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Investigation of aerosol effects on the development of supercell storm using the WRF Double-Moment (WDM) microphysics sc

Investigation of aerosol effects on the development of supercell storm using the WRF Double-Moment (WDM) microphysics schemes Kyo-Sun Sunny Lim 1, Song-You Hong 1 , Seong-Soo Yum 1 , and Jimy Dudhia 2 1 Department of Atmospheric Sciences, Yonsei University, Seoul, Korea

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Investigation of aerosol effects on the development of supercell storm using the WRF Double-Moment (WDM) microphysics sc

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  1. Investigation of aerosol effects on the development of supercell storm using the WRF Double-Moment (WDM) microphysics schemes Kyo-Sun Sunny Lim1, Song-You Hong1, Seong-Soo Yum1, and Jimy Dudhia2 1Department of Atmospheric Sciences, Yonsei University, Seoul, Korea 2Mesoscale and Microscale Meteorology Division/NCAR, Boulder, Colorado, USA

  2. Introduction

  3. Convective storm structure • Impressive progress in understanding convective storm structure and convective weather precipitation has been made after the pioneering work of Schlesinger (1975) as well as Klemp and Wilhelmson (1978). • Li et al. (2008) stressed that graupel plays an important role in the Mesoscale Convective System (MCS)during the Kwajalein Experiment (KWAJEX) simulation because conversion processes of graupel are a significant component of latent heat release, which in turn has a significant impact on the dynamic, thermodynamic, and precipitation characteristics of the evolving MCS. Also, the greater fall speed of graupel compared to low-density ice particles allows graupel to remain suspended in strong updrafts longer and to fall out of weak updrafts faster. • Zhu and Zhang (2006) also mentioned the importance of the Bergeron processes, including the growth and rapid fallout of graupel in the eyewall, and the latent heat of fusion in determining the intensity and inner-core structures of hurricanes

  4. Aerosol Effects on precipitation • Cloud–aerosol interaction isincreasingly recognized as one of the key factors controlling precipitation regimeon local, meso-, and even global scales (Khain et al. 2005, 2008). • Even though the effect of aerosols on precipitation may be complex function of aerosol properties and cloud thermodynamics (Kain et al. 2005), several modeling studies with a graupel contained microphysics schemes show that the total precipitation amount increases with a decrease in the cloud condensation nuclei (CCN) number concentration in a deep convective storm simulation (Resin et al. 1996; Khain and Pokrovsky 2004).

  5. Purpose of this study • Investigating the aerosol effects on the development of supercell storm, focusing on the storm morphology and precipitation using the double-moment bulk microphysics scheme. • The Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) Microphysics scheme has been developed and evaluated on an idealized two-dimensional thunderstorm testbed and on a three-dimensional heavy rainfall case (Lim and Hong 2009). The WDM6 scheme makes it possible to investigate the aerosol effects on cloud properties and precipitation process with prognostic variables of CCN, cloud water, and rain. • The mixed phase WRF Double-Moment 5-class Microphysics (WDM5) scheme is also tested under the varying CCN number concentration. The WDM5 microphysics scheme, which includes the cloud water, rain, ice, and snow substances, also predicts the number concentrations for cloud and rain waters with a prognostic variable of the CCN number concentration.

  6. Warm rain processes : (Khairoutdinov and Kogan, 2000; Cohardt and Pinty, 2000) Cold rain processes : (Hong et al.,2004; Hong and Lim 2006) CCN Ice Vapor Cloud water RAIN Vapor Snow N,q for 2 hydrometeors will be predicted (Double Moment) Graupel q for 4 hydrometeors will be predicted (Single Moment) WDM6 The WRF Double-Moment 6-class (WDM6) Microphysics scheme • Flow chart of the microphysical processes in the WRF Single-Moment 6-class (WSM6) Microphysics scheme

  7. Warm rain processes : (Khairoutdinov and Kogan, 2000; Cohardt and Pinty, 2000) Cold rain processes : (Hong et al.,2004; Hong and Lim 2006) CCN Ice Vapor Cloud water RAIN Snow N,q for 2 hydrometeors will be predicted (Double Moment) Vapor q for 3 hydrometeors will be predicted (Single Moment) WDM5 The WRF Double-Moment 5-class (WDM5) Microphysics scheme • Flow chart of the microphysical processes in the WRF Single-Moment 5-class (WSM5) Microphysics scheme

