Impact of Atmospheric Infrared Sounder Data on the Numerical Simulation of a Historical Mumbai Rain Event

Randhir Singh Atmospheric Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad, India

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P. K. Pal Atmospheric Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad, India

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C. M. Kishtawal Atmospheric Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad, India

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P. C. Joshi Atmospheric Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad, India

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Abstract

In this paper, the three-dimensional variational data assimilation scheme (3DVAR) in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) Mesoscale Model (MM5) is used to study the impact of assimilating Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles on board Aqua, a satellite that is part of NASA’s Earth Observing System. A record-breaking heavy rain event that occurred over Mumbai, India, on 26 July 2005 with 24-h rainfall exceeding 94 cm was used for the simulation.

By analyzing the data from the NCEP–NCAR reanalysis, possible causes of this heavy rainfall event were investigated. The temporal evolution of meteorological fields clearly indicates the formation of midtropospheric mesoscale vortices over Mumbai that exactly coincides with the duration of the intense rainfall. Analysis also indicated the midlevel dryness with higher temperature and moisture in the lower levels. This midlevel dryness with high temperature and moisture in the lower levels increases the conditional instability, which was conducive for the development of very severe local thunderstorms. The midtropospheric mesoscale vortices existed over Mumbai together with lower-level instability and the active monsoon conditions over the west coast resulted in intense rainfall, on the order of 94 cm in 24 h.

Numerical experiments were conducted, with two nested domains (45- and 15-km grid spacing). The assimilation of the AIRS-retrieved temperature and moisture profiles produced significant impacts on the location and intensity of the simulated rainfall. It is seen from the numerical experiments that the assimilation of AIRS data could produce the structure of mesoscale vortices, and lower-level thermodynamics and convergence much more realistically compared with the control simulation. The spatial distribution of the rainfall from the simulation using AIRS data was more realistic than that without AIRS data. To make the quantitative comparison of the predicted rainfall with the observed one, the equitable threat score and bias were calculated for different threshold values of rainfall. Inclusion of AIRS data significantly improved the precipitation as indicated by the equitable threat scores and biases for almost all of the threshold rainfall categories.

Corresponding author address: Randhir Singh, Atmospheric Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad-380015, India. Email: randhir_h@yahoo.com

Abstract

In this paper, the three-dimensional variational data assimilation scheme (3DVAR) in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) Mesoscale Model (MM5) is used to study the impact of assimilating Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles on board Aqua, a satellite that is part of NASA’s Earth Observing System. A record-breaking heavy rain event that occurred over Mumbai, India, on 26 July 2005 with 24-h rainfall exceeding 94 cm was used for the simulation.

By analyzing the data from the NCEP–NCAR reanalysis, possible causes of this heavy rainfall event were investigated. The temporal evolution of meteorological fields clearly indicates the formation of midtropospheric mesoscale vortices over Mumbai that exactly coincides with the duration of the intense rainfall. Analysis also indicated the midlevel dryness with higher temperature and moisture in the lower levels. This midlevel dryness with high temperature and moisture in the lower levels increases the conditional instability, which was conducive for the development of very severe local thunderstorms. The midtropospheric mesoscale vortices existed over Mumbai together with lower-level instability and the active monsoon conditions over the west coast resulted in intense rainfall, on the order of 94 cm in 24 h.

Numerical experiments were conducted, with two nested domains (45- and 15-km grid spacing). The assimilation of the AIRS-retrieved temperature and moisture profiles produced significant impacts on the location and intensity of the simulated rainfall. It is seen from the numerical experiments that the assimilation of AIRS data could produce the structure of mesoscale vortices, and lower-level thermodynamics and convergence much more realistically compared with the control simulation. The spatial distribution of the rainfall from the simulation using AIRS data was more realistic than that without AIRS data. To make the quantitative comparison of the predicted rainfall with the observed one, the equitable threat score and bias were calculated for different threshold values of rainfall. Inclusion of AIRS data significantly improved the precipitation as indicated by the equitable threat scores and biases for almost all of the threshold rainfall categories.

