The Impact of Climate Change on Temperature and Precipitation in Afghanistan with Emphasis on the Helmand and Hariroud Basins by Somayeh Parsa, Azar Zarrin, Abbas Mofidi, Abbasali Dadashi-Roudbari

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Multi-view adversarial attack defending method for host intrusion detection by WANG Fei, QIAN Kehan, LYU Mingqi, ZHU Tiantian, CHEN Honglong

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Seasonal hydrologic responses to climate change based on a CMIP6 multi-model ensemble: A case study of An-Seong watershed in South Korea by Soyoung Woo, Wonjin Kim, Sun Woo Chang, Il-Moon Chung

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Assessment of extreme climate stress across China’s maize harvest region in CMIP6 simulations by Xinmin Chen, Zexu Shi, Dengpan Xiao, Dengpan Xiao, Yang Lu, Yang Lu, Huizi Bai, Man Zhang, Man Zhang, Dandan Ren, Yongqing Qi, Shikai Song, Shikai Song

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A Multi‐Model Ensemble of Baseline and Process‐Based Models Improves the Predictive Skill of Near‐Term Lake Forecasts by Freya Olsson, Tadhg N. Moore, Cayelan C. Carey, Adrienne Breef‐Pilz, R. Quinn Thomas

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Heavy Precipitation Forecasts Based on Multi-model Ensemble Members by Zhi Xiefei, Zhao Chen

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Projected future changes in extreme climate indices affecting rice production in China using a multi-model ensemble of CMIP6 projections by Xinmin Chen, Dengpan Xiao, Dengpan Xiao, Yongqing Qi, Yongqing Qi, Zexu Shi, Huizi Bai, Yang Lu, Yang Lu, Man Zhang, Man Zhang, Peipei Pan, Peipei Pan, Dandan Ren, Xiaomeng Yin, Xiaomeng Yin, Renjie Li, Renjie Li

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Spatiotemporal squeeze-and-excitation residual multiplier network for video action recognition by Huilan LUO, Kang TONG

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Extreme precipitation simulation capability of CMIP6 models and their future spatiotemporal evolution: Case study in Poyang Lake Basin, China by Yinxin Ge, Shanghong Zhang, Weiyi Zhou, Linyang Zhao, Qingqing Fang

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A multi model ensemble reveals net climate benefits from regenerative practices in US Midwest croplands by Bruno Basso, Tommaso Tadiello, Neville Millar, G. Philip Robertson, Keith Paustian, Fidel S. Maureira, Susana Albarenque, Brian Baer, Lydia Price, Prateek Sharma, Chris Villalobos, Ames Fowler, Mathieu Delandmeter, Marco Acutis, Sotirios Archontoulis, Kristofer R. Covey, Luca Doro, Benjamin Dumont, Peter R. Grace, Gerrit Hoogenboom, James W. Jones, Alessia Perego, Alexander Ruane, Claudio O. Stöckle, Yao Zhang

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Increased Extreme Precipitation in Western North America from Cut-Off Lows Under a Warming Climate by Henri Pinheiro, Tercio Ambrizzi, Kevin Hodges

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Multi-Model Ensemble Enhances the Spatiotemporal Comprehensive Performance of Regional Climate in China by Yan Wang, Yan-Jun Shen, Leibin Wang, Ying Guo, Yuanyuan Cheng, Xiaolong Zhang

Subjects: “…multi-model ensemble schemes…”
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Multi-model ensemble machine learning-based downscaling and projection of GRACE data reveals groundwater decline in Saudi Arabia throughout the 21st century by Arfan Arshad, Muhammad Shafeeque, Thanh Nhan Duc Tran, Ali Mirchi, Zaichen Xiang, Cenlin He, Amir AghaKouchak, Jessica Besnier, Md Masudur Rahman

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The enhanced integration of proven techniques to quantify the uncertainty of forecasting extreme flood events based on numerical weather prediction models by Mitra Tanhapour, Jaber Soltani, Hadi Shakibian, Bahram Malekmohammadi, Kamila Hlavcova, Silvia Kohnova, Peter Valent

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Reinforcement learning-based multi-model ensemble for ocean waves forecasting by Weinan Huang, Xiangrong Wu, Xiangrong Wu, Haofeng Xia, Haofeng Xia, Haofeng Xia, Xiaowen Zhu, Yijie Gong, Xuehai Sun

Subjects: “…multi-model ensemble…”
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Combining a Multi‐Lake Model Ensemble and a Multi‐Domain CORDEX Climate Data Ensemble for Assessing Climate Change Impacts on Lake Sevan by Muhammed Shikhani, Johannes Feldbauer, Robert Ladwig, Daniel Mercado‐Bettín, Tadhg N. Moore, Artur Gevorgyan, Amalya Misakyan, Chenxi Mi, Martin Schultze, Bertram Boehrer, Tom Shatwell, Klemens Barfus, Karsten Rinke

Subjects: “…multi model ensemble (MME)…”
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Why Do DJF 2023/24 Upper‐Level 200‐hPa Geopotential Height Forecasts Look Different From the Expected El Niño Response? by Mingyue Chen, Arun Kumar, Michelle L’Heureux, Peitao Peng, Tao Zhang, Martin P. Hoerling, Henry F. Diaz

Subjects: “…multi‐model ensemble mean…”
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From Many to One: Consensus Inference in a MIP by Noel Cressie, Michael Bertolacci, Andrew Zammit‐Mangion

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