Bangladesh using High Resolution VRF-ARW fuIodel" was carried out. salman Khan in the Department of Physics, Khulna University of. The above thesis work or any part of this rvork has not been submitted here for the award of any degree or diploma. Salman Khan titled uStudy on sensitivity of microphysics for the simulation of rainfall for the month of.
ECMWF European Center for Medium-Range Weather Forecasts EUMETSAT European Organization for the Exploitation of Meteorology. In the present study, the Advanced Research WRF (ARW) v3.8.1 model was used to simulate rainfall for the month of May 2015 over Bangladesh. In this research, six different microphysics schemes such as Lin et al., WSM6, Thomson, Morrison Double-Moment (M-2M), Stony Brook University (SBU) and WDM6 coupling with the cumulus parameterization scheme Kain-Fritsch (KF) has been used to simulate total monthly rainfall, monthly heavy rainfall, monthly rainy days and monthly heavy rainy days for the month of May 2015 across Bangladesh.
The standard deviation of all observed parameters, PERSIANN and the simulated model are analyzed and compared. The WDM6 scheme gives better rainfall and wet day performance across the country.
Introduction
The Thompson scheme (Figure 14c) simulated the maximum heart rate in the NE region and no heart rate in the SW region of Bangladesh. The Thompson scheme (Figure 17c) simulated the most rainy days in the NE region and the least in the SW region of Bangladesh. The M-2M scheme (Figure 17d) simulated the most rainy days in the NE region and the least in the SW region of Bangladesh.
SBU-YLin scheme (Figure 17e) simulated maximum rainy days in the NE region and minimum in the SW region of Bangladesh. Thompson scheme (Figure 18c) simulated maximum rainy days in the NE region and minimum in the SW region of Bangladesh. M-2M scheme (Figure 18d) simulated maximum rainy days in the NE region and minimum in the south-SW region of Bangladesh.
The SBU-YLin scheme (Figure 18e) simulated the most rainy days in the NE region and the least in the SW region of Bangladesh. The M-2M scheme (Figure 19d) simulated the most rainy days in the NE region and the least in the southern SW region of Bangladesh. The SBU-YLin scheme (Figure 19e) simulated the most rainy days in the NE region and the least in the southern SW region of Bangladesh.
The WDM6 scheme (Figure 19f) simulated the most rainy days in the NE region and the least in the southern SW region of Bangladesh. The Thompson scheme (Figure 20c) simulated the most rainy days in the NE region and the least in the Khulna region of Bangladesh. The M-2M scheme (Figure 20d) simulated the most rainy days in the NE region and the least in the SW region of Bangladesh.
The SBU-YLin scheme (Figure 20e) has simulated the maximum rainy days in the northeastern region and the minimum in the southwestern region of Bangladesh. The Thompson scheme (Figure 21c) simulated the maximum rainy days in the northeastern region and the minimum rainy days in the southwestern region of Bangladesh. The M-2M scheme (Figure 21d) simulated the maximum rainy days in the northeastern region and the minimum rainy days in the southwestern region.
The SBU-YLin scheme (Figure 21e) has simulated maximum rainy days in the NE region and minimum in the SW region of Bangladesh. The WDM6 scheme (Figure 21f) has simulated maximum rainy days in the NE region and minimum in the SW region of Bangladesh. The scheme has simulated much higher HR days in the NE region and lower in the NW region of the country.
The scheme has simulated higher HR days in the central and NE region of the country.
Conclusions
The simulated number of total rainy days at Sylhet and Bhola for all MPs is almost matched with the observed total rainy days. All MPs have simulated much higher total rainy days for Day 1, Day 2 and Day 3 predictions with few exceptions across the country for the month of May 2015. The number of observed rainy days in the South East region is very few, but different MPs have simulated much higher rainy days in this region.
The distribution pattern of heavy rainfall days for different microphysics schemes is similar in the central, NE, S-SE and SW regions, but in the NW region the number of heavy rainfall days is insignificant. The SD has a minimum at D1 and D2 for the WDM6 schedule for day 1 forecasts and the WSM6 schedule for day 2 and day 3 forecasts for the May 2015 rainfall.
Ferretti, A., Prati C., and Rocca F., 2000: Nonlinear subsidence rate estimates using persistent scatterers in differential sarinterferometry, IEEE Transactions on Geoscience and Remote Sensing. A, 2018: Convective and non-convective rain study of different heavy rainfall events in pre-monsoon season using WRF-ARW model, M.Sc. Thesis, Department of U., 2018: Sensitivity study for simulation of heavy rainfall during Monsoon Season over Bangladesh using high resolution WRF-ARW model , M.Sc.
H., 2004: A revised approach to ice microphysical processes for mass parameterization of clouds and precipitation, Mon. Hong, Y., Hsu K., GaoX., and Sorooshian S., 2004: Precipitation estimation from remotely sensed information using an artificial neural network – cloud classification system, J. Huq, M.S., 1974: Climate of Bangladesh, Studies in Bangladesh Geography ( ed. by A. F. M. Kamaluddin), Section 3, Bangladesh National Geographical Association.
Kruk, N.S., Vendrame I.F., Rocha H.R.D., Chou S.C., and Cabral O., 2010: Downward longwave radiation estimates for clear and sky conditions in the Sertaozinho region of Sao Paulo, Brazil. Karmakar, S., and Khatun A., 1995: Variability and probabilistic estimates of extreme rainfall in Bangladesh during the southwest monsoon season. Kotroni, V., and Lagouvardos K., 2001: Precipitation forecast skill of different convective parameterization and microphysical schemes: Application to cold, Geophysical Research Letters.
Mamun, A., Abdullah, 2016: Simulation of pre-monsoon temperature over Bangladesh using dynamical downscaling with the high-resolution WRF-ARW model, KUET. Otkin, J., Huang HL., and Seifert A., 2006: A comparison of microphysical schemes in the WRF model during a severe weather event. Yamane, Y., and Hayashi T., 2008: Assessment of environmental conditions for local severe thunderstorm formation across the Indian subcontinent, Geophys Res Lett 33: L17806.