Corresponding author address: Randhir Singh, Atmospheric Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad-380015, India. Email: randhir_h@yahoo.com

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  • Adler, R. F., Bolun D. T. , Curtis S. , and Nelkin E. J. , 2000: Tropical rainfall distributions determined using TRMM combined with other satellite and rain gauge information. J. Appl. Meteor., 39 , 20072023.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Atlas, R., 2005: The impact of AIRS data on weather prediction. Proc. SPIE, 5806 , 599606.

  • 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 , 253264.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barker, D. M., Huang W. , Guo Y. R. , Bourgeois A. J. , and Xiao Q. N. , 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132 , 897914.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bohra, A. K., Basu S. , Rajagopal E. N. , Iyengar G. R. , Das Gupta M. , Ashrit R. , and Athiyaman B. , 2006: Heavy rainfall episode over Mumbai on 26 July 2005: Assessment of NWP guidance. Current Sci., 90 , 11881194.

    • Search Google Scholar
    • Export Citation
  • Chahine, M. T., and Coauthors, 2006: AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bull. Amer. Meteor. Soc., 87 , 911926.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, S. H., 2007: The impact of assimilating SSM/I and QuikSCAT satellite winds on Hurricane Isidore simulation. Mon. Wea. Rev., 135 , 549566.

  • Chen, S. H., Vandenberghe F. , Petty G. W. , and Bresch J. F. , 2004: Application of SSM/I satellite data to a hurricane simulation. Quart. J. Roy. Meteor. Soc., 130 , 801825.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, S-H., Zavodsky B. , Jedlovec G. , and Lapenta W. , 2006: Assimilation of Atmospheric Infrared sounder (AIRS) data in regional model. Preprints, 14th Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., P5.12. [Available online at http://ams.confex.com/ams/pdfpapers/103317.pdf.].

  • Colle, B. A., Westrick K. J. , and Mass C. F. , 1999: Evaluation of MM5 and Eta 10 precipitation forecast over the Pacific Northwest during the cool season. Wea. Forecasting, 14 , 137154.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Courtier, P., Thepaut J. N. , and Hollingsworth A. , 1994: A strategy for operational implementation of 4DVAR using an incremental approach. Quart. J. Roy. Meteor. Soc., 120 , 13671387.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Divakarla, M. G., Barnet C. D. , Goldberg M. D. , McMillin L. M. , Maddy E. , Wolf W. , Zhou L. , and Liu X. , 2006: Validation of Atmospheric Infrared Sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts. J. Geophys. Res., 111 .D09S15, doi:10.1029/2005JD006116.

    • Search Google Scholar
    • Export Citation
  • Doyle, J. D., and Warner T. T. , 1988: Verification of mesoscale objective analysis of VAS and rawinsonde data using the March 1982 AVE/VAS special network data. Mon. Wea. Rev., 116 , 358367.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46 , 30773107.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1993: A nonhydrostatic version of the Penn State–NCAR Mesoscale Model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev., 121 , 14931513.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • English, S. J., Renshaw R. J. , Dibben P. C. , Smith A. J. , Rayer P. C. , Poulsen C. , Saunders F. W. , and Eyre J. R. , 2000: A comparison of the impact of TOVS and ATOVS satellite sounding data on the accuracy of numerical weather forecasts. Quart. J. Roy. Meteor. Soc., 126 , 29112931.

    • Search Google Scholar
    • Export Citation
  • Fetzer, E. J., 2006: Preface to special section: Validation of Atmospheric Infrared Sounder observations. J. Geophys. Res., 111 .D09S01, doi:10.1029/2005JD007020.

    • Search Google Scholar
    • Export Citation
  • Fetzer, E. J., and Coauthors, 2003: AIRS/AMSU/HSB validation. IEEE Trans. Geosci. Remote Sens., 41 , 418431.

