Research Progress on Physical Parameterization Schemes in Numerical Weather Prediction Models
First author:Ma Leiming (1975-), male,Shihezi City, Xinjiang Province, Professor. Research areas include numerical prediction, tropical cyclone, and atmospheric dynamics.E-mail:malm@mail.typhoor.gov.cn
Received date: 2017-04-18
Revised date: 2017-06-20
Online published: 2017-07-20
Supported by
Project supported by the National Natural Science Foundation of China “Study on dominant physical mechanism and parameterization for deep convection affected by atmosphere in mid-level troposphere”(No.41475059);Special Project of National Key Research and Development Program of China “Observation on weather conditions for air pollution in China eastern city group and construction on related large data platform”(No.2016YFC0201900)
Copyright
Atmospheric physics in numerical weather prediction model which predominantly determines the evolution of atmospheric processes is mainly described by physical parameterization. As a result, the development of physical parameterization has been a hot research issue in the area of numerical prediction for a long time. In this regard, the theoretical background and history of physical parameterization schemes for convection, microphysics, and planetary boundary layer, were reviewed in this study. It is suggested that the advance of physical parameterization for the model with high-resolution grid spaces should be considered as a principle issue for numerical model development in the future. Although the gird spaces in current operational numerical models generally decrease toward 10 km owing to the rapid development of high-performance computation, yet most of these schemes are designed for coarse grid spaces. Because of this kind of deficiency, the theoretical basis of these schemes inevitably faces controversy. Directions for development of physical parameterization were also suggested according to the trends of research in numerical prediction.
Leiming Ma , Xuwei Bao . Research Progress on Physical Parameterization Schemes in Numerical Weather Prediction Models[J]. Advances in Earth Science, 2017 , 32(7) : 679 -687 . DOI: 10.11867/j.issn.1001-8166.2017.07.0679
| [1] | Schwartz C S, Kain J S, Weiss S J, et al.Next-dayconvection-allowing WRF model guidance: A second look at 2-km versus 4-km grid spacing[J].Monthly Weather Review, 2009, 137: 3 351-3 372, doi: 10.1175/2009MWR2924.1. |
| [2] | Weusthoff T, Ament F, Arpagaus M, et al.Assessing the benefits of convection-permitting models by neighborhood verification: Examples from MAP D-PHASE[J]. Monthly Weather Review, 2010, 138: 3 418-3 433, doi:10.1175/2010MWR3380.1. |
| [3] | Satoh M, Matsuno T, Tomita H, et al.Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for global cloud resolving simulations[J].Journal of Computational Physics, 2008, 227(7): 3 486-3 514. |
| [4] | Miyamoto Y, Kajikawa Y, Yoshida R, et al.Deep moist atmospheric convection in a subkilometer global simulation[J].Geophysical Research Letters, 2013, 40(18): 4 922-4 926. |
| [5] | Grabowski W W, Smolarkiewicz P K.A cloud resolving convection parameterization for modeling the tropical convecting atmosphere[J].Physica D, 1999, 133(1): 171-178. |
| [6] | Randall D, Khairoutdinov M, Arakawa A, et al.Breaking the cloud parameterization deadlock[J].Bulletin of the American Meteorological Society, 2003, 84: 1 547-1 564, doi:10.1175/BAMS-84-11-1547. |
| [7] | Pritchard M S, Moncrieff M W, Somerville R C.Orogenic propagating precipitation systems over the United States in a global climate model with embedded explicit convection[J].Journal of the Atmospheric Sciences, 2011, 68(8): 1 821-1 840. |
