Data from: Improving access and use of climate projections for ecological research through the use of a new Python tool
Data files
Feb 22, 2024 version files 21.26 KB
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chelsa_cmip6.zip
17.74 KB
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README.md
3.52 KB
Abstract
Over the past decade, the use of future climate projections from the Coupled Model Intercomparison Project (CMIP) has become central in biodiversity science. Pre-packaged datasets containing future projections of the widely used bioclimatic variables, for different times and socio-economic pathways, have contributed immensely to the study of climate change implications for biodiversity. However, these datasets lack the flexibility to obtain projections to other target years, and the use of raw data requires coding and spatial information systems expertise. The Python tool, chelsa-cmip6, developed by Karger et. al 2023 provides the flexibility needed by allowing users to generate bioclimatic variables for the time of their choice provided the selected general circulation model and socioeconomic pathway combination exists. This is a fantastic step forward in bringing flexibility to the use of climate datasets in biodiversity and will allow for more widespread use of data provided by CMIP6. We hope it also will prompt the development of more user-friendly tools for the study of the effects of climate change on biodiversity.
README: Improving access and use of climate projections for ecological research through the use of a new Python tool
https://doi.org/10.5061/dryad.3r2280gph
# Improving access and use of climate projections for ecological research through the use of a new Python tool
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Brief summary of contents
Data archive for:
Improving access and use of climate projections for ecological research through the use of a new Python tool
by Andrea Paz, Thomas Lauber, Thomas W. Crowther and Johan van den Hoogen
This archive contains an example notebook script that allows the user to check if the desired combination of GCM and SSP is available for the selected time and area, and then uses the chelsa-cmip6 Python tool (Karger et al 2023) to create bioclimatic variables based on the user-selected scenarios. The bioclimatic variables can then be converted to GeoTiffs, downloaded and used in different applications through R, Python, Google Earth Engine, or others.
This Notebook can be opened locally or uploaded to Google Colab, Deepnote, etc. If uploaded to a platform make sure that the required files are also uploaded to the same folder.
## Description of the data and file structure
The main file is a Jupyter notebook (chelsa_cmip6.ipynb) that requires the modules.py and the requirements.txt files.
The requirements.txt file contains the required python packages that need to be installed prior to running the Jupyter Notebook. This can be done from the Jupyter Notebook by running the first cell.
The modules.py file contains all functions that are required for running the Jupyter Notebook successfully. These functions are loaded by running the second cell in the Jupyter Notebook.
### Schema of data archive
```bash
|- README.md
+---chelsa_cmip6
| chelsa_cmip6.ipynb
| modules.py
| requirements.txt
```
### File details
#### Details for: chelsa_cmip6.ipynb
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* Description: The Jupyter Notebook that allows to check for which combination of GCM and SSP the user can generate bioclimatic variables using the chelsa-cmip6 Python tool (Karger et al 2023). The tool will only work if both historical and future experiments are available for all input variables. Therefore, the user can first check which combinations of GCM members and SSP scenarios are available. Then, the bioclimatic variables can be created using the chelsa-cmip6 Python tool (Karger et al 2023) for the chosen combination of model members, SSP scenarios, a region of interest and the future periods of interest. In a last step, the bioclimatic variables can then be converted to GeoTiffs.
* Format(s): .ipynb
#### Details for: modules.py
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* Description: This python script contains all the functions needed for the Jupyter Notebook. The functions are separated from the Notebook to facilitate the user inputs. They include functions to (i) check the required GCM and SSP combinations, (ii) plot a region of interest, (iii) run the chelsa-cmip6 Python tool (Karger et al 2023) and (iv) convert the NetCDF files into GeoTiffs.
* Format(s): .py
#### Details for: requirements.txt
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* Description: This text file contains the required python packages. The required python packages can be installed using this requirements files.
* Format(s): .txt
## References
Karger, D. N., Chauvier, Y., & Zimmermann, N. E. (2023). chelsa‐cmip6 1.0: a python package to create high resolution bioclimatic variables based on CHELSA ver. 2.1 and CMIP6 data. Ecography, e06535.
Methods
This is a jupiter notebook that allows the user to check if the desired combination of GCM and SSP is available for the selected time and area, and then uses the chelsa-cmip6 tool to create bioclimatic variables based on the user-selected scenarios. This notebook was created to facilitate use of the chelsa-cmip6 Python tool by Karger et al 2023.