Constructing synthetic time series of rainfall events for a hyperarid environment, southern Arava, Israel

A method is proposed for simulating a long-term event-related daily precipitation series in a hyperarid environment. The method permits a rapid and relatively easy way to manipulate the time series to simulate not only the present climate, but other assumptions regarding past changes in rainfall properties too. The method is applied to the hyperarid environment (30 mm year^-1, 2-10 rain-days year^-1) of the southern Arava, Israel. The properties of a synthetic 1000 year daily precipitation record were compared with a dataset from Eilat. The annual rainy-days distribution of the synthetic series and the actual data were found to be similar and the stochastic precipitation procedure accurately simulated both the mean and the variance of annual precipitation amounts. Our approach allows better sensitivity analyses, since the basic parameters (such as seasonality, rainfall amounts, number of rain days, daily rainfall amounts) can be tested separately or combined with other parameters in terms of the impact on model outcome.