LogoClim

Overview

LogoClim is a NetLogo model designed to be integrated into other simulations through the LevelSpace extension (Hjorth et al., 2020), providing high resolution climate data from sources validated and used by the Intergovernmental Panel on Climate Change (IPCC).

The model simplifies and standardizes the integration of climate data into NetLogo, allowing researchers to focus their efforts on the model itself with the assurance of using reliable and widely recognized data. Although its main use is as a component of larger simulations, LogoClim also has its own graphical interface for monitoring and checking the datasets.

For a deep look into the model's structure and implementation, see the user manual.

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Note

LogoClim is an independent project with no affiliation to WorldClim or its developers. Users should be aware that WorldClim datasets are freely available for academic and other non-commercial use only. Any use of WorldClim data within LogoClim must comply with WorldClim's licensing terms.

How It Works

LogoClim uses raster data to represent climate variables such as temperature and precipitation over time. It incorporates historical data (1951-2024) and future climate projections (2021-2100) derived from global climate models under various Shared Socioeconomic Pathways (SSPs, O'Neill et al., 2017).

The model operates on a grid of patches, where each patch represents a geographical area and stores values for latitude, longitude, and selected climate variables. During the simulation, patches update their colors based on the data values. The results can be visualized on a map, accompanied by plots that display the mean, minimum, maximum, and standard deviation of the selected variable over time.

All climate inputs come from WorldClim 2.1, a widely used source of high-resolution climate datasets (Fick & Hijmans, 2017). These data series are offered at various spatial resolutions, ranging from 10 minutes (about 340 km² at the equator) to 30 seconds (about 1 km² at the equator).

Historical Climate Data

This series includes only 12 monthly data points representing long-term average climate conditions for the period 1970-2000. It provides averages on minimum, mean, and maximum temperature, precipitation, solar radiation, wind speed, vapor pressure, elevation, and on bioclimatic variables.

Historical Monthly Weather Data

This series includes 12 monthly data points for each year from 1951 to 2024, based on downscaled data from CRU-TS-4.09, developed by the Climatic Research Unit at the University of East Anglia (Harris et al., 2020). It provides monthly averages for minimum temperature, maximum temperature, and total precipitation.

Future Climate Data

This series includes 12 monthly data points from downscaled climate projections derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (Eyring et al., 2016) for four future periods: 2021-2040, 2041-2060, 2061-2080, and 2081-2100. The projections cover four Shared Socioeconomic Pathways (SSPs): 126, 245, 370, and 585, with data available for average minimum temperature, average maximum temperature, total precipitation, and bioclimatic variables.

Learn more about the data series in the WorldClim website.

Usage

To get started using LogoClim, you must have NetLogo installed. The model was developed with NetLogo 7.0.4. Use this version or newer for best compatibility. The NetLogo website provides easy installers for Windows, macOS, and Linux, along with detailed instructions for installation.

The model also depends on the NetLogo extensions: GIS, Pathdir, String, and Time. These extensions are installed automatically when the model is run for the first time.

With NetLogo ready, follow these steps to get LogoClim up and running.

A. Download the Model

You can download the latest release of the model from the CoMSES Network. This is the recommended option for most users, as it provides a stable version of the model that has been tested and documented.

For the development version, you can clone or download the model GitHub code repository directly.

B. Prepare the Data

The CoMSES Network release includes an example dataset that is ready to use with LogoClim. You can use it as a starting point. But, ideally you should prepare your own data to suit your research needs. The user manual will guide you through the process of downloading and preparing WorldClim data for use with LogoClim.

We also provide other example datasets for testing and demonstration. These files are available in the model's OSF repository and are ready to use with LogoClim. Please note that these datasets are for demonstration purposes only and are not suitable for research applications. Always verify the suitability of the data for your specific research questions and objectives.

C. Run the Model

With the files at hand, open the logoclim.nlogox file in NetLogo. You can find this file in the code directory when using the CoMSES Network release or in the nlogox folder when using the development version.

Use the Select Data Directory button in the model interface to specify their location. This will set the data-path global variable to the correct path, allowing the model to access the data. After that, you can configure the other parameters as needed.

Once everything is set, click on the Setup and then Go buttons to start the simulation. Learn more about the model interface and parameters in the model's Info Tab and the user manual.

Integration with Other Models

LogoClim was created to be integrated with other models using NetLogo's LevelSpace extension. This extension enables parallel execution and data exchange between models.

To facilitate this integration, we created the Logônia model (Vartanian et al., 2026), a fictional plant-growth model providing a practical example of how to integrate LogoClim. It is also available on the CoMSES Network and its code repository is available on GitHub. See the user manual for integration instructions.

