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Indicator Kriging vs. Sequential Indicator Simulation in Mapping Probabilities of Precipitation Occurrence

TitleIndicator Kriging vs. Sequential Indicator Simulation in Mapping Probabilities of Precipitation Occurrence
Publication TypeConference Paper
Year of Publication2014
AuthorsPandžić J
Conference NameDailyMeteo.org/2014
Date Published06/2014
PublisherFaculty of Civil Engineering, University of Belgrade
Conference LocationBelgrade
Abstract

Estimation and simulation are two forms of geostatistical prediction used to assess spatial distribution of a continuous variable (e.g. precipitation) sampled at a finite number of locations. They can be considered as two optimization problems differing in optimization criteria: estimation means minimizing a local error variance and simulation strives to reproduce global statistics (variogram and histogram) of a variable. This paper compares indicator kriging (IK) to sequential indicator simulation (SIS) on the example of mapping probabilities of precipitation occurrence on the territory of the Republic of Serbia. Indicator means that no statements on spatial distribution of the original variable values are made, but rather on spatial distribution of probabilities that the original variable values exceed (or not) some threshold value. The data of four distinctive months (February, June, August and October) in 2009 were chosen as a basis for the prediction. One of the aims was to emphasize the smoothing effect of kriging on stochastic surface which illustrates spatial variability of a certain phenomenon. Although significant similarities between corresponding kriging and averaged simulation maps could be noticed, it is evident that in some cases simulation is much more careful when it comes to prediction of spatial variability, avoiding statements on the existence of the areas of extreme probabilities for something to happen.

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