Climate science is multidisciplinary by nature as it involves research in diverse disciplines such as physics, chemistry, biology, geology, geography, meteorology, oceanography, etc. Common tools, data and techniques used for climate include numerical models, big data analysis, AI, in-situ observations, remote sensing and laboratory experiments. To handle the huge, ever growing and distributed amounts of data involved, the software stack is diverse and complex. Also, given that the tools available are written in different programming languages (Python, Julia, R, Fortran, C, C++) and that scientists often possess different backgrounds and technical skills, this only adds to the challenge of multidisciplinary collaboration. Open Science is undoubtedly the most effective way to overcome these difficulties and EOSC provides the framework to put it into practice.
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