Forecasting the Tropical Cyclone Genesis over the Northwest Pacific through Identifying the Causal Factors in the Cyclone-Climate Interactions

Forecasting the Tropical Cyclone Genesis over the Northwest Pacific through Identifying the... AbstractHow to extract the causal relations in climate-cyclone interactions is an important problem in atmospheric science. Traditionally the most commonly used research methodology in this field is time-delayed correlation analysis. This may be not appropriate, since correlation cannot imply causality as it lacks the needed asymmetry or directedness between dynamical events. In this study, we introduced to this field a recently developed and very concise but rigorous formula, i.e., a formula for information flow (IF), to fulfill the purpose. We proposed a new way to normalize the IF, and then used the normalized IF (NIF) to detect the causal relation between the tropical cyclone (TC) genesis over the western North Pacific (WNP) and a variety of climate modes. It is shown that El Niño–Southern Oscillation as well as Pacific decadal oscillation are the dominant factors that modulate the WNP TC genesis. Besides, the western Pacific subtropical high and the monsoon trough are also playing important roles in affecting, respectively, the TCs in the western and eastern regions of the WNP. With these selected climate indices as predictors, a method of fuzzy graph evolved from a nonparametric Bayesian process (BNP-FG), which is capable of handling situations with insufficient samples, is employed to perform a seasonal TC forecast. A forecast with the classic Poisson regression is also conducted for comparison. We found that the BNP-FG model together with the causality analysis can provide a satisfactory estimation of the numbers of TC genesis observed in recent years. Considering its generality, it is expected to be applicable in other climate-related predictions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

Forecasting the Tropical Cyclone Genesis over the Northwest Pacific through Identifying the Causal Factors in the Cyclone-Climate Interactions

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
D.O.I.
10.1175/JTECH-D-17-0109.1
Publisher site
See Article on Publisher Site

Abstract

AbstractHow to extract the causal relations in climate-cyclone interactions is an important problem in atmospheric science. Traditionally the most commonly used research methodology in this field is time-delayed correlation analysis. This may be not appropriate, since correlation cannot imply causality as it lacks the needed asymmetry or directedness between dynamical events. In this study, we introduced to this field a recently developed and very concise but rigorous formula, i.e., a formula for information flow (IF), to fulfill the purpose. We proposed a new way to normalize the IF, and then used the normalized IF (NIF) to detect the causal relation between the tropical cyclone (TC) genesis over the western North Pacific (WNP) and a variety of climate modes. It is shown that El Niño–Southern Oscillation as well as Pacific decadal oscillation are the dominant factors that modulate the WNP TC genesis. Besides, the western Pacific subtropical high and the monsoon trough are also playing important roles in affecting, respectively, the TCs in the western and eastern regions of the WNP. With these selected climate indices as predictors, a method of fuzzy graph evolved from a nonparametric Bayesian process (BNP-FG), which is capable of handling situations with insufficient samples, is employed to perform a seasonal TC forecast. A forecast with the classic Poisson regression is also conducted for comparison. We found that the BNP-FG model together with the causality analysis can provide a satisfactory estimation of the numbers of TC genesis observed in recent years. Considering its generality, it is expected to be applicable in other climate-related predictions.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Dec 5, 2017

References

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