Web Mapping of Extreme Daily Rainfall Data in Central and Northern Argentina

2021 ◽  
Vol 26 (7) ◽  
pp. 05021013
Author(s):  
Carlos Gastón Catalini ◽  
Nicolás Federico Guillen ◽  
Flavia Marcela Bazzano ◽  
Carlos Marcelo García ◽  
María Magdalena Baraquet
1972 ◽  
Vol 7 (2) ◽  
pp. 79-83 ◽  
Author(s):  
L P Smith

Daily rainfall data for twenty years in arable farming areas are analysed with respect to four standards of drainage and for three lengths of schedule of spring work. Distribution and frequency in time of available work days are interpreted in terms of lateness of sowing and of barley yield. Formulae are established to calculate average yield loss in terms of drainage standard and work schedule, enabling estimates to be made of the effect of planned improvements.


2019 ◽  
Vol 8 (4) ◽  
pp. 2279-2288

A combination of continuous and discrete elements is referred to as a mixed distribution. For example, daily rainfall data consist of zero and positive values. We aim to develop a Bayesian time series model that captures the evolution of the daily rainfall data in Italy, focussing on directly linking the amount and occurrence of rainfall. Two gamma (G1 and G2) distributions with different parameterisations and lognormal distribution were investigated to identify the ideal distribution representing the amount process. Truncated Fourier series was used to incorporate the seasonal effects which captures the variability in daily rainfall amounts throughout the year. A first-order Markov chain was used to model rainfall occurrence conditional on the presence or absence of rainfall on the previous day. We also built a hierarchical prior structure to represent our subjective beliefs and capture the initial uncertainties of the unknown model parameters for both amount and occurrence processes. The daily rainfall data from Urbino rain gauge station in Italy were then used to demonstrate the applicability of our proposed methods. Residual analysis and posterior predictive checking method were utilised to assess the adequacy of model fit. In conclusion, we clearly found that our proposed method satisfactorily and accurately fits the Italian daily rainfall data. The gamma distribution was found to be the ideal probability density function to represent the amount of daily rainfall.


2013 ◽  
Vol 17 (4) ◽  
pp. 1311-1318 ◽  
Author(s):  
F. Yusof ◽  
I. L. Kane ◽  
Z. Yusop

Abstract. A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the ordinary least square (OLS)-based cumulative sum (CUSUM) test for the break date was applied. Break dates were detected in all data sets. The data sets were partitioned according to their respective break date, and a further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern as the original series. The estimate of the fractional parameters d1 and d2 on the subseries obtained by splitting the original series at the break date confirms that there is a long memory in the data generating process (DGP). Therefore this evidence shows a true long memory not due to structural break.


1956 ◽  
Vol 9 (1) ◽  
pp. 151 ◽  
Author(s):  
SC Das

In a previous paper (Das 1955) the author discussed a problem of curve fitting which arose in testing the hypothesis proposed by Bowen (1953) concerning daily rainfall data.


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