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Monthly streamflow forecasting by machine learning methods using dynamic weather prediction model outputs over Iran
Seasonal hydrological forecasts play a critical role in water resources management. The
Copernicus Climate Change Service (C3S) data store provides open access to monthly …
Copernicus Climate Change Service (C3S) data store provides open access to monthly …
Forecasting of compound ocean-fluvial floods using machine learning
Flood modelling and forecasting can enhance our understanding of flood mechanisms and
facilitate effective management of flood risk. Conventional flood hazard and risk …
facilitate effective management of flood risk. Conventional flood hazard and risk …
Adaptive precipitation nowcasting using deep learning and ensemble modeling
Accurate rainfall nowcasting is necessary for real-time flood management in urban areas. In
this paper, some deep neural networks (DNNs) are developed for rainfall nowcasting with …
this paper, some deep neural networks (DNNs) are developed for rainfall nowcasting with …
[HTML][HTML] Deep-learning post-processing of short-term station precipitation based on NWP forecasts
Post-processing methods that rely on fusion-grided forecast products can reduce systematic
biases from Numerical Weather Prediction (NWP) precipitation forecasts. However, these …
biases from Numerical Weather Prediction (NWP) precipitation forecasts. However, these …
Effects of automatic hyperparameter tuning on the performance of multi‐Variate deep learning‐based rainfall nowcasting
Rainfall nowcasting has become increasingly important as we move into an era where more
and more storms are occurring in many countries as a result of climate change. Develo** …
and more storms are occurring in many countries as a result of climate change. Develo** …
Bias correction of global ensemble precipitation forecasts by Random Forest method
One of the most important topics in operational applications of precipitation forecasts is their
improvement by bias correction methods. In this study, the ensemble precipitation forecasts …
improvement by bias correction methods. In this study, the ensemble precipitation forecasts …
Deterministic and probabilistic evaluation of raw and post processed sub-seasonal to seasonal precipitation forecasts in different precipitation regimes
Precipitation is an important and difficult climate variable to predict. Skillful sub-seasonal
precipitation forecast can provide useful information for agriculture and water resources …
precipitation forecast can provide useful information for agriculture and water resources …
Assessment of precipitation estimation from the NWP models and satellite products for the spring 2019 severe floods in Iran
Precipitation monitoring and early warning systems are required to reduce negative flood
impacts. In this study, the performance of ensemble precipitation forecasts of three numerical …
impacts. In this study, the performance of ensemble precipitation forecasts of three numerical …
Performance evaluation of sub‐daily ensemble precipitation forecasts
Nowadays, major advances have been made in meteorological forecasts. For instance,
ensemble forecast systems have been developed to quantify prediction uncertainty. In this …
ensemble forecast systems have been developed to quantify prediction uncertainty. In this …
Spatial connections in extreme precipitation events obtained from NWP forecasts: A complex network approach
Understanding the spatial variability of extreme precipitation events (EPEs) has always been
a challenging task, with climate change further complicating the issue. Many studies have …
a challenging task, with climate change further complicating the issue. Many studies have …