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 …

Estimating accurate spatial distribution of precipitation is important for understanding the
hydrologic cycle and various hydro‐environmental applications. Satellite‐based …

This study compares two nonparametric rainfall data merging methods—the mean bias
correction and double-kernel smoothing—with two geostatistical methods—kriging with …

Deriving high quality precipitation estimates at high spatial resolution is of prime importance
for many hydrological, meteorological, and environmental investigations. Rain gauge …

Accurate rainfall data are of prime importance for many environmental applications. To
provide spatially distributed rainfall data, point measurements are interpolated. However, in …

Deriving high quality daily rainfall estimates are required not only for successful hydrological
modelling but also for its application in ungauged basins. At present, there are two …

Accurate gridded precipitation products with both finer tempo-spatial resolutions are critical
for various scientific communities (eg, hydrology, meteorology, climatology, and agriculture) …

Precipitation estimation at a global scale is essential for global water cycle simulation and
water resources management. The precipitation estimation from gauge‐based, satellite …

Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or
evaluation of weather predictions, for example. This paper investigates the application of …

Geo-spatial interpolation methods are often necessary in instances where the precipitation
estimates available from multisensor source data on a specific spatial grid need to be …