Volume 8, Issue 6, December 2019, Page: 108-116
A Methodology for Applying Conditional Nonlinear Optimal Perturbation and Natural Cybernetics to Tropical Cyclone Mitigation
Peng Yuehua, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Dalian Naval Academy, Dalian, China
Shi Weilai, College of Meteorology and Oceanography, National University of Defense Technology, Nanjing, China
Chen Zhongxin, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China; IT Division (CIO), Food and Agriculture Organization of the United Nations (FAO), Rome, Italy
Wang Ting, College of Meteorology and Oceanography, National University of Defense Technology, Nanjing, China
Received: Nov. 2, 2018;       Accepted: Nov. 27, 2018;       Published: Nov. 21, 2019
DOI: 10.11648/j.wros.20190806.13      View  660      Downloads  177
Investigations into tropical cyclone mitigation, especially those made by Ross Hoffman, are introduced in the beginning to elicit the weather control version of 4-Dimensional Variation (4D-Var) as a nonlinear optimal control technique and the theory of natural cybernetics. Subsequently, the concept of Conditional Nonlinear Optimal Perturbations (CNOP) and the existing connotation of natural cybernetics related to weather modification are briefly presented. After that, the primary application of CNOP, improved by comparison with 4D-Var, are stressed upon, which can make use of the observational data during the controlling process, thereby having some advantages over 4D-Var in weather control. The technique may be called ‘nonlinear optimal forcing variation calculus (NOFV)’ or ‘nonlinear optimal forcing perturbation (NOFP)’ approach, which could make controlling as close to the observation as possible. Moreover, two other applications of CNOP, i.e. inversion of the initial perturbation evolving into a tropical cyclone and the solution of perturbation yielding maximum vertical wind shear with CNOP, are further investigated. Subsequently, the application of natural cybernetics to tropical cyclone mitigation and control, is analyzed in comparison with precipitation enhancement. Meanwhile, the means to realize tropical cyclone control and mitigation are synoptically reviewed. The investigation and analysis show that CNOP approach and natural cybernetics are useful in tropical cyclone mitigation and control.
Conditional Nonlinear Optimal Perturbations (CNOP), Tropical Cyclone Mitigation, Natural Cybernetics, 4-Dimensional Variation (4D-Var), Nonlinear Optimal Forcing Perturbation (NOFP)
To cite this article
Peng Yuehua, Shi Weilai, Chen Zhongxin, Wang Ting, A Methodology for Applying Conditional Nonlinear Optimal Perturbation and Natural Cybernetics to Tropical Cyclone Mitigation, Journal of Water Resources and Ocean Science. Vol. 8, No. 6, 2019, pp. 108-116. doi: 10.11648/j.wros.20190806.13
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gentry R C. 1970: Hurricane Debbie Modification Experiments, August [J]. Science, 1969, 168 (3930): 473—475. doi: 10.1126/science.168.3930.473.
Willoughby, H. E., Jorgensen, D. P., et al., Project stormfury: a scientific chronicle 1962-1983. Bulletin of the American Meteorological Society, 1985, 66 (5), 505-514. doi: 10.1175/1520-0477(1985)066<0505:PSASC>2.0.CO;2.
Hoffman R. N., Controlling hurricanes, Scienfic American, 2004, 291 (4), 68–75.
Henderson J. M., Hoffman R. N., et al., A 4D-Var study on the potential of weather control and exigent weather forecasting, Q. J. R. Meteorol. Soc., 2005, 131, 3037–3051. doi: 10.1256/qj.05.72
Hoffman, R. N., J. M. Henderson, and S. M. Leidner, Using 4DVar to move a simulated tropical cyclone in a mesoscale model. Computers and Mathematics with Applications, 2006, 52 1193-1204. doi: 10.10l6/j.camwa. 2006.11.013.
Wiener N. Cybernetics [M]. Boston: MIT Press, 1948, 194pp.
Song Jian. System Cybernetics [M]// China Encyclopedia, Vol. Automatic Control and System Engineering (in Chinese). Beijing: China Encyclopedia Press, 1991, 1–6.
Zeng Qingcun, Natural Cybernetics. Climatic and Environmental Research (in Chinese). 1996, 1 (1): 11-20.
Duan, W. S., M. Mu, and B. Wang, Conditional nonlinear optimal perturbation as the optimal precursors for ENSO events. J. Geophys. Res., 2004, 109, D23105. doi: 10.1029/2004JD004756.
Duan, W. S., and M. Mu, Investigating decadal variability of El Niño–Southern Oscillation asymmetry by conditional nonlinear optimal perturbation. J. Geophys. Res., 2006, 111, C07015, doi: 10.1029/2005JC003458.
Duan, W. S., F. Xue, and M. Mu, Investigating a nonlinear characteristic of El Niño events by conditional nonlinear optimal perturbation. Atmos. Res., 2009, 94 (1), 10-18. doi: 10.1016/j.atmosres.2008.09.003.
Duan, W., Tian, B., & Hui, X., Simulations of two types of el niño events by an optimal forcing vector approach. Climate Dynamics, 2013, 43 (5-6), 1677-1692. doi: 10.1007/s00382-013-1993-4.
