Advances in Atmospheric Sciences

, Volume 32, Issue 3, pp 319–335 | Cite as

The impact of AIRS atmospheric temperature and moisture profiles on hurricane forecasts: Ike (2008) and Irene (2011)

  • Jing Zheng
  • Jun Li
  • Timothy J. Schmit
  • Jinlong Li
  • Zhiquan Liu


Atmospheric InfraRed Sounder (AIRS) measurements are a valuable supplement to current observational data, especially over the oceans where conventional data are sparse. In this study, two types of AIRS-retrieved temperature and moisture profiles, the AIRS Science Team product (SciSup) and the single field-of-view (SFOV) research product, were evaluated with European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data over the Atlantic Ocean during Hurricane Ike (2008) and Hurricane Irene (2011). The evaluation results showed that both types of AIRS profiles agreed well with the ECMWF analysis, especially between 200 hPa and 700 hPa. The average standard deviation of both temperature profiles was approximately 1 K under 200 hPa, where the mean AIRS temperature profile from the AIRS SciSup retrievals was slightly colder than that from the AIRS SFOV retrievals. The mean SciSup moisture profile was slightly drier than that from the SFOV in the mid troposphere. A series of data assimilation and forecast experiments was then conducted with the Advanced Research version of the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system for hurricanes Ike and Irene. The results showed an improvement in the hurricane track due to the assimilation of AIRS clear-sky temperature profiles in the hurricane environment. In terms of total precipitable water and rainfall forecasts, the hurricane moisture environment was found to be affected by the AIRS sounding assimilation. Meanwhile, improving hurricane intensity forecasts through assimilating AIRS profiles remains a challenge for further study.

