Rainfall spatio-temporal correlation and intermittency structure from micro-γ to meso-β scale in the Netherlands

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  • 1 Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands
  • | 2 R&D Observations and Data Technology, Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
  • | 3 Department of Water Management, Delft University of Technology, Delft, the Netherlands
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Abstract

We investigate the spatio-temporal structure of rainfall at spatial scales from 7m 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 spatio-temporal 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.

Corresponding author: Remko Uijlenhoet, r.uijlenhoet@tudelft.nl

Guest researcher at: Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands.

Guest researcher at: Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands.

This article is included in the 12th International Precipitation Conference (IPC12) special collection.

Abstract

We investigate the spatio-temporal structure of rainfall at spatial scales from 7m 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 spatio-temporal 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.

Corresponding author: Remko Uijlenhoet, r.uijlenhoet@tudelft.nl

Guest researcher at: Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands.

Guest researcher at: Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands.

This article is included in the 12th International Precipitation Conference (IPC12) special collection.

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