In this paper the error in estimating the conditional distribution of rainfall given a particular pre-existing or coexisting southern oscillation condition due to the limited length of the historical record is investigated and some statistical procedures for reducing this error are proposed and investigated. Introduction Rainfall in Australia appears to be influenced by the El-Nino/Southern Osc...

Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to ide...

This chapter also focusesaddresses on precipitation intensity measurements (in particular rate of rainfall or rainfall intensity) due to their rapidly increased need for the interpretation of rainfall patterns, rainfall event modeling and forecasts, everyday meteorological and engineering applications, the investigation of evolving events at the local to regional scale with potential tremendous...

[1] Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) is a satellite infrared-based algorithm that produces global estimates of rainfall at resolutions of 0.25 0.25 and a half-hour. In this study the model parameters of PERSIANN are routinely adjusted using coincident rainfall derived from the Tropical Rainfall Measurement Mission Microwave Im...

1. The importance of rainfall is recognized in arid habitats, but has rarely been explored in ecosystems not viewed as rainfall limited. In addition, most attempts to study how rainfall affects organismal survival have focused on long-term rainfall metrics (e.g. monthly or seasonal patterns) instead of short-term measures. For organisms that are short lived or are sensitive to desiccation, shor...

This paper presents a fuzzy inference model for predicting rainfall using scan data from the USDA Soil Climate Analysis Network Station at Alabama Agricultural and Mechanical University (AAMU) campus for the year 2004. The model further reflects how an expert would perceive weather conditions and apply this knowledge before inferring a rainfall. Fuzzy variables were selected based on judging pa...