The global space-time cascade structure of precipitation: Satellites, gridded gauges and reanalyses
The global space-time cascade structure of precipitation: Satellites, gridded gauges and reanalyses
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DOI：
10.1016/j.advwatres.2012.03.024
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发表时间：
2012-09
影响因子：
4.7
通讯作者：
S. Lovejoy;J. Pinel;D. Schertzer
中科院分区：
文献类型：
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作者：
S. Lovejoy;J. Pinel;D. Schertzer
梯级作为降水模型已有近 25 年的历史，但许多基本问题仍未得到解答，而且大多数应用都是小规模或区域规模。在本文中，我们重新审视其中一些问题，并对四个全球尺度数据集进行相互比较，每个数据集都具有特殊特征：每小时（和约 200 公里）分辨率的美国大陆气候预测中心 (CPC) 网格降水、每小时 3 小时的全球 ECMWF 再分析层状降水产品（1.5° 分辨率）、每小时 6 小时的 2° 二十世纪再分析（1871-2008）以及对 5300 个轨道的分析热带降雨测量任务 (TRMM) 卫星降雨量超过 ±40° 纬度 (1 年)。数据按纬向、经向和时间进行分析。每个都呈现级联结构；空间可达行星尺度，时间可达 5-10 天。对于每一个，我们估计了矩标度指数 (K(q)) 及其接近平均值 (C1) 的特征和有效的外级联尺度。不同方向的级联结构的比较表明，尽管异常仍然存在，但它们在（水平）时空上相对各向同性。对于任何给定方向，不同产品的比较表明非常相似但不相同的缩放特性。为了在超过唯一分辨率的情况下进行正确的相互校准，不同的产品必须具有相同的指数和外标度，因此，虽然相似性令人鼓舞，但其余的异常表明需要改进面积降雨量估算技术。我们的主要结论是，测量技术引入的降雨率偏差大于完美对数线性（缩放）的偏差，因此需要多重分形模型来改进时空降水测量。我们的分析澄清了各种基本问题。例如，CPC 数据显示，在“天气”尺度上，时间小于约 2 天； H=0.17±0.11，因此降雨显然不是级联过程的直接产物（H=0）。类似地，对于低频天气状况（尺度>≈2周），我们发现H≈−0.42，因此波动往往会随着尺度的变化而减小而不是增加，并显示出长期的统计依赖性。最后，我们发现指数 qD≈3 的幂律概率尾部，因此奇点的阶数显然不受限制，排除了包括微正则模型和对数泊松模型在内的几种模型类型。
Cascades have been used as models of precipitation for nearly 25years yet many basic questions remain unanswered and most applications have been to small or to regional scales. In this paper we revisit some of these issues and present an inter comparison of four global scale data sets each with exceptional characteristics: the hourly (and ≈200km) resolution Climate Prediction Center (CPC) gridded precipitation over the continental US, the three hourly global ECMWF reanalysis stratiform precipitation product at 1.5° resolution, the six hourly Twentieth Century reanalysis at 2° (1871–2008) and an analysis of 5300 orbits (1year) of the Tropical Rainfall Measuring Mission (TRMM) satellite rainfall over ±40° latitude. The data were analysed zonally, meridionally and in time. Each showed cascade structures; in space up to planetary scales and in time up to 5–10days. For each we estimated the moment scaling exponent (K(q)) as well as its characterisation near the mean (C1) and the effective outer cascade scales. The comparison of the cascade structures in different directions indicate that although anomalies remain, they are relatively isotropic in (horizontal) space–time. For any given direction, the comparison of the different products indicates very similar but not identical scaling properties. In order to be properly inter calibrated at more than a unique resolution, the different products must have the same exponents and outer scales so that - while the similarities are encouraging – the remaining anomalies point to needed improvements in techniques for estimating areal rainfall. Our main conclusion is that the rain rate biases introduced by the measurement techniques are larger than the deviations from perfect log–log linearity (scaling) so that multifractal models will be needed for improving space–time precipitation measurements. Our analyses clarify various fundamental issues. For example, the CPC data show that at “weather” scales smaller than ≈2days in time; H=0.17±0.11 so that rain is apparently not the direct product of a cascade process (which would have H=0). Similarly, for the low frequency weather regime (scales >≈2weeks) we find H≈−0.42 so that fluctuations tend to decrease rather than increase with scale and display long range statistical dependencies. Finally, we find power law probability tails with exponent qD≈3 so that the orders of singularity are apparently not bounded, ruling out several model types including microcanonical and log-Poisson models.