LogoClim: WorldClim in NetLogo

Overview

This document is a mirror for a paper made for the Journal of Open Source Software (JOSS) about the LogoClim model. The final product is available in the paper folder.

The paper starts here.

Summary

LogoClim is a NetLogo model designed to simulate and visualize climate conditions, serving as a powerful tool for exploring both historical and projected climate data. Its primary goal is to facilitate the integration of climate data into agent-based models (ABMs) and enhance the reproducibility of these simulations.

The model utilizes raster data to represent climate variables such as temperature and precipitation over time. It incorporates historical data (1960-2021) 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 are sourced from WorldClim 2.1, which provides high-resolution interpolated datasets derived from weather station records worldwide (Fick & Hijmans, 2017).

LogoClim follows the FAIR Principles for Research Software (FAIR4RS) (Barker et al., 2022) and is openly available on the CoMSES Network and GitHub. Figure 1 showcases the functionality of the model.

Figure 1: LogoClim’s graphical user interface.

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 widely 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, standardization, and reusability among researchers (Barba, 2022; 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 (ls) 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 created as part of a project of the Sustentarea Research and Extension Center, which aims to evaluate the impact of climate change on the health and nutrition of Brazilian children under five years old (Carvalho et al., 2023). LogoClim functions as a submodel for an ABM designed to help researchers, policymakers, and practitioners better understand the potential consequences of climate change on this vulnerable population.

Acknowledgements

We gratefully acknowledge the contributions of Stephen E. Fick, Robert J. Hijmans, and the entire WorldClim team for their dedication to developing and maintaining the WorldClim datasets.

We also thank the World Climate Research Programme (WCRP), which, through its Working Group on Coupled Modelling, coordinated and promoted the Coupled Model Intercomparison Project Phase 6 (CMIP6).

We acknowledge the climate modeling groups for producing and sharing their outputs; the Earth System Grid Federation (ESGF) for archiving and facilitating access to the data; and the many funding agencies that support both CMIP6 and ESGF.

Finally, we recognize the Sustentarea Research and Extension Center at the University of São Paulo (USP) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for their support in the development of this project.

Author contributions

The roles below were defined based on the Contributor Roles Taxonomy (CRediT).

Daniel Vartanian: Conceptualization, Methodology, Data curation, Software, Validation, Project administration, Writing – Review & editing.

Leandro Martin Totaro Garcia: Validation, Writing – Review & editing.

Aline Martins de Carvalho: Conceptualization, Funding acquisition, Validation, Project administration, Supervision, Writing – Review & editing.

The paper ends here.

License

The code in this paper is licensed under the MIT License, while the document are available under the Creative Commons Attribution 4.0 International License.

Citation

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

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

A BibTeX entry for LaTeX users is

@techreport{vartanian2025,
  title = {LogoClim: WorldClim in NetLogo},
  author = {{Daniel Vartanian} and {Leandro Martin Totaro 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/}
}

References

Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature, 533(7604), 452–454. https://doi.org/10.1038/533452a

Barba, L. A. (2022). Defining the role of open source software in research reproducibility. Computer, 55(8), 40–48. https://doi.org/10.1109/MC.2022.3177133

Barker, M., Chue Hong, N. P., Katz, D. S., Lamprecht, A.-L., Martinez-Ortiz, C., Psomopoulos, F., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., & Honeyman, T. (2022). Introducing the FAIR Principles for research software. Scientific Data, 9(1), 622. https://doi.org/10.1038/s41597-022-01710-x

Carvalho, A. M. de, Klapka, C. S., Magalhães, A. R., Barbosa, B. B., Vartanian, D., & Pereira, E. B. (2023). Global syndemic: The impact of anthropogenic climate change on the health and nutrition of children under five years old attended by Brazil’s public health system (SUS) [Data set]. https://doi.org/10.17605/OSF.IO/8W36C

Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315. https://doi.org/10.1002/joc.5086

Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., Huse, G., Huth, A., Jepsen, J. U., Jørgensen, C., Mooij, W. M., Müller, B., Pe’er, G., Piou, C., Railsback, S. F., Robbins, A. M., … DeAngelis, D. L. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1), 115–126. https://doi.org/10.1016/j.ecolmodel.2006.04.023

Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., DeAngelis, D. L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J., Johnston, A. S. A., Milles, A., Nabe-Nielsen, J., Polhill, J. G., Radchuk, V., Rohwäder, M.-S., Stillman, R. A., Thiele, J. C., & Ayllón, D. (2020). The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. Journal of Artificial Societies and Social Simulation, 23(2), 7. https://doi.org/10.18564/jasss.4259

Hjorth, A., Head, B., Brady, C., & Wilensky, U. (2020). LevelSpace: A NetLogo extension for multi-level agent-based modeling. Journal of Artificial Societies and Social Simulation, 23(1), 4. https://doi.org/10.18564/jasss.4130

O’Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K., Rothman, D. S., van Ruijven, B. J., van Vuuren, D. P., Birkmann, J., Kok, K., Levy, M., & Solecki, W. (2017). The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Global Environmental Change, 42, 169–180. https://doi.org/10.1016/j.gloenvcha.2015.01.004

Peng, R. D. (2011). Reproducible research in computational science. Science, 334(6060), 1226–1227. https://doi.org/10.1126/science.1213847

Ram, K., Boettiger, C., Chamberlain, S., Ross, N., Salmon, M., & Butland, S. (2019). A community of practice around peer review for long-term research software sustainability. Computing in Science & Engineering, 21(2), 59–65. https://doi.org/10.1109/MCSE.2018.2882753