runoff simulation is a vital issue in water resource planning and management. various models with different levels of accuracy and precision are developed for this purpose considering various prediction time scales. in this paper, two models of ihacres (identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data) and ann (artificial neural network) mode...

large-scale climatic signals including ocean-atmosphere interactions, are the main factors influencing the earth’s climatic oscillations and are the most important indices in predicting of climate variables. in this research, precipitation in the next month was predicted by applying artificial neural network (ann), neuro-fuzzy network (nfn), and multiple linear regression (mlr) in semnan synopt...

many of the meteorological variables such as precipitation, strongly depend on the large scale atmospheric and ocean surface circulations.in the current study, the effect of climatic signals on the average monthly rainfall of the adjacent stations of sheshdeh and gharebolagh area was investigated during the statistical period twenty five years from 1985 to 2009. the regression and neural networ...

Abstract. We investigate the climate signature of δ18O tree-ring records from sites distributed all over Europe covering last 400 years. An empirical orthogonal function (EOF) analysis reveals two distinct modes variability on basis existing records. The first mode is associated with anomaly patterns projecting onto El Niño–Southern Oscillation (ENSO) and reflects a multi-seasonal climatic sign...

There is no single reference dataset of long-term global upper-air temperature observations, although several groups have developed datasets from radiosonde and satellite observations for climate-monitoring purposes. The existence of multiple data products allows for exploration of the uncertainty in signals of climate variations and change. This paper examines eight upper-air temperature datas...