Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France by A. Demortier, M. Mandement, V. Pourret, O. Caumont, O. Caumont

“…<p>Personal weather station (PWS) networks owned by citizens now provide near-surface observations at a spatial density unattainable with standard weather stations (SWSs) deployed by national meteorological services. This article aims to assess the benefits of assimilating PWS observations of screen-level temperature and relative humidity in the AROME-France model in the same framework of experiments carried out to assimilate PWS observations of surface pressure in a previous work. …”
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The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County by ALI hashemi, Hojjatollah Yazdanpanah, Mehdi Momeni

“…Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). …”
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Evaluating different drought products for assessing drought and implications on agriculture in Nepal by Shishir Chaulagain, Manoj Lamichhane, Urusha Chaulagain, Sushant Gyawali, Sadina Shrestha, Vishnu Prasad Pandey

“…By utilizing Soil Water Deficit Index (SWDI) alongside Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Flow Index (SFI), this research highlights the complex progression from meteorological to agricultural and hydrological droughts. …”
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Predicting turbidity dynamics in small reservoirs in central Kenya using remote sensing and machine learning by Stefanie Steinbach, Anna Bartels, Andreas Rienow, Bartholomew Thiong’o Kuria, Sander Jaap Zwart, Andrew Nelson

“…Random forest and gradient boosting models showed that annual turbidity outcomes depend on meteorological variables, topography, and land cover (R2 = 0.46 and 0.43 respectively), while longer-term turbidity was influenced more strongly by land management and land cover (R2 = 0.88 and 0.72 respectively). …”
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Apply a deep learning hybrid model optimized by an Improved Chimp Optimization Algorithm in PM2.5 prediction by Ming Wei, Xiaopeng Du

“…First, the Random Forest (RF) model is utilized to evaluate the importance of air pollution and meteorological features and select more suitable input features. …”
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Interval Prediction of Photovoltaic Power Using Improved NARX Network and Density Peak Clustering Based on Kernel Mahalanobis Distance by Wen-He Chen, Long-Sheng Cheng, Zhi-Peng Chang, Han-Ting Zhou, Qi-Feng Yao, Zhai-Ming Peng, Li-Qun Fu, Zong-Xiang Chen

“…Second, density peak clustering improved by kernel Mahalanobis distance (KMDDPC) is applied to classify the dataset into multiple clusters, including forecasting error and meteorological factors. Finally, the joint probability density is established by multivariate kernel density estimation (MKDE) to accomplish the PV power interval prediction. …”
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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…The proposed method has been contrasted with conventional methods by applying a testing environment incorporating essential Meteorological Factors (MF) and historical SE datasets. …”
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Assessing the Impact of Traffic Emissions on Fine Particulate Matter and Carbon Monoxide Levels in Hanoi through COVID-19 Social Distancing Periods by Nhung H. Le, Bich-Thuy Ly, Phong K. Thai, Gia-Huy Pham, Ich-Hung Ngo, Van-Nguyet Do, Thuy T. Le, Luan V. Nhu, Ha Dang Son, Yen-Lien T. Nguyen, Duong H. Pham, Tuan V. Vu

“…It is known that meteorological conditions can have significant effects on the ambient levels of air pollutants. …”
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Operational Forecasting of Wind Speed for an Self-Contained Power Assembly of a Traction Substation by P. V. Matrenin, A. I. Khalyasmaa, A. G. Rusina, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski

“…It is shown that in order to ensure high accuracy and stability of the neural network model of wind speed forecasting, long-term meteorological observations data are required.…”
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Vulnerability of Agrobiodiversity and Agroforestry Settings to Climate Change in Gedeo Zone, Ethiopia by Fikadu Erenso, Azene Andemo

“…Therefore, crop survey both from the home garden and crop field, the last 30 years’ data from five meteorological stations located in the district and the past 30 years’ Landsat satellite images at a 10-year interval within the same season was used. …”
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Impact of sand and dust storms on mortality in Jinan City, China by Chaofan Shen, Mingjun Li, Qingchang Wang, Jinjiao Luan, Jiliang Si, Liangliang Cui

“…The insufficient evidence on SDS hampers effective measures to mitigate its harm.ObjectiveTo reveal the mortality risks associated with SDSs in Jinan City and identify sensitive populations vulnerable to these events.MethodsFor this time-stratified case-crossover study, we collected daily data on all-cause, circulatory, and respiratory deaths, as well as air pollution and meteorological information from Jinan City in China between January 1, 2013, and November 30, 2022. …”
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Determining the Natural Disaster Diversity of Van Province by Fine Kinney Risk Assessment Method (FK-RAM) by Bülent Matpay, Sacit Mutlu

“…It is calculated that the southwestern and northwestern parts of Van province have "Very high risk" and "High risk" in terms of landslides, avalanches and rock falls due to its highly sloping topographical structure and meteorological conditions. Morphologically, it was calculated that the slopes where the slope decreases, at the mouths of the tributaries connected to the main tributaries and towards the valley floors carry a "High risk" of flooding. …”
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Water Accounting and Productivity Analysis to Improve Water Savings of Nile River Basin, East Africa: From Accountability to Sustainability by Hirwa, Hubert, Zhang, Qiuying, Li, Fadong, Qiao, Yunfeng, Measho, Simon, Muhirwa, Fabien, Xu, Ning, Tian, Chao, Cheng, Hefa, Chen, Gang, Ngwijabagabo, Hyacinthe, Turyasingura, Benson, Itangishaka, Auguste Cesar

“…This study aims to evaluate the contributions of hydro meteorological factors to the changes of WA and CWP and subsequent WUE based on the data from 2009–2020 in the Nile River Basin (NRB), East Africa (EA). …”
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Persistence of Soil Enthalpy Drives the Winter and Summer Climate Connection in the Tibetan Plateau by Zouxing Lin, Zhiyan Zuo, Renhe Zhang, Dong Xiao, Qinglong You, Liang Qiao

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Winter is (not) coming: Acoustic monitoring and temperature variation across important bat hibernacula by Nia Toshkova, Maksim Kolev, Stanimira Deleva, Tzvetan Simeonov, Vasil Popov

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A regional site response analysis of the Petobo area after the 2018.09.28 Palu–Donggala Indonesia earthquake using an equivalent-linear model by Rini Kusumawardani, Muhsiung Chang, Togani Cahyadi Upomo, Fernando Lopez-Caballero, Dadang Permana

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Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates by Haider Ali, Hayley J. Fowler, David Pritchard, Geert Lenderink, Stephen Blenkinsop, Elizabeth Lewis

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Simulation of the Hydrological Components of Dez River Basin by the classification of Land Use Categories Using SUFI-2 Algorithm by Elaheh Asgari, Mohammad Baaghideh, Majid Hosseini, Alireza Entezari, Asghar Kamyar

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Review of climate-resilient agriculture for ensuring food security: Sustainability opportunities and challenges of India by Satiprasad Sahoo, Chiranjit Singha, Ajit Govind, Armin Moghimi

“…Climate Resilient Agriculture (CRA) effectively responds to climate change while contributing to sustainable productivity adapted to local hydro-meteorological conditions. CRA provides resilience to climate variability by enhancing agricultural viability through water exchange between surface and groundwater systems. …”
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CM SAF Oransal Bulut Kapalılığı (CFC) Verisinin Başarımı ve Doğu Anadolu Gözlemevi (DAG) Yerleşkesi için Analizi by Cahit Yeşilyaprak, Kazım Kaba

“…EUMETSAT’ın (European Organisation for the Exploitation of Meteorological Satellites; Avrupa Birliği Meteorolojik Uydu İşletme Teşkilatı) denetim ve koordinasyonunda olan CM SAF (Satellite Application Facility on Climate Monitoring; İklim Yönetimi Üzerine Uydu Uygulama Birimi), METEOSAT verilerinden iklimsel çalışmalar için atmosferimize ait çeşitli veri setleri üretmektedir. …”
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