Abstract
This study explored the impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot (2009) using a WRF-based ensemble Kalman filter (EnKF) data assimilation (DA) system. The results showed that the performance of radar EnKF DA was quite sensitive to the number of radars being assimilated and the DA timing relative to the landfall of the tropical cyclone (TC). It was found that assimilating radial velocity (Vr) data from all the four operational radars during the 6 h immediately before TC landfall was quite important for the track and rainfall forecasts after the TC made landfall. The TC track forecast error could be decreased by about 43% and the 24-h rainfall forecast skill could be almost tripled. Assimilating Vr data from a single radar outperformed the experiment without DA, though with less improvement compared to the multiple-radar DA experiment. Different forecast performances were obtained by assimilating different radars, which was closely related to the first-time wind analysis increment, the location of moisture transport, the quasi-stationary rainband, and the local convergence line. However, only assimilating Vr data when the TC was farther away from making landfall might worsen TC track and rainfall forecasts. Besides, this work also demonstrated that Vr data from multiple radars, instead of a single radar, should be used for verification to obtain a more reliable assessment of the EnKF performance.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Barker, D. M., W. Huang, Y. R. Guo, A. J. Bourgeois, and Q. N. Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897–914.
Chien, F.-C., and H.-C. Kuo, 2011: On the extreme rainfall of Typhoon Morakot (2009). J. Geophys. Res., 116, D05104.
Dong, J. L., and M. Xue, 2013: 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). Quart. J. Roy. Meteor. Soc., 139, 467–487.
Dowell, D. C., L. J. Wicker, and C. Snyder, 2011: Ensemble Kalman filter assimilation of radar observations of the 8 May 2003 Oklahoma City supercell: Influences of reflectivity observations on storm-scale analyses. Mon. Wea. Rev., 139, 272–294.
Fang, X. Q., Y.-H. Kuo, and A. Y. Wang, 2011: The impacts of Taiwan topography on the predictability of Typhoon Morakot’s record-breaking rainfall: A high-resolution ensemble simulation. Wea. Forecasting, 26, 613–633.
Gao, S. Z., Z. Y. Meng, F. Q. Zhang, and L. F. Bosart, 2009: Observational analysis of heavy rainfall mechanisms associated with severe tropical storm Bilis (2006) after its landfall. Mon. Wea. Rev., 137, 1881–1897.
Grell, G. A., and D. Dévényi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 38-1–38-4.
Hong, C.-C., M.-Y. Lee, H.-H. Hsu, and J.-L. Kuo, 2010: Role of submonthly disturbance and 40-50 day ISO on the extreme rainfall event associated with Typhoon Morakot (2009) in southern Taiwan. Geophys. Res. Lett., 37, L08805.
Hong, S. Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120.
Huang, C.-Y., C.-S. Wong, and T.-C. Yeh, 2011: Extreme rainfall mechanisms exhibited by Typhoon Morakot (2009). Terrestrial, Atmospheric and Oceanic Sciences, 22, 613–632.
Liang, J., L. G. Wu, X. Y. Ge, and C.-C. Wu, 2011: Monsoonal influence on Typhoon Morakot (2009). Part II: numerical study. J. Atmos. Sci., 68, 2222–2235.
Meng, Z. Y., and F. Q. Zhang, 2008a: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part III: comparison with 3DVar in a real-data case study. Mon. Wea. Rev., 136, 522–540.
Meng, Z. Y., and F. Q. Zhang, 2008b: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part IV: comparison with 3DVar in a month-long experiment. Mon. Wea. Rev., 136, 3671–3682.
Nettleton, L., S. Daud, R. Neitzel, C. Burghart, W.-C. Lee, and P. Hildebrand, 1993: SOLO: a program to peruse and edit radar data. Preprints, 26th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 338–339.
Noh, Y., W.-G. Cheon, S.-Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401–427.
Schwartz, C. S., Z. Q. Liu, Y. S. Chen, and X.-Y. Huang, 2012: Impact of assimilating microwave radiances with a limited-area ensemble data assimilation system on forecasts of Typhoon Morakot. Wea. Forecasting, 27, 424–437.
Skamarock, W. C., and Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note TN-475+STR, 113 pp.
Van Nguyen, H., and Y.-L. Chen, 2011: High-resolution initialization and simulations of Typhoon Morakot (2009). Mon. Wea. Rev., 139, 1463–1491.
