THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

ZHANG Xu-bin; WAN Qi-lin; XUE Ji-shan; DING Wei-yu; LI Hao-rui

Abstract:

An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season (AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall; the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.

Get Citation+

ZHANG Xu-bin, WAN Qi-lin, XUE Ji-shan, et al. THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON [J]. Journal of Tropical Meteorology, 2015, 21(2): 194-210.

Export:

Article Metrics

THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, CMA, Guangzhou 510080 China Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510080 China 3. Chinese Academy of Meteorological Sciences, Beijing 100081 China)

Abstract: An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season (AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall; the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.

HTML

Reference (59)

[1]	SUN Jian-hua, ZHAO Si-xiong. A diagnosis and simulation study of a strong heavy rainfall in South China [J]. Chin J Atmos Sci, 2000, 24(3): 381-392 (in Chinese).
[2]	MENG Wei-guang, WANG An-yu, LI Jiang-nan, et al. Multi-MCSs (Mesoscale Convective Systems) over the heavy rainfall region during 23-24 May 1998 in South China [J]. J Sun Yat-sen Univ (in Chinese), 2003, 42(3): 73-77.
[3]	ZHANG Xiao-hui, NI Yun-qi. A comparative study of a frontal and a non-frontal convective systems [J]. Acta Meteorol Sinica, 2009, 67(1): 108-121 (in Chinese).
[4]	ZHANG Xu-bin, ZHANG Yi. Numerical simulation of a heavy rainfall event in southern China: the mechanism of mesoscale convective system genesis and development [J]. Sci Meteorol Sinica, 2011, 31(2): 145-152 (in Chinese).
[5]	LIU Shu-yuan, ZHENG Yong-guang, TAO Zu-yu. The analysis of the relationship between pulse of LLJ and heavy rain using wind profiler data [J]. J Trop Meteorol, 2003, 9(2): 158-163.
[6]	HE Bian, SUN Zhao-bo. Diagnostic analysis and numerical simulation of persistent torrential rain in South China in June 2008 [J]. Sci Meteorol Sinica, 2010, 30(2): 164-171 (in Chinese).
[7]	CHEN Hong, ZHAO Si-xiong. Heavy rainfall in South China and related circulation during first GARP global experiment period [J]. Chin J Atmos Sci, 2000, 24(2): 238-252 (in Chinese).
[8]	SUN Jian, ZHAO Ping, ZHOU Xiu-ji. The mesoscale structure of a South China rainstorm and the influence of complex topography [J]. Acta Meteorol Sinica, 2002, 60(3): 333-342 (in Chinese).
[9]	WANG Wei, SEAMAN N L. A comparison study of convective schemes in a mesoscale model [J]. Mon Wea Rev, 1997, 125(2): 252-278.
[10]	GALLUS Jr. W A. Eta simulations of three extreme rainfall events: Impact of resolution and choice of convective scheme [J]. Wea Forecast, 1999, 14(3): 405-426.
[11]	GU Jian-feng. Comparative experiments on precipitation prediction with different deep convective parameterization scheme [J]. Meteorol Mon, 1999, 25(4): 39-44 (in Chinese).
[12]	WANG Jian-jie, HU Xin, GUO Xiao-rong. Comparison experiments on cumulus parameterization schemes of the MM5 [J]. J Appl Meteorol Sci, 2001, 12(1): 41-53 (in Chinese).
[13]	WANG Chen-xi. Comparison experiments on the effects of different cumulus parameterization scheme in MM5 on precipitation [J]. Sci Meteorol Sinica, 2004, 24(2): 168-176 (in Chinese).
[14]	JANKOV I, GALLUS Jr. W A, SHAW B, KOCH S E. An Investigation of IHOP Convective System Predictability Using a Matrix of 19 WRF Members [C]// 84th AMS Annual Meeting, Seattle, U.S.A., Jan. 10-15, 2004.
[15]	JANKOV I, GALLUS Jr. W A, SEGAL M, SHAW B, KOCH S E. The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall [J]. Wea Forecast, 2005, 20(6): 1 048-1 060.
[16]	ZHANG Man, WANG Ang-sheng, JI Zhong-zhen. Influence of different precipitation parameterization schemes on a simulated “03.7” heavy rainfall case [J]. Chin J Atmos Sci, 2006, 30(3): 441-451 (in Chinese).
