Skip to main content

Advertisement

SpringerLink
  • Log in
  1. Home
  2. Advances in Atmospheric Sciences
  3. Article
Ground-Space-Sky Observing System Experiment during Tropical Cyclone Mulan in August 2022
Download PDF
Download PDF
  • News & Views
  • Published: 01 November 2022

Ground-Space-Sky Observing System Experiment during Tropical Cyclone Mulan in August 2022

  • Pak-wai Chan1,
  • Wei Han2,
  • Betty Mak1,
  • Xiaohao Qin3,
  • Yongzhu Liu2,
  • Ruoying Yin2 &
  • …
  • Jincheng Wang2 

Advances in Atmospheric Sciences volume 40, pages 194–200 (2023)Cite this article

  • 202 Accesses

  • 31 Altmetric

  • Metrics details

Abstract

Forecasting tropical cyclone track and intensity is a great challenge for the meteorological community, and safeguarding the life and property of people living near the coast is an important issue. One major reason for challenging forecasts is the lack of observations over the vast oceans. During tropical cyclone Mulan between 8 and 10 August 2022 over the northern part of the South China Sea, the meteorological authority and research institutes of Chinese mainland collaborated with the meteorological service in Hong Kong on conducting the first-ever ground-space-sky observing system experiment on tropical cyclone Mulan. The enhanced targeted observations collected during the experiment include Geostationary Interferometric Infrared Sounder, round-trip radiosondes, and aircraft-launched dropsondes. This paper describes the campaign, technical details of the meteorological models used, and impact of the additional targeted observation data on the tropical cyclone forecast. Ideally, similar enhanced observation campaigns could be conducted in the future, not only in the northern part of the South China Sea, but also in other ocean basins.

摘要

缺乏观测数据是台风路径和强度预报面临的一个巨大挑战。2022年8月8−10日间,中国气象局地球系统数值预报中心,联合国家卫星气象中心、国家气象中心、中国气象局大气探测中心,以及中国科学院大气物理研究所大气科学与地球流体力学数值模拟国家重点实验室、复旦大学大气海洋科学系和香港天文台等高校与科研业务单位,在我国南海上空、针对台风木兰(2022)开展了首次地空天观测系统试验。通过风云四号卫星高光谱探测仪、机载下投探空仪、和往返平飘式探空仪获得了宝贵的观测资料。文章对试验方法、试验过程及观测数据对台风实时预报的改进进行了介绍,并以此将推动相关台风观测试验在我国海域的实施。

Download to read the full article text

Working on a manuscript?

Avoid the most common mistakes and prepare your manuscript for journal editors.

Learn more

References

  • Cao, X. Z., Q. Y. Guo, and R. K. Yang, 2019: Research of rising and falling twice sounding based on long-time interval of flat-floating. Chinese Journal of Scientific Instrument, 40(2), 198–204, https://doi.org/10.19650/j.cnki.cjsi.J1803748. (in Chinese with English abstract)

    Google Scholar 

  • Chan, P. W., N. G. Wu, C. Z. Zhang, W. J. Deng, and K. K. Hon, 2018: The first complete dropsonde observation of a tropical cyclone over the South China Sea by the Hong Kong Observatory. Weather, 73, 227–234, https://doi.org/10.1002/wea.3095.

    Article  Google Scholar 

  • Chen, D. H., J. S. Xue, X. S. Shen, J. Sun, Q. L. Wan, Z. Y. Jin, and X. L. Li, 2012: Application and prospect of a new generation of numerical weather prediction system (GRAPES). Strategic Study of CAE., 14(9), 46–54.

    Google Scholar 

  • Chen, G., B. Wang, and J. J. Liu, 2021: Study on the sensitivity of initial perturbations to the development of a vortex observed in Southwest China. J. Geophys. Res.: Atmos., 126, e2021JD034715, https://doi.org/10.1029/2021JD034715.

    Article  Google Scholar 

  • Courtier, P., J. N. Thépaut, and A. Hollingsworth, 1994: A strategy for operational implementation of 4D-Var, using an incremental approach. Quart. J. Roy. Meteor. Soc., 120(519), 1367–1387, https://doi.org/10.1002/qj.49712051912.

    Article  Google Scholar 

  • Duan, W. S., X. Q. Li, and B. Tian, 2018: Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño. Climate Dyn., 51, 3351–3368, https://doi.org/10.1007/s00382-018-4082-x.

