Ali Reza Ildoromi; Hamid Zareabyaneh; Maryam Bayatvarkeshy
Volume 17, Issue 43 , October 2013, , Pages 21-40
Abstract
Rainfall due to its noise and random nature has structural changes at different times. Because of large uncertainty, fluctuations in the amount of rainfall forecast is created the prediction of which has been difficult. In this article, precipitation predictability was carried out rescaled by range analysis ...
Read More
Rainfall due to its noise and random nature has structural changes at different times. Because of large uncertainty, fluctuations in the amount of rainfall forecast is created the prediction of which has been difficult. In this article, precipitation predictability was carried out rescaled by range analysis (R/S) technique in Shiraz, Mashhad and Kerman regions. SnapshotHurst (H) showed that rainfall parameter has the ability of predictability, because H was higher than 0.5 and much closer to the value 1. Minimum Hurst value was 0.8 in Mashhad and maximum Hurst value was 0.92 in Shiraz. In order to predict rainfall we used artificial neural network. Type of input parameters based on Pearson correlation test between data from non-rainfall, were a combination of temperature and humidity data. Number of input parameters, the number of middle layers, and other information related to artificial neural network randomly were selected. As a whole, rainfall estimation was calculated through Peresptron multi-layer neural network for comparing the performance of neural network. Results showed that the use of 3 and 4 meteorological parameters has the best rank estimator. Proposed layouts for the Shiraz station is 1-21-21-3, for Kerman 1-25-25-3 and for Mashhad 1-19-19-4 in which 1-25-25-3 of have correlation coefficients more than 91 percent. Validation rainfall models showed that network designed for rainfall parameters has best performance rainfall in Mashhad, Shiraz and Kerman stations with 4, 11 and 14 percent error respectively. As a whole, results showed that neural network method with considering the temperaturel and humidity data for describing the process and their combination in predicting good results were offered.
Mahmood Khosravi; Mohammad Salighe; Behrooz Sabaghi
Volume 16, Issue 37 , November 2011, , Pages 59-81
Abstract
The sea surface temperature (SST) variations play a very important role in the creation and maintenance of climatological and oceanographic processes such as heavy precipitation and subsequent floods, large-scale sea level fluctuations and tropical cyclones.
In this paper the effects of Oman sea surface ...
Read More
The sea surface temperature (SST) variations play a very important role in the creation and maintenance of climatological and oceanographic processes such as heavy precipitation and subsequent floods, large-scale sea level fluctuations and tropical cyclones.
In this paper the effects of Oman sea surface temperature (SST) on the autumn and winter precipitation of its northern coast, were investigated.
The SST data was obtained from NCEP archives based on 4 points averaging nodes in Oman sea surface using GRADS software. Also the climatic data of 3 stations of Iranian coast (Chahbehar, Jask and Bandar Abas) were used.
The warm (Rw), cold (Rc) and normal (Rb) periods of Oman SST were explained and the median of precipitations in each periods is calculated. The Rw\Rb, Rc\Rb and Rc\Rw ratios were used for evaluating the effects of these conditions on the precipitations anomalies on the coast.
The results shown that the spring warm (cold) SST conditions in Oman sea can decrease (increase) precipitation in the selected stations of regions. Also the winter and autumn precipitation on northern coasts is remarkable, being synchronous to positive anomalies of summer SST.
For considering the mechanism of the effect of Oman sea surface temperature on coastal precipitation, the stream lines, relative humidity and Omega maps were prepared and used. The results showed that the SST effects on stream lines and relative humidity on sea surface are the major mechanisms of precipitation anomalies. Generally during higher precipitation periods, the streamlines over the sea are navigate a longer route and therefore the moisture contents of rainfall systems and ascending currents are suitable for precipitation.
