Integration of modern statistical tools for the analysis of climate extremes into the web-GIS "CLIMATE"

International Conference on Computational Information Technologies for Environmental Sciences 2017

生态环境科学;计算机科学

Ryazanova, A.A.^1,2 ; Okladnikov, I.G.^1,2,3 ; Gordov, E.P.^1,2,3

Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, Russia^1

V.E. Zuev Institute of Atmospheric Optics SB RAS, Tomsk, Russia^2

Institute of Computational Technologies, Tomsk Branch, Tomsk, Russia^3

关键词: Analysis of various;    Environmental characteristic;    Impact on the environment;    Quantile regression;    Statistical packages;    Statistics of extremes;    Structural connections;    Temperature extremes;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/96/1/012014/pdf
DOI  :  10.1088/1755-1315/96/1/012014

来源: IOP

【 摘 要 】

The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called "CLIMATE" to include a dedicated statistical package developed in the R language. The web-GIS "CLIMATE" is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS "CLIMATE" can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.