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Original Research Papers

Mesoscale satellite data assimilation: impact of cloud-affected infrared observations on a cloud-free initial model state

Authors:

Curtis J. Seaman ,

Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523-1371, US
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Manajit Sengupta,

Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, US
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Thomas H. Vonder Haar

Department of Atmospheric Science, Colorado State University, Fort Collins, CO, US
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Abstract

This work presents the results of assimilating cloud-affected radiances from geostationary, infrared window and water vapour channels into a mesoscale, cloud-resolving model using a four-dimensional variational assimilation system for the case of an altocumulus cloud over the Great Plains of the United States. In this case, the initial model state, based on reanalysis data, was virtually cloud-free. The impacts of cloudy-scene radiances on a cloud-free model state (and, more generally, accurate satellite observations on inaccurate model initial conditions) in a four-dimensional variational assimilation framework are discussed. Results indicate that, in a cloud-free model state, the assimilation of cloudy radiances modifies the initial conditions as if no cloud exists. This results in a cooling of the surface and lower troposphere upon assimilation of infrared window channels, and an increase in mid-to upper tropospheric humidity upon assimilation of water vapour channels in an attempt to minimize the differences between the modelled and observed radiances. Neither modification of the initial conditions leads to the formation of the observed cloud. The size of the domain and the background error covariance are found to have a significant impact on the results.

How to Cite: Seaman, C.J., Sengupta, M. and Vonder Haar, T.H., 2010. Mesoscale satellite data assimilation: impact of cloud-affected infrared observations on a cloud-free initial model state. Tellus A: Dynamic Meteorology and Oceanography, 62(3), pp.298–318. DOI: http://doi.org/10.1111/j.1600-0870.2009.00436.x
  Published on 01 Jan 2010
 Accepted on 14 Jan 2009            Submitted on 24 Jul 2009

References

  1. Akella , S. and Navon , I. M . 2009 . Different approaches to model error formulation in 4D-Var: a study with high-resolution advection schemes . Tellus 61A , 112 – 128 .  

  2. Bauer , R , Lopez , R , Salmond , D. , Benedetti , A. , Saarinen , S. and Bonazzola , M . 2006 . Implementation of 1D+4D-Var assimilation of precipitation-affected microwave radiances at ECMWF. II: 4-Dvar . Q.J. R. MeteoroL Soc . 132 , 2307 – 2332 .  

  3. Benedetti , A. and Janiskovi , M . 2008 . Assimilation of MODIS cloud optical depths in the ECMWF model . Mon. Wea. Rev . 136 , 1727 – 1746 .  

  4. Benjamin , S. G. , Devenyi , D. , Weygandt , S. S. , Brundage , K. J. , Brown , J. M. and co-authors . 2004 . An hourly forecast assimilation cycle: the RUC. Mon. Wea. Rev . 132 , 495 – 518 .  

  5. Bryant , F. D. and Latimer , P . 1969 . Optical efficiencies of large particles of arbitrary shape and orientation . J. Colloid Inter Sci . 30 , 291 – 304 .  

  6. Carey , L. D. , Niu , J. , Yang , P. , Kanlciewicz , J. A. , Larson , V. E. and Vonder Haar , T. H . 2008 . The vertical profile of liquid and ice water content in mid-latitude, mixed-phase altocumulus clouds . J. AppL MeteoroL Clim . 47 , 2487 – 2495 .  

  7. Coakley , J. A. and Bretherton , F. P . 1982 . Cloud cover from high-resolution scanner data: detecting and allowing for partially filled fields of view . J. Geophys. Res . 87 , 4917 – 4932 .  

  8. Cohn , S. E . 1997 . An introduction to estimation theory . J. MeteoroL Soc. Jpn . 75 , 257 – 288 .  

  9. Cotton , W. R. , Pielke , Sr., R. A. , Walko , R. L. , Liston , G. E. , Tremback , C. J. and co-authors . 2003 . RAMS 2001: current status and future directions . MeteoroL Atmos. Phys . 82 , 5 – 29 .  

