extended abstractthunderstorm rainfall is one of the most important climatic phenomena in the northwest of iran that has specific variability in spatial distribution. these rains have an important role in case study area climates. the purpose of this study is investigation of spatial distribution of thunderstorm rainfall of mountainous areas of the northwest of iran to modeling thunderstorm in ...

One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resol...

Despite the systematic nature of the monsoon rains over India, large year-to-year variations in the pattern of distribution of rainfall during the season occur. The yearly pattern of rainfall distribution during the monsoon season (May 31-October 2) for each of the years 1901-51 for a network of 105 stations over India is characterized by a set of six distribution parameters. A brief descriptio...

there is a need to analyze and map rainfall erosivity to assess soil erosion at the regional scale. the objectives of this study were to develop a regional model to estimate seasonal erosivity from seasonal rainfall data and to study temporal and spatial distribution of rainfall erosivity for the gorganrood drainage basin in the northeast of iran. six gauging stations with a high temporal resol...

[1] Accurate measurement of rainfall distribution at various spatial and temporal scales is crucial for hydrological modeling and water resources management. In the literature of satellite rainfall estimation, many efforts have been made to calibrate a statistical relationship (including threshold, linear, or nonlinear) between cloud infrared (IR) brightness temperatures and surface rain rates ...

The spatial and temporal structures of extreme rainfall trends in South Korea are investigated in the current study. The trends in the annual maximum rainfall series are detected and their spatial distribution is analyzed. The scaling exponent is employed as an index representing the temporal structure. The temporal structure of the annual maximum series is calculated and spatially analyzed. Su...

Predicting ground rainfall from satellite estimates is useful as input for many applications, especially for areas with sparse rain gauges. We propose a predictive model based on an Additive Gaussian process (AGP) which can be viewed as the sum of a GP for the influence of the satellite estimate and a GP for the spatial distribution of rainfall between gauges. The hyperparameters for the covari...