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    Spatiotemporal Scale Limits and Roles of Biogeochemical Cycles in Climate Predictions

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    Author
    Sakaguchi, Koichi
    Issue Date
    2013
    Keywords
    Carbon cycle
    Climate model
    Climate prediction
    Atmospheric Sciences
    Amazon
    Atmosphere-land interaction
    Advisor
    Zeng, Xubin
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Embargo
    Release after 20-Jul-2013
    Abstract
    There is much confidence in the global temperature change and its attribution to human activities. Global climate models have attained unprecedented complexity in representing the climate system and its response to external forcings. However, climate prediction remains a serious challenge and carries large uncertainty, particularly when the scale of interest becomes small. With the increasing interest in regional impact studies for decision-making, one of the urgent tasks is to make a systematic, quantitative evaluation of the expected skill of climate models over a range of spatiotemporal scales. The first part of this dissertation was devoted to this task, with focus on the predictive skill in the linear trend of surface air temperature. By evaluating the hindcasts for the last 120 year period in the form of deterministic and probabilistic predictions, it was found that the hindcasts can reproduce broad-scale changes in the surface air temperature, showing reliable skill at spatial scales larger than or equal to a few thousand kilometers (30° x 30°) and at temporal scales of 30 years or longer. However, their skill remains limited at smaller spatiotemporal scales, where we saw no significant improvement over climatology or a random guess. Over longer temporal scales, the feedbacks from the carbon cycle to atmospheric CO₂ concentration become important. Therefore the rest of the dissertation attempts to find key processes in the climate-carbon cycle feedback using one of the leading land-climate models, the National Center for Atmospheric Research Community Land Model. Evaluation of site-level simulations using field observations from the Amazon forest revealed that the current formulation for drought-related mortality, which lacks the ecophysiological link between short- and long-term drought stress, prevent the model from simulating realistic forest response. Global simulations showed that such dynamics of vegetation strongly influences the control of the nitrogen cycle on vegetation productivity, which then alters the sensitivity of the terrestrial biosphere to surface air temperature. This implies that if the state of the terrestrial biosphere is inconsistent with the simulated climate, either biased or prescribed, then its feedback to anthropogenic forcing could be also inconsistent.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Atmospheric Sciences
    Degree Grantor
    University of Arizona
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