MPI-ESM1-2-HR 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/siconc_SImon_MPI-ESM1-2-HR_piControl_r1i1p1f1_gn.yaml")
ds=cat.netcdf.read()

Metadata

title	MPI-ESM1-2-HR output prepared for CMIP6
location	/shared/cmip6/data/piControl/seaIce/mon/OImon/siconc/MPI-M.MPI-ESM1-2-HR/r1i1p1
tags	gridded,global,model,monthly
catalog_dir	https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/siconc_SImon_MPI-ESM1-2-HR_piControl_r1i1p1f1_gn.yaml
last updated	2020-09-16

Dataset Contents

<xarray.Dataset>
Dimensions:             (bnds: 2, i: 802, j: 404, time: 6000, vertices: 4)
Coordinates:
  * time                (time) float64 15.5 45.0 74.5 ... 1.826e+05 1.826e+05
  * j                   (j) int32 0 1 2 3 4 5 6 ... 397 398 399 400 401 402 403
  * i                   (i) int32 0 1 2 3 4 5 6 ... 795 796 797 798 799 800 801
    latitude            (j, i) float64 dask.array<chunksize=(404, 802), meta=np.ndarray>
    longitude           (j, i) float64 dask.array<chunksize=(404, 802), meta=np.ndarray>
    type                |S7 b'sea_ice'
Dimensions without coordinates: bnds, vertices
Data variables:
    time_bnds           (time, bnds) float64 dask.array<chunksize=(60, 2), meta=np.ndarray>
    vertices_latitude   (time, j, i, vertices) float64 dask.array<chunksize=(60, 404, 802, 4), meta=np.ndarray>
    vertices_longitude  (time, j, i, vertices) float64 dask.array<chunksize=(60, 404, 802, 4), meta=np.ndarray>
    siconc              (time, j, i) float32 dask.array<chunksize=(60, 404, 802), 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:  359763.0
    contact:                cmip6-mpi-esm@dkrz.de
    creation_date:          2019-08-06T11:33:58Z
    data_specs_version:     01.00.30
    experiment:             pre-industrial control
    experiment_id:          piControl
    external_variables:     areacello
    forcing_index:          1
    frequency:              mon
    further_info_url:       https://furtherinfo.es-doc.org/CMIP6.MPI-M.MPI-ES...
    grid:                   gn
    grid_label:             gn
    history:                2019-08-06T11:33:58Z ; CMOR rewrote data to be co...
    initialization_index:   1
    institution:            Max Planck Institute for Meteorology, Hamburg 201...
    institution_id:         MPI-M
    mip_era:                CMIP6
    nominal_resolution:     50 km
    parent_activity_id:     CMIP
    parent_experiment_id:   piControl-spinup
    parent_mip_era:         CMIP6
    parent_source_id:       MPI-ESM1-2-HR
    parent_time_units:      days since 1850-1-1 00:00:00
    parent_variant_label:   r1i1p1f1
    physics_index:          1
    product:                model-output
    project_id:             CMIP6
    realization_index:      1
    realm:                  seaIce
    references:             MPI-ESM: Mauritsen, T. et al. (2019), Development...
    source:                 MPI-ESM1.2-HR (2017): 
aerosol: none, prescribed...
    source_id:              MPI-ESM1-2-HR
    source_type:            AOGCM
    sub_experiment:         none
    sub_experiment_id:      none
    table_id:               SImon
    table_info:             Creation Date:(09 May 2019) MD5:e6ef8ececc8f33864...
    title:                  MPI-ESM1-2-HR output prepared for CMIP6
    variable_id:            siconc
    variant_label:          r1i1p1f1
    license:                CMIP6 model data produced by MPI-M is licensed un...
    cmor_version:           3.4.0
    tracking_id:            hdl:21.14100/6c0c79b4-3680-4e51-961b-ac0cd475e85f

xarray.Dataset

Dimensions:
- bnds: 2
- i: 802
- j: 404
- time: 6000
- vertices: 4

Coordinates: (6)

time
(time)
float64
15.5 45.0 ... 1.826e+05 1.826e+05
bounds :
time_bnds
units :
days since 1850-1-1 00:00:00
calendar :
proleptic_gregorian
axis :
T
long_name :
time
standard_name :
time
```
array([1.550000e+01, 4.500000e+01, 7.450000e+01, ..., 1.825445e+05,
       1.825750e+05, 1.826055e+05])
```
j
(j)
int32
0 1 2 3 4 5 ... 399 400 401 402 403
units :
1
long_name :
cell index along second dimension
```
array([  0,   1,   2, ..., 401, 402, 403], dtype=int32)
```
i
(i)
int32
0 1 2 3 4 5 ... 797 798 799 800 801
units :
1
long_name :
cell index along first dimension
```
array([  0,   1,   2, ..., 799, 800, 801], dtype=int32)
```

latitude

(j, i)

float64

dask.array<chunksize=(404, 802), meta=np.ndarray>

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

	Array	Chunk
Bytes	2.59 MB	2.59 MB
Shape	(404, 802)	(404, 802)
Count	495 Tasks	1 Chunks
Type	float64	numpy.ndarray

longitude

(j, i)

float64

dask.array<chunksize=(404, 802), meta=np.ndarray>

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

	Array	Chunk
Bytes	2.59 MB	2.59 MB
Shape	(404, 802)	(404, 802)
Count	495 Tasks	1 Chunks
Type	float64	numpy.ndarray

type
()
|S7
b'sea_ice'
long_name :
Sea Ice area type
standard_name :
area_type
```
array(b'sea_ice', dtype='|S7')
```

