Rainfall Spatiotemporal Correlation and Intermittency Structure from Micro-gamma to Meso-beta Scale in the Netherlands

Journal Article (2021)
Author(s)

Thomas C. Leth (Wageningen University & Research)

Hidde Leijnse (Royal Netherlands Meteorological Institute (KNMI), Wageningen University & Research)

A. Overeem (Royal Netherlands Meteorological Institute (KNMI), Wageningen University & Research)

R. Uijlenhoet (Wageningen University & Research, TU Delft - Water Resources)

Research Group
Water Resources
Copyright
© 2021 Thomas C. van Leth, Hidde Leijnse, A. Overeem, R. Uijlenhoet
DOI related publication
https://doi.org/10.1175/JHM-D-20-0311.1
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Thomas C. van Leth, Hidde Leijnse, A. Overeem, R. Uijlenhoet
Research Group
Water Resources
Issue number
8
Volume number
22
Pages (from-to)
2227-2240
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Abstract

e investigate the spatiotemporal structure of rainfall at spatial scales from 7 m to over 200 km in the Netherlands. We used data from two networks of laser disdrometers with complementary interstation distances in two Dutch cities (comprising five and six disdrometers, respectively) and a Dutch nationwide network of 31 automatic rain gauges. The smallest aggregation interval for which raindrop size distributions were collected by the disdrometers was 30 s, while the automatic rain gauges provided 10-min rainfall sums. This study aims to supplement other micro-γ investigations (usually performed in the context of spatial rainfall variability within a weather radar pixel) with new data, while characterizing the correlation structure across an extended range of scales. To quantify the spatiotemporal variability, we employ a two-parameter exponential model fitted to the spatial correlograms and characterize the parameters of the model as a function of the temporal aggregation interval. This widely used method allows for a meaningful comparison with seven other studies across contrasting climatic settings all around the world. We also separately analyzed the intermittency of the rainfall observations. We show that a single parameterization, consisting of a two-parameter exponential spatial model as a function of interstation distance combined with a power-law model for decorrelation distance as a function of aggregation interval, can coherently describe rainfall variability (both spatial correlation and intermittency) across a wide range of scales. Limiting the range of scales to those typically found in micro-γ variability studies (including four of the seven studies to which we compare our results) skews the parameterization and reduces its applicability to larger scales.