Key words

AIRS data assimilation temperature profile moisture profile hurricane forecast WRF 3DVAR 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Atlas, R., 2005: The impact of AIRS data on weather prediction. Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, 599 (July 13, 2005), doi: 10.1117/12.602540.Google Scholar
  2. Aumann, H. H., and Coauthors, 2003: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems. IEEE Trans. Geosci. Remote Sens., 41(2), 253–264, doi: 10.1109/TGRS.2002.808356.CrossRefGoogle Scholar
  3. Avila, L. A., and J. Cangialosi, 2011: Tropical Cyclone Report — Hurricane Irene (AL092011). National Hurricane Center, 45 pp. [Available online at]Google Scholar
  4. Barker, D., and Coauthors, 2012: The weather research and forecasting model’s community variational/ensemble data assimilation system: WRFDA. Bull. Amer. Meteor. Soc., 93, 831–843.CrossRefGoogle Scholar
  5. Berg, R., 2009: Tropical Cyclone Report-Hurricane Ike (AL 092008). National Hurricane Center, 55 pp. [Available online at]Google Scholar
  6. Chahine, M. T., and Coauthors, 2006: AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bull. Amer. Meteor. Soc., 87, 911–926. doi: 10.1175/BAMS-87-7-911.CrossRefGoogle Scholar
  7. Chen, S.-H., Z. Zhao, J. S. Haase, A. Chen, and F. Vandenberghe, 2008: A study of the characteristics and assimilation of retrieved MODIS total precipitable water data in severe weather simulations. Mon. Wea. Rev., 136, 3608–3628.CrossRefGoogle Scholar
  8. Clough, S. A., M. W. Shephard, E. J. Mlawer, J. S. Delamere, M. J. Iacono, K. Cady-Pereira, S. Boukabara, and P. D. Brown, 2005: Atmospheric radiative transfer modeling: A summary of the AER codes. Journal of Quantitative Spectroscopy and Radiative Transfer, 91, 233–244.CrossRefGoogle Scholar
  9. Derber, J. C., and W.-S. Wu, 1998: The use of TOVS cloud-cleared radiances in the NCEP SSI analysis system. Mon. Wea. Rev., 126, 2287–2299.CrossRefGoogle Scholar
  10. Divakarla, M., G. C. D. Barnet, M. D. Goldberg, L. M. McMillin, E. Maddy, W. Wolf, L. Zhou, and X. Liu, 2006: Validation of atmospheric infrared sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts. J. Geophys. Res., 111, D09S15, doi: 10.1029/2005JD 006116.Google Scholar
  11. Emanuel, K. A., 1999: Thermodynamic control of hurricane intensity. Nature, 401, 665–669.CrossRefGoogle Scholar
  12. Fetzer, E. J., B. H. Lambrigtsen, A. Eldering, H. H. Aumann, and M. T. Chahine, 2006: Biases in total precipitable water vapor climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer. J. Geophys. Res., 111, DS09S16, doi: 10.1029/2005JD006598.Google Scholar
  13. 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.CrossRefGoogle Scholar
  14. Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi: 10.1029/2008JD009944.CrossRefGoogle Scholar
  15. Jedlovec, G. J., S. H. Chou, B. T. Zavodsky, and W. Lapenta, 2006: The use of error estimates with AIRS profiles to improve short-term weather forecasts. Proc. SPIE. 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62331B (May 05, 2006), doi: 10.1117/12.665724.Google Scholar
  16. Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181.CrossRefGoogle Scholar
  17. Kawanishi, T., and Coauthors, 2003: The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), NASDA’s contribution to the EOS for global energy and water cycle studies. IEEE Trans. Geosci. Remote Sens., 41, 184–194.CrossRefGoogle Scholar
  18. Kummerow, C., W. Barnes, T. Kozu, J. Shiue, and J. Simpson, 1998: The tropical rainfall measuring mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15, 809–817.CrossRefGoogle Scholar
  19. Kwon, E.-H., J. Li, J. Li, B. J. Sohn, and E. Weisz, 2012: Use of total precipitable water classification of a priori error and quality control in atmospheric temperature and water vapor sounding retrieval. Adv. Atmos. Sci., 29(2), 263–273, doi: 10.1007/s00376-011-1119-z.CrossRefGoogle Scholar
  20. Leidner, S. M., L. Isaksen, and R. N. Hoffman, 2003: Impact of NSCAT winds on tropical cyclones in the ECMWF 4DVAR assimilation system. Mon. Wea. Rev., 131, 3–26.CrossRefGoogle Scholar
  21. Le Marshall, J., and Coauthors, 2006: Improving global analysis and forecasting with AIRS. Bull. Amer. Meteor. Soc., 87, 891–894.CrossRefGoogle Scholar
  22. Lee, Y.-K., Z. Li, J. Li, and T. Schmit, 2014: Evaluation of the GOES-R ABI LAP retrieval algorithm using the GOES-13 Sounder. J. Atmos. Oceanic Tech., 31, 3–19.CrossRefGoogle Scholar
  23. Li, J., and H.-L. Huang, 1999: Retrieval of atmospheric profiles from satellite sounder measurements by use of the discrepancy principle. Appl. Opt., 38, 916–923.CrossRefGoogle Scholar
  24. Li, J., and J. L. Li, 2008: Derivation of global hyperspectral resolution surface emissivity spectra from advanced infrared sounder radiance measurements. Geophys. Res. Lett., 35, L15807, doi: 10.1029/2008GL034559.CrossRefGoogle Scholar
