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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Large-scale spatial variability of rainfall through hidden semi-Markov models of breakpoint data
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Large-scale spatial variability of rainfall through hidden semi-Markov models of breakpoint data

机译：通过隐藏的断点数据的半马尔可夫模型对降雨进行大规模的空间变异

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The breakpoint format for rainfall data records the rain rate and the times when the rain rate changes. A Markov model was chosen so that the states could be aligned with the different physical processes that occur in the atmosphere and are associated with rainfall. However, the data consist only of rain rates and durations with no labels indicating the prevailing process for each datum, thus the states in the model are "hidden". A suitable structure for the model was chosen and fitted to breakpoint data sets from widely spaced localities within New Zealand. At all locations, wet and dry states could be put into two groups such that one (i.e., rain) was characterized by longer periods of lighter precipitation with few dry breaks, while the other (i.e., showers) had shorter but generally heavier periods of precipitation with often long dry breaks in between. The large-scale spatial variability of the rainfall climatology was assessed through model statistics with the frequency of events and the amounts-from and durations-of rain, as distinct from showers, being found to be the most variable. Also, usually only one episode of rain and one of showers constituted a precipitation event.
机译：降雨数据的断点格式记录降雨率和降雨率变化的时间。选择了马尔可夫模型，以便使状态与大气中发生的与降雨相关的不同物理过程保持一致。但是，数据仅包含降雨率和持续时间，没有标签指示每个基准面的流行过程，因此模型中的状态为“隐藏”。选择了适合该模型的结构，并将其安装到新西兰广泛分布的地区的断点数据集。在所有位置，都可以将湿态和干态分为两组，这样一组（即下雨）的特征是降水量较长，降水少，干裂少，而另一组（即阵雨）的降水期较短但通常较重降水之间经常有较长的干间断。降雨气候学的大规模空间变异性是通过模型统计数据进行评估的，事件发生的频率和降雨的数量（与降雨的持续时间不同，与降雨不同）是变化最大的。而且，通常只有一场降雨和一场阵雨构成降雨事件。

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