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    Area of Science:

    • Climate science
    • Computational science
    • Data science

    Background:

    • Climate simulations are vital for addressing anthropogenic climate change.
    • Model outputs are growing in size and complexity due to higher resolution, ensembles, and improved climate system descriptions.

    Purpose of the Study:

    • To examine trends in scientific workflows for climate simulation data analysis.
    • To review advancements in visualization techniques and tools for climate data.

    Main Methods:

    • Analysis of current scientific workflows.
    • Review of emerging visualization technologies.
    • Identification of trends in climate data handling.

    Main Results:

    • Increasing data volumes and complexity necessitate advanced analysis and visualization.
    • Evolution of scientific workflows to manage large-scale climate simulation data.
    • Development of new visualization techniques and tools.

    Conclusions:

    • Adaptation of scientific workflows and tools is essential for effective climate simulation data analysis.
    • Future research should focus on efficient methods for visualizing complex climate data.
    • Technological advancements are key to understanding climate change through simulations.