| 项目编号: | 1347545
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| 项目名称: | Numerical Assessment of the Practical and Intrinsic Predictability of Warm-Season Convection Initiation Using Mesoscale Predictability Experiment (MPEX) Data |
| 作者: | Allen Evans
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| 承担单位: | University of Wisconsin-Milwaukee
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| 批准年: | 2013
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| 开始日期: | 2014-06-01
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| 结束日期: | 2018-05-31
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| 资助金额: | USD456206
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Geosciences - Atmospheric and Geospace Sciences
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| 英文关键词: | convection initiation
; predictability
; moist convection
; intrinsic predictability
; research
; practical predictability
; mpex
; meso-alpha-scale
; convection-permitting real-data numerical simulation
; convection-permitting
; ability
; pre-convective
; mesoscale predictability experiment
; impact
; mpex observation
; property
; non-specialist
; location
; mpex intensive observation period
|
| 英文摘要: | The formation of deep, moist convection, or convection initiation, is highly sensitive to the atmospheric state in which it occurs. Consequently, accurately predicting the timing and location of convection initiation events poses a formidable challenge for storm-scale numerical simulations. The ultimate goal of this research is to improve the ability to predict convection initiation and, subsequently, mitigate the loss of property and life that often accompany intense convective events. To that end, this study examines the practical and intrinsic predictability of convection initiation by assessing the impact of targeted synoptic- to meso-alpha-scale observations obtained in the pre-convective environment by the Mesoscale Predictability Experiment (MPEX) upon convection-permitting real-data numerical simulations of selected convection initiation events. Investigating how predictability evolves in response to a more intensively-sampled representation of the pre-convective environment will increase fundamental understanding regarding the synoptic- to meso-alpha-scale controls upon convection initiation.
Intellectual Merit: Utilizing two ensembles of Ensemble Kalman filter-initialized, convection-permitting real-data numerical simulations, one incorporating MPEX observations and one not, this research tests the hypothesis that a more intensively-sampled representation of the pre-convective atmospheric state is sufficient to improve the practical predictability of pristine convection initiation timing and location over the range of events sampled by MPEX. Probabilistic, temporally-binned spatial verification methods will be utilized to test this hypothesis. Utilizing "perfect model" and "perfect observations" approaches applied to the study of the initial convection initiation event from three MPEX intensive observation periods, each characterized by a different prevailing synoptic-scale flow pattern, the influences of initial condition uncertainty and variability in the numerical representation of sub-grid-scale planetary boundary layer processes upon the intrinsic predictability of convection initiation are examined. In so doing, this research will expand understanding through the provision of critically-needed insight into the limits imposed by current observational constraints upon the predictability of convection initiation, an inherently multi-scale, non-linear physical process. It will further illuminate the controls upon the predictability of convection initiation exerted by the synoptic- and meso-alpha-scales and identify the presence of larger-scale attractors that influence its intrinsic predictability.
Broader Impacts: Deep, moist convection routinely poses significant impacts to both property and life. The ability to mitigate these impacts through the development of more accurate, longer-lead forecasts of deep, moist convection hinges upon our ability to better predict its initiation. Basic insight into convection initiation provided by the research will lead to advances in our ability to predict the timing, location, and occurrence of deep, moist convection. Such advances offer the promise of reducing the substantial losses of property and life due to deep, moist convection and associated phenomena incurred annually. The cross-cutting research themes of predictability, probability, and uncertainty will be communicated to non-specialists through the development of an undergraduate, non-majors Honors seminar titled "Understanding and Communicating Probability and Uncertainty in the Atmospheric Sciences." Graduate students involved with the research will be mentored as to the inherent societal significance of their research, afforded opportunities to communicate research findings to diverse, non-specialist audiences, and encouraged to acquire training in integrating the physical and social sciences. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/96838
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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| Recommended Citation: | |
Allen Evans. Numerical Assessment of the Practical and Intrinsic Predictability of Warm-Season Convection Initiation Using Mesoscale Predictability Experiment (MPEX) Data. 2013-01-01.
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