| [8] | Kooperman G J, Pritchard M S, Somerville R C.Robustness and sensitivities of central US summer convection in the super-parameterized CAM: Multi-model intercomparison with a new regional EOF index[J].Geophysical Research Letters, 2013, 40(12): 3 287-3 291. |
| [9] | Schmidt F.Variable fine mesh in spectral global model[J].Beitraege zur Physik der Atmosphaere, 1977, 50: 211-217. |
| [10] | Skamarock W C, Klemp J B, Duda M G, et al.A multiscale nonhydrostatic atmospheric model using centroidal voronoi tesselations and C-grid staggering[J].Monthly Weather Review, 2012, 140: 3 090-3 105,doi:10.1175/MWR-D-11-00215.1. |
| [11] | Tang Y, Lean H W, Bornemann J.The benefits of the met office variable resolution NWP model for forecasting convection[J].Meteorological Applications, 2013, 20(4): 417-426. |
| [12] | Gentry M S, Lackmann G M.Sensitivity of simulated tropical cyclone structure and intensity to horizontal resolution[J].Monthly Weather Review, 2010, 138(3): 688-704. |
| [13] | Langhans W, Schmidli J, Fuhrer O,et al.Long-term simulations of thermally driven flows and orographic convectionat convection-parameterizing and cloud-resolving resolutions[J].Journal of Applied Meteorology and Climatology, 2013, 52(6): 1 490-1 510. |
| [14] | Bryan G H, Wyngaard J C, Fritsch J M.Resolution requirements for the simulation of deep moist convection[J].Monthly Weather Review, 2003, 131(10): 2 394-2 416. |
| [15] | Cullen M, Brown A.Large eddy simulation of the atmosphere on various scales[J]. Philosophical Transactions of the Royal Society (Series A), 2009, 367(1 899): 2 947-2 956. |
| [16] | Khairoutdinov M F, Krueger S K, Moeng C H, et al.Large-eddy simulation of maritime deep tropical convection[J]. Journal of Advances in Modeling Earth Systems, 2009, 1(4):13, doi:10.3894/JAMES.2009.1.15. |
| [17] | Ma Leiming.Research progress on major structures of tropical cyclone boundary layer[J].Progress in Geophysics, 2013, 28(3):1 259-1 268. |
| [17] | [马雷鸣. 热带气旋边界层关键结构研究进展[J]. 地球物理学进展, 2013, 28(3): 1 259-1 268.] |
| [18] | Davies T, Cullen M J P, Malcolm A J, et al. A new dynamical core for the MetOffice’s global and regional modelling of the atmosphere[J]. Quarterly Journal of the Royal Meteorological Society, 2005, 131: 1 759-1 782,doi:10.1256/qj.04.101. |
| [19] | Seity Y, Brousseau P, Malardel S, et al.The AROME-France convective-scale operational model[J]. Monthly Weather Review, 2011, 139(3): 976-991. |
| [20] | Arakawa A, Jung J H, Wu C M.Toward unification of the multiscale modeling of the atmosphere[J]. Atmospheric Chemistry and Physics, 2011, 11(8): 3 731-3 742. |
| [21] | Wyngaard J C.Toward numerical modeling in the “Terra incognita”[J]. Journal of the Atmospheric Sciences, 2004, 61(14): 1 816-1 826. |
| [22] | Arakawa A.The cumulus parameterization problem: Past, present, and future[J]. Journal of Climate, 2004, 17(13): 2 493-2 525. |
| [23] | Anthes R A.A cumulus parameterization scheme utilizing a one-dimensional cloud model[J]. Monthly Weather Review, 1977, 105(3):270-286. |
| [24] | Ooyama K.A dynamical model for the study of tropicalcyclone development[J]. Geofisica International (Mexico), 1964, 4:187-198. |
| [25] | Charney J G, Eliassen A.On the growth on the hurrican depression[J].Journal of the Atmospheric Sciences, 1964, 21(1): 68-75. |
| [26] | Kuo H L.On formation and intensification of tropical cyclonesthrough latent heat release by cumulus convection[J].Journal of the Atmospheric Sciences, 1965, 22(1): 40-63. |
| [27] | Manabe S, Smagorinsky J, Strickler R F.Simulated climatology of a general circulation model with a hydrological cycle[J].Monthly Weather Review, 1965, 93(12): 769-798. |
| [28] | Betts A K, Miller M J.A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, ATEX and arctic airmass data sets[J]. Quarterly Journal of the Royal Meteorological Society, 1986, 112(473): 693-709. |