  25. Li, J., and H. Liu, 2009: Improved hurricane track and intensity forecast using single field-of-view advanced IR sounding measurements. Geophys. Res. Lett., 36, L11813, doi: 10.1029/2009GL038285.CrossRefGoogle Scholar
  26. Li, J., W. Wolf, W. P. Menzel, W. Zhang, H.-L. Huang, and T. H. Achtor, 2000: Global soundings of the atmosphere from ATOVS measurements: The algorithm and validation. J. Appl. Meteor., 39, 1248–1268.CrossRefGoogle Scholar
  27. Li, J., W. P. Menzel, F. Sun, T. J. Schmit, and J. Gurka, 2004: AIRS sub-pixel cloud characterization using MODIS cloud products. J. Appl. Meteor., 43, 1083–1094.CrossRefGoogle Scholar
  28. Liu, H., and J. Li, 2010: An improvement in forecasting rapid intensification of typhoon Sinlaku (2008) using clear-sky full spatial resolution advanced IR soundings. J. Appl. Meteor. Climatol., 49, 821–827.CrossRefGoogle Scholar
  29. Lorenc, A. C., and Coauthors, 2000: The Met office global threedimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 126, 2991–3012.CrossRefGoogle Scholar
  30. McCarty, W., G. Jedlovec, and T. L. Miller, 2009: Impact of the assimilation of Atmospheric Infrared Sounder radiance measurements on short-term weather forecasts. J. Geophys. Res., 114, D18122, doi: 10.1029/2008JD011626.CrossRefGoogle Scholar
  31. Migliorini, S., 2012: On the equivalence between radiance and retrieval assimilation. Mon. Wea. Rev., 140, 258–265.CrossRefGoogle Scholar
  32. Migliorini, S., C. Piccolo, and C. Rodgers, 2008: Use of the information content in satellite measurements for an efficient interface to data assimilation. Mon. Wea. Rev., 136, 2633–2650.CrossRefGoogle Scholar
  33. Miyoshi, T., and M. Kunii, 2012: Using AIRS retrievals in the WRF-LETKF system to improve regional numerical weather prediction. Tellus A, 64, 18408.CrossRefGoogle Scholar
  34. Morcrette, J. J., H. W. Barker, J. N. S. Cole, M. J. Iacono, and R. Pincus, 2008: Impact of a new radiation package, McRad, in the ECMWF integrated forecasting system. Mon. Wea. Rev., 136, 4773–4798.CrossRefGoogle Scholar
  35. O’Neill, L. L., D. B. Chelton, S. K. Esbensen, and F. F. Wentz, 2005: High-resolution satellite measurements of the atmospheric boundary layer response to SST variations along the Agulhas return current. J. Climate, 18, 2706–2723.CrossRefGoogle Scholar
  36. Parkinson, C. L., 2003: Aqua: An Earth-observing satellite mission to examine water and other climate variables. IEEE Trans. Geosci. Remote Sens., 41, 265–273.CrossRefGoogle Scholar
  37. Parrish, D. F., and J. C. Derber, 1992: The national meteorological center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 1747–1763.CrossRefGoogle Scholar
  38. Pu, Z., X. Li, and E. J. Zipser, 2009: Diagnosis of the initial and forecast errors in the numerical simulation of the rapid intensification of Hurricane Emily (2005). Wea. Forecasting, 24, 1236–1251.CrossRefGoogle Scholar
  39. Pu, Z. X., and L. Zhang, 2010: Validation of atmospheric infrared sounder temperature and moisture profiles over tropical oceans and their impact on numerical simulations of tropical cyclones. J. Geophys. Res., 115, D24114, doi: 10.1029/2010JD014258.CrossRefGoogle Scholar
  40. Reale, O., J. Susskind, R. Rosenberg, E. Brin, E. Liu, L. P. Riishojgaard, J. Terry, and J. C. Jusem, 2008: Improving forecast skill by assimilation of quality-controlled AIRS temperature retrievals under partially cloudy conditions. Geophys. Res. Lett., 35, L08809, doi: 10.1029/2007GL033002.CrossRefGoogle Scholar
  41. Reale, O., W. K. Lau, J. Susskind, E. Brin, E. Liu, L. P. Riishojgaard, M. Fuentes, and R. Rosenberg, 2009: AIRS impact on the analysis and forecast track of tropical cyclone Nargis in a global data assimilation and forecasting system. Geophys. Res. Lett., 36, L06812, doi: 10.1029/2008GL037122.CrossRefGoogle Scholar
  42. Roy, C., and R. Kovordányi, 2012: Tropical cyclone track forecasting techniques—A review. Atmospheric Research, 104–105, 40–69.CrossRefGoogle Scholar
  43. Skamarock, W.C., and Coauthors, 2008: A description of the Advanced Research WRF Version 3. NCAR Tech Note, NCAR/TN-475+STR, 113 pp. [Available online at]Google Scholar
  44. Simpson, J., R. F. Adler, and G. R. North, 1988: A proposed tropical rainfall measuring mission (TRMM) satellite. Bull. Amer. Meteor. Soc., 69, 278–295.CrossRefGoogle Scholar
  45. Smith, W. L., E. Weisz, S. Kirev, D. Zhou, Z. Li, and E. Borbas, 2012: Dual-regression retrieval algorithm for real-time processing of satellite ultraspectral radiances. J. Appl. Meteor. Climatol., 51, 1455–1476.CrossRefGoogle Scholar
