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Simulation and Analysis of Mesoscale Convective Systems (MCSs) Leading to a Severe Flood Over Iran

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Abstract

Simulations of mesoscale convective systems (MCSs) are conducted using the Weather Research and Forecasting (WRF) model. The considered MCSs occurred on 13 and 14 April 2016 over the west and southwest of Iran and resulted in a heavy flood. To determine the appropriate cumulus parameterization scheme to run the model, simulations of the two MCSs were performed using four nesting domains with 36-, 12-, 4-, and 1.33-km horizontal resolution by examining five cumulus parameterization schemes (CPSs) available in the WRF model for the three outer domains. The five implemented CPSs tested include Kain–Fritsch (KF), Betts–Miller–Janjic (BMJ), Grell–Devenyi (GD), improved Grell–Devenyi (G3D), and Grell–Freitas (GF) schemes. Initial fields for the simulations are taken from the Final Global Analysis (FNL) data with 1-degree horizontal resolution at 6-h time intervals. The simulations were evaluated using two available observational data sets: the Global Precipitation Measurement (GPM) satellite and synoptic station data. Comparison of the simulated 24-hourly precipitation from the second domain of the simulations (12 km) against the GPM data showed that the BMJ and GF schemes have the best performance in the simulation of 24-hourly precipitation based on the minimum values of root-mean-square error (RMSE). The comparison between in situ and the simulated precipitation from the third domain with 4-km resolution shows the great success of the GF scheme in predicting precipitation for 2 consecutive days. Regarding the dynamical analysis of the MCS of 13 April 2016, results of the simulation with 1.33-km resolution (using the GF scheme for the three outer domains) suggest that the model can explain several characteristics such as (1) the horizontal pattern of the MCS, including the convective line and stratiform precipitation region, (2) the formation of an elevated unstable moist layer and its slantwise ascent to the rear of the system, (3) the vertical structure of the MCS, and (4) the formation of a rear inflow jet and its descent to the surface under the influence of cooling processes below the stratiform cloud base.

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References

  • Agogbuo, C. N., Nwagbara, M. O., Bekele, E., & Olusegun, A. (2017). Evaluation of selected numerical weather prediction models for a case of widespread rainfall over Central and Southern Nigeria. Journal of Environmental & Analytical Toxicology, 7(491), 2161–2525.

    Google Scholar 

  • 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.

    Google Scholar 

  • Alijani, B., O’Brien, J., & Yarnal, B. (2008). Spatial analysis of precipitation intensity and concentration in Iran. Theoretical and Applied Climatology, 94(1), 107–124.

    Google Scholar 

  • Azadi, M., Taghizadeh, E., Memarian, M. H., & Dmitrieva-Arrago, L. R. (2013). Comparing the results of precipitation forecast based on mesoscale models on the territory of Iran during the cold season. Russian Meteorology and Hydrology, 38(9), 605–613.

    Google Scholar 

  • Ban, N., Schmidli, J., & Schär, C. (2014). Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. Journal of Geophysical Research: Atmospheres, 119(13), 7889–7907.

    Google Scholar 

  • Betts, A. K., & Miller, M. J. (1986). A new convective adjustment scheme. Part II: Single column tests using GATE wave BOMEX ATEX and arctic air-mass data sets. Quarterly Journal of the Royal Meteorological Society, 112(473), 693–709. https://doi.org/10.1002/qj.49711247308

    Article  Google Scholar 

  • Bryan, G. H., Wyngaard, J. C., & Fritsch, J. M. (2003). Resolution requirements for the simulation of deep moist convection. Monthly Weather Review, 131(10), 2394–2416.

    Google Scholar 

  • Chen, F., & Dudhia, J. (2001). Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review, 129(4), 569–585.

    Google Scholar 

  • Choi, H. Y., Ha, J. H., Lee, D. K., & Kuo, Y. H. (2011). Analysis and simulation of mesoscale convective systems accompanying heavy rainfall: The Goyang case. Asia-Pacific Journal of Atmospheric Sciences, 47(3), 265–279.