Wang, C.-C., H.-C. Kuo, Y.-H. Chen, H.-L. Huang, C.-H. Chung, and K. Tsuboki, 2012: Effects of asymmetric latent heating on typhoon movement crossing Taiwan: the case of Morakot (2009) with extreme rainfall. J. Atmos. Sci., 69, 3172–3196.
Wang, M. J., M. Xue, K. Zhao, and J. L. Dong, 2014: Assimilation of T-TREC-Retrieved winds from single-Doppler radar with an ensemble Kalman filter for the forecast of Typhoon Jangmi (2008). Mon. Wea. Rev., 142, 1892–1907.
Weng, Y. H., and F. Q. Zhang, 2012: Assimilating airborne Doppler radar observations with an ensemble Kalman filter for convection-permitting hurricane initialization and prediction: Katrina (2005). Mon. Wea. Rev., 140, 841–859.
Weng, Y. H., M. Zhang, and F. Q. Zhang, 2011: Advanced data assimilation for cloud-resolving hurricane initialization and prediction. Computing in Science & Engineering, 13, 40–49.
Wu, C.-C., 2013: Typhoon Morakot: key findings from the journal TAO for improving prediction of extreme rains at landfall. Bull. Amer. Meteor. Soc., 94, 155–160.
Wu, C.-C., and M. J. Yang, 2011: Preface to the special issue on “Typhoon Morakot (2009): observation, Modeling, and Forecasting”. Terrestrial, Atmospheric and Oceanic Sciences, 22, doi: 10.3319/TAO.2011.10.01.01(TM).
Wu, L. G., J. Liang, and C.-C. Wu, 2011: Monsoonal influence on Typhoon Morakot (2009). Part I: observational analysis. J. Atmos. Sci., 68, 2208–2221.
Yen, T.-H., C.-C. Wu, and G.-Y. Lien, 2011: Rainfall simulations of Typhoon Morakot with controlled translation speed based on EnKF data assimilation. Terrestrial, Atmospheric and Oceanic Sciences, 22, 647–660.
Yu, C.-K., and L.-W. Cheng, 2013: Distribution and mechanisms of orographic precipitation associated with Typhoon Morakot (2009). J. Atmos. Sci., 70, 2894–2915.
Yu, C.-K., and L.-W. Cheng, 2014: Dual-Doppler-derived profiles of the southwesterly flow associated with southwest and ordinary typhoons off the southwestern coast of Taiwan. J. Atmos. Sci., 71, 3202–3222.
Zhang, F., C. Snyder, and J. Z. Sun, 2004: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 132, 1238–1253.
Zhang, F. Q., Z. Y. Meng, and A. Aksoy, 2006: Tests of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part I: perfect model experiments. Mon. Wea. Rev., 134, 722–736.
Zhang, F. Q., Y. H. Weng, J. A. Sippel, Z. Y. Meng, and C. H. Bishop, 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137, 2015–2125.
Zhang, F. Q., Y. H. Weng, Y.-H. Kuo, J. S. Whitaker, and B. G. Xie, 2010: Predicting Typhoon Morakot’s catastrophic rainfall with a convection-permitting mesoscale ensemble system. Wea. Forecasting, 25, 1816–1825.
Zhu, L., Q. L. Wan, X. Y. Shen, Z. Y. Meng, F. Q. Zhang, Y. H. Weng, J. Sippel, Y. D. Gao, Y. J. Zhang, and J. Yue, 2016: Prediction and predictability of high-impact western Pacific landfalling tropical cyclone Vicente (2012) through convectionpermitting ensemble assimilation of Doppler radar velocity. Mon. Wea. Rev., 144, 21–43.
Acknowledgments
This work was sponsored by the Special Fund for Meteorological Research in the Public Interest from the Ministry of Science and Technology of China (Grant No. GYHY201306004), the National Key Basic Research Program of China (Grant No. 2013CB430104), and the National Natural Science Foundation of China (Grant Nos. 41461164006, 41375048 and 41425018). C.-K. YU and L.-W. CHENG were supported by the Ministry of Science and Technology of Taiwan (Grant No. MOST103-2111-M-002-011-MY3).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yue, J., Meng, Z., Yu, CK. et al. Impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot (2009) using WRF-based ensemble Kalman filter data assimilation. Adv. Atmos. Sci. 34, 66–78 (2017). https://doi.org/10.1007/s00376-016-6028-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00376-016-6028-8