Rainfall Enhancement in the Hajar Mountains, Oman
The trial employed a randomised crossover design with the two emitters operated in a pre-determined randomised alternating schedule. Statistical analysis of the trial data was carried out using spatio-temporal models that used meteorological and spatio-temporal covariates to capture natural rainfall variation, enabling prediction of the level of rainfall that would have occurred if the ionisation emitters had not been operated.
The methodology used in the 2013 Oman trial was originally developed for rainfall enhancement trials in Australia. This used dynamically defined target and control areas corresponding to two overlapping 60° arcs emanating from each of the emitter sites and oriented downwind in the direction of an average steering wind (Beare et al. 2010; 2011; Chambers et al. 2012). For the 2013 Oman trial, a simple alternative model was also developed prior to analysis of the trial data. This defined target and control areas in terms of 'corridors' placed symmetrically about each emitter site and oriented downwind along the axis defined by the steering wind direction. The final statistical analysis of the trial was therefore conducted using both a dynamic 60° downwind arc model and a 30km wide dynamic downwind corridor model.
Overall, a positive and significant rainfall enhancement effect attributable to the operation of the emitters was observed over the course of the trial under both models. The total attribution (enhancement effect) in the trial area defined by the 60º arc model, as a percentage of estimated natural rainfall, was estimated to be 11.7 per cent with a semiparametric bootstrap standard error of 9.1 per cent and a corresponding bootstrap confidence of at least 90 per cent for a positive attribution over the course of the trial. The corresponding estimate of total attribution defined by the 30 km corridor model, as a percentage of estimated natural rainfall, was 18 per cent with a semiparametric bootstrap standard error of 8.4 per cent and a bootstrap confidence level of at least 99 per cent for a positive attribution.
Chambers, R., S. Beare, S. D. Peak. (2012) Using dynamically defined controls to evaluate the impact of an ionization technology. J. Wea. Mod. Vol. 44, pp. 16-29.
Beare, S., R. Chambers, S. D. Peak. (2011) Accounting for spatiotemporal variations of rainfall measurements when evaluating ground-based methods of weather modification. J. Wea. Mod. Vol. 43, pp. 44-63.
Beare, S., R. Chambers, S. Peak, (2010) Statistical Modeling of Rainfall Enhancement. Journal of Wea. Modif. 42.