    Google Scholar 

  • Choi, I. J., Jin, E. K., Han, J. Y., Kim, S. Y., & Kwon, Y. (2015). Sensitivity of diurnal variation in simulated precipitation during East Asian summer monsoon to cumulus parameterization schemes. Journal of Geophysical Research: Atmospheres, 120(23), 11–971.

    Google Scholar 

  • Collier, C.G. (2000). Precipitation estimation and forecasting (No. 46). Secretariat to World Meteorological Organization.

  • Das, M. K., Chowdhury, M. A. M., & Das, 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.

    Google Scholar 

  • Das, S., Ashrit, R., Moncrieff, M. W., Das Gupta, M., Dudhia, J., Liu, C., & Kalsi, S. R. (2007). Simulation of intense organized convective precipitation observed during the Arabian Sea Monsoon Experiment (ARMEX). Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2006JD007627

    Article  Google Scholar 

  • Duda, J.D. (2011). WRF simulations of mesoscale convective systems at convection-allowing resolutions. M.S. thesis, Dept. of Geological and Atmospheric Sciences, Iowa State University, 115 pp.

  • Dudhia, J. (1989). Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. Journal of Atmospheric Sciences, 46(20), 3077–3107.

    Google Scholar 

  • Dudhia, J., Weisman, M.L., Skamarock, W.C., & Wang, W. (2003). February. Studies of heavy rainfall in the United States with WRF. In International workshop on NWP models for heavy precipitation in Asia and Pacific areas, Tokyo (pp. 4–6).

  • Fritsch, J. M., Kane, R. J., & Chelius, C. R. (1986). The contribution of mesoscale convective weather systems to the warm-season precipitation in the United States. Journal of Applied Meteorology and Climatology, 25(10), 1333–1345.

    Google Scholar 

  • Gilliland, E.K. and Rowe, C.M. (2007). A comparison of cumulus parameterization schemes in the WRF model. In Proceedings of the 87th AMS Annual Meeting & 21th Conference on Hydrology (vol. 2).

  • Giovannini, L., Davolio, S., Zaramella, M., Zardi, D., & Borga, M. (2021). Multi-model convection-resolving simulations of the October 2018 Vaia storm over Northeastern Italy. Atmospheric Research, 253, 105455.

    Google Scholar 

  • Grell, G. A. (1993). Prognostic evaluation of assumptions used by cumulus parameterizations. Monthly Weather Review, 121(3), 764–787. https://doi.org/10.1175/1520-0493(1993)121<0764:PEOAUB>2.0.CO;2

    Article  Google Scholar 

  • Grell, G. A., & Dévényi, D. (2002). A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophysical Research Letters, 29(14), 38-1–38-4. https://doi.org/10.1029/2002GL015311

    Article  Google Scholar 

  • Grell, G. A., & Freitas, S. R. (2014). A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmospheric Chemistry and Physics, 14(10), 5233–5233. https://doi.org/10.5194/acp-14-5233-2014

    Article  Google Scholar 

  • Guo, Z., Fang, J., Sun, X., Yang, Y., & Tang, J. (2019). Sensitivity of summer precipitation simulation to microphysics parameterization over Eastern China: Convection-permitting regional climate simulation. Journal of Geophysical Research: Atmospheres, 124(16), 9183–9204.

    Google Scholar 

  • Houze, R. A., Jr. (2004). Mesoscale convective systems. Reviews of Geophysics, 42, RG4003.

    Google Scholar 

  • Houze, R. A., Jr., Lee, W. C., & Bell, M. M. (2009). Convective contribution to the genesis of Hurricane Ophelia (2005). Monthly Weather Review, 137(9), 2778–2800.

    Google Scholar 

  • Irannejad, P., Ahmadi-Givi, F., & Pazouki, R. (2009). The role of convection parameterization in the simulation of the winter temperature and precipitation fields over Iran using Regional Climate Model (RegCM3). Journal of the Earth and Space Physics, 35(1), 101–120.

    Google Scholar 

  • Janjic, Z. I. (1990). The step-mountain coordinate: Physical package. Monthly Weather Review, 118(7), 1429–1443.

    Google Scholar 

  • Janjic, Z. I. (1994). The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Monthly Weather Review, 122(5), 927–945.

