• Aksoy, A., , S. Lorsolo, , T. Vukicevic, , K. J. Sellwood, , S. D. Aberson, , and F. Zhang, 2012: The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for high-resolution data: The impact of airborne Doppler radar observations in an OSSE. Mon. Wea. Rev., 140, 18431862, doi:10.1175/MWR-D-11-00212.1.

    • Search Google Scholar
    • Export Citation
  • Aksoy, A., , S. D. Aberson, , T. Vukicevic, , K. J. Sellwood, , S. Lorsolo, , and X. Zhang, 2013: Assimilation of high-resolution tropical cyclone observations with an ensemble Kalman filter using NOAA/AOML/HRD’s HEDAS: Evaluation of the 2008–11 vortex-scale analyses. Mon. Wea. Rev., 141, 18421865, doi:10.1175/MWR-D-12-00194.1.

    • Search Google Scholar
    • Export Citation
  • Barker, D. M., , W. Huang, , Y.-R. Guo, , A. Bourgeois, , and X. N. Xiao, 2004: A three-dimensional variational data assimilation system for use with MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897914, doi:10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chan, J. C. L., , and W. M. Gray, 1982: Tropical cyclone movement and surrounding flow relationships. Mon. Wea. Rev., 110, 13541374, doi:10.1175/1520-0493(1982)110<1354:TCMASF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chang, H., , A. Kumar, , D. Niyogi, , U. C. Mohanty, , F. Chen, , and J. Dudhia, 2009: The role of land surface processes on the mesoscale simulation of the July 26, 2005 heavy rain event over Mumbai, India. Global Planet. Change, 67, 87103, doi:10.1016/j.gloplacha.2008.12.005.

    • Search Google Scholar
    • Export Citation
  • Dowell, D. C., , L. J. Wicker, , and C. Snyder, 2011: Ensemble Kalman filter assimilation of radar observations of the 8 May 2003 Oklahoma City supercell: Influences of reflectivity observations on storm-scale analyses. Mon. Wea. Rev., 139, 272294, doi:10.1175/2010MWR3438.1.

    • 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, doi:10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., , W. M. Frank, , G. J. Holland, , J. D. Jarrel, , and R. L. Southern, 1987: A Global View of Tropical Cyclones. University of Chicago Press, 185 pp.

    • Search Google Scholar
    • Export Citation
  • Elsberry, R. L., , T. D. B. Lambert, , and M. A. Boothe, 2007: Accuracy of Atlantic and eastern North Pacific tropical cyclone intensity forecast guidance. Wea. Forecasting, 22, 747762, doi:10.1175/WAF1015.1.

    • Search Google Scholar
    • Export Citation
  • Gao, J., , M. Xue, , A. Shapiro, , and K. K. Droegemeier, 1999: A variational method for the analysis of three-dimensional wind fields from two Doppler radars. Mon. Wea. Rev., 127, 21282142, doi:10.1175/1520-0493(1999)127<2128:AVMFTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gopalakrishnan, S. G., , F. Marks, , X. Zhang, , J.-W. Bao, , K.-S. Yeh, , and R. Atlas, 2011: The experimental HWRF system: A study on the influence of horizontal resolution on the structure and intensity changes in tropical cyclones using an idealized framework. Mon. Wea. Rev., 139, 17621784, doi:10.1175/2010MWR3535.1.

    • Search Google Scholar
    • Export Citation
  • Govindankutty, M., , A. Chandrasekar, , and D. Pradan, 2010: Impact of 3DVAR assimilation of Doppler Weather Radar wind data and IMD observation for the prediction of a tropical cyclone. Int. J. Remote Sens., 31, 63276345, doi:10.1080/01431160903413689.

    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., , and J.-O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129151.

  • Houze, R. A., 2010: Clouds in tropical cyclones. Mon. Wea. Rev., 138, 293344, doi:10.1175/2009MWR2989.1.

  • Kessler, E., 1969: On the Distribution and Continuity of Water Substance on Atmospheric Circulation. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.

  • Kiran Prasad, S., , U. C. Mohanty, , A. Routray, , K. K. Osuri, , S. S. V. S. Ramakrishna, , and D. Niyogi, 2014: Impact of Doppler weather radar data on thunderstorm simulation during STORM pilot phase—2009. Nat. Hazards, 74, 14031427, doi:10.1007/s11069-014-1250-0.

    • Search Google Scholar
    • Export Citation
  • Kishtawal, C. M., , D. Niyogi, , A. Kumar, , M. Laureano, , and O. Kellner, 2012: Sensitivity of inland decay of tropical cyclones to soil surface characteristics. Nat. Hazards, 63, 15271542, doi:10.1007/s11069-011-0015-2.

