A novel approach for detecting error measurements in a network of automatic weather stations - Archive ouverte HAL Access content directly
Journal Articles International Journal of Parallel, Emergent and Distributed Systems Year : 2022

A novel approach for detecting error measurements in a network of automatic weather stations

(1) , (1) , (2) ,
1
2

Abstract

In the present work, a novel methodology for error detection in automatic weather stations has been implemented. Time series acquired from two highly correlated stations with a station under analysis are utilised to obtain a 24-h air temperature forecast that allows to know if a station register erroneous measurements. Four models to obtain a reliable forecast have been analysed, auto-regressive integrated moving average, Long Short-Term Memory (LSTM), LSTM stacked and a convolutional LSTM model with uncertainty error reduction. The analysis carried out exhibits a significant success with the methodology for three stations reaching error values between 0.98∘C and 1.50∘C and correlation coefficients between 0.72 and 0.81.
Not file

Dates and versions

hal-03527927 , version 1 (16-01-2022)

Identifiers

Cite

R. Llugsi, Samira El Yacoubi, A. Fontaine, P. Lupera. A novel approach for detecting error measurements in a network of automatic weather stations. International Journal of Parallel, Emergent and Distributed Systems, 2022, pp.1-18. ⟨10.1080/17445760.2021.2022672⟩. ⟨hal-03527927⟩
36 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More