    Google Scholar 

  • Janjic, Z. I. (1996). The Mellor-Yamada level 2.5 turbulence closure scheme in the NCEP Eta Model. WORLD METEOROLOGICAL ORGANIZATION-PUBLICATIONS-WMO TD, (pp. 4–14).

  • Janjić, Z. I. (2000). Comments on “Development and evaluation of a convection scheme for use in climate models”. Journal of the Atmospheric Sciences, 57(21), 3686. https://doi.org/10.1175/1520-0469(2000)057<3686:CODAEO>2.0.CO;2

    Article  Google Scholar 

  • Kain, J. S. (2004). The Kain–Fritsch convective parameterization: An update. Journal of Applied Meteorology, 43(1), 170–181. https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2

    Article  Google Scholar 

  • Kain, J. S., Weiss, S. J., Bright, D. R., Baldwin, M. E., Levit, J. J., Carbin, G. W., Schwartz, C. S., Weisman, M. L., Droegemeier, K. K., Weber, D. B., & Thomas, K. W. (2008). Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP. Weather and Forecasting, 23(5), 931–952.

    Google Scholar 

  • Kerkhoven, E., Gan, T. Y., Shiiba, M., Reuter, G., & 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.

    Google Scholar 

  • Kumar, S., Routray, A., Chauhan, R., & 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, 1(1), 18–34.

    Google Scholar 

  • Laing, A.G. (2003). Mesoscale meteorology/mesoscale convective systems. In J.R. Holton (Ed.), Encyclopedia of Atmospheric Sciences (pp. 1251–1261).

  • Lean, H. W., Clark, P. A., Dixon, M., Roberts, N. M., Fitch, A., Forbes, R., & Halliwell, C. (2008). Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Monthly Weather Review, 136(9), 3408–3424.

    Google Scholar 

  • Li, L., Li, W., & Jin, J. (2014). Improvements in WRF simulation skills of southeastern United States summer rainfall: Physical parameterization and horizontal resolution. Climate Dynamics, 43(7–8), 2077–2091.

    Google Scholar 

  • Lin, Y. L., Farley, R. D., & Orville, H. D. (1983). Bulk parameterization of the snow field in a cloud model. Journal of Climate and Applied Meteorology, 22(6), 1065–1092.

    Google Scholar 

  • Litta, A. J., Idicula, S. M., & Mohanty, U. C. (2011). A comparative study of convective parameterization schemes in WRF-NMM model. International Journal of Computer Applications, 33(6), 32–39.

    Google Scholar 

  • Liu, Y., Chen, F., Warner, T., & Basara, J. (2006). Verification of a mesoscale data-assimilation and forecasting system for the Oklahoma City area during the Joint Urban 2003 field project. Journal of Applied Meteorology and Climatology, 45(7), 912–929.

    Google Scholar 

  • Mellor, G. L., & Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4), 851–875.

    Google Scholar 

  • Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., & Clough, S. A. (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14), 16663–16682.

    Google Scholar 

  • Panda, J., & 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.

    Google Scholar 

  • Parker, M. D., & Johnson, R. H. (2000). Organizational modes of midlatitude mesoscale convective systems. Monthly Weather Review, 128(10), 3413–3436.

    Google Scholar 

  • Prein, A. F., Liu, C., Ikeda, K., Bullock, R., Rasmussen, R. M., Holland, G. J., & Clark, M. (2017). Simulating North American mesoscale convective systems with a convection-permitting climate model. Climate Dynamics. https://doi.org/10.1007/s00382-017-3993-2

    Article  Google Scholar 

  • Rajeevan, M., Kesarkar, A., Thampi, S.B., Rao, T.N., Radhakrishna, B., & Rajasekhar, M. (2010). Sensitivity of WRF cloud microphysics to simulations of a severe thunderstorm event over Southeast India. In Annales Geophysicae (Vol. 28, No. 2, pp. 603–619).

  • Raju, P. V. S., Potty, J., & Mohanty, U. C. (2011). Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model. Meteorology and Atmospheric Physics, 113(3–4), 125.