  10. Cucurull , L. , Derber , J. C. , Treadon , R. and Purser , R. J . 2008 . Preliminary impact studies using global positioning system radio occultation profiles at NCEP . Mon. Wea. Rev . 136 , 1865 – 1877 .  

  11. Deblonde , G. and English , S . 2003 . One dimensional variational retrievals from SSMIS simulated observations . J. AppL MeteoroL 42 , 1406 – 1420 .  

  12. Deblonde , G. , Mahfouf , J.-F. , Bilodeau , B. and Anselmo , D . 2007 . One-dimensional variational data assimilation of ssmn observations in rainy atmospheres at MSC . Mon. Wea. Rev . 135 , 152 – 172 .  

  13. Deeter , M. and Evans , K. E 1998 . A hybrid Eddington-single scattering radiative transfer model for computing radiances from thermally emitting atmospheres . J. Quant. Spec. Rad. Trans . 60 , 635 – 648 .  

  14. Evans , K. E 1998 . The spherical harmonics discrete ordinate method for three-dimensional atmospheric radiative transfer . J. Atmos. Sci . 55 , 429 – 446 .  

  15. Fan , X. and Tilley , J. S . 2005 . Dynamic assimilation of MODIS-retrieved humidity profiles within a regional model for high-latitude forecast applications . Mon. Wea. Rev . 133 , 3450 – 3480 .  

  16. Fleishauer , R. P. , Larson , V. E. and Vonder Haar , T. H . 2002 . Observed microphysical structure of midlevel, mixed-phase clouds . J. Atmos. Sci . 59 , 1779 – 1804 .  

  17. Fletcher , S. J. and Zupanski , M . 2006a . A data assimilation method for log-normally distributed observational errors . Q. J. R. MeteoroL Soc . 132 , 2505 – 2519 .  

  18. Fletcher , S. J. and Zupanski , M . 2006b . A hybrid multivariate normal and lognormal distribution for data assimilation . Atmos. Sci. Lett . 7 , 43 – 46 .  

  19. Fletcher , S. J. and Zupanski , M . 2007 . Implications and impacts of transforming lognormal variables into normal variables in VAR . MeteoroL Z . 15 , 1 – 11 .  

  20. Garand , L. and Hallé , J . 1997 . Assimilation of clear and cloudy sky upper tropospheric humidity estimates using GOES-8 and GOES-9 data . J. Atmos. Ocean. Tech . 14 , 1036 – 1054 .  

  21. Greenwald , T. J. , Hertenstein , R. and Vukiéevié , T . 2002 . An all-weather observational operator for satellite radiance assimilation with mesoscale forecast models . Mon. Wea. Rev . 130 , 1882 – 1897 .  

  22. Greenwald , T. J. , Vukiéevié , T. , Grasso , L. D. and Vonder Haar , T. H . 2004 . Adjoint sensitivity analysis of an observational operator for cloudy visible and infrared radiance assimilation . Q.J. R. MeteoroL Soc . 130 , 685 – 705 .  

  23. Ha , S.-Y. , Kuo , Y.-H. , Guo , Y.-R. and Lim , G.-Y . 2003 . Variational assimilation of slant-path wet delay measurements from a hypothetical ground-based GPS network. Part I: comparison with precipitable water assimilation . Mon. Wea. Rev . 131 , 2635 – 2655 .  

  24. Harrington , J. Y . 1997 . The Effects of Radiation and Microphysical Processes on Simulated Warm and Transition Season Arctic Stratus . CSU PhD Dissertation, Colorado State University, Ft. Collins, CO , 289 pp .  

  25. Hoffman , R. N. , Grassotti , C. , Isaacs , R. G. , Louis , J . -E and Nehrkorn , T. 1990. Assessment of simulated satellite lidar wind and retrieved 183 GHz water vapour observations on a global data assimilation system. Mon. Wea. Rev . 118 , 2513 – 2542 .  

