Assessing the Ensemble Assimilation System for Forecasting the Genesis of Tropical Cyclone Sonca (2017) in the Vietnam East Sea using a Lagrangian Approach
Main Article Content
Abstract
: With the aim of evaluating the cyclogenesis predictability of Sonca (2017) using an ensemble prediction system from the local ensemble transform Kalman filter (LETKF) to model WRF, the study proposed a dynamical assessment method with a Lagrangian approach that is stable and independent of time and reference systes. With this approach, the study can clearly distinguish between cases of tropical cyclone (TC) formation and non-formation in the ensemble forecast members. By evaluating the thermodynamic conditions of the low-level circulation between the forming and non-forming groups, the study found that the ocean-atmosphere interaction and the vortex merger process play imnportant roles in the formation of Sonca. The evaluation of the formation location showed that the detected vortex centers from the forming members tended to concentrate near the monsoon trough axis, indicating that this is a highly favorable region for vortex formation in the Vietnam East Sea.
Keywords:
Tropical cyclone, tropical cyclogenesis, data assimilation, LETKF, Lagrangian approach.
References
[1] J. Yuan, D. Wang, C. Liu, H. Han, H. Huang, The Characteristic Differences of Tropical Cyclones Forming Over the Western North Pacific and the South China Sea, 2007.
[2] Y. Du, L. Yang, S.P. Xie, Tropical Indian Ocean Influence on Northwest Pacific Tropical Cyclones in Summer Following Strong El Niño, Journal of Climate, Vol. 24, No. 1, 2011, pp. 315-322.
[3] Z. Ling, G. Wang, C. Wang, Z. Fan, Different effects of Tropical Cyclones Generated in the South China Sea and the Northwest Pacific on the Summer South China Sea Circulation, Journal of Oceanography - J Oceanogr, Vol. 67, 2011,
pp. 347-355,
https://doi.org/10.1007/s10872-011-0044-1.
[4] M. S. Park, M. I. Lee, D. Kim, M. M. Bell, D. H. Cha, R. L. Elsberry, Land-Based Convection Effects on Formation of Tropical Cyclone Mekkhala (2008), Monthly Weather Review,
Vol. 145, No. 4, 2017, pp. 1315-1337, https://doi.org/10.1175/mwr-d-16-0167.1.
[5] M. S. Park, H. S. Kim, C. H. Ho, R. L. Elsberry,
M. I. Lee, Tropical Cyclone Mekkhala’s (2008) Formation Over the South China Sea: Mesoscale, Synoptic-Scale, and Large-Scale Contributions, Monthly Weather Review, Vol. 143, No. 1, 2015, pp. 88-110,
https://doi.org/10.1175/mwr-d-14-00119.1.
[6] T. C. Chen, J. D. Tsay, J. Matsumoto, J. Alpert, Impact of the Summer Monsoon Westerlies on the South China Sea Tropical Cyclone Genesis in May, Weather and Forecasting, Vol. 32, No. 3, 2017,
pp. 925-947,
https://doi.org/10.1175/waf-d-16-0189.1.
[7] T. T. Tien, C. Thanh, N. D. Dung, N. T. Nga, Forecasting the Occurrence of Tropical Depressions in the Bien Dong Sea Using the Classification Method, Journal of Climate Change Science, Vol. 14, No. 6, 2020, pp. 76-83
(in Vietnamese).
[8] T. T. Tien, H. T. Ha, N. T. K. Anh, Forecasting the Formation of Tropical Depression in the Bien Dong Sea Using the WRF-NMM Model, VNU Journal of Science: Earth and Environmental Sciences, Vol. 34, No. 1S, 2018 , https://doi.org/10.25073/2588-1094/vnuees.4337 (in Vietnamese).
[9] T. T. Tien, D. N. Q. Hoa, C. Thanh, C. Kieu, Assessing the Impacts of Augmented Observations on the Forecast of Typhoon Wutip (2013)’s Formation using the Ensemble Kalman Filter, Weather and Forecasting, Vol. 27, 2020, https://doi.org/10.1175/waf-d-20-0001.1.
[10] T. Tien, H. Dao, Experiments on Using WRF Model data Assimilation of Coupled 3DVAR – LETKF in Predicting the Geneses of Tropical Cyclones in the Vietnamese East Sea, VNU Journal of Science: Earth and Environmental Sciences, Vol. 34, 2018, https://doi.org/10.25073/2588-1094/vnuees.4338 (in Vietnamese).