  46. Strow, L. L., S. E. Hannon, S. De-Souza Machado, H. E. Motteler, and D. Tobin, 2003: An overview of the AIRS Radiative Transfer Model. IEEE Trans. Geosci. Remote Sens., 41, 303–313.CrossRefGoogle Scholar
  47. Strow, L. L., S. E. Hannon, S. De-Souza Machado, H. E. Motteler, and D. C. Tobin, 2006: Validation of the atmospheric infrared sounder radiative transfer algorithm. J. Geophys. Res., 111, D09S06, doi: 10.1029/2005JD006146.Google Scholar
  48. Susskind, J., 2007: Improved atmospheric soundings and error estimates from analysis of AIRS/AMSU data. Proc. SPIE. 6684, Atmospheric and Environmental Remote Sensing Data Processing and Utilization III: Readiness for GEOSS, 66840M (September 13, 2007), doi: 10.1117/12.734336.Google Scholar
  49. Susskind, J., C. Barnet, and J. Blaisdell, 2003: Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Trans. Geosci. Remote Sens., 41, 390–409.CrossRefGoogle Scholar
  50. Susskind, J., C. Barnet, J. Blaisdell, L. Iredell, F. Keita, L. Kouvaris, G. Molnar, and M. Chahine, 2006: Accuracy of geophysical parameters derived from Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit as a function of fractional cloud cover. J. Geophys. Res., 111, D09S17, doi: 10.1029/2005JD006272.Google Scholar
  51. Susskind, J., J. M. Blaisdell, L. Irdell, and F. Keita, 2011: Improved temperature sounding and quality control methodology using AIRS/AMSU Data: The AIRS Science Team Version 5 retrieval algorithm. IEEE Trans. Geosci. Remote Sens., 49, 883–907, doi: 10.1109/TGRS.2010.2070508.CrossRefGoogle Scholar
  52. Susskind, J., J. Blaisdell, and L. Iredell, 2012: Significant advances in the AIRS Science Team Version-6 retrieval algorithm. Proc. SPIE 8510, Earth Observing Systems XVII, 85100U (October 15, 2012), doi:10.1117/12.929953.Google Scholar
  53. Tobin, D. C., and Coauthors, 2006: Atmospheric radiation measurement site atmospheric state best estimates for Atmospheric Infrared Sounder temperature and water vapor retrieval validation. J. Geophys. Res., 111, D09S14, doi: 10.1029/2005JD006103.Google Scholar
  54. Weisz, E., J. Li, J. Li, D. K. Zhou, H.-L. Huang, M. D. Goldberg, and P. Yang, 2007: Cloudy sounding and cloud-top height retrieval from AIRS alone single field-of-view radiance measurements. Geophys. Res. Lett., 34, L12802, doi: 10.1029/2007GL030219.CrossRefGoogle Scholar
  55. Weisz, E., W. L. Smith Sr., and N. Smith, 2013: Advances in simultaneous atmospheric profile and cloud parameter regression based retrieval from high-spectral resolution radiance measurements. J. Geophys. Res., 118, 6433–6443.Google Scholar
  56. Wentz, F., and T. Meissner, 2004: updated daily: AMSR-E/Aqua L2B Global Swath Ocean Products Derived from Wentz Algorithm V002, September 2008. National Snow and Ice Data Center. Boulder, Colorado USA. [Available online at ocean.html.]Google Scholar
  57. Wentz, F. J., and T. Meissner, 2007: Supplement 1 Algorithm Theoretical Basis Document for AMSR-E Ocean Algorithms. RSS Tech. Report 051707, Remote Sensing Systems, Santa Rosa, California USA, 6 pp.Google Scholar
  58. Won, Y.-I., 2008: Readme Document for AIRS Level-2 Version 5 Support Products. Goddard Earth Sciences Data and Information Services Center, National Aeronautics and Space Administration. 57 pp. [Available online at:]Google Scholar
  59. Wu, L., and Coauthors, 2012: Relationship of environmental relative humidity with North Atlantic tropical cyclone intensity and intensification rate. Geophys. Res. Lett., 39, L20809, doi: 10.1029/2012GL053546.Google Scholar
  60. Zavodsky, B. T., S. H. Chou, G. Jedlovec, and W. Lapenta, 2007: The impact of atmospheric infrared sounder (AIRS) profiles on short-term weather forecasts. Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65651J (May 07, 2007), doi:10.1117/12.718121.Google Scholar
  61. Zhang, X., Q. Xiao, and P. Fitzpatrick, 2007: The impact of multisatellite data on the initialization and simulation of Hurricane Lili’s (2002) rapid weakening phase. Mon. Wea. Rev., 135, 526–548.CrossRefGoogle Scholar
  62. Zhou, D. K., W. L. Smith, X. Liu, A. M. Larar, S. A. Mango, and H.-L. Huang, 2007: Physically retrieving cloud and thermodynamic parameters from ultraspectral IR measurements. J. Atmos. Sci., 64, 969–982.CrossRefGoogle Scholar

Copyright information

© Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Jing Zheng
    • 1
    • 2
  • Jun Li
    • 1
  • Timothy J. Schmit
    • 3
  • Jinlong Li
    • 1
  • Zhiquan Liu
    • 4
  1. 1.Cooperative Institute for Meteorological Satellite StudiesUniversity of Wisconsin-MadisonWisconsinUSA
  2. 2.National Satellite Meteorological CenterChina Meteorological AdministrationBeijingChina
  3. 3.Advanced Satellite Products Branch, Center for Satellite Applications and ResearchNESDIS/NOAAMadisonUSA
  4. 4.National Center for Atmospheric ResearchBoulderUSA

Personalised recommendations