[17]	XUE Gen-yuan, ZHANG Jian-hai, CHEN Hong-mei, et al. The comparisons of different convective parameterization schemes applying precipitation’s forecast of typhoon landing on Zhejiang and Fujian provinces [J]. Plateau Meteorol, 2007, 26(4): 765-773 (in Chinese).
[18]	WU Hong-yu, CHEN Dei-hui, XU Guo-qiang. Sensitive experiments of various parameterization schemes in different physical processes on Guizhou precipitation [J]. Meteorol Mon, 2007, 33(4): 23-28 (in Chinese).
[19]	LI Yan, QIU Cong-jian, ZHANG Jian-guo. The comparative trial experiments with different convection parameterization schemes in mesoscale models [J]. J Trop Meteorol, 2008, 24(6): 609-618 (in Chinese).
[20]	SUN Jing, LOU Xiao-feng, SHI Yue-qin. The effects of different microphysical schemes on the simulation of a meiyu front heavy rainfall [J]. Acta Meteorol Sinica, 2011, 69(5): 799-809 (in Chinese).
[21]	LIAO Jing-biao, WANG Xue-mei, XIA Bei-cheng, et al. The effects of different physics and cumulus parameterization schemes in WRF on heavy rainfall simulation in PRD [J]. J Trop Meteorol, 2012, 28(4): 461-470 (in Chinese).
[22]	ARAKAWA A, CHEN Jeng-ming. Closure assumptions in the cumulus parameterization problem [C]// Short and Medium Range Numerical Weather Prediction, MATSUNO T (ed), Tokyo, Japan. Aug. 4-8, 1986.
[23]	MOLINARI J M, DUDEK M. Parameterization of convective precipitation in mesoscale numerical models: a critical review [J]. Mon Wea Rev, 1992, 120(2): 326-344.
[24]	HAMMARSTRAND U. Questions involving the use of traditional convection parameterization in NWP models with higher resolution [J]. Tellus, 1998, 50A(3): 265-282.
[25]	XING Yu, LEE Tae-young. Role of convective parameterization in simulations of a convection band at grey-zone resolutions [J]. Tellus, 2010, 62A(5): 617-632.
[26]	KUELL V, GASSMANN A, BOTT A. Towards a new hybrid cumulus parameterization schemes for use in non-hydrostatic weather prediction models [J]. Quart J Roy Meteorol Soc, 2007, 133(623): 479-490.
[27]	DENG Ai-jun, STAUFFER D R. On improving 4-kmmesoscale model simulations [J]. J Appl Meteorol Climatol, 2006, 45(3): 361-381.
[28]	KOTRONI V, LAGOUVARDOS K. Evaluation of MM5 high-resolution real-time forecasts over the urban area of Athens, Greece [J]. J Appl Meteorol, 2004, 43(11): 1 666-1 678.
[29]	NIEMEL? S, FORTELIUS C. Applicability of large-scale convection and condensation parameterization to meso-
[30]	ARAKAWA A, SCHUBERT W H. Interaction of cumulus cloud ensemble with the large-scale environment. Part I [J]. J. Atmos. Sci., 1974, 31: 671-701.
[31]	GRELL G A. Prognostic evaluation of assumptions used by cumulus parameterizations [J]. Mon Wea Rev, 1993, 121: 764-787.
[32]	PAN Hua-lu, WU Wan-shu. Implementing a mass flux convection parameterization for the NMC Medium-Range Forecast model [R]. NMC note, 1995, 409: 40pp.
[33]	HAN Jongil, PAN Hua-lu. Revision of convection and vertical diffusion schemes in the NCEP global forecast system [J]. Wea Forecast, 2011, 26(4): 520-533.
[34]	BETTS A K. A new convective adjustment scheme. Part I: Observational and theoretical basis [J]. Quart J Roy Meteorol Soc, 1986, 112: 677-691.
[35]	BETTS A K, MILLER M J. A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, and arctic air-mass datasets [J]. Quart J Roy Meteorol Soc, 1986, 112: 693-709.
[36]	JANJIC Z I. The step-mountain Eta coordinate model: further developments of the convection, viscous sublayer and turbulence closure schemes [J]. Mon Wea Rev, 1994, 122: 927-945.
[37]	JANJIC Z I. Comments on ”Development and Evaluation of a Convection Scheme for Use in Climate Models” [J]. J Atmos Sci, 2000, 57: p. 3686.
[38]	KAIN J S, FRITSCH J M. A one-dimensional entraining/detraining plume model and its application in convective parameterization [J]. J Atmos Sci, 1990, 47: 2784-2802.
