The Design and Evaluation of Rainfall Modification Experiments

Schickedanz, Paul T.; Huff, Floyd A.

doi:10.1175/1520-0450(1971)010<0502:tdaeor>2.0.co;2

Cited by 7 publications

(1 citation statement)

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“…The complex spatiotemporal variability of cloud properties and resulting precipitation represents the main source of uncertainty in seeding impact evaluations. As such, field experiments offer a single realization of seeding effects within a specific cloud lifetime which may significantly differ from an unseeded (control) cloud [23,24]. In fact, the methodology of experimentation, randomization, and statistical analysis needed for cloud seeding programs draws several parallels with the design of randomized clinical trials in the medical field [25].…”

Section: Introductionmentioning

confidence: 99%

The UAE Cloud Seeding Program: A Statistical and Physical Evaluation

Hosari¹,

Mandous²,

Wehbe³

et al. 2021

Atmosphere

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Operational cloud seeding programs have been increasingly deployed in several countries to augment natural rainfall amounts, particularly over water-scarce and arid regions. However, evaluating operational programs by quantifying seeding impacts remains a challenging task subject to complex uncertainties. In this study, we investigate seeding impacts using both long-term rain gauge records and event-based weather radar retrievals within the framework of the United Arab Emirates (UAE) National Center of Meteorology’s operational cloud seeding program. First, seasonal rain gauge records are inter-compared between unseeded (1981–2002) and seeded (2003–2019) periods, after which a posteriori target/control regression is developed to decouple natural and seeded rainfall time series. Next, trend analyses and change point detection are carried out over the July-October seeding periods using the modified Mann-Kendall (mMK) test and the Cumulative Sum (CUSUM) method, respectively. Results indicate an average increase of 23% in annual surface rainfall over the seeded target area, along with statistically significant change points detected during 2011 with decreasing/increasing rainfall trends for pre-/post-change point periods, respectively. Alternatively, rain gauge records over the control (non-seeded) area show non-significant change points. In line with the gauge-based statistical findings, a physical analysis using an archive of seeded (65) and unseeded (87) storms shows enhancements in radar-based storm properties within 15–25 min of seeding. The largest increases are recorded in storm volume (159%), area cover (72%), and lifetime (65%). The work provides new insights for assessing long-term seeding impacts and has significant implications for policy- and decision-making related to cloud seeding research and operational programs in arid regions.

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Section: Introductionmentioning

confidence: 99%