The rapid development of industrialization and urbanization has had a substantial impact on the increasing air pollution in many populated cities around the globe. Intensive research has shown that ambient aerosols, especially the fine particulate ma...
This study investigates the impact of the sea surface temperature (SST) on the forecast of two typhoons, which consecutively hit South Korea in 2020. SST data were obtained from the Daily Optimum Interpolation Sea Surface Temperature (OISST) version...
Soil temperature patterns are of great importance for any agro-based economy like Bangladesh since they significantly affect biological, chemical, and physical processes that take place in the soil. Unfortunately, there have been no forecast studies...
This study verified the seasonal six-month forecasts for winter temperatures for northern Vietnam in 1998–2018 using a regional climate model (RegCM4) with the boundary conditions of the climate forecast system Version 2 (CFSv2) from the Nation...
This paper selects the case of the Atlantic hurricane “Michael” in 2018 to evaluate the accuracy of the GOES-16 atmospheric temperature profile during the hurricane and its effect on forecasting. Based on the weather research and forecast...
Using the observational data and the forecast and reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) during 2015–2018, the temporal and spatial distribution characteristics of the 2 m temperature forecast errors of EC...
The presence of road ice has always been a key issue during winter months. A reliable forecast system capable of predicting the Land Surface Temperature (LST) and, consequently, its formation is one of the best strategies to operate towards reducing...
In this study, an improved method named spatial disaggregation and detrended bias correction (SDDBC) based on spatial disaggregation and bias correction (SDBC) combined with trend correction was proposed. Using data from meteorological stations over...
Achieving high-performance numerical weather prediction (NWP) is important for people’s livelihoods and for socioeconomic development. However, NWP is obtained by solving differential equations with globally observed data without capturing enou...
Structural health monitoring (SHM) in an electric arc furnace is performed in several ways. It depends on the kind of element or variable to monitor. For instance, the lining of these furnaces is made of refractory materials that can be worn out over...
Due to climate change, extreme temperature events are receiving increased attention. Based on the climate state deviation and threat score (TS), the ability of the Global/Regional Assimilation and Prediction System (GRAPES) ensemble model to forecast...
Accurate short-term forecasts of daily reference evapotranspiration (ET0) are essential for real-time irrigation scheduling. Many models rely on current and historical temperature data to estimate daily ET0. However, easily accessible temperature for...
The accurate forecast of air temperature plays an important role in water resources management, land–atmosphere interaction, and agriculture. However, it is difficult to accurately predict air temperature due to its non-linear and chaotic nature. Sev...
Due to the infeasibility of large-scale electrical energy storage, electricity is generated and consumed simultaneously. Therefore, electricity entities need consumption forecasting systems to plan operations and manage supplies. In addition, accurat...
The article clarifies an approximate variant for calculating the temperature in an inhomogeneous layer cell without a clear boundary under the assumption of significant distance in its center between the upper and lower ends of the silo when heat exc...
In weather forecasting and climate monitoring, daily maximum and minimum air temperatures (TMAX and TMIN) are fundamental for operational and research purposes, from early warning of extreme events to climate change studies. This study provides an in...
Time series forecasting of meteorological variables such as daily temperature has recently drawn considerable attention from researchers to address the limitations of traditional forecasting models. However, a middle-range (e.g., 5–20 days) for...
Globalization and industrialization have significantly disturbed the environmental ecosystem, leading to critical challenges such as global warming, extreme weather events, and water scarcity. Forecasting temperature trends is crucial for enhancing t...
In weather forecasting, numerical weather prediction (NWP) that is based on physical models requires proper post-processing before it can be applied to actual operations. Therefore, research on intelligent post-processing algorithms has always been a...
Temperature-oriented long-horizon forecasting requires stable extrapolation of slowly evolving targets in the presence of local fluctuations and instance-level distribution shifts. This paper presents FADLinear, a target-only linear forecasting archi...
It is important to correctly predict the microclimate of a greenhouse for control and crop management purposes. Accurately forecasting temperatures in greenhouses has been a focus of research because internal temperature is one of the most important...
Temperature forecasting has been a consistent research topic owing to its significant effect on daily lives and various industries. However, it is an ever-challenging task because temperature is affected by various climate factors. Research on temper...
Forecasting is defined as the process of estimating the change in uncertain situations. One of the most vital aspects of many applications is temperature forecasting. Using the Daily Delhi Climate Dataset, we utilize time series forecasting technique...
Surface air temperature is a comprehensive function of aerosols in the atmosphere and various weather factors. However, there is no real-time aerosol concentration feedback in most operational numerical weather prediction (NWP) models. This raises a...
Forecasts on transportation meteorology, such as pavement temperature, are becoming increasingly important in the face of global warming and frequent disruptions from extreme weather and climate events. In this study, we propose a pavement temperatur...
