logoclim

⛅ WorldClim in NetLogo

Keywords

agent-based-modeling climate-change climate-data-visualization cmip6 complex-systems complexity-science environmental-sciences environmental-simulation future-climate-scenarios geospatial-analysis historical-climate-data netlogo reproducible-research shared-socioeconomic-pathways simulations time-series worldclim

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⛅ WorldClim in NetLogo

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Host: GitHub
Owner: sustentarea
License: gpl-3.0
Language: TeX
Default Branch: main
Homepage:
Size: 99.8 MB

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Open Issues: 6
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Topics

agent-based-modeling climate-change climate-data-visualization cmip6 complex-systems complexity-science environmental-sciences environmental-simulation future-climate-scenarios geospatial-analysis historical-climate-data netlogo reproducible-research shared-socioeconomic-pathways simulations time-series worldclim

Created over 1 year ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Funding License Code of conduct Citation Security Codemeta

README.md

LogoClim

Overview

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 science, and other fields that rely on climate data integration.

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).

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 Interface

How It Works

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.

Color Scale

The model uses a color scale ranging from black (representing the lowest value) to white (representing the highest value). Users can adjust the thresholds for these colors using the black-value and white-value sliders. Alternatively, users can set the black or white color to automatically represent the minimum or maximum value of the current data by toggling the black-min and white-max switches. By default, the black threshold is set to 0, and the white threshold corresponds to the maximum value of the current data.

Data Series

In addition to latitude and longitude data points, LogoClim supports simulation with all three climate data series provided by WorldClim 2.1: long-term historical climate averages, historical monthly weather, and future climate projections. 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.

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. 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 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.

How to Use It

Setup

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 (gis), Pathdir (pathdir), String (string), and Time (time) NetLogo extensions. These are automatically installed when the model is run for the first time.

Downloading the Model

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.

Downloading 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.

Running the Model

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.

Integrating with Other Models

LogoClim can be integrated with other models using NetLogo's LevelSpace (ls) extension. This extension enables parallel execution and data exchange between models. For an example of integrating LogoClim with another model, see the FoodClim project.

How to Cite

[!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:

latex @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} }

How to Contribute

Contributions are welcome! Whether you want to report bugs, suggest features, or improve the code or documentation, your input is highly valued.

When contributing code, please follow the tidy design principles and the tidyverse style guide whenever possible.

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.

License

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 Stephen E. Fick, Robert J. Hijmans, and the entire WorldClim team for their outstanding work in creating and maintaining the WorldClim datasets, which form the foundation of this project.

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 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).

Owner

Name: Sustentarea
Login: sustentarea
Kind: organization
Email: sustentarea@usp.br
Location: Brazil

Website: https://www.fsp.usp.br/sustentarea
Repositories: 1
Profile: https://github.com/sustentarea

Research and Extension Center at the University of São Paulo (USP)

Citation (CITATION.cff)

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title: "LogoClim: WorldClim in NetLogo"
message: >-
  If you use this software, please cite it using the metadata from this file.
type: software
authors:
  - given-names: Daniel
    family-names: Vartanian
    email: danvartan@gmail.com
    affiliation: University of São Paulo
    orcid: 'https://orcid.org/0000-0001-7782-759X'
  - given-names: Leandro
    family-names: Garcia
    email: l.garcia@qub.ac.uk
    affiliation: Queen's University Belfast
    orcid: 'https://orcid.org/0000-0001-5947-2617'
  - given-names: Aline Martins
    family-names: Carvalho
    email: alinenutri@usp.br
    affiliation: University of São Paulo
    orcid: 'https://orcid.org/0000-0002-4900-5609'
abstract: >-
  {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 science, and other fields that rely on climate data
  integration.

  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). All climate
  inputs come from WorldClim 2.1, a widely used source of high-resolution,
  interpolated climate datasets based on weather station observations worldwide.
keywords:
  - Agent-Based Modeling
  - Climate Change
  - Climate Data Visualization
  - Climate Model Integration
  - Climate Projections
  - Climate Simulation
  - Cmip6
  - Complex Systems
  - Complexity Science
  - Data Interoperability
  - Environmental Sciences
  - Environmental Simulation
  - Future Climate Scenarios
  - Geospatial Analysis
  - Historical Climate Data
  - LevelSpace
  - Models
  - NetLogo
  - Parallel Execution
  - Raster Data
  - Reproducible Research
  - Shared Socioeconomic Pathways
  - Simulations
  - Spatial Analysis
  - Spatial Resolution
  - SSPs
  - Time Series
  - WorldClim
identifiers:
  - type: doi
    value: 10.17605/OSF.IO/EAPZU
    description: OSF Research Compendium
repository-code: 'https://github.com/sustentarea/logoclim'
repository: 'https://doi.org/10.17605/OSF.IO/EAPZU'
repository-artifact: 'https://doi.org/10.17605/OSF.IO/RE95Z'
license: GPLv3

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