Four-Dimensional Variational Data Analysis of Water Vapor Raman Lidar Data and Their Impact on Mesoscale Forecasts

Matthias Grzeschik Institute of Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

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Hans-Stefan Bauer Institute of Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

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Volker Wulfmeyer Institute of Physics and Meteorology, University of Hohenheim, Stuttgart, Germany

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Dirk Engelbart German Meteorological Service, Lindenberg Observatory, Lindenberg, Germany

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Ulla Wandinger Leibniz Institute for Tropospheric Research, Leipzig, Germany

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Ina Mattis Leibniz Institute for Tropospheric Research, Leipzig, Germany

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Dietrich Althausen Leibniz Institute for Tropospheric Research, Leipzig, Germany

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Ronny Engelmann Leibniz Institute for Tropospheric Research, Leipzig, Germany

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Matthias Tesche Leibniz Institute for Tropospheric Research, Leipzig, Germany

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Andrea Riede Leibniz Institute for Tropospheric Research, Leipzig, Germany

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Abstract

The impact of water vapor observations on mesoscale initial fields provided by a triangle of Raman lidar systems covering an area of about 200 km × 200 km is investigated. A test case during the Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH-2005) was chosen. Evaluation of initial water vapor fields derived from ECMWF analysis revealed that in the model the highly variable vertical structure of water vapor profiles was not recovered and vertical gradients were smoothed out. Using a 3-h data assimilation window and a resolution of 10–30 min, continuous water vapor data from these observations were assimilated in the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) by means of a four-dimensional variational data analysis (4DVAR). A strong correction of the vertical structure and the absolute values of the initial water vapor field of the order of 1 g kg−1 was found. This occurred mainly upstream of the lidar systems within an area, which was comparable with the domain covered by the lidar systems. The correction of the water vapor field was validated using independent global positioning system (GPS) sensors. Much better agreement to GPS zenith wet delay was achieved with the initial water vapor field after 4DVAR. The impact region was transported with the mean wind and was still visible after 4 h of free forecast time.

Corresponding author address: Matthias Grzeschik, Institute of Physics and Meteorology, University of Hohenheim, Garbenstrasse 30, 70599 Stuttgart, Germany. Email: grz@uni-hohenheim.de

This article included in the Fifth International Symposium on Tropospheric Profiling (ISTP) special collection.

Abstract

The impact of water vapor observations on mesoscale initial fields provided by a triangle of Raman lidar systems covering an area of about 200 km × 200 km is investigated. A test case during the Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH-2005) was chosen. Evaluation of initial water vapor fields derived from ECMWF analysis revealed that in the model the highly variable vertical structure of water vapor profiles was not recovered and vertical gradients were smoothed out. Using a 3-h data assimilation window and a resolution of 10–30 min, continuous water vapor data from these observations were assimilated in the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) by means of a four-dimensional variational data analysis (4DVAR). A strong correction of the vertical structure and the absolute values of the initial water vapor field of the order of 1 g kg−1 was found. This occurred mainly upstream of the lidar systems within an area, which was comparable with the domain covered by the lidar systems. The correction of the water vapor field was validated using independent global positioning system (GPS) sensors. Much better agreement to GPS zenith wet delay was achieved with the initial water vapor field after 4DVAR. The impact region was transported with the mean wind and was still visible after 4 h of free forecast time.

Corresponding author address: Matthias Grzeschik, Institute of Physics and Meteorology, University of Hohenheim, Garbenstrasse 30, 70599 Stuttgart, Germany. Email: grz@uni-hohenheim.de

This article included in the Fifth International Symposium on Tropospheric Profiling (ISTP) special collection.

