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Allen, M. (1999). Do-it-yourself climate prediction. Nature 401, 642,

Bacciagaluppi, G. and A. Valentini (2009). Quantum theory at the crossroads: Reconsidering the 1927 Solvay conference. Cambridge U. Press, New York, 2009.

Barkmeijer, J., Buizza, R., & Palmer, T. N. (1999). 3D-Var Hessian singular vectors and their potential use in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc., 125, 2333-2351.

Barkmeijer, J., Buizza, R., Palmer, T. N., Puri, K., & Mahfouf, J.-F. (2001). Tropical singular vectors computed with linearized diabatic physics. Q. J. R. Meteorol. Soc., 127, 685-708.

Bell, J.S. (1964). On the Einstein Podolsky Rosen paradox. Physics Physique Fizika, 1(3):195.

Ben Bouallegue, Z., T. Haiden and D. Richardson (2018). The diagonal score: definitions, properties, and interpretations. Q. J. R. Meteorol. Soc., 144, 1463-1473,

Benacchio, Tommaso, et al. (2021). Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. The International Journal of High Performance Computing Applications, 35.4: 285-311.

Berner, J., Shutts, G. J., Leutbecher, M.,& Palmer, T. N. (2009). A spectral stochastic kinetic energy backscatter scheme and its impact on flow-dependent predictability in the ECMWF ensemble prediction system. Journal of the Atmospheric Sciences, 66(3), 603-626.

Berner, J., Achatz, U., Batte, L., Bengtsson, L., De La Camara, A., Christensen, H. M., ... & Yano, J. I. (2017). Stochastic parameterization: Toward a new view of weather and climate models. Bulletin of the American Meteorological Society, 98(3), 565-588.

Brankovic C., T.N. Palmer, F. Molteni, S. Tibaldi, U. Cubasch (1990). Extended-range predictions with ECMWF models: Time-lagged ensemble forecasting. Q. J. R. Meteorol. Soc., 116, 867-912.

Buizza, R., Tribbia, J., Molteni, F., & Palmer, T. N. (1993). Computation of optimal unstable structures for a numerical weather prediction model. Tellus, 45A, 388-407.

Buizza, R. (1994a). Sensitivity of Optimal Unstable Structures. Q. J. R. Meteorol. Soc., 120, 429-451.

Buizza, R. (1994). Localization of optimal perturbations using a projection operator. Q. J. R. Meteor. Soc., 120, 1647-1682.

Buizza, R., & Palmer, T. N. (1995). The singular-vector structure of the atmospheric general circulation. J. Atmos. Sci., 52, 9, 1434-1456.

Buizza, R., & Montani, A. (1999). Targeting observations using singular vectors. J. Atmos. Sci., 56, 2965-2985.

Buizza, R., Miller, M., & Palmer, T. N. (1999). Stochastic representation of model uncertainties in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc., 125, 2887-2908.

Buizza, R., Leutbecher, M., & Isaksen, L. (2008). Potential use of an ensemble of analyses in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc., 134, 2051-2066.

Buizza, R. (2018). Introduction to the Special Issue on ‘25 years of ensemble forecasting’. Q. J. R. Meteorol. Soc., 1-11.

Chantry, M., Hatfield, S., Dueben, P., Polichtchouk, I., & Palmer, T. (2021). Machine learning emulation of gravity wave drag in numerical weather forecasting. Journal of Advances in Modeling Earth Systems, 13, e2021MS002477.

Chantry, Matthew, et al. (2021). Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI. Philosophical Transactions of the Royal Society A 379.2194. 20200083.

Corti, S., F. Molteni and T.N. Palmer (1999). Signature of recent climate change in frequencies of natural atmospheric circulation regimes. Nature, 398, 799-802.

Coutinho, M. M., Hoskins, B. J., & Buizza, R. (2004). The influence of physical processes on extratropical singular vectors. J. Atmos. Sci., 61, 195-209.

Doblas-Reyes FJ, Weisheimer A, Déqué M, Keenlyside N, McVean M, Murphy JM, Rogel P, Smith D, Palmer TN (2009). Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts. Quart. J. Roy. Met. Soc. 135: 1538-1559.

Dorrington, J, Finney, I, Palmer, T, Weisheimer, A. (2020). Beyond skill scores: exploring sub-seasonal forecast value through a case-study of French month-ahead energy prediction. Q. J. R. Meteorol Soc., 146: 3623-3637.