  26. Illingworth , A. J. , Hogan , R. J. , O’Connor , E. J. , Bouniol , D. , Brooks , M. E. and co-authors . 2007 . Cloudnet. Bull. Am. Meteorol. Soc . 88 , 883 – 898 .  

  27. Jacobs , G. A. and Ngodock , H. E . 2003 . The maintenance of conservative physical laws within data assimilation systems . Mon. Wea. Rev . 131 , 2595 – 2607 .  

  28. Jones , A. S. and Vonder Haar , T. H . 2002 . A dynamic parallel data-computing environment for cross-sensor satellite data merger and scientific analysis . J. Atmos. Ocean. Tech . 19 , 1307 – 1317 .  

  29. Kalnay , E . 2003 . Atmospheric Modeling, Data Assimilation and Predictability . Cambridge University Press , Cambridge, UK , 341 pp .  

  30. Khairoutdinov , M. F. and Randall , D. A . 2003 . Cloud resolving modeling of the ARM Summer 1997 IOP: model formulation, results, uncertainties, and sensitivities . J. Atmos. Sci . 60 , 607 – 625 .  

  31. Kidder , S. Q. and Vonder Haar , T. H . 1995 . Satellite Meteorology: An Introduction . Academic Press , San Diego, CA , 466 pp .  

  32. Lipton , A. E . 1993 . Cloud shading retrieval and assimilation in a satellite-model coupled mesoscale analysis system . Mon. Wea. Rev . 121 , 3062 – 3081 .  

  33. Lipton , A. E. and Modica , G. D . 1999 . Assimilation of visible-band satellite data for mesoscale forecasting in cloudy conditions . Mon. Wea. Rev . 127 , 265 – 278 .  

  34. Marecal , V. and Mahfouf , J.-F . 2002 . Four-dimensional variational assimilation of total column water vapour in rainy areas . Mon. Wea. Rev . 130 , 43 – 58 .  

  35. McMillin , L. M. , Crone , L. J. , Goldberg , M. D. and Kleespies , T. J . 1995 . Atmospheric transmittance of an absorbing gas, 4. OPTRAN: a computationally fast and accurate transmittance model for absorbing gases with fixed and variable mixing ratios at variable viewing angles . J. AppL Opt . 34 , 6269 – 6274 .  

  36. McNally , A. P . 2009 . The direct assimilation of cloud-affected satellite infrared radiances in the ECMWF 4D-Var . Q. J. R. Meteorol. Soc . 135 , 1214 – 1229 .  

  37. McNally , A. P. and Vesperini , M . 1996 . Variational analysis of humidity information from TOVS radiances . Q. J. R. Meteorol. Soc . 122 , 1521 – 1544 .  

  38. McNally , A. P. , Derber , J. C. , Wu , W.-S. and Katz , B. B . 2000 . The use of TOVS level-1B radiances in the NCEP SSI analysis system . Q. J. R. Meteorol. Soc . 126 , 689 – 724 .  

  39. Menzel , W. P. and Purdom , J. F. W . 1994 . Introducing GOES-I: the first of a new generation of geostationary operational environmental satellites . Bull. Am. Meteorol. Soc . 75 , 757 – 781 .  

  40. Meyers , M. P. , Walko , R. L. , Harrington , J. Y. and Cotton , W. R . 1997 . New RAMS cloud microphysics parameterization. Part II: the two-moment scheme . Atmos. Res . 45 , 3 – 39 .  

  41. Mielke , P. W. , Williams , J. S. and Wu , S.-C . 1977 . Covariance analysis techniques based upon bivariate lognormal distribution with weather modification applications . J. AppL Meteorol . 16 , 183 – 187 .  

  42. Miles , N. L. , Verlinde , J. and Clothiaux , E. E . 2000 . Cloud droplet size distribution in low-level stratiform clouds . J. Atmos. Sci . 57 , 295 – 311 .  

