The UAE Cloud Seeding Program: A Statistical and Physical Evaluation
نویسندگان
چکیده
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 by quantifying impacts remains a challenging task subject complex uncertainties. In this study, we investigate using both long-term rain gauge records event-based weather radar retrievals within the framework of United Arab Emirates (UAE) National Center Meteorology’s program. First, seasonal are inter-compared between unseeded (1981–2002) seeded (2003–2019) periods, after which posteriori target/control regression is developed decouple time series. Next, trend analyses change point detection carried out July-October periods modified Mann-Kendall (mMK) test Cumulative Sum (CUSUM) method, respectively. Results indicate an average increase 23% annual surface target area, along with statistically significant points detected during 2011 decreasing/increasing trends for pre-/post-change Alternatively, control (non-seeded) area show non-significant points. line gauge-based statistical findings, physical analysis archive (65) (87) storms shows enhancements radar-based storm properties 15–25 min seeding. The largest increases recorded volume (159%), cover (72%), lifetime (65%). work provides new insights assessing has implications policy- decision-making related research
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ژورنال
عنوان ژورنال: Atmosphere
سال: 2021
ISSN: ['2073-4433']
DOI: https://doi.org/10.3390/atmos12081013