Motivated by the increasing needs for reliable seasonal climate forecasts for enhanced living and protection of property, this study evaluates the predictive skill of the European Center for Medium-range Weather Forecast’s Sub-seasonal to Seasonal (ECMWF-S2S) precipitation forecasts during the peak of West Africa Monsoon in Nigeria. It investigates the ability of the ECMWF-S2S model to reproduc...

Many recent studies have been devoted to the investigation of the nonlinear dynamics of rainfall or streamflow series based on methods of dynamical systems theory. Although finding evidence for the existence of a low-dimensional deterministic component in rainfall or streamflow is of much interest, not much attention has been given to the nonlinear dependencies of the two and especially on how ...

Seasonal prediction of Asian-Australian monsoon (A-AM) precipitation is one of the most important and challenging tasks in climate prediction. In this paper, we evaluate the performance of Grid Atmospheric Model of IAP LASG (GAMIL) on retrospective prediction of the A-AM interannual variation (IAV), and determine to what extent GAMIL can capture the two major observed modes of A-AM rainfall IAV...

The artificial neural networks (ANNs) have been applied to various hydrologic problems recently. This research demonstrates static neural approach by applying Modular feedforward neural network to rainfall-runoff modeling for the upper area of Wardha River in India. The model is developed by processing online data over time using static modular neural network modeling. Methodologies and techniq...

The evolution of landslide displacement is affected by many factors. This paper studied the displacement monitoring data of Liangshuijing Landslide with Factor Analysis Method and found that the dominant factors influencing landslide displacement were in decreasing sequence: cumulative rainfall of anterior two months> rainfall of current month> the average reservoir level of current month>reser...

The topic is very relevant and important because seasonal prediction is still a very active area of research. Thus, any advance in this area will be welcome. However, I am not convinced about the interpretation and the mechanism that connects mixing in summer with rainfall in winter. As the authors mention other works have already found a connection between summertime north Atlantic SST and win...

East Asian summer monsoon (EASM) rainfall impacts the world’s most populous regions. Accurate EASM rainfall prediction necessitates robust paleoclimate reconstructions from proxy data and quantitative linkage to modern climatic conditions. Many precisely dated oxygen isotope records from Chinese stalagmites have been interpreted as directly reflecting past EASM rainfall amount variability, but ...

The topic is very relevant and important because seasonal prediction is still a very active area of research. Thus, any advance in this area will be welcome. However, I am not convinced about the interpretation and the mechanism that connects mixing in summer with rainfall in winter. As the authors mention other works have already found a connection between summertime north Atlantic SST and win...

To recognize application of Artificial Neural Networks (ANNs) in weather forecasting, especially in rainfall forecasting a comprehensive literature review from 1923 to 2012 is done and presented in this paper. And it is found that architectures of ANN such as BPN, RBFN is best established to be forecast chaotic behavior and have efficient enough to forecast monsoon rainfall as well as other wea...

Rainfall intensity plays an important role in landslide prediction especially in mountain areas. However, the rainfall intensity of a location is usually interpolated from rainfall recorded at nearby gauges without considering any possible effects of topographic slopes. In order to obtain reliable rainfall intensity for disaster mitigation, this study proposes a rainfall-vector projection metho...