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Readme in markdown rather than rst, minor additions.

Author: euronion

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README.md

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+Atlite
+======
+
+Atlite is a [free
+software](http://www.gnu.org/philosophy/free-sw.en.html),
+[xarray](http://xarray.pydata.org/en/stable/)-based Python library for
+converting weather data (such as wind speeds, solar radiation,
+temperature and runoff) into power systems data (such as wind power,
+solar power, hydro power and heating demand time series). It is designed
+to work with big datasets, such as hourly global weather data over
+several years at spatial resolutions down to e.g. 0.1 x 0.1 degree
+resolution.
+
+Atlite was originally conceived as a light-weight version of the Aarhus
+University RE Atlas, which produces wind and solar generation time
+series from historical reanalysis data. It has since been extended to
+use weather datasets simulated with projected climate change and to
+compute other time series, such as hydro power, solar thermal collectors
+and heating demand. Atlite is designed to be modular, so that it can
+work with any weather datasets. It currently has modules for the
+following datasets:
+
+-   [NCEP Climate Forecast
+    System](http://rda.ucar.edu/datasets/ds094.1/) hourly historical
+    reanalysis weather data available on a 0.2 x 0.2 degree global grid
+-   [EURO-CORDEX Climate Change Projection](http://www.euro-cordex.net/)
+    three-hourly up until 2100, available on a 0.11 x 0.11 degree grid
+    for Europe
+-   [ECMWF
+    ERA5](https://software.ecmwf.int/wiki/display/CKB/ERA5+data+documentation)
+    hourly historical reanalysis weather data on an approximately 0.3 x
+    0.3 deg global grid
+-   [CMSAF
+    SARAH-2](https://wui.cmsaf.eu/safira/action/viewDoiDetails?acronym=SARAH_V002)
+    half-hourly historical surface radiation on a 0.05 x 0.05 deg grid
+    available for Europe and Africa (automatically interpolated to a 0.2
+    deg grid and combined with ERA5 temperature).
+
+It can process the following weather data fields:
+
+-   Temperature
+-   Downward short-wave radiation
+-   Upward short-wave radiation
+-   Wind speeds
+-   Runoff
+-   Surface roughness
+-   Height maps
+-   Soil temperature
+
+The following power-system relevant time series can be produced for all
+possible spatial distributions of assets:
+
+-   Wind power generation for a given turbine type
+-   Solar PV power generation for a given panel type
+-   Solar thermal collector heat output
+-   Hydroelectric inflow (simplified)
+-   Heating demand (based on the degree-day approximation)
+
+As of 2018 Atlite is under heavy development and therefore it is
+recommended to use caution when using it in a production environment.
+
+Citation for Aarhus University RE Atlas:
+> G. B. Andresen, A. A. Søndergaard, M. Greiner, "Validation of danish wind time series from a
+new global renewable energy atlas for energy system analysis," Energy
+93, Part 1 (2015) 1074 – 1088.
+<doi:http://dx.doi.org/10.1016/j.energy.2015.09.071>.
+
+Atlite was initially developed by the [Renewable Energy
+Group](https://fias.uni-frankfurt.de/physics/schramm/renewable-energy-system-and-network-analysis/)
+at [FIAS](https://fias.uni-frankfurt.de/) to carry out simulations for
+the [CoNDyNet project](http://condynet.de/), financed by the [German
+Federal Ministry for Education and Research
+(BMBF)](https://www.bmbf.de/en/index.html) as part of the [Stromnetze
+Research
+Initiative](http://forschung-stromnetze.info/projekte/grundlagen-und-konzepte-fuer-effiziente-dezentrale-stromnetze/).
+
+Getting started
+---------------
+
+-   Install atlite from this repository with all its library
+    dependencies\
+    ```pip install git+https://github.com/FRESNA/atlite.git```
+-   Download one of the weather datasets listed above:
+    * Data from ERA5 is downloaded automatically (TODO unclear: when and where?)
+-   Adjust the [atlite/config.py](atlite/config.py) directory paths to
+    point to the directory where you downloaded the dataset
+-   Create a cutout, i.e. a geographical rectangle and a selection of
+    times, e.g. all hours in 2011 and 2012, to narrow down the scope
+    -see [examples/create\_cutout.py](examples/create_cutout.py)
+-   Select a sparse matrix of the geographical points inside the cutout
+    you want to aggregate for your time series, and pass it to the
+    appropriate converter function - see [examples/](examples/)
+
+Licence
+-------
+
+Copyright 2016-2017 Gorm Andresen (Aarhus University), Jonas Hörsch
+(FIAS), Tom Brown (FIAS), Markus Schlott (FIAS), David Schlachtberger
+(FIAS)
+
+This program (atlite) is free software: you can redistribute it and/or
+modify it under the terms of the GNU General Public License as published
+by the Free Software Foundation; either [version 3 of the
+License](LICENSE.txt), or (at your option) any later version.
+
+This program is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the [GNU
+General Public License](LICENSE.txt) for more details.