Data variables: (4)

time_bnds

(time, bnds)

float64

dask.array<chunksize=(60, 2), meta=np.ndarray>

	Array	Chunk
Bytes	96.00 kB	960 B
Shape	(6000, 2)	(60, 2)
Count	300 Tasks	100 Chunks
Type	float64	numpy.ndarray

vertices_latitude

(time, j, i, vertices)

float64

dask.array<chunksize=(60, 404, 802, 4), meta=np.ndarray>

units :: degrees_north

	Array	Chunk
Bytes	62.21 GB	622.10 MB
Shape	(6000, 404, 802, 4)	(60, 404, 802, 4)
Count	400 Tasks	100 Chunks
Type	float64	numpy.ndarray

vertices_longitude

(time, j, i, vertices)

float64

dask.array<chunksize=(60, 404, 802, 4), meta=np.ndarray>

units :: degrees_east

	Array	Chunk
Bytes	62.21 GB	622.10 MB
Shape	(6000, 404, 802, 4)	(60, 404, 802, 4)
Count	400 Tasks	100 Chunks
Type	float64	numpy.ndarray

siconc

(time, j, i)

float32

dask.array<chunksize=(60, 404, 802), meta=np.ndarray>

standard_name :: sea_ice_area_fraction
long_name :: Sea-Ice Area Percentage (Ocean Grid)
comment :: Percentage of grid cell covered by sea ice
units :: %
original_name :: siconc
original_units :: 1
history :: 2019-08-06T11:33:58Z altered by CMOR: Converted units from '1' to '%'. 2019-08-06T11:33:58Z altered by CMOR: Treated scalar dimension: 'type'. 2019-08-06T11:33:58Z altered by CMOR: replaced missing value flag (-9e+33) with standard missing value (1e+20).
cell_methods :: area: mean where sea time: mean
cell_measures :: area: areacello

	Array	Chunk
Bytes	7.78 GB	77.76 MB
Shape	(6000, 404, 802)	(60, 404, 802)
Count	300 Tasks	100 Chunks
Type	float32	numpy.ndarray

Attributes: (47)
Conventions :
CF-1.7 CMIP-6.2
activity_id :
CMIP
branch_method :
standard
branch_time_in_child :
0.0
branch_time_in_parent :
359763.0
contact :
cmip6-mpi-esm@dkrz.de
creation_date :
2019-08-06T11:33:58Z
data_specs_version :
01.00.30
experiment :
pre-industrial control
experiment_id :
piControl
external_variables :
areacello
forcing_index :
1
frequency :
mon
further_info_url :
https://furtherinfo.es-doc.org/CMIP6.MPI-M.MPI-ESM1-2-HR.piControl.none.r1i1p1f1
grid :
gn
grid_label :
gn
history :
2019-08-06T11:33:58Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.
initialization_index :
1
institution :
Max Planck Institute for Meteorology, Hamburg 20146, Germany
institution_id :
MPI-M
mip_era :
CMIP6
nominal_resolution :
50 km
parent_activity_id :
CMIP
parent_experiment_id :
piControl-spinup
parent_mip_era :
CMIP6
parent_source_id :
MPI-ESM1-2-HR
parent_time_units :
days since 1850-1-1 00:00:00
parent_variant_label :
r1i1p1f1
physics_index :
1
product :
model-output
project_id :
CMIP6
realization_index :
1
realm :
seaIce
references :
MPI-ESM: Mauritsen, T. et al. (2019), Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Syst.,11, 998-1038, doi:10.1029/2018MS001400, Mueller, W.A. et al. (2018): A high‐resolution version of the Max Planck Institute Earth System Model MPI‐ESM1.2‐HR. J. Adv. Model. EarthSyst.,10,1383–1413, doi:10.1029/2017MS001217
source :
MPI-ESM1.2-HR (2017): aerosol: none, prescribed MACv2-SP atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa) atmosChem: none land: JSBACH3.20 landIce: none/prescribed ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m) ocnBgchem: HAMOCC6 seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model)
source_id :
MPI-ESM1-2-HR
source_type :
AOGCM
sub_experiment :
none
sub_experiment_id :
none
table_id :
SImon
table_info :
Creation Date:(09 May 2019) MD5:e6ef8ececc8f338646ebfb3aeed36bfc
title :
MPI-ESM1-2-HR output prepared for CMIP6
variable_id :
siconc
variant_label :
r1i1p1f1
license :
CMIP6 model data produced by MPI-M 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. 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 :
3.4.0
tracking_id :
hdl:21.14100/6c0c79b4-3680-4e51-961b-ac0cd475e85f