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Part II - High-impact weather in mid latitudes

Published online by Cambridge University Press:  05 March 2016

Edited by
Jianping Li ,
Richard Swinbank ,
Richard Grotjahn  and
Hans Volkert
Jianping Li
Affiliation:
Beijing Normal University
Richard Swinbank
Affiliation:
Met Office, Exeter
Richard Grotjahn
Affiliation:
University of California, Davis
Hans Volkert
Affiliation:
Deutsche Zentrum für Luft- und Raumfahrt eV (DLR)
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Dynamics and Predictability of Large-Scale, High-Impact Weather and Climate Events , pp. 67 - 130
Publisher: Cambridge University Press
Print publication year: 2016

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References

References

Altenhoff, A., Martius, O., and Croci-Maspoli, M. (2008). Linkage of atmospheric blocks and synoptic-scale Rossby waves: A climatological analysis. Tellus 60, 1053–1063.CrossRefGoogle Scholar
Appenzeller, C. and Davies, H. C. (1992). Structure of stratospheric intrusions into the troposphere. Nature 358, 570–572.CrossRefGoogle Scholar
Barnes, E. A. and Hartmann, D. L. (2012). Detection of Rossby wave breaking and its response to shifts of the midlatitude jet with climate change. J. Geophys. Res. 117, D09117, doi:10.1029/2012JD017469.CrossRefGoogle Scholar
Benedict, J. J., Lee, S., and Feldstein, S. B. (2004). Synoptic view of the North Atlantic Oscillation. J. Atmos. Sci. 61, 121–144.2.0.CO;2>CrossRefGoogle Scholar
Berrisford, P., Hoskins, B. J., and Tyrlis, E. (2007). Blocking and Rossby wave breaking on the dynamical tropopause in the Southern Hemisphere. J. Atmos. Sci. 64, 2881–2898.CrossRefGoogle Scholar
Cai, M. (2003). Potential vorticity intrusion index and climate variability of surface temperature. Geophys. Res. Lett. 30, doi:10.1029/2002GL015926.CrossRefGoogle Scholar
Cassou, C. (2008). Intraseasonal interaction between the MaddenJulian Oscillation and the North Atlantic Oscillation. Nature 455, doi:10.1038/nature07286.CrossRefGoogle ScholarPubMed
Davies, H. C. (1999). Theories of frontogenesis, pp. 215–238. In The Life Cycles of Extratropical Cyclones. Shapiro, M. A. and Groenas, S. (eds.). American Meteorological Society.CrossRefGoogle Scholar
Davies, H. C., Schaer, C., and Wernli, H. (1991). The palette of fronts and cyclones within a baroclinic wave development. J. Atmos. Sci. 48, 1666–1689.2.0.CO;2>CrossRefGoogle Scholar
Davis, C. A. and Bosart, L. F. (2006). The formation of hurricane Humberto (2001): The importance of extra-tropical precursors. Quart. J. Roy. Meteor. Soc. 132, 2055–2085.CrossRefGoogle Scholar
Dee, D. P., Uppala, S. M., Simmons, A. J., et al. (2011). The Era-interim reanalysis: configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc. 137, 553–597.CrossRefGoogle Scholar
Doswell, C. A., Ramis, C., Romero, R., and Alonso, S. (1998). A diagnostic study of three heavy precipitation episodes in the western mediterranean region. Weather Forecast 13, 102–124.2.0.CO;2>CrossRefGoogle Scholar
Engel, C. B., Lane, T. P., Reeder, M. J., and Rezny, M. (2013). The meteorology of black saturday. Quart. J. Roy. Meteor. Soc. 139, 585–599.CrossRefGoogle Scholar
Enomoto, T., Ohfuchi, W., Nakamura, H., and Shapiro, M. A. (2007). Remote effects of tropical storm Cristobal upon a cut-off cyclone over Europe in August 2002. Met. Atmos. Phys. 96, 29 – 42.CrossRefGoogle Scholar
Fita, L., Romero, R., and Ramis, C. (2007). Objective quantification of perturbations produced with a piecewise pv inversion technique. Ann. Geophys. 25, 2335–2349.CrossRefGoogle Scholar
Franzke, C., Lee, S., and Feldstein, S. B. (2004). Is the North Atlantic Oscillation a breaking wave? J. Atmos. Sci. 61, 145–160.2.0.CO;2>CrossRefGoogle Scholar
Funatsu, B. M. and Waugh, D.W. (2008). Connections between potential vorticity intrusions and convection in the eastern tropical Pacific. J. Atmos. Sci. 65, 987–1002.CrossRefGoogle Scholar
Gerber, E. P. and Vallis, G. K. (2009). On the zonal structure of the North Atlantic Oscillation and annular modes. J. Atmos. Sci. 66, 332–352.CrossRefGoogle Scholar
Grams, C. M., Wernli, H., Boettcher, M., et al. (2011). The key role of diabatic processes in modifying the upper-tropospheric wave guide: a North Atlantic case-study. Quart. J. Roy. Meteor. Soc. 137, 2174–2193.CrossRefGoogle Scholar
Hanley, J. and Caballero, R. (2012). The role of large-scale atmospheric flow and Rossby wave breaking in the evolution of extreme windstorms over Europe. Geophys. Res. Lett. 39, L21708, doi:10.1029/2012GL053408.CrossRefGoogle Scholar
Hitchman, M. H. and Huesmann, A. S. (2007). A seasonal climatology of Rossby wave breaking in the 320-2000-K layer. J. Atmos. Sci. 64, 1922–1940.CrossRefGoogle Scholar
Hoskins, B. J., James, I. N., and White, G. H. (1983). The shape, propagation and mean-flow interaction of large-scale weather systems. J. Atmos. Sci. 40, 1595–1612.2.0.CO;2>CrossRefGoogle Scholar
Hoskins, B. J., McIntyre, M. E., and Robertson, A. W. (1985). On the use and significance of isentropic potential vorticity maps. Quart. J. Roy. Meteor. Soc. 111, 877–946.CrossRefGoogle Scholar
Isotta, F., Martius, O., Sprenger, M., and Schwierz, C. (2008). Long-term trends of synoptic-scale breaking Rossby waves in the northern hemisphere between 1958 and 2001. Int. J. Clim. 28, 1551–1562.CrossRefGoogle Scholar
Kiladis, G. N. and Weickmann, K. M. (1992). Circulation anomalies associated with tropical convection during northern winter. Mon. Wea. Rev. 120, 1900–1923.2.0.CO;2>CrossRefGoogle Scholar
Knippertz, P. (2005). Tropical-extratropical interactions associated with an Atlantic tropical plume and subtropical jet streak. Mon. Wea. Rev. 133, 2759–2776.CrossRefGoogle Scholar
Knippertz, P. (2007). Tropical-extratropical interactions related to upper-level troughs at low latitudes. Dynam. Atmos. Oceans 43, 36–62.CrossRefGoogle Scholar
Leroux, M. D., Plu, M., Barbary, D., Roux, F., and Arbogast, P. (2013). Dynamical and physical processes leading to tropical cyclone intensification under upper-level trough forcing. J. Atmos. Sci. 70, 2547–2565.CrossRefGoogle Scholar
Martius, O., Schwierz, C., and Davies, H. C. (2007). Breaking waves at the Tropopause in the wintertime Northern Hemisphere: Climatological analyses of the orientation and the theoretical LC1/2 classification. J. Atmos. Sci. 64, 2576–2592.CrossRefGoogle Scholar
Martius, O., Sodemann, H., Joos, H., et al. (2013). The role of upper-level dynamics and surface processes for the Pakistan flood of July 2010. Quart. J. Roy. Meteor. Soc. 139, 1780–1797.CrossRefGoogle Scholar
Masato, G., Hoskins, B., and Woollings, T. (2012). Wave-breaking characteristics of mid-latitude blocking. Quart. J. Roy. Meteor. Soc. 138, 1285–1296. doi: 10.1002/qj.990CrossRefGoogle Scholar
Massacand, A., Wernli, H., and Davies, H. (1998). Heavy precipitation on the Alpine southside: An upper-level precursor. Geophys. Res. Lett. 25, 1435–1438.CrossRefGoogle Scholar
Matthews, A. J. and Kiladis, G. N. (1999). Interaction between ENSO, transient circulation, and tropical convection over the Pacific. J. Clim. 12, 3062–3086.2.0.CO;2>CrossRefGoogle Scholar
McIntyre, M. E. and Palmer, T. N. (1984). The 'surf zone’ in the stratosphere. Atmos. Terr. Phys. 46, 825–849.CrossRefGoogle Scholar
McTaggart-Cowan, R., Deane, G. D., Bosart, L. F., Davis, C. A., and Galarneau, T. J. (2008). Climatology of tropical cyclogenesis in the North Atlantic (1948-2004). Mon. Wea. Rev. 136, 1284–1304.CrossRefGoogle Scholar
McTaggart-Cowan, R., Galarneau, T. J., Bosart, L. F., Moore, R. W., and Martius, O. (2013). A global climatology of baroclinically influenced tropical cyclogenesis. Mon. Wea. Rev. 141, 1963–1989.CrossRefGoogle Scholar
Michel, C. and Riviere, G. (2011). The link between Rossby wave breakings and weather regime transitions. J. Atmos. Sci. 68, 1730–1748.CrossRefGoogle Scholar
Michel, C., Riviere, G., Terray, L., and Joly, B. (2012). The dynamical link between surface cyclones, upper-tropospheric Rossby wave breaking and the life cycle of the Scandinavian blocking. Geophys. Res. Lett. 39, L10806.CrossRefGoogle Scholar