[11] W. C. Skamarock, J. Klemp, J. Dudhia, D. O. Gill, D. Barker, W. Wang, J. G. Powers, A Description of the Advanced Research WRF Version 3,
Vol. 27, No. 2008, pp. 3-27.
[12] C. Q. Kieu, M. T. Nguyen, T. M. Hoang, T. N. Duc, Sensitivity of the Track and Intensity Forecasts of Typhoon Megi (2010) to Satellite-derived Atmospheric Motion Vectors with the Ensemble Kalman Filter, J. Atmos. Oceanic Technol,
Vol. 29, No. 2012, pp. 1794-1810, https://doi.org/10.1175/jtech-d-12-00020.1.
[13] T. D. Du, T. N. Duc, C. Kieu, Initializing the WRF Model with Tropical Cyclone Real-time Reports Using the Ensemble Kalman Filter Algorithm, Pure Appl. Geophys, Vol. 174, 2017, pp. 2803-2825, https://doi.org/10.1007/s00024-017-1568-0.
[14] C. Q. Kieu, P. T. Minh, H. T. Mai, An Application of the Multi-physics Ensemble Kalman Filter to Typhoon Forecast, Pure Appl. Geophys, Vol. 171, 2014, pp. 1473-1497, https://doi.org/10.1007/s00024-013-0681-y.
[15] M. Tong, Impact of Assimilating Aircraft Reconnaissance Observations on Tropical Cyclone Initialization and Prediction using Operational HWRF and GSI Ensemble–Variational Hybrid Data Assimilation, Mon. Wea. Rev, Vol. 146, 2018, pp. 4155-4177, https://doi.org/10.1175/mwr-d-17-0380.1.
[16] Z. Zhang, V. Tallapragada, C. Kieu, S. Trahan,
W. Wang, HWRF Based Ensemble Prediction System using Perturbations from GEFS and Stochastic Convective Trigger Function, Trop. Cyclone Res. Rev., Vol. 3, No. 2015, pp. 145-161,
[17] B. Rutherford, T. J. Dunkerton, M. T. Montgomery, Lagrangian Vortices in Developing Tropical Cyclones, Quarterly Journal of the Royal Meteorological Society, Vol. 141, No. 693, 2015, pp. 3344-3354, https://doi.org/10.1002/qj.2616.
[18] B. Rutherford, T. Dunkerton, M. Montgomery,
S. Braun, The genesis of Hurricane Nate and its Interaction with A Nearby Environment of Very Dry Air, Atmospheric Chemistry and Physics,
Vol. 17, No. 17, 2017, pp. 10349-10366, https://doi.org/10.5194/acp-17-10349-2017.
[19] B. Rutherford, M. A. Boothe, T. J. Dunkerton,
M. T. Montgomery, Dynamical Properties of Developing Tropical Cyclones Using Lagrangian Flow Topology, Quarterly Journal of the Royal Meteorological Society, Vol. 144, No. 710, 2018, pp. 218-230, https://doi.org/10.1002/qj.3196.
[20] K. J. Tory, H. Ye, R. A. Dare, Understanding the Geographic Distribution of Tropical Cyclone
Formation for Applications in Climate Models, Climate Dynamics, Vol. 50, No. 7, 2018,
pp. 2489-2512,
https://doi.org/10.1007/s00382-017-3752-4.
[21] K. J. Tory, R. A. Dare, N. E. Davidson, J. L. McBride, S. S. Chand, The importance of Low-Deformation Vorticity in Tropical Cyclone Formation, Atmos. Chem. Phys., Vol. 13, No. 4, 2013, pp. 2115-2132, https://doi.org/10.5194/acp-13-2115-2013.
[22] K. J. Tory, R. A. Dare, Sea Surface Temperature Thresholds for Tropical Cyclone Formation, Journal of Climate, Vol. 28, No. 20, 2015,
pp. 8171-8183,
https://doi.org/10.1175/jcli-d-14-00637.1.
[23] A. Okubo, Horizontal Dispersion of Floatable Particles in the Vicinity of Velocity Singularities Such as Convergences, Deep Sea Research and Oceanographic Abstracts, Vol. 17, No. 3, 1970, pp. 445-454,
https://doi.org/10.1016/0011-7471(70)90059-8.
[24] J. Weiss, The Dynamics of Enstrophy Transfer in Two-dimensional Hydrodynamics, Physica D: Nonlinear Phenomena, Vol. 48, No. 2, 1991,
pp. 273-294,
https://doi.org/10.1016/0167-2789(91)90088-Q.
