Summary
Synoptic/diagnostic case studies have increasingly come to rely on numerical simulations started from some initial state after which the model generated fields receive no further information from observed data. The purpose of this paper is to demonstrate the use of a dynamic data assimilation technique based on nudging to create a dynamically consistent high-resolution four-dimensional data set that can be used for synoptic diagnostic studies. The nudging technique is applied in the Goddard Mesoscale Atmospheric Simulation System (GMASS) using the 3-h radiosonde data collected during GALE IOP 1. A unique aspect of this application is nudging toward data analyses for which the areal coverage shifts with time. One of the two nudging simulations assimilates surface pressure in addition to the temperature, mixing ratio, and wind components. The nudging values are determined by linear interpolation between 3-h observation times. Assuming a linear variation of the assimilated value in time leads to estimates of the nudging coefficients which take into account the accuracy of the observations.
Both nudging simulations are more accurate in terms of S hand root-mean-square error (RMSE) scores than a control sunulation without successive initialization. The nudging simulation with surface pressure is more accurate than the nudging simulation without surface pressure assimilation for this case. The simulation with surface pressure nudging captures the surface cyclogenesis and the associated strong rise-fall couplet in the 500 hPa height field. It also exhibits the strongest ageostrophic flow and exit region vertical circulation associated with a jet streak on the western side of the intensifying upper-level trough.
The data sets made possible by the dynamic assimilation/ simulation cycles are dynamically consistent, have high spatial and temporal resolution and are ideally suited for diagnostic studies. Examples presented include the evolution of the ageostrophic flow associated with the exit region of an upper-level jet propagating toward the base of an intensifying trough with increasing cyclonic curvature of the flow. The nudging simulation with surface pressure provides the resolution and accuracy required to depict the rapid transformation (within a 12-h period) of the exit region ageostrophic flow from predominantly cross contour to along contour as the jet streak approaches the base of the trough.
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References
Anthes, R. A., 1974: Data assimilation and initialization of hurricance prediction models.J. Atmos. Sci.,31, 702–719.
Aune, R. M., Uccellini, L. W., Petersen, R. A., Tuccillo, J. J., 1987: A VAS-numerical model impact study using Gal-Chen's variational approach.Mon. Wea. Rev.,115, 1009–1035.
Barnes, S. L., 1973: Mesoscale objective analysis using weighted time-series observations. NOAA Tech. Memo. ERL NSSL-62, National Severe Storms Laboratory, Norman, OK 73069, 60 pp. [NTIS COM-73-10781].
Cressman, G. P., 1959: An operational objective analysis system.Mon. Wea. Rev.,87, 367–374.
Davies, H. C., Turner, R. E., 1977: Updating prediction models by dynamical relaxation: an examination of the technique.Quart. J. Roy. Meteor. Soc.,103, 225–245.
Dirks, R. A., Kuettner, J. P., Moore, J. A., 1988: Genesis of Atlantic Lows Experiment (GALE). An overview.Bull. Am. Meteor. Soc.,69, 148–160.
Douglas, S. G., Warner, T. T., 1987: Utilization of VAS satellite data in the initialization of an oceanic cyclogenesis simulation.Mon. Wea. Rev.,115, 2996–3012.
Hoke, J. E., 1976: Initialization of models for numerical weather prediction by a dynamic-initialization technique. Ph. D. Thesis, The Pennsylvania State University, 202 pp.
Hoke, J. E., Anthes, R. A., 1976. The initialization of numerical models by a dynamic-initialization technique.Mon. Wea. Rev.,104, 1551–1556.
Hoke, J. E., Phillips, N. A., DiMego, G. J., Tuccillo, J. J., Sela, J. G., 1989. The Regional Analysis and Forecast System of the National Meteorological Center.Wea. and Forcasting,4, 323–334.
Kaplan, M. L., Zack, J. W., Wong, V. C., Tuccillo, J. J., 1982. Initial results from a mesoscale atmospheric simulation system and comparisons with the AVE-SESAME I data set.Mon. Wea. Rev.,110, 1564–1590.
Keyser, D., Uccellini, L. W., 1987: Regional models: Emerging research tools for synoptic meteorologists.Bull. Amer. Meteor. Soc.,68, 306–320.
Kistler, R. E., 1974: A study of data assimilation techniques in an autobarotropic primitive equation, channel model. M. S. Thesis, Dept. of Meteorology, The Pennsylvania State University, 84 pp.