Moore, R. W., Martius, O., and Davies, H. C. (2008). Downstream development and Kona low genesis. Geophys. Res. Lett. L20814.CrossRefGoogle Scholar
Moore, R. W., Martius, O., and Spengler, T. (2010). The modulation of the subtropical and extratropical atmosphere in the pacific basin in response to the Madden-Julian Oscillation. Mon. Wea. Rev. 138, 2761–2779.CrossRefGoogle Scholar
Nakamura, H., Nakamura, M., and Andreason, J. L. (1997). The role of high- and low-frequency dynamics in blocking formation. Mon. Wea. Rev., 125, 2074–2093, DOI: 10.1175/1520-04932.0.CO;2>CrossRefGoogle Scholar
Nakamuara, H. and Fukamachi, T. (2004). Evolution and dynamics of summertime blocking over the Far East and the associated surface Okhotsk high. Quart. J. Roy. Meteor. Soc. 130, 1213–1233.CrossRefGoogle Scholar
Ndarana, T. and Waugh, D. (2011). A climatology of Rossby wave breaking on the Southern Hemisphere tropopause. J. Atmos. Sci. 68, 798–811.CrossRefGoogle Scholar
Nuissier, O., Ducrocq, V., Ricard, D., Lebeaupin, C., and Anquetin, S. (2008). A numerical study of three catastrophic precipitating events over southern France. I: Numerical framework and synoptic ingredients. Quart. J. Roy. Meteor. Soc. 134, 111–130.CrossRefGoogle Scholar
Pelly, J. L. and Hoskins, B. J. (2003). A new perspective on blocking. J. Atmos. Sci. 60, 743–755.2.0.CO;2>CrossRefGoogle Scholar
Porcu, F., Carrassi, A., Medaglia, C. M., Prodi, F., and Mugnai, A. (2007). A study on cut-off low vertical structure and precipitation in the Mediterranean region. Meteorol. Atmos. Phys. 96, 121–140.CrossRefGoogle Scholar
Postel, G. A. and Hitchman, M. H. (1999). A climatology of Rossby wave breaking along the subtropical tropopause. J. Atmos. Sci. 56, 359–373.2.0.CO;2>CrossRefGoogle Scholar
Rivière, G. (2009). Effect of latitudinal variations in low-level baroclinicity on eddy life cycles and upper-tropospheric wave-breaking processes. J. Atmos. Sci., 66, 1569–1592. doi: http://dx.doi.org/10.1175/2008JAS2919.1CrossRefGoogle Scholar
Rivière, G. (2011). A dynamical interpretation of the poleward shift of the jet streams in global warming scenarios. J. Atmos. Sci. 68, 1253–1266.CrossRefGoogle Scholar
Rivière, G., Laine, A., Lapeyre, G., Salas-Melia, D., and Kageyama, M. (2010). Links between Rossby wave breaking and the North Atlantic Oscillation-Arctic Oscillation in present-day and last glacial maximum climate simulations. J. Clim. 23, 2987–3008.CrossRefGoogle Scholar
Rivière, G. and Orlanski, I. (2007). Characteristics of the Atlantic storm-track eddy activity and its relation with the North Atlantic Oscillation. J. Atmos. Sci. 64, 241–266.CrossRefGoogle Scholar
Schlemmer, L., Martius, O., Sprenger, M., Schwierz, C., and Twitchett, A. (2010). Disentangling the forcing mechanisms of a heavy precipitation event along the alpine south side using potential vorticity. Mon. Wea. Rev. 138, 2336–2353.CrossRefGoogle Scholar
Shapiro, M. A., Wernli, H., Bond, N. A., and Langland, R. (2001). The influence of the 1997–99 El Nino Southern Oscillation on extratropical baroclinic life cycles over the eastern North Pacific. Quart. J. Roy. Meteor. Soc. 127, 331–342.Google Scholar
Slingo, J. M. (1998). Extratropical forcing of tropical convection in a northern winter simulation with the UGAMP GCM. Quart. J. Roy. Meteor. Soc. 124, 27–51.CrossRefGoogle Scholar
Sprenger, M., Martius, O., and Arnold, J. (2013). Cold surge episodes over southeastern brazil – a potential vorticity perspective. Int. J. Climatol. 33, 2758–2767.CrossRefGoogle Scholar
Takaya, K. and Nakamura, H. (2005). Mechanisms of intraseasonal amplification of the cold Siberian high. J. Atmos. Sci., 62, 4423–4440.doi: http://dx.doi.org/10.1175/JAS3629.1CrossRefGoogle Scholar
Thorncroft, C. D., Hoskins, B. J., and McIntyre, M. F. (1993). Two paradigms of baroclinic-wave life-cycle behavior. Quart. J. Roy. Meteor. Soc. 119, 17–55.Google Scholar
Ulbrich, U., Bruecher, T., Fink, A., et al. (2003). The central European floods of August 2002: Part 2 Synoptic causes and considerations with respect to climatic change. Weather 58, 434–442.CrossRefGoogle Scholar
Waugh, D. W. and Polvani, L. M. (2000). Climatology of intrusions into the tropical upper troposphere. Geophys. Res. Lett. 27, 3857–3860.CrossRefGoogle Scholar
Wernli, H. and Sprenger, M. (2007). Identification and ERA-15 climatology of potential vorticity streamers and cutoffs near the extratropical tropopause. J. Atmos. Sci. 64, 1569–1586.CrossRefGoogle Scholar
Woollings, T., Hoskins, B., Blackburn, M., and Berrisford, P. (2008). A new Rossby wave-breaking interpretation of the North Atlantic Oscillation. J. Atmos. Sci. 65, 609–626.CrossRefGoogle Scholar

References

Ashcroft, L. C., Pezza, A. B., and Simmonds, I. (2009). Cold events over Southern Australia: Synoptic climatology and hemispheric structure, J. Clim, 22, 6679–6698.CrossRefGoogle Scholar
Barnes, E. A. and Hartmann, D. L. (2011). Rossby wave scales, propagation and the variability of eddy-driven jets, J. Atmos. Sci., 68, 2893–2908.CrossRefGoogle Scholar
Barnes, E. A. and Hartmann, D. L. (2012). Detection of Rossby wave breaking and its response to shifts of the midlatitude jet with climate change, J. Geophys. Res. D09117, doi: 10.1029/2012JD017469CrossRefGoogle Scholar
Dee, D. P. et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc., 137, 553–597.CrossRefGoogle Scholar
Dima, I. M., Wallace, J. M., and Kraucunas, I. (2005). Tropical zonal momentum balance in the NCEP reanalyses, J. Atmos. Sci., 62, 2499–2513.CrossRefGoogle Scholar
Eichelberger, S. J. and Hartmann, D. L. (2007). Zonal jet structure and the leading mode of variability, J. Clim., 20, 5149–5163.CrossRefGoogle Scholar
Franzke, C. (2013). Persistent regimes and extreme events of the North Atlantic atmospheric circulation, Phil. Trans. R. Soc. A, 371, 20110471.CrossRefGoogle ScholarPubMed
Garfinkel, C. I. and Waugh, D. W. (2014). Tropospheric Rossby wave breaking and variability of the latitude of the eddy-driven jets*, J. Climate, 27, 7069–7085.CrossRefGoogle Scholar
Garfinkel, C. I., Waugh, D. W., and Gerber, E. P. (2013). The effect of tropospheric jet latitude on coupling between the stratospheric polar vortex and the troposphere, Journal of Climate, 26, 2077–2097.CrossRefGoogle Scholar
Garfinkel, C. I. and Harnik, N. (2015). The non-Gaussianity and spatial asymmetry of temperature extremes relative to the jet: the role of horizontal advection. To be submitted.Google Scholar
Harnik, N. (2014). Extreme upper level cyclonic vorticity events in relation to the southern hemisphere jet stream. Geophys. Res. Lett., 41, 4373–4380.CrossRefGoogle Scholar
Harnik, N., Galanti, E., Martius, O., and Adam, O. (2014). The Anomalous Merging of the African and North Atlantic Jet Streams during Northern Hemisphere Winter of 2010. J. Climate, 27, 7319–7334.CrossRefGoogle Scholar
Held, I. M. (1975). Momentum transport by quasi-geostrophic eddies. J. Atmos. Sci., 32, 1494–1497.2.0.CO;2>CrossRefGoogle Scholar
Held, I. M. (2000). The general circulation of the atmosphere. Introduction to general circulation theories. Proc. Prog. Geophys. Fluid Dyn. Woods Hole Oceanogr. Inst., http://gfd.whoi.edu/proceedings/2000/PDFvol2000.html.Google Scholar
Held, I. M. and Hou, A. Y. (1980). Nonlinear axially symmetric circulations in a nearly inviscid atmosphere, J. Atmos. Sci., 37(3), 515–533.2.0.CO;2>CrossRefGoogle Scholar
Held, I. M. and Suarez, M. J. (1994). A proposal for the intercomparison of the dynamical cores of atmospheric general-circulation models, B. Am. Meteorol. Soc., 75, 1825–1830.2.0.CO;2>CrossRefGoogle Scholar
Kalnay, E. et al. (1996). The NCEP/NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77 434–471.2.0.CO;2>CrossRefGoogle Scholar
Lachmy, O. and Harnik, N. (2014). The transition to a subtropical jet regime and its maintenance, J. Atmos. Sci., 71, 1389–1409.CrossRefGoogle Scholar
Lee, S. and Kim, H. K. (2003). The dynamical relationship between subtropical and eddy-driven jets, J. Atmos. Sci., 60, 1490–1503.2.0.CO;2>CrossRefGoogle Scholar
