A preliminary investigation of radar rainfall estimation in the Ardennes region and a first hydrological application for the Ourthe catchment
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This paper presents a comparative study on the mapping of temperature and precipitation fields in complex Alpine terrain. Its relevance hinges on the major impact that inadequate interpolations of meteorological forcings bear on the accuracy of hydrologic ...
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 ...
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 ...
As rainfall constitutes the main source of water for the terrestrial hydrological processes, accurate and reliable measurement and prediction of its spatial and temporal distribution over a wide range of scales is an important goal for hydrology. We invest ...
A case study of an intense convective event occurring in the Swiss Alps (Davos) is presented. Polarimetric X-band observations of this event showed an unusual strong signature in terms of differential reflectivity Zdr, differential phase shift on backscatt ...
Water resources management and hydrological risks are based, to a large extent, on our competence to generate relevant hydrological scenarios under present and future climatic situations. In alpine areas, characterized by highly complex topography, the ava ...
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 ...
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 ...
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 rain rate fields into drop size distribution (DSD) fields is proposed. It is based on a previously presented DSD simulator that has been modified to take into account prescribed block-averaged rain rate values at a coars ...