The potential for skill across the range of the seamless weather-climate prediction problem: a stimulus for our scienceHoskins, B. (2013) The potential for skill across the range of the seamless weather-climate prediction problem: a stimulus for our science. Quarterly Journal of the Royal Meteorological Society, 139 (672). pp. 573-584. ISSN 1477-870X Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1002/qj.1991 Abstract/SummaryPredictability is considered in the context of the seamless weather-climate prediction problem, and the notion is developed that there can be predictive power on all time-scales. On all scales there are phenomena that occur as well as longer time-scales and external conditions that should combine to give some predictability. To what extent this theoretical predictability may actually be realised and, further, to what extent it may be useful is not clear. However the potential should provide a stimulus to, and high profile for, our science and its application for many years.
Ambaum MHP, Hoskins BJ, Stephenson DB. 2001. Arctic Oscillation or
North Atlantic Oscillation? J. Climate 14: 3495–3507.
Arribas A, Glover M, Maidens A, Peterson K, GordonM,MacLachlan C,
Graham R, Fereday D, Camp J, Scaife AA, Xavier P, McLean P,
Colman A, Cusack S. 2011. The GloSea4 ensemble prediction system
for seasonal forecasting. Mon. Weather Rev. 139: 1891–1910.
BaldwinMP, DunkertonTJ. 2001. Stratosphericharbingers of anomalous
weather regimes. Science 244: 581–584.
Bengtsson LK, Magnusson L, K¨all´en E. 2008. Independent estimations
of the asymptotic variability in an ensemble forecast system. Mon.
Weather Rev. 136: 4105–4112.
Boer GJ. 2004. Long time-scale potential predictability in an ensemble
of coupled climate models. Clim. Dyn. 23: 29–44.
Boer GJ. 2009. Changes in internal variability and decadal predictability
under global warming. J. Climate 22: 3098–3109.
Brunet G, Shapiro M, Hoskins BJ, Moncrieff M, Dole R, Kiladis GN,
Kirtman B, Lorenc AC, Mills B, Morss R, Polavarapu S, Rogers D,
Schaake J, Shukla J. 2010. Collaboration of the weather and climate
communities to advance subseasonal-to-seasonal prediction. Bull.
Amer. Meteorol. Soc. 91: 1397–1406.
Buizza R. 2001. Chaos and weather prediction. Il Nuovo Cimento C 24:
273–302.
Cassou C. 2008. On the interaction between the Madden–Julian
Oscillation and the North Atlantic Oscillation. Nature 455: 523–527.
Charney JG, Shukla J. 1981. Predictability of monsoons. In Monsoon
Dynamics, Lighthill MJ, Pearce RP (eds) Cambridge University Press:
Cambridge, UK. 99–109.
Cohen J, Jones J. 2011. A new index for more accuratewinter predictions.
Geophys. Res. Lett. 38: L21701, DOI: 10.1029/2011GL049626
Czaja A, Blunt N. 2011. A new mechanism for ocean–atmosphere
coupling in middle latitudes. Q. J. R. Meteorol. Soc. 137: 1095–1101.
DelSole T, Tippett MK, Shukla J. 2011. A significant component of
unforced multi-decadal variability in the recent acceleration of global
warming. J. Climate 24: 909–926.
Deser C, Phillips AS, Bourdette V, Teng H. 2012. Uncertainty in climate
change projections: the role of internal variability. Clim. Dyn. 38:
527–546. DOI: 10.1007/s00382-010-0977-x
Feldstein FB. 2000. The timescale, power spectra and climate noise
properties of teleconnection patterns. J.Climate 13:: 4430–4440.
Hawkins E, Sutton R. 2009. The potential to narrow uncertainty in
regional climate predictions. Bull. Amer. Meteorol. Soc. 90: 1095–1107.
Hawkins E, Sutton R. 2011. The potential to narrow uncertainty in
projections of regional precipitation change. Clim. Dyn. 37: 407–418.
Hong C-C, Hsu H-H, Lin N-H, Chiu H. 2011. Roles of European
blocking and tropical–extratropical interaction in the 2010 Pakistan
flooding. Geophys. Res. Lett. 38: L13806, DOI: 10.1029/2011GL047583
Hoskins BJ, Ambrizzi T. 1993. Rossby wave propagation on a realistic
longitudinally varying flow. J. Atmos. Sci. 50: 1661–1671.
Hoskins BJ, Bretherton FP. 1972. Atmospheric frontogenesis models:
Mathematical formulation and solution. J. Atmos. Sci. 29: 11–37.
Hoskins BJ, Karoly D. 1981. The steady linear response of a spherical
atmosphere to thermal and orographic forcing. J. Atmos. Sci. 38:
1179–1196.
Hurrell J, Meehl G, Bader D, Delworth T, Kirtman B,Wielicki B. 2009. A
unified modeling approach to climate system prediction. Bull. Amer.
Meteorol. Soc. 90: 1819–1832.
Ineson S, Scaife AA, Knight JR, Manners JC, Dunstone NJ, Gray LJ,
Haigh JD. 2011. Solar forcing of winter climate variability in the
Northern Hemisphere. Nature Geosci. 4: 753–757.
Knight JR, Allan RJ, FollandCK, VellingaM,MannME. 2005.Asignature
of persistent natural thermohaline circulation cycles in observed
climate. Geophys. Res. Lett. 32: L20708, DOI: 10.1029/2005GL024233
Kuroda Y. 2008. Role of the stratosphere on the predictability of
medium-range weather forecasts: a case study of winter 2003/4.
Geophys.Res.Lett. 35: L19701.
Kushnir Y, Robinson WA, Blad´e I, Hall NMJ, Peng S, Sutton R. 2002.
Atmospheric GCMresponse to extratropical SST anomalies: synthesis
and evaluation. J.Climate 15: 2233–2256.
Kushnir Y, Newman M, Smith D, Vimont D, Delworth T, Meehl G,
Stockdale T. 2011. Distinguishing the roles of natural variability
and anthropogenically forced decadal climate variability. Bull. Amer.
Meteorol. Soc. 92: 141–156.
Lockwood M, Harrison RG, Woollings T, Solanki SK. 2010. Are cold
winters in Europe associated with low solar activity? Environ. Res. Lett.
5: 024001.
Lorenz EN. 1969. The predictability of a flow which possesses many
scales of motion. Tellus 21: 289–307.
Matthews AJ, Hoskins BJ, Masutani M. 2004. The global response to
tropical heating in the Madden–Julian oscillation during the northern
winter. Q. J. R. Meteorol. Soc. 130: 1991–2011.
Meehl GA, Goddard L, Murphy J, Stouffer RJ, Boer G, Danabasoglu G,
Dixon K, Giorgetta MA, Greene A, Hawkins AE, Hegerl G, Karoly D,
Keenlyside N, Kimoto M, Kirtman B,Navarra A, Pulwarty R, SmithD,
Stammer D, Stockdale T. 2009. Decadal prediction: Can it be skillful?
Bull. Amer. Meteorol. Soc. 90: 1467–1485.
Minobe S, Kuwano-Yoshida A, Komori N, Xie S-P, Small RJ. 2008.
Influence of theGulf Stream on the troposphere. Nature 452: 206–210.
Miyakoda K, Gordon T, Caverly R, Stern W, Sirutis J, Bourke W. 1983.
Simulation of a blocking event in January 1977. Mon. Weather Rev.
111: 846–869.
Murphy JM, Sexton DM, Burnett DN, Jones GS, Webb MJ, Collins M,
Stainforth DA. 2004. Quantification of modelling uncertainty in a
large ensemble of climate change simulations. Nature 430: 768–772.
Nakamura H, Sampe T, Goto A, Ohfuchi W, Xie S. 2008. On the
importance of mid-latitude oceanic frontal zones for the mean state
and dominant variability in the tropospheric circulation. Geophys.
Res. Lett. 35: L15709, DOI: 10.1029/2008GL034010
NastromGD, Gage KS. 1985. A climatology of atmospheric wavenumber
spectra of wind and temperature observed by commercial aircraft. J.
Atmos. Sci. 42: 950–960.
Palmer TN. 2012. Towards the probabilistic Earth-system simulator:
a vision for the future of weather and climate prediction. Q. J. R.
Meteorol. Soc. In press. DOI: 10.1002/qj.1923
Palmer TN, Webster PJ. 1995. Towards a unified approach to
climate and weather prediction. In Global Change: Proc. of the First
Demetra Meeting on Climate Change,Chianciano Terme, Italy, 28–31
October 1991. EUR 15158 EN. European Commission: Brussels.
265–280.
Parker DE, Folland CK, Scaife AA, Knight JR, Baines P, Dong B.
2007. Decadal to multidecadal variability and the climate change
background. J. Geophys. Res. 112: D18115.
Pohlmann H, Jungclaus JH, Kohl A, Stammer D, Marotzke J. 2009.
Initializing decadal climate predictions with the GECCO oceanic
synthesis. J. Climate 22: 3926–3928.
Rashid HA, Hendon HH, Wheeler MC, Alves O. 2011. Prediction of the
Madden–Julian Oscillation with the POAMA dynamical prediction
system. Clim. Dyn. 36: 649–661.
Rodwell MR, Hoskins BJ. 1996. Monsoons and the dynamics of deserts.
Q. J. R. Meteorol. Soc. 122: 1385–1404.
Rowntree PR. 1972. The influence of tropical east Pacific Ocean
temperatures on the atmosphere. Q. J. R. Meteorol. Soc. 98: 290–321.
Shapiro MA, Shukla J, Brunet G, Nobre C, B´eland M, Dole R,
Trenberth KE, Anthes R, Asrar G, Barrie L, Bougeault P, Brasseur G,
BurridgeDM, BusalacchiA,Caughey J, Chen D, Church J, EnomotoT,
Hoskins BJ, Hov Ø, Laing A, Le Treut H, Marotzke J, McBean G,
Meehl G, Miller M, Mills B, Mitchell JM, Moncrieff M, Nakazawa T,
OlafssonH, Palmer TN, Parsons D, Rogers D, Simmons A, Troccoli A,
Toth Z, Uccellini L, Velden C, Wallace JM. 2010. An Earth-system
prediction initiative for the twenty-first century. Bull. Amer. Meteorol.
Soc. 91: 1377–1388.
Shukla J. 1981. Dynamical predictability of monthly means. J. Atmos.
Sci. 38: 2547–2572.
Shukla J. 1998. Predictability in the midst of chaos: A scientific basis for
climate forecasting. Science 282: 728–731.
Slingo J, Palmer TN. 2011. Uncertainty in weather and climate
prediction. Phil. Trans. R. Soc. London A 369: 4751–4767. DOI:
10.1098/rsta.2011.0161
Smith DM, Eade R, Dunstone NJ, Fereday D, Murphy JM, Pohlmann H,
Scaife AA. 2010. Skilful multi-year predictions of hurricane frequency.
Nature Geosci. 3: 846–849.
Solomon A, Goddard L, Kumar A, Carton J, Deser C, Fukumori I,
Greene AM, Hegerl G, Kirtman B, Kushnir Y, Newman M, Smith D,
Vimont D, Delworth T, Meehl GA, Stockdale T. 2011. Distinguishing
the roles of natural and anthropogenically forced decadal climate
variability. Bull. Amer. Meteorol. Soc. 92: 141–156.
Thompson DWJ, Wallace JM. 2000. Annular modes in the extratropical
circulation. Part I: Month-to-month variability. J. Climate 13:
1000–1016.
Vitart F, Huddleston MR,D´equ´eM, Palmer TN, Stockdale T, Davey MK,
Ineson S, Weisheimer A. 2007. Dynamically based seasonal forecasts
of Atlantic tropical storm activity issued in June by EuroSIP. Geophys.
Res. Lett. 34: L16815, DOI: 10.1029/2007GL030740
Wallace JM, Thompson DWJ. 2002. The Pacific center of action of the
Northern Hemisphere Annular Mode: Real or artifact? J. Climate 15:
1987–1991.
WCRP. 2005. The World Climate Research Programme Strategic
Framework 2005-15. WCRP-123, WMO/TD-No.1291. World
Meteorological Organization: Geneva.
Webber BGM, Matthews AJ, Heywood KJ, Stevens DP. 2011. Ocean
Rossby waves as a triggering mechanism for primary Madden–Julian
Oscillation events. Q. J. R. Meteorol. Soc. 138: 514–527.
Weisheimer A, Doblas-Reyes FJ, Jung T, Palmer TN. 2011. On the
predictability of the extreme summer 2003 over Europe. Geophys. Res.
Lett. 38: L05704. DOI: 10.1029/2010GL046455
Wheeler M, Kiladis GN. 1999. Convectively coupled equatorial waves:
Analysis of clouds and temperature in the wavenumber–frequency
domain. J. Atmos. Sci. 56: 374–399.
Woollings T, Lockwood M, Masato G, Bell C, Gray L. 2010. Enhanced
signature of solar variability in Eurasian winter climate. Geophys. Res.
Lett. 37: L20805.
Wu Z, Huang NE, Wallace JM, Smoliak BV, Chen X. 2011. On the
time-vaying trend in global-mean surface temperature. Clim. Dyn. 37:
759–773. DOI: 10.1007/s00382-011-1128-8
Yang G-Y, Hoskins BJ, Slingo JM. 2007. Convectively coupled equatorial
waves. Part III: Synthesis structures and their forcing and evolution.
J. Atmos. Sci. 64: 3438–3451.
Yeh T-C. 1949. On energy dispersion in the atmosphere. J. Meteorol. 6:
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The potential for skill across the range of the seamless weather-climate prediction problem: a stimulus for our scienceHoskins, B. (2013) The potential for skill across the range of the seamless weather-climate prediction problem: a stimulus for our science. Quarterly Journal of the Royal Meteorological Society, 139 (672). pp. 573-584. ISSN 1477-870X Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1002/qj.1991 Abstract/SummaryPredictability is considered in the context of the seamless weather-climate prediction problem, and the notion is developed that there can be predictive power on all time-scales. On all scales there are phenomena that occur as well as longer time-scales and external conditions that should combine to give some predictability. To what extent this theoretical predictability may actually be realised and, further, to what extent it may be useful is not clear. However the potential should provide a stimulus to, and high profile for, our science and its application for many years.
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