    Google Scholar 

  • Schumacher, R. S., & Johnson, R. H. (2005). Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Monthly Weather Review, 133(4), 961–976.

    Google Scholar 

  • Schumacher, R. S., & Johnson, R. H. (2006). Characteristics of US extreme rain events during 1999–2003. Weather and Forecasting, 21(1), 69–85.

    Google Scholar 

  • Schwartz, C. S., Kain, J. S., Weiss, S. J., Xue, M., Bright, D. R., Kong, F., Thomas, K. W., Levit, J. J., Coniglio, M. C., & Wandishin, M. S. (2010). Toward improved convection-allowing ensembles: Model physics sensitivities and optimizing probabilistic guidance with small ensemble membership. Weather and Forecasting, 25(1), 263–280.

    Google Scholar 

  • Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X., Wang, W., & Powers, J.G. (2008). Ncar technical note: A description of the advanced research wrf version 3 (ncar/tn-475+ str). Boulder, Colorado, USA: Nacional Center for Atmospheric Research.

  • Tadesse, A., & Anagnostou, E. N. (2009). Characterization of warm season convective systems over US in terms of cloud to ground lightning, cloud kinematics, and precipitation. Atmospheric Research, 91(1), 36–46.

    Google Scholar 

  • Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106(D7), 7183–7192.

    Google Scholar 

  • Wang, W., & Seaman, N. L. (1997). A comparison study of convective parameterization schemes in a mesoscale model. Monthly Weather Review, 125(2), 252–278.

    Google Scholar 

  • Weisman, M. L., Davis, C., Wang, W., Manning, K. W., & Klemp, J. B. (2008). Experiences with 0–36-h explicit convective forecasts with the WRF-ARW model. Weather and Forecasting, 23(3), 407–437.

    Google Scholar 

  • Yang, M. J., & Tung, Q. C. (2003). Evaluation of rainfall forecasts over Taiwan by four cumulus parameterization schemes. Journal of the Meteorological Society of Japan Ser II, 81(5), 1163–1183.

    Google Scholar 

  • Yavinchan, S., Exell, R. H., & Sukawat, D. (2011). Convective parameterization in a model for the prediction of heavy rain in southern Thailand. Journal of the Meteorological Society of Japan. Ser. II, 89, 201–224.

    Google Scholar 

  • Yu, X., & Lee, T. Y. (2010). Role of convective parameterization in simulations of a convection band at grey-zone resolutions. Tellus a: Dynamic Meteorology and Oceanography, 62(5), 617–632.

    Google Scholar 

  • Yuter, S. E., & Houze, R. A., Jr. (1998). The natural variability of precipitating clouds over the western Pacific warm pool. Quarterly Journal of the Royal Meteorological Society, 124(545), 53–99.

    Google Scholar 

  • Zepka, G. S., Azambuja, R. R., Vargas Jr, V. R., Saraiva, A. C. V., & Pinto Jr, O. (2014). Predicting Heavy Precipitation and Lightning for a Mesoscale Convective System Case Over Southern Brazil.

  • Zeyaeyan, S., Fattahi, E., Ranjbar, A., Azadi, M., & Vazifedoust, M. (2017). Evaluating the effect of physics schemes in WRF simulations of summer rainfall in north west Iran. Climate, 5(3), 48.

    Google Scholar 

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Acknowledgements

The authors would like to thank Dr. Alireza Mahmoudian for his help in editing the manuscript.

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  1. Institute of Geophysics, University of Tehran, Post Box: 14155-6466, Tehran, Islamic Republic of Iran

    Masoomeh Ahmadloo, Maryam Gharaylou & Majid M. Farahani

  2. Atmospheric Sciences Research Center, Iranian National Institute for Oceanography and Atmospheric Science, Tehran, Iran

    Nafiseh Pegahfar

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  1. Masoomeh Ahmadloo
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Ahmadloo, M., Gharaylou, M., Farahani, M.M. et al. Simulation and Analysis of Mesoscale Convective Systems (MCSs) Leading to a Severe Flood Over Iran. Pure Appl. Geophys. 179, 1485–1507 (2022). https://doi.org/10.1007/s00024-022-02983-4

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