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Evaluation of Practical Predictability of Blocking Anticyclones Using Modern Hydrodynamic Models

Russian Meteorology and Hydrology volume 47, pages 1–13 (2022)Cite this article

Abstract

The problem of predictability of atmospheric processes such as blocking in the Northern Hemisphere on intraseasonal timescales is considered using the operational version of the semi-Lagrangian atmosphere model for long-rahge forecasting (SL-AV) of the Hydrometcenter of Russia, as well as the U.K. Met Office coupled atmosphere–ocean model (UKMO) and the reanalysis of the European Center for Medium-range Weather Forecasts (ERA5). It is shown that beyond the first forecast week, the quality of deterministic forecasts drops sharply, and the forecast error grows rapidly. The use of probabilistic formulations makes it possible to extend the time interval of the skillful forecast from a week to a month. The dependence of the forecast quality on initial data of the model, as well as on spatiotemporal scales of blocking systems, is demonstrated by the case study (the summer of 2010 in the European part of Russia). Some specific features of the verification of forecasts of rare events, such as blocking, are noted. The results can be used for preparing long-range meteoroloical forecasts on intraseasonal timescales.

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REFERENCES

  1. Analysis of Abnormal Weather Conditions on the Territory of Russia in the Summer of 2010. Collected Papers, Ed. by N. P. Shakina (Triada, Moscow, 2011) [in Russian].

    Google Scholar 

  2. V. P. Dymnikov, Stability and Predictability of Large-scale Atmospheric Processes (IVM RAN, Moscow, 2007) [in Russian].

    Google Scholar 

  3. D. B. Kiktev, E. N. Kruglova, and I. A. Kulikova, “On the Evaluation of the Extremality Index EFI,” Meteorol. Gidrol., No. 1 (2020) [Russ. Meteorol. Hydrol., No. 1, 45 (2020)].

    Article  Google Scholar 

  4. D. B. Kiktev, I. V. Trosnikov, M. A. Tolstykh, and R. B. Zaripov, “Verification of Forecasts of Seasonal Anomalies of Meteorological Fields for SL-AV Model in the SMIP-2 Experiment,” Meteorol. Gidrol., No. 6 (2006) [Russ. Meteorol. Hydrol., No. 6 (2006)].

  5. A. V. Murav’ev and R. M. Vilfand, “Standardization of Skill Scores for Medium- and Long-term Weather Forecasts,” Meteorol. Gidrol., No. 12 (2000) [Russ. Meteorol. Hydrol., No. 12 (2000)].

  6. A. V. Murav’ev, D. B. Kiktev, A. Yu. Bundel’, T. G. Dmitrieva, and A. V. Smirnov, “Verification of High-impact Weather Event Forecasts for the Region of the Sochi-2014 Olympic Games. Part I: Deterministic Forecasts during the Test Period,” Meteorol. Gidrol., No. 9 (2015) [Russ. Meteorol. Hydrol., No. 9, 40 (2015)].

    Article  Google Scholar 

  7. V. A. Tishchenko, V. M. Khan, R. M. Vil’fand, and E. Roget, “Studying the Development of Atmospheric Processes Associated with Blocking and Quasistationary Anticyclones in the Atlantic European Sector,” Meteorol. Gidrol., No. 7 (2013) [Russ. Meteorol. Hydrol., No. 7, 38 (2013)].

    Article  Google Scholar 

  8. M. A. Tolstykh, D. B. Kiktev, R. B. Zaripov, M. Yu. Zaichenko, and V. V. Shashkin, “Simulation of the Seasonal Atmospheric Circulation with the New Version of the Semi-Lagrangian Atmospheric Model,” Izv. Akad. Nauk, Fiz. Atmos. Okeana, No. 2, 46 (2010) [Izv., Atmos. Oceanic Phys., No. 2, 46 (2010)].

    Article  Google Scholar 

  9. M. A. Tolstykh, R. Yu. Fadeev, V. V. Shashkin, G. S. Goyman, R. B. Zaripov, D. B. Kiktev, S. V. Makhnorylova, V. G. Mizyak, and V. S. Rogutov, “Multiscale Global Atmosphere Model SL-AV: The Results of Medium-range Weather Forecasts,” Meteorol. Gidrol., No. 11 (2018) [Russ. Meteorol. Hydrol., No. 11, 43 (2018)].

    Article  Google Scholar 

  10. A. N. Filatov, “Long-range Weather Forecasting and Stability and Predictability of Atmospheric Processes,” in Sixty Years to the Center of Hydrometeorological Forecasts (Gidrometeoizdat, Leningrad, 1989) [in Russian].

