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Larow, T. E.; Krishnamurti, T. N. (2011)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Subjects:
A coupled ocean-atmosphere initialization scheme using Newtonian relaxation has beendeveloped for the Florida State University coupled ocean-atmosphere global general circulationmodel. The initialization scheme is used to initialize the coupled model for seasonal forecastingthe boreal summers of 1987 and 1988. The atmosphere model is a modified version of theFlorida State University global spectral model, resolution T-42. The ocean general circulationmodel consists of a slightly modified version of the Hamburg’s climate group model describedin Latif (1987) and Latif et al. (1993). The coupling is synchronous with information exchangedevery two model hours. Using ECMWF atmospheric daily analysis and observed monthlymean SSTs, two, 1-year, time-dependent, Newtonian relaxation were performed using thecoupled model prior to conducting the seasonal forecasts. The coupled initializations wereconducted from 1 June 1986 to 1 June 1987 and from 1 June 1987 to 1 June 1988. Newtonianrelaxation was applied to the prognostic atmospheric vorticity, divergence, temperature anddew point depression equations. In the ocean model the relaxation was applied to the surfacetemperature. Two, 10-member ensemble integrations were conducted to examine the impact ofthe coupled initialization on the seasonal forecasts. The initial conditions used for the ensemblesare the ocean’s final state after the initialization and the atmospheric initial conditions areECMWF analysis. Examination of the SST root mean square error and anomaly correlationsbetween observed and forecasted SSTs in the Nin˜o-3 and Nin˜o-4 regions for the 2 seasonalforecasts, show closer agreement between the initialized forecast than two, 10-member noninitializedensemble forecasts. The main conclusion here is that a single forecast with the coupledinitialization outperforms, in SST anomaly prediction, against each of the control forecasts(members of the ensemble) which do not include such an initialization, indicating possibleimportance for the inclusion of the atmosphere during the coupled initialization.DOI: 10.1034/j.1600-0870.1998.00006.x
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Anderson, J. and Gudgel, R. 1997. Impact of atmospheric initial conditions on seasonal predictions with a coupled ocean-atmosphere model. Proceedings of the 21st Annual Climate diagnostic Workshop. Department of Commerce/NOAA, 61-62.
    • Arakawa, A. and Lamb, V. R. 1977. Computational design of the basic dynamical processes for the UCAL general circulation model. J. Comput. Phys. 16, 173-263.
    • Barnett, T. P., Latif, M., Kirk, E. and Roeckner, E. 1991. On ENSO Physics. J. Climate 4, 487-515.
    • Businger, J. A., Wyngaard, J. C., Izumi, Y. and Bradly, E. F. 1971. Flux profile relationship in the atmospheric surface layer. J. Atmos. Sci. 28, 181-189.
    • Chang, L. W. 1978. Determination of surface flux of sensible heat, latent heat and momentum utilizing the bulk Richardson number. Papers in Meteor. Res. 1, 16-24.
    • Chen, D., Zebiak, S. E., Busalacchi, A. J. and Cane, M. A. 1995. An improved procedure for El Ni n˜o forecasting. Implications for predictability. Science 269, 1699-1702.
    • Daley, R. and Puri, K. 1980. Four-dimensional data assimilation and the slow manifold. Mon. Wea. Rev. 108, 85-99.
    • Derber, J. D. and Rosati, A. 1989. A global oceanic data assimilation system. J. Phys. Oceanogr. 19, 1333-1347.
    • Ghil, M. and Malanotte-Rizzoli, P. 1991. Data assimilation in meteorology and oceanography. Advances in Geophysics 33, 141-266.
    • Hellerman, S. and Rosenstein, M. 1983. Normal monthly wind stress over the world ocean with error estimates. J. Phys. Oceanogr. 13, 1093-1104.
    • Hoke, J. E. and Anthens, A. 1976. The initialization of numerical models by a dynamic-initialization technique. Mon. Wea. Rev. 105, 1551-1556.
    • HuVman, G. J., Adler, R. F., Rudolf, B., Schneider, U. and Keehn, P. R. 1995. Global precipitation estimates based on a technique for combining satellite-based estimates, rain-gauge analysis, and NWP model precipitation information. J. Climate 8, 1284-1295.
    • Ji, M., Kumar, A. and Leetmaa, A. 1994. A multi-season climate forecast system at the National Meteorological Center. Bull. Amer. Meteorol. Soc. 75, 569-577.
