precipitation is considered as one of the most important factures in water cycle. prediction of monthly precipitation is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins.in this study we studied and evaluated gene expression programming to predict the precipitation of the kakareza river (in lorestan...

Drought is one of the most serious natural disasters in China. Drought disasters occur frequently and caused huge economic loss in recently. In this paper, a drought prediction model based on weighted Markov Chain is put forward. An application is demonstrated by Anhui province of Huaihe River in China. Based on the precipitation data during 1958-2006 at monthly scale, the different time scales...

Normalized Difference Vegetation Index (NDVI) is generally recognized as a good indicator of terrestrial vegetation productivity. Understanding climatic influences, in particular precipitation and temperature, on NDVI enables prediction of productivity changes under different climatic scenarios. We examined temporal responses of remotely sensed NDVI to precipitation and temperature during a nin...

one of the most important impact of climate change is reduction of precipitation in some areas including iran. hence, climate change studies are essential in these areas. besides, according to ipcc, some meteorological stations of iran, such as tabriz (capital of east azerbaijan province) have showed a downward trend in precipitation. therefore, east azerbaijan province was selected as the stud...

The 2011 East Africa drought caused dire situations across several countries and led to a widespread and costly famine in the region. Numerous dynamic and statistical drought prediction models have been used for providing drought information and/or early warning. The concept of Ensemble Streamflow Prediction (ESP) has been successfully applied to univariate drought indicators (e.g., the Standar...

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network Sulaimani Governorate. Eight models were developed, for each as prediction. The accuracy prediction obtain excellent with correlation coefficients between predicted and measured values ranged from (90% 97.2%). are found after many trials those highest coefficient selected...

Simplifications used in regional climate models decrease the accuracy of the regional climate models. To overcome this deficiency, usually a statistical technique of MOS is used to improve the skill of gridded outputs of the Numerical Weather Prediction (NWP) models. In this paper, an experimental synoptic-climatology based method has been used to calibrate, and decrease amount of errors in GFS...