Dorrington, J., Strommen, K. and Fabiano, F. (2022). CMIP6 models trend towards less persistent European blocking regimes in a warming climate. Accepted for publication in Geophysical Research Letters (2022).

Einstein, A. (1947). Letter to Max Born on March 3, 1947. In Albert Einstein, Hedwig Born, Max Born, Bertrand Russell, and Werner Heisenberg, Editors, Briefwechsel: 1916-1955. Nymphenburger Verlagshandlung, 1969.

Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation. Geosci. Model Dev. 9: 1937-1958.

Farrell B.F., (1989). Optimal excitation of baroclinic waves. J. Atmos. Sci., 46, 1193-1206.

Folland CK, Woodcock A. (1986). Experimental monthly long-range forecasts for the United Kingdom. Part I. Description of the forecasting system. Met. Mag. 115: 301-318.

Folland CK, Woodcock A, Varah LD (1986). Experimental monthly long-range forecasts for the United Kingdom. Part III. Skill of the monthly forecasts. Met. Mag. 115: 377-958.

Hoffman R.N. and E. Kalnay (1983). Lagged average forecasting, an alternative to Monte Carlo forecasting. Tellus, 35A, 100-118.

Hollingsworth A. (1979). An experiment in Monte Carlo forecasting. Proceedings of the ECMWF Workshop on Stochastic-Dynamic Forecasting (17-19 Oct. 1979), pp. 65-85.

Holton, J.R. (1980). Wave propagation and transport in the middle atmosphere. Phil. Trans. Roy. Soc. A, 296, 73–85.

Jacob, F. (1988): The statue within: an autobiography. New York: Cold Spring Harbor Laboratory Press.

Jung, T., Palmer, T. N., & Shutts, G. J. (2005). Influence of a stochastic parameterization on the frequency of occurrence of North Pacific weather regimes in the ECMWF model. Geophysical Research Letters, 32(23).

Kendon E, Short C, Pope J, Chan S, Wilkinson J, Tucker S, Bett P, Harris G. (2021). Update to UKCP Local (2.2km) projections.

Klinker, E. and Sardeshmukh, P. (1992). The Diagnosis of Mechanical Dissipation in the Atmosphere from Large-Scale Balance Requirements. Journal of the Atmospheric Sciences. 49:7.<0608:TDOMDI>2.0.CO;2.

Klocke, D. and Rodwell, M.J. (2014), A comparison of two numerical weather prediction methods for diagnosing fast-physics errors in climate models. Q.J.R. Meteorol. Soc., 140: 517-524.

Klöwer, M., Hatfield, S., Croci, M., Düben, P. D., & Palmer, T. N. (2022). Fluid simulations accelerated with 16 bits: Approaching 4x speedup on A64FX by squeezing ShallowWaters.jl into Float16. Journal of Advances in Modeling Earth Systems, 14, e2021MS002684.

Lacarra J-F. and O. Talagrand (1988). Short-range evolution of small perturbations in a barotropic model. Tellus, 40A, 81-95.

Lang, S.T.K., Dawson, A., Diamantakis, M., Dueben, P., Hatfield, S., Leutbecher, M., et al. (2021). More accuracy with less precision. Q. J. R. Meteorol. Soc., 147( 741, 4358– 4370. Available from:

Maryon RH, Storey AM (1985). A multivariate statistical model for forecasting anomalies of half-monthly mean surface pressure. J. Climat. 5: 561-578.

Mansfield DA (1986). The skill of dynamical long-range forecasts, including the effect of sea surface temperature anomalies. Q. J. R. Meteorol. Soc. 112: 1145-1176.

McIntyre M.E. (1982). How well do we understand the dynamics of stratospheric warmings? J. Meteorol. Soc. Japan 60, 37–65.

McIntyre M.E., Palmer T.N. (1983). Breaking planetary waves in the stratosphere. Nature 305, 593–600.

McIntyre, M.E., Palmer T.N. (1984). The “surf zone” in the stratosphere. J. Atmos. Terr. Phys. 46, 825–49.

Miyakoda K, Gordon T, Caverly R, Stern W, Siritus J, Bourke W. (1983). Simulation of a blocking event in January 1977. Mon. Wea. Rev. 111: 846-869.