    • Kanamitsu, N. 1975. On numerical prediction over a global tropical belt. Report No. 75-1. Available from the Department of Meteorology. Florida State University. Tallahassee, Fl. 32306, 1-282.
    • Kanamitsu, N., Tada, K., Kudo, K., Sato, T. and Isa, N. 1983. Description of the JMA operational spectral model. J. Meteor. Soc. Japan 61, 812-828.
    • Krishnamurti, T. N., Low-Nam, S. and Pasch, R. 1983. Cumulus parameterization and rainfall rates (II). Mon. Wea. Rev. 111, 815-828.
    • Krishnamurti, T. N., Kumar, A., Yap, K. S., Dastoor, A., Davidson, N. and Sheng, J. 1990. Performance of a high resolution mesoscale tropical prediction model. Advances in Geophysics 32, 133-286.
    • Krishnamurti, T. N., Jishan Xue, Bedi, H. S., Ingles, K. and Oosterhof, D. 1991. Physical initialization for numerical weather prediction over the tropics. T ellus 43A/B, 53-81.
    • LaRow, T. E. 1997. Seasonal Simulation using a coupled ocean-atmosphere model. PhD Thesis. Florida State University, pp. 191.
    • Latif, M. 1987. Tropical Ocean circulation experiments. J. Phys. Oceanogr. 17, 246-263.
    • Latif, M., Sterl, A., Maier-Reimer, E. and Junge, M. M. 1993. Climate variability in a coupled GCM. Part I: The tropical Pacific. J. Climate 6, 5-21.
    • Latif, M., Barnett, T. P., Cane, M. A., Flugel, M., Graham, N. E., Von Storch, H., Xu, J. S. and Zebiak, S. E. 1994. A review of ENSO prediction studies. Climate Dynamics 9, 167-179.
    • Latif, M., Stockdale, T., WolV, J., Burgers, G., MaierReimer, E., Junge, M., Arpe, K. and Bengtsson, L. 1994b. Climatology and variability in the ECHO coupled GCM. T ellus 46A, 351-366.
    • Levitus, S. 1982. Climatological atlas of the world ocean. NOAA Professional paper no. 13, 173 pp., 17 microfiche.
    • Louis, J.-F. 1981. A parametric model of vertical eddy fluxes in the atmosphere. Boundary L ayer Meteorology 17, 187-202.
    • Oberhuber, J. M. 1988. An atlas based on the COADS data set: the budgets of heat, buoyancy and turbulent kinetic energy at the surface of the global ocean. MaxPlanck-Institute for Meteorology/Hamburg Report No. 15.
    • Pacanowski, R. and Philander, G. 1981. Parameterization of vertical mixing in numerical models of tropical oceans. J. Phys. Oceanogr. 23, 1443-1451.
    • Reynolds, R. W. 1988. A real-time global sea surface temperature analysis. J. Climate 1, 75-86.
    • Ramamurthy, M. K. and Carr, F. H. 1987. Fourdimensional data assimilation in the monsoon region. Part I: Experiments with wind data. Mon. Wea. Rev. 115, 1678-1706.
    • Rosati, A., Miyakoda, K. and Gudgel, R. 1997. The impact of ocean initial conditions on ENSO forecasting with a coupled model. Mon. Wea. Rev. 125, 754-772.
    • StauVer, D. R. and Seaman, N. L. 1990. Use of FourDimensional Data Assimilation in a limited area mesoscale model part II. EVects of data assimilation within the planetary boundary layer. Mon. Wea. Rev. 119, 734-754.
    • Stockdale, T., Burgers, G., Latif, M. and WolV, J. 1994. Some sensitivities of a coupled ocean-atmosphere GCM. T ellus 46A, 367-380.
    • Stricherz, J. N., O'Brien, J. J. and Legler, D. M. 1992. Atlas of Florida State University winds for T OGA 1966-1985, 256 pp.
    • Tiedke, M. 1984. The sensitivity of the time-mean largescale flow to cumulus convection in the ECMWF model. Workshop on Convection in large-scale numerical model ECMWF, 297-317.
    • Yap, K. S. 1995. Impact of a Newtonian assimilation and physical initialization on the initialization and prediction by a tropical mesoscale model. Mon. Wea. Rev. 123, 833-861.
    • Zebiak, S. E. and Cane, M. A. 1987. A model of El Ni n˜oSouthern Oscillation. Mon. Wea. Rev. 115, 2262-2278.
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