Mahlstein, I., Martius, O., Chevalier, C., and Ginsbourger, D. (2012). Changes in the odds of extreme events in the Atlantic basin depending on the position of the extratropical jet, Geophys. Res. Lett., 39, L22805.CrossRefGoogle Scholar
Marengo, J. A., Ambrizzi, T., Kiladis, G., and Liebmann, B. (2002). Upper-air wave trains over the Pacific Ocean and wintertime cold surges in tropical-subtropical South America leading to freezes in southern and southeastern Brazil, Theor. Appl. Clim., 73, 223–242.CrossRefGoogle Scholar
Martius, O., Zenklusen, E., Schwierz, C., and Davies, H. C. (2006). Episodes of alpine heavy precipitation with an overlying elongated stratospheric intrusion: A climatology, Int. J. Climatol., 26, 1149–1164.CrossRefGoogle Scholar
Michel, C. and Riviere, G. (2014). Sensitivity of the position and variability of the eddy-driven jet to different SST profiles in an aquaplanet general circulation model, J. Atmos. Sci., 71, 349–371.CrossRefGoogle Scholar
Nakamura, H., Sampe, T., Tanimoto, Y., and Shimpo, A. (2004). Observed associations among storm tracks, jet streams and midlatitude oceanic fronts, Geophysical Monograph Series, 147, 329–345.Google Scholar
Panetta, R. L. (1993). Zonal jets in wide baroclinically unstable regions: Persistence and scale selection, J. Atmos. Sci., 50, 2073–2106.2.0.CO;2>CrossRefGoogle Scholar
Petoukhov, V., Rahmstorf, S., Petri, S., and Schellnhuber, H. J. (2013). Quasi resonant amplification of planetary waves and recent northern hemisphere weather extremes, Proc. Natl. Acad. Sci. U.S.A., 110, 5336–5341.CrossRefGoogle Scholar
Randel, W. J. and Held, I. M. (1991). Phase speed spectra of transient eddy fluxes and critical layer absorption, J. Atmos. Sci., 48, 688–697.2.0.CO;2>CrossRefGoogle Scholar
Randel, W. J. and Stanford, J. L. (1985). An observational study of medium scale wave dynamics in the southern hemisphere summer. Part I: Wave structure and energetics. J. Atmos. Sci., 42, 1172–1188.2.0.CO;2>CrossRefGoogle Scholar
Rhines, P. B. (1975). Waves and turbulence on a beta-plane, J. Fluid Mech., 69, 417–443.CrossRefGoogle Scholar
Romero, R., Sumner, G., Ramis, C., and Genoves, A. (1999). A classification of the atmospheric circulation patterns producing significant daily rainfall in the Spanish Mediterranean area. Int. J. Climatol., 19, 765–785.3.0.CO;2-T>CrossRefGoogle Scholar
Schlemmer, L., Martius, O., Sprenger, M., Schwierz, C., and Twitchett, A. (2010). Disentangling the forcing mechanisms of a heavy precipitation event along the alpine south side using potential vorticity inversion. Mon. Wea. Rev., 138, 2336–2353, doi: 10.1175/2009MWR3202.1.CrossRefGoogle Scholar
Schneider, E. K. (1977). Axially symmetric steady-state models of the basic state for instability and climate studies. Part II. Nonlinear circulations, J. Atmos. Sci., 34, 280–296.2.0.CO;2>CrossRefGoogle Scholar
Schubert, S., Wang, H., and Suarez, M. (2011). Warm season subseasonal variability and climate extremes in the northern hemisphere: The role of stationary Rossby waves, J. Clim., 24, 4773–4792.CrossRefGoogle Scholar
Schubert, S. D., Wang, H., Koster, R., Suarez, M., and Groisman, P. Y. (2014). Northern Eurasian heat waves and droughts. J. Clim., 27, 3169–3207.CrossRefGoogle Scholar
Son, S. W. and Lee, S. (2005). The response of westerly jets to thermal driving in a primitive equation model, J. Atmos. Sci., 62, 3741–3757.CrossRefGoogle Scholar
Sprenger, M., Martius, O., and Arnold, J. (2012). Cold surge episodes over Southeastern Brazil – a potential vorticity perspective, Int. J. Climatol., 33, 2758–2767.CrossRefGoogle Scholar
Wallace, J. M., Held, I. M., Thompson, D. W. J., Trenberth, K. E., and Walsh, J. E. (2014). Global warming and winter weather, Science, 343.CrossRefGoogle ScholarPubMed
Woollings, T., Hannachi, A., Hoskins, B., and Turner, A. (2010). A regime view of the North Atlantic oscillation and its response to anthropogenic forcing, J. Clim., 23(6), 1291–1307.CrossRefGoogle Scholar

References

Anderson, J. L. (1996). A method for producing and evaluating probabilistic forecasts from ensemble model integrations. J. Climate, 9, 1518–1530.2.0.CO;2>CrossRefGoogle Scholar
Baldauf, M., Seifert, A., Förstner, J., et al. (2011). Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities. Mon. Wea. Rev., 139, 3887–3905.CrossRefGoogle Scholar
Ben Bouallègue, Z., Theis, S. E., and Gebhardt, C. (2013). Enhancing COSMO-DE ensemble forecasts by inexpensive techniques. Meteor. Z., 22, 49–59..CrossRefGoogle Scholar
Bentzien, S. and Friederichs, P. ( 2012 ). Generating and calibrating probabilistic quantitative precipitation forecasts from the high-resolution NWP model COSMO-DE. Wea. Forecasting, 27, 988–1002.CrossRefGoogle Scholar
Bentzien, S. and Friederichs, P. (2014). Decomposition and graphical portrayal of the quantile score. Quart. J. Roy. Meteor. Soc., 40, 1924–1934.CrossRefGoogle Scholar
Bouttier, F., Vie, B., Nussier, O., and Raynaud, L. (2012). Impact of stochastic physics in a convection-permitting ensemble. Mon. Wea. Rev., 140, 3706–3721.CrossRefGoogle Scholar
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,CrossRefGoogle Scholar
Bremnes, J. B. (2004). Probabilistic forecasts of precipitation in terms of quantiles using NWP model output. Mon. Wea. Rev., 132, 338–347.2.0.CO;2>CrossRefGoogle Scholar
Brier, G. W. (1950). Verification of forecasts expressed in terms of probability. Mon. Wea. Rev., 78, 1–3.2.0.CO;2>CrossRefGoogle Scholar
Broecker, J. (2012). Probability forecasts. In Forecast Verification: A Practitioner’s Guide in Atmospheric Science, eds. Jolliffe, I. T. and Stephenson, D. B., 2nd edn., Wiley.Google Scholar
Buizza, R., Miller, M., and Palmer, T. N. (1999). Stochastic representation of model uncertainties in the ECMWF ensemble prediction system. Quart. J. R. Meteorol. Soc., 125, 2887–2908.CrossRefGoogle Scholar
Candille, G. and Talagrand, O. (2005). Evaluation of probabilistic prediction systems for a scalar variable, Quart. J. Roy. Meteor. Soc., 131, 2131–2150.CrossRefGoogle Scholar
Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer.CrossRefGoogle Scholar
Cooley, D., Nychka, D., and Naveau, P. (2007). Bayesian spatial modeling of extreme precipitation return levels. J. Amer. Stat. Assoc., 102, 824–840.CrossRefGoogle Scholar
Cooley, D. and Sain, S. R. (2010). Spatial hierarchical modeling of precipitation extremes from a regional climate model. Journal of Agricultural, Biological, and Environmental Statistics, 15, 381–402.CrossRefGoogle Scholar
Di Narzo, A. F. and Cocchi, D. (2010). A Bayesian hierarchical approach to ensemble weather forecasting. J. Roy. Stat. Soc. Ser. C, 59, 405–422.CrossRefGoogle Scholar
Efron, B. and Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC.CrossRefGoogle Scholar
Evensen, G. (1994). Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99(C5), 10143–10162.CrossRefGoogle Scholar
Fahrmeir, L. and Tutz, G. (1994). Multivariate Statistical Modelling Based on Generalized Linear Models. Springer.CrossRefGoogle Scholar
Ferro, C. A. T. (2013). Fair scores for ensemble forecasts. Quart. J. Roy. Meteor. Soc., doi: 10.1002/qj.2270, 2013CrossRefGoogle Scholar
Fricker, T.E., Ferro, C. A. T., and Stephenson, D. B. (2013). Three recommendations for evaluating climate predictions, Meteorol. Appl., 20, 246–255.Google Scholar
Friederichs, P. and Hense, A. (2007). Statistical downscaling of extreme precipitation events using censored quantile regression. Mon. Wea. Rev., 135, 2365–2378.CrossRefGoogle Scholar
Friederichs, P. (2010). Statistical downscaling of extreme precipitation using extreme value theory. Extremes, 13, 109–132.CrossRefGoogle Scholar
Frigessi, A., Haug, O., and Rue, H. (2003). A dynamic mixture model for unsupervised tail estimation without threshold selection. Extremes, 5, 219–236.CrossRefGoogle Scholar
Gebhardt, C., Theis, S. E., Paulat, M., and Ben Bouallègue, Z. (2011). Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variations of lateral boundaries. Atmospheric Research, 100, 168–177.CrossRefGoogle Scholar
