0. Getting Started with xarray

NOC Near-Present Day Hackathon¶

Tutorial 0. Getting Started with xarray for Ocean Science¶

Contact:¶

Ollie Tooth (oliver.tooth@noc.ac.uk)

Background:¶

Ocean models produce large, multi-dimensional fields (e.g. temperature, salinity, velocity) that vary in time and space and are described by physical coordinates (e.g., depth). Additionally, scalar and vector output variables are often stored on different, staggered model grids (e.g., Arakawa A-, B-, C-grids), meaning that we must often transform variables prior to performing any computations.

xarray is an open-source Python library which provides data structures that explicitly represent the physical coordinates, rather than treating model outputs as anonymous multi-dimensional arrays. In practice, this means we can perform dimension-aware computations using dimension labels, such as time, depth, etc., which automatically align variables stored on the same grid or sharing the same time dimension.

This Tutorial provides an introduction to xarray for ocean model analysis and is intended as a quick reference that you can return to during the hackathon and beyond.

We will cover:

How to...

1.1 Basics¶

xarray extends the NumPy and pandas Python libraries to handle labelled, multi-dimensional arrays.

Fundamental Ideas:

Each dimensions has a name (e.g., "time", "depth", "lat", "lon").
Coordinates are attached to dimensions (e.g., depth values in meters).
Metadata (units, long_name, etc.) are preserved.

Key advantages:

Labelled dimensions → No guessing axis order.
Automatic alignment & broadcasting → Safer calculations.
Lazy loading + Dask support → scalable to large datasets O(TBs).
Seamless reading & writing of NetCDF files
Integrated plotting features

Core Data Structures:

DataArray: a single variable + coordinates + attributes
Dataset: a collection of DataArrays sharing coordinates
DataTree: a tree-like hierarchical collection of xarray DataArray or Dataset objects.

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import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr
import matplotlib.pyplot as plt

1.2 Opening a Dataset¶

xarray includes several example datasets.

Here, we will use the NOAA Extended Reconstructed global Sea Surface Temperature (SST) monthly averages dataset.

This is similar in structure to typical ocean model surface output:

Dimensions: time × lat × lon
Variable: sst
Includes metadata and coordinates

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ds = xr.tutorial.load_dataset("ersstv5")
ds
ds = xr.tutorial.load_dataset("ersstv5")
ds

Out[3]:

<xarray.Dataset> Size: 40MB
Dimensions:    (time: 624, nbnds: 2, lat: 89, lon: 180)
Coordinates:
  * time       (time) datetime64[ns] 5kB 1970-01-01 1970-02-01 ... 2021-12-01
  * lat        (lat) float32 356B 88.0 86.0 84.0 82.0 ... -84.0 -86.0 -88.0
  * lon        (lon) float32 720B 0.0 2.0 4.0 6.0 ... 352.0 354.0 356.0 358.0
Dimensions without coordinates: nbnds
Data variables:
    time_bnds  (time, nbnds) float64 10kB 9.969e+36 9.969e+36 ... 9.969e+36
    sst        (time, lat, lon) float32 40MB -1.8 -1.8 -1.8 -1.8 ... nan nan nan
Attributes: (12/37)
    climatology:               Climatology is based on 1971-2000 SST, Xue, Y....
    description:               In situ data: ICOADS2.5 before 2007 and NCEP i...
    keywords_vocabulary:       NASA Global Change Master Directory (GCMD) Sci...
    keywords:                  Earth Science > Oceans > Ocean Temperature > S...
    instrument:                Conventional thermometers
    source_comment:            SSTs were observed by conventional thermometer...
    ...                        ...
    creator_url_original:      https://www.ncei.noaa.gov
    license:                   No constraints on data access or use
    comment:                   SSTs were observed by conventional thermometer...
    summary:                   ERSST.v5 is developed based on v4 after revisi...
    dataset_title:             NOAA Extended Reconstructed SST V5
    data_modified:             2022-06-07

xarray.Dataset

Dimensions:
- time: 624
- nbnds: 2
- lat: 89
- lon: 180

Coordinates: (3)

time

(time)

datetime64[ns]

