Journal of Meteorological Research

, Volume 32, Issue 5, pp 804–818 | Cite as

Remote Sensing of Tropical Cyclone Thermal Structure from Satellite Microwave Sounding Instruments: Impacts of Optimal Channel Selection on Retrievals

  • Yang Han
  • Fuzhong Weng
Regular Articles


Accurate information on atmospheric temperature of tropical cyclones (TCs) is important for monitoring and prediction of their developments and evolution. For hurricanes, temperature anomaly in the upper troposphere can be derived from Advanced Microwave Sounding Unit (AMSU) and Advanced Technology Microwave Sounder (ATMS) through either regression-based or variational retrieval algorithms. This study investigates the dependency of TC warm core structure on emission and scattering processes in the forward operator used for radiance computations in temperature retrievals. In particular, the precipitation scattering at ATMS high-frequency channels can significantly change the retrieval outcomes. The simulation results in this study reveal that the brightness temperatures at 183 GHz could be depressed by 30–50 K under cloud ice water path of 1.5 mm, and thus, the temperature structure in hurricane atmosphere could be distorted if the ice cloud scattering was inaccurately characterized in the retrieval system. It is found that for Hurricanes Irma, Maria, and Harvey that occurred in 2017, their warm core anomalies retrieved from ATMS temperature sounding channels 4–15 were more reasonable and realistic, compared with the retrievals from all other channel combinations and earlier hurricane simulation results.

Key words

Advanced Technology Microwave Sounder (ATMS) Microwave Retrieval Testbed (MRT) warm core hurricane Irma Maria Harvey 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bauer, P., E. Moreau, F. Chevallier, et al.,2006: Multiple-scatter ing microwave radiative transfer for data assimilation applications. Quart. J. Roy. Meteor. Soc., 132, 1259–1281, doi: 10.1256/qj.05.153.CrossRefGoogle Scholar
  2. Boukabara, S. A., K. Garrett, W. C. Chen, et al.,2011: MiRS: An all-weather 1DVAR satellite data assimilation and retrieval system. IEEE Trans. Geosci. Remote Sens., 49, 3249–3272, doi: 10.1109/tgrs.2011.2158438.CrossRefGoogle Scholar
  3. Brown, S., B. Lambrigtsen, B. Lim, et al, 2017: Demonstrating the impact of rapid repeat passive microwave observations from the global hawk: Implications for future smallsat or GEO missions. Proceedings of 2017 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Fort Worth, TX, USA, 5938–5941, doi: 10.1109/IGARSS.2017.8128361.Google Scholar
  4. Chen, H., and D. L. Zhang, 2013: On the rapid intensification of Hurricane Wilma (2005). Part II: Convective bursts and the upper-level warm core. J. Atmos. Sci., 70, 146–162, doi: 10.1175/JAS-D-12-062.1.Google Scholar
  5. Clough, S. A., M. W. Shephard, E. J. Mlawer, et al.,2005: Atmospheric radiative transfer modeling: A summary of the AER codes. J. Quantit. Spectros. Radia. Trans., 91, 233–244, doi: 10.1016/j.jqsrt.2004.05.058.CrossRefGoogle Scholar
  6. Dolling, K., and G. M. Barnes, 2014: The evolution of Hurricane Humberto (2001). J. Atmos. Sci., 71, 1276–1291, doi: 10.1175/JAS-D-13-0164.1.CrossRefGoogle Scholar
  7. Gray, W. M., 1968: Global view of the origin of tropical disturbances and storms. Mon. Wea. Rev., 96, 669–700, doi: 10. 1175/1520-0493(1968)096<0669:GVOTOO>2.0.CO;2.CrossRefGoogle Scholar
  8. Halverson, J. B., J. Simpson, G. Heymsfield, et al.,2006: Warm core structure of Hurricane Erin diagnosed from high altitude dropsondes during CAMEX-4. J. Atmos. Sci., 63, 309–324, doi: 10.1175/JAS3596.1.CrossRefGoogle Scholar
  9. Han, Y., F. Z. Weng, X. L. Zou, et al.,2016: Characterization of geolocation accuracy of Suomi NPP Advanced Technology Microwave Sounder measurements. J. Geophys. Res. Atmos., 121, 4933–4950, doi: 10.1002/2015JD024278.CrossRefGoogle Scholar
  10. Hawkins, H. F., and D. T. Rubsam, 1968: Hurricane Hilda, 1964. Mon. Wea. Rev, 96, 617–636, doi: 10.1175/1520-0493(1968) 096<0701:HH>2.0.CO;2.CrossRefGoogle Scholar
  11. Hawkins, H. F., and S. M. Imbembo, 1976: The structure of a small, intense hurricane—Inez 1966. Mon. Wea. Rev., 104, 418–442, doi: 10.1175/1520-0493(1976)104<0418:TSOASI> 2.0.CO;2.CrossRefGoogle Scholar
  12. JPSS ATMS ATBD, 2013: Joint Polar Satellite System (JPSS) Advanced Technology Microwave Sounder (ATMS) SDR Calibration Algorithm Theoretical Basic Document (ATBD). [Available online at]. Accessed online on 5 September 2018.Google Scholar
  13. Kidder, S. Q., M. D. Goldberg, R. M. Zehr, et al.,2000: Satellite analysis of tropical cyclones using the Advanced Microwave Sounding Unit (AMSU). Bull. Amer. Meteor. Soc., 81, 1241–1259, doi: 10.1175/1520-0477(2000)081<1241:SAOTC U>2.3.CO;2.CrossRefGoogle Scholar
  14. Kim, E., C.-H. J. Lyu, K. Anderson, et al.,2014: S-NPP ATMS instrument prelaunch and on-orbit performance evaluation. J. Geophys. Res. Atmos., 119, 5653–5670, doi: 10.1002/2013 JD020483.CrossRefGoogle Scholar
  15. Komaromi, W. A., and J. D. Doyle, 2017: Tropical cyclone outflow and warm core structure as revealed by HS3 dropsonde data. Mon. Wea. Rev., 145, 1339–1359, doi: 10.1175/MWRD-16-0172.1.CrossRefGoogle Scholar
  16. La Seur, N. E., and H. F. Hawkins, 1963: An analysis of Hurricane Cleo (1958) based on data from research reconnaissance aircraft. Mon. Wea. Rev., 91, 694–709, doi: 10. 1175/1520-0493(1963)091<0694:AAOHCB>2.3.CO;2.CrossRefGoogle Scholar
  17. Liu, G. S., and J. A. Curry, 1993: Determination of characteristic features of cloud liquid water from satellite microwave measurements. J. Geophys. Res. Atmos., 98, 5069–5092, doi: 10.1029/92JD02888.CrossRefGoogle Scholar
  18. Liu, Q. H., and F. Z. Weng, 2005: One-dimensional variational retrieval algorithm of temperature, water vapor, and cloud water profiles from Advanced Microwave Sounding Unit (AMSU). IEEE Trans. Geosci. Remote Sens., 43, 1087–1095, doi: 10.1109/TGRS.2004.843211.CrossRefGoogle Scholar
  19. Liu, Q. H., and F. Z. Weng, 2006: Radiance assimilation in studying Hurricane Katrina. Geophys. Res. Lett., 33, L22811, doi: 10.1029/2006GL027543.CrossRefGoogle Scholar
  20. Liu, Y. B., D. L. Zhang, and M. K. Yau, 1999: A multiscale numerical study of Hurricane Andrew (1992). Part II: Kinematics and inner-core structures. Mon. Wea. Rev., 127, 2597–2616, doi: 10.1175/1520-0493(1999)127<2597:AMNSOH>2.0. CO;2.Google Scholar
  21. Rosenkranz, P. W., and C. D. Barnet, 2006: Microwave radiative transfer model validation. J. Geophys. Res. Atmos., 111, D09S07, doi: 10.1029/2005JD006008.Google Scholar
  22. Saunders, R., P. Rayer, P. Brunel, et al.,2007: A comparison of radiative transfer models for simulating Atmospheric Infrared Sounder (AIRS) radiances. J. Geophys. Res. Atmos., 112, D01S90, doi: 10.1029/2006JD007088.CrossRefGoogle Scholar
  23. Stern, D. P., and F. Q. Zhang, 2016: The warm-core structure of Hurricane Earl (2010). J. Atmos. Sci., 73, 3305–3328, doi: 10.1175/JAS-D-15-0328.1.CrossRefGoogle Scholar
  24. Tian, X. X., and X. L. Zou, 2016: ATMS-and AMSU-A-derived hurricane warm core structures using a modified retrieval algorithm. J. Geophys. Res. Atmos., 121, 12630–12646, doi: 10.1002/2016JD025042.CrossRefGoogle Scholar
  25. Vigh, J. L., and W. H. Schubert, 2009: Rapid development of the tropical cyclone warm core. J. Atmos. Sci., 66, 3335–3350, doi: 10.1175/2009JAS3092.1.CrossRefGoogle Scholar
  26. Wang, Z., M. T. Montgomery, and T. J. Dunkerton, 2010: Genesis of pre-Hurricane Felix (2007). Part II: Warm core formation, precipitation evolution, and predictability. J. Atmos. Sci., 67, 1730–1744, doi: 10.1175/2010JAS3435.1.Google Scholar
  27. Weng, F. Z., 2007: Advances in radiative transfer modeling in support of satellite data assimilation. J. Atmos. Sci., 64, 3799–3807, doi: 10.1175/2007JAS2112.1.CrossRefGoogle Scholar
  28. Weng, F. Z., and H. Yang, 2016: Validation of ATMS calibration accuracy using Suomi NPP pitch maneuver observations. Remote Sens., 8, 332, doi: 10.3390/rs8040332.CrossRefGoogle Scholar
  29. Weng, F. Z., and X. L. Zou, 2014: 30-year atmospheric temperature record derived by one-dimensional variational data assimilation of MSU/AMSU-A observations. Climate Dyn., 43, 1857–1870, doi: 10.1007/s00382-013-2012-5.CrossRefGoogle Scholar
  30. Weng, F., X. Zou, X. Wang, et al.,2012: Introduction to Suomi national polar-orbiting partnership advanced technology microwave sounder for numerical weather prediction and tropical cyclone applications. J. Geophys. Res. Atmos., 117, D19112, doi: 10.1029/2012JD018144.Google Scholar
  31. Weng, F. Z., X. L. Zou, N. H. Sun, et al.,2013: Calibration of Suomi national polar-orbiting partnership advanced technology microwave sounder. J. Geophys. Res. Atmos., 118, 11,187–11,200, doi: 10.1002/jgrd.50840.CrossRefGoogle Scholar
  32. Yang, H., and F. Z. Weng, 2016: Corrections for on-orbit ATMS lunar contamination. IEEE Trans. Geosci. Remote Sens., 54, 1918–1924, doi: 10.1109/TGRS.2015.2490198.CrossRefGoogle Scholar
  33. Zhu, T., and F. Z. Weng, 2013: Hurricane Sandy warm-core structure observed from Advanced Technology Microwave Sounder. Geophys. Res. Lett., 40, 3325–3330, doi: 10.1002/grl.50626.CrossRefGoogle Scholar
  34. Zou, X. L., F. Z. Weng, and H. Yang, 2014a: Connecting the time series of microwave sounding observations from AMSU to ATMS for long-term monitoring of climate. J. Atmos. Oceanic Technol., 31, 2206–2222, doi: 10.1175/JTECH-D-13-002 32.1.CrossRefGoogle Scholar
  35. Zou, X. L., L. Lin, and F. Z. Weng, 2014b: Absolute calibration of ATMS upper level temperature sounding channels using GPS RO observations. IEEE Trans. Geosci. Remote Sens., 52, 1397–1406, doi: 10.1109/TGRS.2013.2250981.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Nanjing University of Information Science & TechnologyNanjingChina
  2. 2.State Key Laboratory of Severe WeatherChinese Academy of Meteorological SciencesBeijingChina

Personalised recommendations