Gneiting, T., Balabdaoui, F., and Raftery, A. E. (2007). Probabilistic forecasts, calibration and sharpness. Journal of the Royal Statistical Society. Series B (Methodological), 69, 243–268.CrossRefGoogle Scholar
Gneiting, T. and Katzfuss, M. (2014). Probabilistic forecasting. Annual Review of Statistics and its Application, 1, 125151.CrossRefGoogle Scholar
Gneiting, T. and Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. J. Amer. Stat. Assoc., 102, 359–378.CrossRefGoogle Scholar
Gneiting, T., Raftery, A. E., Westveld, A. H., and Goldman, T. (2005). Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS Estimation. Mon. Wea. Rev., 133, 1098–1118.CrossRefGoogle Scholar
Gneiting, T. and Ranjan, R. (2013). Combining predictive distributions. Electronic Journal of Statistics, 7, 1747–1782.CrossRefGoogle Scholar
Golding, B. W., Ballard, S. P., Mylne, K., et al. (2014). Forecasting capabilities for the London 2012 Olympics. Bull. Amer. Meteor. Soc., 95, 883–896.CrossRefGoogle Scholar
Hagedorn, R, Hamill, T. M., and Whitaker, J. S. (2008). Probabilistic forecast calibration using ECMWF and GFS ensemble forecasts. Part I: 2-meter temperature. Mon. Wea. Rev., 136, 2608–2619.CrossRefGoogle Scholar
Hamill, T. M. (2001). Interpretation of rank histograms for verifying ensemble forecasts. Mon. Wea. Rev., 129, 550–560.2.0.CO;2>CrossRefGoogle Scholar
Hamill, T. M., Hagedorn, R., and Whitaker, J. S. (2008). Probabilistic forecast calibration using ECMWF and GFS ensemble reforecasts. Part II: precipitation. Mon. Wea. Rev., 136, 2620–2632.CrossRefGoogle Scholar
Hamill, T. M. and Colucci, S. J. (1997). Verification of Eta-RSM short-range ensemble forecasts. Mon. Wea. Rev., 125, 1312–1327.2.0.CO;2>CrossRefGoogle Scholar
Hersbach, H. (2000). Decomposition of the continuous ranked probability score for ensemble prediction systems. Wea. Forecasting, 15, 559–570.2.0.CO;2>CrossRefGoogle Scholar
Houtekamer, P. L. and Mitchell, H. L. (2005). Ensemble Kalman filtering. Quart. J. Roy. Meteor. Soc., 131, 3269–3289.CrossRefGoogle Scholar
Jolliffe, I. T. and Stephenson, D. B. (eds.) (2010). Forecast Verification: A Practitioner’s Guide in Atmospheric Science. 2nd edn. Wiley.Google Scholar
Joslyn, S. and Savelli, S. (2010). Communicating forecast uncertainty: Public perception of weather forecast uncertainty. Meteor. Appl., 17, 180–195.CrossRefGoogle Scholar
Joslyn, S., Nadav-Greenberg, L., and Nichols, R. M. (2009). Probability of precipitation: Assessment and enhancement of end-user understanding. Bull. Amer. Meteor. Soc., 90, 185–193.CrossRefGoogle Scholar
Kalnay, E. (2003). Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press, Cambridge.Google Scholar
Koenker, R. (2005). Quantile regression. Econometric Society Monographs, 38, Cambridge University Press.Google Scholar
Koenker, R. and Machado, J. A. F. (1999). Goodness of fit and related inference processes for quantile regression. J. Amer. Stat. Assoc., 94, 1296–1310.CrossRefGoogle Scholar
Lean, H. W., Clark, P. A., Dixon, M., et al. (2008). Characteristics of high-resolution versions of the Met Office unified model for forecasting convection over the United Kingdom. Mon. Wea. Rev., 136, 3408–3424.CrossRefGoogle Scholar
Lorenz, E. N. (1969). The predictability of a flow which possesses many scales of motion. Tellus, 21, 289–307.CrossRefGoogle Scholar
Matheson, J. E. and Winkler, R. L. (1976). Scoring rules for continuous probability distributions. Management Science, 22, 1087–1096.CrossRefGoogle Scholar
Matsueda, M. and Nakazawa, T. (2014). Early warning products for severe weather events derived from operational medium-range ensemble forecasts. Meteor. Appl., doi: 10.1002/met.1444CrossRefGoogle Scholar
Molteni, F., Buizza, R., Palmer, T. N., and Petroliagis, T. (1996). The ECMWF ensemble prediction system: methodology and validation. Quart. J. Roy. Meteor. Soc., 122, 73–119.CrossRefGoogle Scholar
Murphy, A. H. (1973). A new vector partition of the probability score. Journal of Applied Meteorology, 12, 595–600.2.0.CO;2>CrossRefGoogle Scholar
Murphy, A. H. and Winkler, R. L. (1987). A general framework for forecast verification. Mon. Wea. Rev., 115, 1330–1338.2.0.CO;2>CrossRefGoogle Scholar
Murphy, J. M. and Palmer, T. N. (1986). Experimental monthly long-range forecasts for the United Kingdom. 2. A Real-time long-range forecast by an ensemble of numerical integrations. Meteorol. Mag., 115, 337–349.Google Scholar
Neal, R., Boyle, P., Grahame, N., Mylne, K., and Sharpe, M. (2014). Ensemble based first guess support towards a risk based national severe weather warning service, Meteorol. Apps., 21, 563–577.CrossRefGoogle Scholar
NCAR – Research Applications Laboratory (2013). Verification: Weather Forecast Verification Utilities. R package version 1.36.Google Scholar
Nussier, O., Joly, B., Vie, B., and Ducrocq, V. (2012). Uncertainty of lateral boundary conditions in a convective-permitting ensemble: a strategy of selection for Mediterranean heavy precipitation events. Nat. Hazards Earth Syst. Sci., 12, 2993–3011.CrossRefGoogle Scholar
Oesting, M., Schlather, M., and Friederichs, P. (2013). Conditional modelling of extreme wind gusts by bivariate Brown-Resnick processes. arXiv:1312.4584 [stat.ME].Google Scholar
Peralta, C., Ben Bouallègue, Z., Theis, S. E., Gebhardt, C., and Buchhold, M. (2012). Accounting for initial condition uncertainties in COSMO-DE-EPS. J. Geophys. Res., 117, D07108.CrossRefGoogle Scholar
R Core Team, R (2013). A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Raftery, A. E., Gneiting, T., Balabdaoui, F., and Polakowski, M. (2005). Using Bayesian model averaging to calibrate forecast ensembles. Mon. Wea. Rev., 133, 1155–1174.CrossRefGoogle Scholar
Roberts, N. M. and Lean, H. W. (2008). Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon. Wea. Rev., 136, 78–97.CrossRefGoogle Scholar
Roulston, M. S. and Smith, L. A. (2002). Evaluating probabilistic forecasts using information theory. Mon. Wea. Rev., 130, 1653–1660.2.0.CO;2>CrossRefGoogle Scholar
Sang, H. and Gelfand, A. E. (2009). Hierarchical modeling for extreme values observed over space and time. Environmental and Ecological Statistics, 16, 407–426.CrossRefGoogle Scholar
Schmeits, M. J. and Kok, K. J. (2010). A comparison between raw ensemble output, (modified) Bayesian model averaging, and extended logistic regression using ECMWF ensemble precipitation reforecasts. Mon. Wea. Rev., 138, 4199–4211.CrossRefGoogle Scholar
Shutts, G. (2005). A kinetic energy backscatter algorithm for use in ensemble prediction systems. Quart. J. Roy. Meteor. Soc., 131, 3079–3102.CrossRefGoogle Scholar
Stephan, K., Klink, S., and Schraff, C. (2008). Assimilation of radar-derived rain rates into the convective-scale model COSMO-DE at DWD. Quart. J. Roy. Meteor. Soc., 134, 1315–1326.CrossRefGoogle Scholar
Stephenson, D. B., Coelho, C. A. S., Doblas-Reyes, F. J., and Balmaseda, M. (2005). Forecast assimilation: a unified framework for the combination of multi-model weather and climate predictions. Tellus A, 57, 253–264.CrossRefGoogle Scholar
Tang, Y., Lean, H. W., and Bornemann, J., (2012). The benefits of the Met Office variable resolution NWP model for forecasting convection. Meteor. Appl., 20, 417–426.CrossRefGoogle Scholar
Tennant, W. J., Shutts, G. J., Arribas, A., and Thompson, S. A. (2011). Using a stochastic kinetic energy backscatter scheme to improve MOGREPS probabilistic forecast skill. Mon. Wea. Rev., 139, 1190–1206.CrossRefGoogle Scholar
Theis, S. E., Hense, A., and Damrath, U. (2005). Probabilistic precipitation forecasts from a deterministic model: A pragmatic approach. Meteor. Appl., 12, 257–268.CrossRefGoogle Scholar
Tibshirani, R. J. (1996). Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society. Series B (Methodological), 58, 267–288.CrossRefGoogle Scholar
Toth, Z., and Kalnay, E. (1993). Ensemble forecasting at NMC – the generation of perturbations. Bull. Amer. Meteorol. Soc., 74, 2317–2330.2.0.CO;2>CrossRefGoogle Scholar
Van der Grijn, G., Paulsen, J. E., Lalarette, F., and Leutbecher, M. (2004). Early medium-range forecasts of tropical cyclones. ECMWF newsletter, 102, 7–14.Google Scholar
