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The Impact of Microphysical Schemes on Hurricane Intensity and Track Asia-Pacific J. Atmos. Sci. 47(1), 1-16, 2011 DOI:10.1007/s13143-011-1001-z The Impact of Microphysical Schemes on Hurricane Intensity and Track Wei-Kuo Tao1, Jainn Jong Shi1,2, Shuyi S. Chen3, Stephen Lang1,4, Pay-Liam Lin5, Song-You Hong6, Christa Peters-Lidard7 and Arthur Hou8 1Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA 2Goddard Earth Sciences and Technology Center, University of Maryland at Baltimore County, Maryland, USA 3Rosentiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA 4Science Systems and Applications, Inc., Lanham, Maryland, USA 5Department of Atmospheric Science, National Central University, Jhong-Li, Taiwan, R.O.C. 6Department of Atmospheric Sciences and Global Environment Laboratory, Yonsei University, Seoul, Korea 7Hydrological Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA 8Goddard Modeling Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA (Manuscript received 5 February 2010; revised 11 June 2010; accepted 6 July 2010) © The Korean Meteorological Society and Springer 2011 Abstract: During the past decade, both research and operational 1. Introduction numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex micro- Advances in computing power allow atmospheric prediction physical schemes originally developed for high-resolution cloud re- models to be run at progressively finer scales of resolution, using solving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation increasingly more sophisticated physical parameterizations and system. It incorporates a modern software framework, advanced dy- numerical methods. The representation of cloud microphysical namics, numerics and data assimilation techniques, a multiple move- processes is a key component of these models. Over the past able nesting capability, and improved physical packages. WRF can be decade both research and operational numerical weather predic- used for a wide range of applications, from idealized research to tion (NWP) models [i.e., the Fifth-generation National Center operational forecasting, with an emphasis on horizontal grid sizes in the for Atmospheric Research (NCAR) - Penn State University Mes- range of 1-10 km. The current WRF includes several different micro- oscale Model (MM5), the National Centers for Environmental physics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these Prediction (NCEP) Eta, and the Weather Research and Fore- schemes is compared to those of the other microphysics schemes casting Model (WRF)] have started using more complex available in WRF for an Atlantic hurricane case (Katrina). In addition, microphysical schemes that were originally developed for high- a brief review of previous modeling studies on the impact of resolution cloud-resolving models (CRMs). CRMs, which are microphysics schemes and processes on the intensity and track of run at horizontal resolutions on the order of 1-2 km or finer, can hurricanes is presented and compared against the current Katrina study. simulate explicitly complex dynamical and microphysical pro- In general, all of the studies show that microphysics schemes do not cesses associated with deep, precipitating atmospheric convection. have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies A recent report to the United States Weather Research Program found that simulated hurricanes had the strongest deepening or (USWRP) Science Steering Committee specifically calls for the intensification when using only warm rain physics. This is because all replacement of implicit cumulus parameterization schemes with of the simulated precipitating hydrometeors are large raindrops that explicit bulk schemes in NWP as part of a community effort to quickly fall out near the eye-wall region, which would hydrostatically improve quantitative precipitation forecasts (QPF, Fritsch and produce the lowest pressure. In addition, these studies suggested that Carbone, 2002). intensities become unrealistically strong when evaporative cooling There is no doubt that cloud microphysics play an important from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated storms. However, role in non-hydrostatic high-resolution simulations as evidenced there are many differences between the different modeling studies, by the extensive amount of research devoted to the development which are identified and discussed. and improvement of cloud microphysical schemes and their application to the study of precipitation processes, hurricanes and Key words: Hurricane, microphysics, high-resolution modeling, other severe weather events over the past two and a half decades precipitation processes (see Table 1). Many different approaches have been used to examine the impact of microphysics on precipitation processes associated with convective systems*. For example, ice phase schemes were developed in the 80’s (Lin et al., 1983; Cotton et Corresponding Author: Dr. Wei-Kuo Tao, Code 613.1, NASA/GSFC, Greenbelt, MD 20771, USA. *The effects of aerosols [see a brief review by Tao et al. (2007)] on E-mail: [email protected] microphysical (processes) schemes have also been studied. 