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  • Althausen, D., Müller D. , Ansmann A. , Wandinger U. , Hube H. , Clauder E. , and Zörner S. , 2000: Scanning 6-wavelength 11-channel aerosol lidar. J. Atmos. Oceanic Technol., 17 , 14691482.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anthes, R. A., and Warner T. T. , 1978: Development of hydrodynamic models suitable for air pollution and other mesometeorological studies. Mon. Wea. Rev., 106 , 10451078.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arnaud, P., Bouvier C. , Cisneros L. , and Dominguez R. , 2002: Influence of rainfall spatial varibility on flood prediction. J. Hydrol., 260 , 216230.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barker, D. M., Huang W. , Guo Y-R. , 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
  • Berg, L. K., and Zhong S. , 2005: Sensitivity of MM5-simulated boundary layer characteristics to turbulence parameterizations. J. Appl. Meteor., 44 , 14671483.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bright, D. R., and Mullen S. L. , 2002: The sensitivity of the numerical simulation of the southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5. Wea. Forecasting, 17 , 99114.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caya, A., Sun J. , and Snyder C. , 2005: A comparison between the 4DVAR and the ensemble Kalman filter techniques for radar data assimilation. Mon. Wea. Rev., 133 , 30813094.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cheng, W. Y. Y., and Cotton W. R. , 2004: Sensitivity of a cloud-resolving simulation of the genesis of a mesoscale convective system to horizontal heterogeneities in soil moisture initialization. J. Hydrometeor., 5 , 934958.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crook, N. A., 1996: Sensitivity of moist convection forced by boundary layer processes to low-level thermodynamic fields. Mon. Wea. Rev., 124 , 17671785.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deutscher Wetterdienst, 2000: Satellite application facility on climate monitoring: Science plan. Deutscher Wetterdienst Tech. Rep. SAF/CM/DWD/SCI3.0, 154 pp.

  • Doms, G., Gassmann A. , Heise E. , Raschendorfer M. , Schraff C. , and Schrodin R. , 2002: Parameterization issues in the nonhydrostatic NWP-model LM. Proc. Seminar on Key Issues in the Parameterization of Subgrid Physical Processes, Reading, United Kingdom, ECMWF, 205–252.

  • Ducrocq, V., Lafore J-P. , Redelsperger J-L. , and Orain F. , 2000: Initialization of a fine-scale model for convective-system prediction: A case study. Quart. J. Roy. Meteor. Soc., 126 , 30413065.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Engelbart, D., and Haas E. , 2007: LAUNCH-2005: International Lindenberg campaign for assessment of humidity and cloud profiling systems and its impact on high-resolution modelling. Proc. COST-720 Final Symp. on Applications of Atmospheric Profiles in Research and Operations, Toulouse, France, Météo-France.

    • Search Google Scholar
    • Export Citation
  • Errico, R., Raeder K. , and Ehrendorfer M. , 2004: Singular vectors for moisture-measuring norms. Quart. J. Roy. Meteor. Soc., 130 , 963987.

  • Faccani, C., and Ferretti R. , 2005: Data assimilation of high-density observations. I: Impact on initial conditions for the MAP/SOP IOP2b. Quart. J. Roy. Meteor. Soc., 131A , 2142.

    • Search Google Scholar
    • Export Citation
  • Fillion, L., and Mahfouf J-F. , 2000: Coupling of moist-convective and stratiform precipitation processes for variational data assimilation. Mon. Wea. Rev., 128 , 109124.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Flores, A., Ruffini G. , and Rius A. , 2000: 4D tropospheric tomography using GPS slant wet delays. Ann. Geophys., 18 , 223234.

  • Gendt, G., Dick G. , Reigber C. , Tomassini M. , Lui Y. , and Ramatschi M. , 2004: Near real time GPS water vapor monitoring for numerical weather prediction in Germany. J. Meteor. Soc. Japan, 82 , 361370.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goldsmith, J. E. M., Blair F. H. , Bisson S. E. , and Turner D. D. , 1998: Turn-key Raman lidar for profiling atmospheric water vapor, clouds, and aerosols. Appl. Opt., 37 , 49794990.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grell, G. A., Dudhia J. , and Stauffer D. R. , 1995: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note NCAR/TN-398+STR, 122 pp.

  • Hamill, T. M., and Snyder C. , 2002: Using improved background-error covariances from an ensemble Kalman filter for adaptive observations. Mon. Wea. Rev., 130 , 15521572.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holt, T. R., Niyogi D. , Chen F. , Manning K. , LeMone M. A. , and Qureshi A. , 2006: Effect of land–atmosphere interactions on the IHOP 24–25 May 2002 convective case. Mon. Wea. Rev., 134 , 113133.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lorenc, A., 2003: The potential of the ensemble Kalman filter for NWP—A comparison with 4D-VAR. Quart. J. Roy. Meteor. Soc., 129 , 31833203.

  • MacDonald, A., Xie Y. , and Ware R. , 2002: Diagnosis of three dimensional water vapor using a GPS network. Mon. Wea. Rev., 130 , 386397.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mattis, I., and Jaenisch V. , 2006: Automated Lidar Data Analyzer (ALDA) for RAMSES—The autonomously operating German Meteorological Service Raman Lidar for Atmospheric Moisture Sensing. Proc. 23rd Int. Laser Radar Conf., Nara, Japan, 215–218.

