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  1. 1641

    Study on Hydrological Prediction of Qingshui River Basin Based on PRECIS Regional Climate Model by MA Wenjing, PAN Zhangrong, LIU Zhenlu

    Published 2023-01-01
    “…Frequent occurrences of extreme weather will lead to unstable changes in rivers' hydrological conditions.The SWAT hydrological model is used to simulate and verify the runoff at the Quanyanshan hydrometric station in Qingshui River,and then the runoff change at the Quanyanshan station in the Qingshui River Basin by the middle and end of the 21st century is simulated based on the PRECIS regional climate model.The results show that by the middle and end of the 21st century,with the increase in temperature and the decrease in rainfall,the runoff volume of the Qingshui River will drop.Specifically,by the middle of the 21st century,the simulated runoff volumes are basically the same under two scenarios.However,by the end of the 21st century,the simulated runoff volume is larger than that under the SSP4.5 scenario due to the higher predicted rainfall under the SSP8.5 scenario.…”
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  2. 1642

    Aural Myiasis, a Rare Cause of Earache by Ibrahim Al Jabr

    Published 2015-01-01
    “…It is more common to occur in tropical regions, where humidity and warm weather provide a good environment for this infestation. …”
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  3. 1643

    Climate Forecast and Decision Making in Agriculture by Clyde Fraisse, David Zierden, Norman Breuer, John Jackson, Jr., Charles Brown

    Published 2004-08-01
    “…Often the decisions are made based on some type of forecast, such as price, weather, or climate. This document is ABE 352, one of a series of the Agricultural and Biological Engineering Department, Florida Cooperative Extension Service, Institute of Food and Sciences, University of Florida. …”
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  4. 1644

    Bridging gaps: Integrating gender into climate-responsive Disaster Risk Management by Virginia Murray

    Published 2025-01-01
    “…Climate change sets a new challenge for disaster risk management as it increases the frequency and severity of extreme weather events, disproportionately impacting vulnerable and marginalized communities. …”
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  5. 1645

    Aplicabilidad del Pronóstico de Variabilidad Climática Estacional: El Manejo de Riesgos en la Producción del Tomate en el sur del Estado de Florida by Norman Breuer, Clyde Fraisse, Gene McAvoy, David Letson

    Published 2010-05-01
    “…It describes the difference between weather and climate, suggests climate-based management options available to tomato growers, and discusses economic and risk management implications of seasonal climate variability for tomato producers and extensionists in South Florida. …”
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  6. 1646

    What Is the ENSO Climatology Tool? by Caroline Staub, Clyde W. Fraisse, Eduardo Gelcer, Daniel R. Dourte

    Published 2017-09-01
    “… On a global scale, periodic anomalies in sea surface temperatures coupled with shifts in atmospheric pressure and winds, such as those associated with the El Niño Southern Oscillation (ENSO), can have profound impacts on weather conditions. ENSO affects atmospheric circulation patterns well into the midlatitudes and is the leading driver of seasonal climate variability in the United States. …”
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  7. 1647

    FEN-MRMGCN: A Frontend-Enhanced Network Based on Multi-Relational Modeling GCN for Bus Arrival Time Prediction by Ting Qiu, Chan-Tong Lam, Bowie Liu, Benjamin K. Ng, Xiaochen Yuan, Sio Kei Im

    Published 2025-01-01
    “…Our approach effectively combines external factors, such as traffic congestion and weather conditions, particularly in dense bus route areas, thereby significantly enhancing bus arrival time prediction accuracy. …”
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  8. 1648

    Effect of Forest Management Types on Soil Carbon Stocks in Montane Forests: A Case Study of Eastern Mau Forest in Kenya by George K. Tarus, Stanley W. Nadir

    Published 2020-01-01
    “…The results indicated that there were no significant differences in the carbon stocks among the forest management types (F4,16 = 0.61, P=0.613). However, seasonal weather changes significantly affected the amount of carbon stocks among the forest management types (F4,16 = 0.61, P>0.05). …”
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  9. 1649

    Comprehensive approach to predictive analysis and anomaly detection for road crash fatalities by Chopparapu Gowthami, S. Kavitha

    Published 2025-01-01
    “…Finding high-risk areas and creating focused interventions to increase road safety are made possible by the research’s analysis of numerous variables that affect the number of fatalities in traffic crashes, including weather, road features, and geographic locations. …”
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  10. 1650