    • Search Google Scholar
    • Export Citation
  • Mandal, M., , and U. C. Mohanty, 2006: Impact of satellite derived wind in mesoscale simulation of Orissa super cyclone. Indian J. Mar. Sci., 35, 161173.

    • Search Google Scholar
    • Export Citation
  • Marks, F. D., 2003: State of the science: Radar view of tropical cyclones. Radar and Atmospheric Science: A Collection of Essays in Honor of David Atlas, Meteor. Monogr., No. 52, Amer. Meteor. Soc., 33–74.

  • Marks, F. D., , and L. K. Shay, 1998: Landfalling tropical cyclones: Forecast problems and associated research opportunities. Bull. Amer. Meteor. Soc., 79, 305323, doi:10.1175/1520-0477(1998)079<0305:LTCFPA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mohanty, U. C., , K. K. Osuri, , A. Routray, , M. Mohapatra, , and S. Pattanayak, 2010: Simulation of Bay of Bengal tropical cyclones with WRF Model: Impact of initial and boundary conditions. Mar. Geod., 33, 294314, doi:10.1080/01490419.2010.518061.

    • Search Google Scholar
    • Export Citation
  • Mohapatra, M., , D. P. Nayak, , R. P. Sharma, , and B. K. Bandyopadhyay, 2013: Evaluation of official tropical cyclone track forecast over north Indian Ocean issued by India Meteorological Department. J. Earth Syst. Sci., 122, 589601, doi:10.1007/s12040-013-0291-1.

    • Search Google Scholar
    • Export Citation
  • Niyogi, D., , T. Holt, , S. Zhong, , P. C. Pyle, , and J. Basara, 2006: Urban and land surface effects on the 30 July 2003 mesoscale convective system event observed in the Southern Great Plains. J. Geophys. Res., 111, D19107, doi:10.1029/2005JD006746.

    • Search Google Scholar
    • Export Citation
  • Niyogi, D., , C. Kishtawal, , S. Tripathi, , and R. S. Govindaraju, 2010: Observational evidence that agricultural intensification and land use change may be reducing the Indian summer monsoon rainfall. Water Resour. Res., 46, W03533, doi:10.1029/2008WR007082.

    • Search Google Scholar
    • Export Citation
  • Osuri, K. K., , U. C. Mohanty, , A. Routray, , and M. Mohapatra, 2012a: The impact of satellite-derived wind data assimilation on track, intensity, and structure of tropical cyclones over the North Indian Ocean. Int. J. Remote Sens., 33, 16271652, doi:10.1080/01431161.2011.596849.

    • Search Google Scholar
    • Export Citation
  • Osuri, K. K., , U. C. Mohanty, , A. Routray, , M. A. Kulkarni, , and M. Mohapatra, 2012b: Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over the North Indian Ocean. Nat. Hazards, 63, 13371359, doi:10.1007/s11069-011-9862-0.

    • Search Google Scholar
    • Export Citation
  • Osuri, K. K., , U. C. Mohanty, , A. Routray, , M. Mohapatra, , and D. Niyogi, 2013: Real-time track prediction of tropical cyclones over the North Indian Ocean using the ARW model. J. Appl. Meteor. Climatol., 52, 24762492, doi:10.1175/JAMC-D-12-0313.1.

    • Search Google Scholar
    • Export Citation
  • Parrish, D. F., , and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 17471763, doi:10.1175/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Regional Specialized Meteorological Centre, 2007: Report on cyclonic disturbances over North Indian Ocean. RSMC Tropical Cyclone Rep., India Meteorological Department, New Delhi, India, 98 pp. [Available online at http://www.imd.gov.in/section/nhac/dynamic/RSMC-2007.pdf.]

  • Regional Specialized Meteorological Centre, 2009: Cyclonic disturbances over North Indian Ocean during 2009: A report. RSMC Tropical Cyclone Rep. 05/2010, India Meteorological Department, New Delhi, India, 117 pp. [Available online at http://www.imd.gov.in/section/nhac/dynamic/RSMC-2009.pdf.]

  • Regional Specialized Meteorological Centre, 2010: Report on cyclonic disturbances over North Indian Ocean during 2010. RSMC Tropical Cyclone Rep. 1/2011, India Meteorological Department, New Delhi, India, 162 pp. [Available online at http://www.imd.gov.in/section/nhac/dynamic/RSMC-2010.pdf.]

