Numerical Study of Boundary Layer Structure and Rainfall after Landfall of Typhoon Fitow (2013): Sensitivity to Planetary Boundary Layer Parameterization

Meiying DONG; Chunxiao JI; Feng CHEN; Yuqing WANG

doi:10.1007/s00376-018-7281-9

ADVANCES IN ATMOSPHERIC SCIENCES > 2019 > 36(4): 431-450. > DOI: 10.1007/s00376-018-7281-9

Meiying DONG, Chunxiao JI, Feng CHEN, Yuqing WANG. 2019: Numerical Study of Boundary Layer Structure and Rainfall after Landfall of Typhoon Fitow (2013): Sensitivity to Planetary Boundary Layer Parameterization. Adv. Atmos. Sci, 36(4): 431-450., https://doi.org/10.1007/s00376-018-7281-9

Citation:

PDF (8124 KB)

Numerical Study of Boundary Layer Structure and Rainfall after Landfall of Typhoon Fitow (2013): Sensitivity to Planetary Boundary Layer Parameterization

1.
Zhejiang Institute of Meteorological Sciences, Hangzhou 310008, China
2.
International Pacific Research Center, and Department of Meteorology, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, Honolulu, Hawaii, HI 96822, USA

More Information

Corresponding author:
Chunxiao JI
Received Date: 09 November 2017
Revised Date: 13 November 2018
Accepted Date: 19 November 2018

Graphical Abstract

Abstract

Abstract

The boundary layer structure and related heavy rainfall of Typhoon Fitow (2013), which made landfall in Zhejiang Province, China, are studied using the Advanced Research version of the Weather Research and Forecasting model, with a focus on the sensitivity of the simulation to the planetary boundary layer parameterization. Two groups of experimentsone with the same surface layer scheme and including the Yonsei University (YSU), Mellor-Yamada-Nakanishi-Niino Level 2.5, and Bougeault and Lacarrere schemes; and the other with different surface layer schemes and including the Mellor-Yamada-Janji? and Quasi-Normal Scale Elimination schemesare investigated. For the convenience of comparative analysis, the simulation with the YSU scheme is chosen as the control run because this scheme successfully reproduces the track, intensity and rainfall as a whole. The maximum deviations in the peak tangential and peak radial winds may account for 11% and 33% of those produced in the control run, respectively. Further diagnosis indicates that the vertical diffusivity is much larger in the first group, resulting in weaker vertical shear of the tangential and radial winds in the boundary layer and a deeper inflow layer therein. The precipitation discrepancies are related to the simulated track deflection and the differences in the simulated low-level convergent flow among all tests. Furthermore, the first group more efficiently transfers moisture and energy and produces a stronger ascending motion than the second, contributing to a deeper moist layer, stronger convection and greater precipitation.
- planetary boundary layer parameterization,
- landfalling typhoon,
- boundary layer structure,
- rainfall
摘要

针对大气行星边界层物理过程影响登陆台风结构和强降水的敏感性问题, 本文以2013年造成中国浙江最强日降水的Fitow台风为例, 利用高分辨率WRF模式和谱动力张弛逼近技术, 设计了两组敏感性试验: 第一组试验采用了相同的表面层方案, 包括采用YSU, MYNN2和BouLac边界层方案的3个试验; 第二组试验采用了不同的表面层方案, 包括采用MYJ和QNSE边界层方案的2个试验, 探讨了大气行星边界层参数化对登陆台风结构和强降水的影响效应和可能过程. 结果表明: (1)采用YSU边界层方案较成功再现了Fitow台风的路径, 强度和极端强降水, 路径和强度平均误差为19 km和2.8 m s-1 , 逐6h降水的相对误差多小于10%, 为方便文中对比分析该试验被选为控制试验. (2)台风边界层结构对于不同边界层参数化方案比较敏感. 各试验之间最大切向风和径向风的偏差可分别占控制试验最大切向风和切向风的11%和33%, 这种差异主要与水汽和能量的湍流垂直混合有关. 第一组试验中垂直交换效率明显高于第二组试验, 从而导致了第一组试验中台风边界层结构具有较弱的切向风, 径向风垂直切变和更深厚入流. (3)不同边界层参数化方案对登陆后台风强降水影响明显. 这一方面与不同边界层参数化引起引导气流不同导致台风路径出现偏折有关, 另一方面也与台风和周围环境相互作用导致低层辐合线位置差异相联系. 不同边界层参数化过程的反馈使得暴雨区在低层风场, 辐合以及垂直运动产生差异. 总体上, 相比于第二组试验, 第一组试验水汽和能量的湍流垂直交换更加充分, 上升运动更强, 更有助于深厚湿层, 强对流和台风极端强降水的发生.
- 行星边界层参数化 /
- 登陆台风 /
- 边界层结构 /
- 降水

