We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Prediction of heavy rainfall events over Rangamati, Bangladesh using high-resolution MM5 model.
- Authors
Ahasan, M.; Mannan Chowdhury, M.; Quadir, D.
- Abstract
In this study, prediction of the heavy rainfall events over Rangamati, Bangladesh has been carried out using the Fifth-Generation PSU/NCAR Mesoscale Model (MM5) conducting two historical rainfall events. The model was run on two-way triple-nested domains at 45, 15, 5 km horizontal resolutions using Anthes-Kuo cumulus parameterization schemes (CPS) with MRF planetary boundary layer (PBL). Bangladesh is the main focus area in this study. Thus, Bangladesh is taken as inner most domain (D3) with 5 km horizontal resolution. The model-predicted rainfall was compared with TRMM 3B42V7 and BMD observed rainfall. Both subjective and objective evaluation methods have been followed. The MM5 model produces realistic prediction of heavy rainfall events in terms of intensity and structure. The results show that the model performed all the Day 1 (24 h), Day 2 (48 h) and Day 3 (72 h) predictions reasonably well. The predictions are more accurate for Day 2 (48 h) and worse for Day 4 (96 h) in both cases. The prediction deteriorates as the prediction time increases. Thus, the prediction may be updated in every 24 h which would provide more realistic prediction. The RMSE shows that the value for 24 h prediction lies within 10-20 mm range. The prediction error is minimal for 48 h prediction, the error ranging from 8 to 12 mm. The error increases thereafter for 72 and 96 h of predictions. The errors range from around 10-20 and 15-25 mm, respectively. The topography/terrain over the southeast hilly region of Bangladesh has not been resolved by USGS terrain data which was used in the MM5 model. Thus, accurate and high-resolution terrain data of this region is expected to improve the performance of the model over the southeast hilly regions of Bangladesh.
- Subjects
BANGLADESH; RAINFALL; PREDICTION models; ATMOSPHERIC models; WEATHER forecasting; METEOROLOGICAL observations
- Publication
Meteorology & Atmospheric Physics, 2015, Vol 127, Issue 2, p183
- ISSN
0177-7971
- Publication type
Article
- DOI
10.1007/s00703-014-0354-0