  11. N. P. Shakina, A. R. Ivanova, B. A. Birman, and E. N. Skriptunova, “Blocking: 2010 Summer Conditions in the Context of Modern Knowledge,” in Analysis of Abnormal Weather Conditions on the Territory of Russia in the Summer of 2010. Collected Papers (Triada, Moscow, 2011) [in Russian].

  12. T. Aikawa, M. Inatsu, N. Nakano, and T. Iwano, “Mode-decomposed Equation Diagnosis for Atmospheric Blocking Development,” J. Atmos. Sci., 76 (2019).

    Article  Google Scholar 

  13. D. Barriopedro, E. M. Fischer, J. Luterbacher, R. M. Trigo, and R. Garcia-Herrera, “The Hot Summer of 2010: Redrawing the Temperature Record Map of Europe,” Science, 332 (2011).

    Article  Google Scholar 

  14. R. Berggren, B. Bolin, and C. G. Rossby, “An Aerological Study of Zonal Motion, Its Perturbation and Break-down,” Tellus, 1 (1949).

    Article  Google Scholar 

  15. E. M. Black, G. Blackburn, B. Harrison, B. Hoskins, and J. Methven, “Factors Contributing to the Summer 2003 European Heatwave,” Weather, 59 (2006).

    Article  Google Scholar 

  16. E. E. Ebert, “Neighborhood Verification: A Strategy for Rewarding Close Forecasts,” Wea. Forecast., 24 (2009).

    Article  Google Scholar 

  17. C. A. T. Ferro and D. B. Stephenson, “Extremal Dependence Indices: Improved Verification Measures for Extreme Events and Warnings,” Wea. Forecast., 26 (2012).

    Article  Google Scholar 

  18. Forecast Verification in Atmospheric Science. A Practitioner’s Guide, 2nd ed., Ed. by I. Jolliffe and D. Stephenson (John Wiley & Sons Ltd, 2012).

    Google Scholar 

  19. E. Gilleland, D. A. Ahijevych, B. G. Brown, B. Casati, and E. Ebert, “Intercomparison of Spatial Forecast Verification Methods,” Wea. Forecast., 34 (2009).

    Article  Google Scholar 

  20. E. Gilleland, D. A. Ahijevych, B. G. Brown, and E. E. Ebert, “Verifying Forecasts Spatially,” Bull. Amer. Meteorol. Soc., 91 (2010).

  21. HIWeather: A 10-year Research Project, WMO Bulletin, Vol. 66 (2) (2017), www.wmo.int/pages/prog/arep/wwrp/new/documents/.

  22. A. Hollingsworth, K. Arpe, M. Tiedtke, M. Capaldo, and H. Savijarvi, “The Performance of a Medium-range Forecast Model in Winter—Impact of Physical Parameterization,” Mon. Wea. Rev., 108 (1980).

    Article  Google Scholar 

  23. Z. Jiang and D. Luo, “Study of the Optimal Precursors for Blocking Events,” Adv. Atmos. Sci., No. 3, 22 (2005).

    Article  Google Scholar 

  24. Z. Jiang and D. Wang, “A Study of Precursors to Blocking Anomalies in Climatological Flows by Using Conditional Nonlinear Optimal Perturbations,” Quart. J. Roy. Meteorol. Soc. A, 136 (2010).

  25. M. Kimoto, H. Mukougawa, and S. Yoden, “Medium-range Forecast Skill Variation and Blocking Transition: A Case Study,” Mon. Wea. Rev., No. 8, 120 (1992).

    Article  Google Scholar 

  26. H. Lejenas and H. Okland, “Characteristics of Northern Hemisphere Blocking as Determined from a Long Time Series of Observational Data,” Tellus A, 35 (1983).

  27. E. N. Lorenz, “A Study of the Predictability of a 28-variable Atmospheric Model,” Tellus, 17 (1965).

    Article  Google Scholar 

  28. E. N. Lorenz, “The Physical Bases of Climate and Climate Modelling,” in Climate Predictability, GARP Publication Series 16 (World Meteorological Association, Geneva, 1975).

  29. D. Luo, J. Li, and F. Huang, “Life Cycles of Blocking Flows Associated with Synoptic-scale Eddies: Observed Results and Numerical Experiments,” Adv. Atmos. Sci., No. 4, 19 (2002).

    Article  Google Scholar 

  30. D. Luo, J. Liu, and J. Li, “Interaction between Planetary-scale Diffluent Flow and Synoptic-scale Waves during the Life Cycle of Blocking,” Adv. Atmos. Sci., No. 4, 27 (2010).

    Article  Google Scholar 

  31. A. R. Lupo and P. J. Smith, “The Interaction between a Midlatitude Blocking Anticyclone and Synoptic-scale Cyclones That Occurred during the Summer Season,” Mon. Wea. Rev., No. 2, 126 (1998).