  • Gal-Chen, T., Schmidt B. D. , and Uccellini L. W. , 1986: Simultaneous experiments for testing the assimilation of geostationary satellite temperature retrievals into a numerical prediction model. Mon. Wea. Rev., 114 , 12131230.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garand, L., Beaulne A. , and Wagneur N. , 2006: Assimilation of AIRS hyperspectral radiances at MSC. Preprints, 14th Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., P5.13. [Available online at http://ams.confex.com/ams/pdfpapers/98316.pdf.].

  • Grell, G. A., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev., 121 , 764787.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grell, G. A., Dudhia J. , and Stauffer D. R. , 1994: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR/TN-398+STR, 131 pp.

  • Hollinger, J., 1989: DMSP Special Sensor Microwave/Imager calibration/validation. Naval Research Laboratory Final Rep., Vol. 1, 153 pp.

  • Hong, S-Y., and Pan H-L. , 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124 , 23222339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ide, K., Courtier P. , Ghil M. , and Lorenc A. C. , 1997: Unified notation for data assimilation: Operational, sequential and variational. J. Meteor. Soc. Japan, 75 , 180189.

    • Search Google Scholar
    • Export Citation
  • Jenamani, R. K., Bhan S. C. , and Kalsi S. R. , 2006: Observational forecasting aspects of the meteorological event that caused a record highest rainfall in Mumbai. Current Sci., 90 , 13441363.

    • Search Google Scholar
    • Export Citation
  • Jung, J. A., Zapotocny T. H. , Treadon R. E. , and Le Marshall J. F. , 2006: Atmospheric Infrared Sounder assimilation experiments using NCEP’s GFS. Preprints, 14th Conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., P5.11. [Available online at http://ams.confex.com/ams/pdfpapers/103965.pdf.].

  • Le Marshall, J., and Coauthors, 2005a: AIRS hyperspectral data improves Southern Hemisphere forecasts. Aust. Meteor. Mag., 54 , 5760.

  • Le Marshall, J., and Coauthors, 2005b: Impact of Atmospheric Infrared Sounder observations on weather forecasts. Eos, Trans. Amer. Geophys. Union, 86 .109, 115, 116.

    • Search Google Scholar
    • Export Citation
  • Le Marshall, J., and Coauthors, 2005c: AIRS associated accomplishments at the JCSDA—First use of full spatial resolution hyperspectral data show significant improvements in global forecasts. Proc. SPIE, 5890 .doi:10.1117/12.615757.

    • Search Google Scholar
    • Export Citation
  • Le Marshall, J., and Coauthors, 2006: Improving global analysis and forecasting with AIRS. Bull. Amer. Meteor. Soc., 87 , 891894.

  • Lipton, A. E., and Vonder Haar T. H. , 1990: Mesoscale analysis by numerical modeling coupled with sounding retrieval from satellites. Mon. Wea. Rev., 118 , 13081329.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lipton, A. E., Modica G. D. , Heckman S. T. , and Jackson A. J. , 1995: Satellite–model coupled analysis of convective potential in Florida with VAS water vapor and surface temperature data. Mon. Wea. Rev., 123 , 32923304.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McNally, A. P., and Vesperini M. , 1996: Variational analysis of humidity information from TOVS radiances. Quart. J. Roy. Meteor. Soc., 122 , 15211544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., Taubman S. J. , Brown P. D. , Lacono M. J. , and Clough S. A. , 1997: Radiative transfer for homogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. J. Geophys. Res., 102 , D14. 1666316682.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ruggiero, F. H., Sashegyi K. D. , Lipton A. E. , Madala R. V. , and Raman S. , 1999: Coupled assimilation of geostationary satellite sounder data into a mesoscale model using the Bratseth analysis approach. Mon. Wea. Rev., 127 , 802820.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shirtliffe, G., 1999: QuikSCAT science data products user’s manual. Jet Propulsion Laboratory Publ. D-18053, Pasadena, CA, 90 pp.

