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Score-driven models for air temperature analysis

delete2026-06-01
delete1
PRE
AI
S
Sumnikova, Alzbeta
P
Petra Tomanová *
DOI：10.1007/s10100-026-01020-2delete
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Abstract

Abstract

En 中文
This study analyzes historical temperature trends using Generalized Autoregressive Score (GAS) models, which capture time-varying dynamics in time series data. Using temperature data from Czechia, we examine average temperatures as well as extremes, including maximum and minimum values, and identify a consistent upward trend across all indicators, particularly since 1950. The GAS models demonstrate superior in-sample fit and out-of-sample forecasting performance compared to traditional approaches such as ARMA and GARCH models. Forecasts based on the GAS model project a substantial increase in temperatures of 1.29 degrees C over the next 40 years.
Keywords:
Air temperature
Climate
Score-driven model

Journal

C
Central European Journal of Operations Research
IF:
2.3
Papers:
35
Citations:
1.3K

Organization

No organization information available