1970-01-01 ... 2021-12-01

long_name :: Time
delta_t :: 0000-01-00 00:00:00
avg_period :: 0000-01-00 00:00:00
prev_avg_period :: 0000-00-07 00:00:00
standard_name :: time
axis :: T
actual_range :: [19723. 81204.]

array(['1970-01-01T00:00:00.000000000', '1970-02-01T00:00:00.000000000',
       '1970-03-01T00:00:00.000000000', ..., '2021-10-01T00:00:00.000000000',
       '2021-11-01T00:00:00.000000000', '2021-12-01T00:00:00.000000000'],
      shape=(624,), dtype='datetime64[ns]')

lat

(lat)

float32

88.0 86.0 84.0 ... -86.0 -88.0

units :: degrees_north
long_name :: Latitude
actual_range :: [ 88. -88.]
standard_name :: latitude
axis :: Y
coordinate_defines :: center

array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,
        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,
        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,
        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,
       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,
       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,
       -80., -82., -84., -86., -88.], dtype=float32)

lon

(lon)

float32

0.0 2.0 4.0 ... 354.0 356.0 358.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,
        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,
        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,
        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,
       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,
       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,
       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,
       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,
       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,
       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,
       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,
       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,
       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,
       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],
      dtype=float32)

Data variables: (2)

time_bnds

(time, nbnds)

float64

9.969e+36 9.969e+36 ... 9.969e+36

long_name :: Time Boundaries

array([[9.96920997e+36, 9.96920997e+36],
       [9.96920997e+36, 9.96920997e+36],
       [9.96920997e+36, 9.96920997e+36],
       ...,
       [9.96920997e+36, 9.96920997e+36],
       [9.96920997e+36, 9.96920997e+36],
       [9.96920997e+36, 9.96920997e+36]], shape=(624, 2))

sst

(time, lat, lon)

float32

-1.8 -1.8 -1.8 -1.8 ... nan nan nan

long_name :: Monthly Means of Sea Surface Temperature
units :: degC
var_desc :: Sea Surface Temperature
level_desc :: Surface
statistic :: Mean
dataset :: NOAA Extended Reconstructed SST V5
parent_stat :: Individual Values
actual_range :: [-1.8 42.32636]
valid_range :: [-1.8 45. ]

array([[[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        ...,
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],

       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        ...,
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],

       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        ...,
...
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],

       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        ...,
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],

       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
        ...,
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan],
        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]],
      shape=(624, 89, 180), dtype=float32)

