Spatiotemporal Scale Limits and Roles of Biogeochemical Cycles in Climate Predictions

Persistent Link:
http://hdl.handle.net/10150/268598
Title:
Spatiotemporal Scale Limits and Roles of Biogeochemical Cycles in Climate Predictions
Author:
Sakaguchi, Koichi
Issue Date:
2013
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
Keywords:
Carbon cycle; Climate model; Climate prediction; Atmospheric Sciences; Amazon; Atmosphere-land interaction
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Atmospheric Sciences
Degree Grantor:
University of Arizona
Advisor:
Zeng, Xubin

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleSpatiotemporal Scale Limits and Roles of Biogeochemical Cycles in Climate Predictionsen_US
dc.creatorSakaguchi, Koichien_US
dc.contributor.authorSakaguchi, Koichien_US
dc.date.issued2013-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © 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.en_US
dc.description.releaseRelease after 20-Jul-2013en_US
dc.description.abstractThere 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.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectCarbon cycleen_US
dc.subjectClimate modelen_US
dc.subjectClimate predictionen_US
dc.subjectAtmospheric Sciencesen_US
dc.subjectAmazonen_US
dc.subjectAtmosphere-land interactionen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineAtmospheric Sciencesen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorZeng, Xubinen_US
dc.contributor.committeememberCastro, Christopher L.en_US
dc.contributor.committeememberGupta, Hoshin V.en_US
dc.contributor.committeememberShuttleworth, W. Jamesen_US
dc.contributor.committeememberZeng, Xubinen_US
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