131 lines
6.3 KiB
Python
131 lines
6.3 KiB
Python
# SPDX-FileCopyrightText: : 2017-2021 The PyPSA-Eur Authors
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#
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# SPDX-License-Identifier: MIT
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"""
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Create cutouts with `atlite <https://atlite.readthedocs.io/en/latest/>`_.
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For this rule to work you must have
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- installed the `Copernicus Climate Data Store <https://cds.climate.copernicus.eu>`_ ``cdsapi`` package (`install with `pip``) and
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- registered and setup your CDS API key as described `on their website <https://cds.climate.copernicus.eu/api-how-to>`_.
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.. seealso::
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For details on the weather data read the `atlite documentation <https://atlite.readthedocs.io/en/latest/>`_.
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If you need help specifically for creating cutouts `the corresponding section in the atlite documentation <https://atlite.readthedocs.io/en/latest/examples/create_cutout.html>`_ should be helpful.
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Relevant Settings
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-----------------
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.. code:: yaml
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atlite:
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nprocesses:
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cutouts:
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{cutout}:
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.. seealso::
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Documentation of the configuration file ``config.yaml`` at
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:ref:`atlite_cf`
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Inputs
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------
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*None*
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Outputs
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-------
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- ``cutouts/{cutout}``: weather data from either the `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`_
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reanalysis weather dataset or `SARAH-2 <https://wui.cmsaf.eu/safira/action/viewProduktSearch>`_
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satellite-based historic weather data with the following structure:
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**ERA5 cutout:**
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=================== ========== ========== =========================================================
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Field Dimensions Unit Description
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=================== ========== ========== =========================================================
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pressure time, y, x Pa Surface pressure
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------------------- ---------- ---------- ---------------------------------------------------------
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temperature time, y, x K Air temperature 2 meters above the surface.
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------------------- ---------- ---------- ---------------------------------------------------------
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soil temperature time, y, x K Soil temperature between 1 meters and 3 meters
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depth (layer 4).
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------------------- ---------- ---------- ---------------------------------------------------------
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influx_toa time, y, x Wm**-2 Top of Earth's atmosphere TOA incident solar radiation
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------------------- ---------- ---------- ---------------------------------------------------------
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influx_direct time, y, x Wm**-2 Total sky direct solar radiation at surface
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------------------- ---------- ---------- ---------------------------------------------------------
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runoff time, y, x m `Runoff <https://en.wikipedia.org/wiki/Surface_runoff>`_
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(volume per area)
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------------------- ---------- ---------- ---------------------------------------------------------
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roughness y, x m Forecast surface roughness
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(`roughness length <https://en.wikipedia.org/wiki/Roughness_length>`_)
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------------------- ---------- ---------- ---------------------------------------------------------
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height y, x m Surface elevation above sea level
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------------------- ---------- ---------- ---------------------------------------------------------
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albedo time, y, x -- `Albedo <https://en.wikipedia.org/wiki/Albedo>`_
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measure of diffuse reflection of solar radiation.
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Calculated from relation between surface solar radiation
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downwards (Jm**-2) and surface net solar radiation
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(Jm**-2). Takes values between 0 and 1.
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------------------- ---------- ---------- ---------------------------------------------------------
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influx_diffuse time, y, x Wm**-2 Diffuse solar radiation at surface.
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Surface solar radiation downwards minus
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direct solar radiation.
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------------------- ---------- ---------- ---------------------------------------------------------
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wnd100m time, y, x ms**-1 Wind speeds at 100 meters (regardless of direction)
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=================== ========== ========== =========================================================
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.. image:: ../img/era5.png
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:scale: 40 %
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A **SARAH-2 cutout** can be used to amend the fields ``temperature``, ``influx_toa``, ``influx_direct``, ``albedo``,
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``influx_diffuse`` of ERA5 using satellite-based radiation observations.
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.. image:: ../img/sarah.png
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:scale: 40 %
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Description
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-----------
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"""
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import logging
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import atlite
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import geopandas as gpd
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import pandas as pd
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from _helpers import configure_logging
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logger = logging.getLogger(__name__)
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if __name__ == "__main__":
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if 'snakemake' not in globals():
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from _helpers import mock_snakemake
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snakemake = mock_snakemake('build_cutout', cutout='europe-2013-era5')
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configure_logging(snakemake)
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cutout_params = snakemake.config['atlite']['cutouts'][snakemake.wildcards.cutout]
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snapshots = pd.date_range(freq='h', **snakemake.config['snapshots'])
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time = [snapshots[0], snapshots[-1]]
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cutout_params['time'] = slice(*cutout_params.get('time', time))
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if {'x', 'y', 'bounds'}.isdisjoint(cutout_params):
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# Determine the bounds from bus regions with a buffer of two grid cells
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onshore = gpd.read_file(snakemake.input.regions_onshore)
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offshore = gpd.read_file(snakemake.input.regions_offshore)
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regions = onshore.append(offshore)
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d = max(cutout_params.get('dx', 0.25), cutout_params.get('dy', 0.25))*2
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cutout_params['bounds'] = regions.total_bounds + [-d, -d, d, d]
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elif {'x', 'y'}.issubset(cutout_params):
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cutout_params['x'] = slice(*cutout_params['x'])
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cutout_params['y'] = slice(*cutout_params['y'])
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logging.info(f"Preparing cutout with parameters {cutout_params}.")
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features = cutout_params.pop('features', None)
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cutout = atlite.Cutout(snakemake.output[0], **cutout_params)
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cutout.prepare(features=features)
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