FullText(HTML)

References (57)

References

Black, P. G.,Coauthors, 2007: Air-sea exchange in hurricanes: Synthesis of observations from the coupled boundary layer air-sea transfer experiment. Bull. Amer. Meteor. Soc., 88, 357-374, https://doi.org/10.1175/BAMS-88-3-357

Bougeault P.,P. Lacarrere, 1989: Parameterization of orography-induced turbulence in a mesobeta-scale model. Mon. Wea. Rev., 117, 1872, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2

Braun S. A.,W.-K. Tao, 2000: Sensitivity of high-resolution simulations of Hurricane Bob (1991) to planetary boundary layer parameterizations. Mon. Wea. Rev., 128, 3941-3961, https://doi.org/10.1175/1520-0493(2000)129<3941:SOHRSO>2.0.CO;2

Cha D.-H.,Y. Q. Wang, 2013: A dynamical initialization scheme for real-time forecasts of tropical cyclones using the WRF model. Mon. Wea. Rev., 141, 964-986, https://doi.org/10.1175/MWR-D-12-00077.1

Chen L.-S.,Y.-H. Ding, 1979: An Introduction to Typhoons in the Western Pacific. Science Press, Beijing, China, 179- 181. (in Chinese)

Chen F.,J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2

Davis C.,L. F. Bosart, 2002: Numerical simulations of the genesis of Hurricane Diana (1984). Part II: Sensitivity of track and intensity prediction. Mon. Wea. Rev., 130, 1100-1124, https://doi.org/10.1175/1520-0493(2002)130<1100:NSOTGO>2.0.CO;2

Deng G.,Y.-S. Zhou, and J.-T. Li, 2005: The experiments of the boundary layer schemes on simulated typhoon Part I. The effect on the structure of typhoon. Chinese Journal of Atmospheric Sciences, 29(3), 813-824, https://doi.org/10.3878/j.issn.1006-9895.2005.03.09

Dudhia J.,1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077-3107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2

Emanuel K. A.,1986: An air-sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci., 43, 585, https://doi.org/10.1175/1520-0469(1986)043<0585:AASITF>2.0.CO;2

Emanuel K. A.,1995: Sensitivity of tropical cyclones to surface exchange coefficients and a revised steady-state model incorporating eye dynamics. J. Atmos. Sci., 52, 3969-3976, https://doi.org/10.1175/1520-0469(1995)052<3969:SOTCTS>2.0.CO;2

Emanuel K. A.,1997: Some aspects of hurricane inner-core dynamics and energetics. J. Atmos. Sci., 54, 1014-1026, https://doi.org/10.1175/1520-0469(1997)054<1014:SAOHIC>2.0.CO;2

Foster R. C.,2009: Boundary-layer similarity under an axisymmetric, gradient wind vortex. Bound.-Layer Meteor., 131, 321-344, https://doi.org/10.1007/s10546-009-9379-1

Gopalakrishnan S. G.,F. D. Marks Jr., J. A. Zhang, X. Zhang, J.-W. Bao, and V. Tallapragada, 2013: A study of the impacts of vertical diffusion on the structure and intensity of the tropical cyclones using the high resolution HWRF system. J. Atmos. Sci., 70, 524-541, https://doi.org/10.1175/JAS-D-11-0340.1

Hill K. A.,G. M. Lackmann, 2009: Analysis of idealized tropical cyclone simulations using the weather research and forecasting model: Sensitivity to turbulence parameterization and grid spacing. Mon. Wea. Rev., 137: 745-765, https://doi.org/10.1175/2008MWR2220.1

Holland, G. J., 1984: Tropical cyclone motion. A comparison of theory and observation. J. Atmos. Sci., 41, 68, https://doi.org/10.1175/1520-0469(1984)041<0068:TCMACO>2.0.CO;2

Hong S.-Y.,H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124, 2322, https://doi.org/10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2

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, https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2

Hong S.-Y.,Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318-2341, https://doi.org/10.1175/MWR3199.1

