# CLIMADA
CLIMADA stands for **CLIM**ate **ADA**ptation and is a probabilistic natural catastrophe impact model, that also calculates averted damage (benefit) thanks to adaptation measures of any kind (from grey to green infrastructure, behavioural, etc.).
As of today, CLIMADA provides global coverage of major climate-related extreme-weather hazards at high resolution via a [data API](https://climada.ethz.ch/data-api/v1/docs), namely (i) tropical cyclones, (ii) river flood, (iii) agro drought and (iv) European winter storms, all at 4km spatial resolution - wildfire to be added soon. For all hazards, historic and probabilistic event sets exist, for some also under select climate forcing scenarios (RCPs) at distinct time horizons (e.g. 2040). See also [papers](https://github.com/CLIMADA-project/climada_papers) for details.
CLIMADA is divided into two parts (two repositories):
1. the core [climada_python](https://github.com/CLIMADA-project/climada_python) contains all the modules necessary for the probabilistic impact, the averted damage, uncertainty and forecast calculations. Data for hazard, exposures and impact functions can be obtained from the [data API](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_util_api_client.ipynb). [Litpop](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_entity_LitPop.ipynb) is included as demo Exposures module, and [Tropical cyclones](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_hazard_TropCyclone.ipynb) is included as a demo Hazard module.
2. the petals [climada_petals](https://github.com/CLIMADA-project/climada_petals) contains all the modules for generating data (e.g., TC_Surge, WildFire, OpenStreeMap, ...). Most development is done here. The petals builds-upon the core and does not work as a stand-alone.
It is recommend for new users to begin with the core (1) and the [tutorials](https://github.com/CLIMADA-project/climada_python/tree/main/doc/tutorial) therein.
This is the Python (3.8+) version of CLIMADA - please see https://github.com/davidnbresch/climada for backward compatibility (MATLAB).
## Getting started
CLIMADA runs on Windows, macOS and Linux.
The released versions of CLIMADA are available from [conda-forge](https://anaconda.org/conda-forge/climada-petals).
Use the [Mamba](https://mamba.readthedocs.io/en/latest/) package manager to install it:
```shell
mamba install -c conda-forge climada-petals
```
It is **highly recommended** to install CLIMADA into a **separate** Conda environment.
See the [installation guide](https://climada-python.readthedocs.io/en/latest/guide/install.html) for further information.
Follow the [tutorial](https://climada-python.readthedocs.io/en/latest/tutorial/1_main_climada.html) `climada_python-x.y.z/doc/tutorial/1_main_climada.ipynb` in a Jupyter Notebook to see what can be done with CLIMADA and how.
## Documentation
Documentation is available on Read the Docs:
Note that all the documentations has two versions,'latest' and 'stable', and explicit version numbers, such as 'v3.1.1', in the url path. 'latest' is created from the 'develop' branch and has the latest changes by developers, 'stable' from the latest release. For more details about documentation versions, please have a look at [here](https://readthedocs.org/projects/climada-python/versions/).
CLIMADA python:
* [online (recommended)](https://climada-python.readthedocs.io/en/latest/)
* [PDF file](https://climada-python.readthedocs.io/_/downloads/en/stable/pdf/)
CLIMADA petals:
* [online (recommended)](https://climada-petals.readthedocs.io/en/latest/)
* [PDF file](https://climada-petals.readthedocs.io/_/downloads/en/stable/pdf/)
* [petals Tutorials on GitHub](https://github.com/CLIMADA-project/climada_petals/tree/main/doc/tutorial)
The documentation can also be [built locally](https://climada-python.readthedocs.io/en/latest/README.html).
## Citing CLIMADA
If you use CLIMADA please cite (in general, in particular for academic work) :
The [used version](https://zenodo.org/search?page=1&size=20&q=climada)
and/or the following published articles:
Aznar-Siguan, G. and Bresch, D. N., 2019: CLIMADA v1: a global weather and climate risk assessment platform, Geosci. Model Dev., 12, 3085–3097, https://doi.org/10.5194/gmd-12-3085-2019
Bresch, D. N. and Aznar-Siguan, G., 2021: CLIMADA v1.4.1: towards a globally consistent adaptation options appraisal tool, Geosci. Model Dev., 14, 351-363, https://doi.org/10.5194/gmd-14-351-2021
Please see all CLIMADA-related scientific publications in our [repository of scientific publications](https://github.com/CLIMADA-project/climada_papers) and cite according to your use of select features, be it hazard set(s), exposure(s) ...
In presentations or other graphical material, as well as in reports etc., where applicable, please add the logo as follows:\
As key link, please use https://wcr.ethz.ch/research/climada.html, as it will last and provides a bit of an intro, especially for those not familiar with GitHub - plus a nice CLIMADA infographic towards the bottom of the page
## Contributing
See the [Contribution Guide](https://climada-python.readthedocs.io/en/latest/misc/CONTRIBUTING.html).
## Versioning
We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [releases on this repository](https://github.com/CLIMADA-project/climada_petals/releases).
## License
Copyright (C) 2017 ETH Zurich, CLIMADA contributors listed in AUTHORS.
