25 citations as recorded by crossref.

1. Parameter estimation of an atmospheric model using geostationary satellite observation to improve prediction of tropical cyclones: an idealized experiment Y. Hirose et al. https://doi.org/10.1007/s44394-026-00021-8
2. Role of assimilation of microwave humidity sounder (MHS) satellite radiance in forecast of structure and intensity of VSCS Vardah 2016 A. Thankachan & K. Satya Singh https://doi.org/10.1016/j.asr.2024.06.068
3. Machine learning-based sensitivity of solar radiation forecasts to cloud-related parameters in WRF-Solar J. Yoon et al. https://doi.org/10.1016/j.solener.2026.114570
4. Uncertainty quantification and optimization of precipitating hydrometeor parameters for winter precipitation in a cloud microphysics scheme K. Kim et al. https://doi.org/10.1016/j.atmosres.2025.108554
5. Parameter Calibration to Improve the Prediction of Tropical Cyclones over the Bay of Bengal Using Machine Learning–Based Multiobjective Optimization H. Baki et al. https://doi.org/10.1175/JAMC-D-21-0184.1
6. Optimization of parameters in the surface-layer scheme of the Weather Research and Forecasting (WRF) model for near-surface wind and temperature J. Lee et al. https://doi.org/10.1016/j.atmosres.2026.109034
7. Effect of wave–current–surge interactions on simulated wave conditions in a strait via an optimal WRF typhoon model H. Li & K. Wei https://doi.org/10.1016/j.oceaneng.2025.120962
8. The Sensitivity of the Icosahedral Non-Hydrostatic Numerical Weather Prediction Model over Greece in Reference to Observations as a Basis towards Model Tuning E. Avgoustoglou et al. https://doi.org/10.3390/atmos14111616
9. A numerical study on the oceanic response to intense tropical storms over the Bay of Bengal using a high-resolution coupled atmosphere-ocean model K. Thatiparthi et al. https://doi.org/10.1007/s10236-025-01765-5
10. Machine learning based parameter sensitivity of regional climate models—a case study of the WRF model for heat extremes over Southeast Australia P. Reddy et al. https://doi.org/10.1088/1748-9326/ad0eb0
11. Comparative assessment of WRF’s parameterization scheme combinations in assessing land-surface feedback flux and its drivers: a case study of Phailin tropical cyclone S. Mandal et al. https://doi.org/10.1007/s00704-024-05032-3
12. Combinatorial Optimization of Physics Parameterization Schemes for Typhoon Simulation Based on a Simple Genetic Algorithm (SGA) Z. Lu et al. https://doi.org/10.1007/s13351-024-3105-2
13. Sensitivity analysis of the physics options in the Weather Research and Forecasting model and its impact on storm surge simulations during two tropical cyclones over the Bay of Bengal V. Yalla et al. https://doi.org/10.1016/j.dynatmoce.2025.101643
14. Effectiveness of the ARW model in the simulation of tropical cyclones over the Bay of Bengal on a cloud-resolving scale M. Reshma & K. Singh https://doi.org/10.1080/19475705.2025.2583464
15. Prioritization of meteorological factors for rainfall prediction: a hybrid fuzzy AHP and fuzzy TOPSIS approach R. Adnan & R. Kumaravel https://doi.org/10.1088/1402-4896/adcbeb
16. Comparative evaluation of high-resolution rainfall products over South Peninsular India in characterising precipitation extremes M. Sneha & A. Nair https://doi.org/10.1007/s11069-023-05936-9
17. Optimization of the World Ocean Model of Biogeochemistry and Trophic dynamics (WOMBAT) using surrogate machine learning methods P. Buchanan et al. https://doi.org/10.5194/bg-22-5349-2025
18. The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at kilometre scale J. Castillo et al. https://doi.org/10.5194/gmd-15-4193-2022
19. A discrete element method study on rice seed particles with different sizes under loading: Stress distribution and force chain evolution L. Chen et al. https://doi.org/10.1016/j.cpms.2026.05.004
20. Estimation of possible extreme droughts for a dam catchment in Korea using a regional-scale weather model and long short-term memory network M. Shin & Y. Jung https://doi.org/10.2166/nh.2023.192
21. Sensitivity of NEMO4.0-SI3 model parameters on sea ice budgets in the Southern Ocean Y. Nie et al. https://doi.org/10.5194/gmd-16-1395-2023
22. ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool D. Di Santo et al. https://doi.org/10.5194/gmd-18-433-2025
23. Spatiotemporal bias correction of satellite precipitation products using multimodel techniques over temporally coherent clusters in South Peninsular India S. M R et al. https://doi.org/10.1016/j.atmosres.2025.108244
24. Prediction and interpretation of pathogenic bacteria occurrence at a recreational beach using data-driven algorithms J. Jang et al. https://doi.org/10.1016/j.ecoinf.2023.102370
25. The Sensitivity of Extreme Rainfall Simulations to WRF Parameters During Two Intense Southwest Monsoon Events in the Philippines K. Henson et al. https://doi.org/10.1007/s13143-024-00380-6