  • Singh, R., Pal P. K. , Kishtawal C. M. , and Joshi P. C. , 2008: The impact of variational assimilation of SSM/I and QuikSCAT satellite observations on the numerical simulation of Indian Ocean tropical cyclones. Wea. Forecasting, 23 , 460476.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Srinivasan, V., 1972: Discussion of typical synoptic situations over Konkan and coastal Karnataka. Forecasting Manual III-3.7, India Meteorological Department, New Delhi, India, 3–7.

    • Search Google Scholar
    • Export Citation
  • Susskind, J., Barnet C. , and Blaisdell J. , 2003: Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB under cloudy conditions. IEEE Trans. Geosci. Remote Sens., 41 , 390409.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Susskind, J., Barnet C. , Blaisdell J. , Iredell L. , Keita F. , Kouvaris L. , Molnar G. , and Chahine M. , 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.

    • Search Google Scholar
    • Export Citation
  • Tian, B., Waliser D. E. , Fetzer E. J. , Lambrigtsen B. H. , Yung Y. , and Wang B. , 2006: Vertical moist thermodynamic structure and spatial–temporal evolution of the MJO in AIRS observations. J. Atmos. Sci., 63 , 24622485.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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:10.1029/2005JD00610.

    • Search Google Scholar
    • Export Citation
  • Tomassini, M. D., LeMeur X. , and Saunders R. W. , 1998: Near-surface satellite wind observations of hurricanes and their impact on ECMWF model analyses and forecast. Mon. Wea. Rev., 126 , 12741286.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, L., Braun S. A. , Qu J. J. , and Hao X. , 2006: Simulating the formation of Hurricane Isabel (2003) with AIRS data. Geophys. Res. Lett., 33 .L04804, doi:10.1029/2005GL024665.

    • Search Google Scholar
    • Export Citation
  • Xiao, Q., Zou X. , and Kuo Y. H. , 2000: Incorporating the SSM/I-derived precipitable water and rainfall rate into a numerical model: A case study for the ERICA IOP-4 cyclone. Mon. Wea. Rev., 128 , 87108.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiao, Q., Zou X. , Pondeca M. , Sharpiro M. A. , and Velden C. , 2002: Impact of GMS-5 and GOES-9 satellite-derived winds on the prediction of a NORPEX extratropical cyclone. Mon. Wea. Rev., 130 , 507528.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zapotocny, T. H., and Coauthors, 2000: A case study of the sensitivity of the Eta Data Assimilation System. Wea. Forecasting, 15 , 603621.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zapotocny, T. H., Menzel W. P. , Nelson J. P. III, and Jung J. A. , 2002: An impact study of five remotely sensed and five in situ data types in the Eta Data Assimilation System. Wea. Forecasting, 17 , 263285.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zapotocny, T. H., Menzel W. P. , Jung J. A. , and Nelson J. P. III, 2005: A four-season impact study of rawinsonde, GOES, and POES data in Eta Data Assimilation System. Part I: The total contribution. Wea. Forecasting, 20 , 161177.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zavodsky, B. T., Lazarus S. M. , Blotiman P. F. , and Sharp D. W. , 2004: Assimilation of MODIS temperature and water vapor profiles into a mesoscale analysis system. Preprints, 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 2.5. [Available online at http://ams.confex.com/ams/pdfpapers/68594.pdf.].

  • Zhang, X., Xiao Q. , and Patrick F. , 2007: The impact of multisatellite data on the initialization and simulation of Hurricane Lili’s (2002) rapid weakening phase. Mon. Wea. Rev., 135 , 526548.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhao, Y., Wang B. , Ji Z. , Liang X. , Deng G. , and Zhang X. , 2005: Improved track forecasting of typhoon reaching landfall from four-dimensional variational data assimilation of AMSU A retrieved data. J. Geophys. Res., 110 .D14101, doi:10.1029/2004JD005267.

    • Search Google Scholar
    • Export Citation
  • Zhu, T., Zhang D. L. , and Weng F. , 2002: Impact of Advanced Microwave Sounding Unit measurements on hurricane prediction. Mon. Wea. Rev., 130 , 24162432.

    • Crossref
    • Search Google Scholar
    • Export Citation
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