Skip to main content
Log in

Influence of natural rainfall variability on the evaluation of artificial precipitation enhancement

Science China Earth Sciences Aims and scope Submit manuscript

Abstract

Evaluating cloud seeding effects is one of the most critical issues in artificial precipitation enhancement experiments. However, the evaluation is not straightforward because there is natural rainfall variability, which subjects the atmosphere to spatiotemporal instabilities. The aim of this study is to analyze natural rainfall variability using the modern statistical simulation method, “bootstrap”, to analyze its influence on the evaluation of seeding activities and to take proper measures to control the influence. The study is based on the 1997–2007 airborne seeding macro records and the daily precipitation data in Jilin Province. The influence of natural rainfall variability can be reduced through three approaches: the increase of the supposed “seeded” sample size N, the rejection of outliers, and the selection of similar control units. A larger N leads to smaller calculated precipitation variability and detectable lower limits of seeding effects. When N is near 470 and the seeding effect is between 20% and 30%, the confidence level reaches 90%. For a single seeding operation, the case deletion model that rejects strong influence points and selects similar control units is established to control the influence of natural precipitation variability, which obviously improves the evaluation of artificial precipitation enhancement. The results demonstrate that the relative seeding effect in Jilin Province is concentrated mainly in the range of 0 to 30%, with an average of 11.95%, and has no significant linear relationship with the actual precipitation amount. However, the fluctuation amplitude of the relative effect decreases as the precipitation amount rises.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Abbas A, Mustafa A. 1999. Syrian rain enhancement project (1991–1998). In: Secretariat of World Meteorological Organization, ed. 7th WMO Scientific Conference on Weather Modification, Chiang Mai, Thailand. 118–120

    Google Scholar 

  • Anthony R O, William L W. 1975. On the effect of natural rainfall variability and measurement errors in the detection of seeding effect. J Appl Meteorol, 14: 929–938

    Article  Google Scholar 

  • Beare S, Chambers R, Peake S. 2010. Accounting for spatiotemporal variation of rainfall measurements when evaluating ground-based methods of weather modification. Centre for Statistical and Survey Methodology, University of Wollongong, Working Paper

    Google Scholar 

  • Dikta G, Kvesic M, Schmidt C. 2006. Theory and methods-bootstrap approximations in model checks for binary data. J Am Stat Assoc, 101: 521–530

    Article  Google Scholar 

  • Fang B, Ban X X, Xaio H. 2009. Study on statistical power of artificial precipitation experimental area in Liaoning (in Chinese). Plateau Meteorol, 28: 586–593

    Google Scholar 

  • Gabriel K R, Chin F H. 1980. Power study of re-randomization test. In: Secretariat of World Meteorological Organization, ed. 3rd WMO Scientific Conference on Weather Modification, Clemont-Ferrand, France. 21–25

    Google Scholar 

  • Gabriel K R. 1979. Some statistical issues in weather experimentation. Comm Statis-Theor Meth, A8: 975–1015

    Article  Google Scholar 

  • Geerts B, Miao Q, Yang Y, et al. 2010. An airborne profiling radar study of the impact of glaciogenic cloud seeding on snowfall from winter orographic clouds. J Atmos Sci, 67: 3286–3302

    Article  Google Scholar 

  • Gerhard D, Sundarraman S, Thorsten W. 2013. Bootstrap based model checks with missing binary response data. Stat Probabil Lett, 83: 219

    Article  Google Scholar 

  • Hsu C F, Gabriel K R, Changnon S A. 1981. Statistical techniques and key issues for the evaluation of operational weather modification. J Weather Modif, 13: 195–199

    Google Scholar 

  • John A F, William L W, Robert W B, et al. 1981. Comments on “FACE rainfall results: seeding effect or natural variability?”. J Appl Meteorol, 20: 98–107

    Article  Google Scholar 

  • Kempthorne O, Doerfler T E. 1969. The behavior of some significance tests under experimental randomization. Biometrika, 56: 231–248

    Article  Google Scholar 

  • Manton M J, Warren L, Kenyon S L, et al. 2011. A confirmatory snowfall enhancement project in the snowy mountains of Australia. Part I: Project design and response variables. J Appl Meteor Climatol, 50: 1432–1447

