The Development and Testing of a New Method to Evaluate the Operational Cloud-Seeding Programs in Texas

Abstract

A method for the objective evaluation of short-term, nonrandomized operational convective cloud-seeding projects on a floating-target-area basis has been developed and tested in the context of the operational cloud-seeding projects of Texas. The computer-based method makes use of the Next-Generation Radar (NEXRAD) mosaic radar data to define fields of circular (25-km radius) floating-target analysis units with lifetimes from the first echo to the disappearance of all echoes and then superimposes the track and seeding actions of the project seeder aircraft onto the unit fields to define seeded (S) and nonseeded (NS) analysis units. Objective criteria (quantified herein) are used to identify ?control? (C) matches for each of the seed units from the archive of NS units. To minimize potential contamination by seeding, no matching is allowed for any control unit if its perimeter came within 25 km of the perimeter of a seed unit during its lifetime. The methodology was used to evaluate seeding effects in the High Plains Underground Water Conservation District (HP) and Edwards Aquifer Authority (EA) programs during the 1999, 2000, and 2001 (EA only) seasons. Objective unit matches were selected from within and outside each operational target within 12, 6, 3, and 2 h of the time on a given day that seeding of a particular unit took place. These were done to determine whether selection biases and the diurnal convective cycle confounded the results. Matches were also drawn from within and outside each target using the entire archive of days on which seeding was done. Although the results of all analyses are subjected to statistical testing, the resulting probability (P) values were used solely to determine the relative strength of the various findings. In the absence of treatment, randomization P values cannot be used as proof of seeding efficacy. The apparent effect of seeding in both programs was large?even after determining the effect of selection biases and the diurnal convective cycle. The most conservative and credible estimates of seeding effects were obtained from control matches drawn from outside the operational target within 2 h of the time that each unit was seeded initially. Under these circumstances, the percentage increase exceeds 50% and the volumetric increment was greater than 3000 acre-feet (3700 kt) per unit with strong P-value support (i.e., <0.0001) in both the HP and EA programs. This is in good agreement with the apparent percentage effects of seeding for the randomized Texas and Thailand cloud-seeding programs, which were 43% and 48%?92%, respectively. The results and their P-value support after partitioning gave even stronger indications of positive seeding effects. Although the results of these and other analyses described herein make a strong case for enhanced rainfall by the operational seeding programs, such programs must not be viewed as substitutes for randomized seeding efforts that are conducted in conjunction with realistic cloud modeling and are followed by replication, preferably by independent groups for maximum credibility.