    Article  Google Scholar 

  • Guo, Q. Y., R. K. Yang, K. Q. Cheng, and C. X. Li, 2020: Refractive index quality control and comparative analysis of multi-source occultation based on sounding observation. Journal of Applied Meteorological Science, 31(1), 13–26, https://doi.org/10.11898/1001-7313.20200102. (in Chinese with English abstract)

    Google Scholar 

  • Hu, H. Q., J. Y. Liu, L. L. Da, W. H. Guo, K. Liu, and B. L. Cui, 2021: Identification of the sensitive area for targeted observation to improve vertical thermal structure prediction in summer in the Yellow Sea. Acta Oceanologica Sinica, 40(7), 77–87, https://doi.org/10.1007/s13131-021-1738-x.

    Article  Google Scholar 

  • Jiang, L., W. S. Duan, and H. L. Liu, 2022: The most sensitive initial error of sea surface height anomaly forecasts and its implication for target observations of mesoscale eddies. J. Phys. Oceanogr., 52, 723–740, https://doi.org/10.1175/JPO-D-21-0200.1.

    Google Scholar 

  • Li, J., J. L. Li, J. Otkin, T. J. Schmit, and C. Y. Liu, 2011: Warning information in a preconvection environment from the geostationary advanced infrared sounding system — A simulation study using the IHOP case. J. Appl. Meteorol. Climatol., 50, 776–783, https://doi.org/10.1175/2010JAMC2441.1.

    Article  Google Scholar 

  • Liu, Y. Z., X. S. Shen, and X. L. Li, 2013: Research on the singular vector perturbation of the GRAPES global model based on the total energy norm. Acta Meteorologica Sinica, 71(3), 517–526, https://doi.org/10.11676/qxxb2013.043. (in Chinese with English abstract)

    Google Scholar 

  • Liu, Y. Z., L. Zhang, and Z. H. Lian, 2018: Conjugate gradient algorithm in the four-dimensional variational data assimilation system in GRAPES. Journal of Meteorological Research, 32(6), 974–984, https://doi.org/10.1007/s13351-018-8053-2.

    Article  Google Scholar 

  • Lu, Y., and H. H. Zhou, 2016: Statistical and computational guarantees of Lloyd’s algorithm and its variants. arXiv: 1612.02099, https://doi.org/10.48550/arXiv.1612.02099.

  • Mu, M., W. S. Duan, and B. Wang, 2003: Conditional nonlinear optimal perturbation and its applications. Nonlinear Processes in Geophysics, 10, 493–501, https://doi.org/10.5194/npg-10-493-2003.

    Article  Google Scholar 

  • Mu, M., F. F. Zhou, and H. L. Wang, 2009: A method for identifying the sensitive areas in targeted observations for tropical cyclone prediction: Conditional nonlinear optimal perturbation. Mon. Wea. Rev., 137, 1623–1639, https://doi.org/10.1175/2008MWR2640.1.

    Article  Google Scholar 

  • Mu, M., R. Feng, and W. S. Duan, 2017: Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its prediction. J. Geophys. Res.: Oceans, 122, 1141–1153, https://doi.org/10.1002/2016JC012527.

    Article  Google Scholar 

  • Palmer, T. N., R. Gelaro, J. Barkmeijer, and R. Buizza, 1998: Singular vectors, metrics, and adaptive observations. Journal of the Atmospheric Sciences, 55, 633–653, https://doi.org/10.1175/1520-0469(1998)055<0633:SVMAAO>2.0.CO;2.

    Article  Google Scholar 

  • Paraskevopoulou, S. E., D. Y. Barsakcioglu, M. R. Saberi, A. Eftekhar, and T. G. Constandinou, 2013: Feature extraction using first and second derivative extrema (FSDE) for real-time and hardware-efficient spike sorting. Journal of Neuroscience Methods, 215(1), 29–37, https://doi.org/10.1016/j.jneumeth.2013.01.012.

    Article  Google Scholar 

  • Qin, X. H., and M. Mu, 2012: Influence of conditional nonlinear optimal perturbations sensitivity on typhoon track forecasts. Quart. J. Roy. Meteor. Soc., 138, 185–197, https://doi.org/10.1002/qj.902.

    Article  Google Scholar 

  • Qin, X. H., W. S. Duan, P.-W. Chan, B. Y. Chen, and K.-N. Huang, 2022: Effects of dropsonde data in field campaigns on forecasts of tropical cyclones over the western North Pacific in 2020 and the role of CNOP sensitivity. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-022-2136-9.

  • Rousseeuw, P. J., 1987: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65, https://doi.org/10.1016/0377-0427(87)90125-7.

