Assessing the Effectiveness of Spectral Nudging in Improving Tropical Cyclone Track Simulations over the Western North Pacific Using the WRF Model
Abstract
1. Introduction
2. Spectral Nudging Technique
3. Model Setup and Experiment Design
- Type 1: West–northwest–north curving tracks passing north of Taiwan (referred to as curving tracks, hereafter).
- Type 2: Northwestward tracks passing near Taiwan.
- Type 3: Westward tracks passing south of Taiwan.
- Type 4: Irregular tracks.
4. Results
4.1. Quantitative Assessment of Tropical Cyclone Track Forecast Errors
4.2. West–Northwest–North Curving Track Passing North of Taiwan Island
4.3. Northwest Track Passing Vicinity of Taiwan
4.4. Westward Track Passing South of Taiwan
4.5. Irregular Track
5. Conclusions and Discussions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
SCS | South China Sea |
WNP | Western North Pacific |
TC | Tropical cyclone |
CTL | Control sensitivity experiment |
SN | Spectral nudging sensitivity experiment |
References
- Elsner, J.B.; Liu, K.-B. Examining the ENSO-typhoon hypothesis. Clim. Res. 2003, 25, 43–54. [Google Scholar] [CrossRef]
- Chen, L. Tropical meteorological calamities and its research evaluation. Meteorol. Mon. 2010, 36, 101–110. [Google Scholar]
- Schmidt, S.; Kemfert, C.; Höppe, P. The impact of socio-economics and climate change on tropical cyclone losses in the USA. Reg. Environ. Change 2010, 10, 13–26. [Google Scholar] [CrossRef]
- Wei, Z.; Sui, G.; Tang, D. An overview of assessment and approaches on typhoon disaster. J. Catastrophol. 2012, 27, 117–123. [Google Scholar]
- Huang, W.; Duan, Y.; Xue, J.; Chen, D. Operational experiments and its performance analysis of the tropical cyclone numerical model (GRAPES_TCM). Acta Meteorol. Sin. 2007, 65, 578–587. [Google Scholar]
- Goerss, J.S.; Sampson, C.R. A history of Western North Pacific tropical cyclone track forecast skill. Weather Forecast. 2004, 19, 633–638. [Google Scholar] [CrossRef]
- Yamaguchi, M.; Ishida, J.; Sato, H.; Nakagawa, M. WGNE intercomparison of tropical cyclone forecasts by opertional NWP models: A quarter century and beyond. Bull. Am. Meteorol. Soc. 2017, 98, 2337–2349. [Google Scholar] [CrossRef]
- Chan, J.C.L.; Gary, W.M. Tropical cyclone movement and surrounding flow relationships. Mon. Weather Rev. 1982, 110, 1354–1374. [Google Scholar] [CrossRef]
- Xie, L.; Liu, B.; Peng, S. Application of scale-selective data assimilation to tropical cyclone track simulation. J. Geophys. Res. 2010, 115, D17105. [Google Scholar] [CrossRef]
- Waldron, K.M.; Paegle, J.; Horel, J.D. Sensitivity of a spectrally filtered and nudged limited-area model to outer model options. Mon. Weather Rev. 1996, 124, 529–547. [Google Scholar]
- von Storch, H.; Langenberg, H.; Feser, F. A spectral nudging technique for dynamical downscaling purposes. Mon. Weather Rev. 2000, 128, 3664–3673. [Google Scholar] [CrossRef]
- Miguez-Macho, G.; Stenchikov, G.L.; Robock, A. Regional climate simulations over North America: Interaction of local processes with improved large-scale flow. J. Clim. 2005, 18, 1227–1246. [Google Scholar] [CrossRef]
