Skip to content
main
Switch branches/tags
Code

GitHub Workflow Status (branch)

CESM LENS on AWS

Examples of analysis of CESM LENS data publicly available on Amazon S3 (us-west-2 region) using xarray and dask.

Re-create notebooks with Pangeo Binder

Try these notebooks on Pangeo Binder. Note that the session is ephemeral. Your home directory will not persist, so remember to download your notebooks if you made changes that you need to use at a later time!

badge

ESM catalog

The main catalog URL is:

https://raw.githubusercontent.com/NCAR/cesm-lens-aws/main/intake-catalogs/aws-cesm1-le.json

This catalog is an ESM collection catalog. The data is stored in Zarr format and meant to be opened with Xarray.

Requirements

Using this catalog requires the following package versions:

Examples

To open the catalog and load a data set from Python, you can run the following code:

In [1]: import intake

In [2]: col = intake.open_esm_datastore("https://raw.githubusercontent.com/NCAR/cesm-lens-aws/main/intake-catalogs/aws-cesm1-le.json")

In [3]: col
Out[3]: <aws-cesm1-le catalog with 55 dataset(s) from 391 asset(s)>

In [4]: col.df.head()
Out[4]:
  component frequency experiment  ... dim_per_tstep                start                  end
0       atm     daily       CTRL  ...           2.0  0402-01-01 12:00:00  2200-12-31 12:00:00
1       atm     daily       CTRL  ...           2.0  0402-01-01 12:00:00  2200-12-31 12:00:00
2       atm     daily       CTRL  ...           2.0  0402-01-01 12:00:00  2200-12-31 12:00:00
3       atm     daily       CTRL  ...           2.0  0402-01-01 12:00:00  2200-12-31 12:00:00
4       atm     daily       CTRL  ...           2.0  0402-01-01 12:00:00  2200-12-31 12:00:00

[5 rows x 9 columns]

In [5]: col_subset = col.search(experiment="RCP85", frequency="monthly", variable=["hi", "aice"])

In [6]: dsets = col_subset.to_dataset_dict(zarr_kwargs={"consolidated": True}, storage_options={"anon": True})

--> The keys in the returned dictionary of datasets are constructed as follows:
        'component.experiment.frequency'
 |████████████████████████████████████████████████████████████████████████████████████████████████████| 100.00% [2/2 00:00<00:00]
In [7]: dsets.keys()
Out[7]: dict_keys(['ice_sh.RCP85.monthly', 'ice_nh.RCP85.monthly'])

In [8]: ds = dsets['ice_sh.RCP85.monthly']

In [9]: ds
Out[9]:
<xarray.Dataset>
Dimensions:      (d2: 2, member_id: 40, ni: 320, nj: 76, time: 1140)
Coordinates:
  * member_id    (member_id) int64 1 2 3 4 5 6 7 8 ... 34 35 101 102 103 104 105
  * time         (time) object 2006-01-16 12:00:00 ... 2100-12-16 12:00:00
    time_bounds  (time, d2) object dask.array<chunksize=(1140, 2), meta=np.ndarray>
Dimensions without coordinates: d2, ni, nj
Data variables:
    aice         (member_id, time, nj, ni) float32 dask.array<chunksize=(1, 1140, 76, 320), meta=np.ndarray>
    hi           (member_id, time, nj, ni) float32 dask.array<chunksize=(1, 1140, 76, 320), meta=np.ndarray>
Attributes:
    comment3:                  seconds elapsed into model date:      0
    conventions:               CF-1.0
    nco_openmp_thread_number:  1
    source:                    sea ice model: Community Ice Code (CICE)
    NCO:                       4.3.4
    contents:                  Diagnostic and Prognostic Variables
    comment2:                  File written on model date 20060201
    comment:                   All years have exactly 365 days
    intake_esm_dataset_key:    ice_sh.RCP85.monthly

Reference Documentation

Source Code for CESM LENS on AWS Site

The source code for https://doi.org/10.26024/wt24-5j82 resides in the site directory of this repository.

The site is built with sphinx.

To build the site locally, please use conda to set up a build environment with all dependencies.

First, make a local clone of this source repository on your machine. For example:

git clone https://github.com/NCAR/cesm-lens-aws

Set up your a conda environment:

conda env create -f site/environment.yml
conda activate cesm-lens-aws-site
bash site/install-extension.sh

You can then build the site with:

make live

About

Examples of analysis of CESM LENS data publicly available on Amazon S3 (us-west-2 region) using xarray and dask

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages