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  1. Free, publicly-accessible full text available July 8, 2025
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  4. Digital network twin (DNT) is a promising paradigm to replicate real-world cellular networks toward continual assessment, proactive management, and what-if analysis. Existing discussions have been focusing on using only deep learning techniques to build DNTs, which raises widespread concerns regarding their generalization, explainability, and transparency. In this paper, we explore an alternative approach to augment network simulators with context-aware neural agents. The main challenge lies in the non-trivial simulation-to-reality (sim-to-real) discrepancy between offline simulators and real-world networks. To solve the challenge, we propose a new learn-to-bridge algorithm to cost-efficiently bridge the sim-to-real discrepancy in two alternative stages. In the first stage, we select states to query performances in real-world networks by using newly-designed cost-aware Bayesian optimization. In the second stage, we train the neural agent to learn the state context and bridge the probabilistic discrepancy based on Bayesian neural networks (BNN). In addition, we build a small-scale end-to-end network testbed based on OpenAirInterface RAN and Core with USRP B210 and a smartphone, and replicate the network in Network Simulator 3 (NS-3). The evaluation results show that, our proposed solution substantially outperforms existing methods, with more than 92% reduction in the sim-to-real discrepancy. 
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    Free, publicly-accessible full text available May 20, 2025
  5. The higher‐order turbulence scheme, Cloud Layers Unified by Binormals (CLUBB), is known for effectively simulating the transition from cumulus to stratocumulus clouds within leading atmospheric climate models. This study investigates an underexplored aspect of CLUBB: its capacity to simulate near‐surface winds and the Planetary Boundary Layer (PBL), with a particular focus on its coupling with surface momentum flux. Using the GFDL atmospheric climate model (AM4), we examine two distinct coupling strategies, distinguished by their handling of surface momentum flux during the CLUBB's stability‐driven substepping performed at each atmospheric time step. The static coupling maintains a constant surface momentum flux, while the dynamic coupling adjusts the surface momentum flux at each CLUBB substep based on the CLUBB‐computed zonal and meridional wind speed tendencies. Our 30‐year present‐day climate simulations (1980–2010) show that static coupling overestimates 10‐m wind speeds compared to both control AM4 simulations and reanalysis, particularly over the Southern Ocean (SO) and other midlatitude ocean regions. Conversely, dynamic coupling corrects the static coupling 10‐m winds biases in the midlatitude regions, resulting in CLUBB simulations achieving there an excellent agreement with AM4 simulations. Furthermore, analysis of PBL vertical profiles over the SO reveals that dynamic coupling reduces downward momentum transport, consistent with the found wind‐speed reductions. Instead, near the tropics, dynamic coupling results in minimal changes in near‐surface wind speeds and associated turbulent momentum transport structure. Notably, the wind turning angle serves as a valuable qualitative metric for assessing the impact of changes in surface momentum flux representation on global circulation patterns. 
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    Free, publicly-accessible full text available May 1, 2025
  6. Abstract

    Our study investigates the global impact of midlatitude cyclones on extreme wind speed events in both hemispheres under a warmer climate. Using the latest version of the high-resolution ≈ 50 km grid-spacing atmospheric climate model AM4, developed by the Geophysical Fluid Dynamics Laboratory, we conducted simulations covering the 71-years period 1949–2019 for both the present-day climate and an idealised future global warming climate scenario with a homogeneous Sea Surface Temperature (SST) increase by 2 K. Our findings reveal that extreme near-surface wind speeds increase by up to 3% K−1towards the poles while decrease by a similar amount in the lower midlatitudes. When considering only extreme wind speed events objectively attributed to midlatitude cyclones, we observe a migration by the same amount towards higher latitudes both in percentage per degree SST warming and absolute value. The total number of midlatitude cyclones decreases by roughly 4%, but the proportion of cyclone-associated extreme wind speed events increases by 10% in a warmer climate. Finally, Northwestern Europe, the British Isles, and the West Coast of North America are identified as hot spots with the greatest socio-economic impacts from increased cyclone-associated extreme winds.

     
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