- Liu, B.; Xie, L. A scale-selective data assimilation approach to improving tropical cyclone track and intensity forecasts in a limited-area model: A case study of hurricane Felix (2007). Weather Forecast. 2012, 27, 124–140. [Google Scholar] [CrossRef]
- Cha, D.; Wang, Y. A dynamical initialization scheme for real-time forecasts of tropical cyclones using the WRF model. Mon. Weather Rev. 2013, 141, 964–986. [Google Scholar] [CrossRef]
- Guo, X.; Zhong, W. The use of a spectral nudging technique to determine the impact of environmental factors on the track of typhoon Megi (2010). Atmosphere 2017, 8, 257. [Google Scholar] [CrossRef]
- Qu, H.; Li, X.; Ling, T.; Zhang, Y. Influence of spectral nudging assimilation technique on typhoon track and intensity simulation. Mar. Forecast. 2018, 35, 17–29. [Google Scholar]
- Skamarock, W.C.; Klemp, J.B.; Dudhia, J.; Gill, D.O.; Liu, Z.; Berner, J.; Wang, W.; Powers, J.G.; Duda, M.G.; Barker, D.M.; et al. A description of the Advanced Research WRF Model version 4. In NCAR Technical Notes NCAR/TN-556+STR; National Center Atmospheric Research: Boulder, CO, USA, 2019. [Google Scholar]
- Ying, M.; Zhang, W.; Yu, H.; Lu, X.; Feng, J.; Fan, Y.; Zhu, Y.; Chen, D. An overview of the China Meteorological Administration tropical database. J. Atmos. Oceanic Technol. 2014, 31, 287–301. [Google Scholar] [CrossRef]
- Mann, H.B.; Whitney, D.R. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 1947, 18, 50–60. [Google Scholar] [CrossRef]
- Huang, W.; Dong, J.; Wang, J.; Xu, Y. Characteristics of extratropical transition of hurricane Sandy. J. Meteorol. Environ. 2015, 31, 53–62. [Google Scholar]
- Yu, J.; Tang, J.; Dai, Y.; Yu, B. Analyses in errors and their causes of Chinese typhoon track operational forecasts. Meteorol. Mon. 2012, 38, 695–700. [Google Scholar]
Description | Selection |
---|---|
WRF version | 4.0 |
Dynamic solver | ARW |
Horizontal grid spacing | 36 km |
Vertical levels | 45 (top 50 hPa) |
Integration time | 120 s |
Microphysics | WSM6 |
Longwave radiation | RRTMG |
Shortwave radiation | RRTMG |
Surface | Revised MM5 Monin–Obukhov |
Land surface | NOAH |
Planetary boundary layer | YSU |
Cumulus parameterization | Tiedtke |
Initial and boundary data | NCEP FNL 1.0° × 1.0°, every 6 h, with a 6 h boundary update |
Geographical data | USGS 30″ DEM (terrain), USGS 24-category 30″ (land use), default green fraction/albedo/soil type from WPS_GEOG |
Spin-up | 12 h (not included in evaluation period) |
Typhoon Cases | Track Patterns | Wavenumbers |
---|---|---|
Ampil 2018 | Type 1 | Ja = 6, Ka = 9 |
Haikui 2012 | Type 1 | Ja = 7, Ka = 6 |
Lekima 2019 | Type 1 | Ja = 5, Ka = 6 |
Matsa 2005 | Type 1 | Ja = 7, Ka = 10 |
Meari 2011 | Type 1 | Ja = 6, Ka = 9 |
Mitag 2019 | Type 1 | Ja = 8, Ka = 9 |
Muifa 2011 | Type 1 | Ja = 7, Ka = 10 |
Rumbia 2018 | Type 1 | Ja = 7, Ka = 6 |
Haitang 2005 | Type 2 | Ja = 11, Ka = 7 |
Soulik 2013 | Type 2 | Ja = 9, Ka = 5 |
Nepartak 2016 | Type 2 | Ja = 7, Ka = 5 (SN) Ja = 8, Ka = 6 (SN1) |
Meranti 2016 | Type 2 | Ja = 7, Ka = 5 (SN) Ja = 7, Ka = 0 (SN1) |
Saola 2012 | Type 2 | Ja = 7, Ka = 6 (SN) Ja = 8, Ka = 7 (SN1) |
Talim 2005 | Type 2 | Ja = 7, Ka = 5 |
Matmo 2014 | Type 2 | Ja = 7, Ka = 9 (SN) Ja = 6, Ka = 8 (SN1) |
Longwang 2005 | Type 2 | Ja = 8, Ka = 9 |
