Exploring district heating systems: A SCADA dataset for enhanced explainabilityMendeley Data by Stevica Cvetković, Milan Zdravković, Marko Ignjatović

“…Spanning a period of up to five years (2019–2024), the dataset originates from a SCADA system, capturing critical parameters such as heating fluid temperatures in the supply and return lines of both primary and secondary flows, energy transmission measurements, and outdoor temperatures from a local meteorological station. All measured data underwent comprehensive pre-processing using established methodologies, resulting in uniformly spaced hourly data free of errors or missing values. …”
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WIND ENERGY EVALUATION AND TURBINE IDENTIFICATION FOR POWER GENERATION IN SOME SELECTED AREAS IN NIGERIA by MUSEDIQ ADEDOYIN SULAIMAN, IGNATIUS KEMA OKAKWU, AKINTUNDE SAMSON ALAYANDE, OLAKUNLE ELIJAH OLABODE, AUGUSTUS EHIREMEN IBHAZE

“…The data used are obtained from Nigeria Meteorological Agency (NIMET) between the durations of 11 and 54 years, measured at an anemometer height of 10m. …”
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Vulnérabilité de la population face aux fortes chaleurs dans l’agglomération de Kairouan (Tunisie centrale) by Mohamed Chebli, Salem Dahech, Sami Charfi

“…At first, this paper shows, the characteristics of hot weather in Kairouan, based on meteorological data (TX and TN) recorded by the city's synoptic station and covering the period 1980-2023. …”
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Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications by Manogaran Madhiarasan, Mohamed Louzazni

“…The performances of the proposed neural network-based forecasting models are analyzed with various hidden neurons and validated using the acquired real-time meteorological data. The proposed neural network forecasting models achieve rigorous results with reduced errors for the considered applications and aid sustainability.…”
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Climate effects on the diversification strategy of export firms: Evidence from China. by Junmei Zhang, Lianying Yao

“…Using export and meteorological data of Chinese firms from 2000 to 2016, the empirical results confirm an inverted U-shaped relationship, implying that extreme temperatures significantly reduce firms' export product diversification. …”
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LPR-MLP: A Novel Health Prediction Model for Transmission Lines in Grid Sensor Networks by Yunliang Chen, Shaoqian Chen, Nian Zhang, Hao Liu, Honglei Jing, Geyong Min

“…The LPR-MLP model consists of two parts: (1) local binary pattern (LBP), principal component analysis (PCA), and ReliefF are used to process image data and meteorological and mechanical data and (2) the multilayer perceptron (MLP) method is then applied to build the prediction model. …”
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Analysis of the Hail Phenomenon in Bistrița-Năsăud County in 2024: Localization, Impact, Perception, and Mitigation by Andras-István BARTA, Irina RABOȘAPCA, Ștefan BILAȘCO, Aurelian Cosmin MOLDOVAN, Tania MIHĂIESCU

“…The research integrates climatological data, meteorological observations, and locally sourced information to evaluate the frequency, localization, and intensity of hail across the region. …”
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The Dependence of Cold and Hot Patches on Local Plasma Transport and Particle Precipitation in Northern Hemisphere Winter by Duan Zhang, Qing‐He Zhang, Y.‐Z. Ma, Kjellmar Oksavik, L. R. Lyons, Zan‐Yang Xing, Marc Hairston, Z.‐X. Deng, J.‐J. Liu

“…Abstract By using a database of 4,634 cold patches (high density and low electron temperature) and 4,700 hot patches (high density and high electron temperature) from Defense Meteorological Satellite Program F16 in 2005–2018 winter months (October–March), we present a statistical survey of the distributions of polar cap patches for different interplanetary magnetic field (IMF) orientations and ionospheric convection geometries. …”
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Impact of the Total Area and Spatial Distribution of Green Infrastructure on the Canopy Urban Heat Island at the Metropolitan Region of São Paulo - A Numerical Study by Stefano Jericó Daminello, Flávia Noronha Dutra Ribeiro

