Dani Jones on Muck Rack

Dani Jones

Kalamazoo
As seen in: The New York Times, Nature, Wiley Online Library, KCNC-TV (Denver, CO), Bulletin of the American Meteorological Society (BAMS), Kirkus Reviews, Sooper Articles, Roar News
Saved by Grace • Mom to Braxton & Beckett • Published Author • Small Business Owner • Blogger • Dog Mom to Charley & Valor🐾• 💍Wife to Jason ✌🏽🌎🤘🏽
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Articles

MY SISTER, THE FREAK

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By Dani Jones
| Kirkus Reviews Verified
A fast-paced, heartfelt tale of sisterhood, secrets, and saving the day. Sisters must overcome their differences to fight intergalactic evil. Middle schooler Mary Seaver is prone to energetic outbursts and offbeat behavior, and she’s filled with imaginative ideas. Her teenage sister, Allison, who goes by Al, is her polar opposite and wants nothing more than a typical high school experience filled with sports and school dances.
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The biogeochemical transport by the Gulf Stream - Communications Earth & Environment

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By Richard Williams, Peter Brown, Yohei Takano, Gael Forget, Dani Jones, Anna Katavouta, Elaine L. McDonagh, Vassil Roussenov
| Nature Verified
Abstract The Gulf Stream is important for the climate system through its transport and air-sea exchange of heat. What is less well accepted is the role of the Gulf Stream in the carbon cycle. Here we examine how the Gulf Stream provides a “biogeochemical stream”, a sub-surface horizontal flux carrying waters with high concentrations of nutrients and low concentrations of anthropogenic carbon.
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Mapping Out How Machine Learning and Artificial Intelligence Will Change Great Lakes Observations, Modeling, and Forecasting in the Coming Decade

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By Dani Jones, Scott Steinschneider, Paul J. Roebber, Sage Osborne
| Bulletin of the American Meteorological Society (BAMS)
Keywords: Inland seas/lakes; Watersheds; Forecasting; Water resources; Artificial intelligence; Machine learning AI Horizons What: Twenty-two scientists gathered to explore how machine learning and artificial intelligence could transform Great Lakes observations, modeling, and forecasting. Participants discussed enhancing predictive models, improving observational network design, and identifying key challenges and opportunities.
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