Big data in Earth science: Emerging practice and promise
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Big data in Earth science: Emerging practice and promise

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  • Journal Title:
    Science
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  • Description:
    Improvements in the number and resolution of Earth- and satellite-based sensors coupled with finer-resolution models have resulted in an explosion in the volume of Earth science data. This data-rich environment is changing the practice of Earth science, extending it beyond discovery and applied science to new realms. This Review highlights recent big data applications in three subdisciplines—hydrology, oceanography, and atmospheric science. We illustrate how big data relate to contemporary challenges in science: replicability and reproducibility and the transition from raw data to information products. Digital twins (DTs) enable us to learn from the past, understand the current state, and improve the accuracy of future predictions. Big data are traditionally defined by five V’s—volume, velocity, veracity, variety, and value. These describe data that are large, arrive quickly, may be of mixed reliability or accuracy, are in a number of formats, and have high value. Understanding Earth as an integrated system leads to the need to look at all sorts of phenomena, hence the need for big data.
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  • Source:
    Vance et al., Science 383, 1193 (2024)
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    Accepted Manuscript
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    The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
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    Submitted
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