Attributes: (37)
climatology :
Climatology is based on 1971-2000 SST, Xue, Y., T. M. Smith, and R. W. Reynolds, 2003: Interdecadal changes of 30-yr SST normals during 1871.2000. Journal of Climate, 16, 1601-1612.
description :
In situ data: ICOADS2.5 before 2007 and NCEP in situ data from 2008 to present. Ice data: HadISST ice before 2010 and NCEP ice after 2010.
keywords_vocabulary :
NASA Global Change Master Directory (GCMD) Science Keywords
keywords :
Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature >
instrument :
Conventional thermometers
source_comment :
SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets) or Engine Room Intaker
geospatial_lon_min :
-1.0
geospatial_lon_max :
359.0
geospatial_laty_max :
89.0
geospatial_laty_min :
-89.0
geospatial_lat_max :
89.0
geospatial_lat_min :
-89.0
geospatial_lat_units :
degrees_north
geospatial_lon_units :
degrees_east
cdm_data_type :
Grid
project :
NOAA Extended Reconstructed Sea Surface Temperature (ERSST)
original_publisher_url :
http://www.ncdc.noaa.gov
References :
https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v5 at NCEI and http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.ersst.v5.html
source :
In situ data: ICOADS R3.0 before 2015, NCEP in situ GTS from 2016 to present, and Argo SST from 1999 to present. Ice data: HadISST2 ice before 2015, and NCEP ice after 2015
title :
NOAA ERSSTv5 (in situ only)
history :
created 07/2017 by PSD data using NCEI's ERSST V5 NetCDF values
institution :
This version written at NOAA/ESRL PSD: obtained from NOAA/NESDIS/National Centers for Environmental Information and time aggregated. Original Full Source: NOAA/NESDIS/NCEI/CCOG
citation :
Huang et al, 2017: Extended Reconstructed Sea Surface Temperatures Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons. Journal of Climate, https://doi.org/10.1175/JCLI-D-16-0836.1
platform :
Ship and Buoy SSTs from ICOADS R3.0 and NCEP GTS
standard_name_vocabulary :
CF Standard Name Table (v40, 25 January 2017)
processing_level :
NOAA Level 4
Conventions :
CF-1.6, ACDD-1.3
metadata_link :
:metadata_link = https://doi.org/10.7289/V5T72FNM (original format)
creator_name :
Boyin Huang (original)
date_created :
2017-06-30T12:18:00Z (original)
product_version :
Version 5
creator_url_original :
https://www.ncei.noaa.gov
license :
No constraints on data access or use
comment :
SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets), Engine Room Intakers, or floats and drifters
summary :
ERSST.v5 is developed based on v4 after revisions of 8 parameters using updated data sets and advanced knowledge of ERSST analysis
dataset_title :
NOAA Extended Reconstructed SST V5
data_modified :
2022-06-07

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# Inspect dimensions, coordinates, variables
print(ds.dims)
print(ds.coords)
print(ds.data_vars)
# Inspect dimensions, coordinates, variables
print(ds.dims)
print(ds.coords)
print(ds.data_vars)

FrozenMappingWarningOnValuesAccess({'time': 624, 'nbnds': 2, 'lat': 89, 'lon': 180})
Coordinates:
  * time     (time) datetime64[ns] 5kB 1970-01-01 1970-02-01 ... 2021-12-01
  * lat      (lat) float32 356B 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0
  * lon      (lon) float32 720B 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0
Data variables:
    time_bnds  (time, nbnds) float64 10kB 9.969e+36 9.969e+36 ... 9.969e+36
    sst        (time, lat, lon) float32 40MB -1.8 -1.8 -1.8 -1.8 ... nan nan nan

1.3 Dataset & DataArray¶

xarray has two core data structures:

Dataset

Container of multiple variables stored as DataArrays
Similar to a NetCDF file in memory

DataArray

Single N-dimensional variable
Contains:
- data
- dimensions
- coordinates
- attributes

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sst = ds["sst"]

sst.dims, sst.shape
sst = ds["sst"]

sst.dims, sst.shape

Out[6]:

(('time', 'lat', 'lon'), (624, 89, 180))

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sst.coords
sst.coords

Out[7]:

Coordinates:
  * time     (time) datetime64[ns] 5kB 1970-01-01 1970-02-01 ... 2021-12-01
  * lat      (lat) float32 356B 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0
  * lon      (lon) float32 720B 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0

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sst.attrs
sst.attrs

Out[8]:

{'long_name': 'Monthly Means of Sea Surface Temperature',
 'units': 'degC',
 'var_desc': 'Sea Surface Temperature',
 'level_desc': 'Surface',
 'statistic': 'Mean',
 'dataset': 'NOAA Extended Reconstructed SST V5',
 'parent_stat': 'Individual Values',
 'actual_range': array([-1.8    , 42.32636], dtype=float32),
 'valid_range': array([-1.8, 45. ], dtype=float32)}

0.4 Indexing & Selection¶

Indexing (NumPy-style)

Uses integer positions
Fragile if dimension order changes

Selection (xarray-style)

Uses dimension names
Safer and more readable

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sst.isel(time=0)
sst.isel(time=0)

Out[9]:

<xarray.DataArray 'sst' (lat: 89, lon: 180)> Size: 64kB
array([[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       ...,
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]],
      shape=(89, 180), dtype=float32)
Coordinates:
  * lat      (lat) float32 356B 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0
  * lon      (lon) float32 720B 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0
    time     datetime64[ns] 8B 1970-01-01
Attributes:
    long_name:     Monthly Means of Sea Surface Temperature
    units:         degC
    var_desc:      Sea Surface Temperature
    level_desc:    Surface
    statistic:     Mean
    dataset:       NOAA Extended Reconstructed SST V5
    parent_stat:   Individual Values
    actual_range:  [-1.8     42.32636]
    valid_range:   [-1.8 45. ]

xarray.DataArray

'sst'

lat: 89
lon: 180

-1.8 -1.8 -1.8 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan nan nan nan

array([[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       ...,
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]],
      shape=(89, 180), dtype=float32)

Coordinates: (3)

lat

(lat)

float32

88.0 86.0 84.0 ... -86.0 -88.0

units :: degrees_north
long_name :: Latitude
actual_range :: [ 88. -88.]
standard_name :: latitude
axis :: Y
coordinate_defines :: center

array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,
        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,
        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,
        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,
       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,
       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,
       -80., -82., -84., -86., -88.], dtype=float32)

lon

(lon)

float32

0.0 2.0 4.0 ... 354.0 356.0 358.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,
        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,
        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,
        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,
       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,
       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,
       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,
       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,
       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,
       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,
       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,
       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,
       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,
       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],
      dtype=float32)

time
()
datetime64[ns]
1970-01-01
long_name :
Time
delta_t :
0000-01-00 00:00:00
avg_period :
0000-01-00 00:00:00
prev_avg_period :
0000-00-07 00:00:00
standard_name :
time
axis :
T
actual_range :
[19723. 81204.]
```
array('1970-01-01T00:00:00.000000000', dtype='datetime64[ns]')
```

Attributes: (9)
long_name :
Monthly Means of Sea Surface Temperature
units :
degC
var_desc :
Sea Surface Temperature
level_desc :
Surface
statistic :
Mean
dataset :
NOAA Extended Reconstructed SST V5
parent_stat :
Individual Values
actual_range :
[-1.8 42.32636]
valid_range :
[-1.8 45. ]

In [10]:

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sst.sel(time="1990-01-01")
sst.sel(time="1990-01-01")

Out[10]:

<xarray.DataArray 'sst' (lat: 89, lon: 180)> Size: 64kB
array([[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       ...,
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]],
      shape=(89, 180), dtype=float32)
Coordinates:
  * lat      (lat) float32 356B 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0
  * lon      (lon) float32 720B 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0
    time     datetime64[ns] 8B 1990-01-01
Attributes:
    long_name:     Monthly Means of Sea Surface Temperature
    units:         degC
    var_desc:      Sea Surface Temperature
    level_desc:    Surface
    statistic:     Mean
    dataset:       NOAA Extended Reconstructed SST V5
    parent_stat:   Individual Values
    actual_range:  [-1.8     42.32636]
    valid_range:   [-1.8 45. ]

xarray.DataArray

'sst'

lat: 89
lon: 180

-1.8 -1.8 -1.8 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan nan nan nan

array([[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],
       ...,
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]],
      shape=(89, 180), dtype=float32)

Coordinates: (3)

lat

(lat)

float32

88.0 86.0 84.0 ... -86.0 -88.0

units :: degrees_north
long_name :: Latitude
actual_range :: [ 88. -88.]
standard_name :: latitude
axis :: Y
coordinate_defines :: center

array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,
        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,
        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,
        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,
       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,
       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,
       -80., -82., -84., -86., -88.], dtype=float32)

lon

(lon)

float32

0.0 2.0 4.0 ... 354.0 356.0 358.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,
        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,
        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,
        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,
       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,
       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,
       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,
       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,
       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,
       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,
       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,
       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,
       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,
       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],
      dtype=float32)

time
()
datetime64[ns]
1990-01-01
long_name :
Time
delta_t :
0000-01-00 00:00:00
avg_period :
0000-01-00 00:00:00
prev_avg_period :
0000-00-07 00:00:00
standard_name :
time
axis :
T
actual_range :
[19723. 81204.]
```
array('1990-01-01T00:00:00.000000000', dtype='datetime64[ns]')
```

