Examination of parameter variations in the U. S. Navy Global Ensemble

Article English OPEN
Reynolds, Carolyn A. ; Ridout, James A. ; McLay, Justin G. (2011)
  • Publisher: Co-Action Publishing
  • Journal: Tellus A (issn: 1600-0870)
  • Related identifiers: doi: 10.3402/tellusa.v63i5.15870
  • Subject:
    arxiv: Physics::Atmospheric and Oceanic Physics

The impact of parameter variations on the Navy Operational Global Atmospheric Prediction System ensemble performance is examined, and subsets of ensemble members are used to identify the relative impact of the individual parameters. Two sets of parameter variations are considered. The first set has variations in the parametrization of cumulus convection only. The second set has variations in both convection and boundary layer parametrizations. In the tropics, parameter variations significantly increase ensemble spread in wind and temperature fields, and significantly reduce Brier scores for low-level wind speed and temperature, primarily through improvements to the resolution (the impact in the extratropics is negligible). There are also small but significant improvements in the ensemble mean tropical cyclone track forecasts. For the metrics considered here, the second set of parameter variations outperforms the first set. Examination of the spread within ensemble subsets suggests that the parameter with the biggest overall impact is one that helps to control the convective updraft parcel temperature deficit at cloud base level. Variations in the von Kármán constant significantly increase ensemble spread in the low-level tropical winds near the date line, and in the low-level temperature field throughout the tropics and subtropics.
  • References (58)
    58 references, page 1 of 6

    Alhamed, A., Lakshmivarahan, S. and Stensrud, D. J. 2002. Cluster analysis of multimodel ensemble data from SAMEX. Mon. Wea. Rev. 130, 226-256.

    Andreas, E. L. 2009. A new value of the von Ka´rma´n constant: implications and implementation. J. Appl. Met. Clim. 48, 923-944.

    Berner, J., Schutts, G. J., Leutbecher, M. and Palmer, T. N. 2009. A spectral stochastic kinetic energy backscatter scheme and its impact on flow-dependent predictability in the ECMWF ensemble prediction system. J. Atmos. Sci. 66, 603-626.

    Berner, J., Ha, S.-Y., Hacker, J. P., Fournier, A. and Snyder, C. 2011. Model uncertainty in a mesoscale ensemble prediction system: stochastic versus multi-physics representations. Mon. Wea. Rev. 139, 1972-1995.

    Betts, A. K. and Miller, M. J. 1986. A new convective adjustment scheme. Part II: single column tests using GATE wave, BOMEX, ATEX and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc. 112, 693-709.

    Bishop, C. H. and Toth, Z. 1999. Ensemble transformation and adaptive observations. J. Atmos. Sci. 56, 1748-1765.

    Bowler, N. E., Arribas, A., Beare, S. E., Mylne, K. R. and Schutts, G. J. 2009. The local ETKF and SKEB: upgrades to the MOGREPS shortrange ensemble prediction system. Quart. J. Roy. Meteor. Soc. 135, 767-776.

    Bowler, N. E., Arribas, A., Mylne, K. R., Robertson, K. B. and Beare, S. E. 2008. The MOGREPS short-range ensemble prediction system. Quart. J. Roy. Meteor. Soc. 134, 703-722.

    Businger, J. A., Wyngaard, J. C., Izumi, Y. and Bradley, E. F. 1971. Flux profile relationships in the atmospheric surface layer. J. Atmos. Sci. 28, 181-189.

    Bright, D. R. and Mullen, S. L. 2002. Short-range ensemble forecasts of precipitation during the southwest monsoon. Wea. Forecast. 17, 1080-1100.

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