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Advances in Meteorology
Volume 2016 (2016), Article ID 2170746, 10 pages
http://dx.doi.org/10.1155/2016/2170746
Research Article

Reconstruction of Typhoon Structure Using 3-Dimensional Doppler Radar Radial Velocity Data with the Multigrid Analysis: A Case Study in an Idealized Simulation Context

1Key Laboratory of State Oceanic Administration for Marine Environmental Information Technology, National Marine Data and Information Service, State Oceanic Administration, Tianjin 300171, China
2NOAA Earth System Research Laboratory, Boulder, CO 80305-3328, USA
3NOAA Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ 08540-6649, USA

Received 25 March 2016; Revised 2 June 2016; Accepted 6 June 2016

Academic Editor: Mario M. Miglietta

Copyright © 2016 Hongli Fu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Sun and N. A. Crook, “Real-time low-level wind and temperature analysis using single WSR-88D data,” Weather and Forecasting, vol. 16, no. 1, pp. 117–132, 2001. View at Publisher · View at Google Scholar · View at Scopus
  2. S. S. Weygandt, A. Shapiro, and K. K. Droegemeier, “Retrieval of model initial fields from single-Doppler observations of a supercell thunderstorm. Part I: single-Doppler velocity retrieval,” Monthly Weather Review, vol. 130, no. 3, pp. 433–453, 2002. View at Publisher · View at Google Scholar · View at Scopus
  3. S. S. Weygandt, A. Shapiro, and K. K. Droegemeier, “Retrieval of model initial fields from single-Doppler observations of a supercell thunderstorm. Part II: thermodynamic retrieval and numerical prediction,” Monthly Weather Review, vol. 130, no. 3, pp. 454–476, 2002. View at Publisher · View at Google Scholar · View at Scopus
  4. Y.-C. Liou, J.-L. Chiou, W.-H. Chen, and H.-Y. Yu, “Improving the model convective storm quantitative precipitation nowcasting by assimilating state variables retrieved from multiple-Doppler radar observations,” Monthly Weather Review, vol. 142, no. 11, pp. 4017–4035, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Sun and N. A. Crook, “Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint—part I: model development and simulated data experiments,” Journal of the Atmospheric Sciences, vol. 54, no. 12, pp. 1642–1661, 1997. View at Publisher · View at Google Scholar · View at Scopus
  6. J. Sun and N. A. Crook, “Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: retrieval experiments of an observed Florida convective storm,” Journal of the Atmospheric Sciences, vol. 55, no. 5, pp. 835–852, 1998. View at Publisher · View at Google Scholar · View at Scopus
  7. J. Gao, M. Xue, A. Shapiro, and K. K. Droegemeier, “A variational method for the analysis of three-dimensional wind fields from two Doppler radars,” Monthly Weather Review, vol. 127, no. 9, pp. 2128–2142, 1999. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Lindskog, H. Järvinen, and D. B. Michelson, “Development of radar wind data assimilation for the HIRLAM 3DVar,” HIRLAM Technical Report 52, 2002. View at Google Scholar
  9. J.-D. Gao, M. Xue, K. Brewster, and K. K. Droegemeier, “A three-dimensional variational data analysis method with recursive filter for Doppler radars,” Journal of Atmospheric and Oceanic Technology, vol. 21, no. 3, pp. 457–469, 2004. View at Publisher · View at Google Scholar · View at Scopus
  10. Q. Xiao, Y.-H. Kuo, J. Sun et al., “Assimilation of Doppler radar observations with a regional 3DVAR system: impact of Doppler velocities on forecasts of a heavy rainfall case,” Journal of Applied Meteorology, vol. 44, no. 6, pp. 768–788, 2005. View at Publisher · View at Google Scholar · View at Scopus
  11. J. Gao, M. Xue, S.-Y. Lee, A. Shapiro, Q. Xu, and K. K. Droegemeier, “A three-dimensional variational single-Doppler velocity retrieval method with simple conservation equation constraint,” Meteorology and Atmospheric Physics, vol. 94, no. 1–4, pp. 11–26, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. M. Hu, M. Xue, and K. Brewster, “3DVAR and cloud analysis with WSR-88D level-II data for the prediction of the Fort Worth, Texas, tornadic thunderstorms. Part I: cloud analysis and its impact,” Monthly Weather Review, vol. 134, no. 2, pp. 675–698, 2006. View at Publisher · View at Google Scholar · View at Scopus
  13. M. Hu, M. Xue, J. Gao, and K. Brewster, “3DVAR and cloud analysis with WSR-88D level-II data for the prediction of the Fort Worth, Texas, tornadic thunderstorms—part II: impact of radial velocity analysis via 3DVAR,” Monthly Weather Review, vol. 134, no. 2, pp. 699–721, 2006. View at Publisher · View at Google Scholar · View at Scopus
  14. Q. Xiao and J. Sun, “Multiple-radar data assimilation and short-range quantitative precipitation forecasting of a squall line observed during IHOP_2002,” Monthly Weather Review, vol. 135, no. 10, pp. 3381–3404, 2007. View at Publisher · View at Google Scholar · View at Scopus
  15. S. Sugimoto, N. A. Crook, J. Sun, Q. Xiao, and D. Barker, “Assimilation of Doppler radar data with WRF 3DVAR: evaluation of its potential benefits to quantitative precipitation forecasting through Observing System Simulation Experiments,” Monthly Weather Review, vol. 137, pp. 4011–4029, 2009. View at Google Scholar
