15 citations as recorded by crossref.

1. Multimodel comparison and assessment of short to medium range precipitation and temperature forecasts over India: Implications towards forecasting of meteorological indices in India S. Saminathan et al. 10.1002/joc.8409
2. Quantification of the effect of hydrological drivers on actual evapotranspiration using the Bayesian model averaging approach for various landscapes over Northeast Asia Y. Hao et al. 10.1016/j.jhydrol.2022.127543
3. Evaluation of Empirical Equations and Machine Learning Models for Daily Reference Evapotranspiration Prediction Using Public Weather Forecasts Y. Liang et al. 10.3390/w15223954
4. Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations J. Xu et al. 10.3390/rs13214464
5. Assessment of surface downward longwave radiation in CMIP6 with comparison to observations and CMIP5 J. Xu et al. 10.1016/j.atmosres.2022.106056
6. Calibrating anomalies improves forecasting of daily reference crop evapotranspiration Q. Yang et al. 10.1016/j.jhydrol.2022.128009
7. Bias-correcting input variables enhances forecasting of reference crop evapotranspiration Q. Yang et al. 10.5194/hess-25-4773-2021
8. Classification of Weather Conditions Based on Supervised Learning for Swedish Cities M. Safia et al. 10.3390/atmos14071174
9. Probabilistic post-processing of short to medium range temperature forecasts: Implications for heatwave prediction in India S. Saminathan & S. Mitra 10.1007/s10661-024-12418-3
10. Multi-model Subseasonal Precipitation Forecasts over the Contiguous United States: Skill Assessment and Statistical Postprocessing Y. Li et al. 10.1175/JHM-D-21-0029.1
11. Post-processing of the UKMO ensemble precipitation product over various regions of Iran: integration of long short-term memory model with principal component analysis S. Alizadeh et al. 10.1007/s00704-022-04170-w
12. A Two‐Stage Framework for Bias and Reliability Tests of Ensemble Hydroclimatic Forecasts T. Zhao et al. 10.1029/2022WR032568
13. Modeling the optimal dosage of coagulants in water treatment plants using various machine learning models M. Achite et al. 10.1007/s10668-022-02835-0
14. Medium-range forecasting of daily reference evapotranspiration across China using numerical weather prediction outputs downscaled by extreme gradient boosting J. Fan et al. 10.1016/j.jhydrol.2021.126664
15. Reconstructing climate trends adds skills to seasonal reference crop evapotranspiration forecasting Q. Yang et al. 10.5194/hess-26-941-2022