    Article  Google Scholar 

  • Schmit, T. J., J. Li, S. A. Ackerman, and J. J. Gurka, 2009: High-spectral- and high-temporal-resolution infrared measurements from geostationary orbit. J. Atmos. Oceanic Technol., 26(11), 2273–2292, https://doi.org/10.1175/2009jtecha1248.1.

    Article  Google Scholar 

  • Simon, H. D., 1984: The Lanczos algorithm with partial reorthogonalization. Mathematics of Computation, 42(165), 115–142, https://doi.org/10.2307/2007563.

    Article  Google Scholar 

  • Wang, D., J. C. Wang, W. H. Tian, and Q. Y. Guo, 2020: Quality control and uncertainty analysis of return radiosonde data. Chinese Journal of Atmospheric Sciences, 44(4), 865–884, https://doi.org/10.3878/j.issn.1006-9895.1912.19203. (in Chinese with English abstract)

    Google Scholar 

  • Yang, L. C., W. S. Duan, Z. F. Wang, and W. Y. Yang, 2022: Toward targeted observations of the meteorological initial state for improving the PM2.5 forecast of a heavy haze event that occurred in the Beijing-Tianjin-Hebei region. Atmospheric Chemistry and Physics, 22, 11 429–11 453, https://doi.org/10.5194/ACP-22-11429-2022.

    Article  Google Scholar 

  • Yin, R. Y., W. Han, Z. Q. Gao, and G. Wang, 2019: A study on longwave infrared channel selection based on estimates of background errors and observation errors in the detection area of FY-4A. Acta Meteorologica Sinica, 77(5), 898–910, https://doi.org/10.11676/qxxb2019.051. (in Chinese with English abstract)

    Google Scholar 

  • Yin, R. Y., W. Han, Z. Q. Gao, and D. Di, 2020: The evaluation of FY4A’s Geostationary Interferometric Infrared Sounder (GIIRS) long-wave temperature sounding channels using the GRAPES global 4D-Var. Quart. J. Roy. Meteor. Soc., 146, 1459–1476, https://doi.org/10.1002/qj.3746.

    Article  Google Scholar 

  • Yin, R. Y., W. Han, Z. Q. Gao, and J. Li, 2021: Impact of high temporal resolution FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) radiance measurements on Typhoon forecasts: Maria (2018) case with GRAPES global 4D-Var assimilation system. Geophys. Res. Lett., 48, e2021GL093672, https://doi.org/10.1029/2021GL093672.

    Article  Google Scholar 

  • Zhang, L., and Coauthors, 2019: The operational global four-dimensional variational data assimilation system at the China Meteorological Administration. Quart. J. Roy. Meteor. Soc., 145, 1882–1896, https://doi.org/10.1002/qj.3533.

    Article  Google Scholar 

Download references

Acknowledgements

This study was adjointly supported by the National Natural Science Foundation of China (Grant Nos. 41930971 and 42075155).

Author information

Authors and Affiliations

  1. Hong Kong Observatory, Hong Kong, China

    Pak-wai Chan & Betty Mak

  2. China Meteorological Administration Earth System Modeling and Prediction Centre, Beijing, 100081, China

    Wei Han, Yongzhu Liu, Ruoying Yin & Jincheng Wang

  3. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Xiaohao Qin

Authors
  1. Pak-wai Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Betty Mak
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaohao Qin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yongzhu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ruoying Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jincheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaohao Qin.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chan, Pw., Han, W., Mak, B. et al. Ground-Space-Sky Observing System Experiment during Tropical Cyclone Mulan in August 2022. Adv. Atmos. Sci. 40, 194–200 (2023). https://doi.org/10.1007/s00376-022-2267-z

Download citation

  • Received: 19 September 2022

  • Revised: 30 September 2022

  • Accepted: 09 October 2022

  • Published: 01 November 2022

  • Issue Date: February 2023

  • DOI: https://doi.org/10.1007/s00376-022-2267-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

关键词

  • 地空天
  • 观测系统试验
  • 台风木兰(2022)

Key words

  • ground-space-sky
  • observing system experiment
  • TC Mulan (2022)
Download PDF

Working on a manuscript?

Avoid the most common mistakes and prepare your manuscript for journal editors.

Learn more

Advertisement

Over 10 million scientific documents at your fingertips

Switch Edition
  • Academic Edition
  • Corporate Edition
  • Home
  • Impressum
  • Legal information
  • Privacy statement
  • California Privacy Statement
  • How we use cookies
  • Manage cookies/Do not sell my data
  • Accessibility
  • FAQ
  • Contact us
  • Affiliate program

Not logged in - 44.201.94.236

Not affiliated

Springer Nature

© 2023 Springer Nature Switzerland AG. Part of Springer Nature.