Molteni, F., U. Cubasch and S. Tibaldi (1988). 30 and 60-day forecast experiments with the ECMWF spectral models. In: “Persistent meteo-oceanographic anomalies and teleconnections”, Pontificiae Academiae Scientiarum Scripta Varia no. 69, Vatican City, 505-555.

Molteni F. and T.N. Palmer (1993). Predictability and finite-time instability of the northern winter circulation. Q. J. R. Meteorol. Soc., 119, 269-298.

Molteni F., R. Buizza, T.N. Palmer and T. Petroliagis (1996). The ECMWF ensemble prediction system:methodology and validation. Q. J. R. Meteorol. Soc., 122, 73-119.

Mureau R., F. Molteni and T.N. Palmer (1993). Ensemble prediction using dynamically conditioned perturbations. Q. J. R. Meteorol. Soc., 119, 299-323.

Murphy JM, Palmer TN (1986). Experimental monthly long-range forecasts for the United Kingdom. Part II. A real-time long-range forecast by an ensemble of numerical integrations. Met. Mag. 115: 337-349.

Murphy JM (1988). The impact of ensemble forecasts on predictability. Q. J. R. Meteorol. Soc. 114: 463-493.

Murphy JM (1990). Assessment of the practical utility of extended range ensemble forecasts. Q. J. R. Meteorol. Soc. 116: 89-125.

Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth, DA (2004). Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 429: 768-772.

Murphy JM, GR Harris, DMH Sexton, EJ Kendon, PE Bett, RT Clark, KE Eagle, G Fosser, F Fung, JA Lowe, RE McDonald, RN McInnes, CF McSweeney, JFB Mitchell, JW Rostron, HE Thornton, S Tucker, K Yamazaki (2018). UKCP18 Land Projections: Science Report.

Ollinaho, P., Lock, S. J., Leutbecher, M., Bechtold, P., Beljaars, A., Bozzo, A., ... & Sandu, I. (2017). Towards process‐level representation of model uncertainties: stochastically perturbed parametrizations in the ECMWF ensemble. Q. J. R. Meteorol. Soc., 143(702), 408-422.

Palmer, T.N. (1981). Diagnostic study of a wave- number-2 stratospheric sudden warming in a transformed Eulerian-mean formalism. J. Atmos. Sci., 38, 844-855.

Palmer TN, Zhaobo S (1985). A modelling and observational study of the relationship between sea surface temperature in the north-west Atlantic and the atmospheric general circulation. Q. J. R. Meteorol. Soc. 111: 947-975.

Palmer TN, Shutts GJ, Swinbank R (1986). Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parametrization. Q. J. R. Meteorol. Soc. 112: 1031-1069.

Palmer, T. N. (1993). A nonlinear dynamical perspective on climate change. Weather 48.10: 314-326.

Palmer, T. N., Gelaro, R., Barkmeijer, J., & Buizza, R. (1998). Singular vectors, metrics, and adaptive observations. J. Atmos. Sci., 55, 6, 633-653.

Palmer, T. N. (2001). A nonlinear dynamical perspective on model error: A proposal for non‐local stochastic‐dynamic parametrization in weather and climate prediction models. Q. J. R. Meteorol. Soc., 127(572), 279-304.

Palmer, T. N., F. J. Doblas-Reyes, A. Weisheimer, and M. J. Rodwell. (2008). Toward Seamless Prediction: Calibration of Climate Change Projections Using Seasonal Forecasts. Bulletin of the American Meteorological Society 89.4: 459-470.

Palmer, T. N., Buizza, R., Doblas-Reyes, F., Jung, T., Leutbecher, M., Shutts, G., M STeinheimer & Weisheimer, A. (2009). Stochastic parametrization and model uncertainty. ECMWF TechMemo, 598.

Palmer, T. (2009). The Invariant Set Postulate: a new geometric framework for the foundations of quantum theory and the role played by gravity. Proceedings of the Royal Society A. 465 (2110): 3165 3185.

Palmer, T.N. (2011). The invariant set hypothesis: a new geometric framework for the foundations of quantum theory and the role played by gravity. Electronic Notes in Theoretical Computer Science, 270(2):115–119.

Palmer, T. (2020). Human Creativity and Consciousness: Unintended Consequences of the Brain’s Extraordinary Energy Efficiency? Entropy, 22, 281.

Palmer, T. The Primacy of Doubt. OUP Oxford, Hardcover – 18 Oct. 2022.

