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首页> 外文期刊>International Journal of Climatology: A Journal of the Royal Meteorological Society >Radar-guided interpolation of climatological precipitation data
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Radar-guided interpolation of climatological precipitation data

机译:雷达引导的气候降水数据插值

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摘要

A refined approach for interpolating daily precipitation accumulations is presented, which combines radar-based information to characterize the spatial distribution and gross accumulation of precipitation with observed daily rain-gauge data to adjust for spatially varying errors in the radar estimates. Considering the rain gauge observations to be true values at each measurement location, daily radar errors are calculated at these points. These errors are then interpolated back to the radar grid. providing a spatially varying daily adjustment that can be applied across the radar domain. In contrast to similar techniques that are employed at hourly intervals to adjust radar-rainfall estimates operationally, this refined approach is intended to provide high-spatial-resolution precipitation data for climatological purposes, such as drought and environmental monitoring. retrospective impact analyses. and (when time series of Sufficient length become available) assessment of temporal precipitation variations at high-spatial-resolution. Compared to the Multisensor Precipitation Estimators (MPEs) used operationally, the refined method yields lower cross-validated interpolation errors regardless of season or daily precipitation amount. Comparisons between cross-validated C radar estimates aggregated to monthly totals with operational (non-cross-validated) Parameter-elevation Regressions oil Independent Slopes Model (PRISM) precipitation estimates are also favourable. The new method provides a radar-based alternative to similar climatologies based oil the spatial interpolation of gauge data alone (e.g. PRISM). Copyright (c) 2008 Royal Meteorological Society
机译:提出了一种内插日降水量累积量的改进方法,该方法结合了基于雷达的信息来表征降水的空间分布和总累积量,并结合观测到的每日雨量计数据来调整雷达估算中的空间变化误差。考虑到雨量计的观测值在每个测量位置都是真实值,因此在这些点计算每日雷达误差。然后将这些误差内插回雷达网格。提供可以在整个雷达范围内应用的空间变化的每日调整。与每小时间隔使用类似技术来调整雷达降雨量估算的技术相比,这种改进的方法旨在为气候目的(例如干旱和环境监测)提供高空间分辨率的降水数据。回顾性影响分析。 (当足够长的时间序列可用时)以高空间分辨率评估时间降水变化。与可操作使用的多传感器降水估算器(MPE)相比,无论季节或日降水量如何,改进的方法产生的交叉验证插值误差均较小。交叉验证的C雷达估计值与使用(非交叉验证的)参数高程回归油独立斜坡模型(PRISM)降水估计值的月总计总量之间的比较也是有利的。新方法提供了一种基于雷达的替代方法,可以仅通过仪表数据的空间插值(例如PRISM)来替代基于类似气候的石油。版权所有(c)2008皇家气象学会

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