57 citations as recorded by crossref.

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2. Development of hybrid machine learning-based carbonation models with weighting function Z. Chen et al. 10.1016/j.conbuildmat.2022.126359
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7. Projected Increase in Probability of East Asian Heavy Rainy Summer in the 21st Century by CMIP5 Models Y. Fu et al. 10.1007/s00376-021-0347-0
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15. Forecasting Daily Flood Water Level Using Hybrid Advanced Machine Learning Based Time-Varying Filtered Empirical Mode Decomposition Approach M. Jamei et al. 10.1007/s11269-022-03270-6
16. Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development C. Pande et al. 10.1016/j.jclepro.2024.141035
17. Selecting a climate model subset to optimise key ensemble properties N. Herger et al. 10.5194/esd-9-135-2018
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19. Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting M. Ali et al. 10.1016/j.renene.2023.01.108
20. The Sailor diagram – A new diagram for the verification of two-dimensional vector data from multiple models J. Sáenz et al. 10.5194/gmd-13-3221-2020
21. Wind-wave hindcast using modified ECMWF ERA-Interim wind field in the Mediterranean Sea A. Elkut et al. 10.1016/j.ecss.2021.107267
22. Sensitivity of South Asian summer monsoon simulation to land surface schemes in Weather Research and Forecasting model S. Lu & H. Zuo 10.1002/joc.7278
23. Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices . Dimple et al. 10.1016/j.ecoinf.2023.102093
24. Impacts of Land Surface Parameterizations on Simulations over the Arid and Semiarid Regions: The Case of the Loess Plateau in China S. Lu et al. 10.1175/JHM-D-21-0143.1
25. Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting M. Jamei et al. 10.1016/j.ecolind.2023.110478
26. Application of Taylor diagram in the evaluation of joint environmental distributions' performances M. Simão et al. 10.1007/s40868-020-00081-5
27. An improved multivariable integrated evaluation method and tool (MVIETool) v1.0 for multimodel intercomparison M. Zhang et al. 10.5194/gmd-14-3079-2021
28. Assessing the Performance of a Dynamical Downscaling Simulation Driven by a Bias-Corrected CMIP6 Dataset for Asian Climate Z. Xu et al. 10.1007/s00376-023-3101-y
29. New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes M. Ali et al. 10.1016/j.ecolind.2023.111030
30. Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks M. Ali et al. 10.1016/j.renene.2023.119773
31. A double decomposition-based modelling approach to forecast weekly solar radiation R. Prasad et al. 10.1016/j.renene.2020.01.005
32. Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts M. Ali et al. 10.1016/j.jhydrol.2020.124647
33. A new diagram for performance evaluation of complex models A. Izzaddin et al. 10.1007/s00477-024-02678-3
34. Evaluation of the WRF physics ensemble using a multivariable integrated evaluation approach over the Haihe river basin in northern China D. Dai et al. 10.1007/s00382-021-05723-x
35. Evaluation of CMIP6 models toward dynamical downscaling over 14 CORDEX domains M. Zhang et al. 10.1007/s00382-022-06355-5
36. Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia P. Rai et al. 10.1007/s00704-022-04233-y
37. Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms M. Ali et al. 10.1016/j.rser.2020.110003
38. Evaluation of Observed and Future Climate Change Projection for Uttarakhand, India, Using CORDEX-SA N. Tyagi et al. 10.3390/atmos13060947
39. Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach M. Jamei et al. 10.1016/j.apenergy.2022.119925
40. Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction M. Ali et al. 10.1038/s41598-022-09482-5
41. Climate change scenario projections and their implications on food systems in Taita Taveta County, Kenya F. Nyambariga et al. 10.1371/journal.pclm.0000114
42. Validation of net radiation from multi-models and satellite retrieval over Nigeria O. Ojo 10.1007/s40808-022-01647-5
43. Bias correction and projection of temperature over the altitudes of the Upper Indus Basin under CMIP6 climate scenarios from 1985 to 2100 K. Jamal et al. 10.2166/wcc.2023.180
44. The role of temporal resolution of meteorological inputs from reanalysis data in estimating air humidity for modelling applications M. Viggiano et al. 10.1016/j.agrformet.2021.108672
45. Robust machine learning algorithms for predicting coastal water quality index M. Uddin et al. 10.1016/j.jenvman.2022.115923
46. Assessing the performance of 33 CMIP6 models in simulating the large-scale environmental fields of tropical cyclones Y. Han et al. 10.1007/s00382-021-05986-4
47. Future frequency and intensity of Western Disturbance(s) T. Midhuna et al. 10.1002/joc.7944
48. A Comprehensive Experimental and Computational Investigation on Estimation of Scour Depth at Bridge Abutment: Emerging Ensemble Intelligent Systems M. Pandey et al. 10.1007/s11269-023-03525-w
49. Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation Z. Zheng et al. 10.1016/j.rser.2023.113645
50. Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100) Z. Xu et al. 10.1038/s41597-021-01079-3
51. Projected changes in summer water vapor transport over East Asia under the 1.5°C and 2.0°C global warming targets Z. XU & K. FAN 10.1080/16742834.2019.1569869
52. Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia M. Ali et al. 10.1016/j.renene.2021.06.052
53. Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach Z. Zheng et al. 10.1016/j.engappai.2023.105984
54. Performance evaluation of multi-satellite rainfall products in the Gidabo catchment, Rift Valley Basin, Ethiopia K. Gebretsadkan et al. 10.2166/wcc.2023.097
55. Recent Progress in Numerical Atmospheric Modeling in China R. Yu et al. 10.1007/s00376-019-8203-1
56. The Spectral Diagram as a new tool for model assessment in the frequency domain: Application to a global ocean general circulation model with tides M. Calim Costa et al. 10.1016/j.cageo.2021.104977
57. Accuracy, uncertainty, and interpretability assessments of ANFIS models to predict dust concentration in semi-arid regions Z. Ebrahimi-Khusfi et al. 10.1007/s11356-020-10957-z