  43. Molkov , I. and Schlesinger , M. E . 1993 . Analysis of global cloudiness, part I: comparison of METEOR, Nimbus-7 and ISCCP satellite data . J. Geophys. Res . 98 , 12849 – 12868 .  

  44. Moreau , E. , Lopez , P. , Bauer , P. , Tompkins , A. M. , Janisková. , M. and co-authors . 2004 . Variational retrieval of temperature and humidity profiles using rain rates versus microwave brightness temperatures. Q. J. R. Meteorol. Soc . 130 , 827 – 852 .  

  45. Nocedal , J . 1980 . Updating quasi-Newton matrices with limited storage . Math. Comp . 35 , 773 – 782 .  

  46. Pielke , R. A. , Cotton , W. R. , Walko , R. L. , Tremback , C. J. , Lyons , W. A. and co-authors . 1992 . A comprehensive meteorological modeling system-RAMS. Meteorol. Atmos. Phys . 49 , 69 – 91 .  

  47. Raymond , W. H. , Wade , G. S. and Zapotocny , T. H . 2004 . Assimilating GOES brightness temperatures. Part I: upper-tropospheric moisture . J. AppL Meteorol . 43 , 17 – 27 .  

  48. Rossow , W. B. and Dueñas , E. N . 2004 . The ISCCP web site, an online source for research . Bull. Am. Meteorol. Soc . 85 , 167 – 172 .  

  49. 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 , 802 – 821 .  

  50. Ruston , B. C. and Vonder Haar , T. H . 2004 . Characterization of summertime microwave emissivities from the Special Sensor Microwave Imager over the conterminous United States . J. Geophys. Res . 109 , D19103 , https://doi.org/10.1029/2004JD004890 .  

  51. Seaman , C. J. and Vonder Haar , T. H . 2003 . Observed and Calculated Properties of Mid-level, Mixed-phase Clouds . Masters Thesis, Colorado State University , Fort Collins, CO , 92 pp .  

  52. Sengupta , M. , Clothiaux , E. E. and Ackerman , T. P . 2004 . Climatology of warm boundary layer clouds at the ARM SGP site and their comparisons to models . J. Clim . 17 , 4760 – 4782 .  

  53. Shanno , D. F ., 1985 . Globally convergent conjugate gradient algorithms . Math. Prog . 33 , 61 – 67 .  

  54. Stunder , B. J. B. 1997. NCEP Model Output - FNL Archive Data. TD-6141, National Climatic Data Center. Available online at: http://www.arl.noaa.govifnl.php.  

  55. Tomassini , M. , Kelly , G. and Saunders , R . 1999 . Use and impact of satellite atmospheric motion winds on ECMWF analyses and forecasts . Mon. Wea. Rev . 127 , 971 – 986 .  

  56. Trémolet , Y . 2007 . Model-error estimation in 4D-Var . Q. J. R. Meteorol. Soc . 133 , 1267 – 1280 .  

  57. Tripoli , G. J. and Cotton , W. R . 1982 . The Colorado State University three-dimensional cloud/mesoscale model - 1982. Part I: general theoretical framework and sensitivity experiments . J. Recherches Atmos . 16 , 185 – 219 .  

  58. van Leeuwen , P. J . 2001 . An ensemble smoother with error estimates . Mon. Wea. Rev . 129 , 709 – 728 .  

  59. Vukiéevié , T. , Greenwald , T. , Zupanski , M. , Zupanski , D. , Vonder Haar , T. and co-authors . 2004 . Mesoscale cloud state estimation from visible and infrared satellite radiances. Mon. Wea. Rev . 132 , 3066 – 3077 .  

  60. Vukiéevié , T. and Paegle , J . 1989 . The influence of one-way interacting lateral boundary conditions upon predictability of flow in bounded numerical models . Mon. Wea. Rev . 117 , 340 – 350 .  

