Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Land Carbon Cycle Modeling: Matrix Approach, Data Assimilation, Ecological Forecasting, and Machine Learning

Land Carbon Cycle Modeling: Matrix Approach, Data Assimilation, Ecological Forecasting, and Machine Learning

Smith, Benjamin
Luo, Yiqi

Hardcover

Environmental Studies

Currently unavailable to order

ISBN10: 1032698497
ISBN13: 9781032698496
Publisher: CRC Press
Published: Jun 14 2024
Pages: 296
Language: English

Carbon moves through the atmosphere, through the oceans, onto land, and into ecosystems. This cycling has a large effect on climate - changing geographic patterns of rainfall and the frequency of extreme weather - and is altered as the use of fossil fuels adds carbon to the cycle. The dynamics of this global carbon cycling are largely predicted over broad spatial scales and long periods of time by Earth system models. This book addresses the crucial question of how to assess, evaluate, and estimate the potential impact of the additional carbon to the land carbon cycle. The contributors describe a set of new approaches to land carbon cycle modeling for better exploring ecological questions regarding changes in carbon cycling; employing data assimilation techniques for model improvement; doing real- or near-time ecological forecasting for decision support; and combining newly available machine learning techniques with process-based models to improve prediction of the land carbon cycle under climate change. This new edition includes seven new chapters: machine learning and its applications to carbon cycle research (five chapters); principles underlying carbon dioxide removal from the atmosphere, contemporary active research and management issues (one chapter); and community infrastructure for ecological forecasting (one chapter).

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