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@article{155097,
        author = {Giriraj Patil and Krishnakant Sonji and Kiran Kanasnale and Basva priya Kodge and Konapur Anand},
        title = {Climate Extremes: Observations, Visualization, Prediction and Impacts},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {1439-1442},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155097},
        abstract = {Climate science as a data-intensive subject has been overwhelmingly affected by the era of data science and relevant technological revolutions. The big successes of data science analytics in diverse areas over the past decade have also prompted the expectation of data science and its efficacy on the big problem—climate change. This discrepancy stems from the complex nature of climate data as well as the scientific questions climate science brings forth. This article introduces a data science audience to the challenges and opportunities to mine large climate datasets. climate change has been at the forefront of the big climate data analytics implementations and exhaustive research has been carried out covering a variety of topics. This paper aims to present an outlook of data science in climate change studies over the recent years by investigating and summarizing the current status of data science applications in climate change-related studies. It is also expected to serve as a one-stop reference directory for researchers and stakeholders with an overview of this trending subject at a glance, which can be useful in guiding future research and improvements in the exploitation of climate data.},
        keywords = {},
        month = {},
        }