# -*- coding: utf-8 -*- # SPDX-FileCopyrightText: : 2017-2023 The PyPSA-Eur Authors # # SPDX-License-Identifier: MIT """ Create cutouts with `atlite <https://atlite.readthedocs.io/en/latest/>`_. For this rule to work you must have - installed the `Copernicus Climate Data Store <https://cds.climate.copernicus.eu>`_ ``cdsapi`` package (`install with `pip``) and - registered and setup your CDS API key as described `on their website <https://cds.climate.copernicus.eu/api-how-to>`_. .. seealso:: For details on the weather data read the `atlite documentation <https://atlite.readthedocs.io/en/latest/>`_. 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. Relevant Settings ----------------- .. code:: yaml atlite: nprocesses: cutouts: {cutout}: .. seealso:: Documentation of the configuration file ``config/config.yaml`` at :ref:`atlite_cf` Inputs ------ *None* Outputs ------- - ``cutouts/{cutout}``: weather data from either the `ERA5 <https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>`_ reanalysis weather dataset or `SARAH-2 <https://wui.cmsaf.eu/safira/action/viewProduktSearch>`_ satellite-based historic weather data with the following structure: **ERA5 cutout:** =================== ========== ========== ========================================================= Field Dimensions Unit Description =================== ========== ========== ========================================================= pressure time, y, x Pa Surface pressure ------------------- ---------- ---------- --------------------------------------------------------- temperature time, y, x K Air temperature 2 meters above the surface. ------------------- ---------- ---------- --------------------------------------------------------- soil temperature time, y, x K Soil temperature between 1 meters and 3 meters depth (layer 4). ------------------- ---------- ---------- --------------------------------------------------------- influx_toa time, y, x Wm**-2 Top of Earth's atmosphere TOA incident solar radiation ------------------- ---------- ---------- --------------------------------------------------------- influx_direct time, y, x Wm**-2 Total sky direct solar radiation at surface ------------------- ---------- ---------- --------------------------------------------------------- runoff time, y, x m `Runoff <https://en.wikipedia.org/wiki/Surface_runoff>`_ (volume per area) ------------------- ---------- ---------- --------------------------------------------------------- roughness y, x m Forecast surface roughness (`roughness length <https://en.wikipedia.org/wiki/Roughness_length>`_) ------------------- ---------- ---------- --------------------------------------------------------- height y, x m Surface elevation above sea level ------------------- ---------- ---------- --------------------------------------------------------- albedo time, y, x -- `Albedo <https://en.wikipedia.org/wiki/Albedo>`_ measure of diffuse reflection of solar radiation. Calculated from relation between surface solar radiation downwards (Jm**-2) and surface net solar radiation (Jm**-2). Takes values between 0 and 1. ------------------- ---------- ---------- --------------------------------------------------------- influx_diffuse time, y, x Wm**-2 Diffuse solar radiation at surface. Surface solar radiation downwards minus direct solar radiation. ------------------- ---------- ---------- --------------------------------------------------------- wnd100m time, y, x ms**-1 Wind speeds at 100 meters (regardless of direction) =================== ========== ========== ========================================================= .. image:: img/era5.png :scale: 40 % A **SARAH-2 cutout** can be used to amend the fields ``temperature``, ``influx_toa``, ``influx_direct``, ``albedo``, ``influx_diffuse`` of ERA5 using satellite-based radiation observations. .. image:: img/sarah.png :scale: 40 % Description ----------- """ import logging import atlite import geopandas as gpd import pandas as pd from _helpers import configure_logging logger = logging.getLogger(__name__) if __name__ == "__main__": if "snakemake" not in globals(): from _helpers import mock_snakemake snakemake = mock_snakemake("build_cutout", cutout="europe-2013-era5") configure_logging(snakemake) cutout_params = snakemake.params.cutouts[snakemake.wildcards.cutout] snapshots = pd.date_range(freq="h", **snakemake.params.snapshots) time = [snapshots[0], snapshots[-1]] cutout_params["time"] = slice(*cutout_params.get("time", time)) if {"x", "y", "bounds"}.isdisjoint(cutout_params): # Determine the bounds from bus regions with a buffer of two grid cells onshore = gpd.read_file(snakemake.input.regions_onshore) offshore = gpd.read_file(snakemake.input.regions_offshore) regions = pd.concat([onshore, offshore]) d = max(cutout_params.get("dx", 0.25), cutout_params.get("dy", 0.25)) * 2 cutout_params["bounds"] = regions.total_bounds + [-d, -d, d, d] elif {"x", "y"}.issubset(cutout_params): cutout_params["x"] = slice(*cutout_params["x"]) cutout_params["y"] = slice(*cutout_params["y"]) logging.info(f"Preparing cutout with parameters {cutout_params}.") features = cutout_params.pop("features", None) cutout = atlite.Cutout(snakemake.output[0], **cutout_params) cutout.prepare(features=features)