Weather Types Affect Rain Microstructure: Implications for Estimating Rain Rate

Wael Ghada,Andreas Hamann,Joan Bech,Nicole Estrella,Annette Menzel

doi:10.3390/rs12213572

Abstract

Quantitative precipitation estimation (QPE) through remote sensing has to take rain microstructure into consideration, because it influences the relationship between radar reflectivity Z and rain intensity R. For this reason, separate equations are used to estimate rain intensity of convective and stratiform rain types. Here, we investigate whether incorporating synoptic scale meteorology could yield further QPE improvements. Depending on large-scale weather types, variability in cloud condensation nuclei and the humidity content may lead to variation in rain microstructure. In a case study for Bavaria, we measured rain microstructure at ten locations with laser-based disdrometers, covering a combined 18,600 h of rain in a period of 36 months. Rain was classified on a temporal scale of one minute into convective and stratiform based on a machine learning model. Large-scale wind direction classes were on a daily scale to represent the synoptic weather types. Significant variations in rain microstructure parameters were evident not only for rain types, but also for wind direction classes. The main contrast was observed between westerly and easterly circulations, with the latter characterized by smaller average size of drops and a higher average concentration. This led to substantial variation in the parameters of the radar rain intensity retrieval equation Z–R. The effect of wind direction on Z–R parameters was more pronounced for stratiform than convective rain types. We conclude that building separate Z–R retrieval equations for regional wind direction classes should improve radar-based QPE, especially for stratiform rain events.

Highlights

Understanding rain microstructure can provide us with an insight into the prevailing rain formation processes leading to it
We ask: (1) What is the effect of weather types on rain microstructure, considering both types of rain? and (2) Is there consistent variation in the Z–R parameters between weather types that would suggest opportunities to improve Quantitative precipitation estimation (QPE) with radar-based methods? To address these questions, we investigate disdrometer records under different large-scale wind direction patterns at a daily scale, and rain type classifications at one-minute intervals over a period of three years
This research demonstrated that rain microstructure varies significantly between weather types in both stratiform and convective rain

Summary

Introduction

Understanding rain microstructure can provide us with an insight into the prevailing rain formation processes leading to it. Rain microstructure varies on different spatial scales ranging from few meters [7], to few hundreds of meters [8], to regional [9,10] and global extents [11,12] This variation occurs with seasons [13], rain types [14], and large-scale weather types [15,16,17]. A clear example of the different rain formation processes leading to variations in rain drop size distribution is the discrepancy between convective and stratiform rain. This has been quantified in a number of studies [5,14,18,19]. Recent methods employed machine learning and reached higher performance levels when using four rain drop size distribution parameters [27,28]

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Discussion

Conclusion