Quantification of the Small-Scale Spatial Structure of the Raindrop Size Distribution from a Network of Disdrometers
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Power laws relating the different radar observables (from conventional or polarimetric radar systems) are commonly used in the processing of radar measurements (e.g., attenuation correction) and in their conversion into rain rate values (e.g., Z-R relation ...
Precipitation is an important component of the Earth' water cycle and needs to be carefully monitored. Its large variability over a wide range of spatial and temporal scales must be taken into account. For example, hydrological models require accurate rain ...
Reliable quantitative precipitation estimation is crucial to better understand and eventually prevent water-related natural hazards (floods, landslides, avalanches, ...). Because rainfall is highly variable in time and space, precipitation monitoring and f ...
[1] In mountainous regions, snow accumulation on the ground is crucial for mountain hydrology and water resources. The present study investigates the link between the spatial variability in snowfall and in snow accumulation in the Swiss Alps. A mobile pola ...
The ability to predict the runoff response of an urban catchment to rainfall is crucial for managing drainage systems effectively and controlling discharges from urban areas. In this paper we assess the potential of commercial microwave links (MWL) to capt ...
Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gaug ...
Rainfall intermittency is analyzed and quantified at small spatial and temporal scales using 2 years of radar and disdrometer data collected in Switzerland. Analytical models are fitted and used to describe the intermittency for spatial scales between 0 an ...
This work aims at quantifying the variability of the parameters of the power laws used for rain-rate estimation from radar data, on the basis of raindrop size distribution measurements over a typical weather radar pixel. Power laws between the rain rate an ...
Insight into the spatial variability of the (rain) drop size distribution (DSD), and hence rainfall, is of primary importance for various environmental applications like cloud/precipitation microphysical processes, numerical weather modeling, and estimatio ...
A stochastic method to disaggregate rainfall fields into DSD fields is proposed. It is based on a previously presented DSD simulator that has been modified in order to take into account imposed mean values provided at the coarser scale. The integral quanti ...