[25] G. R. M. Gregor, The Tropical Cyclone Hazard Over the South China Sea 1970–1989: Annual Spatial and Temporal Characteristics, Applied Geography, Vol. 15, No. 1, 1995, pp. 35-52, https://doi.org/10.1016/0143-6228(95)91061-2.
[26] R. W. Griffiths, E. J. Hopfinger, Experiments with Baroclinic Vortex Pairs in A Rotating Fluid, Journal of Fluid Mechanics, Vol. 173, No. 1986, pp. 501-518, https://doi.org/10.1017/S0022112086001246.
[2] Y. Du, L. Yang, S.P. Xie, Tropical Indian Ocean Influence on Northwest Pacific Tropical Cyclones in Summer Following Strong El Niño, Journal of Climate, Vol. 24, No. 1, 2011, pp. 315-322.
[3] Z. Ling, G. Wang, C. Wang, Z. Fan, Different effects of Tropical Cyclones Generated in the South China Sea and the Northwest Pacific on the Summer South China Sea Circulation, Journal of Oceanography - J Oceanogr, Vol. 67, 2011,
pp. 347-355,
https://doi.org/10.1007/s10872-011-0044-1.
[4] M. S. Park, M. I. Lee, D. Kim, M. M. Bell, D. H. Cha, R. L. Elsberry, Land-Based Convection Effects on Formation of Tropical Cyclone Mekkhala (2008), Monthly Weather Review,
Vol. 145, No. 4, 2017, pp. 1315-1337, https://doi.org/10.1175/mwr-d-16-0167.1.
[5] M. S. Park, H. S. Kim, C. H. Ho, R. L. Elsberry,
M. I. Lee, Tropical Cyclone Mekkhala’s (2008) Formation Over the South China Sea: Mesoscale, Synoptic-Scale, and Large-Scale Contributions, Monthly Weather Review, Vol. 143, No. 1, 2015, pp. 88-110,
https://doi.org/10.1175/mwr-d-14-00119.1.
[6] T. C. Chen, J. D. Tsay, J. Matsumoto, J. Alpert, Impact of the Summer Monsoon Westerlies on the South China Sea Tropical Cyclone Genesis in May, Weather and Forecasting, Vol. 32, No. 3, 2017,
pp. 925-947,
https://doi.org/10.1175/waf-d-16-0189.1.
[7] T. T. Tien, C. Thanh, N. D. Dung, N. T. Nga, Forecasting the Occurrence of Tropical Depressions in the Bien Dong Sea Using the Classification Method, Journal of Climate Change Science, Vol. 14, No. 6, 2020, pp. 76-83
(in Vietnamese).
[8] T. T. Tien, H. T. Ha, N. T. K. Anh, Forecasting the Formation of Tropical Depression in the Bien Dong Sea Using the WRF-NMM Model, VNU Journal of Science: Earth and Environmental Sciences, Vol. 34, No. 1S, 2018 , https://doi.org/10.25073/2588-1094/vnuees.4337 (in Vietnamese).
[9] T. T. Tien, D. N. Q. Hoa, C. Thanh, C. Kieu, Assessing the Impacts of Augmented Observations on the Forecast of Typhoon Wutip (2013)’s Formation using the Ensemble Kalman Filter, Weather and Forecasting, Vol. 27, 2020, https://doi.org/10.1175/waf-d-20-0001.1.
[10] T. Tien, H. Dao, Experiments on Using WRF Model data Assimilation of Coupled 3DVAR – LETKF in Predicting the Geneses of Tropical Cyclones in the Vietnamese East Sea, VNU Journal of Science: Earth and Environmental Sciences, Vol. 34, 2018, https://doi.org/10.25073/2588-1094/vnuees.4338 (in Vietnamese).
[11] W. C. Skamarock, J. Klemp, J. Dudhia, D. O. Gill, D. Barker, W. Wang, J. G. Powers, A Description of the Advanced Research WRF Version 3,
Vol. 27, No. 2008, pp. 3-27.
[12] C. Q. Kieu, M. T. Nguyen, T. M. Hoang, T. N. Duc, Sensitivity of the Track and Intensity Forecasts of Typhoon Megi (2010) to Satellite-derived Atmospheric Motion Vectors with the Ensemble Kalman Filter, J. Atmos. Oceanic Technol,
Vol. 29, No. 2012, pp. 1794-1810, https://doi.org/10.1175/jtech-d-12-00020.1.