Temperature control and its prediction has turned into a research challenge for the knowledge of the planet and its effects on different human activities and this will assure, in conjunction with energy efficiency, a sustainable development reducing...
The smart building concept aims to use smart technology to reduce energy consumption, as well as to improve comfort conditions and users’ satisfaction. It is based on the use of smart sensors and software to follow both outdoor and indoor conditions...
In some hydrological systems, mitigation strategies are applied based on short-range water temperature forecasts to reduce stress caused to aquatic organisms. While various uncertainty sources are known to affect thermal modeling, their impact on wat...
Accurate, high-resolution gridded air temperature forecasts are essential, particularly in mountainous areas with complex terrain. This study proposes a two-stage processing framework DOWN + BC to downscale Global Forecast System (GFS) temperature fo...
Accurate dynamic liquid-level monitoring in rod-pumped oil wells requires not only reliable identification of the gas–liquid interface from distributed sensing data but also stable forecasting over extended horizons. This study develops a physi...
Accurate multi-horizon forecasting of greenhouse air temperature is essential for sensor-based environmental monitoring and control-oriented decision support. However, conventional evaluation methods often rely on open-loop or semi-closed-loop settin...
Ultra-short-term electrical load forecasting is an important guarantee for the safety and efficiency of energy system operation. Temperature is also an important factor affecting the changes in electric load. However, in different cases, the impact o...
System reliability, which is essential for the normal operation of satellites in orbit, is decisively governed by the performance of solar array, making accurate temperature forecasting of solar array imperative. Reliable solar array temperature fore...
The integration of photovoltaic (PV) systems into the global energy landscape has been boosted in recent years, driven by environmental concerns and research into renewable energy sources. The accurate prediction of temperature and solar irradiance i...
Accurate temperature prediction is essential for understanding climate variability and hydrological extremes. In this context, Long Short-Term Memory (LSTM) networks have become a widely adopted tool for temperature forecasting; however, their perfor...
Accurate temperature forecasting is critical for various sectors, yet traditional methods struggle with complex atmospheric dynamics. Deep neural networks (DNNs), especially transformer-based DNNs, offer potential advantages, but face challenges with...
The accurate temperature forecasting system provides essential benefits for managing outdoor activities, controlling electricity consumption, and ensuring public health and safety in areas with extreme heat. The researchers developed a hybrid Long Sh...
Efforts to understand the influence of historical climate change, at global and regional levels, have been increasing over the past decade. In particular, the estimates of air temperatures have been considered as a key factor in climate impact studie...
Accurate electricity demand forecasting for a short horizon is very important for day-to-day control, scheduling, operation, planning, and stability of the power system. The main factors that affect the forecasting accuracy are deterministic variable...
The bearing temperature forecasting provide can provide early detection of the gearbox operating status of wind turbines. To achieve high precision and reliable performance in bearing temperature forecasting, a novel hybrid model is proposed in the p...
Temperature is widely known as one of the most important drivers to forecast electricity and gas variables, such as the load. Because of that reason, temperature forecasting is and has been for years of great interest for energy forecasters and sever...
The big data from various sensors installed on-board for monitoring the status of ship devices is very critical for improving the efficiency and safety of ship operations and reducing the cost of operation and maintenance. However, how to utilize the...
Steelmaking has been experiencing continuous challenges and advances concerning process methods and control models. Integrated steelmaking begins with the hot metal, a crude liquid iron that is produced in the blast furnace (BF). The hot metal is the...
The Artificial Hummingbird Algorithm (AHA) is a recent swarm intelligence optimizer with a simple structure and few control parameters. However, it still faces limitations in search regulation, population diversity maintenance, and late-stage exploit...
In this study, an improved version of the outlier robust extreme learning machine (IORELM) is introduced as a new method for multi-step-ahead hourly air temperature forecasting. The proposed method was calibrated and used to estimate the hourly air t...
Biosphere–atmosphere interactions are a critical component of the Earth’s climate system. Many of these interactions are currently contributing to temperature increases and accelerating global warming. One of the main factors responsible...
The axle temperature is an index factor of the train operating conditions. The axle temperature forecasting technology is very meaningful in condition monitoring and fault diagnosis to realize early warning and to prevent accidents. In this study, a...
With growing concerns over climate change, accurately predicting temperature trends is crucial for informed decision-making and policy development. In this study, we perform a comprehensive comparative analysis of four advanced time series forecastin...
Regional rapid forecasting of vertical ocean temperature profiles is increasingly important for marine aquaculture, as these profiles directly affect habitat management and the physiological responses of farmed species. However, observational tempera...
Road surface icing is a major cause of skid-related winter accidents, making preemptive maintenance essential. Current decisions rely mainly on regional weather information, which cannot capture how road surface temperature (RST) varies between secti...
of 67