocean, xu_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: height of C_cell
units :: m





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

geolat_c

(yu_ocean, xu_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: uv latitude
units :: degrees_N
valid_range :: [-91.0, 91.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

geolat_e

(yt_ocean, xu_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: Geographic latitude of E_cell centers
units :: degree_north





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

geolat_n

(yu_ocean, xt_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: Geographic latitude of N_cell centers
units :: degree_north





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

geolat_t

(yt_ocean, xt_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: tracer latitude
units :: degrees_N
valid_range :: [-91.0, 91.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

geolon_c

(yu_ocean, xu_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: uv longitude
units :: degrees_E
valid_range :: [-281.0, 361.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

geolon_e

(yt_ocean, xu_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: Geographic longitude of E_cell centers
units :: degree_east





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

geolon_n

(yu_ocean, xt_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: Geographic longitude of N_cell centers
units :: degree_east





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

geolon_t

(yt_ocean, xt_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: tracer longitude
units :: degrees_E
valid_range :: [-281.0, 361.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

(yt_ocean, xt_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: ocean depth on t-cells
standard_name :: sea_floor_depth_below_geoid
units :: m
valid_range :: [-1000000000.0, 1000000000.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

(yu_ocean, xu_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: ocean depth on u-cells
units :: m
valid_range :: [-1000000000.0, 1000000000.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

kmt

(yt_ocean, xt_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: number of depth levels on t-grid
units :: dimensionless
valid_range :: [-10.0, 1000000000.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

kmu

(yu_ocean, xu_ocean)

float32

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

cell_methods :: time: point
long_name :: number of depth levels on u-grid
units :: dimensionless
valid_range :: [-10.0, 1000000000.0]





  
      Array  Chunk 
  
  
     Bytes  38.88 MB   38.88 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float32  numpy.ndarray

st_edges_ocean

(st_edges_ocean)

float64

0.0 10.07 ... 5.29e+03 5.5e+03

cartesian_axis :: Z
long_name :: tcell zstar depth edges
positive :: down
units :: meters

array([   0.      ,   10.0671  ,   20.16    ,   30.2889  ,   40.4674  ,
         50.714802,   61.057499,   71.532303,   82.189903,   93.100098,
        104.359703,  116.101402,  128.507599,  141.827606,  156.400208,
        172.683105,  191.287704,  213.020096,  238.922699,  270.309509,
        308.779297,  356.186401,  414.545685,  485.854401,  571.842773,
        673.697571,  791.842773,  925.85437 , 1074.545654, 1236.186401,
       1408.779297, 1590.30957 , 1778.922729, 1973.020142, 2171.287598,
       2372.683105, 2576.400146, 2781.827637, 2988.507568, 3196.101562,
       3404.359619, 3613.100098, 3822.189941, 4031.532227, 4241.057617,
       4450.714844, 4660.467285, 4870.289062, 5080.160156, 5290.066895,
       5500.      ])

st_ocean

(st_ocean)

float64

5.034 15.1 ... 5.185e+03 5.395e+03

cartesian_axis :: Z
edges :: st_edges_ocean
long_name :: tcell zstar depth
positive :: down
units :: meters

array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,
       5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,
       1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,
       1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,
       3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,
       7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,
       1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,
       2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,
       3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,
       4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03])

sw_edges_ocean

(sw_edges_ocean)

float64

5.034 15.1 ... 5.395e+03 5.5e+03

cartesian_axis :: Z
long_name :: ucell zstar depth edges
positive :: down
units :: meters

array([5.033550e+00, 1.510065e+01, 2.521935e+01, 3.535845e+01, 4.557635e+01,
       5.585325e+01, 6.626175e+01, 7.680285e+01, 8.757695e+01, 9.862325e+01,
       1.100962e+02, 1.221067e+02, 1.349086e+02, 1.487466e+02, 1.640538e+02,
       1.813125e+02, 2.012630e+02, 2.247773e+02, 2.530681e+02, 2.875508e+02,
       3.300078e+02, 3.823651e+02, 4.467263e+02, 5.249824e+02, 6.187031e+02,
       7.286921e+02, 8.549935e+02, 9.967153e+02, 1.152376e+03, 1.319997e+03,
       1.497562e+03, 1.683057e+03, 1.874788e+03, 2.071252e+03, 2.271323e+03,
       2.474043e+03, 2.678757e+03, 2.884898e+03, 3.092117e+03, 3.300086e+03,
       3.508633e+03, 3.717567e+03, 3.926813e+03, 4.136251e+03, 4.345864e+03,
       4.555566e+03, 4.765369e+03, 4.975209e+03, 5.185111e+03, 5.395023e+03,
       5.500000e+03])

sw_ocean

(sw_ocean)

float64

10.07 20.16 ... 5.29e+03 5.5e+03

cartesian_axis :: Z
edges :: sw_edges_ocean
long_name :: ucell zstar depth
positive :: down
units :: meters

array([  10.0671  ,   20.16    ,   30.2889  ,   40.4674  ,   50.714802,
         61.057499,   71.532303,   82.189903,   93.100098,  104.359703,
        116.101402,  128.507599,  141.827606,  156.400208,  172.683105,
        191.287704,  213.020096,  238.922699,  270.309509,  308.779297,
        356.186401,  414.545685,  485.854401,  571.842773,  673.697571,
        791.842773,  925.85437 , 1074.545654, 1236.186401, 1408.779297,
       1590.30957 , 1778.922729, 1973.020142, 2171.287598, 2372.683105,
       2576.400146, 2781.827637, 2988.507568, 3196.101562, 3404.359619,
       3613.100098, 3822.189941, 4031.532227, 4241.057617, 4450.714844,
       4660.467285, 4870.289062, 5080.160156, 5290.066895, 5500.      ])

wet

(yt_ocean, xt_ocean)

float64

dask.array<chunksize=(2700, 3600), meta=np.ndarray>

long_name :: land/sea flag (0=land) for T-cell
units :: none





  
      Array  Chunk 
  
  
     Bytes  77.76 MB   77.76 MB 
     Shape  (2700, 3600)   (2700, 3600) 
     Count  2 Tasks  1 Chunks 
     Type  float64  numpy.ndarray

xt_ocean
(xt_ocean)
float64
-279.9 -279.8 ... 79.85 79.95
cartesian_axis :
X
long_name :
tcell longitude
units :
degrees_E
```
array([-279.95, -279.85, -279.75, ...,   79.75,   79.85,   79.95])
```
xu_ocean
(xu_ocean)
float64
-279.9 -279.8 -279.7 ... 79.9 80.0
cartesian_axis :
X
long_name :
ucell longitude
units :
degrees_E
```
array([-279.9, -279.8, -279.7, ...,   79.8,   79.9,   80. ])
```
yt_ocean
(yt_ocean)
float64
-81.11 -81.07 ... 89.94 89.98
cartesian_axis :
Y
long_name :
tcell latitude
units :
degrees_N
```
array([-81.108632, -81.066392, -81.024153, ...,  89.894417,  89.936657,
        89.978896])
```
yu_ocean
(yu_ocean)
float64
-81.09 -81.05 -81.0 ... 89.96 90.0
cartesian_axis :
Y
long_name :
ucell latitude
units :
degrees_N
```
array([-81.087512, -81.045273, -81.003033, ...,  89.915537,  89.957776,
        90.      ])
```

Data variables: (0)
Attributes: (1)
NCO :
4.0.3