LogoClim: WorldClim in NetLogo

Overview

This document is a mirror of a paper prepared for the Journal of Open Source Software (JOSS), describing the LogoClim model. The final version is available in the paper folder.

The paper starts here.

Summary

LogoClim is a NetLogo model for simulating and visualizing global climate conditions. It allows researchers to integrate high-resolution climate data into agent-based models, supporting reproducible research in ecology, agriculture, environmental sciences, and other fields that rely on climate data.

The model utilizes 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). All climate inputs come from WorldClim 2.1, a widely used source of high-resolution, interpolated climate datasets based on weather station observations worldwide (Fick & Hijmans, 2017), available for academic and other non-commercial use.

LogoClim follows the FAIR Principles for Research Software (Barker et al., 2022) and is openly available on the CoMSES Network and GitHub. Figure 1 and Figure 2 illustrate the model’s interface and functionality. See the Logônia model (Vartanian et al., 2025) for an example of its integration into a full NetLogo simulation.

Figure 1: LogoClim Graphical User Interface — Brazil.

Statement of need

The lack of reproducibility is a major concern in science (Baker, 2016), including in computational research (Peng, 2011). This challenge is particularly relevant for agent-based models, which are used to simulate complex phenomena (Grimm et al., 2006, 2020). One effective strategy to address this issue is the development of open, specialized tools that enhance transparency and promote standardization, and reusability among researchers (Berger et al., 2024; Ram et al., 2019). This is why LogoClim was created.

The LogoClim model was developed for seamless integration with other models through NetLogo’s LevelSpace extension (Hjorth et al., 2020), which enables parallel execution and data exchange between models. This integration capability makes it particularly valuable for agent-based simulations that incorporate climate data to study ecological, environmental, or social processes affected by climate conditions.

The model was originally developed as part of a project by the Sustentarea Research and Extension Center, aimed at evaluating the impact of climate change on the health and nutrition of Brazilian children under five years old (Carvalho et al., 2023). Over the course of its development, however, we realized that its applications extend well beyond the scope of that study.

While other programming languages, such as R, offer tools like the geodata package (Hijmans et al., 2024), there are currently no equivalent tools providing this functionality for NetLogo.

How it works

LogoClim operates on a grid of patches, with each patch representing a geographic area and storing values for latitude, longitude, and selected climate variables. During simulation, patches update their colors based on the underlying data, enabling users to visualize spatial and temporal changes. The model interface also provides plots showing the mean, minimum, maximum, and standard deviation of the selected variable over time.

The model supports all three climate data series from WorldClim 2.1: long-term historical climate averages (1970–2000), historical monthly weather (1951–2024), and future climate projections (2021–2100). Each series is available at multiple spatial resolutions (from 10 minutes (~340 km² at the equator) to 30 seconds (~1 km² at the equator)), which can be selected within the model interface. Further details about each series are available on the WorldClim website.

The datasets are available for download from WorldClim 2.1, but must be converted to ASCII format for compatibility with NetLogo. To simplify this workflow, we provide Quarto notebooks with reproducible pipelines for downloading and processing the data. These notebooks can be customized to meet specific research needs.

We also provide example datasets for testing and demonstration. These files are available in the model’s OSF repository and are ready to use with LogoClim. To illustrate how LogoClim can be used in practice, we also developed the Logônia model (Vartanian et al., 2025), which showcases its integration into a full NetLogo simulation.

Figure 2: LogoClim Graphical User Interface — United Kingdom.

Acknowledgements

We gratefully acknowledge Stephen E. Fick, Robert J. Hijmans, and the entire WorldClim team for their outstanding work in creating and maintaining the WorldClim datasets. LogoClim is an independent project with no affiliation to WorldClim or its developers. Users should note 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.

We also acknowledge the Sustentarea Research and Extension Center at the University of São Paulo (USP), the Department of Science and Technology of the Secretariat of Science, Technology, and Innovation and of the Health Economic-Industrial Complex (SECTICS) of the Ministry of Health of Brazil, and the National Council for Scientific and Technological Development (CNPq) for their support in the development of this project (grant no. 444588/2023-0).

The paper ends here.

How to cite

To cite this paper in publications please use the following format:

Vartanian, D., Garcia, L., & Carvalho, A. M. (2025). LogoClim: WorldClim in NetLogo [Manuscript]. Sustentarea Research and Extension Center at the University of São Paulo. https://sustentarea.github.io/logoclim-article

A BibTeX entry for LaTeX users is

@misc{vartanian2025,
  title = {LogoClim: WorldClim in NetLogo},
  author = {{Daniel Vartanian} and {Leandro Garcia} and {Aline Martins de Carvalho}},
  year = {2025},
  address = {São Paulo},
  institution = {Sustentarea Research and Extension Group at the University of São Paulo},
  langid = {en},
  url = {https://sustentarea.github.io/logoclim-article}
  note = {Manuscript}
}

License

This document is licensed under the Creative Commons Attribution 4.0 International License. This means you can share and adapt the material for any purpose, even commercially, as long as you give appropriate credit, provide a link to the license, and indicate if changes were made.

Acknowledgements

This work was developed with support from the Sustentarea Research and Extension Center at the University of São Paulo (USP).

This work was supported by the Department of Science and Technology of the Secretariat of Science, Technology, and Innovation and of the Health Economic-Industrial Complex (SECTICS) of the Ministry of Health of Brazil, and the National Council for Scientific and Technological Development (CNPq) (grant no. 444588/2023-0)

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