Abstract
In this study, the impacts of horizontal resolution on the conditional nonlinear optimal perturbation (CNOP) and on its identified sensitive areas were investigated for tropical cyclone predictions. Three resolutions, 30 km, 60 km, and 120 km, were studied for three tropical cyclones, TC Mindulle (2004), TC Meari (2004), and TC Matsa (2005).
Results show that CNOP may present different structures with different resolutions, and the major parts of CNOP become increasingly localized with increased horizontal resolution. CNOP produces spiral and baroclinic structures, which partially account for its rapid amplification. The differences in CNOP structures result in different sensitive areas, but there are common areas for the CNOP-identified sensitive areas at various resolutions, and the size of the common areas is different from case to case. Generally, the forecasts benefit more from the reduction of the initial errors in the sensitive areas identified using higher resolutions than those using lower resolutions. However, the largest improvement of the forecast can be obtained at the resolution that is not the highest for some cases. In addition, the sensitive areas identified at lower resolutions are also helpful for improving the forecast with a finer resolution, but the sensitive areas identified at the same resolution as the forecast would be the most beneficial.
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Ancell, B. C., and C. F. Mass, 2006: Structure, growth rates, and tangent linear accuracy of adjoint sensitivities with respect to horizontal and vertical resolution. Mon. Wea. Rev., 134, 2971–2988.
Bergot, T., G. Hello, A. Joly, and S. Malardel, 1999: Adaptive observations: A feasibility study. Mon. Wea. Rev., 127, 743–765.
Birgin, E. G., J. E. Martinez, and R. Marcos, 2001: Algorithm 813: SPG-Software for convex-constrained optimization. ACM Transactions on Mathematical Software, 27, 340–349.
Bishop, C. H., B. J. Etherton, and S. J. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Mon. Wea. Rev., 129, 420–436.
Buizza, R., C. Cardinali, G. Kelly, and J. Thépaut, 2007: The value of targeted observations Part II: The value of observations taken in singular vectors-based target areas. Quart. J. Roy. Meteor. Soc., 133, 1817–1832.
Cardinali, C., R. Buizza, G. Kelly, M. Shapiro, and J-N. Thépaut, 2007: The value of observations. Part III: Influence of weather regimes on targeting. Quart. J. Roy. Meteor. Soc., 133, 1833–1842.
Chen, Y., and M. K. Yau, 2001: Spiral bands in a simulated hurricane. Part I: Vortex rossby wave verification. J. Atmos. Sci, 58, 2128–2145.
Duan, W. S., and M. Mu, 2006: Investigating decadal variability of El Nino-Southern Oscillation asymmetry by conditional nonlinear optimal perturbation. J. Geophys. Res., 111, Co7015, doi: 10.1029/2005JC003458.
Dudhia, J., 1993: A nonhydrostatic version of the Penn State/NCAR Mesoscale Model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev., 121, 1493–1513.
Ehrendorfer, M., and R. M. Errico, 1995: Mesoscale predictability and the spectrum of optimal perturbations. J. Atmos. Sci., 52, 3475–3500.
Gall, R., J. Tuttle, and P. Hildebrand, 1998: Small-scale spiral bands observed in Hurricanes Andrew, Hugo, and Erin. Mon. Wea. Rev., 126, 1749–1766.
Gelaro, R., T. Rosmond, and R. Daley, 2002: Singular vector calculations with an analysis error variance metric. Mon. Wea. Rev., 130(5), 1166–1186.
Gilmour, I., L. A. Smith, and R. Buizza, 2001: Linear regime duration: Is 24 hours a long time in synoptic weather forecasting? J. Atmos. Sci., 58, 3525–3539.
Guinn, T. A., and W. H. Schubert, 1993: Hurricane spiral bands. J. Atmos. Sci., 50, 3380–3403.
Hamill, T. M., and C. Snyder, 2002: Using improved background-error covariance from an ensemble Kalman filter for adaptive observations. Mon. Wea. Rev., 130, 1552–1572.
Langland, R. H., 1999: Workshop on targeted observations for extratropical and tropical forecasting. Bull. Amer. Meteor. Soc., 80, 2331–2338.
Leutbecher, M., J. Barkmeijer, T. N. Palmer, and A. J. Thorpe, 2002: Potential improvement to forecasts of two severe storms using targeted observations. Quart. J. Roy. Meteor. Soc., 128, 1641–1670.
Majumdar, S. J., S. D. Aberson, C. H. Bishop, R. Buizza, M. S. Peng, and C. A. Reynolds, 2006: A comparison of adaptive observing guidance for Atlantic tropical cyclones. Mon. Wea. Rev., 134, 2354–2372.
Montgomery, M. T., and R. J. Kallenbach, 1997: A theory for vortex Rossby waves and its application to spiral bands and intensity changes in hurricanes. Quart. J. Roy. Meteor. Soc., 123, 535–565.