Attributes: (9)
long_name :
Monthly Means of Sea Surface Temperature
units :
degC
var_desc :
Sea Surface Temperature
level_desc :
Surface
statistic :
Mean
dataset :
NOAA Extended Reconstructed SST V5
parent_stat :
Individual Values
actual_range :
[-1.8 42.32636]
valid_range :
[-1.8 45. ]

In [11]:

Copied!

sst.sel(lat=slice(-30, 30), lon=slice(120, 280))
sst.sel(lat=slice(-30, 30), lon=slice(120, 280))

Out[11]:

<xarray.DataArray 'sst' (time: 624, lat: 0, lon: 81)> Size: 0B
array([], shape=(624, 0, 81), dtype=float32)
Coordinates:
  * time     (time) datetime64[ns] 5kB 1970-01-01 1970-02-01 ... 2021-12-01
  * lat      (lat) float32 0B 
  * lon      (lon) float32 324B 120.0 122.0 124.0 126.0 ... 276.0 278.0 280.0
Attributes:
    long_name:     Monthly Means of Sea Surface Temperature
    units:         degC
    var_desc:      Sea Surface Temperature
    level_desc:    Surface
    statistic:     Mean
    dataset:       NOAA Extended Reconstructed SST V5
    parent_stat:   Individual Values
    actual_range:  [-1.8     42.32636]
    valid_range:   [-1.8 45. ]

xarray.DataArray

'sst'

time: 624
lat: 0
lon: 81

array([], shape=(624, 0, 81), dtype=float32)

Coordinates: (3)

time

(time)

datetime64[ns]

1970-01-01 ... 2021-12-01

long_name :: Time
delta_t :: 0000-01-00 00:00:00
avg_period :: 0000-01-00 00:00:00
prev_avg_period :: 0000-00-07 00:00:00
standard_name :: time
axis :: T
actual_range :: [19723. 81204.]

array(['1970-01-01T00:00:00.000000000', '1970-02-01T00:00:00.000000000',
       '1970-03-01T00:00:00.000000000', ..., '2021-10-01T00:00:00.000000000',
       '2021-11-01T00:00:00.000000000', '2021-12-01T00:00:00.000000000'],
      shape=(624,), dtype='datetime64[ns]')

lat
(lat)
float32
units :
degrees_north
long_name :
Latitude
actual_range :
[ 88. -88.]
standard_name :
latitude
axis :
Y
coordinate_defines :
center
```
array([], dtype=float32)
```

lon

(lon)

float32

120.0 122.0 124.0 ... 278.0 280.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,
       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,
       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,
       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,
       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,
       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,
       264., 266., 268., 270., 272., 274., 276., 278., 280.], dtype=float32)

Attributes: (9)
long_name :
Monthly Means of Sea Surface Temperature
units :
degC
var_desc :
Sea Surface Temperature
level_desc :
Surface
statistic :
Mean
dataset :
NOAA Extended Reconstructed SST V5
parent_stat :
Individual Values
actual_range :
[-1.8 42.32636]
valid_range :
[-1.8 45. ]

0.4.1 Spatial Subsetting¶

Example: Tropical Pacific SSTs

In [12]:

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trop_pac = sst.sel(
    lat=slice(-10, 10),
    lon=slice(160, 260)
)

trop_pac
trop_pac = sst.sel(
    lat=slice(-10, 10),
    lon=slice(160, 260)
)

trop_pac

Out[12]:

<xarray.DataArray 'sst' (time: 624, lat: 0, lon: 51)> Size: 0B
array([], shape=(624, 0, 51), dtype=float32)
Coordinates:
  * time     (time) datetime64[ns] 5kB 1970-01-01 1970-02-01 ... 2021-12-01
  * lat      (lat) float32 0B 
  * lon      (lon) float32 204B 160.0 162.0 164.0 166.0 ... 256.0 258.0 260.0
Attributes:
    long_name:     Monthly Means of Sea Surface Temperature
    units:         degC
    var_desc:      Sea Surface Temperature
    level_desc:    Surface
    statistic:     Mean
    dataset:       NOAA Extended Reconstructed SST V5
    parent_stat:   Individual Values
    actual_range:  [-1.8     42.32636]
    valid_range:   [-1.8 45. ]

xarray.DataArray

'sst'

time: 624
lat: 0
lon: 51

array([], shape=(624, 0, 51), dtype=float32)

Coordinates: (3)

time

(time)

datetime64[ns]

1970-01-01 ... 2021-12-01

long_name :: Time
delta_t :: 0000-01-00 00:00:00
avg_period :: 0000-01-00 00:00:00
prev_avg_period :: 0000-00-07 00:00:00
standard_name :: time
axis :: T
actual_range :: [19723. 81204.]

array(['1970-01-01T00:00:00.000000000', '1970-02-01T00:00:00.000000000',
       '1970-03-01T00:00:00.000000000', ..., '2021-10-01T00:00:00.000000000',
       '2021-11-01T00:00:00.000000000', '2021-12-01T00:00:00.000000000'],
      shape=(624,), dtype='datetime64[ns]')

lat
(lat)
float32
units :
degrees_north
long_name :
Latitude
actual_range :
[ 88. -88.]
standard_name :
latitude
axis :
Y
coordinate_defines :
center
```
array([], dtype=float32)
```

lon

(lon)

float32

160.0 162.0 164.0 ... 258.0 260.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([160., 162., 164., 166., 168., 170., 172., 174., 176., 178., 180., 182.,
       184., 186., 188., 190., 192., 194., 196., 198., 200., 202., 204., 206.,
       208., 210., 212., 214., 216., 218., 220., 222., 224., 226., 228., 230.,
       232., 234., 236., 238., 240., 242., 244., 246., 248., 250., 252., 254.,
       256., 258., 260.], dtype=float32)

Attributes: (9)
long_name :
Monthly Means of Sea Surface Temperature
units :
degC
var_desc :
Sea Surface Temperature
level_desc :
Surface
statistic :
Mean
dataset :
NOAA Extended Reconstructed SST V5
parent_stat :
Individual Values
actual_range :
[-1.8 42.32636]
valid_range :
[-1.8 45. ]

0.5 Plotting¶

xarray integrates with matplotlib for fast visualisation.

In [13]:

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sst.isel(time=0).plot()
plt.title("Global SST (first timestep)")
plt.show()
sst.isel(time=0).plot()
plt.title("Global SST (first timestep)")
plt.show()

No description has been provided for this image

In [14]:

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sst_eq = sst.sel(lat=0, lon=200, method="nearest")
sst_eq.plot()
plt.title("Equatorial SST time series")
plt.show()
sst_eq = sst.sel(lat=0, lon=200, method="nearest")
sst_eq.plot()
plt.title("Equatorial SST time series")
plt.show()

0.6 Core Operations¶

0.6.1 Reduction Operations¶

Common ocean diagnostics:

Mean SST
Zonal or meridional averages
Time averages

xarray reductions explicitly name dimensions.

In [15]:

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sst_mean = sst.mean(dim="time")
sst_mean.plot()
plt.title("Mean SST")
plt.show()
sst_mean = sst.mean(dim="time")
sst_mean.plot()
plt.title("Mean SST")
plt.show()

OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.