  16. F. Q. Zhang, Y. Weng, J. A. Sippel, Z. Meng, and C. H. Bishop, “Cloud-resolving hurricane initialization and prediction through assimilation of doppler radar observations with an ensemble Kalman filter,” Monthly Weather Review, vol. 137, no. 7, pp. 2105–2125, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. K. Zhao and M. Xue, “Assimilation of coastal Doppler radar data with the ARPS 3DVAR and cloud analysis for the prediction of Hurricane Ike (2008),” Geophysical Research Letters, vol. 36, no. 12, Article ID L12803, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. A. D. Schenkman, M. Xue, A. Shapiro, K. Brewster, and J. Gao, “The analysis and prediction of the 8-9 May 2007 Oklahoma tornadic mesoscale convective system by assimilating WSR-88D and CASA radar data using 3DVAR,” Monthly Weather Review, vol. 139, no. 1, pp. 224–246, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. Y. Z. Li, X. G. Wang, and M. Xue, “Assimilation of radar radial velocity data with the wrf hybrid ensemble–3DVAR system for the prediction of hurricane ike (2008),” Monthly Weather Review, vol. 140, no. 11, pp. 3507–3524, 2012. View at Publisher · View at Google Scholar · View at Scopus
  20. N. Du, M. Xue, K. Zhao, and J. Min, “Impact of assimilating airborne Doppler radar velocity data using the ARPS 3DVAR on the analysis and prediction of Hurricane Ike (2008),” Journal of Geophysical Research Atmospheres, vol. 117, no. 17, Article ID D18113, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. S. Abhilash, A. K. Sahai, K. Mohankumar, J. P. George, and S. Das, “Assimilation of Doppler weather radar radial velocity and reflectivity observations in WRF-3DVAR system for short-range forecasting of convective storms,” Pure and Applied Geophysics, vol. 169, no. 11, pp. 2047–2070, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. J. Dong and M. Xue, “Assimilation of radial velocity and reflectivity data from coastal WSR-88D radars using an ensemble Kalman filter for the analysis and forecast of landfalling hurricane Ike (2008),” Quarterly Journal of the Royal Meteorological Society, vol. 139, no. 671, pp. 467–487, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. L. Zhu, Q. Wan, X. Shen et al., “Prediction and predictability of high-impact Western Pacific landfalling Tropical Cyclone Vicente (2012) through convection-permitting ensemble assimilation of doppler radar velocity,” Monthly Weather Review, vol. 144, no. 1, pp. 21–43, 2016. View at Publisher · View at Google Scholar · View at Scopus
  24. F. Shen, J. Min, and D. Xu, “Assimilation of radar radial velocity data with the WRF Hybrid ETKF-3DVAR system for the prediction of Hurricane Ike (2008),” Atmospheric Research, vol. 169, pp. 127–138, 2016. View at Publisher · View at Google Scholar · View at Scopus
  25. Y. F. Xie, S. E. Koch, J. A. McGinley, S. Albers, and N. Wang, “A sequential variational analysis approach for mesoscale data assimilation,” in Proceedings of the 21st Conference on Weather Analysis and Forecasting/17th Conference on Numerical Weather Prediction, 15B.7, American Meteorological Society, Washington, DC, USA, 2005, http://ams.confex.com/ams/pdfpapers/93468.pdf.
  26. Y. Xie, S. Koch, J. McGinley et al., “A space-time multiscale analysis system: a sequential variational analysis approach,” Monthly Weather Review, vol. 139, no. 4, pp. 1224–1240, 2011. View at Publisher · View at Google Scholar · View at Scopus
  27. Z. J. He, Y. F. Xie, W. Li et al., “Application of the sequential three-dimensional variational method to assimilating SST in a global ocean model,” Journal of Atmospheric and Oceanic Technology, vol. 25, no. 6, pp. 1018–1033, 2008. View at Publisher · View at Google Scholar · View at Scopus
  28. W. Li, Y. Xie, Z. He et al., “Application of the multigrid data assimilation scheme to the China seas' temperature forecast,” Journal of Atmospheric and Oceanic Technology, vol. 25, no. 11, pp. 2106–2116, 2008. View at Publisher · View at Google Scholar · View at Scopus
  29. W. Li, Y. F. Xie, S.-M. Deng, and Q. Wang, “Application of the multigrid method to the two-dimensional Doppler radar radial velocity data assimilation,” Journal of Atmospheric and Oceanic Technology, vol. 27, no. 2, pp. 319–332, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. W. Li, Y. F. Xie, and G. J. Han, “A theoretical study on the multi-grid data assimilation scheme using a simple bilinear interpolation scheme,” Acta Oceanologica Sinica, vol. 32, no. 3, pp. 80–87, 2013. View at Google Scholar
  31. R. Fletcher, Practical Methods of Optimization, John Wiley & Sons, Chichester, UK, 2nd edition, 1987. View at MathSciNet
  32. R. H. Byrd, P. Lu, J. Nocedal, and C. Y. Zhu, “A limited memory algorithm for bound constrained optimization,” SIAM Journal on Scientific Computing, vol. 16, no. 5, pp. 1190–1208, 1995. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  33. J. Derber and A. Rosati, “A global oceanic data assimilation system,” Journal of Physical Oceanography, vol. 19, no. 9, pp. 1333–1347, 1989. View at Publisher · View at Google Scholar