Author(s)

Runmo Wang ¹, Zonghong Han ¹, Shiqin Li ², Jing Chen ³

Affiliation(s)

¹ School of Electrical Engineering and Automation, Qilu University of Technology, Jinan, Shandong, 250353, China
² School of Information Science and Engineering, Harbin Institute of Technology (Weihai), Weihai, Shandong, 264209, China
³ School of Mathematics and Statistics, Qilu University of Technology, Jinan, Shandong, 250353, China

Corresponding Author

Runmo Wang

ABSTRACT

This paper presents a quantitative and qualitative analysis of extreme precipitation. First, it is used to filter abnormal precallofil values using robust Mahalanobis distance. At the same time, consider the influence of related variables on the annual precipitation. It has been high in precipitation in 2003, 2016 and 2021, and higher precipitation is 1964, 1983 and 1992. Using nonlinear least squares method to fit the correlation between the annual precipitation and other climate indicators, the PRCP has an unstable oscillation in July, and DEWP and TEMP have an oscillation rise trend, and SLP is attenuated.

KEYWORDS

Robust Mahalanobis distance, nonlinear least squares method, precipitation analysis

CITE THIS PAPER

Runmo Wang, Zonghong Han, Shiqin Li, Jing Chen, Research on Extreme Precipitation Analysis Model Based on Robust Mahalanobis Distance and Nonlinear Fitting. Environment, Resource and Ecology Journal (2022) Vol. 6: 20-23. DOI: http://dx.doi.org/10.23977/erej.2022.060104.

REFERENCES

[1] Maining, Ren Zhihua, Wang Wei, Liu Na, Cao Ning. Comparative analysis of parallel observation of national precipitation weather [J / OL]. Study on arid zone: 1-11 [2022-01-05]. Http: //Kns.cnki.net/kcms/detail/65.1095.x. 20211224.1422.002.html.
[2] Bidush Ranjan Swar et al. Genetic Diversity Studies in MAGIC Population of Soybean (Glycine max (L.) Merrill) Based on Mahalanobis D2 Distance [J]. International Journal of Plant & Soil Science, 2021: 18-25.

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