Spatial interpolation of rainfall in the dry zone of Sri Lanka

One of the problems which often arises in climatology is either data at a given site is missing or the site is ungauged. In this study, a spatial interpolation model was developed to estimate the weekly rainfall of the Dry zone of Sri Lanka at ungauged sites assuming that the spatial continuity of rainfall at two neighbouring locations are exponentially correlated. Twenty years of weekly rainfall data from six stations located in the Dry zone was used in the study. To support the methodology, the results of the exponential model were compared with the other two methods of spatial interpolation techniques, namely, the local mean and the inverse distance methods. The results of the study indicates that the exponential correlation model is a promising candidate for estimating mean weekly rainfall of the Dry zone. However, the local mean and the inverse distance methods compare quite well along with the exponential model, indicating that more complex models have no particular advantage over simple models for estimating rainfall in the Dry zone of Sri Lanka. Nevertheless, the results point towards the relative importance of the exponential model as opposed to the other two models when the neighbouring locations do not have long series of historical records

Stochastic simulation of solar radiation from sunshine duration in Sri Lanka

A stochastic model for generating daily sunshine hours and solar radiation that reaches the earth's surface in dry zone of Sri Lanka has been developed. Historical sunshine data which represent a Weibull probability density function and universal Angstrom type equations were used in the model giving daily and monthly sunshine and solar radiation. Simulated values clearly follows the astronomical phenomenon and local atmospheric conditions. The lowest solar radiation values (14 to 15 MJ m⁻² day⁻¹) were obtained during the major rainy season. The highest values (around 20 MJ m⁻² day⁻¹) were evident around the Vernal Equinox (March and April). Sri Lanka being small in size (65,000 km²) and small latitudinal extent (<4°), the model may form the basis for more comprehensive solar radiation generating models for other areas in Sri Lanka

On development and comparative study of two Markov models of rainfall in the dry zone of Sri Lanka

Being closer to the equator, the most important climatic element for agricultural production in Sri Lanka is rainfall which is erratic and highly unpredictable in nature, especially in the dry zone. This study attempts to model the weekly rainfall climatology of dry zone using Markov processes as the driving mechanism based on the 51 years of past data. The weekly occurrence of rainfall was modelled by two-state first and second order Markov chains while the amount of rainfall on a rainy week was approximated by taking random variates from the best fitted right skewed probability distribution out of Gamma, Weibull, Log-Normal and Exponential distributions. The parameters of the both models namely, elements of transition matrices, and scale and shape parameters of the desired distribution, were determined using weekly data. Both first and second Markov chains performed similarly in terms of modelling weekly rainfall occurrence and amount of rainfall if rain occurred. Use of second order Markov chain did not enhance the representativeness of the simulated data to the observed data in spite of being penalised for its large number of computations. Weekly rainfall data generated with the first-order Markov chain model preserve the statistical and seasonal characteristics that exist in the historical records