2021/10/21 by Hewei Wang, Muhammad Salman Pathan, Wang, Hewei +5
Decision Sciences · Earth and Planetary Sciences · Engineering · #Applications (stat.AP) #Atmospheric and Oceanic Physics (physics.ao-ph) #Energy Load and Power Forecasting #FOS: Computer and information sciences #FOS: Physical sciences #Forecasting Techniques and Applications #Meteorological Phenomena and Simulations
paper · pdf · doi:10.48550/arxiv.2110.13812
openalex publication_date 2021/10/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Air temperature is an essential factor that directly impacts the weather. Temperature can be counted as an important sign of climatic change, that profoundly impacts our health, development, and urban planning. Therefore, it is vital to design a framework that can accurately predict the temperature values for considerable lead times. In this paper, we propose a technique based on exponential smoothing method to accurately predict temperature using historical values. Our proposed method shows good performance in capturing the seasonal variability of temperature. We report a root mean square error of 4.62 K for a lead time of 3 days, using daily averages of air temperature data. Our case study is based on weather stations located in the city of Alpena, Michigan, United States.