Koch, S. E., des Jardins, M., Kocin, P. J., 1983: An interactive Barnes objective map analysis scheme for use with satellite and conventional data.J. Climate Appl. Meteor.,22, 1487–1503.
Krishnamurti, T. N., Bedi, H. S., Heckley, W., Ingles, K., 1988: Reduction of the spinup time for evaporation and precipitation in a spectral model.Mon. Wea. Rev.,116, 907–920.
Kuo, Y.-H., Guo, Y.-R., 1989: Dynamic initialization using observations from a network of profilers and its impact on short-range numerical weather prediction.Mon. Wea. Rev.,117, 1975–1998.
Manobianco, J., Uccellini, L. W., Brill, K. F., Kocin, P. J., 1990: Contrasting the impact of dynamic data assimilation on the numerical simulations of cyclogenesis during GALE IOP 10 and IOP 1.Meteor. Atmos. Phys.,45, 41–63.
Petersen, R. A., 1986: Detailed three-dimensional isentropic analysis using an objective cross-sectional approach.Mon. Wea. Rev.,114, 719–735.
Petersen, R. A., Tuccillo, J. J., Brill, K. F., Uccellini, L. W., 1985: The sensitivity of a mesoscale forecast model to detailed three-dimensional isentropic initial analysis and varied vertical model resolution. Preprints, Seventh Conf. Numerical Weather Prediction, Montreal, Canada, Amer. Meteor. Soc., 83–90.
Pielke, R. A., Cram, J. M., 1987: An alternate procedure for analyzing surface geostrophic winds and pressure over elevated terrain.Wea. and Forecasting,2, 229–236.
Ramamurthy, M. K., Carr, F. H., 1987: Four-dimensional data assimilation in the monsoon region. Part I: Experiments with wind data.Mon. Wea. Rev.,115, 1678–1706.
Reed, R. J., 1955: A study of a characteristic type of upperlevel frontogenesis.J. Meteor.,12, 226–237.
Reed, R. J., Danielsen, E. F., 1959: Fronts in the vicinity of the tropopause.Arch. Meteor. Geophys. Bioklim., Ser. A,11, 1–17.
Stauffer, D. R., Seaman, N. L., 1988: Use of four-dimensional data assimilation to limit error growth in a mesoscale numerical model simulation. Preprints, Eighth Conf. on Numerical Weather Prediction, Baltimore, MD, Amer. Meteor. Soc., 408–415.
Stauffer, D. R., Seaman, N. L., 1987: A real-data numerical study and four-dimensional data assimilation application for mesobeta-scale flow in complex terrain. Proc. Symp. Mesoscale Analysis & Forecasting. Vancouver, Canada, ESA, 533–538.
Stauffer, D. R., Warner, T. T., Seaman, N. L., 1985: A Newtonian “nudging” approach to four-dimensional data assimilation: Use of SESAME-IV data in a mesoscale model. Preprints, Seventh Conf. on Numerical Weather Prediction, Montreal, Canada, Amer. Meteor. Soc., 77–82.
Teweles, S. Jr., Wobus, H. B., 1954: Verification of prognostic charts. Bull. Amer. Meteor. Soc.,35, 455–463.
Uccellini, L. W., Petersen, R. A., Brill, K. F., Kocin, P. J., Tuccillo, J. J., 1987. Synergistic interactions between an upper-level jet streak and diabatic processes that influence the development of a low-level jet and a secondary coastal cyclone.Mon. Wea. Rev.,115, 2227–2261.
Wang, W., Warner, T. T., 1988: Use of four-dimensional data assimilation by Newtonian relaxation and latent-heat forcing to improve a mesoscale-model precipitation forecast. A case study.Mon. Wea. Rev.,116, 2593–2613.
Whitaker, J. S., Uccellini, L. W., Brill, K. F., 1988: A modelbased diagnostic study of the rapid development phase of the Presidents' Day cyclone.Mon. Wea. Rev.,116, 2337–2365.
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Brill, K.F., Uccellini, L.W., Manobianco, J. et al. The use of successive dynamic initialization by nudging to simulate cyclogenesis during GALE IOP 1. Meteorl. Atmos. Phys. 45, 15–40 (1991). https://doi.org/10.1007/BF01027473
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DOI: https://doi.org/10.1007/BF01027473