课题基金 / 基金详情

Presidential Young Investigators Award - Soil Moisture Dynamics and Droughts

Presidential Young Investigators Award - Soil Moisture Dynamics and Droughts
总统青年研究员奖 - 土壤水分动态和干旱
批准号:
9158150
负责人:
Dara Entekhabi
金额:
$0.8万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1991
资助国家:
美国
项目状态:
已结题
起止时间:
1991-07-15 至 1991-09-01

项目摘要

项目成果

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中文摘要
翻译
该项目由总统青年研究人员奖计划支持。今后五年进行的研究将集中于发展和分析干旱的发生和持续时间,使用随机微分方程来模拟大陆水和热量平衡。将为若干气候实例编制干旱持续时间的统计分布。将导出该模式的持续和长期依赖特征,并与气候强迫因子相关。通过大陆型气候的水文气候学模型,将说明水文、陆地、地表-大气相互作用在干旱动力学中的重要性。这项研究的好处将是更好地理解偶尔引发干旱的大尺度大气流动特征的随机扰动和逐年随机变化持续存在并影响人类社会和自然环境的条件。有了更好的了解,就可以减轻干旱的后果。
英文摘要
This project is supported through the Presidential Young Investigators Award program. The studies conducted during the next five years will concentrate on the development and analysis of the occurrence and duration of droughts using stochastic differential equations to model continental water and heat balance. The statistical distribution of drought durations for several climatic case examples will be developed. The persistent and long-range dependence characteristics for this model will be derived and related to climatic forcing factors. Through the model for hydroclimatology of continental- type climates, the importance of hydrologic land surface-atmosphere interactions in the dynamics of drought will be illustrated. The benefits of this research will be to better understand the stochastic perturbations and year-to-year random variations in large scale atmospheric flow features which occasionally trigger drought conditions that persist and impact human society and the natural environment. With a better understanding mitigation of drought consequences could be achieved.
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Collaborative Research: NSF-BSF--Tropospheric Response to Zonal Asymmetry of the Stratospheric Polar Vortex and Its Aapplication to Subseasonal to Seasonal (S2S) Prediction
Collaborative Research: The combined influence of sea ice and snow cover on Northern Hemisphere atmospheric climate variability
Collaborative Research: Linkages in Winter-Time Climate Variability and the Basis for Climate Predictability in the North Atlantic Sector
Collaborative Research: WCR: Incorporation of Model Bias and Uncertainty in Land Surface Hydrologic Flux Prediction Using a Data Assimilation Network
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