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Title of Journal: Adv Atmos Sci

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Abbravation: Advances in Atmospheric Sciences

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Science Press

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10.1002/pssb.2220700156

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1861-9533

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Incorporation of parameter uncertainty into spatia

Authors: Joon Jin Song Soohyun Kwon GyuWon Lee
Publish Date: 2015/01/04
Volume: 32, Issue: 3, Pages: 413-423
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Abstract

Quantitative precipitation estimation QPE plays an important role in meteorological and hydrological applications Groundbased telemetered rain gauges are widely used to collect precipitation measurements Spatial interpolation methods are commonly employed to estimate precipitation fields covering nonobserved locations Kriging is a simple and popular geostatistical interpolation method but it has two known problems uncertainty underestimation and violation of assumptions This paper tackles these problems and seeks an optimal spatial interpolation for QPE in order to enhance spatial interpolation through appropriately assessing prediction uncertainty and fulfilling the required assumptions To this end several methods are tested transformation detrending multiple spatial correlation functions and Bayesian kriging In particular we focus on a shortterm and timespecific rather than a longterm and eventspecific analysis This paper analyzes a stratiform rain event with an embedded convection linked to the passing monsoon front on the 23 August 2012 Data from a total of 100 automatic weather stations are used and the rainfall intensities are calculated from the difference of 15 minute accumulated rainfall observed every 1 minute The onehour average Rainfall Intensity is then calculated to minimize the measurement random error Crossvalidation is carried out for evaluating the interpolation methods at regional and local levels As a result transformation is found to play an important role in improving spatial interpolation and uncertainty assessment and Bayesian methods generally outperform traditional ones in terms of the criteria

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