WMO (2005). THORPEX International Research Implementation Plan, World Meteorological Organization WMO/TD no 1258, WWRP/THORPEX no. 4.Google Scholar
Wang, X. and Bishop, C. H. (2003). A comparison of breeding and Ensemble Transform Kalman Filter ensemble forecast schemes. J. Atmos. Sci., 60, 1140–1158.2.0.CO;2>CrossRefGoogle Scholar
Wei, M., Toth, Z., Wobus, R., and Zhu, Y. (2008). Initial perturbations based on the ensemble transform (ET) technique in the NCEP global operational forecast system. Tellus A, 60(1).CrossRefGoogle Scholar
Wilks, D. S. (2009). Extending logistic regression to provide full-probability-distribution MOS forecasts, Meteor. Appl., 16, 361–368.CrossRefGoogle Scholar
Wilks, D. S. (2011). Statistical Methods in the Atmospheric Sciences, 3rd edn. Elsevier.Google Scholar
Yamaguchi, M., Nakazawa, T., and Hoshino, S. (2012). On the relative benefits of a multi-centre grand ensemble for tropical cyclone track prediction in the western North Pacific. Q. J. Roy. Meteorol. Soc., 138, 2019–2029.CrossRefGoogle Scholar

References

Altenhoff, A. M., Martius, O., Croci‐Maspoli, M., Schwierz, C., and Davies, H. C. (2008). Linkage of atmospheric blocks and synoptic‐scale Rossby waves: a climatological analysis. Tellus A, 60(5), 1053–1063.CrossRefGoogle Scholar
Anstey, J. A., Davini, P., Gray, L. J., et al. (2013). Multi-model analysis of Northern Hemisphere winter blocking: Model biases and the role of resolution. J. Geophys. Res. Atmos., 118, 3956–3971.CrossRefGoogle Scholar
Arblaster, J. M., Meehl, G. A., and Karoly, D. J. (2011). Future climate change in the Southern Hemisphere: Competing effects of ozone and greenhouse gases. Geophys. Res. Lett., 38, L02701,CrossRefGoogle Scholar
Bader, J., Mesquita, M. D., Hodges, K. I., et al. (2011). A review on Northern Hemisphere sea-ice, storminess and the North Atlantic Oscillation: Observations and projected changes. Atmospheric Research, 101(4), 809–834.CrossRefGoogle Scholar
Barnes, E. A. (2013). Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes, Geophys. Res. Lett., 40, 4728–4733.CrossRefGoogle Scholar
Barnes, E. A., Slingo, J., and Woollings, T. (2012). A methodology for the comparison of blocking climatologies across indices, models and climate scenarios. Climate Dynamics, 38(11–12), 2467–2481.CrossRefGoogle Scholar
Barnes, E. A. and Polvani, L. M. (2013). Response of the midlatitude jets and of their variability to increased greenhouse gases in the CMIP5 models. Journal of Climate, 26, doi:10.1175/JCLI-D-12-00536.1.CrossRefGoogle Scholar
Bengtsson, L., Hodges, K. I., and Keenlyside, N. (2009). Will extratropical storms intensify in a warmer climate? Journal of Climate, 22, 2276–2301.CrossRefGoogle Scholar
Berckmans, J., Woollings, T., Demory, M. E., Vidale, P. L., and Roberts, M. (2013). Atmospheric blocking in a high resolution climate model: influences of mean state, orography and eddy forcing. Atmospheric Science Letters, 14, 34–40.CrossRefGoogle Scholar
Blackmon, M. L., Wallace, J. M., Lau, N. C., and Mullen, S. L. (1977). An observational study of the Northern Hemisphere wintertime circulation. Journal of the Atmospheric Sciences, 34, 1040–1053.2.0.CO;2>CrossRefGoogle Scholar
Boer, G. J., (1996). Some dynamical consequences of greenhouse gas warming. Atmosphere-Ocean, 33, 731–751.CrossRefGoogle Scholar
Booth, J. F., Wang, S., and Polvani, L. (2013). Midlatitude storms in a moister world: lessons from idealized baroclinic life cycle experiments. Climate Dynamics, 41, 787–802.CrossRefGoogle Scholar
Branscome, L. E. and Gutowski, W. J. Jr (1992). The impact of doubled CO2 on the energetics and hydrologic processes of mid-latitude transient eddies. Climate Dynamics, 8, 29–37.CrossRefGoogle Scholar
Buehler, T., Raible, C. C., and Stocker, T. F. (2011). The relationship of winter season North Atlantic blocking frequencies to extreme cold or dry spells in the ERA‐40. Tellus A, 63, 212–222.CrossRefGoogle Scholar
Butler, A. H., Thompson, D. W., and Heikes, R. (2010). The steady-state atmospheric circulation response to climate change-like thermal forcings in a simple general circulation model. Journal of Climate, 23, 3474–3496.CrossRefGoogle Scholar
Butler, A. H., Thompson, D. W., and Birner, T. (2011). Isentropic slopes, downgradient eddy fluxes, and the extratropical atmospheric circulation response to tropical tropospheric heating. Journal of the Atmospheric Sciences, 68, 2292–2305.CrossRefGoogle Scholar
Cattiaux, J., Vautard, R., Cassou, C., et al. (2010), Winter 2010 in Europe: A cold extreme in a warming climate, Geophys. Res. Lett., 37, L20704, doi:10.1029/2010GL044613.CrossRefGoogle Scholar
Cattiaux, J. and Cassou, C. (2013). Opposite CMIP3/CMIP5 trends in the wintertime Northern Annular Mode explained by combined local sea ice and remote tropical influences, Geophys. Res. Lett., 40, 3682–3687, doi:10.1002/grl.50643.CrossRefGoogle Scholar
Catto, J. L., Shaffrey, L. C., and Hodges, K. I. (2011). Northern Hemisphere extratropical cyclones in a warming climate in the HiGEM high-resolution climate model. J. Climate, 24, 5336–5352.CrossRefGoogle Scholar
Chang, E. K. (2009). Are band-pass variance statistics useful measures of storm track activity? Re-examining storm track variability associated with the NAO using multiple storm track measures. Climate dynamics, 33, 277–296.CrossRefGoogle Scholar
Chang, E. K., Guo, Y., and Xia, X. (2012). CMIP5 multimodel ensemble projection of storm track change under global warming. Journal of Geophysical Research: Atmospheres, 117(D23).CrossRefGoogle Scholar
Chen, G., Lu, J., and Frierson, D. M. W. (2008). Phase speed spectra and the latitude of surface westerlies: interannual variability and global warming trend. Journal of Climate, 21, 5942–5959.CrossRefGoogle Scholar
Colle, B. A., Zhang, Z., Lombardo, K. A., et al. (2013). Historical evaluation and future prediction of eastern North American and western Atlantic extratropical cyclones in the CMIP5 models during the cool season. J. Climate, 26, 6882–6903.CrossRefGoogle Scholar
Croci-Maspoli, M. and Davies, H. C. (2009). Key dynamical features of the 2005/06 European winter. Monthly Weather Review, 137, 664–678.CrossRefGoogle Scholar
Dacre, H. F. and Gray, S. L. (2013). Quantifying the climatological relationship between extratropical cyclone intensity and atmospheric precursors, Geophys. Res. Lett., 40, 2322–2327.CrossRefGoogle Scholar
Delcambre, S. C., Lorenz, D. J., Vimont, D. J., and Martin, J. E. (2013). Diagnosing Northern Hemisphere jet portrayal in 17 CMIP3 global climate models: twenty-first-century projections. J. Climate, 26, 4930–4946.CrossRefGoogle Scholar
de Vries, H., Woollings, T., Anstey, J., Haarsma, R. J., and Hazeleger, W. (2013). Atmospheric blocking and its relation to jet changes in a future climate. Climate Dynamics, 41, 2643–2654.CrossRefGoogle Scholar
Dunn-Sigouin, E. and Son, S.-W. (2013). Northern Hemisphere blocking frequency and duration in the CMIP5 models, J. Geophys. Res. Atmos., 118, 1179–1188.CrossRefGoogle Scholar
Feldstein, S. B. (2000). The timescale, power spectra, and climate noise properties of teleconnection patterns. Journal of Climate, 13, 4430–4440.2.0.CO;2>CrossRefGoogle Scholar
Fink, A. H., Bruecher, T., Ermert, V., Krueger, A., and Pinto, J. G. (2009). The European storm Kyrill in January 2007: synoptic evolution, meteorological impacts and some considerations with respect to climate change. Natural Hazards and Earth System Sciences, 9, 405–423.CrossRefGoogle Scholar
Fink, A., Pohle, S., Pinto, J., and Knippertz, P. (2012). Diagnosing the influence of diabatic processes on the explosive deepening of extratropical cyclones. Geophysical Research Letters, 39.CrossRefGoogle Scholar
Francis, J. A. and Vavrus, S. J. (2012). Evidence linking arctic amplification to extreme weather in mid-latitudes, Geophys. Res. Lett. 39, L06801.CrossRefGoogle Scholar
Franzke, C. and Woollings, T. (2011). On the persistence and predictability properties of North Atlantic climate variability. Journal of Climate, 24, 466–472.CrossRefGoogle Scholar