CLIMADA is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License Version 3, 29 June 2007 as published by the Free Software Foundation, https://www.gnu.org/licenses/gpl-3.0.html
CLIMADA 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 for more details: https://www.gnu.org/licenses/gpl-3.0.html
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"description": "# CLIMADA\n\nCLIMADA stands for **CLIM**ate **ADA**ptation and is a probabilistic natural catastrophe impact model, that also calculates averted damage (benefit) thanks to adaptation measures of any kind (from grey to green infrastructure, behavioural, etc.).\n\nAs of today, CLIMADA provides global coverage of major climate-related extreme-weather hazards at high resolution via a [data API](https://climada.ethz.ch/data-api/v1/docs), namely (i) tropical cyclones, (ii) river flood, (iii) agro drought and (iv) European winter storms, all at 4km spatial resolution - wildfire to be added soon. For all hazards, historic and probabilistic event sets exist, for some also under select climate forcing scenarios (RCPs) at distinct time horizons (e.g. 2040). See also [papers](https://github.com/CLIMADA-project/climada_papers) for details.\n\nCLIMADA is divided into two parts (two repositories):\n\n1. the core [climada_python](https://github.com/CLIMADA-project/climada_python) contains all the modules necessary for the probabilistic impact, the averted damage, uncertainty and forecast calculations. Data for hazard, exposures and impact functions can be obtained from the [data API](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_util_api_client.ipynb). [Litpop](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_entity_LitPop.ipynb) is included as demo Exposures module, and [Tropical cyclones](https://github.com/CLIMADA-project/climada_python/blob/main/doc/tutorial/climada_hazard_TropCyclone.ipynb) is included as a demo Hazard module.\n2. the petals [climada_petals](https://github.com/CLIMADA-project/climada_petals) contains all the modules for generating data (e.g., TC_Surge, WildFire, OpenStreeMap, ...). Most development is done here. The petals builds-upon the core and does not work as a stand-alone.\n\nIt is recommend for new users to begin with the core (1) and the [tutorials](https://github.com/CLIMADA-project/climada_python/tree/main/doc/tutorial) therein.\n\nThis is the Python (3.8+) version of CLIMADA - please see https://github.com/davidnbresch/climada for backward compatibility (MATLAB).\n\n## Getting started\n\nCLIMADA runs on Windows, macOS and Linux.\nThe released versions of CLIMADA are available from [conda-forge](https://anaconda.org/conda-forge/climada-petals).\nUse the [Mamba](https://mamba.readthedocs.io/en/latest/) package manager to install it:\n\n```shell\nmamba install -c conda-forge climada-petals\n```\n\nIt is **highly recommended** to install CLIMADA into a **separate** Conda environment.\nSee the [installation guide](https://climada-python.readthedocs.io/en/latest/guide/install.html) for further information.\n\nFollow the [tutorial](https://climada-python.readthedocs.io/en/latest/tutorial/1_main_climada.html) `climada_python-x.y.z/doc/tutorial/1_main_climada.ipynb` in a Jupyter Notebook to see what can be done with CLIMADA and how.\n\n## Documentation\n\nDocumentation is available on Read the Docs:\n\nNote that all the documentations has two versions,'latest' and 'stable', and explicit version numbers, such as 'v3.1.1', in the url path. 'latest' is created from the 'develop' branch and has the latest changes by developers, 'stable' from the latest release. For more details about documentation versions, please have a look at [here](https://readthedocs.org/projects/climada-python/versions/).\n\nCLIMADA python:\n\n* [online (recommended)](https://climada-python.readthedocs.io/en/latest/)\n* [PDF file](https://climada-python.readthedocs.io/_/downloads/en/stable/pdf/)\n\nCLIMADA petals:\n\n* [online (recommended)](https://climada-petals.readthedocs.io/en/latest/)\n* [PDF file](https://climada-petals.readthedocs.io/_/downloads/en/stable/pdf/)\n* [petals Tutorials on GitHub](https://github.com/CLIMADA-project/climada_petals/tree/main/doc/tutorial)\n\nThe documentation can also be [built locally](https://climada-python.readthedocs.io/en/latest/README.html).\n\n## Citing CLIMADA\n\nIf you use CLIMADA please cite (in general, in particular for academic work) :\n\nThe [used version](https://zenodo.org/search?page=1&size=20&q=climada)\n\nand/or the following published articles:\n\nAznar-Siguan, G. and Bresch, D. N., 2019: CLIMADA v1: a global weather and climate risk assessment platform, Geosci. Model Dev., 12, 3085\u20133097, https://doi.org/10.5194/gmd-12-3085-2019\n\nBresch, D. N. and Aznar-Siguan, G., 2021: CLIMADA v1.4.1: towards a globally consistent adaptation options appraisal tool, Geosci. Model Dev., 14, 351-363, https://doi.org/10.5194/gmd-14-351-2021\n\nPlease see all CLIMADA-related scientific publications in our [repository of scientific publications](https://github.com/CLIMADA-project/climada_papers) and cite according to your use of select features, be it hazard set(s), exposure(s) ...\n\nIn presentations or other graphical material, as well as in reports etc., where applicable, please add the logo as follows:\\\n\n\nAs key link, please use https://wcr.ethz.ch/research/climada.html, as it will last and provides a bit of an intro, especially for those not familiar with GitHub - plus a nice CLIMADA infographic towards the bottom of the page\n\n## Contributing\n\nSee the [Contribution Guide](https://climada-python.readthedocs.io/en/latest/misc/CONTRIBUTING.html).\n\n## Versioning\n\nWe use [SemVer](http://semver.org/) for versioning. 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