2 ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES Table 1. Key papers using high-resolution numerical cloud models (including those that developed new improved microphysical schemes) to study the impact of microphysical schemes on precipitation. Model type (2D or 3D), microphysical scheme (one moment or multi-moment bulk), resolution (km), number of vertical layers, time step (seconds), case and integration time (hours) are all listed. Papers with a “*” are used for comparison with the present study, papers with a “#” denote development of a new scheme, papers with a “$” modify/improve existing schemes, papers with a “&” compare different schemes, and papers with a “%” indicate process (budget) studies. TCM3 stands for the “Tropical Cyclone Model with triple nested movable mesh”. Also only papers with bulk schemes are listed. Resolutions Key Papers Model Microphysics Integration Time Case Vertical Layers Lin et al. (1983) 2D 3-ICE 200 m/95 48 min Hail Event Montana Cotton et al. Orographic 2D 3-ICE & Ni 500 m/31 5 hours (1982, 1986) Snow Rutledge and Hobbs 2D 3-ICE 600 m/20 Steady State Narrow Cold Front (1984) Kinematics * 2D Lord et al. (1984) 3-ICE vs Warm Rain 2 km/20 4.5 days Idealized axisymmetric # 2D 3-ICE scheme vs Warm 12 September GATE Yoshizaki (1986) 0.5 km/32 4.5 hours slab-symmetric Rain Squall Line 2D 12 September GATE Nicholls (1987) 3-ICE vs Warm Rain 0.5 km/25 5 hours slab-symmetric Squall Line Fovell and Ogura 2D #% 3-ICE vs Warm Rain 1 km/31 10 hours Mid-latitude Squall Line (1988) slab-symmetric Tao and Simpson 2D # 3-ICE vs Warm Rain 1 km/31 12 hours GATE Squall Line (1989, 1993) and 3D Tao et al. (1990) 2D 3-ICE 1 km/31 12 hours GATE Squall Line McCumber et al. 2D 3-ICE scheme (graupel %$ 12 hours GATE Squall Line (1991) and 3D vs hail, 2ICE vs 3ICE) 1 km/31 2D Wu et al. (1999) 2 ICE 3 km/52 39 days TOGA COARE slab-symmetric Ferrier (1994), 2D COHMEX, GATE # 2-moment 4-ICE 1 km/31 12 hours Ferrier et al. (1995) slab-symmetric Squall Line 2D Tao et al. (1995) 3-ICE 0.75 and 1 km/31 12 hours EMEX, PRESTORM slab-symmetric Walko et al. (1995)# 2D 4-ICE 0.3 km/80 30 min Idealized Meyers et al. (1997)#$ 2D 2-moment 4-ICE 0.5 km/80 30 min Idealized Straka and Mansell # 3D 10-ICE 0.5 km/30? ~2 hours Idealized (2005) Lang et al. (2007)$ 3D 3-ICE .25 to 1km /41 8 hours LBA Zeng et al. (2008)$ 2D and 3D 3-ICE 1 km/41 40 days SCSMEX, KWAJEX Milbrandt and Yau # 1D Three-moment /51 50 minutes Idealized Hail Storm (2005) # Two moments and Single column model 27 SHEBA Morrison et al. (2005) Single column model 3 days 2-ICE layers FIRE-FACE Morrison and # 2D Two-moment ICE 50 m/60 90 minutes Idealized Grabowski (2008) # MM5 3-ICE and 2-moment Reisner et al. (1998) 2.2 km/27 6 hours (2.2 km grid) Winter Storms Non-hydrostatic for ICE # MM5 Thompson et al. (2004) 3-ICE 10 km/39 3 hours Idealized 2D $ WRF Thompson et al. (2008) 3-ICE 10 km/39 6 hours Idealized 2D MM5 Colle and Mass (2000) 3-ICE 1.33 km/38 96 hours Orographic Flooding Non-hydrostatic % 2-D MM5 Colle and Zeng (2004) 3-ICE 1.33 km/39 12 hours Orographic Non-hydrostatic % MM5 Colle et al. (2005) 3-ICE 1.33 km/320 36 hours IMPROVE Non-hydrostatic 31 January 2011 Wei-Kuo Tao et al. 3 Table 1. (Continued) Resolutions Key Papers Model Microphysics Integration Time Case Vertical Layers * MM5 Yang and Ching (2005) 3-ICE 6.67 km/23 2.5 days Typhoon Toraji (2001) Non-hydrostatic * MM5 Zhu and Zhang (2006b) 3-ICE 4 km/24 5 days Bonnie (1998) Non-hydrostatic Wang (2002)* TCM3-hydrostatic 3-ICE 5 km/21 5 days Idealized # WRF Korean Heavy Rainfall Hong et al. (2004) 3-ICE 45 km/23 48 hours Non-hydrostatic event * WRF Li and Pu (2008) 2-ICE and 3-ICE 3 km/31 1.25 days Hurricane Emily (2005) Non-hydrostatic Jankov et al. WRF 2-ICE and * 12 km/31 1 day IHOP (2005, 2007) Non-hydrostatic 3ICE *** WRF Korean Heavy Snow Dudhia et al. (2008) 3-ICE 5 km/31 1.5 days Non-hydrostatic event WRF 2-ICE and 1km/31 1.5 days IHOP and Hurricane Tao et al. - Present study Non-hydrostatic 3ICE 1.667 km/31 3 days Katrina (2005) al., 1982, 1986; Rutledge and Hobbs, 1984), and the impact of (2005) determined that condensation, snow deposition, accretion those ice processes on precipitation processes associated with of cloud water by rain and melting are important processes deep convection were investigated (Yoshizaki, 1986; Nicholls, associated with orographic precipitation events.
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