Moller, J. D., and M. T. Montgomery, 2000: Tropical cy clone evolution via potential vorticity anomalies in a three-dimensional balance Model. J. Atmos. Sci, 57, 3366–3387.
Moon, Y., and D. S. Nolan, 2010: The dynamic response of the hurricane wind field to spiral rainband heating. J. Atmos. Sci, 67, 1779–1805, doi: 10.1175/2010JAS3171.1.
Mu, M., and W. S. Duan, 2003: A new approach to studying ENSO predictability: conditional nonlinear optimal perturbation. Chinese Science Bulletin, 48, 747–749.
Mu, M., and Z. Y. Zhang, 2006: Conditional nonlinear optimal perturbations of a barotropic model. J. Atmos. Sci., 63, 1587–1604.
Mu, M., and Z. N. Jiang, 2008: A new method to generate the initial perturbations in ensemble forecast: conditional nonlinear optimal perturbations. Chinese Science Bulletin, 53, 2062–2068S.
Mu, M., L. Sun, and D. A. Hank, 2004: The sensitivity and stability of the ocean’s thermohaline circulation to finite amplitude perturbations. J. Phys. Oceanogr., 34, 2305–2315.
Mu, M., H. L. Wang, and F. F. Zhou, 2007a: A preliminary application of Conditional Nonlinear Optimal Perturbation to adaptive observation. Chinese J. Atmos. Sci., 31, 1102–1112. (in Chinese)
Mu, M., H. Xu, and W. S. Duan, 2007b: A kind of initial errors related to “spring predictability barrier” for El Niño events in Zebiak-Cane model. Geophys. Res. Lett., doi: 10.1029/2006GL027412.
Mu, M., F. F. Zhou, and H. L. Wang, 2009: A method to identify the sensitive areas in targeting for tropical cyclone prediction: Conditional nonlinear optimal perturbation. Mon. Wea. Rev., 137, 1623–1639.
Palmer, T. N., R. Gelaro, J. Barkmeijer, and R. Buizza, 1998: Singular vectors, metrics, and adaptive observations. J. Atmos. Sci., 55, 633–653.
Rivier, O., G. Lapeyre, and O. Talagrand, 2008: Nonlinear generalization of singular vectors: Behavior in a baroclinic unstable flow. J. Atmos. Sci, 65, 1896–1911.
Sun, L., M. Mu, D. J. Sun, and X. Y. Yin, 2005: Passive mechanism of decadal variation of thermohaline circulation. J. Geophys. Res., 110, C07025, doi: 10.1029/2005JC002897.
Tan, X. W., B. Wang, and D. L. Wang, 2010: Impact of different guidances on sensitive areas of targeting observations based on the CNOP method. Acta Meteorologica Sinica, 24, 17–30.
Terwisscha van Scheltinga, A. D., and H. A. Dijkstra, 2008: Conditional nonlinear optimal perturbations of the double-gyre ocean circulation. Nonlinear Processes Geophysics, 15, 727–734.
Wu, C. C., J. H. Chen, P. H. Lin, and K. H. Chou, 2007: Targeted observations of tropical cyclone movement based on the adjoint-derived sensitivity steering vector. J. Atmos. Sci., 64, 2611–2626.
Wang, B., and X. W. Tan, 2010: Conditional nonlinear optimal perturbations: adjoint-free calculation method and preliminary test. Mon. Wea. Rev., 138, 1043–1049.
Wu, C. C., and Coauthors, 2009: Intercomparison of targeted observation guidance for tropical cyclones in the northwestern Pacific. Mon. Wea. Rev., 137, 2471–2492.
Yamaguchi, M., T. Iriguchi, T. Nakazawa, and C. C. Wu, 2009: An observing system experiment for Typhoon Conson (2004) using a singular vector method and DOTSTAR data. Mon. Wea. Rev., 137, 2801–2816.
Yu, Y. S., W. S. Duan, H. Xu, M. Mu, 2009: Dynamics of nonlinear error growth and season-dependent predictability of El Niño events in the Zebiak-Cane model. Quart. J. Roy. Meteor. Soc., 135, doi: 10.1002/qj.526.
Zou, X., F. Vandenberghe, M. Pondeca, and Y.-H. Kuo, 1997: Introduction to adjoint techniques and the MM5 adjoint modeling system. NCAR Tech. Note, NCAR/TN-435-STR, 107pp.
Zhou, F. F., and M. Mu, 2011: The impact of verification area design on tropical cyclone targeted observations based on the CNOP method. Adv. Atmos. Sci., 28, 997–1010, doi: 10.1007/s00376-011-0120-x.
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Zhou, F., Mu, M. The impact of horizontal resolution on the CNOP and on its identified sensitive areas for tropical cyclone predictions. Adv. Atmos. Sci. 29, 36–46 (2012). https://doi.org/10.1007/s00376-011-1003-x
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DOI: https://doi.org/10.1007/s00376-011-1003-x