  61. Vukiéevié , T. , Sengupta , M. , Jones , A. S. and Vonder Haar , T. H . 2006 . Cloud resolving satellite data assimilation: information content of IR window observations and uncertainties in estimation . J. Atmos. Sci . 63 , 901 – 919 .  

  62. Walko , R. L. , Band , L. E. , Baron , J. , Kittel , T. G. F. , Lammers , R. and co-authors . 2000 . Coupled atmosphere-biophysics-hydrology models for environmental modeling. J. Appl. Meteorol . 39 , 931 – 944 .  

  63. Walko , R. , Cotton , W. R. , Meyers , M. P. and Harrington , J. Y . 1995 . New RAMS cloud microphysics parameterization. Part I: the single-moment scheme . Atmos. Res . 38 , 29 – 62 .  

  64. Warren , S. G. , Hahn , C. J. , London , J. , Chervin , R. M. and Jenne , R . 1986 . Global Distribution of Total Cloud Cover and Cloud Type Amount Over Land. NCAR TN-317 STR, 212 pp .  

  65. Warren , S. G. , Hahn , C. J. , London , J. , Chervin , R. M. and Jenne , R . 1988 . Global Distribution of Total Cloud Cover and Cloud Type Amount Over the Ocean. NCAR TN-317 STR, 212 pp .  

  66. Watkinson , L. R. , Lawless , A. S. , Nicholls , N. K. and Roulstone , I . 2007 . Weak constraints in four-dimensional variational data assimilation . MeteoroL Z . 16 , 767 – 776 .  

  67. Weng , F ., 2007 . Advances in radiative transfer modeling in support of satellite data assimilation . J. Atmos. Sci . 64 , 3799 – 3807 .  

  68. Weng , F. , Zhu , T. and Yan , B . 2007 . Satellite data assimilation in numerical weather prediction models. Part II: uses of rain-affected radiances from microwave observations for hurricane vortex analysis . J. Atmos. Sci . 64 , 3910 – 3925 .  

  69. Wu , X. , Diak , G. R. , Hayden , C. M. and Young , J. A . 1995 . Short-range precipitation forecasts using assimilation of simulated satellite water vapour profiles and column cloud liquid water amounts . Mon. Wea. Rev . 123 , 347 – 365 .  

  70. Xie , Y. , Lu , C. and Browning , G . 2002 . Impact of formulation of cost function and constraints on three-dimensional variational data assimilation . Mon. Wea. Rev . 130 , 2433 – 2447 .  

  71. Yucel , I. , Shuttleworth , W. J. , Gao , X. and Sorooshian , S . 2003 . Short-term performance of MM5 with cloud-cover assimilation from satellite observations . Mon. Wea. Rev . 131 , 1797 – 1810 .  

  72. Zapotocny , T. H. , Menzel , W. R , Nelson , BI, J. P. 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. Forecast . 17 , 263 – 285 .  

  73. Zupanski , M . 1993 . A preconditioning algorithm for large-scale minimization problems . Tellus 45A , 478 – 492 .  

  74. Zupanski , M . 1996 . A preconditioning algorithm for four-dimensional variational data assimilation . Mon. Wea. Rev . 124 , 2562 – 2573 .  

  75. Zupanski , D . 1997 . A general weak constraint applicable to operational 4DVAR data assimilation systems . Mon. Wea. Rev . 125 , 2274 – 2292 .  

  76. Zupanski , M. , Zupanski , D. , Parrish , D. , Rogers , E. and DiMego , D . 2002 . Four-dimensional variational data assimilation for the blizzard of 2000 . Mon. Wea. Rev . 130 , 1967 – 1988 .  

  77. Zupanski , M. , Zupanski , D. , Vukiéevié , T. , Eis , K. and Vonder Haar , T . 2005 . CIRA/CSU four-dimensional variational data assimilation system . Mon. Wea. Rev . 133 , 829 – 843 .  

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