  8. І. Ideal Case Simulation

  9. Numerical Experimental Setup

  10. Experimental Design Case 3D idealized supercell thunderstorm Grid: Both directions comprised 81 points with a 2 km grid spacing. The number of vertical layers was 40. Integration Time: 2 hours with a time step of 12 seconds. Physics MPS: WDM6 and WDM5 (Lim and Hong 2009) PBL : Yonsei University (YSU) (Hong et al. 2006) SW : A simple cloud-interactive (Dudhia 1989) LW : Rapid Radiative Transfer Model (RRTM) (Mlawer et al. 1997) Surface temperature is not predicted without any surface model.

  11. Experimental Design Sensitivity Experiment • Impact of the initial aerosol concentration on the development of supercell storm is evaluated by varying the number and mass of aerosols, as is reflected in the changes in the number concentrations of CCN. • Simulations were initiated with the six different initial CCN number concentrations from 10 cm-3 to 104 cm-3with the both WDM6 and WDM5 microphysics scheme, respectively. • An additional sensitivity experiment, the WDM6(VG) experiment, was performed to explore the effect of faster sedimentation velocity of graupel than that of snow. In the WDM6(VG) experiment, the value of VDGis replaced with that of VDS. The density of graupel is also replaced by the value of snow. Summary of conducted sensitivity experiments

  12. Previous Study • Simulated Storm structure using the Klemp-Wilhelmson (1978) numerical cloud model • Skew-T-log-P plot of temperature and dew point profiles • Hodograph and simulated storm structure at 40, 80, 120 min for the right-flank supercell from Weisman and Klemp (1984)

  13. CCN Effects : • Results with the WDM6 microphysics scheme

  14. Storm structure (Low level rain water fields, maximum vertical velocities, and surface wind) WDM6_CCN1 WDM6_CCN2 WDM6_CCN3 WDM6_CCN4 Weisman and Klemp (1984) The WDM6_CCN2 run shows similar storm structure with that in the Weisman and Klemp (1986). More sporadic rain water field near the eyewall of simulated storm

  15. Cloud Properties Effective Cloud Droplet Size Cloud Droplet Number Concentration (CNC) More activation of aerosols A large number of cloud droplets are competing for a fixed amount of available water vapor Rain Drop Number Concentration (RNC) Effective Rain Drop Size A large number of small cloud droplets hinder the effective autoconversion process

  16. Vertical Profiles of Hydrometeors • The effective radius of cloud droplets is reduced with an increasing CCN number concentration, hindering the conversion of cloud droplets to raindrops. • A largest graupel mass occurs in the lowest CCN number concentration case because a large amount of raindrops is transported and frozen in the cold cloud regime.

  17. Accumulated Precipitation WDM6_CCN1 WDM6_CCN2 Reduced precipitation! (Resin et al. 1996; Khain and Pokrovsky 2004; Li et al. 2008) • The reduced precipitation with increasing aerosol is explained by • suppressed conversion of cloud droplets to raindrops and • reduced convective strength over the strong convective core region WDM6_CCN3 WDM6_CCN4

  18. Cross section :Hydrometeors and Wind WDM6_CCN1 WDM6_CCN2 • Well organized convective cell • Graupel can hang over the strong updraft regions. WDM6_CCN3 Exaggerated snow-mass loading WDM6_CCN4 Reduced rainfall amount over the heavy precipitation region and increased one over the over the eyewall region