In [16]:

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sst_zonal = sst.mean(dim="lon")
sst_zonal.plot()
plt.title("Zonal mean SST")
plt.show()
sst_zonal = sst.mean(dim="lon")
sst_zonal.plot()
plt.title("Zonal mean SST")
plt.show()

0.6.2 Group-By Operations¶

Group-By is essential for:

Seasonal cycles
Climatologies
Anomaly calculations

In [17]:

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sst_clim = sst.groupby("time.month").mean(dim="time")
sst_clim
sst_clim = sst.groupby("time.month").mean(dim="time")
sst_clim

Out[17]:

<xarray.DataArray 'sst' (month: 12, lat: 89, lon: 180)> Size: 769kB
array([[[-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        ...,
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan]],

       [[-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
...
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan]],

       [[-1.7994802, -1.7995852, -1.7998399, ..., -1.7997632,
         -1.7996233, -1.7994753],
        [-1.7995453, -1.7997496, -1.8000005, ..., -1.8000005,
         -1.799799 , -1.7995732],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        ...,
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan]]], shape=(12, 89, 180), dtype=float32)
Coordinates:
  * month    (month) int64 96B 1 2 3 4 5 6 7 8 9 10 11 12
  * lat      (lat) float32 356B 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0
  * lon      (lon) float32 720B 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0
Attributes:
    long_name:     Monthly Means of Sea Surface Temperature
    units:         degC
    var_desc:      Sea Surface Temperature
    level_desc:    Surface
    statistic:     Mean
    dataset:       NOAA Extended Reconstructed SST V5
    parent_stat:   Individual Values
    actual_range:  [-1.8     42.32636]
    valid_range:   [-1.8 45. ]

xarray.DataArray

'sst'

month: 12
lat: 89
lon: 180

-1.8 -1.8 -1.8 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan nan nan nan

array([[[-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        ...,
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan]],

       [[-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
...
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan]],

       [[-1.7994802, -1.7995852, -1.7998399, ..., -1.7997632,
         -1.7996233, -1.7994753],
        [-1.7995453, -1.7997496, -1.8000005, ..., -1.8000005,
         -1.799799 , -1.7995732],
        [-1.8000005, -1.8000005, -1.8000005, ..., -1.8000005,
         -1.8000005, -1.8000005],
        ...,
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan],
        [       nan,        nan,        nan, ...,        nan,
                nan,        nan]]], shape=(12, 89, 180), dtype=float32)

Coordinates: (3)

month

(month)

int64

1 2 3 4 5 6 7 8 9 10 11 12

array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])

lat

(lat)

float32

88.0 86.0 84.0 ... -86.0 -88.0

units :: degrees_north
long_name :: Latitude
actual_range :: [ 88. -88.]
standard_name :: latitude
axis :: Y
coordinate_defines :: center

array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,
        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,
        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,
        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,
       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,
       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,
       -80., -82., -84., -86., -88.], dtype=float32)

lon

(lon)

float32

0.0 2.0 4.0 ... 354.0 356.0 358.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,
        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,
        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,
        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,
       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,
       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,
       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,
       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,
       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,
       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,
       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,
       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,
       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,
       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],
      dtype=float32)

Attributes: (9)
long_name :
Monthly Means of Sea Surface Temperature
units :
degC
var_desc :
Sea Surface Temperature
level_desc :
Surface
statistic :
Mean
dataset :
NOAA Extended Reconstructed SST V5
parent_stat :
Individual Values
actual_range :
[-1.8 42.32636]
valid_range :
[-1.8 45. ]

In [18]:

Copied!

sst_clim.plot(col="month", col_wrap=4)
plt.show()
sst_clim.plot(col="month", col_wrap=4)
plt.show()

In [19]:

Copied!

sst_anom = sst.groupby("time.month") - sst_clim
sst_anom
sst_anom = sst.groupby("time.month") - sst_clim
sst_anom

Out[19]:

<xarray.DataArray 'sst' (time: 624, lat: 89, lon: 180)> Size: 40MB
array([[[ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        ...,
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan]],

       [[ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
...
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan]],

