Radar-based rainfall information has been widely used in hydrological and meteorological
applications, as it provides data with a high spatial and temporal resolution that improve …

Rainfall is one of the most basic meteorological and hydrological elements. Quantitative
rainfall estimation has always been a common concern in many fields of research and …

Precipitation is one of the essential variables in rainfall-runoff modeling. For hydrological
purposes, the most commonly used data sources of precipitation are rain gauges and …

This paper aims to stimulate discussion based on the experiences derived from the QUICS
project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses …

Satellite rainfall estimates (SREs) are prone to bias as they are indirect derivatives of the
visible, infrared, and/or microwave cloud properties, and hence SREs need correction. We …

The assessment of precipitation over land is extremely important for a number of scientific
purposes related to the mitigation of natural hazards, climate modelling and prediction …

In this paper we present a non-stationary stochastic generator for radar rainfall fields based
on the short-space Fourier transform (SSFT). The statistical properties of rainfall fields often …

In this study we propose and demonstrate a data-driven approach in an “information-
theoretic” framework to quantitatively estimate precipitation. In this context, predictive …

The effective precipitation (P e) and crop water requirements (ET c) can reflect the
agricultural water supply and demand situations under natural precipitation conditions, and …

A Reduced-Space Ensemble Kalman Filter Approach for Flow-Dependent Integration of Radar
Extrapolation Nowcasts and NWP Precipitation Ensembles in: Monthly Weather Review …