| [29] | Arakawa A, Schubert W H.Interaction of a cumulus cloud ensemble with the large-scale environment, Part I[J].Journal of the Atmospheric Sciences, 1974, 31(3):674-701. |
| [30] | Zhang G J, McFarlane N A.Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Center general circulation model[J].Atmosphere-Ocean, 1995, 33(3):407-446. |
| [31] | Kain J S, Fritsch J M.A one-dimensional entraining/ detraining plume model and its application in convective parameterization[J].Journal of the Atmospheric Sciences,1990,47(23):2 784-2 802. |
| [32] | Kain J S, Fritsch J M.Convective parameterization for mesoscale models: The Kain-Fritsch scheme[M]∥The Representation of Cumulus Convection in Numerical Models. Boston: American Meteorological Society, 1993: 165-170. |
| [33] | Ma L M,Tan Z M.Improving the behavior of the cumulus parameterization for tropical cyclone prediction: Convection trigger[J]. Atmospheric Research, 2009, 92(2): 190-211. |
| [34] | DeRooy W C, Bechtold P, Frohlich K, et al. Entrainment and detrainment in cumulus convection: An overview[J]. Quarterly Journal of the Royal Meteorological Society, 2013, 139(670): 1-19. |
| [35] | Emanuel K A.A scheme for representing cumulus convection in large-scale models[J]. Journal of the Atmospheric Sciences 1991, 48(21): 2 313-2 329. |
| [36] | Sakradzija M, Seifert A, Heus T.Fluctuations in a quasi-stationary shallow cumulus cloud ensemble[J]. Nonlinear Processes Geophys, 2015, 22(1): 65-85. |
| [37] | Weisman L, Skamarock W C, Klemp J B.The resolution dependence of explicitly modeled convective systems[J].Monthly Weather Review, 1997, 125(4): 527-548. |
| [38] | Pedersen C A, Winther J G.Intercomparison and validation of snow albedo parameterization schemes in climate models[J]. Climate Dynamics, 2005, 25(4): 351-362. |
| [39] | Berg P, Wagner S,Kunstmann H, et al.High resolution regional climate model simulations for Germany: Part I-Validation[J]. Climate Dynamics, 2013, 40(1/2): 401-414. |
| [40] | Fosser G, Khodayar S, Berg P.Benefit of convection permitting climate model simulations in the representation of convective precipitation[J]. Climate Dynamics, 2014, 44(1): 45-60. |
| [41] | Moeng C H, Sullivan P, Khairoutdinov M, et al.A mixed scheme for subgrid-scale fluxes in cloud-resolving models[J]. Journal of the Atmospheric Sciences, 2010, 67(11): 3 692-3 705. |
| [42] | Donner L J, Wyman B L, Hemler R S, et al.The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3[J]. Journal of Climate, 2011, 24(13): 3 484-3 519. |
| [43] | Bechtold P N, Semane P, Lopez J P, et al.Representing equilibrium and nonequilibrium convection in large-scale models[J]. Journal of the Atmospheric Sciences, 2014, 71(2): 734-753. |
| [44] | Moeng C H.A closure for updraft-downdraft representation of subgrid-scale fluxes in cloud-resolving models[J]. Monthly Weather Review, 2014, 142(2): 703-715. |
| [45] | Roh W, Satoh M.Evaluation of precipitating hydrometeor parameterizations in a single-moment bulk microphysics scheme for deep convective systems over the tropical central Pacific[J]. Journal of the Atmospheric Sciences, 2014, 71(7): 2 654-2 673. |
| [46] | Pruppacher H R, Klett J D, Wang P K.Microphysics of Clouds and Precipitation[M]. Netherlands: Taylor and Francis, 1998. |
| [47] | Cohen C, McCaul Jr E W. The sensitivity of simulated convective storms to variations in prescribed single-moment microphysics parameters that describe particle distributions, sizes, and numbers[J]. Monthly Weather Review, 2006, 134(9): 2 547-2 565. |
| [48] | Morrison H, Milbrandt J.Comparison of two-moment bulk microphysics schemes in idealized supercell thunderstorm simulations[J]. Monthly Weather Review, 2010, 139: 1 103-1 130,doi:10.1175/2010MWR3433.1. |