Hu X.-M.,J. W. Nielsen-Gammon, and F.-Q. Zhang, 2010: Evaluation of three planetary boundary layer schemes in the WRF model. Journal of Applied Meteorology and Climatology, 49, 1831-1844, https://doi.org/10.1175/2010JAMC2432.1

Ikeda, K., Coauthors, 2010: Simulation of seasonal snowfall over Colorado, Atmos. Res., 97, 462-477, https://doi.org/10.1016/j.atmosres.2010.04.010

Janjić, Z. I., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2

Janjić, Z. I., 2000: Comments on "Development and evaluation of a convection scheme for use in climate models". J. Atmos. Sci., 57, 3686, https://doi.org/10.1175/1520-0469(2000)057<3686:CODAEO>2.0.CO;2

Janjić, Z. I., 2001: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model. NCEP Office Note #437, 61 pp.

Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898-918, https://doi.org/10.1175/MWR-D-11-00056.1

Kepert J. D.,2012: Choosing a boundary layer parameterization for tropical cyclone modeling. Mon. Wea. Rev., 140(5), 1427-1445, https://doi.org/10.1175/MWR-D-11-00217.1

Li X. L.,Z.-X. Pu, 2008: Sensitivity of numerical simulation of early rapid intensification of Hurricane Emily (2005) to cloud microphysical and planetary boundary layer parameterizations. Mon. Wea. Rev., 136(12): 4819-4838, https://doi.org/10.1175/2008MWR2366.1

Liu J. J.,F. M. Zhang, and Z. X. Pu, 2017: Numerical simulation of the rapid intensification of Hurricane Katrina (2005): Sensitivity to boundary layer parameterization schemes. Adv. Atmos. Sci., 34(4), 482-496, https://doi.org/10.1007/s00376-016-6209-5

Malkus J. S.,1958: On the structure and maintenance of the mature hurricane eye. J. Meteor., 15, 337, https://doi.org/10.1175/1520-0469(1958)015<0337:OTSAMO>2.0.CO;2

Malkus, J. S, H. Riehl, 1960: On the dynamics and energy transformations in steady-state hurricanes. Tellus, 12, 1-20, https://doi.org/10.1111/j.2153-3490.1960.tb01279.x

Mellor G. L.,T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys., 20, 851-875, https://doi.org/10.1029/RG020i004p00851

Ming J.,J. A. Zhang, 2016: Effects of surface flux parameterization on the numerically simulated intensity and structure of typhoon morakot (2009). Adv. Atmos. Sci., 33( 1), 58- 72.10.1007/s00376-015-4202-z

0cf580c2480b5e62b3e8fc4e939c9f08

http%3A%2F%2Fwww.cnki.com.cn%2FArticle%2FCJFDTotal-DQJZ201601006.htm

http://link.springer.com/10.1007/s00376-015-4202-zThe effects of surface flux parameterizations on tropical cyclone(TC) intensity and structure are investigated using the Advanced Research Weather Research and Forecasting(WRF-ARW) modeling system with high-resolution simulations of Typhoon Morakot(2009).Numerical experiments are designed to simulate Typhoon Morakot(2009) with different formulations of surface exchange coefficients for enthalpy(C_K) and momentum(C_D) transfers,including those from recent observational studies based on in situ aircraft data collected in Atlantic hurricanes.The results show that the simulated intensity and structure are sensitive to C_K and C_D,but the simulated track is not.Consistent with previous studies,the simulated storm intensity is found to be more sensitive to the ratio of C_K/C_D than to C_K or C_D alone.The pressure-wind relationship is also found to be influenced by the exchange coefficients,consistent with recent numerical studies.This paper emphasizes the importance of C_D and C_K on TC structure simulations.The results suggest that C_D and C_K have a large impact on surface wind and flux distributions,boundary layer heights,the warm core,and precipitation.Compared to available observations,the experiment with observed C_D and C_K generally simulated better intensity and structure than the other experiments,especially over the ocean.The reasons for the structural differences among the experiments with different C_D and C_K setups are discussed in the context of TC dynamics and thermodynamics.

