Rainfall prediction is very complex hydrologic process and is important as it holds the key to any countries’ economy. Proposed model presents a new approach for yearly rainfall prediction of 30 Indian subdivisions. Yearly rainfall data of the Indian subdivision is available from IITM, Pune. The combination of Fast Fourier Transform (FFT) and Feed Forward Neural Network (FFNN) is applied for ne...

In this study we model the daily rainfall occurrence using Markov Chain Analogue Yearmodel (MCAYM) and the intensity or amount of daily rainfall using three different probability distributions; gamma, exponential and mixed exponential distributions. Combining the occurrence and intensity model we obtain Markov Chain Analogue Year gamma model (MCAYGM), Markov Chain Analogue Year exponentia...

Under a weather hazard prevention program in Taiwan, the Vaisala Meteorological Instrument, Inc., of Finland and the Environmental Science and Engineering Corporation of Taiwan jointly developed and installed more than 300 stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) over this subtropical island with an area of approximately 30 000 km. The Taiwan ARMTS network ...

A regional climate model named Providing REgional Climates for Impacts Studies (PRECIS) adapted in generating rainfall scenarios for the SAARC (South Asian Association for Regional Cooperation) region. At first, PRECIS generated rainfall scenario is calibrated with ground-based observed rainfall during baseline period (1961-1990) in Bangladesh. The regression coefficients obtained through calib...

It was originally suggested that this paper should deal with problems associated with the management of grazings under low rainfall conditions and the title submitted was “Problems of management of grassland under low rainfall conditions in South Africa.” It was decided, however, that as much of the veld under low rainfall conditions was not grassland, it would be better to deal with the main v...

The continuous occurrence of changes in the global climate causes significant variability in the seasonal and intra-seasonal rainfall pattern, which often leads to frequent floods and droughts in India. To reduce the magnitude of effect of such natural calamities and for better management of water resources, it is essential to predict the rainfall, well in advance. In this study the possible re...

introduction: rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature sst sea surface temperature and sea level pressure slp sea level pressure. climate anomalies being related to each other at large distance is called teleconnection. as physical relationships between rainfall and teleconnection patterns are not defined clearly, we used inte...

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...

The payout and price of a rainfall-based index insurance contract are both functions of rainfall, which is a random process. In order to design and price these contracts, therefore, the buyers and the sellers of the contracts must both have a satisfactory understanding of the rainfall process, and must be able to communicate their beliefs to each other in order to negotiate the design and price...