    Article  Google Scholar 

  32. M. Matsueda, “Predictability of Euro-Russian Blocking in Summer of 2010,” Geophys. Res. Lett., No. 6, 38 (2011).

  33. K. Miakoda, G. D. Hembree, R. F. Strikler, and I. Shulman, “Cumulative Results of Extended Forecast Experiments. I: Model Performance for Winter Cases,” Mon. Wea. Rev., 100 (1972).

    Article  Google Scholar 

  34. F. Molteni and T. N. Palmer, “Predictability and Finite-time Instability of the Northern Winter Circulation,” Quart. J. Roy. Meteorol. Soc., 119 (1993).

  35. M. Mu and Z. N. Jiang, “A Method to Find Perturbations That Trigger Blocking Onset: Conditional Nonlinear Optimal Perturbations,” J. Atmos. Sci., 65 (2008).

    Article  Google Scholar 

  36. P. J. Neiman, P. O. Persson, F. M. Ralph, D. P. Jorgensen, A. B. White, and D. E. Kingsmill, “Modification of Fronts and Precipitation by Coastal Blocking during an Intense Landfalling Winter Storm in Southern California: Observations during CALJET,” Mon. Wea. Rev., 132 (2004).

    Article  Google Scholar 

  37. J. L. Pelly and B. J. Hoskins, “A New Perspective on Blocking,” J. Atmos. Sci., No. 3, 60 (2003).

    Article  Google Scholar 

  38. L.-A. Quandt, J. H. Keller, O. Martius, J. Pinto, and S. C. Jones, “Ensemble Sensitivity Analysis of the Blocking System over Russia in Summer 2010,” Mon. Wea. Rev., No. 2, 147 (2019).

    Article  Google Scholar 

  39. L.-A. Quandt, J. H. Keller, O. Martius, and S. C. Jones, “Forecast Variability of the Blocking System over Russia in Summer 2010 and Its Impact on Surface Conditions,” Wea. Forecast., 32 (2017).

    Article  Google Scholar 

  40. N. M. Roberts and H. W. Lean, “Scale-selective Verification of Rainfall Accumulations from High-resolution Forecasts of Convective Events,” Mon. Wea. Rev., 136 (2008).

  41. P. J. Roebber, “Visualizing Multiple Measures of Forecast Quality,” Wea. Forecast., 24 (2009).

    Article  Google Scholar 

  42. S. Saha and H. M. van den Dool, “A Measure of Practical Limit of Predictability,” Mon. Wea. Rev., 116 (1988).

  43. G. J. Shutts, “The Propagation of Eddies in Diffluent Jet Streams: Eddy Vorticity Forcing of Blocking Flow Fields,” Quart. J. Roy. Meteorol. Soc., 109 (1983).

    Google Scholar 

  44. Standardized Verification System (SVS) for Long-Range Forecasts (LRF). New Attachment II-9 to the Manual on the GDPS (WMO-No. 485), Vol. I (WMO, Geneva, 2002).

  45. H. Tennekes, “Karl Popper and the Accountability of Numerical Forecasting,” in ECMWF Workshop Proceedings. New Developments in Predictability (European Centre for Medium-Range Weather Forecasts, London, 1991).

  46. S. Tibaldi and F. Molteni, “On the Operational Predictability of Blocking,” Tellus A, 42 (1990).

    Article  Google Scholar 

  47. Z. Toth and E. Kalnay, “Ensemble Forecasting at NCEP and the Breeding Method,” Mon. Wea. Rev., 125 (1997).

    Article  Google Scholar 

  48. D. S. Wilks, Statistical Methods in the Atmospheric Sciences, 3rd ed. (Academic, London, 2011).

    Google Scholar 

  49. W. Youna and H. Tang, “PNA Predictability at Various Time Scale,” J. Climate, 26 (2013).

    Article  Google Scholar 

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Authors and Affiliations

  1. Hydrometeorological Research Center of the Russian Federation, 123242, Moscow, Russia

    I. A. Kulikova, E. N. Kruglova & V. M. Khan

  2. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017, Moscow, Russia

    V. M. Khan

Authors
  1. I. A. Kulikova
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  2. E. N. Kruglova
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  3. V. M. Khan
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Correspondence to I. A. Kulikova.

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Kulikova, I.A., Kruglova, E.N. & Khan, V.M. Evaluation of Practical Predictability of Blocking Anticyclones Using Modern Hydrodynamic Models. Russ. Meteorol. Hydrol. 47, 1–13 (2022). https://doi.org/10.3103/S1068373922010010

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Keywords

  • long-range meteoroloical forecasts
  • extreme events
  • blocking systems
  • practical predictability
  • forecast skill scores