    Identifying the pedoclimatic conditions most critical in the susceptibility of a grapevine cultivar to esca disease by Valérie Hofstetter, Vinciane Monod, Matthieu Wilhelm, Olivier Viret, Katia Gindro, Daniel Croll, Vivian Zufferey

    Published 2025-01-01
    “…We compared these data with climatic data obtained from weather stations for these same plots for four years and over the long term. …”
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  11. 1651

    Design and simulation of a 5 KW solar-powered hybrid electric vehicle charging station with a ANN–Kalman filter MPPT and MPC-based inverter control for reduced THD by Youness Hakam, Hajar Ahessab, Ahmed Gaga, Mohamed Tabaa, Benachir El Hadadi

    Published 2025-03-01
    “…Controlled by Texas Instruments’ TMS320F28379D digital signal processor, this system offers stable, low-cost EV charging by prioritizing solar energy use, even under harsh weather conditions, over reliance on grid power.…”
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  12. 1652

    The effects of wind farm wakes on freezing sea spray in the mid-Atlantic offshore wind energy areas by D. Rosencrans, D. Rosencrans, J. K. Lundquist, J. K. Lundquist, J. K. Lundquist, M. Optis, M. Optis, N. Bodini

    Published 2025-01-01
    “…Thus, it is crucial to understand the icing hazard across the mid-Atlantic. We analyze Weather Research and Forecasting model numerical weather prediction simulations at a coarse temporal resolution over a 21-year period to assess freezing sea spray (FSS) events over the long-term record and at finer granularity over the 2019–2020 winter season to identify the post-construction turbine impacts. …”
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  13. 1653

    Learning from wildfires: A scalable framework to evaluate treatment effects on burn severity by Caden P. Chamberlain, Garrett W. Meigs, Derek J. Churchill, Jonathan T. Kane, Astrid Sanna, James S. Begley, Susan J. Prichard, Maureen C. Kennedy, Craig Bienz, Ryan D. Haugo, Annie C. Smith, Van R. Kane, C. Alina Cansler

    Published 2024-12-01
    “…In contrast, thinning‐only treatments only produced low/moderate‐severity effects under the more moderate fire weather conditions in the Schneider Springs Fire. …”
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  14. 1654

    On the measurement of microclimate by Ilya M. D. Maclean, James P. Duffy, Stef Haesen, Sanne Govaert, Pieter De Frenne, Thomas Vanneste, Jonathan Lenoir, Jonas J. Lembrechts, Marcus W. Rhodes, Koenraad Van Meerbeek

    Published 2021-08-01
    “…Abstract Many organisms live in environments in which temperatures differ substantially from those measured by standard weather stations. The last decade has witnessed a paradigm shift in efforts to quantify these differences and to understand their ecological, functional and evolutionary implications. …”
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  15. 1655

    Wildfire danger under changing climates in the southern Great Plains throughout the 21st century by Shanmin Fang, Jia Yang, Chris B. Zou, Erik S. Krueger, Tyson E. Ochsner, Quan Zhang

    Published 2025-01-01
    “…While it is expected that future climate change will affect wildfire danger levels by altering fire weather and fuel conditions, there remains a significant gap in understanding how these changes will manifest in the SGP. …”
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  16. 1656
  17. 1657

    Retrieval of Land Surface Temperature From Passive Microwave Observations Using CatBoost-Based Adaptive Feature Selection by Yang Dai, Yingbao Yang, Xin Pan, Penghua Hu, Xiangjin Meng, Fanggang Li, Zhenwei Wang

    Published 2025-01-01
    “…Passive microwave (PMW) remote sensing is increasingly employed for generating seamless all-weather land surface temperature (LST) data due to its ability to penetrate cloud cover and capture the actual surface conditions underneath. …”
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  18. 1658
  19. 1659
  20. 1660

    A machine learning and clustering-based approach for county-level COVID-19 analysis. by Charles Nicholson, Lex Beattie, Matthew Beattie, Talayeh Razzaghi, Sixia Chen

    Published 2022-01-01
    “…This paper employs both supervised and unsupervised methods to identify the critical county-level demographic, mobility, weather, medical capacity, and health related county-level factors for studying COVID-19 propagation prior to the widespread availability of a vaccine. …”
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