Numerical study of the microphysics of a mesoscale convective system leads to flash flood events in the west and southwest of Iran

Document Type : Original Article

Authors

1 M.Sc. Graduate of Meteorology/ Institute of Geophysics, University of Tehran

2 Faculty member /Department of Space Physics, Institute of Geophysics, University of Tehran

3 Associate Professor/ Institute of Geophysics, University of Tehran

Abstract

This study investigated the performance of the Weather Research and Forecasting (WRF) mesoscale model in the simulation of microphysical parameters of a mesoscale convective system (MCS) event. This case study occurred during 13 April 2016 over the west and southwest of Iran and resulted in a flood in these areas. For all simulations, the WRF model uses a one-way nesting for three meshes of 36, 12, and 4 km horizontal resolution, respectively. In all simulations, the data from NCEP global final analysis (FNL) on 1-degree by 1-degree grids provide initial and boundary conditions. The results obtained from the model simulations are compared with the observations. The distribution of daily precipitation from the second domain of the model outputs showed the Morrison scheme has better performance in the simulation of maximum rainfall and spatial distribution of daily rainfall than the Thompson scheme.
Comparison between the simulated daily precipitation in the third domain of all simulations and the observed daily precipitation at 40 synoptic stations in the study area shows that two schemes predict about half of the amount of rainfall in the region close to observational amounts for the mentioned day. Following, the time series of simulated values and station observations plotted for a variety of surface variables such as 2-meter temperature, relative humidity, and sea surface pressure for 13 April 2016 at Ahwaz station; it is possible to verify the model simulations for each of these parameters.
The last section investigated several microphysical parameters from the two simulations to better understand the MCS properties. In examining the vertical profile of these microphysical variables, no noticeable difference was observed from the simulation compared with the two schemes. Almost similar concentrations and fall velocities show that the precipitation results from the simulations are comparable and slightly different.