    Google Scholar 

  • Ronald C, Larry M P, Wesley J. 1992. Case-deletion diagnostics for mixed models. Technometrics, 34: 38–45

    Article  Google Scholar 

  • Rosenfeld D, Axisa D, Woodley W L, et al. 2010. A quest for effective hygroscopic cloud seeding. J Appl Meteor Climatol, 49: 1548–1562

    Article  Google Scholar 

  • Salvam A M, Murty A S R, Murty B V R. 1979. Numerical simulation of cloud seeding experiments in Maherashtra State, India. J Weather Modif, 11: 116–140

    Google Scholar 

  • Sarah A T, Roelof T B, Courtney W, et al. 2012. The Queensland cloud seeding research program. Bull Amer Meteorol Soc, 93: 75–90

    Article  Google Scholar 

  • Schickedanz P T, Huff F A. 1971. The design and evaluation of rainfall modification experiments. J Appl Meteorol, 10: 502–514

    Article  Google Scholar 

  • Wang W. 2008. Numerical analysis of statistical power in precipitation enhancement of non-randomized experiment and statistical method improvement (in Chinese). Thesis for Master Degree. Beijing: Chinese Academy of Meteorological Sciences

    Google Scholar 

  • Wang X L, Liu J. 1992. The effect test and criterion of clouds seeding during 1980–1987 in Jilin Province (in Chinese). J Appl Meteorol Sci, 4: 418–423

    Google Scholar 

  • Xue L, Hashimoto A, Murakami M, et al. 2013. Implementation of a silver iodide cloud an airborne profiling radar study of the impact of glaciogenic cloud seeding seeding parameterization in WRF. Part I: Model description and idealized 2D sensitivity tests. J Appl Meteor Climatol, 52: 1433–1457

    Article  Google Scholar 

  • Xue Y, Chen L P. 2007. Statistical Modeling with R (in Chinese). Beijing: Tsinghua University Press

    Google Scholar 

  • Ye J D, Cheng K M, Zeng G P. 1981. The statistical characteristics of areal rainfall and the effects of randomized cloud seeding experiment in Gutian, Fujian (in Chinese). Acta Meteorol Sin, 39: 474–482

    Google Scholar 

  • Ye J D, Luo X P, Zeng G P, et al. 1984. Numerical analysis of statistical power in randomized precipitation enhancement experiment (in Chinese). Acta Meteorol Sin, 42: 69–79

    Google Scholar 

  • Yue C L, Huang Y X. 2009. Modern statistical analysis of economic data using SAS (in Chinese). Hefei: Press of University of Science and Technology of China

    Google Scholar 

  • Zheng G G, Chen Y, Wang P F, et al. 2005. Critical issues in weather modification research (in Chinese). Beijing: China Meteorological Press. 27–92

    Google Scholar 

  • Zeng G P, Fang S Z, Xiao F. 1991. The total analysis of the effect of artificial rainfall in Gutian Reservoir Area, Fujian (1975–1986) (in Chinese). Chin J Atmos Sci, 4: 97–108

    Google Scholar 

  • Zeng G P, Liu J. 1993. A research on a statistical simulation method for the test of the artificial rainfall effect (in Chinese). Acta Meteorol Sin, 51: 241–247

    Google Scholar 

  • Zeng G P, Zhang C A, Li M L. 2000. Study on statistic numerical simulation method of precept statistic design of artificial precipitation (in Chinese). Chin J Atmos Sci, 24: 131–141

    Google Scholar 

  • Zeng G P, Zheng X Z, Fang S Z, et al. 1994. Research on the method of evaluating the efficiency of the non-randomized artificial precipitation experiments (in Chinese). Chin J Atmos Sci, 18: 233–242

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to XiangHua Wu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, X., Niu, S., Jin, D. et al. Influence of natural rainfall variability on the evaluation of artificial precipitation enhancement. Sci. China Earth Sci. 58, 906–914 (2015). https://doi.org/10.1007/s11430-015-5055-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-015-5055-0

Keywords

Navigation