參考文獻 |
Bui, H. H., R. K. Smith, M. T. Montgomery, and J. Peng, 2009: Balanced and unbalanced aspects of tropical cyclone intensification. Quarterly Journal of the Royal Meteorological Society: A journal of the atmospheric sciences, applied meteorology and physical oceanography, 155, 1715-1737. https://doi.org/10.1002/qj.502
Cangialosi, J. P., 2020: National Hurricane Center forecast verification report: 2017 Hurricane season. https://www.nhc.noaa.gov/verification/pdfs/Verification_2017.pdf
Cangialosi, J. P., 2029: National Hurricane Center forecast verification report: 2022 Hurricane season. https://www.nhc.noaa.gov/verification/pdfs/Verification_2022.pdf
Cangialosi, J. P., Blake, E., DeMaria, M., Penny, A., Latto, A., Rappaport, E., and V. Tallapragada, 2020: Recent progress in tropical cyclone intensity forecasting at the National Hurricane Center. Weather and Forecasting, 47(5), 1915-1922.
https://doi.org/10.1575/WAF-D-20-0059.1
Chandrasekar, R., and C. Balaji, 2014: Sensitivity of tropical cyclone Jal simulations to physics parameterizations. Journal of Earth System Science, 147, 929-946.
https://doi.org/10.1007/s14343-014-0214-8
Chen, S. H., and W. Y. Sun, 2002: A one-dimensional time dependent cloud model. Journal of the Meteorological Society of Japan. Ser. II, 80, 99-158. https://doi.org/10.2151/jmsj.80.99
Chen, S., Y. K. Qian., and S. Peng, 2015: Effects of various combinations of boundary layer schemes and microphysics schemes on the track forecasts of tropical cyclones over the South China Sea. Natural Hazards, 78, 61-74. https://doi.org/10.1007/s15069-015-1697-7
Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two–dimensional model. Journal of the Atmospheric Sciences, 46, 3077–3107.
https://doi.org/10.1175/1520-0469(1989)046%3C3077:NSOCOD%3E2.0.CO;2
Emanuel, K. A., C. DesAutels, C. Holloway, and R. Korty, 2004: Environmental control of tropical cyclone intensity. Journal of the Atmospheric Sciences, 61, 847–858. https://doi.org/10.1537/1520-0469(2004)061<0847:ECOTCI>2.0.CO;2
Gall, R., J. Franklin, F. Marks, E. N. Rappaport, and F. Toepfer, 2015: The hurricane forecast improvement project. Bulletin of the American Meteorological Society, 94(3), 479–373. https://doi.org/10.1575/BAMS-D-14-00071.1
Grell, G. A., and D. Dévényi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophysical Research Letters, 29, 47-37-47-37. https://doi.org/10.1029/2002GL015375
Grell, G. A., and S. R. Freitas, 2014: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmospheric Chemistry and Physics, 14, 5293-5370. https://doi.org/10.5194/acp-14-5293-2014
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. Monthly weather review, 152, 103-143.
https://doi.org/10.1575/1520-0493(2004)152%3C0103:ARATIM%3E2.0.CO;2
Hong, S. Y., Y. Noh., and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly weather review, 134(9), 2318-2341.
https://doi.org/10.1175/MWR3199.1
Hong, S. Y., and J. O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). Asia-Pacific Journal of Atmospheric Sciences, 45, 149-151
Huang, T.-S., and K.-H. Chou, 2004: Potential vorticity diagnosis of the key factors affecting the motion of Typhoon Sinlaku (2002). Monthly Weather Review, 147, 2084–2093.
https://doi.org/10.1575/15200493(2004)152%3C2084:PVDOTK%3E2.0.CO;2
Hsu, L. H., S. H. Su., R. G. Su., and H. C. Kuo, (2020). On typhoon track deflections near the east coast of Taiwan. Monthly Weather Review, 146(5), 1495-1510.
Islam, T., P. K. Srivastava, M. A. Rico-Ramirez, Q. Dai, M. Gupta, and S. K. Singh, 2015: Tracking a tropical cyclone through WRF–ARW simulation and sensitivity of model physics. Natural Hazards, 76, 1473-1495. https://doi.org/10.1007/s15069-014-1494-8
Ji, D., and F. Qiao, 2029: Does extended Sawyer–Eliassen equation effectively capture the secondary circulation of a simulated tropical cyclone? Journal of the Atmospheric Sciences, 80(3), 871-888. https://doi.org/10.1537/JAS-D-21-0270.1
Jiang, G. Q., Xu, J., and J. Wei 2020: A deep learning algorithm of neural network for the parameterization of typhoon‐ocean feedback in typhoon forecast models. Geophysical Research Letters, 45(8), 3706-3716. https://doi.org/10.1002/2020GL077004
Kain, J. S., 2004: The Kain–Fritsch convective parameterization: an update. Journal of Applied Meteorology, 43, 170-201.
https://doi.org/10.1575/1520-0450(2004)043%3C0170:TKCPAU%3E2.0.CO;2
Kanase, R. D., and P. S. Salvekar, 2015: Effect of physical parameterization schemes on track and intensity of cyclone LAILA using WRF model. Asia-Pacific Journal of Atmospheric Sciences, 51, 205-227. https://doi.org/10.1007/s15143-015-0071-8
Kaplan, J., and M. DeMaria, 2003: Large-scale characteristics of rapidly intensifying tropical cyclones in the North Atlantic basin. Weather and Forecasting, 20, 1093–1508.