  19. 2-1. Graupel Effects : Results with the WDM5 microphysics scheme

  20. Importance of Graupel Species in Simulating Convective Clouds Numerical Modeling Studies • Li et al. (2008) stressed that graupel plays an important role in the Mesoscale Convective System (MCS) during the Kwajalein Experiment (KWAJEX) simulation because conversion processes of graupel are a significant component of latent heat release, which in turn has a significant impact on the dynamic, thermodynamic, and precipitation characteristics of the evolving MCS. Also, the greater fall speed of graupel compared to low-density ice particles allows graupel to remain suspended in strong updrafts longer and to fall out of weak updrafts faster. • Zhu and Zhang (2006) also mentioned the importance of the Bergeron processes, including the growth and rapid fallout of graupel in the eyewall, and the latent heat of fusion in determining the intensity and inner-core structures of hurricanes • Houze et al. (1992) found the development of the significant amount of graupel in the updrafts region in Hurricane Norbert (1984) though the mapping and interpolating data collected on board a WP-3D aircraft. To confirm the graupel effects in simulating convective storm cell, the WDM5 microphysics are implemented and tested. Observational Study

  21. Storm structure (Low level rain water fields, maximum vertical velocities, and surface wind) WDM5_CCN1 WDM5_CCN2 Weisman and Klemp (1984) WDM5_CCN3 WDM5_CCN4 WDM6_CCN4 • Hook type storm structure • Similar storm structure irrespective of CCN number

  22. Cloud Properties Effective Cloud Droplet Size Cloud Droplet Number Concentration (CNC) Rain Drop Number Concentration (RNC) Effective Rain Drop Size Large differences in the magnitude of rain drop diameter under varying CCN number concentration in the WDM5

  23. Vertical Profiles of Hydrometeors • Without inclusion of graupel, the snow portion of the whole hydrometeors increases • A largest mixing ratio of snow reveals in the lowest CCN number concentration case because of the frozen process of more amount of rain water. WDM6

  24. Accumulated Precipitation WDM5_CCN1 WDM5_CCN2 Increased precipitation! (Lynn et al. 2005; Khain et al. 2005; Lee et al. 2008 ) WDM5_CCN3 WDM5_CCN4 Increased precipitation at high aerosol: due to stronger, more numerous updraughts, initiated by stronger convergence lines.

  25. Cross section :Hydrometeors and Wind WDM5_CCN1 WDM5_CCN2 • Ambiguous separation between the stratiform and convective core region WDM5_CCN3 Increased CCN nucleation with more evaporation and stronger convergence WDM5_CCN4 Increased rainfall amount along the convection region

  26. 2-2. Graupel Effects : Results with the WDM6(VG) experiment

  27. Sensitivity Experiment : WDM6(VG) • Accumulated Precipitation • Storm Structure WDM6(VG)_CCN2 WDM5_CCN2 Increased precipitation! • Cross section (Hydrometeors and Wind) Similar Responses with the WDM5 microphysics scheme under varying CCN number concentration WDM6(VG)_CCN2 WDM5_CCN2 Denser graupel with relatively strong sedimentation velocity is essential for maintaining the observed supecell storm structure.

  28. Ⅱ. Real Case Simulation

  29. Precipitation Observation OBS (TMPA) Statistics [WDM6] Bias (mm): 23.95 RMSE (mm): 151.5 PC: 0.66 [WDM5] Bias (mm): 24.27 RMSE (mm): 149.7.5 PC: 0.63 WDM6 WDM5

  30. CCN Effects on Precipitation WDM6 WDM5 The total precipitation decreases sharply when the CCN number concentration is over 103 cm-3 with the WDM6 microphysics scheme but increases with the WDM5 microphysics scheme. Similar Responses with the ideal case simulation!!

  31. Concluding Remarks • The aerosol effects on the development of supercell storm were investigated using the double-moment microphysics schemes focusing on the storm morphology and precipitation. • The reason for the different storm structure and aerosol effects between the WDM6 and WDM5 microphysics schemes can be deduced from the existence of graupelin the bulk microphysics representation. • Without graupel, supercell storm structure is poorly captured and CCN effects are not correctly represented within the WDM5 microphysics scheme. The WDM6_VG experiment also confirms the importance of graupel in simulating the supercell storm. • To understand the aerosol effects properly within the GCM, more sophisticated and refined microphysical processes including the graupel quantity is demandable. Accurate treatment of aerosol related to the precipitation process is also needed.

  32. Thank you !! E-mail : klim@yonsei.ac.kr

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