Mlawer E. J.,S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 663-16 682, https://doi.org/10.1029/97JD00237

Nakanishi M.,H. Niino, 2004: An improved Mellor-Yamada level-3 model with condensation physics: Its design and verification. Bound.-Layer Meteor., 112, 1-31, https://doi.org/10.1023/B:BOUN.0000020164.04146.98

Ooyama K.,1969: Numerical simulation of the life cycle of tropical cyclones. J. Atmos. Sci., 26, 3, https://doi.org/10.1175/1520-0469(1969)026<0003:NSOTLC>2.0.CO;2

Rosenthal S. L.,1971: The response of a tropical cyclone model to variations in boundary layer parameters, initial conditions, lateral boundary conditions, and domain size. Mon. Wea. Rev., 99, 767, https://doi.org/10.1175/1520-0493(1971)099<0767:TROATC>2.3.CO;2

Rotunno R.,K. A. Emanuel, 1987: An air-sea interaction theory for tropical cyclones. Part II: Evolutionary study using a nonhydrostatic axisymmetric numerical model. J. Atmos. Sci., 44, 542, https://doi.org/10.1175/1520-0469(1987)044<0542:AAITFT>2.0.CO;2

Shin H. H.,S. Y. Hong, 2011: Intercomparison of planetary boundary-layer parametrizations in the WRF model for a single day from CASES-99. Bound.-Layer Meteor., 139(2), 261-281, https://doi.org/10.1007/s10546-010-9583-z

Skamarock, W. C.,Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-475 + STR, Natl. Cent. for Atmos. Res., Boulder, Colo, https://doi.org/10.5065/D68S4MVH

Smith, R. K, G. L. Thomsen, 2010: Dependence of tropical-cyclone intensification on the boundary-layer representation in a numerical model. Quart. J. Roy. Meteor. Soc., 136, 1671-1685, https://doi.org/10.1002/qj.687

Stull R. B.,1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, 515-520, https://doi.org/10.1007/978-94-009-3027-8

Sukoriansky S.,B. Galperin, 2008: A Quasi-Normal Scale Elimination (QNSE) theory of turbulent flows with stable stratification and its application in weather forecast systems. Proc. 6th IASME/WSEAS International Conf. on Heat Transfer, Thermal Engineering and Environment (THE'08), Rhodes, Greece, WSEAS Press, 376- 380.

Sukoriansky S.,B. Galperin, and V. Perov, 2005: `Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice'. Bound.-Layer Meteor., 117, 231-257, https://doi.org/10.1007/s10546-004-6848-4

Wang C.-X.,2013: Experiments of influence of planetary boundary layer parameterization on Muifa typhoon prediction. Advances in Earth Science, 28( 2), 197- 208. (in Chinese)10.11867/j.issn.1001-8166.2013.02.0197

9daffc9880fb91f8cb290a03e6d7d3bb

http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-DXJZ201302003.htm

http://en.cnki.com.cn/Article_en/CJFDTOTAL-DXJZ201302003.htmThe GRAPES-TCM is used to make prediction experiments for Typhoon Muifa(1109).Thirty six experiments are made and the integral time is 72 h.By experiments,the influence of two boundary layer parameterization schemes鈥擬RF scheme and YSU scheme on typhoon prediction under different circumstances is analyzed. Theexperiment results show that Muifa track and intensity are both sensitive to the boundary layer scheme's change.The sensitivity magnitude is related to some other factors such as convection parameterization scheme and typhoon initial intensity.The intensity sensitivity is greater than the track sensitivity.For weak typhoon,the track and intensity predictions with YSU scheme are overall better than that with MRF scheme.For strong typhoon,between the two boundary layer schemes,MRF scheme's track prediction is better.Which scheme's intensity prediction is better is related to the choice of the convection scheme.In all cases,Muifa intensity with YSU scheme is obviously stronger than that with MRF scheme,and the precipitation and the sensible heat flux and latent heat flux with YSU scheme are all greater than that with MRF scheme.When the boundary layer scheme is YSU scheme,the turbulence mixing in the boundary layer is more powerful,which leads to more sensible heat flux and more latent heat flux.More latent heat flux leads to more precipitation which releases more latent heat.More latent heat release and more sensible heat flux lead to stronger typhoon.