| [49] | Van Weverberg K, Goudenhoofdt E, Blahak U, et al.Comparison of one-moment and two-moment bulk microphysics for high-resolution climate simulations of intense precipitation[J]. Atmospheric Research, 2014, 147:145-161. |
| [50] | Seifert A, Beheng K.A two-moment cloud microphysics parameterization for mixed-phase clouds: Part 1. Model description[J]. Meteorology and Atmospheric Physics, 2006, 92(1): 45-66. |
| [51] | Rosenfeld D,Sherwood S,Wood R,et al.Climate effects of aerosol-cloud interactions[J].Science,2014,343(6 169):379-380. |
| [52] | Tao W K, Chen J P, Li Z, et al.Impact of aerosols on convective clouds and precipitation[J]. Reviews of Geophysics, 2012, 50(2):1-62. |
| [53] | Morrison H, Tessendorf S A, Ikeda K, et al.Sensitivity of a simulated midlatitude squall line to parameterization of raindrop breakup[J]. Monthly Weather Review, 2012, 140(8): 2 437-2 460. |
| [54] | Koren I, Remer L, Altaratz O, et al.Aerosol-induced changes of convective cloud anvils produce strong climate warming[J]. Atmospheric Chemistry and Physics, 2010, 10(10): 5 001-5 010. |
| [55] | Zhu Rong, Xu Dahai.Multi-scale trubulent planetary boundary layer parameterization in mesoscale numerical simulation[J]. Journal of Applied Meteorological Sciences, 2004, 15(5):543-555. |
| [55] | [朱蓉, 徐大海. 中尺度数值模拟中的边界层多尺度湍流参数化方案[J]. 应用气象学报, 2004, 15(5):543-555.] |
| [56] | Jiang Weimei,Mou Lifeng.Simulation research for PBL using non-local closure over complex underlying surface domain[J].Chinese Journal of Atmospheric Sciences, 1999, 23(1):25-33. |
| [56] | [蒋维楣, 牟礼凤. 复杂下垫面模拟域大气边界层非局地闭合模拟研究[J].大气科学, 1999, 23(1):25-33.] |
| [57] | Deardorff J W.Theoretical expression for the countergradient vertical heat flux[J].Journal of Geophysical Research, 1972, 77(30):5 900-5 904. |
| [58] | Mailhôt J, Benoit R.A finite-element model of the atmospheric boundary layer suitable for use with numerical weatherprediction models[J].Journal of the Atmospheric Sciences, 1982, 39(10):2 249-2 266. |
| [59] | Troen I, Mahrt L.A simple model of the atmospheric boundary layer: Sensitivity to surface evaporation[J].Boundary-Layer Meteorology, 1986, 37(1/2):129-148. |
| [60] | Hong S Y, Pan H L.Nonlocal boundary layer vertical diffusion in a medium-range forecast model[J].Monthly Weather Review, 1996, 124(10):2 322-2 339. |
| [61] | Shin H H, Dudhia J.Evaluation of PBL parameterizations in WRF at sub-kilometer grid spacings: Turbulence statistics in the dry convective boundary layer[J]. Monthly Weather Review,2016, 144(3): 1 161-1 177. |
| [62] | Ma Leiming.Research progress on China typhoon numerical prediction models and associated major techniques[J]. Progress in Geophysics,2014,29(3):1 013-1 022. |
| [62] | [马雷鸣. 国内台风数值预报模式及其关键技术研究进展[J]. 地球物理学进展, 2014, 29(3): 1 013-1 022.] |
| [63] | Seidel D J, Ao C O, Li K.Estimating climatological planetary boundary layer heights from radiosonde observations: Comparison of methods and uncertainty analysis[J]. Journal of Geophysical Research, 2010, 115(D16),doi:10.1029/2009JD013680. |
| [64] | Smith R K.The surface boundary layer of a hurricane[J]. Tellus,1968, 20:473-483. |
| [65] | Blackadar A K.High-resolution models of the planetary boundary layer[C]∥Pfafflin J R, Ziegler E N, eds.Advances in Environmental Science and Engineering. Gordon and Breach Science, 1979, 1: 50-85. |
| [66] | Bryan G H, Rotunno R.The influence of near-surface, high-entropy air in hurricane eyes on maximum hurricane intensity[J]. Journal of the Atmospheric Sciences, 2009, 66(1): 148-158. |
| [67] | Zhang J A, Marks F D, Montgomery M T, et al.An estimation of turbulent characteristics in the low-level region of intense Hurricanes Allen (1980) and Hugo (1989)[J]. Monthly Weather Review, 2011, 139(5): 1 447-1 462. |
