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31 changes: 17 additions & 14 deletions README.md
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option appraisal. Designed by a large scientific community, it helps reasearchers, policymakers, and businesses analyse the impacts of natural hazards and
explore adaptation strategies.

As of today, CLIMADA provides global coverage of major climate-related extreme-weather hazards at high resolution (4x4km) via a [data API](https://climada.ethz.ch/data-api/v1/docs) For select hazards, historic and probabilistic events sets, for past, present and future climate exist at distinct time horizons.
You will find a repository containing scientific peer-reviewed articles that explain software components implemented in CLIMADA [here](https://github.com/CLIMADA-project/climada_papers).
## Overview

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.
1. [Core (`climada_python`)](https://github.com/CLIMADA-project/climada_python) contains all the modules necessary for computing probabilistic impact, averted damage, and uncertainty, sensitivity analysis and impact function calibration. Data for hazard, exposures and impact functions can be obtained from the [data API](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_util_api_client.ipynb). [Litpop](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_entity_LitPop.ipynb) is included as demo Exposures module, and [Tropical cyclones](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_hazard_TropCyclone.ipynb) is included as a demo Hazard module.
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1. [Core (`climada_python`)](https://github.com/CLIMADA-project/climada_python) contains all the modules necessary for computing probabilistic impact, averted damage, and uncertainty, sensitivity analysis and impact function calibration. Data for hazard, exposures and impact functions can be obtained from the [data API](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_util_api_client.ipynb). [Litpop](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_entity_LitPop.ipynb) is included as demo Exposures module, and [Tropical cyclones](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_hazard_TropCyclone.ipynb) is included as a demo Hazard module.
1. [Core (`climada_python`)](https://github.com/CLIMADA-project/climada_python) contains all the modules necessary for computing probabilistic impact, averted damage, and peform uncertainty, sensitivity analysis and impact function calibration. Demonstration data for hazard, exposures and impact functions can be obtained from the [data API](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_util_api_client.ipynb). [Litpop](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_entity_LitPop.ipynb) is included as demo Exposures module, and [Tropical cyclones](https://github.com/CLIMADA-project/climada_python/blob/main/doc/user-guide/climada_hazard_TropCyclone.ipynb) is included as a demo Hazard module.

2. [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. Petals is an extension of Core and does **not** work as a stand-alone module.

For new users, we recommend to begin with the core (1) and the [tutorials](https://github.com/CLIMADA-project/climada_python/tree/main/doc/tutorial) therein.
For new users, we recommend to begin with Core (1) and the [tutorials](https://github.com/CLIMADA-project/climada_python/tree/main/doc/user-guide) therein.

This is the Python version of CLIMADA - please see [here](https://github.com/davidnbresch/climada) for backward compatibility with the MATLAB version.
A [publication repository](https://github.com/CLIMADA-project/climada_papers) contains scientific, peer-reviewed articles that explain software components implemented in CLIMADA.
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Based on feedback from the CLIMADA Days:

Suggested change
A [publication repository](https://github.com/CLIMADA-project/climada_papers) contains scientific, peer-reviewed articles that explain software components implemented in CLIMADA.
A [publication repository](https://github.com/CLIMADA-project/climada_papers) contains code and data used in CLIMADA case-studies for scientific, peer-reviewed articles.

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hmmm I am not sure what feedback this is referring too. Maybe the one saying that it is hard to find examples of CLIMADA applications? In this case I would formulate it differently. Maybe?

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A [publication repository](https://github.com/CLIMADA-project/climada_papers) contains scientific, peer-reviewed articles that explain software components implemented in CLIMADA.
A [repository](https://github.com/CLIMADA-project/climada_papers) contains case-study examples most of them in the form of scientific, peer-reviewed articles that further explain software components implemented in CLIMADA.

Otherwise I feel it is even more innaccessible to practitionners that are looking for examples, not scientific studies per se.


CLIMADA provides global coverage of major climate-related extreme-weather hazards at high resolution (4x4km) via a [data API](https://climada.ethz.ch/data-api/v1/docs) for select hazards, historic and probabilistic events sets, for past, present and future climate exist at distinct time horizons.

This is the Python version of CLIMADA - For backward compatibility with the MATLAB version please see https://github.com/davidnbresch/climada.

## Getting started

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```

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.
See the [installation guide](https://climada-python.readthedocs.io/en/latest/getting-started/install.html) for further information.

Follow the [tutorials](https://climada-python.readthedocs.io/en/stable/tutorial/1_main_climada.html) in a Jupyter Notebook to see what can be done with CLIMADA and how.
Follow the [tutorials](https://climada-python.readthedocs.io/en/stable/user-guide/1_main_climada.html) in a Jupyter Notebook to see what can be done with CLIMADA and how.

## Documentation

The online documentation is available on [Read the Docs](https://climada-python.readthedocs.io/en/stable/).The documentation of each release version of CLIMADA can be accessed separately through the drop-down menu at the bottom of the left sidebar. Additionally, the version 'stable' refers to the most recent release (installed via `conda`), and 'latest' refers to the latest unstable development version (the `develop` branch).
The online documentation is available on [Read the Docs](https://climada-python.readthedocs.io/en/stable/). The documentation of each release version of CLIMADA can be accessed separately through the drop-down menu at the bottom of the left sidebar. Additionally, the version 'stable' refers to the most recent release (installed via `conda`), and 'latest' refers to the latest unstable development version (the `develop` branch).

CLIMADA python:
CLIMADA Core (`climada_python`):

- [online (recommended)](https://climada-python.readthedocs.io/en/latest/)
- [PDF file](https://climada-python.readthedocs.io/_/downloads/en/stable/pdf/)
- [core Tutorials on GitHub](https://github.com/CLIMADA-project/climada_python/tree/main/doc/tutorial)
- [Core tutorials on GitHub](https://github.com/CLIMADA-project/climada_python/tree/main/doc/user-guide)

CLIMADA petals:
CLIMADA Petals (`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)
- [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).

Expand All @@ -59,7 +62,7 @@ See the [Citation Guide](https://climada-python.readthedocs.io/en/latest/misc/ci

Please use the following logo if you are presenting results obtained with or through CLIMADA:

![https://github.com/CLIMADA-project/climada_python/blob/main/doc/guide/img/CLIMADA_logo_QR.png](https://github.com/CLIMADA-project/climada_python/blob/main/doc/guide/img/CLIMADA_logo_QR.png?raw=true)
![https://github.com/CLIMADA-project/climada_python/blob/main/doc/guide/img/CLIMADA_logo_QR.png](https://github.com/CLIMADA-project/climada_python/blob/main/doc/development/img/CLIMADA_logo_QR.png?raw=true)

## Contributing

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