GODAS

NCEP Global Ocean Data Assimilation System

Load in Python

from intake import open_catalog

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

uploader_github	rabernat
uploader_email	rpa@ldeo.columbia.edu
url	https://www.esrl.noaa.gov/psd/data/gridded/data.godas.html
tags	['ocean', 'data assimilation']

Dataset Contents

xarray.Dataset

Dimensions:
- lat: 417
- lat_u: 417
- level: 40
- level_w: 40
- lon: 360
- lon_u: 360
- time: 471
Coordinates: (7)
- lat
  (lat)
  float32
  -74.16667 -73.83334 ... 64.499
  GridType :
  Cylindrical Equidistant Projection Grid
  actual_range :
  [-74.5, 64.4990005493164]
  axis :
  Y
  long_name :
  latitude
  standard_name :
  latitude
  units :
  degrees_north
```
array([-74.16667, -73.83334, -73.50001, ...,  63.83234,  64.16566,  64.499  ],
      dtype=float32)
```
- lat_u
  (lat_u)
  float32
  -74.0 -73.66667 ... 64.66566
  GridType :
  Cylindrical Equidistant Projection Grid
  actual_range :
  [-74.0, 64.9990005493164]
  axis :
  Y
  long_name :
  latitude
  standard_name :
  latitude
  units :
  degrees_north
```
array([-74.     , -73.66667, -73.33334, ...,  63.99901,  64.33234,  64.66566],
      dtype=float32)
```
- level
  (level)
  float32
  5.0 15.0 25.0 ... 3972.0 4478.0
  actual_range :
  [5.0, 4478.0]
  axis :
  Z
  long_name :
  depth below sea level
  positive :
  down
  units :
  m
```
array([   5.,   15.,   25.,   35.,   45.,   55.,   65.,   75.,   85.,   95.,
        105.,  115.,  125.,  135.,  145.,  155.,  165.,  175.,  185.,  195.,
        205.,  215.,  225.,  238.,  262.,  303.,  366.,  459.,  584.,  747.,
        949., 1193., 1479., 1807., 2174., 2579., 3016., 3483., 3972., 4478.],
      dtype=float32)
```
- level_w
  (level_w)
  float32
  10.0 20.0 30.0 ... 4225.0 4736.0
  actual_range :
  [10.0, 4736.0]
  axis :
  Z
  long_name :
  depth below sea level
  positive :
  down
  units :
  m
```
array([  10.,   20.,   30.,   40.,   50.,   60.,   70.,   80.,   90.,  100.,
        110.,  120.,  130.,  140.,  150.,  160.,  170.,  180.,  190.,  200.,
        210.,  220.,  231.,  250.,  282.,  334.,  412.,  521.,  665.,  848.,
       1071., 1336., 1643., 1990., 2376., 2797., 3249., 3727., 4225., 4736.],
      dtype=float32)
```
- lon
  (lon)
  float32
  0.5 1.5 2.5 ... 357.5 358.5 359.5
  GridType :
  Cylindrical Equidistant Projection Grid
  actual_range :
  [0.5, 359.5]
  axis :
  X
  long_name :
  longitude
  standard_name :
  longitude
  units :
  degrees_east
```
array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)
```
- lon_u
  (lon_u)
  float32
  1.0 2.0 3.0 ... 358.0 359.0 360.0
  GridType :
  Cylindrical Equidistant Projection Grid
  actual_range :
  [1.0, 360.0]
  axis :
  X
  long_name :
  longitude
  standard_name :
  longitude
  units :
  degrees_east
```
array([  1.,   2.,   3., ..., 358., 359., 360.], dtype=float32)
```
- time
  (time)
  datetime64[ns]
  1980-01-01 ... 2019-03-01
  avg_period :
  0000-01-00 00:00:00
  axis :
  T
  delta_t :
  0000-01-00 00:00:00
  info :
  This is the FIRST day of the averaging period.
  long_name :
  time
  standard_name :
  time
```
array(['1980-01-01T00:00:00.000000000', '1980-02-01T00:00:00.000000000',
       '1980-03-01T00:00:00.000000000', ..., '2019-01-01T00:00:00.000000000',
       '2019-02-01T00:00:00.000000000', '2019-03-01T00:00:00.000000000'],
      dtype='datetime64[ns]')
```

Data variables: (12)

dbss_obil

(time, lat, lon)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: unknown
level_indicator :: 238
long_name :: Geometric Depth Below Sea Surface
parameter_number :: 195
parameter_table_version :: 129
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: m
unpacked_valid_range :: [0.0, 5000.0]
valid_range :: [-16383, 16383]
var_desc :: ocean isothermal layer depth below sea surface





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

dbss_obml

(time, lat, lon)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: unknown
level_indicator :: 237
long_name :: Geometric Depth Below Sea Surface
parameter_number :: 195
parameter_table_version :: 129
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: m
unpacked_valid_range :: [0.0, 5000.0]
valid_range :: [-16383, 16383]
var_desc :: ocean mixed layer depth below sea surface





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

dzdt

(time, level_w, lat, lon)

float32

dask.array<chunksize=(4, 40, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: Multiple Levels
level_indicator :: 160
long_name :: Geometric vertical velocity
parameter_number :: 40
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: m/s
unpacked_valid_range :: [-0.0020000000949949026, 0.0020000000949949026]
valid_range :: [-16384, 16384]
var_desc :: geometric vertical velocity





