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Applying ranking techniques for estimating influence of Earth variables on temperature forecast error by Flores, M. Julia; Ruiz-Vásquez, Melissa; Bastos, Ana; Orth, René is a scholarly article available to read on EtoBox.

What is Applying ranking techniques for estimating influence of Earth variables on temperature forecast error about?

This paper describes how to analyze the influence of Earth system variables on the errors when providing temperature forecasts. The initial framework to get the data has been based on previous research work, which resulted in a very interesting discovery. However, the aforementioned study only worked on individual correlations of the variables with respect to the error. This research work is going to re-use the main ideas but introduce three main novelties: (1) applying a data science approach by a few representative locations; (2) taking advantage of the rankings created by Spearman correlation but enriching them with other metrics looking for a more robust ranking of the variables; (3) evaluation of the methodology by learning random forest models for regression with the distinct experimental variations. The main contribution is the framework that shows how to convert correlations into rankings and combine them into an aggregate ranking. We have carried out experiments on five chosen locations to analyze the behavior of this ranking-based methodology. The results show that the specific performance is dependent on the location and season, which is expected, and that this selection

Author

Flores, M. Julia; Ruiz-Vásquez, Melissa; Bastos, Ana; Orth, René

Published

2024

Language

EN