[13] T. D. Du, T. N. Duc, C. Kieu, Initializing the WRF Model with Tropical Cyclone Real-time Reports Using the Ensemble Kalman Filter Algorithm, Pure Appl. Geophys, Vol. 174, 2017, pp. 2803-2825, https://doi.org/10.1007/s00024-017-1568-0.
[14] C. Q. Kieu, P. T. Minh, H. T. Mai, An Application of the Multi-physics Ensemble Kalman Filter to Typhoon Forecast, Pure Appl. Geophys, Vol. 171, 2014, pp. 1473-1497, https://doi.org/10.1007/s00024-013-0681-y.
[15] M. Tong, Impact of Assimilating Aircraft Reconnaissance Observations on Tropical Cyclone Initialization and Prediction using Operational HWRF and GSI Ensemble–Variational Hybrid Data Assimilation, Mon. Wea. Rev, Vol. 146, 2018, pp. 4155-4177, https://doi.org/10.1175/mwr-d-17-0380.1.
[16] Z. Zhang, V. Tallapragada, C. Kieu, S. Trahan,
W. Wang, HWRF Based Ensemble Prediction System using Perturbations from GEFS and Stochastic Convective Trigger Function, Trop. Cyclone Res. Rev., Vol. 3, No. 2015, pp. 145-161,
[17] B. Rutherford, T. J. Dunkerton, M. T. Montgomery, Lagrangian Vortices in Developing Tropical Cyclones, Quarterly Journal of the Royal Meteorological Society, Vol. 141, No. 693, 2015, pp. 3344-3354, https://doi.org/10.1002/qj.2616.
[18] B. Rutherford, T. Dunkerton, M. Montgomery,
S. Braun, The genesis of Hurricane Nate and its Interaction with A Nearby Environment of Very Dry Air, Atmospheric Chemistry and Physics,
Vol. 17, No. 17, 2017, pp. 10349-10366, https://doi.org/10.5194/acp-17-10349-2017.
[19] B. Rutherford, M. A. Boothe, T. J. Dunkerton,
M. T. Montgomery, Dynamical Properties of Developing Tropical Cyclones Using Lagrangian Flow Topology, Quarterly Journal of the Royal Meteorological Society, Vol. 144, No. 710, 2018, pp. 218-230, https://doi.org/10.1002/qj.3196.
[20] K. J. Tory, H. Ye, R. A. Dare, Understanding the Geographic Distribution of Tropical Cyclone
Formation for Applications in Climate Models, Climate Dynamics, Vol. 50, No. 7, 2018,
pp. 2489-2512,
https://doi.org/10.1007/s00382-017-3752-4.
[21] K. J. Tory, R. A. Dare, N. E. Davidson, J. L. McBride, S. S. Chand, The importance of Low-Deformation Vorticity in Tropical Cyclone Formation, Atmos. Chem. Phys., Vol. 13, No. 4, 2013, pp. 2115-2132, https://doi.org/10.5194/acp-13-2115-2013.
[22] K. J. Tory, R. A. Dare, Sea Surface Temperature Thresholds for Tropical Cyclone Formation, Journal of Climate, Vol. 28, No. 20, 2015,
pp. 8171-8183,
https://doi.org/10.1175/jcli-d-14-00637.1.
[23] A. Okubo, Horizontal Dispersion of Floatable Particles in the Vicinity of Velocity Singularities Such as Convergences, Deep Sea Research and Oceanographic Abstracts, Vol. 17, No. 3, 1970, pp. 445-454,
https://doi.org/10.1016/0011-7471(70)90059-8.
[24] J. Weiss, The Dynamics of Enstrophy Transfer in Two-dimensional Hydrodynamics, Physica D: Nonlinear Phenomena, Vol. 48, No. 2, 1991,
pp. 273-294,
https://doi.org/10.1016/0167-2789(91)90088-Q.
[25] G. R. M. Gregor, The Tropical Cyclone Hazard Over the South China Sea 1970–1989: Annual Spatial and Temporal Characteristics, Applied Geography, Vol. 15, No. 1, 1995, pp. 35-52, https://doi.org/10.1016/0143-6228(95)91061-2.
[26] R. W. Griffiths, E. J. Hopfinger, Experiments with Baroclinic Vortex Pairs in A Rotating Fluid, Journal of Fluid Mechanics, Vol. 173, No. 1986, pp. 501-518, https://doi.org/10.1017/S0022112086001246.