Lightning Prediction in the Tehran Region Using the WRF Model With Multiple Physical Parameterizations and an Ensemble Approach by Sakineh Khansalari, Maryam Gharaylou

“…Comparisons with ENTLN data showed that configurations 1 and 2, using WSM6 and Goddard schemes, achieved the highest Probability of Detection, Critical Success Index, and higher Success Rates for actual lightning events. …”
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L2-GNN: Graph neural networks with fast spectral filters using twice linear parameterization by Siying Huang, Xin Yang, Zhengda Lu, Hongxing Qin, Huaiwen Zhang, Yiqun Wang

“…To improve learning on irregular 3D shapes, such as meshes with varying discretizations and point clouds with different samplings, we propose L2-GNN, a new graph neural network that approximates the spectral filters using twice linear parameterization. First, we parameterize the spectral filters using wavelet filter basis functions. …”
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Improving the Parameterization of Complex Subsurface Flow Properties With Style‐Based Generative Adversarial Network (StyleGAN) by Wei Ling, Behnam Jafarpour

“…Numerical experiments involving model calibration with the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) in single‐phase and two‐phase fluid flow examples are used to assess the capabilities and limitations of these methods. The results show that parameterization with StyleGANs provides superior performance in terms of reconstruction fidelity and flexibility, underscoring its potential for improving the representation and reconstruction of complex spatial patterns in subsurface flow model calibration problems.…”
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Physical insights of squared speed of sound parameterized Brans-Dicke gravity through cosmic parameters and thermodynamics by Nadeem Azhar, Abdul Jawad, Shamaila Rani, Mohammad Mahtab Alam, Sanjar Shaymatov, Sania

“…In most cases, the Om diagnostic shows a quintessence-like era, the jerk parameter and statefinder parameter show the ΛCDM limit and the ω−ω′ plane indicates a freezing region of the universe. …”
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Physical Parameterization Sensitivity of Noah-MP for Hydrothermal Simulation Within the Active Layer on the Qinghai–Tibet Plateau by Yongliang Jiao, Ren Li, Tonghua Wu, Xiaodong Wu, Shenning Wang, Jimin Yao, Guojie Hu, Xiaofan Zhu, Jianzong Shi, Yao Xiao, Erji Du, Yongping Qiao

“…Further analysis showed that scheme 2 of INF yielded better simulation results than scheme 1. …”
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Improved Parameterization of Cloud Droplet Spectral Dispersion Expected to Reduce Uncertainty in Evaluating Aerosol Indirect Effects by Ping Zhang, Yuan Wang, Jiming Li, Fang Fang, Lei Zhu, Jingjing Lv

“…Abstract Relative dispersion (ε), as a parameter characterizing droplet spectral shape, exerts a considerable impact on cloud radiation and precipitation processes, and its accurate parameterization is urgently needed in models. Current ε parameterizations, which are based on droplet number concentration or simply set as constants, are inadequate to satisfy the demand. …”
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A parameterized model for the real-time reconstruction of underwater sound speed fields in oceanic eddy environment by Luochuan Xu, Anmin Zhang, Xuehai Sun, Xuehai Sun, Jian Xu, Yi Liu, Dan Chen, Linglong Chen

“…With its remarkable advantages in both reconstruction efficiency and accuracy, this model shows great potential for practical applications in marine acoustic operations.…”
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A parameterized model for tower crane energy consumption was developed based on theoretical formulation and field data by Fan Zhang, Chunli Zhang, Yan Fu, Jun Liu, Jiarui Bu, Peng Duan, Si Chen

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Switching Linear Parameter-Varying Controller Design With H∞ Performance Based on Youla Parameterization by Weilin Wu, Wei Xie, Liejun Li

“…This article utilizes the Youla parameterization method to design a switching linear parameter-varying (LPV) output-feedback controller. …”
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Toward a unified parameterization of three dimensional turbulent transport in high resolution numerical weather prediction models by Ping Zhu, Kwun Yip. Fung, Xuejin Zhang, Jun A. Zhang, Jian-Wen Bao, Chuan-Kai Wang, Bin Liu, Zhan Zhang, Lucas Harris, Kun Gao, Fanglin Yang, Jongil Han, Weiguo Wang

“…Abstract In numerical weather prediction (NWP) models, horizontal and vertical turbulent mixing is parameterized separately within the dynamic solver of a model and by a one-dimensional standalone module outside the dynamic core. …”
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Data-Driven Sensitivity Analysis of the Influence of Geometric Parameterized Variables on Flow Fields Under Different Design Spaces by Xiaoyu Xu, Hongbo Chen, Chenliang Zhang, Yanhui Duan, Guangxue Wang

“…In aerodynamic shape optimization, geometric parameterized variables have a significant impact on the flow field, thereby influencing both the effectiveness and efficiency of the optimization process. …”
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Parameterization and quantification of two key operando physio-chemical descriptors for water-assisted electro-catalytic organic oxidation by Bailin Tian, Fangyuan Wang, Pan Ran, Luhan Dai, Yang Lv, Yuxia Sun, Zhangyan Mu, Yamei Sun, Lingyu Tang, William A. Goddard, Mengning Ding

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Solving Steady-state Mono-energy Neutron Diffusion Solution Set with Parameterized Physics-informed Neural Network by XIE Yuchen, MA Yu, WANG Yahui