[39]	KAIN J S, FRITSCH J M. Convective parameterization for mesoscale models: The Kain-Fritcsh scheme [C]// The Representation of Cumulus Convection in Numerical Models. Boston, MA: American Meteorological Society, 24: 165-170.
[40]	LIN Yuh-lang, FARLEY R D, ORVILLE H D. Bulk parameterization of the snow field in a cloud model [J]. J Climate Appl Meteorol, 1983, 22: 1 065-1 092.
[41]	HONG S Y, LIM J O J. The WRF Single-Moment 6-Class Microphysics Scheme (WSM6) [J]. J Kor Meteorol Soc, 2006, 42: 129-151.
[42]	DUDHIA J, HONG S Y, LIM K S. A new method for representing mixed-phase particle fall speeds in bulk microphysics parameterizations [J]. J Meteorol Soc Jpn, 2008, 86A: 33-44.
[43]	HONG S Y, JUANG H M H, ZHAO Qing-yun. Implementation of prognostic cloud scheme for a regional spectral model [J]. Mon Wea Rev, 1998, 126: 2 621-2 639.
[44]	HONG S Y, DUDHIA J, CHEN Shu-hua. A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation [J]. Mon Wea Rev, 2004, 132: 103-120.
[45]	HU Zhi-jin, LOU Xiao-feng, BAO Shao-wu, et al. A simplified explicit scheme of phase-mixed cloud and precipitation [J]. J Appl Meteorol Sci, 1998, 9(3): 257-264 (in Chinese).
[46]	LIU Qi-jun, HU Zhi-jin, ZHOU Xiu-ji. Explicit cloud schemes of HLAFS and simulation of heavy rainfall and clouds, Part I: explicit cloud schemes [J]. J Appl Meteorol Sci, 2003, 14 (suppl.): 60-67 (in Chinese).
[47]	BLACKADAR A K. Modeling the nocturnal boundary layer [C]// Preprints, Third Symposium on Atmospheric Turbulence, Diffusion and Air Quality, Raleigh, NC, Amer Meteorol Soc, 1976: 46-49.
[48]	BLACKADAR A K. High resolution models of the planetary boundary layer [M]// Advances in Environmental Science and Engineering, PFAFFLIN J, ZIEGLER E.(ed), Vol. 1, No. 1, Gordon and Breach, 50-85.
[49]	DUDHIA J. A multi-layer soil temperature model for MM5 [C]// Sixth Annual PSU/NCAR Mesoscale Model Users' Workshop, Boulder CO, 1996: 49-50.
[50]	CHEN Fei, DUDHIA J. Coupling an advanced land surface�Chydrology model with the Penn State�CNCAR MM5 modeling system. Part I: Model implementation and sensitivity [J]. Mon Wea Rev, 2001, 129: 569-585.
[51]	EK M B, MITCHELL K E, LIN Y, et al. Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model [J]. J Geophys Res, 2003, 108(D22): 8-851.
[52]	HONG S Y, PAN Hua-lu. Nonlocal boundary layer vertical diffusion in a medium-range forecast model [J]. Mon Wea Rev, 1996, 124: 2 322-2 339.
[53]	HONG S Y, NOH Y, DUDHIA J. A new vertical diffusion package with an explicit treatment of entrainment processes [J]. Mon Wea Rev, 2006, 134: 2 318-2 341.
[54]	HONG S Y. Stable Boundary Layer Mixing in a Vertical Diffusion Scheme [C]// Kor Meteorol Soc, Fall Conference, Seoul, 2007: 25-26.
[55]	KUO Ying-hwa, CHENG Lin-sheng, ANTHES R A. Mesoscale analysis of the Sichuan flood catastrophe 11-15 July 1981 [J]. Mon Wea Rev, 1986, 114(11): 1 984-2 003.
[56]	YANAI M, ESBENSEN S, CHU J H. Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets [J]. J Atmos Sci, 1973, 30: 611-627.
[57]	THOMPSON Jr. R M, PAYNE S W, RECKER E E, et al. Structure and properties of synoptic-scale wave disturbances in the Intertropical Convergence Zone of the eastern Atlantic [J]. J Atmos Sci, 1979, 36: 53-72.
[58]	YANAI M, JOHNSON R H. Impacts of cumulus convection on thermodynamic fields [M]// Representation of Cumulus Convection in Numerical Models of the Atmosphere, Meteorol Monogr, No. 46, Amer Meteorol Soc, 1993: 39-62.
[59]	LIAO Jie, TAN Zhe-min. Numerical simulation of a heavy rainfall event along the Meiyu front: Influences of different scale weather systems [J]. Acta Meteorol Sinica, 2005, 63(5): 771-789 (in Chinese).

THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

Abstract:

References

Get Citation+

Share Article

Article Metrics

Proportional views

Manuscript History

Online:

通讯作者: 陈斌, bchen63@163.com