To recognize application of Artificial Neural Networks (ANNs) in weather forecasting,
especially in rainfall forecasting a comprehensive literature review from 1923 to 2012 is …

The objective of the study is the application of the artificial neural networks, to the spatial
interpolation of rainfall variables. This methodology is applied on mean rainfall variable of …

METODY ANALIZ PRZESTRZENNYCH W BADANIU ZMIENNOŚCI OPADÓW W EUROPIE THE
METHODS OF SPATIAL ANALYSIS FOR PRECIPITATION FIELDS IN Page 1 71 Metody analiz …

In this research work the astrological parameters has been identified, those are physically
linked with long range area weighted rainfall (LR-AWR) of 132 rain-gauge stations over …

Due to the relative scarcity of weather stations, the climate conditions of large areas are not
adequately represented by a weather station. This is especially true for regions with complex …

Forecasting of long range meteorological data time series especially monsoon rainfall
becomes a challenging operational task for world's scientists and meteorologists. To …

An estimated 39 million m3 of timber was damaged across the Southeast Forest District of
Mississippi due to Hurricane Katrina. Aggregated forest plot-level biometrics was coupled …

Gandin kriging is a new downscaling method which is based on optimum linear interpolation
and uses a physical regression model to calculate the deterministic mean field part. Here …

To be familiar with appropriateness of Neural Network in climate prediction and spatial
interpolation, e comprehensive literature review of past 50 years is done and offered in this …

Weather forecasting (especially rainfall) is one of the most important and challenging
operational tasks carried out by meteorological services all over the world. It is furthermore a …