Acid deposition is one of the most important environmental issues in East Asia including Japan. The long range transport of acidic species from Asian continent to Japan islands cause large amount of acid deposition especially in winter. These phenomena are strongly affected by the precipitation on the sea, however, it is not easy to get enough information on it. This study aims to develop a sim...

Accurate rainfall forecasting is critical because it has a great impact on people’s social and economic activities. Recent trends on various literatures shows that Deep Learning (Neural Network) is a promising methodology to tackle many challenging tasks. In this study, we introduce a brand-new data-driven precipitation prediction model called DeepRain. This model predicts the amount of rainfal...

drought as a climatic phenomenon affected many different environmental issues and generally is associated with the decreasing in average precipitation. evaluation and monitoring of the drought is a fundamental step in proper programming of water resources management. regarding the recent conditions water scarcity in the urmia lake basin, assessment of the drought index in this region is inevita...

formation of asphaltene deposition during oil production, processing and synthesis is known as a fundamental problem of petroleum reservoir worldwide. asphaltene is a petroleum fraction that can lead to increasing the operating costs in these industries. variations in operational pressure, temperature and fluid composition are generally the significant cause of asphaltene precipitation. in this...

Rainfall is considered a highly valuable climatologic resource, particularly in arid regions. As one of the primaryinputs that drive watershed dynamics, rainfall has been shown to be crucial for accurate distributed hydrologicmodeling. Precipitation is known only at certain locations; interpolation procedures are needed to predict this variablein other regions. In this study, the ordinary cokri...

Based on a widely used satellite precipitation product (TRMM Multi-satellite Precipitation Analysis 3B43), we analyzed the spatiotemporal variability of precipitation over the Pacific Ocean for 1998–2014 at seasonal and interannual timescales, separately, using the conventional empirical orthogonal function (EOF) and investigated the seasonal patterns associated with El Niño–Southern Oscillatio...

Precipitation variability and magnitude are expected to change in many parts of the world over the 21st century. We examined the potential effects of intra-annual rainfall patterns on soil nitrogen (N) transport and transformation in the unsaturated soil zone using a deterministic dynamic modeling approach. The model based on TOUGHREACT [corrected], which has been tested and applied in several ...

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...

This paper introduces two parsimonious models for predicting runoff for ungauged basins from the observed river flow data in gauged basins and precipitation data from rain gauging stations in the same area. The models assume the runoff is related to the precipitation subject to variance of drainage basins. The runoff can be modeled as a function of precipitation and parameters determined by bas...

A probabilistic precipitation forecasting model using generalized additive models (GAMs) and Bayesian model averaging (BMA) was proposed in this paper. GAMs were used to fit the spatial-temporal precipitation models to individual ensemble member forecasts. The distributions of the precipitation occurrence and the cumulative precipitation amount were represented simultaneously by a single Tweedi...