User Manual

Note

This section describes the technical setup required to render the user manual locally. You do not need any of this to use LogoClim.

LogoClim's user manual is developed using the latest versions of the Quarto publishing system, the NetLogo environment, and the R programming language. To ensure consistent results, the renv R package is used to manage and restore the R environment.

To render the manual or reproduce its analyses locally, install the dependencies listed above and follow the steps below.

1. Clone this repository to your local machine.
2. Open the project in the terminal or in your preferred IDE.
3. Install package dependencies by running Rscript -e "renv::restore()" in the terminal or renv::restore() in an R console. Make sure R is installed and available in your system's PATH before running this command.
4. Open the Quarto notebook files (.qmd) and run the code as described.

To render the entire manual, run the following command in the terminal:

quarto render

The rendering process may take some time depending on your machine. Once complete, the Quarto book will be available in the docs folder.

Notes

• When running renv::restore(), check the output for any missing system dependencies like GDAL. These are usually installed automatically via your OS package manager, but if something fails, you may need to handle them manually. See render-manual.yaml for a list of system dependencies required for your operating system.
• We do not recommend using external environments such as Anaconda, as these can cause issues with R package installation and management. This project relies on several system dependencies, all of which are automatically installed via the Comprehensive R Archive Network (CRAN).
• We recommend using the installers provided by the R Project or the rig installation manager from r-lib when installing R. If your IDE lacks a built-in R console, consider installing arf for a better experience.
• Avoid using VPNs, corporate proxies, or other network-routing tools while processing the data, as these can interfere with the downloads.
• If you run into issues with renv (it can be a bit of a pain sometimes), you can use renv::deactivate(clean = TRUE) to remove the environment completely. In that case, you will need to install all required packages manually.

Contributing

Contributions are always welcome, whether that's reporting bugs, suggesting features, or improving the code or documentation.

Before opening a new issue, please check the issues tab to see if your topic has already been reported.

You can also support the development of LogoClim by becoming a sponsor.

Click here to make a donation. Please mention LogoClim in your donation message.

Citation

Note

When using WorldClim data, you must also cite the original data sources.

The appropriate citation depends on the specific dataset utilized. Please refer to the WorldClim website for up-to-date citation guidelines and dataset references.

If you use this model in your research, please cite it to acknowledge the effort invested in its development and maintenance. Your citation helps support the ongoing improvement of the model.

To cite LogoClim in publications please use the following format:

Vartanian, D., Garcia, L., & Carvalho, A. M. (2026). LogoClim: WorldClim in NetLogo [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21330590

A BibLaTeX entry for LaTeX users is:

@software{vartanian2026,
  title = {LogoClim: WorldClim in NetLogo},
  author = {{Daniel Vartanian} and {Leandro Garcia} and {Aline Martins de Carvalho}},
  year = {2026},
  doi = {10.5281/zenodo.21330590},
  publisher = {Zenodo}
}

License

Copyright (C) 2026 Sustentarea Research and Extension Center

LogoClim 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, 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 for more details.

You should have received a copy of the GNU General Public License along with
this program. If not, see <https://www.gnu.org/licenses/>.

Acknowledgments

We gratefully acknowledge Robert J. Hijmans, Stephen E. Fick, and the entire WorldClim team for their outstanding work in creating and maintaining the WorldClim datasets.

We thank the Climatic Research Unit at the University of East Anglia and the United Kingdom's Met Office for developing and providing access to the CRU-TS-4.09 dataset, a vital source of historical climate data.

We also acknowledge the World Climate Research Programme (WCRP), its Working Group on Coupled Modelling, and the Coupled Model Intercomparison Project Phase 6 (CMIP6) for coordinating and advancing global climate model development.

We are grateful to the climate modeling groups for producing and sharing their model outputs, the Earth System Grid Federation (ESGF) for archiving and providing access to the data, and the many funding agencies that support CMIP6 and ESGF.

This work was supported by the Sustentarea Research and Extension Center at the University of São Paulo (USP).

This work was supported by the Resiclima Network, an international collaboration for the multidimensional and interdisciplinary study of global climate change.

This work was supported by the National Council for Scientific and Technological Development (CNPq) of the Ministry of Science, Technology and Innovation (MCTI) of Brazil and by the Department of Science and Technology (DECIT) of the Secretariat of Science, Technology, Innovation and Strategic Health Inputs (SECTICS) of the Ministry of Health (MS) of Brazil, through Call CNPq/DECIT/SECTICS/MS No. 18/2023 (No. 444588/2023-0).