| [68] | García-Díez M, Fernandez J, Casanueva A,et al.Exploring WRF configuration sensitivity over the Euro-Cordex domain[C]∥Proceedings of CORDEX-WRF Workshop, Tenerife, September, 2012. |
| [69] | Kepert J D.Slab- and height-resolving models of the tropical cyclone boundary layer. Part I: Comparing the simulations[J]. Quarterly Journal of the Royal Meteorological Society, 2010, 136(562):1 686-1 699. |
| [70] | Storm B, Dudhia J, Basu S, et al.Evaluation of the weather research and forecasting model on forecasting low-level jets: Implications for wind energy[J]. Wind Energy, 2009, 12(1):81-90. |
| [71] | Shin H H, Hong S Y.Inter-comparison of planetary boundary layer parametrizations in the WRF model for a single day from CASES-99[J]. Boundary-Layer Meteorology,2011, 139(2):261-281. |
| [72] | Storm B, Basu S.The WRF model forecast-derived low-level wind shear climatology over the United States Great Plains[J]. Energies,2010, 3(2):258-276. |
| [73] | Ma L M,Bao X W.Parametrization of planetary boundary-layer height with helicity and verification with tropical cyclone prediction[J].Boundary-Layer Meteorology,2016,160(3):569-593. |
| [74] | Molinari J, Vollaro D.Rapid intensification of a sheared tropical storm[J].Monthly Weather Review, 2010, 138(10): 3 869-3 885. |
| [75] | Siebesma A P, Soares P M, Teixeira J.A combined eddy-diffusivity mass-flux approach for the convective boundary layer[J]. Journal of the Atmospheric Sciences, 2007, 64(4): 1 230-1 248. |
| [76] | Shin H H, Hong S Y.Analysis of resolved and parameterized vertical transports in convective boundary layers at gray-zone resolutions[J]. Journal of the Atmospheric Sciences, 2013, 70(10): 3 248-3 261. |
| [77] | Ban N, Schmidli J, Schär C.Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations[J]. Journal of Geophysical Research:Atmosphere, 2014, 119:7 889-7 907, doi: 10.1002/2014JD021478. |
| [78] | Duan Yihong, Chen Lianshou, Liang Jianyin, et al.Research progress in the unusual variations of typhoons before and after landfalling[J]. Acta Meteorologica Sinica, 2014, 72(5):969-986. |
| [78] | [端义宏, 陈联寿, 梁建茵, 等. 台风登陆前后异常变化的研究进展[J]. 气象学报, 2014, 72(5): 969-986.] |
| [79] | Ma L, Duan Y, Zhu Y.The structure and rainfall features of tropical cyclone Rammasun (2002)[J]. Advances in Atmospheric Sciences, 2004, 21(6):951-963. |
| [80] | Ma L, Qin Z, Duan Y, et al.Impacts of TRMM SRR assimilation on the numerical prediction of tropical cyclone[J]. Acta Oceanologica Sinica, 2006, 25(5):14-26. |
| [81] | Ma L, Chan J, Davidson N E, et al.Initialization with diabaticheating from satellite-derived rainfall[J]. Atmospheric Research, 2007, 85: 148-158. |
| [82] | Ma Leiming.A new approach to typhoon vortex initialization based on the dynamic retrieval of sea level pressure[J]. Acta Meteorologica Sinica,2011,69(6): 978-989. |
| [82] | [马雷鸣. 基于海平面气压动力反演的台风涡旋初始化方法[J].气象学报, 2011, 69(6): 978-989.] |
| [83] | Gong Ziping, Ke Hengyu, Wu Xiongbin, et al.HF radar observation of Longwang typhoon in the Taiwan Straight[J]. Chinese Journal of Geophysics, 2007, 50(6): 1 695-1 702. |
| [83] | [龚子平, 柯亨玉, 吴雄斌, 等. “龙王”台风期间高频地波雷达数据分析[J]. 地球物理学报, 2007, 50(6): 1 695-1 702.] |
| [84] | Li Lun, Wu Xiongbin, Long Chao, et al.Regularization inversion method for extrating ocean wave spectra from HFSWR sea echo[J]. Chinese Journal of Geophysics, 2013, 56(1): 219-229. |
| [84] | [李伦, 吴雄斌, 龙超, 等. 基于正则化方法的高频地波雷达海浪方向谱反演[J]. 地球物理学报, 2013, 56(1): 219-229.] |
| [85] | Mu Mu, Wang Qiang, Duan Wansuo, et al.Application of conditional nonlinear optimal perturbation to targeted observation studies of the atmosphere and ocean[J]. Acta Meteorologica Sinica,2014, 72(5): 1 001-1 011. |
| [85] | [穆穆,王强,段晚锁,等.条件非线性最优扰动法在大气与海洋目标观测研究中的应用[J].气象学报,2014,72(5):1 001-1 011.] |
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