  • Regional Specialized Meteorological Centre, 2011: Report on cyclonic disturbances over North Indian Ocean during 2011. RSMC Tropical Cyclone Rep. 02/2012, India Meteorological Department, New Delhi, India, 181 pp. [Available online at http://www.rsmcnewdelhi.imd.gov.in/images/pdf/publications/annual-rsmc-report/rsmc-2011.pdf.]

  • Routray, A., , U. C. Mohanty, , S. R. H. Rizvi, , D. Niyogi, , K. K. Osuri, , and D. Pradhan, 2010: Impact of Doppler weather radar data on simulation of Indian monsoon depressions. Quart. J. Roy. Meteor. Soc., 136, 18361850, doi:10.1002/qj.678.

    • Search Google Scholar
    • Export Citation
  • Routray, A., , U. C. Mohanty, , K. K. Osuri, , and S. Kiran Prasad, 2013: Improvement of monsoon depressions forecast with assimilation of Indian DWR data using WRF-3DVAR analysis system. Pure Appl. Geophys., 170, 23292350, doi:10.1007/s00024-013-0648-z.

    • Search Google Scholar
    • Export Citation
  • Routray, A., , S. C. Kar, , P. Mali, , and K. Sowjanya, 2014: Simulation of monsoon depressions using WRF-VAR: Impact of different background error statistics and lateral boundary conditions. Mon. Wea. Rev., 142, 35863613, doi:10.1175/MWR-D-13-00285.1.

    • Search Google Scholar
    • Export Citation
  • Singh, R., , P. K. Pal, , C. M. Kishtawal, , and P. C. Joshi, 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, doi:10.1175/2007WAF2007014.1.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , J. B. Klemp, , J. Dudhia, , D. O. Gill, , D. M. Barker, , W. Wang, , and J. G. Powers, 2005: A description of the advanced research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v2.pdf.]

  • Sun, J., , and N. A. Crook, 1997: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments. J. Atmos. Sci., 54, 16421661, doi:10.1175/1520-0469(1997)054<1642:DAMRFD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sun, J., , and N. A. Crook, 1998: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci., 55, 835852, doi:10.1175/1520-0469(1998)055<0835:DAMRFD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Vrieling, A., , G. Sterk, , and S. M. De Jong, 2009: Mapping rainfall erosivity for Africa with TRMM time series. EGU General Assembly 2009, Vienna, Austria, European Geosciences Union, Geophys. Res. Abstract 11-2034. [Available online at http://meetings.copernicus.org/egu2009/.]

  • Wang, Y., 2002: Sensitivity of tropical cyclone intensification and intensity to cloud microphysics parameterization. Preprints, 25th Conf. on Hurricanes and Tropical Meteorology, San Diego, CA, Amer. Meteor. Soc., 438–439.

  • Wu, L., , and B. Wang, 2000: A potential vorticity tendency diagnostic approach for tropical cyclone motion. Mon. Wea. Rev., 128, 18991911, doi:10.1175/1520-0493(2000)128<1899:APVTDA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xavier, V. F., , A. Chandrasekar, , H. Rahman, , D. Niyogi, , and K. Alapaty, 2008: The effect of assimilation of satellite and conventional meteorological data for the prediction of a monsoon depression over India using a mesoscale model. Meteor. Atmos. Phys., 101, 6592, doi:10.1007/s00703-008-0314-7.

    • Search Google Scholar
    • Export Citation
  • Xiao, Q., , and J. Sun, 2007: Multiple-radar data assimilation and short-range quantitative precipitation forecasting of a squall line observed during IHOP_2002. Mon. Wea. Rev., 135, 33813404, doi:10.1175/MWR3471.1.

    • Search Google Scholar
    • Export Citation
  • Xiao, Q., , Y.-H. Kuo, , J. Sun, , W.-C. Lee, , M. E. Li, , Y.-R. Guo, , and D. M. Barker, 2005: Assimilation of Doppler radar observations with a regional 3DVAR system: Impact of Doppler velocities on forecasts of a heavy rainfall case. J. Appl. Meteor., 44, 768788, doi:10.1175/JAM2248.1.

    • Search Google Scholar
    • Export Citation
  • Yamasaki, M., 2013: A study on the effects of the ice microphysics on tropical cyclones. Adv. Meteor., 2013, 573786, doi:10.1155/2013/573786.

    • Search Google Scholar
    • Export Citation
  • Zhao, K., , and M. Xue, 2009: Assimilation of coastal Doppler radar data with the ARPS 3DVAR and cloud analysis for the prediction of Hurricane Ike (2008). Geophys. Res. Lett., 36, L12803, doi:10.1029/2009GL038658.

