We present the results of the impact of the 3D variational data assimilation (3DVAR) system within the Weather Research and Forecasting (WRF) model to simulate three heavy rainfall events (25–28 June 2005, 29–31 July 2004, and 7–9 August 2002) over the Indian monsoon region. For each event, two numerical experiments were performed. In the first experiment, namely the control simulation (CNTL), the low-resolution global analyses are used as the initial and boundary conditions of the model. In the second experiment (3DV-ANA), the model integration was carried out by inserting additional observations in the model’s initial conditions using the 3DVAR scheme. The 3DVAR used surface weather stations, buoy, ship, radiosonde/rawinsonde, and satelli...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Mo...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. M...
The background error covariance structure influences a variational data assimilation system immense...
We present the results of the impact of the 3D variational data assimilation (3DVAR) system within t...
Abstract We present the results of the impact of the 3D variational data assimilation (3DVAR) system...
An attempt is made to evaluate the impact of the three dimensional variational (3DVAR) data assimila...
The present study examines the performance of the Advance Research Weather Research and Forecasting ...
The mesoscale Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorol...
Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model...
Weather Research and Forecasting (WRF) is a mesoscale numerical weather prediction model that can pr...
This study examines the impact of three-dimensional variational data assimilation (3DVAR) on the pre...
The procedure to combine mathematical models with noise data, in order to improve numeri...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Mo...
In this study, the impact of different initial land conditions on the simulation of thunderstorms an...
The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon low...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Mo...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. M...
The background error covariance structure influences a variational data assimilation system immense...
We present the results of the impact of the 3D variational data assimilation (3DVAR) system within t...
Abstract We present the results of the impact of the 3D variational data assimilation (3DVAR) system...
An attempt is made to evaluate the impact of the three dimensional variational (3DVAR) data assimila...
The present study examines the performance of the Advance Research Weather Research and Forecasting ...
The mesoscale Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorol...
Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model...
Weather Research and Forecasting (WRF) is a mesoscale numerical weather prediction model that can pr...
This study examines the impact of three-dimensional variational data assimilation (3DVAR) on the pre...
The procedure to combine mathematical models with noise data, in order to improve numeri...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Mo...
In this study, the impact of different initial land conditions on the simulation of thunderstorms an...
The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon low...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Mo...
Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. M...
The background error covariance structure influences a variational data assimilation system immense...