Frierson, D. M. W., Held, I. M., and Zurita-Gotor, P. (2007). A gray-radiation aquaplanet moist GCM. Part II: energy transports in altered climates. J. Atmos. Sci., 64, 1680–1693.CrossRefGoogle Scholar
Froude, L. S. (2010). TIGGE: Comparison of the prediction of Northern Hemisphere extratropical cyclones by different ensemble prediction systems. Weather and Forecasting, 25, 819–836.CrossRefGoogle Scholar
Gillett, N. P. and Thompson, D. W. (2003). Simulation of recent Southern Hemisphere climate change. Science, 302, 273–275.CrossRefGoogle ScholarPubMed
Held, I. M. (1993). Large-scale dynamics and global warming. Bulletin of the American Meteorological Society, 74, 228–241.2.0.CO;2>CrossRefGoogle Scholar
Graff, L. and LaCasce, J. (2012). Changes in the extratropical storm tracks in response to changes in SST in an AGCM. Journal of Climate, 25, 1854–1870.CrossRefGoogle Scholar
Haarsma, R. J., Selten, F., and van Oldenborgh, G. J. (2013a). Anthropogenic changes of the thermal and zonal flow structure over Western Europe and Eastern North Atlantic in CMIP3 and CMIP5 models. Climate Dynamics, 41, 2577–2588.CrossRefGoogle Scholar
Haarsma, R. J., Hazeleger, W., Severijns, C., et al. (2013b). More hurricanes to hit western Europe due to global warming, Geophys. Res. Lett., 40, 1783–1788.CrossRefGoogle Scholar
Hartmann, D. L. (2000). The key role of lower-level meridional shear in baroclinic wave life cycles. Journal of the Atmospheric Sciences, 57, 389–401.2.0.CO;2>CrossRefGoogle Scholar
Harvey, B. J., Shaffrey, L. C., Woollings, T. J., Zappa, G., and Hodges, K. I. (2012). How large are projected 21st century storm track changes? Geophys. Res. Lett., 39, L18707.CrossRefGoogle Scholar
Harvey, B., Shaffrey, L., and Woollings, T. (2013). Equator-to-pole temperature differences and the extra-tropical storm track responses of the cmip5 climate models. Climate Dynam. doi: 10.1007/s00382-013-1883–9.CrossRefGoogle Scholar
Hernández-Deckers, D. and von Storch, J. S. (2010). Energetics responses to increases in greenhouse gas concentration. Journal of Climate, 23, 3874–3887.CrossRefGoogle Scholar
Hoskins, B. J. and Hodges, K. I. (2002). New perspectives on the Northern Hemisphere winter storm tracks. Journal of the Atmospheric Sciences, 59, 1041–1061.2.0.CO;2>CrossRefGoogle Scholar
Hwang, Y.-T. and Frierson, D. M. W. (2010). Increasing atmospheric poleward energy transport with global warming. Geophysical Research Letters, 37, L24807.CrossRefGoogle Scholar
Hwang, Y. T., Frierson, D. M., and Kay, J. E. (2011). Coupling between Arctic feedbacks and changes in poleward energy transport. Geophysical Research Letters, 38, L17704.CrossRefGoogle Scholar
Jung, T., Balsamo, G., Bechtold, P., et al. (2010). The ECMWF model climate: Recent progress through improved physical parametrizations, Q. J. Roy. Meteorol. Soc., 136, 1145–1160.CrossRefGoogle Scholar
Jung, T. and Coauthors (2012). High‐resolution global climate simulations with the ECMWF model in Project Athena: experimental design, model climate, and seasonal forecast skill. J. Climate, 25, 3155–3172.CrossRefGoogle Scholar
Karpechko, A. Y. and Manzini, E. (2012). Stratospheric influence on tropospheric climate change in the Northern Hemisphere, J. Geophys. Res., 117, D05133.CrossRefGoogle Scholar
Kidston, J., Vallis, G. K., Dean, S. M., and Renwick, J. A. (2011). Can the increase in the eddy length scale under global warming cause the poleward shift of the jet streams? Journal of Climate, 24, 3764–3780.CrossRefGoogle Scholar
Kodama, C., and Iwasaki, T. (2009). Influence of the SST Rise on Baroclinic Instability Wave Activity under an Aquaplanet Condition. Journal of the Atmospheric Sciences, 66, 2272–2287.CrossRefGoogle Scholar
Lambert, S. J. and Fyfe, J. C. (2006). Changes in winter cyclone frequencies and strengths simulated in enhanced greenhouse warming experiments: results from the models participating in the IPCC diagnostic exercise. Climate Dynam., 26, 713–728.CrossRefGoogle Scholar
Lang, C. and Waugh, D. W. (2011). Impact of climate change on the frequency of Northern Hemisphere summer cyclones, J. Geophys. Res., 116, D04103.CrossRefGoogle Scholar
Li, C. and Wettstein, J. J. (2012). Thermally driven and eddy-driven jet variability in reanalysis. Journal of Climate, 25, 1587–1596.CrossRefGoogle Scholar
Lim, E. P. and Simmonds, I. (2009). Effect of tropospheric temperature change on the zonal mean circulation and SH winter extratropical cyclones. Climate Dynamics, 33, 19–32.CrossRefGoogle Scholar
Liu, J., Curry, J. A., Wang, H., Song, M., and Horton, R. M. (2012). Impact of declining arctic sea ice on winter snowfall. P. Natl. Acad. Sci. USA, 109, 4074–4079.CrossRefGoogle ScholarPubMed
Long, Z., Perrie, W., Gyakum, J., Laprise, R., and Caya, D. (2009). Scenario changes in the climatology of winter midlatitude cyclone activity over eastern North America and the Northwest Atlantic. Journal of Geophysical Research-Atmospheres, 114.CrossRefGoogle Scholar
Lorenz, D. J. and Hartmann, D. L. (2003). Eddy-zonal flow feedback in the Northern Hemisphere winter. Journal of Climate, 16, 1212–1227.2.0.CO;2>CrossRefGoogle Scholar
Lorenz, D. J. and DeWeaver, E. T. (2007). Tropopause height and zonal wind response to global warming in the IPCC scenario integrations. Journal of Geophysical Research: Atmospheres, 112, D10.CrossRefGoogle Scholar
Lu, J., Chen, G., and Frierson, D. M. W. (2008). Response of the zonal mean atmospheric circulation to El Nino versus global warming. Journal of Climate, 21, 5835–5851.CrossRefGoogle Scholar
Lucarini, V. and Ragone, F. (2011). Energetics of climate models: net energy balance and meridional enthalpy transport. Reviews of Geophysics, 49.CrossRefGoogle Scholar
Ludwig, P., Pinto, J. G., Reyers, M., and Gray, S. L. (2014). The role of anomalous SST and surface fluxes over the southeastern North Atlantic in the explosive development of windstorm Xynthia. Q.J.R. Meteorol. Soc., 140, 1729–1741.CrossRefGoogle Scholar
Lunkeit, F., Fraedrich, K., and Bauer, S. E. (1998). Storm tracks in a warmer climate: sensitivity studies with a simplified global circulation model. Climate Dynamics, 14, 813–826.CrossRefGoogle Scholar
Masato, G., Hoskins, B. J., and Woollings, T. (2013). Winter and summer Northern Hemisphere blocking in CMIP5 models. J. Climate, 26, 7044–7059.CrossRefGoogle Scholar
Masato, G., Woollings, T., and Hoskins, B. J. (2014). Structure and impact of atmospheric blocking over the Euro-Atlantic region in present day and future simulations. Geophys. Res. Lett., 41, 1051–1058.CrossRefGoogle Scholar
Matsueda, M. (2011). Predictability of Euro-Russian blocking in summer of 2010, Geophys. Res. Lett., 38, L06801.CrossRefGoogle Scholar
Matsueda, M., Mizuta, R., and Kusunoki, S. (2009). Future change in wintertime atmospheric blocking simulated using a 20‐km‐mesh atmospheric global circulation model. Journal of Geophysical Research: Atmospheres, 114, D12.CrossRefGoogle Scholar
McDonald, R. E. (2011). Understanding the impact of climate change on Northern Hemisphere extra-tropical cyclones. Climate Dynamics, 37, 1399–1425.CrossRefGoogle Scholar
Mizuta, R., Matsueda, M., Endo, H., and Yukimoto, S. (2011). Future change in extratropical cyclones associated with change in the upper troposphere. Journal of Climate, 24, 6456–6470.CrossRefGoogle Scholar
Morgenstern, O. and Coauthors (2010). Anthropogenic forcing of the Northern Annular Mode in CCMVal-2 models. Journal of Geophysical Research-Atmospheres, 115.CrossRefGoogle Scholar
Neu, U. et al. (2013). IMILAST – a community effort to intercompare extratropical cyclone detection and tracking algorithms. Bull. Amer. Meteor. Soc., 94, 529–547.CrossRefGoogle Scholar
O’Gorman, P. A. (2010). Understanding the varied response of the extratropical storm tracks to climate change. Proceedings of the National Academy of Sciences, 107, 19176–19180.CrossRefGoogle ScholarPubMed
Palmer, T. N., Shutts, G. J., and Swinbank, R. (1986). Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parametrization. Quarterly Journal of the Royal Meteorological Society, 112(474), 1001–1039.CrossRefGoogle Scholar
