Sensitivity of global solar irradiance to transposition models: Assessing risks associated with model discrepancies by Yasser F. Nassar, Hala J. El-Khozondar, Mohamed M. Khaleel, Abdussalam A. Ahmed, Abdulgader H. Alsharif, Monaem Elmnifi, Mark Amoah Nyasapoh

“…Global and sky-diffuse horizontal irradiances are measured by meteorological stations and satellites. Global horizontal solar irradiance is converted into a global tilted solar irradiance using transposition models (TMs). …”
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HVSR Analysis of Rockslide Seismic Signals to Assess the Subsoil Conditions and the Site Seismic Response by Alessia Lotti, Veronica Pazzi, Gilberto Saccorotti, Andrea Fiaschi, Luca Matassoni, Giovanni Gigli

“…The available data allowed an extensive comparison between seismic signals, displacement, and meteorological information. The measured displacements are well correlated with the precipitation trend, but unfortunately no resemblance with the seismic data was observed. …”
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Long-Term Statistical Analysis of Severe Weather and Climate Events in Greece by Vassiliki Kotroni, Antonis Bezes, Stavros Dafis, Dimitra Founda, Elisavet Galanaki, Christos Giannaros, Theodore Giannaros, Athanasios Karagiannidis, Ioannis Koletsis, George Kyros, Konstantinos Lagouvardos, Katerina Papagiannaki, Georgios Papavasileiou

“…This paper analyzes severe weather events and trends in Greece from 2010 to 2023, leveraging data from an expanded network of weather stations spanning across Greece, as well as long-term meteorological data from the reference weather station in the center of Athens. …”
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Multi-Scale Building Load Forecasting Without Relying on Weather Forecast Data: A Temporal Convolutional Network, Long Short-Term Memory Network, and Self-Attention Mechanism Appro... by Lanqian Yang, Jinmin Guo, Huili Tian, Min Liu, Chang Huang, Yang Cai

“…Under the condition of lacking meteorological forecast data, this paper proposes to utilize a temporal convolutional network (TCN) to extract the coupled spatial features among multivariate loads. …”
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Analysis of heating degree day requirments changes under climate change in South Khorasan by hossein Imani pour, abdolreza Kashki, mokhtar Karami

“…For this purpose, daily data from the minimum and maximum temperature of 11 stations of the South Khorasan province were received from the Meteorological Organization of Iran during the period of 1990-2015. …”
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Improving the Forecast Accuracy of PM_2.5 Using SETAR-Tree Method: Case Study in Jakarta, Indonesia by Dinda Ayu Safira, Heri Kuswanto, Muhammad Ahsan

“…The results showed that: (1) SETAR-Tree outperformed LSTM, achieving lower RMSE (0.1691 in-sample, 0.2159 out-sample) and MAPE (2.83% in-sample, 2.98% out-sample) compared to LSTM’s RMSE (0.2038 in-sample, 0.2399 out-sample) and MAPE (3.48% in-sample, 4.05% out-sample); (2) SETAR-Tree demonstrated better responsiveness to sudden regime changes, capturing complex pollution patterns influenced by meteorological and anthropogenic factors; (3) PM_2.5 in Jakarta often exceeds the WHO limits, highlighting this study’s importance in supporting strategic planning and providing an early warning system to reduce outdoor activity during extreme pollution.…”
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Multivariate analysis of long-term climate data in connection with yield, earliness and the problem of global warming by V. M. Efimov, D. V. Rechkin, N. P. Goncharov

“…This article presents the results of a multivariate analysis of meteorological extremes which caused crop failures in Eastern and Western Europe in last 2600 years according to chronicle data and paleoreconstructions as well as reconstructions of heliophysical data for the last 9000 years. …”
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Sensitivity of physical parameterization of WRF model in urban climate simulation and Heat Island mitigation in a stable atmospheric condition (case study: Tehran and Alborz provin... by fahimeh shakeri, gholamabbas Fallah ghalhari, hashem akbari, zahra hejazizadeh

“…In this research, the sensitivity of the meteorological elements (such as mean temperature, relative humidity and wind speed) to different physical parameterizations in the numerical forecast model (WRF) was evaluated to simulate the climate of the city and adjust the Urban Heat Island of the study area.To study urban environmental issues, the Urban Canopy Model (UCM) was coupled to the WRF model. …”
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Multi-Sensor Instrument for Aerosol In Situ Measurements by Ilya Bruchkouski, Artur Szkop, Jakub Wink, Justyna Szymkowska, Aleksander Pietruczuk

“…This assessment was supported by simultaneous measurements from two reference instruments (APS 3321 and SMP S3082), along with auxiliary observations from a ceilometer and meteorological station. To enhance particle transmission efficiency to the IAMU sensors, aerodynamic modeling of the inlet pipes was performed, accounting for particle density and diameter. …”
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Forest fire risk assessment model optimized by stochastic average gradient descent by Zexin Fu, Adu Gong, Jinhong Wan, Wanru Ba, Haihan Wang, Jiaming Zhang