  
      Array  Chunk 
  
  
     Bytes  11.31 GB   96.08 MB 
     Shape  (471, 40, 417, 360)   (4, 40, 417, 360) 
     Count  119 Tasks  118 Chunks 
     Type  float32  numpy.ndarray

pottmp

(time, level, lat, lon)

float32

dask.array<chunksize=(4, 40, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: Multiple Levels
level_indicator :: 160
long_name :: Potential temperature
parameter_number :: 13
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: K
unpacked_valid_range :: [260.0, 310.0]
valid_range :: [-16384, 16384]
var_desc :: potential temperature





  
      Array  Chunk 
  
  
     Bytes  11.31 GB   96.08 MB 
     Shape  (471, 40, 417, 360)   (4, 40, 417, 360) 
     Count  119 Tasks  118 Chunks 
     Type  float32  numpy.ndarray

salt

(time, level, lat, lon)

float32

dask.array<chunksize=(4, 40, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: Multiple Levels
level_indicator :: 160
long_name :: Salinity
parameter_number :: 88
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: kg/kg
unpacked_valid_range :: [0.0, 0.10000000149011612]
valid_range :: [-16384, 16384]
var_desc :: salinity





  
      Array  Chunk 
  
  
     Bytes  11.31 GB   96.08 MB 
     Shape  (471, 40, 417, 360)   (4, 40, 417, 360) 
     Count  119 Tasks  118 Chunks 
     Type  float32  numpy.ndarray

sltfl

(time, lat, lon)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: surface
level_indicator :: 1
long_name :: Salt Flux
parameter_number :: 199
parameter_table_version :: 129
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: g/cm2/s
unpacked_valid_range :: [-3.999999989900971e-06, 8.000000093488779e-07]
valid_range :: [-16384, 16384]
var_desc :: salt flux





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

sshg

(time, lat, lon)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: surface
level_indicator :: 1
long_name :: Sea Surface Height Relative to Geoid
parameter_number :: 198
parameter_table_version :: 129
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: m
unpacked_valid_range :: [-3.0, 3.0]
valid_range :: [-16383, 16383]
var_desc :: sea surface height relative to geoid





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

thflx

(time, lat, lon)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: surface
level_indicator :: 1
long_name :: Total downward heat flux at surface (downward is positive)
parameter_number :: 202
parameter_table_version :: 129
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: W/m2
unpacked_valid_range :: [-1400.0, 1400.0]
valid_range :: [-16384, 16384]
var_desc :: total downward heat flux at surface





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

ucur

(time, level, lat_u, lon_u)

float32

dask.array<chunksize=(4, 40, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: Multiple Levels
level_indicator :: 160
long_name :: u-component of current
parameter_number :: 49
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: m/s
unpacked_valid_range :: [-2.0, 2.0]
valid_range :: [-16384, 16384]
var_desc :: u of current





  
      Array  Chunk 
  
  
     Bytes  11.31 GB   96.08 MB 
     Shape  (471, 40, 417, 360)   (4, 40, 417, 360) 
     Count  119 Tasks  118 Chunks 
     Type  float32  numpy.ndarray

uflx

(time, lat_u, lon_u)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: surface
level_indicator :: 1
long_name :: Momentum flux, u component
parameter_number :: 124
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: N/m^2
unpacked_valid_range :: [-2.0, 2.0]
valid_range :: [-16384, 16384]
var_desc :: zonal momentum flux





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

vcur

(time, level, lat_u, lon_u)

float32

dask.array<chunksize=(4, 40, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: Multiple Levels
level_indicator :: 160
long_name :: v-component of current
parameter_number :: 50
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: m/s
unpacked_valid_range :: [-2.0, 2.0]
valid_range :: [-16384, 16384]
var_desc :: v of current





  
      Array  Chunk 
  
  
     Bytes  11.31 GB   96.08 MB 
     Shape  (471, 40, 417, 360)   (4, 40, 417, 360) 
     Count  119 Tasks  118 Chunks 
     Type  float32  numpy.ndarray

vflx

(time, lat_u, lon_u)

float32

dask.array<chunksize=(12, 417, 360), meta=np.ndarray>

center :: US National Weather Service - NCEP (WMC)
dataset :: NCEP GODAS
gds_grid_type :: 0
level_desc :: surface
level_indicator :: 1
long_name :: Momentum flux, v component
parameter_number :: 125
parameter_table_version :: 2
parent_stat :: Individual Obs
statistic :: Monthly Mean
sub_center :: Environmental Modeling Center
units :: N/m^2
unpacked_valid_range :: [-2.0, 2.0]
valid_range :: [-16384, 16384]
var_desc :: meridional momentum flux





  
      Array  Chunk 
  
  
     Bytes  282.83 MB   7.21 MB 
     Shape  (471, 417, 360)   (12, 417, 360) 
     Count  41 Tasks  40 Chunks 
     Type  float32  numpy.ndarray

Attributes: (13)
Conventions :
COARDS
References :
https://www.esrl.noaa.gov/psd/data/gridded/data.godas.html
comment :
NOTE: THESE ARE THE BIAS CORRECTED GODAS FILES.
creation_date :
Sat Dec 16 20:00:00 MDT 2006
dataset_title :
NCEP Global Ocean Data Assimilation System (GODAS)
grib_file :
godas.M.198001-12.grb
history :
Created 2006/12 by Hoop
html_BACKGROUND :
http://www.cpc.ncep.noaa.gov/products/GODAS/background.shtml
html_GODAS :
www.cpc.ncep.noaa.gov/products/GODAS
html_REFERENCES :
http://www.cpc.ncep.noaa.gov/products/GODAS/background.shtml
sfcHeatFlux :
Note that the net surface heat flux are the total surface heat flux from the NCEP reanalysis 2 plus the relaxation terms.
time_comment :
The internal time stamp indicates the FIRST day of the averaging period.
title :
GODAS: Global Ocean Data Assimilation System