Pelly, J. L. and Hoskins, B. J. (2003). A new perspective on blocking. Journal of the Atmospheric Sciences, 60, 743–755.2.0.CO;2>CrossRefGoogle Scholar
Petoukhov, V. and Semenov, V. A. (2010). A link between reduced Barents-Kara sea ice and cold winter extremes over northern continents. J. Geophys. Res. 115, D21.CrossRefGoogle Scholar
Pfahl, S. and Wernli, H. (2012). Quantifying the relevance of atmospheric blocking for co‐located temperature extremes in the Northern Hemisphere on (sub‐) daily time scales. Geophysical Research Letters, 39.CrossRefGoogle Scholar
Pinto, J. G., Ulbrich, U., Leckebusch, G. C., et al. (2007). Changes in storm track and cyclone activity in three SRES ensemble experiments with the ECHAM5/MPI-OM1 GCM. Climate Dynamics, 29, 195–210.CrossRefGoogle Scholar
Raible, C. C., Ziv, B., Saaroni, H., and Wild, M. (2010). Winter synoptic-scale variability over the Mediterranean Basin under future climate conditions as simulated by the ECHAM5. Climate Dynamics, 35, 473–488.CrossRefGoogle Scholar
Rind, D. (2008). The consequences of not knowing low- and high-latitude climate sensitivity. Bulletin of the American Meteorological Society, 89, 855–864.CrossRefGoogle Scholar
Riviere, G. (2011). A dynamical interpretation of the poleward shift of the jet streams in global warming scenarios. Journal of the Atmospheric Sciences, 68, 1253–1272.CrossRefGoogle Scholar
Scaife, A. A., Woollings, T., Knight, J., Martin, G., and Hinton, T. (2010). Atmospheric blocking and mean biases in climate models. Journal of Climate, 23, 6143–6152.CrossRefGoogle Scholar
Scaife, A. A., Copsey, D., Gordon, C., et al. (2011). Improved Atlantic winter blocking in a climate model. Geophysical Research Letters, 38(23).CrossRefGoogle Scholar
Scaife, A. A., Spangehl, T., Fereday, D. R., et al. (2012). Climate change projections and stratosphere–troposphere interaction. Climate Dynamics, 38, 2089–2097.CrossRefGoogle Scholar
Schneider, T., O’Gorman, P. A., and Levine, X. J. (2010). Water vapor and the dynamics of climate changes. Reviews of Geophysics, 48.CrossRefGoogle Scholar
Screen, J. A., and Simmonds, I. (2013). Exploring links between Arctic amplification and mid-latitude weather, Geophys. Res. Lett., 40, 959–964.CrossRefGoogle Scholar
Shaffrey, L. C., Stevens, I., Norton, W. A., et al. (2009). UK HiGEM: The new UK high-resolution global environment model-model description and basic evaluation. Journal of Climate, 22, 1861–1896.CrossRefGoogle Scholar
Shutts, G. J. (1983). The propagation of eddies in diffluent jetstreams: Eddy vorticity forcing of ‘blocking’ flow fields. Quarterly Journal of the Royal Meteorological Society, 109, 737–761.Google Scholar
Simmons, A. J. and Hoskins, B. J. (1978). The life cycles of some nonlinear baroclinic waves. Journal of the Atmospheric Sciences, 35, 414–432.2.0.CO;2>CrossRefGoogle Scholar
Simpson, I. R., Blackburn, M., and Haigh, J. D. (2009). The role of eddies in driving the tropospheric response to stratospheric heating perturbations. Journal of the Atmospheric Sciences, 66, 1347–1365.CrossRefGoogle Scholar
Simpson, I. R., Blackburn, M., Haigh, J. D., and Sparrow, S. N. (2010). The impact of the state of the troposphere on the response to stratospheric heating in a simplified GCM. Journal of Climate, 23, 6166–6185.CrossRefGoogle Scholar
Son, S. W. and Lee, S. (2005). The response of westerly jets to thermal driving in a primitive equation model. Journal of the Atmospheric Sciences, 62(10), 3741–3757.CrossRefGoogle Scholar
Son, S. W., Polvani, L. M., Waugh, D. W., et al. (2008). The impact of stratospheric ozone recovery on the Southern Hemisphere westerly jet. Science, 320, 1486–1489.CrossRefGoogle ScholarPubMed
Thompson, D. W., Lee, S., and Baldwin, M. P. (2003). Atmospheric processes governing the northern hemisphere annular mode/North Atlantic oscillation. Geophysical Monograph-American Geophysical Union, 134, 81–112.Google Scholar
Ulbrich, U., Leckebusch, G. C., and Pinto, J. G. (2009). Extra-tropical cyclones in the present and future climate: a review. Theoretical and Applied Climatology, 96, 117–131.CrossRefGoogle Scholar
Ulbrich, U. et al. (2013). Are greenhouse gas signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking methodology? Meteorol Z. 22, 61–68 doi:10.1127/0941–2948/2013/0420.CrossRefGoogle Scholar
Vallis, G. K. and Gerber, E. P. (2008). Local and hemispheric dynamics of the North Atlantic Oscillation, annular patterns and the zonal index. Dynamics of Atmospheres and Oceans, 44, 184–212.CrossRefGoogle Scholar
Woollings, T. (2010). Dynamical influences on European climate: an uncertain future. Philosophical Transactions of the Royal Society A, 368, 3733–3756.CrossRefGoogle ScholarPubMed
Woollings, T. and Blackburn, M. (2012). The North Atlantic jet stream under climate change and its relation to the NAO and EA patterns. Journal of Climate, 25, 886–902.CrossRefGoogle Scholar
Woollings, T., Hoskins, B., Blackburn, M., and Berrisford, P. (2008). A new Rossby wave-breaking interpretation of the North Atlantic Oscillation. Journal of the Atmospheric Sciences, 65, 609–626.CrossRefGoogle Scholar
Woollings, T., Gregory, J., Pinto, J., Reyers, M., and Brayshaw, D. (2012a). Response of the North Atlantic storm track to climate change shaped by ocean-atmosphere coupling. Nature Geoscience, 5, 313–317.CrossRefGoogle Scholar
Woollings, T., Harvey, B., Zahn, M., and Shaffrey, L. (2012b). On the role of the ocean in projected atmospheric stability changes in the Atlantic polar low region, Geophys. Res. Lett., 39, L24802.CrossRefGoogle Scholar
Woollings, T., Harvey, B., and Masato, G. (2014). Arctic warming, atmospheric blocking and cold European winters in CMIP5 models. Env. Res. Lett., 9, 014002.CrossRefGoogle Scholar
Wu, Y., Ting, M., Seager, R., Huang, H. P., and Cane, M. A. (2011). Changes in storm tracks and energy transports in a warmer climate simulated by the GFDL CM2. 1 model. Climate Dynamics, 37, 53–72.CrossRefGoogle Scholar
Yang, S. and Christensen, J. H. (2012). Arctic sea ice reduction and European cold winters in cmip5 climate change experiments. Geophys. Res. Lett. 39(20).CrossRefGoogle Scholar
Yin, J. H. (2005). A consistent poleward shift of the storm tracks in simulations of 21st century climate. Geophys. Res. Lett., 32, L18701. doi:10.1029/2005GL023684.CrossRefGoogle Scholar
Zahn, M. and von Storch, H. (2010). Decreased frequency of North Atlantic polar lows associated with future climate warming. Nature, 467, 309–312.CrossRefGoogle ScholarPubMed
Zappa, G., Shaffrey, L. C., and Hodges, K. I. (2013a). The ability of CMIP5 models to simulate North Atlantic extratropical cyclones. Journal of Climate, 26, 5379–5396.CrossRefGoogle Scholar
Zappa, G., Shaffrey, L. C., Hodges, K. I., Sansom, P. G., and Stephenson, D. B. (2013b). A multi-model assessment of future projections of North Atlantic and European extratropical cyclones in the CMIP5 climate models. Journal of Climate, 26, 5846–5862.CrossRefGoogle Scholar
Zappa, G., Masato, G., Shaffrey, L., Woollings, T., and Hodges, K. (2014). Linking Northern Hemisphere blocking and storm track biases in the CMIP5 climate models. Geophysical Research Letters. 41, 135–139.CrossRefGoogle Scholar

References

Arribas, A., Glover, M., Maidens, A., et al. (2011). The GloSea4 ensemble prediction system for seasonal forecasting. Mon. Wea. Rev., 139, 1891–1910.CrossRefGoogle Scholar
Barnston, A. G. and Livezey, R. E. (1987). Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon. Wea. Rev., 115, 1083–1126.2.0.CO;2>CrossRefGoogle Scholar
Boer, G. and Hamilton, K. (2008). QBO influence on extratropical predictive skill, Clim. Dyn., 31, 987–1000.Google Scholar
Brönnimann, S. (2007). Impact of El Niño–Southern Oscillation on European climate. Rev. Geophys., 45, doi: 10.1029/2006RG000199CrossRefGoogle Scholar
Cassou, C. (2008). Intraseasonal interaction between the Madden Julian Oscillation and the North Atlantic Oscillation. Nature, 455, 523–527.CrossRefGoogle ScholarPubMed
