This paper conducts the assimilating experiments and simulating experiments on typhoon “Aere” (No. 0418), by use of bogus data assimilation (BDA) method combined with advanced microwave sounding unit-A (AMSU-A) data assimilation method in the fifth-generation National Center for Atmospheric Research (NCAR)/Penn State Mesoscale Model Version-3 (MM5V3), the Radiative Transfer for TIROS-N Operational Vertical Sounder Version-7 (RTTOV) model, and their adjoint models. The Bogus data constructed with BDA technique are mainly located at sea level, while the peak energy contribution levels of the sounder channels selected in AMSU-A data assimilation technique are mainly located at upper troposphere. The two types of data can reconstruct the meso-scale information and improve the typhoon initial fields under the model dynamic forcing effect, respectively from the low level and the upper level of atmosphere during the assimilating process. Numerical results show that with four-dimensional variational data assimilation (4DVAR) technique the circulation of initial fields is improved, the “warm core” of typhoon is enhanced, the “cloud water” phenomenon that occurs in the optimal initial fields and the numerical model is changed into “warm start” from “cold start”. 1. Introduction Typhoon is one of the most frequent disasters affecting human beings. With the development of numerical forecasting techniques, numerical forecasting of typhoon has entered an operational stage. However, the prediction accuracy is far from meeting the requirements of disaster prevention and reduction. If the track and intensity of typhoon can be accurately forecasted, necessary preparedness can be performed beforehand and serious economic loss can be much reduced. Due to severe deficiency of conventional observation data over sea, the results of objective analysis can not precisely describe the thermal structure and circulation characteristics of initial typhoon, especially its mesoscale structure, which is one of the main reasons for serious errors in typhoon numerical forecasting. Therefore, how to provide more rational initial values is an urgent task. Since 1990s, an initializing method of artificial typhoon mode is introduced into typhoon forecasting research [1–3]. With this method, an ideal bogus typhoon mode with 3-dimensional circulation structure and thermal structure is constructed according to the observation data, and then it is implanted into the initial typhoon analysis fields to construct new initial typhoon optimal fields. This method is now widely applied in Typhoon
References
[1]
T. Iwasaki, H. Nakano, and H. Sugi, “The performance of a typhoon track prediction model,” Journal of the Meteorological Society of Japan, vol. 65, pp. 555–570, 1987.
[2]
M. B. Mathur, “The National Meteorological Center's quasi-lagrangian model for hurricane prediction,” Monthly Weather Review, vol. 119, no. 6, pp. 1419–1447, 1991.
[3]
Y. Kurihara, M. A. Bender, and R. J. Ross, “An initialization scheme of hurricane models by vortex specification,” Monthly Weather Review, vol. 121, no. 7, pp. 2030–2045, 1993.
[4]
J. M. Lewis and J. C. Derber, “The use of adjoint equation to solve a variational adjustment problem with advective constraints,” Tellus, vol. 37A, pp. 309–322, 1985.
[5]
F.-X. Le Dimet and O. Talagrand, “Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects,” Tellus, vol. 38A, no. 2, pp. 97–110, 1986.
[6]
P. Courtier and O. Talagrand, “Variational assimilation of meteorological observations with the adjoint vorticity equation. Part I: theory,” Quarterly Journal of the Royal Meteorological Society, vol. 113, no. 478, pp. 1311–1328, 1987.
[7]
X. Zou and Q. Xiao, “Studies on the initialization and simulation of a mature hurricane using a variational bogus data assimilation scheme,” Journal of the Atmospheric Sciences, vol. 57, no. 6, pp. 836–860, 2000.
[8]
Q. Xiao, X. Zou, and B. Wang, “Initialization and simulation of a landfalling hurricane using a variational bogus data assimilation scheme,” Monthly Weather Review, vol. 128, no. 7, pp. 2252–2269, 2000.
[9]
Z.-X. Pu and S. A. Braun, “Evaluation of bogus vortex techniques with four-dimensional variational data assimilation,” Monthly Weather Review, vol. 129, no. 8, pp. 2023–2039, 2001.
[10]
F. Weng, T. Zhu, and B. Yan, “Satellite data assimilation in numerical weather prediction models. Part II: uses of rain-affected radiances from microwave observations for hurricane vortex analysis,” Journal of the Atmospheric Sciences, vol. 64, no. 11, pp. 3910–3925, 2007.
[11]
Q. Xiao, L. Chen, and X. Zhang, “Evaluations of BDA scheme using the advanced research WRF (ARW) model,” Journal of Applied Meteorology and Climatology, vol. 48, no. 3, pp. 680–689, 2009.
[12]
Y. Zhao, B. Wang, and Y. Wang, “Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA),” Meteorology and Atmospheric Physics, vol. 98, no. 3-4, pp. 269–282, 2007.
[13]
K.-H. Chou and C.-C. Wu, “Typhoon initialization in a mesoscale combination of the bogused vortex and the dropwindsonde data in DOTSTAR,” Monthly Weather Review, vol. 136, no. 3, pp. 865–879, 2008.
[14]
F. Weng, “Advances in radiative transfer modeling in support o satellite data assimilation,” Journal of the Atmospheric Sciences, vol. 64, no. 11, pp. 3799–3807, 2007.
[15]
X. Zou, Q. Xiao, A. E. Lipton, and G. D. Modica, “A numerical study of the effect of GOES sounder cloud-cleared brightness temperatures on the prediction of Hurricane Felix,” Journal of Applied Meteorology, vol. 40, no. 1, pp. 34–55, 2001.
[16]
J. F. Le Marshall, L. M. Leslie, R. F. Abbey Jr., and L. Qi, “Tropical cyclone track and intensity prediction: the generation and assimilation of high-density, satellite-derived data,” Meteorology and Atmospheric Physics, vol. 80, no. 1–4, pp. 43–57, 2002.
[17]
Y.-F. Wang, B. Wang, G. Ma, and Y.-S. Wang, “Effects of 4DVAR with multifold observed data on the typhoon track forecast,” Chinese Science Bulletin, vol. 48, pp. 93–98, 2003.
[18]
H. Zhang, J. Xue, G. Zhu, S. Zhuang, X. Wu, and F. Zhang, “Application of direct assimilation of ATOVS microwave radiances to typhoon track prediction,” Advances in Atmospheric Sciences, vol. 21, no. 2, pp. 283–290, 2004.
[19]
T. H. Zapotocny, J. A. Jung, J. F. Le Marshall, and R. E. Treadon, “A two-season impact study of four satellite data types and rawinsonde data in the NCEP global data assimilation system,” Weather and Forecasting, vol. 23, no. 1, pp. 80–100, 2008.
[20]
G. A. Grell, J. Dudhia, and D. R. Stauffer, “A description of the fifth-generation penn state/NCAR Mesoscale Model (MM5),” NCAR Technical Note NCAR/TN-398 + STR, National Center for Atmospheric Research, Boulder, Colo, USA, 1994.
[21]
I. B. Troen and L. Mahrt, “A simple model of the atmospheric boundary layer; sensitivity to surface evaporation,” Boundary-Layer Meteorology, vol. 37, no. 1-2, pp. 129–148, 1986.
[22]
J. R. Eyre and H. M. Woolf, “Transmittance of atmospheric gases in the microwave region: a fast model,” Applied Optics, vol. 27, pp. 3244–3249, 1988.
