Commercial microwave links (CMLs) in telecommunication networks can provide relevant information for remote sensing of precipitation and other environmental variables, such as path-averaged drop size distribution, evaporation, or humidity. The CoMMon field ...
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 ...
Like precipitation, the raindrop size distribution (DSD) is strongly variable in space and time. Understanding this variability is important for quantifying and minimizing some of the uncertainties in radar measurements and their interpretation in terms of ...
A method for the stochastic simulation of (rain)drop size distributions (DSDs) in space and time using geostatistics is presented. At each pixel, the raindrop size distribution is described by a Gamma distribution with two or three stochastic parameters. T ...
The spatial structure of the raindrop size distribution (DSD) conveys crucial information for reliable quantitative estimation of rainfall using remote sensing techniques. To investigate this question, a network of 16 optical disdrometers has been deployed ...
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 ...
The variability of the (rain)drop size distribution (DSD) in time and space is an intrinsic property of rainfall, of primary importance for various environmental fields such as remote sensing of precipitation for example. DSD observations are usually colle ...
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 ...
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 ...
