CMCC-CM2-SR5 output prepared for CMIP6

Load in Python

from intake import open_catalog

cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/mlotst_Omon_CMCC-CM2-SR5_piControl_r1i1p1f1_gn.yaml")
ds=cat.netcdf.read()

Metadata

title	CMCC-CM2-SR5 output prepared for CMIP6
location	/shared/cmip6/data/piControl/ocean/mon/Omon/mlotst/CMCC-CM2-SR5/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/mlotst_Omon_CMCC-CM2-SR5_piControl_r1i1p1f1_gn.yaml
last updated	2020-09-29

Dataset Contents

<xarray.Dataset>
Dimensions:             (bnds: 2, i: 292, j: 362, time: 6000, vertices: 4)
Coordinates:
  * time                (time) float64 15.5 45.0 74.5 ... 1.825e+05 1.825e+05
  * i                   (i) int32 0 1 2 3 4 5 6 ... 285 286 287 288 289 290 291
  * j                   (j) int32 0 1 2 3 4 5 6 ... 355 356 357 358 359 360 361
    latitude            (i, j) float64 dask.array<chunksize=(292, 362), meta=np.ndarray>
    longitude           (i, j) float64 dask.array<chunksize=(292, 362), meta=np.ndarray>
Dimensions without coordinates: bnds, vertices
Data variables:
    time_bnds           (time, bnds) float64 dask.array<chunksize=(3000, 2), meta=np.ndarray>
    vertices_latitude   (time, i, j, vertices) float64 dask.array<chunksize=(3000, 292, 362, 4), meta=np.ndarray>
    vertices_longitude  (time, i, j, vertices) float64 dask.array<chunksize=(3000, 292, 362, 4), meta=np.ndarray>
    mlotst              (time, i, j) float32 dask.array<chunksize=(3000, 292, 362), meta=np.ndarray>
Attributes:
    Conventions:            CF-1.7 CMIP-6.2
    activity_id:            CMIP
    branch_method:          standard
    branch_time_in_child:   0.0
    branch_time_in_parent:  0.0
    comment:                none
    contact:                T. Lovato
    creation_date:          2020-06-09T20:55:17Z
    data_specs_version:     01.00.31
    experiment:             pre-industrial control
    experiment_id:          piControl
    external_variables:     areacello
    forcing_index:          1
    frequency:              mon
    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.CMCC.CMCC-CM...
    grid:                   native ocean curvilinear grid
    grid_label:             gn
    history:                2020-06-09T20:55:17Z ;rewrote data to be consiste...
    initialization_index:   1
    institution:            Fondazione Centro Euro-Mediterraneo sui Cambiamen...
    institution_id:         CMCC
    mip_era:                CMIP6
    nominal_resolution:     100 km
    parent_activity_id:     CMIP
    parent_experiment_id:   piControl-spinup
    parent_mip_era:         CMIP6
    parent_source_id:       CMCC-CM2-SR5
    parent_time_units:      days since 1850-01-01
    parent_variant_label:   r1i1p1f1
    physics_index:          1
    product:                model-output
    realization_index:      1
    realm:                  ocean
    references:             none
    run_variant:            1st realization
    source:                 CMCC-CM2-SR5 (2016): 
aerosol: MAM3
atmos: CAM5...
    source_id:              CMCC-CM2-SR5
    source_type:            AOGCM
    sub_experiment:         none
    sub_experiment_id:      none
    table_id:               Omon
    table_info:             Creation Date:(05 February 2020) MD5:6a248fd76c55...
    title:                  CMCC-CM2-SR5 output prepared for CMIP6
    variable_id:            mlotst
    variant_label:          r1i1p1f1
    license:                CMIP6 model data produced by CMCC is licensed und...
    cmor_version:           3.5.0
    tracking_id:            hdl:21.14100/2e177b7d-460b-4156-a349-995d1c8eefd0

xarray.Dataset

Dimensions:
- bnds: 2
- i: 292
- j: 362
- time: 6000
- vertices: 4

Coordinates: (5)

time
(time)
float64
15.5 45.0 ... 1.825e+05 1.825e+05
bounds :
time_bnds
units :
days since 1850-01-01
calendar :
365_day
axis :
T
long_name :
time
standard_name :
time
```
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 1.824235e+05,
       1.824540e+05, 1.824845e+05])
```
i
(i)
int32
0 1 2 3 4 5 ... 287 288 289 290 291
units :
1
long_name :
first spatial index for variables stored on an unstructured grid
```
array([  0,   1,   2, ..., 289, 290, 291], dtype=int32)
```
j
(j)
int32
0 1 2 3 4 5 ... 357 358 359 360 361
units :
1
long_name :
second spatial index for variables stored on an unstructured grid
```
array([  0,   1,   2, ..., 359, 360, 361], dtype=int32)
```

latitude

(i, j)

float64

dask.array<chunksize=(292, 362), meta=np.ndarray>

standard_name :: latitude
long_name :: latitude
units :: degrees_north
bounds :: vertices_latitude

