A View for Atmospheric Unpredictability

Xiuhua Cai,Jingli Sun,Ying Yu,Hongxing Cao,Xiaoyi Fang

doi:10.3389/feart.2021.686832

Xiuhua Cai, Jingli Sun + Show 3 more

Open Access

https://doi.org/10.3389/feart.2021.686832

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Abstract

Based on Chaotic Dynamics, this paper illustrated the necessity of research and the objective existence of atmospheric unpredictability. Actually, inaccurate forecast happens all the time in both operational weather forecasting and climate prediction in which atmospheric unpredictability hides. By means of Discrete Mathematics, this paper also defined the Degree of Hesitation and the Predictable Days with which to discuss and compare the relationship between the predictability and unpredictability of several different forecast objects. In addition, this paper discussed the approaches of evaluating the atmospheric predictability and unpredictability, emphatically showed the Experience Assessment Method. At the last, this paper also proved the existence of atmospheric unpredictability by an example.

Highlights

The study of atmospheric predictability, that is weather predictability, and climate predictability, has had a long history
This paper has studied the unpredictability of atmosphere, based on defining some variables using discrete mathematics and periphery theory
The unpredictability and the predictability are listed as the same unary, which allows us to make conceptual and methodological changes in the study of predictable problems, that is, whether using dynamics or statistics to study the problem of predictability, we should consider studying both predictability and unpredictability, instead of just studying predictability

Summary

Introduction

The study of atmospheric predictability, that is weather predictability, and climate predictability, has had a long history. The earliest study of dynamical predictability appeared in 1957 when Thompson firstly raised the issue of the predictability of Numerical Weather Prediction. Suppose an error exists in the initial field, it will be doubled after a period of time the integral of the equation of atmospheric motion, and it will get bigger and bigger. This length of time is called Predictability (Thompson, 1957). Zheng et al (2013) used similar-dynamical method to correct the forecast error of the predictable components, so as to statistically reduce the model error and the influence of the random components on the predictable components. Due to different definitions of predictability and different research methods, there were various predictability studies, the conclusions are often significantly different from each other (Wang, 2005; Li et al, 2006; Wang, 2009; Chen et al, 2019; Mu et al, 2020; Zhuang et al, 2020)

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