Dujuan 2015 | Type 2 | Ja = 7, Ka = 5 (SN) Ja = 8, Ka = 6 (SN1) |
Usagi 2013 | Type 2 | Ja = 8, Ka = 6 |
Trami 2013 | Type 2 | Ja = 7, Ka = 6 |
Soudelor 2015 | Type 2 | Ja = 7, Ka = 5 (SN) Ja = 8, Ka = 6 (SN1) |
Megi 2016 | Type 2 | Ja = 7, Ka = 5 (SN) Ja = 8, Ka = 6 (SN1) |
Damrey 2005 | Type 3 | Ja = 8, Ka = 6 |
Haiyan 2013 | Type 3 | Ja = 10, Ka = 6 |
Mangkut 2018 | Type 3 | Ja = 10, Ka = 6 (SN) Ja = 10, Ka = 5 (SN1) |
Rammasun 2014 | Type 3 | Ja = 10, Ka = 5 |
Utor 2013 | Type 3 | Ja = 7, Ka = 6 |
Ewiniar 2018 | Type 4 | Ja = 5, Ka = 5 |
Megi 2010 | Type 4 | Ja = 7, Ka = 5 |
Vicente 2012 | Type 4 | Ja = 7, Ka = 6 |
Track Type | Typhoon Cases | Track Position Errors (km) | Improvement (%) | |
---|---|---|---|---|
CTL | SN/SN1 | (CTL−SN)/CTL | ||
1 | Ampil 2018 | 198.30 | 85.74 * | 56.8 |
1 | Haikui 2012 | 235.65 | 43.83 * | 81.4 |
1 | Lekima 2019 | 431.45 | 49.97 * | 88.4 |
1 | Matsa 2005 | 116.88 | 72.74 * | 37.8 |
1 | Meari 2011 | 110.96 | 79.65 * | 28.2 |
1 | Mitag 2019 | 136.28 | 74.83 * | 45.1 |
1 | Muifa 2011 | 357.51 | 26.27 * | 92.7 |
1 | Rumbia 2018 | 172.04 | 89.24 * | 48.1 |
2 | Haitang 2005 | 297.27 | 57.50 * | 80.7 |
2 | Soulik 2013 | 129.28 | 39.30 * | 69.6 |
2 | Nepartak 2016 | 216.51 | 44.10 */41.58 * | 79.6/80.8 |
2 | Meranti 2016 | 211.75 | 50.34 */453.16 * | 76.2/−114 |
2 | Saola 2012 | 239.49 | 68.60 */49.86 * | 71.4/79.2 |
2 | Talim 2005 | 277.91 | 60.12 * | 78.4 |
2 | Matmo 2014 | 193.34 | 72.53 */73.53 * | 62.5/62.0 |
2 | Longwang 2005 | 715.03 | 81.70 * | 88.6 |
2 | Dujuan 2015 | 172.81 | 43.14 */48.10 * | 75.0/72.2 |
2 | Usagi 2013 | 44.74 | 16.87 * | 62.3 |
2 | Trami 2013 | 165.54 | 49.57 * | 70.1 |
2 | Soudelor 2015 | 52.02 | 31.82 */30.70 * | 38.8/41.0 |
2 | Megi 2016 | 218.75 | 174.94 */150.93 * | 20.0/31.0 |
3 | Damrey 2005 | 112.85 | 45.53 * | 59.7 |
3 | Haiyan 2013 | 158.72 | 28.24 * | 82.2 |
3 | Mangkut 2018 | 134.05 | 26.13 */29.75 * | 80.5/77.8 |
3 | Rammasun 2014 | 165.17 | 43.78 * | 73.5 |
3 | Utor 2013 | 361.72 | 39.86 * | 89.0 |
4 | Ewiniar 2018 | 63.54 | 76.20 | −19.9 |
4 | Megi 2010 | 205.22 | 51.68 * | 74.8 |
4 | Vicente 2012 | 198.80 | 82.72 * | 58.4 |
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Huang, W.; Xie, L.; Hong, F.; Zhu, J. Assessing the Effectiveness of Spectral Nudging in Improving Tropical Cyclone Track Simulations over the Western North Pacific Using the WRF Model. Atmosphere 2025, 16, 1028. https://doi.org/10.3390/atmos16091028
Huang W, Xie L, Hong F, Zhu J. Assessing the Effectiveness of Spectral Nudging in Improving Tropical Cyclone Track Simulations over the Western North Pacific Using the WRF Model. Atmosphere. 2025; 16(9):1028. https://doi.org/10.3390/atmos16091028
Chicago/Turabian StyleHuang, Weiwei, Lian Xie, Fei Hong, and Jiwen Zhu. 2025. "Assessing the Effectiveness of Spectral Nudging in Improving Tropical Cyclone Track Simulations over the Western North Pacific Using the WRF Model" Atmosphere 16, no. 9: 1028. https://doi.org/10.3390/atmos16091028
APA StyleHuang, W., Xie, L., Hong, F., & Zhu, J. (2025). Assessing the Effectiveness of Spectral Nudging in Improving Tropical Cyclone Track Simulations over the Western North Pacific Using the WRF Model. Atmosphere, 16(9), 1028. https://doi.org/10.3390/atmos16091028