Wang H.,Y. Q. Wang, and H.-M. Xu, 2013: Improving simulation of a tropical cyclone using dynamical initialization and large-scale spectral nudging: A case study of Typhoon Megi (2010). Acta Meteorologica Sinica, 27, 455-475, https://doi.org/10.1007/s13351-013-0418-y

Wang Y. Q.,2012: Recent research progress on tropical cyclone structure and intensity. Tropical Cyclone Research and Review, 1, 254-275, https://doi.org/10.6057/2012TCRR02.05

Wang Y. Q.,J. D. Kepert, and G. J. Holland, 2001: The effect of sea spray evaporation on tropical cyclone boundary layer structure and intensity. Mon. Wea. Rev., 129, 2481-2500, https://doi.org/10.1175/1520-0493(2001)129<2481:TEOSSE>2.0.CO;2

Xu H.-Y.,Y. Zhu, R. Liu, H.-F. Shen, D.-H. Wang, and G.-Q. Zhai, 2013: Simulation experiments with different planetary boundary layer schemes in the lower reaches of the Yangtze River. Chinese Journal of Atmospheric Sciences, 37(1), 149-159, https://doi.org/10.3878/j.issn.1006-9895.2012.12021

Ying M.,W. Zhang, H. Yu, X. Q. Lu, J. X. Feng, Y. X. Fan, Y. T. Zhu, and D. Q. Chen, 2014: An overview of the China meteorological administration tropical cyclone database. J. Atmos. Oceanic Technol., 31, 287-301, https://doi.org/10.1175/JTECH-D-12-00119.1

Yu Z.,Y. Wang and H. Xu, 2015: Observed rainfall asymmetry in tropical cyclones making landfall over China. J. Appl. Meteor. Climatol., 54( 1), 117- 136.10.1175/JAMC-D-13-0359.1

9fd15219dde150bd5b290f89017ca540

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JApMC..54..117Y

http://journals.ametsoc.org/doi/10.1175/JAMC-D-13-0359.1In this study, the rainfall asymmetries in tropical cyclones (TCs) that made landfall in the Hainan (HN),Guangdong (GD), Fujian (FJ), and Zhejiang (ZJ) provinces of mainland China and Taiwan (TW) from2001 to 2009 were analyzed on the basis of TRMM satellite 3B42 rainfall estimates. The results reveal thatin landfalling TCs, the wavenumber 1 rainfall asymmetry shows the downshear to downshear-left maximumin environmental vertical wind shear (VWS), which is consistent with previous studies for TCs overthe open oceans. A cyclonic rotation from south China to east China in the location of the rainfall maximumhas been identified. Before landfall, the location of the rainfall maximum rotated from southwest tosoutheast of the TC center for TCs making landfall in the regions from HN to GD, TW, FJ, and ZJ. Afterlandfall, the rotation became from southwest to northeast of the TC center from south China to east China.It is shown that this cyclonic rotation in the location of the rainfall maximum is well correlated with a cyclonicrotation from south China to east China in the environmental VWS between 200 and 850 hPa, indicatingthat the rainfall asymmetry in TCs that made landfall over China is predominantly controlled bythe large-scale VWS. The cyclonic rotation of VWS is found to be related to different interactions betweenthe midlatitude westerlies and the landfalling TCs in different regions. The results also indicate that theaxisymmetric (wavenumber 0) component of rainfall generally decreased rapidly after landfall in moststudied regions.1.

Zhang C.-X.,Y. Q. Wang, and K. Hamilton, 2011: Improved representation of boundary layer clouds over the Southeast Pacific in ARW-WRF using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev., 139, 3489-3513, https://doi.org/10.1175/MWR-D-10-05091.1

Zhang D.-L.,W. Z. Zheng, 2004: Diurnal cycles of surface winds and temperatures as simulated by five boundary layer parameterizations. J. Appl. Meteor., 43, 157, https://doi.org/10.1175/1520-0450(2004)043<0157:DCOSWA>2.0.CO;2

Zhang F. M.,Z. X. Pu, 2017: Effects of vertical eddy diffusivity parameterization on the evolution of landfalling hurricanes. J. Atmos. Sci., 74(6), 1879-1905, https://doi.org/10.1175/JAS-D-16-0214.1

Zhang F. M.,Z. X. Pu, and C. H. Wang, 2017: Effects of boundary layer vertical mixing on the evolution of hurricanes over land. Mon. Wea. Rev., 145(6), 2343-2361, https://doi.org/10.1175/MWR-D-16-0421.1

Zhang J. A.,D. S. Nolan, R. F. Rogers, and V. Tallapragada, 2015: Evaluating the impact of improvements in the boundary layer parameterization on hurricane intensity and structure forecasts in HWRF. Mon. Wea. Rev., 143, 3136-3155, https://doi.org/10.1175/MWR-D-14-00339.1

Zhu P.,K. Menelaou, and Z. D. Zhu, 2014: Impact of subgrid-scale vertical turbulent mixing on eyewall asymmetric structures and mesovortices of hurricanes. Quart. J. Roy. Meteor. Soc., 140, 416-438, https://doi.org/10.1002/qj.2147

Zhu Q.-G.,J. H. Lin, S.-W. Shou, and D.-S. Tang. 2000: Principles and Methods of Synoptic Meteorology. China Meteorological Press, Beijing, China, 320- 321.

