pynldas2 0.19.3
Get NLDAS2 forcing data.
License: MIT
Requires Python: >=3.9

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================ ====================================================================
Package          Description
================ ====================================================================
PyNHD_           Navigate and subset NHDPlus (MR and HR) using web services
Py3DEP_          Access topographic data through National Map's 3DEP web service
PyGeoHydro_      Access NWIS, NID, WQP, eHydro, NLCD, CAMELS, and SSEBop databases
PyDaymet_        Access daily, monthly, and annual climate data via Daymet
PyGridMET_       Access daily climate data via GridMET
PyNLDAS2_        Access hourly NLDAS-2 data via web services
HydroSignatures_ A collection of tools for computing hydrological signatures
AsyncRetriever_  High-level API for asynchronous requests with persistent caching
PyGeoOGC_        Send queries to any ArcGIS RESTful-, WMS-, and WFS-based services
PyGeoUtils_      Utilities for manipulating geospatial, (Geo)JSON, and (Geo)TIFF data
================ ====================================================================

.. _PyGeoHydro: https://github.com/hyriver/pygeohydro
.. _AsyncRetriever: https://github.com/hyriver/async-retriever
.. _PyGeoOGC: https://github.com/hyriver/pygeoogc
.. _PyGeoUtils: https://github.com/hyriver/pygeoutils
.. _PyNHD: https://github.com/hyriver/pynhd
.. _Py3DEP: https://github.com/hyriver/py3dep
.. _PyDaymet: https://github.com/hyriver/pydaymet
.. _PyGridMET: https://github.com/hyriver/pygridmet
.. _PyNLDAS2: https://github.com/hyriver/pynldas2
.. _HydroSignatures: https://github.com/hyriver/hydrosignatures

PyNLDAS2: Hourly NLDAS-2 Forcing Data
-------------------------------------

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Features
--------

PyNLDAS2 is a part of `HyRiver <https://github.com/hyriver/HyRiver>`__ software stack that
is designed to aid in hydroclimate analysis through web services. This package
provides access `NLDAS-2 Forcing dataset <https://ldas.gsfc.nasa.gov/nldas/v2/forcing>`__
via `Hydrology Data Rods <https://disc.gsfc.nasa.gov/information/tools?title=Hydrology+Data+Rods>`__.
Currently, only hourly data is supported. There are three main functions:

- ``get_bycoords``: Forcing data for a list of coordinates as a ``pandas.DataFrame`` or
  ``xarray.Dataset``,
- ``get_bygeom``: Forcing data within a geometry as a ``xarray.Dataset``,
- ``get_grid_mask``: NLDAS2
  `land/water grid mask <https://ldas.gsfc.nasa.gov/nldas/specifications>`__
  as a ``xarray.Dataset``.

Both ``get_bygeom`` and ``get_bycoords`` functions save the intermediate files
returned by the web service in a local cache folder (``./cache`` in the current
directory). The cache folder is created automatically when the functions are
called for the first time. The cache folder is used to store the intermediate
files to avoid re-downloading them. These two functions allow modifying the
web service calls via two options:

- ``conn_timeout``: Sets the connection timeout in seconds. The default value
  is 5 minutes. This can be increaseed for larger requests. If running these
  functions fails with a connection timeout error, try increasing this value.
- ``validate_filesize``: If ``True``, the functions compares the file size
  of the previously cached files in the ``./cache`` folder, if they exist, with
  their size on the remote server. If the sizes do not match, the cached files are
  removed and they will be re-download. By default this is set to ``False`` since
  the files on the server rarely change. So, if a request has already been cached
  there shouldn't be a need for re-donwloading them from scratch. However, if you
  suspect that the files on the server have changed or the functions fails to process
  the cached files, you can set this to ``True`` or manually delete the cached
  files in the ``./cache`` folder.

You can find some example notebooks
`here <https://github.com/hyriver/HyRiver-examples>`__.
You can also try using PyNLDAS2 without installing
it on your system by clicking on the binder badge. A Jupyter Lab
instance with the HyRiver stack pre-installed will be launched in your web browser,
and you can start coding!

Moreover, requests for additional functionalities can be submitted via
`issue tracker <https://github.com/hyriver/pynldas2/issues>`__.

Citation
--------
If you use any of HyRiver packages in your research, we appreciate citations:

.. code-block:: bibtex

    @article{Chegini_2021,
        author = {Chegini, Taher and Li, Hong-Yi and Leung, L. Ruby},
        doi = {10.21105/joss.03175},
        journal = {Journal of Open Source Software},
        month = {10},
        number = {66},
        pages = {1--3},
        title = {{HyRiver: Hydroclimate Data Retriever}},
        volume = {6},
        year = {2021}
    }

Installation
------------

You can install ``pynldas2`` using ``pip``:

.. code-block:: console

    $ pip install pynldas2

Alternatively, ``pynldas2`` can be installed from the ``conda-forge`` repository
using `Conda <https://docs.conda.io/en/latest/>`__:

.. code-block:: console

    $ conda install -c conda-forge pynldas2

Quick start
-----------

The NLDAS2 database provides forcing data at 1/8th-degree grid spacing and range
from 01 Jan 1979 to present. Let's take a look at NLDAS2 grid mask that includes
land, water, soil, and vegetation masks:


.. code-block:: python

    import pynldas2 as nldas

    grid = nldas.get_grid_mask()

.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/nldas_grid.png
    :target: https://github.com/hyriver/HyRiver-examples/blob/main/notebooks/nldas.ipynb

Next, we use `PyGeoHydro <https://github.com/hyriver/pygeohydro>`__ to get the
geometry of a HUC8 with ID of 1306003, then we get the forcing data within the
obtained geometry.

.. code-block:: python

    from pygeohydro import WBD

    huc8 = WBD("huc8")
    geometry = huc8.byids("huc8", "13060003").geometry[0]
    clm = nldas.get_bygeom(geometry, "2010-01-01", "2010-01-31", 4326)

.. image:: https://raw.githubusercontent.com/hyriver/HyRiver-examples/main/notebooks/_static/nldas_humidity.png
    :target: https://github.com/hyriver/HyRiver-examples/blob/main/notebooks/nldas.ipynb

Road Map
--------

- [ ] Add PET calculation functions similar to
  `PyDaymet <https://github.com/hyriver/pydaymet>`__ but at hourly timescale.
- [ ] Add a command line interfaces.

Contributing
------------

Contributions are appreciated and very welcomed. Please read
`CONTRIBUTING.rst <https://github.com/hyriver/pynldas2/blob/main/CONTRIBUTING.rst>`__
for instructions.