NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL

WANG Shu-chang; HUANG Si-xun; ZHANG Wei-min; ZHU Xiao-qian; CAO Xiao-qun; LI Yi

Abstract:

Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation “Weather Research and Forecasting Model”. Several options of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.

Get Citation+

WANG Shu-chang, HUANG Si-xun, ZHANG Wei-min, et al. NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL [J]. Journal of Tropical Meteorology, 2008, 14(1): 1-10.

Export:

Article Metrics

NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL

Abstract: Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation “Weather Research and Forecasting Model”. Several options of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.

HTML

Reference (17)

[1]	WANG Shu-chang, HUANG Si-xun, LI Yi, Sensitivenumerical simulation and analysis of rainstorm using nestedWRF model. [J]. J. Hydrodyn., Ser.B, 2006, 18(5): 578-586.
[2]	CHEN Min, HUANG X Y. Digital filter Initialization forMM5 [J]. Mon. Wea. Rev., 2006,134(4): 1222-1236.
[3]	LYNCH P, Huang X Y. Initialization of the HIRLAMmodel using a digital filter [J]. Mon. Wea. Rev., 1992, 120(6),1019-1034.
[4]	MACHENHAUER B. On the dynamics of gravityoscillations in a shallow water model with applications tonormal mode initialization [J]. Beitr. Atmos. Phys., 1977, 50:253-271.
[5]	DE PONDECA M S F V, ZOU X. Moisture retrievals fromsimulated zenith delay “observations” and their impact onshort-range precipitation forecasts [J]. Tellus, 2001, 53A(2):192-214.
[6]	GAUTHIER P, THEPAUT J N. Impact of the digital filteras a weak constraint in the preoperational 4DVAR assimilationsystem of Météo-France [J]. Mon. Wea. Rev., 2001, 129(8),2089-2102.
[7]	LYNCH P. Digital filters for numerical weather prediction.HIRLAM [R] Technical Report. 1993, No 10.
[8]	LYNCH P. The Dolph-Chebyshev window: a simpleoptimal filter [J]. Mon. Wea. Rev., 1997, 125(4): 655-660.
[9]	HUANG X Y, LYNCH P. Diabatic digital filterinitialization: Application to the HIRLAM model [J]. Mon.Wea. Rev., 1993, 121: 589-603.
[10]	TEMPERTON C, WILLIAMSON D L. Normal-modeinitialization for a multilevel gridpoint model. Part 1: Linearaspects [J]. Mon. Wea. Rev., 1981, 109(4): 729-743.
[11]	WILLIAMSON D L, TEMPERTON C. Normal-modeinitialization for a multilevel gridpoint model. Part II:Nonlinear aspects [J]. Mon. Wea. Rev., 1981, 109(4): 744-757.
[12]	HUANG X Y, SUNDQVIST H. Initialization of cloudwater content and cloud cover for numerical prediction models[J]. Mon. Wea. Rev., 1993, 121(10): 2719-2726.
[13]	WAN Qi-Lin, XUE Ji-shan, CHEN Zhi-tong, et al. Thetest of applying radar TREC wind in three-dimensionalvariational assimilation [J]. J. Trop. Meteor., 2006, 12(1): 59-66.
[14]	DU Qin, SHEN Tong Li. Study of modification to modelerror by using the adjoint model assimilation system [J]. J.Trop. Meteor., 2007, 23(2): 182-188.
[15]	GU Jian-feng, XUE Jishan, YAN Hong. A summarizationof the four- demensional variational Doppler radar analysissystem[J]. J. Trop. Meteor., 2004, 20(1): 2-14.
[16]	POLAVARAPU S, TANGUAY M, Fillion L. Fourdimensional variational data assimilation with digital filterinitialization [J]. Mon. Wea. Rev., 2000, 128(7): 2491-2510.
[17]	WEE T K, KUO Y H. Impact of a digital filter as a weakconstraint in MM5 4DVAR [J]. Mon. Wea. Rev., 2004, 132(2):543-559.

NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL

Abstract:

References

Get Citation+

Share Article

Article Metrics

Proportional views

Manuscript History

Online:

通讯作者: 陈斌, bchen63@163.com