Cohen, J. and Entekhabi, D. (1999). Eurasian snow cover variability and Northern Hemisphere climate predictability, GRL, 26, 345–348.CrossRefGoogle Scholar
Eade, R., Smith, D., Scaife, A.A., and Wallace, E. (2014). Do seasonal to decadal climate predictions underestimate the predictability of the real world? Geophys. Res. Lett., DOI: 10.1002/2014GL061146.CrossRefGoogle Scholar
Ebdon, R. A. (1975). The quasi-biennial oscillation and its association with tropospheric circulation patterns. Meteorol. Mag., 104, 282–297.Google Scholar
Fereday, D., Maidens, A., Arribas, A., Scaife, A. A., and Knight, J. R. (2012). Seasonal forecasts of Northern Hemisphere Winter 2009/10. Env. Res. Lett., 7, doi:10.1088/1748-9326/7/3/034031.CrossRefGoogle Scholar
Franzke, C., Lee, S., and Feldstein, S. B. (2004). Is the North Atlantic Oscillation a breaking wave?. J. Atmos. Sci., 61, 145–160.2.0.CO;2>CrossRefGoogle Scholar
Gray, L. J. et al. (2010). Solar influences on climate. Rev. Geophys. 48, RG4001.CrossRefGoogle Scholar
Graystone, P., (1959). Meteorological office discussion on tropical meteorology. Met. Magazine, 88, 117.Google Scholar
Hanna, E., Cropper, T. E., Jones, P. D., Scaife, A. A., and Allan, R. (2014). Recent seasonal asymmetric changes in the NAO: a marked summer decline and increased winter variability. Int. J. Clim., DOI: 10.1002/joc.4157.CrossRefGoogle Scholar
Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M. (eds.) (2003). The North Atlantic Oscillation: Climatic Significance and Environmental Impact, American Geophysical Union, Washington, DC, 279 pp.CrossRefGoogle Scholar
Ilkka, J., Heikki, T., and Väinö, N. (2012). The variability of winter temperature, its impacts on society, and the potential use of seasonal forecasts in Finland. Weather 67, 328–332.CrossRefGoogle Scholar
Ineson, S. and Scaife, A. A. (2009). The role of the stratosphere in the European climate response to El Nino. Nat. Geosci., 2, 32–36.CrossRefGoogle Scholar
Ineson, S., Scaife, A. A., Knight, J. R., et al. (2011), Solar forcing of winter climate variability in the Northern Hemisphere, Nat. Geosci., 4, 753–757, doi:10.1038/GEO1282.Google Scholar
Johansson, Å. (2007): Prediction skill of the NAO and PNA from daily to seasonal time scales. J. Climate, 20, 1957–1975. doi:10.1175/JCLI4072.1CrossRefGoogle Scholar
Jones, P. D., Jόnsson, T, and Wheeler, D. (1997). Extension to the North Atlantic Oscillation using early instrumental pressure observations from Gibraltar and south-west Iceland. Int. J. Climatol. 17, 1433–1450.3.0.CO;2-P>CrossRefGoogle Scholar
Kang, D., Lee, M. I., Im, J., et al. (2014). Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems. Geophys. Res. Lett., 10, 3577–3585, doi:10.1002/2014GL060011.CrossRefGoogle Scholar
Karpechko, A. Y. and Manzini, E. (2012). Stratospheric influence on tropospheric climate change in the Northern Hemisphere, J. Geophys. Res., 117, D05133, doi:10.1029/2011JD017036.CrossRefGoogle Scholar
Keeley, S. P. E., Sutton, R.T., and Shaffrey, L. C. (2009). Does the North Atlantic Oscillation show unusual persistence on intraseasonal timescales? Geophys. Res. Lett., 36, L22706, doi:10.1029/2009GL040367.CrossRefGoogle Scholar
Kim, H-M., Webster, P., and Curry, J. (2012). Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter. Clim. Dyn., 23, doi:10.1007/s00382-012-1364-6.Google Scholar
Koenigk, T. and Mikolajewicz, U. (2009). Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model. Clim. Dyn. 32, 783–798, doi:10.1007/s00382-008-0419-1CrossRefGoogle Scholar
Labitzke, K. (1987). Sunspots, the QBO, and the stratospheric temperature in the north polar region. Geophys. Res. Lett. 14, 535–537.CrossRefGoogle Scholar
Li, J. and Wang, J. X. L. (2003). A modified zonal index and its physical sense. Geophys. Res. Lett., 30(12), 1632, doi: 10.1029/2003GL017441.CrossRefGoogle Scholar
Marshall, A. and Scaife, A.A. (2009). Impact of the Quasi-Biennial Oscillation on 321 seasonal forecasts. J. Geophys. Res., 114, D18110, doi:10.1029/2009JD011737.Google Scholar
Marshall, A. and Scaife, A.A. (2010). Improved predictability of stratospheric sudden warming events in an AGCM with enhanced stratospheric resolution. J. Geophys. Res., vol.115, D16114, doi:10.1029/2009JD012643.CrossRefGoogle Scholar
Matthes, K., Kuroda, Y., Kodera, K., and Langematz, U. (2006). Transfer of the solar signal from the stratosphere to the troposphere: Northern winter. J. Geophys. Res. 111, D06108.CrossRefGoogle Scholar
Morgenstern, O. et al. (2010). Review of the formulation of present generation stratospheric chemistry-climate models and associated external forcing. J Geophys Res 115, D00M02. doi: 10.1029/2009JD013728CrossRefGoogle Scholar
Ouzeau, G., Cattiaux, J., Douville, H., Ribes, A., and Saint‐Martin, D. (2011). European cold winter 2009–2010: How unusual in the instrumental record and how reproducible in the ARPEGE‐Climat model? Geophys. Res. Lett., 38, L11706, doi:10.1029/2011GL047667.CrossRefGoogle Scholar
Pascoe, C. L., Gray, L. J., and Scaife, A. A. (2006). A GCM study of the influence of equatorial winds on the timing of sudden stratospheric warmings, Geophys. Res. Lett., 33, L06825, doi:10.1029/2005GL024715.CrossRefGoogle Scholar
Renggli, D., Leckebusch, G. C., Ulbrich, U., Gleixner, S. N., and Faust, E. (2011). The skill of seasonal ensemble prediction systems to forecast wintertime windstorm frequency over the North Atlantic and Europe. Mon. Wea. Rev. 139, 3052–3068.CrossRefGoogle Scholar
Riddle, E. E., Butler, A. H., Furtado, J. C., Cohen, J. L., and Kumar, A., (2013). CFSv2 ensemble prediction of the wintertime Arctic Oscillation. Climate Dyn., 41, 1099–1116, doi:10.1007/s00382-013-1850-5.CrossRefGoogle Scholar
Riviere, G. and Orlanski, I. (2007). Characteristics of the Atlantic storm-track eddy activity and its relation with the North Atlantic Oscillation, J. Atm. Sci., 64, 241–266.CrossRefGoogle Scholar
Scaife, A. A., Folland, C. K., Alexander, L., Moberg, A., and Knight, J. R. (2008). European climate extremes and the North Atlantic Oscillation. J. Clim., 21, 72–83.CrossRefGoogle Scholar
Scaife, A. A., Spangehl, T., Fereday, D., et al. (2012). Climate change and stratosphere-troposphere interaction. Clim. Dyn., 38, 2089–2097, doi:10.1007/s00382-011-1080-7.CrossRefGoogle Scholar
Scaife, A. A., Arribas, A., Blockley, E., et al. (2014). Skilful long range prediction of European and North American winters. Geophys. Res. Lett., 41, 2514–2519, doi:10.1002/2014GL059637.CrossRefGoogle Scholar
Schmidt, H., Kieser, J., Misios, S., and Gruzdev, A. N. (2013). The atmospheric response to solar variability: Simulations with a general circulation and chemistry model for the entire atmosphere, in: Luebken, F.-J. (ed.): Climate And Weather of the Sun-Earth System (CAWSES): Highlights from a priority program, Springer, Dordrecht, the Netherlands.Google Scholar
Shabbar, A., Huang, J., and Higuchi, K. (2001). The relationship between the wintertime north Atlantic oscillation and blocking episodes in the north Atlantic. Int. J. Climatol., 21, 355–369. doi: 10.1002/joc.612CrossRefGoogle Scholar
Stenchikov, G., Robock, A., Ramaswamy, V., et al. (2002). Arctic Oscillation response to the 1991 Mount Pinatubo eruption: effects of volcanic aerosols and ozone depletion. J. Geophys. Res., 107 (D24), 4803, doi:10.1029/2002JD002090.CrossRefGoogle Scholar
Thompson, D. W. J. and Wallace, J. M. (1998). The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett. 25, 1297–1300.CrossRefGoogle Scholar
Vallis, G. and Gerber, E. (2008). Local and hemispheric dynamics of the North Atlantic Oscillation, annular patterns and the zonal index. Dyn. Atmos. Oceans, 44, 184–212.CrossRefGoogle Scholar
Walker, G. T. and Bliss, E. W. (1932). World weather V. Mem. Roy. Meteor. Soc., 4, 53–84.Google Scholar
Wu, Z., Wang, B., Li, J., and Jin, F. (2009). An empirical seasonal prediction model of the East Asian summer monsoon using ENSO and NAO. J. Geophys. Res., 114, D18120, doi:10.1029/2009JD011733.CrossRefGoogle Scholar

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