“…Abstract A rapid verticalization to accommodate the citizens of the Metropolitan Region of São Paulo is altering the balance of radiation and atmospheric heat, highlighting the need to understand the impact that green and built infrastructure have on the canopy urban heat island phenomenon. This meteorological phenomenon occurs mainly due to the difference in landscape between urban and rural areas. …”
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Heat transfer software for local materials in Cameroon (HTSLM 1.0): simplified building energy software based on local realities by Lynda Phalone Ndjonnou Tchawa, Lucien Mandeng Mandeng, Joël Durel Tchinang Tchameu, Ramses Tanankem Menkem, Florian Kamsu Kom, Jacques Lionel Ntamag, Joseph Pondi

“…We present how we manage Cameroon’s meteorological data to implement them in LOBATIN/HTSLM 1.0 and we compare our results with pre-existing software such as EnergyPlus. …”
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The impact of temperature on cotton yield and production in Xinjiang, China by Yongyan Zhao, Yumeng Zhu, Shouli Feng, Ting Zhao, Luyao Wang, Zhihong Zheng, Nijiang Ai, Xueying Guan

“…This study analyzes temperature data from 33 meteorological stations in Xinjiang (1981–2020) alongside cotton yield data to assess cold damage during key cotton growth stages. …”
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Temperature and Humidity Prediction Based on Machine Learning by Xiong Yanqi

“…This research highlights the significant potential of machine learning techniques hi enhancing meteorological forecasting, providing valuable insights and tools for improving decision-making in industries heavily influenced by weather conditions.…”
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Evaluation of Technical Aspects of Solar Photovoltaic (PV) Power Installations on Farmland by Lorenzo Sabino, Rafiq Asghar, Fabio Crescimbini, Francesco Riganti Fulginei

“…This research evaluates the technical and economic aspects of solar photovoltaic (PV) power installations on farmland, utilizing a simulation model in MATLAB to forecast annual system output based on nominal power and meteorological data. This study compares various configurations, including single-sided versus double-sided modules and fixed versus tracker structures, to determine their efficiency, losses, and economic viability. …”
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Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method by Tianxiang Yao, Xianghong Lai

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Evaluation of the WRF-Chem performance for the air pollutants over the United Arab Emirates by Y. Yarragunta, D. Francis, R. Fonseca, N. Nelli

“…<p>This study presents a comprehensive evaluation of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) in simulating meteorological parameters and concentrations of air pollutants across the United Arab Emirates (UAE) for June and December 2022, representing the contrasting summer and winter climatic conditions. …”
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Exploring coastal climate adaptation through storylines: Insights from cyclone Idai in Beira, Mozambique by Henrique M.D. Goulart, Panagiotis Athanasiou, Kees van Ginkel, Karin van der Wiel, Gundula Winter, Izidine Pinto, Bart van den Hurk

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Convergence Rate of Numerical Solutions for Nonlinear Stochastic Pantograph Equations with Markovian Switching and Jumps by Zhenyu Lu, Tingya Yang, Yanhan Hu, Junhao Hu

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Trend Analysis Method on Vertical Axis by Yavuz Selim GÜÇLÜ

“…Climate change has accelerated with the significant increase in the amount of greenhouse gases. When the meteorological and hydrological data are examined, the effect of this change is clearly revealed. …”
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Statistical Downscaling for Rainfall Forecasts Using Modified Constructed Analog Method in Thailand by Patchalai Anuchaivong, Dusadee Sukawat, Anirut Luadsong

“…This method is used to forecast the daily rainfall and was received from the Thai Meteorological Department (TMD) from the period during 1979 to 2010 at thirty stations. …”
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Climate change, air pollution and chronic respiratory diseases: understanding risk factors and the need for adaptive strategies by Jiayu Xu, Zekang Su, Chenchen Liu, Yuxuan Nie, Liangliang Cui

“…Results indicated an increased risk of CRD (mainly COPD, asthma) associated with environmental factors, such as air pollutants, adverse meteorological conditions, extreme temperatures, sandstorms, wildfire, and atmospheric allergens. …”
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