       [[-5.19752502e-04, -4.14729118e-04, -1.60098076e-04, ...,
         -2.36749649e-04, -3.76701355e-04, -5.24640083e-04],
        [-4.54664230e-04, -2.50339508e-04,  5.96046448e-07, ...,
          5.96046448e-07, -2.00986862e-04, -4.26769257e-04],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        ...,
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan]]],
      shape=(624, 89, 180), dtype=float32)
Coordinates:
  * time     (time) datetime64[ns] 5kB 1970-01-01 1970-02-01 ... 2021-12-01
  * lat      (lat) float32 356B 88.0 86.0 84.0 82.0 ... -82.0 -84.0 -86.0 -88.0
  * lon      (lon) float32 720B 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0
    month    (time) int64 5kB 1 2 3 4 5 6 7 8 9 10 11 ... 3 4 5 6 7 8 9 10 11 12
Attributes:
    long_name:     Monthly Means of Sea Surface Temperature
    units:         degC
    var_desc:      Sea Surface Temperature
    level_desc:    Surface
    statistic:     Mean
    dataset:       NOAA Extended Reconstructed SST V5
    parent_stat:   Individual Values
    actual_range:  [-1.8     42.32636]
    valid_range:   [-1.8 45. ]

xarray.DataArray

'sst'

time: 624
lat: 89
lon: 180

5.96e-07 5.96e-07 5.96e-07 5.96e-07 5.96e-07 ... nan nan nan nan nan

array([[[ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        ...,
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan]],

       [[ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
...
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan]],

       [[-5.19752502e-04, -4.14729118e-04, -1.60098076e-04, ...,
         -2.36749649e-04, -3.76701355e-04, -5.24640083e-04],
        [-4.54664230e-04, -2.50339508e-04,  5.96046448e-07, ...,
          5.96046448e-07, -2.00986862e-04, -4.26769257e-04],
        [ 5.96046448e-07,  5.96046448e-07,  5.96046448e-07, ...,
          5.96046448e-07,  5.96046448e-07,  5.96046448e-07],
        ...,
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan],
        [            nan,             nan,             nan, ...,
                     nan,             nan,             nan]]],
      shape=(624, 89, 180), dtype=float32)

Coordinates: (4)

time

(time)

datetime64[ns]

1970-01-01 ... 2021-12-01

long_name :: Time
delta_t :: 0000-01-00 00:00:00
avg_period :: 0000-01-00 00:00:00
prev_avg_period :: 0000-00-07 00:00:00
standard_name :: time
axis :: T
actual_range :: [19723. 81204.]

array(['1970-01-01T00:00:00.000000000', '1970-02-01T00:00:00.000000000',
       '1970-03-01T00:00:00.000000000', ..., '2021-10-01T00:00:00.000000000',
       '2021-11-01T00:00:00.000000000', '2021-12-01T00:00:00.000000000'],
      shape=(624,), dtype='datetime64[ns]')

lat

(lat)

float32

88.0 86.0 84.0 ... -86.0 -88.0

units :: degrees_north
long_name :: Latitude
actual_range :: [ 88. -88.]
standard_name :: latitude
axis :: Y
coordinate_defines :: center

array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,
        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,
        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,
        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,
       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,
       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,
       -80., -82., -84., -86., -88.], dtype=float32)

lon

(lon)

float32

0.0 2.0 4.0 ... 354.0 356.0 358.0

units :: degrees_east
long_name :: Longitude
actual_range :: [ 0. 358.]
standard_name :: longitude
axis :: X
coordinate_defines :: center

array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,
        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,
        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,
        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,
       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,
       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,
       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,
       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,
       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,
       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,
       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,
       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,
       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,
       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],
      dtype=float32)

month

(time)

int64

1 2 3 4 5 6 7 ... 6 7 8 9 10 11 12

array([ 1,  2,  3, ..., 10, 11, 12], shape=(624,))

Attributes: (9)
long_name :
Monthly Means of Sea Surface Temperature
units :
degC
var_desc :
Sea Surface Temperature
level_desc :
Surface
statistic :
Mean
dataset :
NOAA Extended Reconstructed SST V5
parent_stat :
Individual Values
actual_range :
[-1.8 42.32636]
valid_range :
[-1.8 45. ]