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Critical Issues in Weather Modification Research (2003) / Chapter Skim
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Appendix B: Modern Statistical Methods and Weather Modification Research
Pages 107-113

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From page 107...
... For example, one will never be able to "randomize" effectively all sources of uncontrollable bias in weather modification experiments. Consequently, sophisticated statistical models have to be considered to explore potential significant effects.
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From page 108...
... 9961. Second, such models can be used to incorporate very complicated spatial and temporal dependence in the generalized linear mixed model fiamework discussed above with relative ease (e.g., Diggle et al., 1998~.
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From page 109...
... the net result is that with relatively simple physical and stochastic representations in tile sequence of conditional models (e.g., RHS of ~24) , we can obtain a posterior distribution for u and v that has verb complicated spatial structure; one that, through the quantification of uncertainty, can "adapt" to a wide variety of observations and our prior knowledge of the geophysical system.
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From page 110...
... Data Models Datasets commonly considered for atmospheric processes are complicated and usually exhibit substantial spatial, temporal, or spatio-temporal dependence. The major advantage of modeling the conditional distribution of the data given the true process is that substantial simplifications in model form are possible.
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From page 111...
... approach is the quantification of such subjective judgment. Hierarchical models provide a coherent probabilistic framework ilk which to incorporate explicitly in the model the uncertainty related to j udgment, scientific reasoning' subjective decisions' and experience.
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From page 112...
... In each please ofthis analysis, modern model-based statistical methods could be used. Although such a model-based design perspective is advantageous, one could still use the model building and data analysis approach suggested here to analyze results front past experiments or from new experiments that were not designed from this perspective CONCLUSION In addition to new technological advances in the atmosphere ic sciences' substantial advances also have occurred in the statistical sciences over the past three decades.
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From page 113...
... 1975. Bayesian and classical statistical methods applied to randomized Deadlier modification experiments.
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Key Terms

  • modification experiments
  • hierarchical bayesian
  • process models
  • linear mixed
  • bayesian statistical

  • parameter distributions
  • statistical models
  • modification research
  • generalized linear
  • change assessment

  • experimental design
  • process distribution
  • bayesian analysis
  • mixed model
  • hierarchical models

  • scientific insight
  • conditional distribution
  • statistical sciences
  • models provide
  • monitoring networks

  • hierarchical analysis
  • develop understanding
  • atmospheric circulation
  • implement bayesian
  • model building

  • parameter models
  • prior knowledge
  • past weather
  • bayesian paradigm
  • model fiamework


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