“…The model is based on the Regional Disaster System Theory (RDST), and incorporates 11 indicators of meteorological, vegetation, and human activity factors from the aspects of hazard-formative factor, hazard-formative environment, and hazard-affected body, and achieves a prediction accuracy of 94.38% and a coefficient of determination of 0.9581 when compared with historical data and the Global Fire Weather Index (FWI). …”
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Study of air pollution of Isfahan based on NO2 measured data by OMI Satellite sensor by Atefeh Shahmohammadi, Ali Bayat, Saeed mashhadizadeh Maleki

“…In this paper, daily data of nitrogen dioxide from Ozone Monitoring Instrument (OMI) satellite sensor, wind and surface temperature of Isfahan Meteorological Station data were used between October 2004 and May 2016. …”
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Paradigm Shift in Typhoon Forecasting for the Korean Peninsula: A Case Study on the Applicability of the Typhoon-Ready System by Hana Na, Woo-Sik Jung

“…The TRS framework incorporates indices, such as the Strong Wind Index (SWI), Heavy Rainfall Index (HRI), Storm Surge Index (SSI), and Air Quality Index (AQI), effectively combining meteorological modeling with vulnerability analysis. Results demonstrate that the TRS outperforms traditional systems by accurately identifying high-risk zones and correlating them with observed damage patterns. …”
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The effects and the macroeconomic dynamics of natural disaster damages: investigation of local evidence by Agim Kukeli

“…This study investigates the macroeconomic consequences of natural disasters in southeast Texas, a region frequently distressed by meteorological and hydrological events. By concentrating on a county-level analysis, we methodically assess the impacts of natural disaster damages on key economic indicators: aggregate personal income, aggregate wages, wages per worker, aggregate employment and aggregate income transfers over the period 1990–2019. …”
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Analyzing precipitation trends in the Cholistan Desert, Pakistan: A statistical and GIS-based study by Haider Shamsheir, Haq Fazlul, Mark Bryan G.

“…Using data from five meteorological stations, we applied a combination of Geographic Information System (GIS) techniques and statistical analyses to assess both seasonal fluctuations and annual trends in precipitation. …”
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Development potential of multi-cropping systems and its influence on agricultural water consumption in the Huang–Huai–Hai River Basin of China by Linghui Li, Qingming Wang, Yong Zhao, Jiaqi Zhai, Haihong Li, Shuying Han, Lichuan Wang, Yunpeng Gui

“…This study analyzed the spatial-temporal changes of the actual and potential CS based on the remote sensing and meteorological dataset from 2001 to 2022 to explore the development potentiality of multi-cropping systems (MCS), and adapted the CS change into the Decision Support System for Agrotechnology Transfer model (DSSAT) to simulate the change of evapotranspiration. …”
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Elevation of natural vulnerability in the karst aquifers (case study: karst aquifers of Sheshpier and Borgan, Fars province) by Mehdi kashefi, mojgan entezari, maryam Jafari Aghdam

“…To prepare a natural vulnerability map are used geological maps, soil, vegetation, digital elevation model (10 meter) and precipitation statistics of meteorological stations and vulnerability map is evaluated as three factors of C, O, p. …”
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Cultivating clean skies: unveiling the tapestry of air quality in Gujarat through innovative machine learning analysis by Gaddam Advitha, Allada Nagasai Varaprasad, Koti Vennela Khushi, Pullabhotla Vijay, Sukanta Nayak

“…Furthermore, the study sheds light on the significant impact of meteorological factors, especially maximum temperature, on AQI fluctuations, necessitating adaptive strategies to counteract climate change's repercussions on air quality.…”
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Forecasting Average Daily Temperature in the Khorasan Razavi Province by sayyed mohamad Hosseini, Abdolhossein Adelzadeh

“…The maximum and minimum of these stations in the time interval from 01/01/1987 to 01/01/2014 equal as 9862 days from the meteorological organization of Iran. Then, was calculated the correlation of the average daily temperature of selected stations with high atmospheric data (500 HPa level) with the northern hemisphere in Surfer Software. …”
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Drought Occurrence Pattern in Tigray Region, Northern Ethiopia by A.S. Tefera, J.O. Ayoade, N.J. Bello

“…In doing so, monthly climate data collected on selected stations, from the Dutch national weather service known as the Royal Netherlands Meteorological Institute (KNMI), was used to assess the drought trends and characterize the study area in terms of drought duration, severity, intensity, frequency, spatial extent as well as drought trend. …”
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A Machine Learning Approach for Environmental Assessment on Air Quality and Mitigation Strategy by Chetan Shetty, S. Seema, B. J. Sowmya, Rajesh Nandalike, S. Supreeth, Dayananda P., Rohith S., Vishwanath Y., Rajeev Ranjan, Venugopal Goud

“…Predicting air pollution is a complex task due to various challenges associated with the dynamic and multifaceted nature of the atmosphere such as meteorological variability, local emissions and sources, data quality and availability, and emerging pollutants. …”
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