Gray, W. M., Global view of the origin of tropical disturbances and storms. Mon. Wea. Rev., 1968, 96, 669–700. doi: 10.1175/1520-0493(1968)096<0669:GVOTOO>2.0.CO;2.
Isabelle Dicaire, RyokoNakamura, et al., Space options for tropical cyclone hazard mitigation. Acta Astronautica, 2015, 107, 208–217. doi: 10.1016/j.actaastro.2014.11.022.
Lei Hengchi, Wei Lei, Zeng Qingcun. Cybernetics in the artificial weather modification. I: Direct and inverse or optimal controlling problem for precipitation enhancement operation [J]. Climatic and Environmental Research (in Chinese), 2012, 17 (6): 968-978. doi: 10.3878/j.issn.1006-9585.2012.06.33.
McBride, J. L., and R. M. Zehr, Observational analysis of tropical cyclone formation. Part II: Comparison of non-developing versus developing systems. J. Atmos. Sci., 1981, 38, 1132–1151. doi: 10.1175/1520-0469(1981)038<1132:OAOTCF>2.0.CO;2.
Mu M, and Duan W S, A new approach to studying ENSO predictability: Conditional nonlinear optimal perturbation, Chin. Sci. Bull., 2003, 48, 1045-1047. doi: 10.1007/BF03184224.
Mu, M., L. Sun, and D. A. Henk, The sensitivity and stability of the ocean's thermocline circulation to finite amplitude freshwater perturbations. J. Phys. Oceanogr., 2004, 34, 2305-2315. doi: 10.1175/1520-0485(2004)034<2305:TSASOT>2.0.CO;2.
Mu M, Jiang Z. A new approach to the generation of initial Derturbations for ensemble prediction: Conditional nonlinear optimal perturbation. Chinese Sci Bull, 2008, 53 (113): 6. doi: 10.1007/s11434-008-0272-y.
Mu M, Zhou F, Wang H. A method to identify the sensitive areas n targeting for tropical cyclone prediction: conditional nonlinear optimal perturbation. Mon Weather Rev, 2009, 137, 16. doi: 10.1175/2008MWR2640.1.
Peng Y H, Duan W S, Xiang J. Effect of Stochastic MJO Forcing on ENSO Predictability. Advances in Atmospheric Sciences, 2011, 28 (6), 11. DOI: 10.1007/s00376-011-0126-4.
Peng Y H, Duan W S, Xiang J. Can the uncertainties of Madden Jullian Oscillation cause a significant“spring predictability barrier”for ENSO events. Acta Meteorologica Sinica, 2012, 26 (5): 12. DOI: 10.1007/s13351-012-0503-7.
Peng Y H, Song J Q, Xiang J, Sun C Z. Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: Part I. Effect on the maximum prediction error. Acta Oceanologica Sinica, 2015, 34 (5): 7. DOI: 10.1007/s13131-015-0000-0.
Peng Y H, Zheng C W, Lian T, Xiang J. Can intra-seasonal wind stress forcing strongly affect spring predictability barrier for ENSO in Zebiak–Cane model? Ocean Dynamics, 2018, 68: 1273–1284. DOI: 10.1007/s10236-018-1196-y.
Sheets C. Robert, Analysis of Hurricane Debbie Modification Results Using the Variational Optimization Approach [J]. Monthly Weather Review, 1973, 101, 663—684. doi: 10.1175/1520-0493(1973)101<0663:AOHDMR>2.3.CO;2.
Tuleya, R. E., and Y. Kurihara, A numerical study on the effects of environmental flow on tropical storm genesis. Mon. Wea. Rev., 1981, 109, 2487–2506. doi: 10.1175/1520-0493(1981)109<2487:ANSOTE>2.0.CO;2.
Wang, B., J. J. Liu, et al., An economical approach to four-dimensional variational data assimilation. Adv. Atmos. Sci., 2010, 27 (4), 715–727, doi: 10.1007/s00376-009-9122-3.
Wang, B., and Y. Zhao, A new data assimilation approach. Acta Meteorologica Sinica (in Chinese), 2005, 63 (5), 694-701.
Wang, Y., Rao, Y., Tan, Z. M., A statistical analysis of the effects of vertical wind shear on tropical cyclone intensity change over the western north pacific. Monthly Weather Review, 2015, 143 (9). doi: 10.1175/MWR-D-15-0049.1
Zehr, R. M., Tropical cyclogenesis in the western North Pacific. NOAA Tech. Rep. NESDIS, 1992, 61, 181 pp.
Zeng Q C, Wu L, Hong Z X. Cybernetics in the artificial weather modification. III: A framework of artificial weather modification based on the natural cybernetics [J]. Climatic and Environmental Research (in Chinese), 2012, 17 (6): 986–990. doi: 10.3878/j.issn.1006-9585.2012.06.35.
Zheng C W, Xiao Z N, Peng Y H, Li C Y, Du Z B. Rezoning global offshore wind energy resources. Renewable Energy, 2018, 129: 1-11. Doi: 10.1016/j.renene.2018.05.090.
Browse journals by subject