  • Mattis, I., and Coauthors, 2002: Relative-humidity profiling in the troposphere with a Raman lidar. Appl. Opt., 41 , 64516462.

  • Nehrkorn, T., Modica G. D. , Cemiglia M. , Ruggiero F. H. , Michalakes J. G. , and Zou X. , 2001: MM5 adjoint development using TAMC: Experiences with an automatic code generator. Preprints, 14th Conf. on Numerical Weather Prediction, Ft. Lauderdale, FL, Amer. Meteor. Soc., 481–484. [Available online at http://ams.confex.com/ams/pdfpapers/22235.pdf.].

  • Randel, D. L., and Coauthors, 1999: The WCRP/GEWEX Global Water Vapor Project (GVaP): Science plan. IGPO Publication Series 27, 46 pp. [Available from the International GEWEX Project Office, 1010 Wayne Ave., Silver Spring, MD 20910.].

  • Richard, E., Cosma S. , Benoit R. , Binder P. , Buzzi A. , and Kaufmann P. , 2003: Intercomparison of mesoscale meteorological models for precipitation forecasting. Hydrol. Earth Syst. Sci., 7 , 799811.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosatti, G., Cesari D. , and Bonaventura L. , 2005: Semi-implicit, semi-Lagrangian modelling for environmental problems on staggered Cartesian grids with cut cells. J. Comput. Phys., 204 , 353377.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ruggiero, F. H., Modica G. D. , Nehrkorn T. , Cerniglia M. , Michalakes J. , and Zou X. , 2001: Development of an MM5-based four-dimensional variational assimilation system for distributed memory multiprocessor computers. Preprints, HPCMP 2001 User’s Group Conf., Biloxi, MS, U.S. Naval Oceanographic Office.

  • Stauffer, D. R., and Seaman N. L. , 1994: Multiscale four-dimensional data assimilation. J. Appl. Meteor., 33 , 416434.

  • Steppeler, J., and Coauthors, 2006: Prediction of clouds and rain using a z-coordinate nonhydrostatic model. Mon. Wea. Rev., 134 , 36253643.

  • Trier, S., Chen F. , and Manning K. , 2004: A study of convection initiation in a mesoscale model using high-resolution land surface initial conditions. Mon. Wea. Rev., 132 , 29542976.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, D., Ferrare R. , Brasseur L. H. , Feltz W. , and Tooman T. , 2002: Automated retrievals of water vapor and aerosol profiles from an operational Raman lidar. J. Atmos. Oceanic Technol., 19 , 3750.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wandinger, U., 2005: Raman lidar. Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere, C. Weitkamp, Ed., Springer, 241–271.

    • Search Google Scholar
    • Export Citation
  • Whiteman, D., 2003: Examination of the traditional Raman lidar technique. II: Evaluating the ratios for water vapor and aerosols. Appl. Opt., 42 , 25932608.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wulfmeyer, V., and Coauthors, 2003: Workshop report: Lidar research network water vapor and wind. Meteor. Z., 12 , 524.

  • Wulfmeyer, V., Bauer H. S. , Grzeschik M. , Behrendt A. , Vandenberghe F. , Browell E. V. , Ismail S. , and Ferrare R. A. , 2006: Four-dimensional variational assimilation of water vapour differential absorption lidar data: The first case study within IHOP_2002. Mon. Wea. Rev., 134 , 209230.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiao, Q., Zou X. , and Wang B. , 2000: Initialization and simulation of a land-falling hurricane using a variational bogus data assimilation scheme. Mon. Wea. Rev., 128 , 22522269.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zängl, G., 2004a: Numerical simulations of the 12–13 August 2002 flooding event in eastern Germany. Quart. J. Roy. Meteor. Soc., 130 , 19211940.

  • Zängl, G., 2004b: The sensitivity of simulated orographic precipitation to model components other than cloud microphysics. Quart. J. Roy. Meteor. Soc., 130 , 18571875.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zou, X., Kuo Y-H. , and Guo Y-R. , 1995: Assimilation of atmospheric radio refractivity using a nonhydrostatic adjoint model. Mon. Wea. Rev., 123 , 22292250.

    • Crossref
    • Search Google Scholar
    • Export Citation
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