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Maximization of Precipitation for the 1997 Storm Event Over American River Watershed, California Using a Regional Atmospheric Model

机译:利用区域大气模型,加利福尼亚州美国河流域的1997年风暴事件降水最大化

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A model-based 72-hour maximum precipitation (MP) was estimated for American River Watershed (ARW) in California by means of a physically-based numerical atmospheric model (Ohara et al. 2011). First, comparing the simulated basin-averaged precipitation against the PRISM data, a regional atmospheric model, MM5, was calibrated. Second, using the calibrated regional atmospheric model, the model-simulated precipitation field in ARW was successfully validated at nine individual rain gauge stations in the watershed. Then, the 1997 storm event, one of the severest storm events over ARW, was maximized by the modification of the model boundary and initial conditions. The initial and boundary conditions in the outer domain of the atmospheric model were modified by three methods: 1) the atmospheric moisture, 2) the storm event duration with maintaining equilibrium atmospheric condition, and 3) spatially shifting the atmospheric conditions. It was found that these modifications of the model boundary conditions significantly increased the precipitation over ARW. These results clearly indicate the importance of wind and moisture conditions at the boundary of the atmospheric modeling domain. The artificially maximized storm yielded 549 mm of 72-hour precipitation depth by the combination of the humidity and storm duration maximization, and 541 mm depth by shifting the atmospheric conditions to the ones toward south by 5.0 degrees. Consequently, the 72-hour maximum precipitation of the 1997 event over ARW can be maximized to as high as 550 mm. Although this study presents only a demonstrative maximization work, it shows that the presented modeling approach can be a potential alternative to the standard Probable Maximum Precipitation (PMP) estimation without depending upon the linear relationships required in the standard PMP method.
机译:基于模型的72小时的最大降水量(MP)通过基于物理的数值大气模型的装置(Ohara等人,2011)估计美国流域(ARW)在加利福尼亚。首先,对PRISM数据进行比较的模拟流域平均降水量,区域性大气模型,MM5,进行校准。其次,使用校准区域大气模型,在ARW模型模拟的降水场成功地在流域九个单独雨量计站验证。然后,1997年风暴事件,经ARW最严重的风暴事件中的一个,是由模型边界和初始条件的修改最大化。 1)大气中的水分,2)风暴事件持续时间与维持平衡的大气条件,以及3)在空间上移位所述大气条件:在大气模型的外结构域的初始和边界条件,通过三种方法改性。结果发现,模型的边界条件,这些修改显著增加了ARW沉淀。这些结果清楚地表明风和湿度条件下的大气建模领域的边界的重要性。人工最大化风暴产生由湿度和风暴持续时间最大化的组合549毫米72小时的沉淀的深度,并且通过5.0度移位大气条件朝向南方的那些541毫米深度。因此,1997年事件超过ARW的72小时的最大降水量可最大化至高达550毫米。虽然这项研究礼物只是一个示范最大化的工作,这表明所提出的建模方法可以是标准的可能最大降水(PMP)估算的潜在替代品,而不依赖于标准PMP方法所需的线性关系。

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