SENSITIVITY TEST OF PARAMETERIZATION SCHEMES OF MM5 MODEL FOR PREDICTION OF THE HIGH IMPACT RAINFALL EVENTS OVER BANGLADESH

Abstract

The sensitivity test of parameterization schemes for prediction of summer monsoon high impact rainfallevents (HIRE) over Bangladesh has been performed using the Fifth-Generation PSU/NCAR Mesoscale Model(MM5) conducting six historical HIRE cases. The MM5 model was run on triple-nested domains at 45, 15, 5 kmhorizontal resolutions using Anthes-Kuo (AK), Grell (Gr), Kain-Fritsch (KF), Betts-Miller (BM) andKain-Fritsch2 (KF2) cumulus parameterization schemes (CPS) with Medium Range Forecast (MRF) andBlackadar planetary boundary layer (PBL).The model predicted rainfall was compared both spatially andquantitatively with Tropical Rainfall Measuring Mission (TRMM) rainfall. While parameterization options ofMM5 model have been investigated spatially for Bangladesh, Anthes-Kuo CPS with both MRF and BlackadarPBL (AKM & AKB) options of MM5 have found suitable. Quantitatively, Anthes-Kuo CPS with MRF PBL (AKM)option has calculated the better average rainfall over Bangladesh. By this way, AKM has found suitable in bothspatial and quantitaive comparisons. Thus, Anthes-Kuo CPS with MRF PBL (AKM) has considered as the bestMM5 option for prediction of summer monsoon HIRE cases over Bangladesh.The sensitivity test of parameterization schemes for prediction of summer monsoon high impact rainfall events (HIRE) over Bangladesh has been performed using the Fifth-Generation PSU/NCAR Mesoscale Model (MM5) conducting six historical HIRE cases. The MM5 model was run on triple-nested domains at 45, 15, 5 km horizontal resolutions using Anthes-Kuo (AK), Grell (Gr), Kain-Fritsch (KF), Betts-Miller (BM) and Kain-Fritsch2 (KF2) cumulus parameterization schemes (CPS) with Medium Range Forecast (MRF) and Blackadar planetary boundary layer (PBL).The model predicted rainfall was compared both spatially and quantitatively with Tropical Rainfall Measuring Mission (TRMM) rainfall. While parameterization options of MM5 model have been investigated spatially for Bangladesh, Anthes-Kuo CPS with both MRF and Blackadar PBL (AKM & AKB) options of MM5 have found suitable. Quantitatively, Anthes-Kuo CPS with MRF PBL (AKM) option has calculated the better average rainfall over Bangladesh. By this way, AKM has found suitable in both spatial and quantitaive comparisons. Thus, Anthes-Kuo CPS with MRF PBL (AKM) has considered as the best MM5 option for prediction of summer monsoon HIRE cases over Bangladesh. DOI: http://dx.doi.org/10.3329/jme.v44i1.19496