“…The results show that the PINN surrogate model under hard constraints has higher predictive accuracy, and the acceleration ratio is over 1 000. …”

Significance of Cloud Microphysics and Cumulus Parameterization Schemes in Simulating an Extreme Flood-Producing Precipitation Event in the Central Himalaya by Ujjwal Tiwari, Andrew B. G. Bush

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The Role of Forcing and Parameterization in Improving Snow Simulation in the Upper Colorado River Basin Using the National Water Model by Yanjun Gan, Yu Zhang, Cezar Kongoli, Ming Pan

“…Results showed that NWM driven by AORC forcings captured the overall temporal variation of SWE but underestimated its amount. …”
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Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation by Oliver Watt‐Meyer, Noah D. Brenowitz, Spencer K. Clark, Brian Henn, Anna Kwa, Jeremy McGibbon, W. Andre Perkins, Lucas Harris, Christopher S. Bretherton

“…Overall, this study shows potential for the replacement of human‐designed parameterizations with data‐driven ones in a realistic setting.…”
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Impact of modified parameterizations in CLM5.0 on soil hydrothermal dynamics in permafrost regions of the Qinghai–Tibet Plateau by Shu-Hua Yang, Lin Zhao, Guo-Jie Hu, Jian-Jun Cao, Qing Huang, Tong-Hua Wu, Xiao-Dong Wu, Yu-Xin Zhang, Yi-Zhen Du, Dong-Liang Li, Jian Chen, Ren Li

“…The results showed that soil temperature was more sensitive to the modified soil thermal conductivity and unfrozen water schemes, with average RMSE reduced by approximately 0.60 °C compared to the default CLM5.0. …”
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Evaluation of Land-atmosphere Coupling Strength in Low-latitude Highland of Southeast Asia by WRF Model Parameterization Schemes by Xiuzhi WANG, Qidong YANG, Shuaichen HE, Zilin SHI, Bingrong LÜ

“…Southeast Asia's Low-Latitude Highland （LLH） is one of the hotspots of land-atmosphere coupling in the world， with its land-atmosphere interaction has significant impacts on climate， hydrology and environment.This study employs Uniform Design （UD） method to conduct 48 groups of simulation using different parameterization schemes of Weather Research and Forecasting （WRF） model.By optimizing the parameterization schemes， the variables related to land-atmosphere interaction in this area are simulated and evaluated.The findings are as follows： （1） The ensemble of 48 simulation groups demonstrates good performance for near-surface air temperature， near-surface specific humidity， surface downward longwave radiation， surface upward longwave radiation and surface soil temperature， with average Taylor Skill Score （TSS） values exceeding 0.8； for near-surface wind speed， precipitation， surface sensible heat flux， surface latent heat flux， surface downward shortwave radiation and surface upward shortwave radiation， the ensemble simulation can adequately capture the characteristics of these variables， with average TSS values ranging between 0.4 and 0.8； but for surface soil moisture， the ensemble simulation performance is poor， with average TSS values less than 0.4.The variability among different simulation groups is minimal for near-surface wind speed， precipitation， surface latent heat flux， surface downward shortwave radiation， surface upward shortwave radiation， surface soil temperature and surface soil moisture （TSS range < 0.2）； but for the surface sensible heat flux， the variability among different simulation groups is significant （TSS range > 0.3）.（2） The optimal parameterization schemes based on equal-weighted averaged TSS can enhance simulation accuracy for near-surface air temperature， near-surface specific humidity， surface downward longwave radiation， surface upward longwave radiation and surface soil temperature， with correlation coefficients exceeding 0.9 and minor deviations from reference values.However， this optimization could not significantly improve simulation performance for near-surface wind speed， precipitation， surface sensible heat flux， surface latent heat flux and surface soil moisture， where deviations remain substantial.（3） The optimal parameterization schemes can reasonably capture the spatial and temporal features of land-atmosphere coupling， showing strong coupling strength in northeast and southwest LLH， with temporal correlation coefficient greater than 0.9.Nonetheless， the simulated values of coupling strength is generally weaker than the reference values， primarily due to poor simulation performance of surface latent heat flux and surface downward shortwave radiation.…”
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Evaluation of Topographic Effect Parameterizations in Weather Research and Forecasting Model over Complex Mountainous Terrain in Wildfire-Prone Regions by Yong Han Jo, Seung Hee Kim, Yun Gon Lee, Chang Ki Kim, Jinkyu Hong, Junhong Lee, Keunchang Jang

“…The simulation results of the wildfire case in 2019 show that subgrid-scale orographic parameterization considerably improves model performance regarding wind speed, with a lower root mean square error (RMSE) and bias by 53% and 57%, respectively. …”
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Effect of a Scale‐Aware Convective Parameterization Scheme on the Simulation of Convective Cells‐Related Heavy Rainfall in South Korea by Haerin Park, Gayoung Kim, Dong‐Hyun Cha, Eun‐Chul Chang, Joowan Kim, Sang‐Hun Park, Dong‐Kyou Lee

“…Abstract In this study, the effect of a scale‐aware convective parameterization scheme (CPS) on the simulation of heavy precipitation in the gray‐zone was investigated using the Weather Research and Forecasting (WRF) model. …”
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