C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, A quick gap-filling of missing hydrometeorological data, Journal of Geophysical Research-Atmospheres, 119 (15), 9290–9300, doi:10.1002/2014JD021633, 2014.
Data-gaps are ubiquitous in hydrometeorological time series and filling these values remains still a challenge. Since datasets without missing values may be a prerequisite in performing many analyses, a quick and efficient gap-filling methodology is required. In this study the problem of filling sporadic, single-value gaps using time-adjacent observations from the same location is investigated. The applicability of a local average (i.e., based on few neighboring in time observations) is examined and its advantages over the sample average (i.e., using the whole dataset) are illustrated. The analysis reveals that a quick and very efficient (i.e., minimum mean squared estimation error) gap-filling is achieved by combining a strictly local average (i.e., using one observation before and one after the missing value) with the sample mean.
Full text is only available to the NTUA network due to copyright restrictions
See also: http://dx.doi.org/10.1002/2014JD021633
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