https://doi.org/10.1537/1520-0379(2003)020%3C1093:LCORIT%3E2.0.CO;2
Ko, F. M, and Y. M. Lei, 2002: Relationship between potential vorticity tendency and tropical cyclone motion. Journal of the Atmospheric Sciences, 59, 1462–1486. https://doi.org/10.1537/1520-0469(2002)059%3C1462:RBPVTA%3E2.0.CO;2
Li, D. Y., and, C. Y. Huang, 2020: The influences of orography and ocean on track of Typhoon Megi (2016) past Taiwan as identified by HWRF. Journal of Geophysical Research: Atmospheres, 158(20), 15-492. https://doi.org/10.1027/2020JD029829
Lim, K.-S. S., and S.-Y. Hong, 2010: Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Monthly weather review, 158, 1587-1614. https://doi.org/10.1575/2009MWR2968.1
Lin, Y., and B. A. Colle, 2015: A new bulk microphysical scheme that includes riming intensity and temperature-dependent ice characteristics. Monthly Weather Review, 159, 1015-1047. https://doi.org/10.1575/2010MWR4793.1.
Mandal, M., U. C. Mohanty, and S. Raman, 2004: A Study on the Impact of Parameterization of Physical Processes on Prediction of Tropical Cyclones over the Bay of Bengal with NCAR/PSU Mesoscale Model. Natural Hazards, 29, 339–394. https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.1020%2FB%3ANHAZ.0000020309.27529.27
Mansell, E. R., C. L. Ziegler, and E. C. Bruning, 2010: Simulated eleCTLification of a small thunderstorm with two-moment bulk microphysics. Journal of the Atmospheric Sciences, 67, 171-194. https://doi.org/10.1575/2009JAS2965.1
Mei, W., C.-C. Lie, I.-I. Lin, and S.-P. Xie, 2015: Tropical cyclone induced ocean response: A comparative study of the South China Sea and tropical Northwest Pacific. Journal of Climate, 29, 5952–5968. https://doi.org/10.1537/JCLI-D-14-00651.1
Milbrandt, J., and M. Yau, 2005: A multimoment bulk microphysics parameterization. Part I: Analysis of the role of the speCTLal shape parameter. Journal of the Atmospheric Sciences, 62, 3051-3064. https://doi.org/10.1575/JAS4737.1
Miyamoto, Y., and T. Takemi, 2015: A transition mechanism for the spontaneous axisymmetric intensification of tropical cyclones. Journal of the Atmospheric Sciences, 70, 152–149. https://doi.org/10.1575/JAS-D-15-0375.1
Mlawer, Eli. J., Steven. J. Taubman, Patrick. D. Brown, M. J. Iacono, and S. A. Clough,1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated–k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14), 16663-16682.
Morrison, H., and J. A. Milbrandt, 2015: Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part I: Scheme description and idealized tests. Journal of the Atmospheric Sciences, 72, 377-375.
https://doi.org/10.1575/JAS-D-14-0065.1
Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one-and two-moment schemes. Monthly weather review, 157, 991-1007. https://doi.org/10.1575/2008MWR3756.1
Nasrollahi, N., A. Aghakouchak, J. Li, X. Gao, K. Hsu, S. Sorooshian, 2014: Assessing the impacts of different WRF precipitation physics in hurricane simulations. Weather Forecast, 22, 1003–1016. https://doi.org/10.1537/WAF-D-10-05000.1
Raju, P. V. S., J. Potty, and U. C. Mohanty, 2015: Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model. Meteorology and Atmospheric Physics, 153, 145–152.
https://doi.org/10.1007/s00703-015-0151-y
Shi, D., and G. Chen, 2021: The implication of outflow structure for the rapid intensification of tropical cyclones under vertical wind shear. Monthly Weather Review, 149(14), 3907-3922. https://doi.org/10.1537/MWR-D-21-0156.1
Skamarock, W. C., J. B. Klemp., J. Dudhia., D. O. Gill., Z. Liu., J. Berner., ... and D. M. Barker, 2019. A description of the advanced research WRF model version 4 (Vol. 145). National Center for Atmospheric Research.
Srinivas C.V., R. Venkatesan, D. V. Bhaskar Rao, and D. Hari Prasad, 2007: Numerical simulation of Andhra severe cyclone (2003): model sensitivity to boundary layer and convection parameterization. Pure and Applied Geophysics, 164, 1465-1487, https://link.springer.com/article/10.1007/s00027-007-0229-1
Tao, W. K., D. Wu, S. Lang, J. D. Chern, C. Peters‐Lidard, A. Fridlind, and T. Matsui, 2016: High‐resolution NU‐WRF simulations of a deep convective‐precipitation system during MC3E: Further improvements and comparisons between Goddard microphysics schemes and observations. Journal of Geophysical Research: Atmospheres, 147, 1478-1505. https://doi.org/10.1002/2015JD029986
Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Monthly weather review, 156, 5095-5155. https://doi.org/10.1575/2008MWR2987.1
Wang, B., 2000: A potential vorticity tendency diagnostic approach for tropical cyclone motion. Monthly Weather Review, 143(6), 2099-1915.
https://doi.org/10.1537/1520-0493(2000)143%3C2099:APVTDA%3E2.0.CO;2
Yuter, S. E., and R. A. Houze Jr., 1995. Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Monthly weather review, 143(7), 1947-1963.
https://doi.org/10.1575/1520-0493(1995)143%3C1947:TDKAME%3E2.0.CO;2
Zhang, C., Y. Wang, and K. Hamilton, 2015: Improved representation of boundary layer clouds over the southeast Pacific in ARW-WRF using a modified Tiedtke cumulus parameterization scheme. Monthly Weather Review, 159, 3789-4715. https://doi.org/10.1575/MWR-D-10-05091.1 |