Cited By

Get Citation

PDF

XML

Article views (1865) PDF downloads (89)

Turn off MathJax

Article Contents

Abstract

References

	Qiumeng XUE, Li GUAN, Xiaoning SHI. 2022: One-Dimensional Variational Retrieval of Temperature and Humidity Profiles from the FY4A GIIRS. ADVANCES IN ATMOSPHERIC SCIENCES, 39(3): 471-486. DOI: 10.1007/s00376-021-1032-z
	Peng ZHANG, Qifeng LU, Xiuqing HU, Songyan GU, Lei YANG, Min MIN, Lin CHEN, Na XU, Ling Sun, Wenguang BAI, Gang MA, Di XIAN. 2019: Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies. ADVANCES IN ATMOSPHERIC SCIENCES, 36(9): 1027-1045. DOI: 10.1007/s00376-019-8215-x
	JIANG Yuan, LIU Liping. 2014: A Test Pattern Identification Algorithm and Its Application to CINRAD/SA(B) Data. ADVANCES IN ATMOSPHERIC SCIENCES, 31(2): 331-343. DOI: 10.1007/s00376-013-2315-9
	JIE Weihua, WU Tongwen, WANG Jun, LI Weijing, LIU Xiangwen. 2014: Improvement of 6-15 Day Precipitation Forecasts Using a Time-Lagged Ensemble Method. ADVANCES IN ATMOSPHERIC SCIENCES, 31(2): 293-304. DOI: 10.1007/s00376-013-3037-8
	JIN Ling, Fanyou KONG, LEI Hengchi*, and HU Zhaoxia. 2014: A Methodological Study on Using Weather Research and Forecasting (WRF) Model Outputs to Drive a One-Dimensional Cloud Model. ADVANCES IN ATMOSPHERIC SCIENCES, 31(1): 230-240. DOI: 10.1007/s00376-013-2257-2
	WANG Geli, YANG Peicai, ZHOU Xiuji. 2013: Nonstationary Time Series Prediction by Incorporating External Forces. ADVANCES IN ATMOSPHERIC SCIENCES, 30(6): 1601-1607. DOI: 10.1007/s00376-013-2134-z
	XUE Hai-Le, SHEN Xue-Shun, CHOU Ji-Fan. 2013: A Forecast Error Correction Method in Numerical Weather Prediction by Using Recent Multiple-time Evolution Data. ADVANCES IN ATMOSPHERIC SCIENCES, 30(5): 1249-1259. DOI: 10.1007/s00376-013-2274-1
	GUO Yanjun, DING Yihui. 2011: Impacts of Reference Time Series on the Homogenization of Radiosonde Temperature. ADVANCES IN ATMOSPHERIC SCIENCES, 28(5): 1011-1022. DOI: 10.1007/s00376-010-9211-3
	LI Zhen, YAN Zhongwei. 2010: Application of Multiple Analysis of Series for Homogenization to Beijing Daily Temperature Series (1960--2006). ADVANCES IN ATMOSPHERIC SCIENCES, 27(4): 777-787. DOI: 10.1007/s00376-009-9052-0
	Peng Yongqing, Zhu Yufeng, Yan Shaojin. 1994: Preliminary Study of Reconstruction of a Dynamic System Using an One-Dimensional Time Series. ADVANCES IN ATMOSPHERIC SCIENCES, 11(3): 277-284. DOI: 10.1007/BF02658146

Numerical Study of Boundary Layer Structure and Rainfall after Landfall of Typhoon Fitow (2013): Sensitivity to Planetary Boundary Layer Parameterization

Abstract

摘要

References

Related Articles

Catalog

Numerical Study of Boundary Layer Structure and Rainfall after Landfall of Typhoon Fitow (2013): Sensitivity to Planetary Boundary Layer Parameterization

Abstract

摘要

References

Related Articles

Catalog

Export File

Citation

Format

Content