Keywords


  1. Ahmadloo, M., Gharaylou, M., Farahani, M.M., and Pegahfar, N. 2022. Simulation and Analysis of Mesoscale Convective Systems (MCSs) Leading to a Severe Flood Over Iran. Pure and Applied Geophysics, 1-23.
  2. Alam, M.M. 2014. Impact of cloud microphysics and cumulus parameterization on simulation of heavy rainfall event during 7–9 October 2007 over Bangladesh. Journal of Earth System Science, 123(2), 259-279.
  3. Bryan, G.H., and Morrison, H. 2012. Sensitivity of a simulated squall line to horizontal resolution and parameterization of microphysics. Monthly Weather Review, 140(1), 202–225.
  4. Chen, Y., Ping, F., Zhou, S., Shen, X., and Sun, Y. 2021. Influence of microphysical processes on the initiation of the mesoscale convective system of a rainstorm over Beijing. Atmospheric Research, 254, 105518.
  5. Choi, H.Y., Ha, J.H., Lee, D.K., and Kuo, Y.H. 2011. Analysis and simulation of mesoscaleconvective systems accompanying heavy rainfall: the Goyang case. Asia-Pacific Journal of Atmospheric Sciences, 47(3), 265-279.
  6. Das, S., Ashrit, R., Moncrieff, M.W., Das Gupta, M., Dudhia, J., Liu, C. and Kalsi, S.R. 2007. Simulation of intense organized convective precipitation observed during the Arabian Sea Monsoon Experiment (ARMEX). Journal of Geophysical Research: Atmospheres, 112(D20).
  7. Dasa, M.K., Chowdhuryb, M.A., and Dasc, S. 2015. Sensitivity Study with Physical Parameterization Schemes for Simulation of Mesoscale Convective Systems Associated with Squall Events. International Journal of Earth and Atmospheric Science, 2(2), 20-36.
  8. Duda, J.D. 2011. WRF simulations of mesoscale convective systems at convection-allowing resolutions. Iowa State University.
  9. Fan, J., Leung, L.R., Rosenfeld, D., Chen, Q., Li, Z., Zhang, J., and Yan, H., 2013. Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds. Proceedings of the National Academy of Sciences, 110(48), E4581-E4590.
  10. Feng, Z., Leung, L. R., Houze Jr, R.A., Hagos, S., Hardin, J., Yang, Q., and Fan, J. 2018. Structure and evolution of mesoscale convective systems: Sensitivity to cloud microphysics in convection‐permitting simulations over the United States. Journal of Advances in Modeling Earth Systems, 10(7), 1470-1494.
  11. Heymsfield, A.J., and Donner, L.J. 1990. A scheme for parameterizing ice-cloud water content in general circulation models. Journal of Atmospheric Sciences, 47(15), 1865-1877.
  12. Houze, R.A. 2004. Mesoscale convective systems. Reviews of Geophysics, 42, RG4003.
  13. Hyndman, R.J., and Koehler, A.B., 2006, Another look at measures of forecast accuracy. International Journal of forecasting, 22(4), 679-688.
  14. Kerkhoven, E., Gan, T.Y., Shiiba, M., Reuter, G., and Tanaka, K. 2006. A comparison of cumulus parameterization schemes in a numerical weather prediction model for a monsoon rainfall event. Hydrological Processes: An International Journal, 20(9), 1961-1978.
  15. Kumar, S., Routray, A., Chauhan, R., and Panda, J. 2014. Impact of parameterization schemes and 3DVAR data assimilation for simulation of heavy rainfall events along west coast of India with WRF modeling system. International Journal of Earth and Atmospheric Science, 01: 18-34.
  16. Lee, H., and Baik, J.J. 2018. A comparative study of bin and bulk cloud microphysics schemes in simulating a heavy precipitation case. Atmosphere, 9(12), 475.
  17. Litta, A.J., Idicula, S.M., and Mohanty, U.C. 2011. A comparative study of convective parameterization schemes in WRF-NMM model. International Journal of Computer Applications, 33(6), 32-39.
  18. Liu, C., and Moncrieff, M.W. 2007. Sensitivity of Cloud-Resolving Simulations of Warm-Season Convection to Cloud Microphysics Parameterizations, Monthly Weather Review, 135(8), 2854-2868.
  19. Mapes, B. E., and Houze Jr, R. A., 1993, Cloud clusters and superclusters over the oceanic warm pool. Monthly Weather Review, 121(5), 1398-1416.
  20. Morrison, H., Curry, J.A., and Khvorostyanov, V.I. 2005. A New Double - Moment Microphysics Parameterization for Application in Cloud and Climate Models. Part I: Description Journal of Atmospheric Sciences, 62(6), 1665–1677.
  21. Morrison, H., and Pinto, J.O. 2005. Mesoscale modeling of springtime Arctic mixed-phase stratiform clouds using a new two-moment bulk microphysics scheme. Journal of the Atmospheric Sciences, 62(10), 3683–3704.
  22. Morrison, H., Thompson, G., and Tatarskii, V. 2009. Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Monthly Weather Review, 137(3), 991–1007.
  23. Panda, J., and Giri R.K. 2012. A comprehensive study of surface and upper air characteristics over two stations on the west coast of India during the occurrence of a cyclonic storm. Natural Hazards, 64(2): 1055-1078.
  24. Prein, A.F., Liu, C., Ikeda, K., Bullock, R., Rasmussen, R.M., Holland, G.J., and Clark, M. 2017. Simulating North American mesoscale convective systems with a convection-permitting climate model. Climate Dynamics.
  25. Rahman, M.M., and Lu, M. 2015. Model spin-up behavior for wet and dry basins: a case study using the Xinanjiang model. Water, 7(8), 4256-4273.
  26. Raju P.V.S., Potty J. and Mohanty, U.C. 2011. Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model. MAP, 113(3-4): 125-137.
  27. Rajeevan, M., Kesarkar, A., Thampi, S. B., Rao, T.N., Radhakrishna, B., and Rajasekhar, M. 2010. Sensitivity of WRF cloud microphysics to simulations of a severe thunderstorm event over Southeast India. In Annales geophysicae: atmospheres, hydrospheres and space sciences, 28(2), 603.
  28. Schumacher, R.S., and Johnson, R.H. 2005. Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Monthly weather review, 133(4), 961-976.
  29. Schumacher, R.S., and Johnson, R.H. 2006. Characteristics of U.S. extreme rain events during 1999–2003. Weather Forecasting, 21(1), 69–85.
  30. Sharifi, E., Steinacker, R. and Saghafian, B. 2016. Assessment of GPM-IMERG and other precipitation products against gauge data under different topographic and climatic conditions in Iran: Preliminary results. Remote Sensing, 8(2), 135.
  31. Singh, K.S., Bonthu, S., Purvaja, R., Robin, R.S., Kannan, B.A.M., and Ramesh, R. 2018. Prediction of heavy rainfall over Chennai Metropolitan City, Tamil Nadu, India: Impact of microphysical parameterization schemes. Atmospheric Research, 202, 219-234.
  32. Skamarock, W.C. 2004. Evaluating mesoscale NWP models using kinetic energy spectra. Monthly Weather Review, 132(12), 3019–3032.
  33. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D.O., Barker, D. M., Duda, M. G., and Powers, J.G. 2008. A description of the advanced research WRF version 3, vol. NCAR Technical Note, vol. NCAR/TN–475+ STR. NCAR Scientific Divisions, Boulder, Colorado, USA.
  34. Thompson, G., Field, P.R., Rasmussen, R.M. and Hall, W.D. 2008. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: implementation of a new snow parameterization. Mon. Weather. Rev, 136(12), 5095–5115.
  35. Van Weverberg, K., Vogelmann, A.M., Lin, W., Luke, E.P., Cialella, A., Minnis, P., et al. 2013. The role of cloud microphysics parameterization in the simulation of mesoscale convective system clouds and precipitation in the tropical Western Pacific. Journal of the Atmospheric Sciences, 70(4), 1104–1128.
  36. Wang, W., and Seaman, N.L. 1997. A comparison study of convective parameterization schemes in a mesoscale model, Mon. Wea. Rev. 125, 252–27.
  37. Yuter, S.E., and Houze Jr, R.A. 1998. The natural variability of precipitating clouds over the western Pacific warm pool. Quarterly Journal of the Royal Meteorological Society, 124(545), 53-99.