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).
See the Logônia model for an
example of how to integrate LogoClim into your model.
If you find this project useful, please consider giving it a star!
Important
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.
LogoClim 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.
The model supports simulation with all three climate data series provided by WorldClim 2.1. Each series is available at multiple spatial resolutions (from 10 minutes (~340 km² at the equator) to 30 seconds (~1 km² at the equator)) and can be selected within the model interface to fit your research needs. More information about each series can be found in the WorldClim website.
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.
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. It provides monthly averages for minimum temperature, maximum temperature, and total precipitation.
This series includes 12 monthly data points from downscaled climate projections derived from CMIP6 models for four future periods: 2021-2040, 2041-2060, 2061-2080, and 2081-2100. The projections cover four SSPs: 126, 245, 370, and 585, with data available for average minimum temperature, average maximum temperature, total precipitation, and bioclimatic variables.
Refer to the Info tab in the model for additional details.
To get started, ensure you have NetLogo installed. This model was developed using NetLogo 7.0.0, so it is recommended to use this version or later.
The model relies on the GIS,
Pathdir,
String, and
Time NetLogo extensions. These
are automatically installed when the model is run for the first time.
You can download the latest release of the model from its GitHub releases page. For the development version, you can clone or download its GitHub repository directly.
To run the model, make sure to download all files in the nlogox
folder. Note that climate data from WorldClim is required but not
included in this repository; see the next section for instructions on
obtaining and preparing the data.
LogoClim relies on raster data to represent climate variables. 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 in the repository qmd folder
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.
After downloading and processing the files, place them in the data
folder within the model’s directory. Alternatively, you can use the
Select Data Directory button in the model interface to specify the
location of your data files.
We suggest starting with the 10-minute resolution to verify that the model runs smoothly on your system before trying higher resolutions.
Once everything is set, open the logoclim.nlogox file located in the
nlogox folder to start exploring!
Refer to the Info tab in the model for additional details.
LogoClim was created to be integrated with other models using
NetLogo’s
LevelSpace
extension. This extension enables parallel execution and data exchange
between models.
See the Logônia model for an
example of how to integrate LogoClim into your model.
Important
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. (2025). LogoClim: WorldClim in NetLogo [Computer software]. https://doi.org/10.17605/OSF.IO/EAPZU
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},
doi = {10.17605/OSF.IO/EAPZU},
note = {Computer software}
}Contributions are welcome! Whether you want to report bugs, suggest features, or improve the code or documentation, your input is highly valued. Please check the issues tab for existing issues or to open a new one.
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.
Copyright (C) 2025 Daniel Vartanian
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/>.
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.
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.
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This work was developed with support from the Sustentarea Research and Extension Center at the University of São Paulo (USP). |
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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). |