	Array	Chunk
Bytes	845.63 kB	845.63 kB
Shape	(292, 362)	(292, 362)
Count	5 Tasks	1 Chunks
Type	float64	numpy.ndarray

longitude

(i, j)

float64

dask.array<chunksize=(292, 362), meta=np.ndarray>

standard_name :: longitude
long_name :: longitude
units :: degrees_east
bounds :: vertices_longitude

	Array	Chunk
Bytes	845.63 kB	845.63 kB
Shape	(292, 362)	(292, 362)
Count	5 Tasks	1 Chunks
Type	float64	numpy.ndarray

Data variables: (4)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(3000, 2), meta=np.ndarray>

	Array	Chunk
Bytes	96.00 kB	48.00 kB
Shape	(6000, 2)	(3000, 2)
Count	6 Tasks	2 Chunks
Type	float64	numpy.ndarray

vertices_latitude

(time, i, j, vertices)

float64

dask.array<chunksize=(3000, 292, 362, 4), meta=np.ndarray>

units :: degrees_north

	Array	Chunk
Bytes	20.30 GB	10.15 GB
Shape	(6000, 292, 362, 4)	(3000, 292, 362, 4)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

vertices_longitude

(time, i, j, vertices)

float64

dask.array<chunksize=(3000, 292, 362, 4), meta=np.ndarray>

units :: degrees_east

	Array	Chunk
Bytes	20.30 GB	10.15 GB
Shape	(6000, 292, 362, 4)	(3000, 292, 362, 4)
Count	8 Tasks	2 Chunks
Type	float64	numpy.ndarray

mlotst

(time, i, j)

float32

dask.array<chunksize=(3000, 292, 362), meta=np.ndarray>

standard_name :: ocean_mixed_layer_thickness_defined_by_sigma_t
long_name :: Ocean Mixed Layer Thickness Defined by Sigma T
comment :: Sigma T is potential density referenced to ocean surface.
units :: m
cell_methods :: area: mean where sea time: mean
cell_measures :: area: areacello

	Array	Chunk
Bytes	2.54 GB	1.27 GB
Shape	(6000, 292, 362)	(3000, 292, 362)
Count	6 Tasks	2 Chunks
Type	float32	numpy.ndarray

Attributes: (48)
Conventions :
CF-1.7 CMIP-6.2
activity_id :
CMIP
branch_method :
standard
branch_time_in_child :
0.0
branch_time_in_parent :
0.0
comment :
none
contact :
T. Lovato
creation_date :
2020-06-09T20:55:17Z
data_specs_version :
01.00.31
experiment :
pre-industrial control
experiment_id :
piControl
external_variables :
areacello
forcing_index :
1
frequency :
mon
further_info_url :
https://furtherinfo.es-doc.org/CMIP6.CMCC.CMCC-CM2-SR5.piControl.none.r1i1p1f1
grid :
native ocean curvilinear grid
grid_label :
gn
history :
2020-06-09T20:55:17Z ;rewrote data to be consistent with CMIP for variable mlotst found in table Omon.; none
initialization_index :
1
institution :
Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy
institution_id :
CMCC
mip_era :
CMIP6
nominal_resolution :
100 km
parent_activity_id :
CMIP
parent_experiment_id :
piControl-spinup
parent_mip_era :
CMIP6
parent_source_id :
CMCC-CM2-SR5
parent_time_units :
days since 1850-01-01
parent_variant_label :
r1i1p1f1
physics_index :
1
product :
model-output
realization_index :
1
realm :
ocean
references :
none
run_variant :
1st realization
source :
CMCC-CM2-SR5 (2016): aerosol: MAM3 atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa) atmosChem: none land: CLM4.5 (BGC mode) landIce: none ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m) ocnBgchem: none seaIce: CICE4.0
source_id :
CMCC-CM2-SR5
source_type :
AOGCM
sub_experiment :
none
sub_experiment_id :
none
table_id :
Omon
table_info :
Creation Date:(05 February 2020) MD5:6a248fd76c55aa6d6f7b3cc6866b5faf
title :
CMCC-CM2-SR5 output prepared for CMIP6
variable_id :
mlotst
variant_label :
r1i1p1f1
license :
CMIP6 model data produced by CMCC is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.
cmor_version :
3.5.0
tracking_id :
hdl:21.14100/2e177b7d-460b-4156-a349-995d1c8eefd0