    • Search Google Scholar
    • Export Citation
  • Zhao, Q., , and Y. Jin, 2008: High-resolution radar data assimilation for Hurricane Isabel (2003) at landfall. Bull. Amer. Meteor. Soc., 89, 13551372, doi:10.1175/2008BAMS2562.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, D.-L., , and H. Chen, 2012: Importance of the upper-level warm core in the rapid intensification of a tropical cyclone. Geophys. Res. Lett., 39, L02806, doi:10.1029/2011GL050578.

    • Search Google Scholar
    • Export Citation
  • Zhu, T., , and D.-L. Zhang, 2006: Numerical simulation of Hurricane Bonnie (1998). Part II: Sensitivity to cloud microphysical processes. J. Atmos. Sci., 63, 109126, doi:10.1175/JAS3599.1.

    • Search Google Scholar
    • Export Citation
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Improved Prediction of Bay of Bengal Tropical Cyclones through Assimilation of Doppler Weather Radar Observations

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  • 1 School of Earth, Ocean and Climate Sciences, Indian Institute of Technology, Bhubaneswar, India
  • | 2 National Centre for Medium Range Weather Forecasting, Noida, India
  • | 3 Purdue University, West Lafayette, Indiana
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Abstract

The impact on tropical cyclone (TC) prediction from assimilating Doppler weather radar (DWR) observations obtained from the TC inner core and environment over the Bay of Bengal (BoB) is studied. A set of three operationally relevant numerical experiments were conducted for 24 forecast cases involving 5 unique severe/very severe BoB cyclones: Sidr (2007), Aila (2009), Laila (2010), Jal (2010), and Thane (2011). The first experiment (CNTL) used the NCEP FNL analyses for model initial and boundary conditions. In the second experiment [Global Telecommunication System (GTS)], the GTS observations were assimilated into the model initial condition while the third experiment (DWR) used DWR with GTS observations. Assimilation of the TC environment from DWR improved track prediction by 32%–53% for the 12–72-h forecast over the CNTL run and by 5%–25% over GTS and was consistently skillful. More gains were seen in intensity, track, and structure by assimilating inner-core DWR observations as they provided more realistic initial organization/asymmetry and strength of the TC vortex. Additional experiments were conducted to assess the role of warm-rain and ice-phase microphysics to assimilate DWR reflectivity observations. Results indicate that the ice-phase microphysics has a dominant impact on inner-core reflectivity assimilation and in modifying the intensity evolution, hydrometeors, and warm core structure, leading to improved rainfall prediction. This study helps provide a baseline for the credibility of an observational network and assist with the transfer of research to operations over the India monsoon region.

Corresponding author address: U. C. Mohanty, School of Earth, Ocean and Climate Sciences, Indian Institute of Technology, Toshali Bhavan, Satya Nagar, Bhubaneswar, 751007, India. E-mail: ucmohanty@gmail.com

Abstract

The impact on tropical cyclone (TC) prediction from assimilating Doppler weather radar (DWR) observations obtained from the TC inner core and environment over the Bay of Bengal (BoB) is studied. A set of three operationally relevant numerical experiments were conducted for 24 forecast cases involving 5 unique severe/very severe BoB cyclones: Sidr (2007), Aila (2009), Laila (2010), Jal (2010), and Thane (2011). The first experiment (CNTL) used the NCEP FNL analyses for model initial and boundary conditions. In the second experiment [Global Telecommunication System (GTS)], the GTS observations were assimilated into the model initial condition while the third experiment (DWR) used DWR with GTS observations. Assimilation of the TC environment from DWR improved track prediction by 32%–53% for the 12–72-h forecast over the CNTL run and by 5%–25% over GTS and was consistently skillful. More gains were seen in intensity, track, and structure by assimilating inner-core DWR observations as they provided more realistic initial organization/asymmetry and strength of the TC vortex. Additional experiments were conducted to assess the role of warm-rain and ice-phase microphysics to assimilate DWR reflectivity observations. Results indicate that the ice-phase microphysics has a dominant impact on inner-core reflectivity assimilation and in modifying the intensity evolution, hydrometeors, and warm core structure, leading to improved rainfall prediction. This study helps provide a baseline for the credibility of an observational network and assist with the transfer of research to operations over the India monsoon region.

Corresponding author address: U. C. Mohanty, School of Earth, Ocean and Climate Sciences, Indian Institute of Technology, Toshali Bhavan, Satya Nagar, Bhubaneswar, 751007, India. E-mail: ucmohanty@gmail.com
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