Pathak, Jaideep, et al. (2022). Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators. arXiv preprint arXiv:2202.11214.

Penland, C., & Sardeshmukh, P. D. (1995). The optimal growth of tropical sea surface temperature anomalies. Journal of Climate, 8(8), 1999-2024.

Rabier, F., Järvinen, H., Klinker, E., Mahfouf, J.-F., and Simmons, A. (2000). The ECMWF operational implementation of four-dimensional variational assimilation. I: Experimental results with simplified physics, Q. J. R. Meteorol. Soc., 126, 1143–1170,

Rasp, S., Dueben, P. D., Scher, S., Weyn, J. A., Mouatadid, S., & Thuerey, N. (2020). WeatherBench: A benchmark data set for data-driven weather forecasting. Journal of Advances in Modeling Earth Systems, 12, e2020MS002203.

Rodwell, M.J. and Jung, T. (2008). Understanding the local and global impacts of model physics changes: an aerosol example. Q. J. R. Meteorol. Soc., 134: 1479-1497.

Rodwell, M. J., Lang, S. T. K., Ingleby, N. B., Bormann, N., Hólm, E., Rabier, F., Richardson, D. S., and Yamaguchi, M. (2016). Reliability in ensemble data assimilation, Q. J. R. Meteorol. Soc., 142, 443–454,

Rodwell, M.J. and Palmer, T.N. (2007). Using numerical weather prediction to assess climate models. Q. J. R. Meteorol. Soc., 133: 129-146.

Rodwell, M. J., Richardson, D. S., Parsons, D. B., and Wernli, H. (2018). Flow-Dependent Reliability: A Path to More Skillful Ensemble Forecasts, Bull. Amer. Meteor. Soc., 99, 1015–1026,

Rodwell, M. J. and Wernli, H. (2022): The Cyclogenesis Butterfly: Uncertainty growth and forecast reliability during extratropical cyclogenesis, Weather Clim. Dynam. Discuss. [preprint],, in review.

Shukla J. (1981). Dynamical predictability of monthly means. J. Atmos. Sci. 38:2547-2572.

Shutts, G. (2005). A kinetic energy backscatter algorithm for use in ensemble prediction systems. Q. J. R. Meteorol. Soc., 131(612), 3079-3102.

Slingo A. (Ed.), 1985: Handbook of the Meteorological Office 11-layer atmospheric general circulation model. Volume 1: model description. Dynamical Climatology Technical Note No. 29, Meteorological Office.

Smith DM, Cusack S, Colman AW, Folland CK, Harris GR, Murphy JM (2007). Improved surface temperature prediction for the coming decade from a global climate model. Science 317: 796-799.

Smith D, Scaife A, Boer G, Caian M, Doblas-Reyes F, Guemas V, Hawkins E, Hazeleger W. Hermanson L, Ho C, Ishii M, Kharin V, Kimoto M, Kirtman B, Lean J, Matei D, Merryfield W, Müller W, Pohlmann H, Rosati A, Wouters B, Wyser K, (2013). Real-time multi-model decadal predictions. Clim. Dyn. 41: 2875-2888.

Stainforth, D., Aina, T., Christensen, C. et al. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature 433, 403–406,

Stanger J, Finney I, Weisheimer A, Palmer T. (2019). Optimising the use of ensemble information in numerical weather forecasts of wind power generation. Environ. Res. Lett., 14, 124086.

Strommen, K, and Palmer, T. N. (2019). Signal and noise in regime systems: A hypothesis on the predictability of the North Atlantic Oscillation. Q. J. R. Meteorol. Soc. 145.718 (2019): 147-163.

Strommen, K., Watson, P. A., & Palmer, T. N. (2019). The impact of a stochastic parameterization scheme on climate sensitivity in EC‐Earth. Journal of Geophysical Research: Atmospheres, 124(23), 12726-12740.

Summhammer, J. et al (2018). Quantum Dynamics and Non-Local Effects Behind Ion Transition States during Permeation in Membrane Channel Proteins. Entropy, 20, 558.

Tennie, Felix, and Tim Palmer (2022). Quantum Computers for Weather and Climate Prediction: The Good, the Bad and the Noisy. arXiv preprint arXiv:2210.17460.

Wallace JM, Gutzler DS, (1981). Teleconnections in the geopotential height field during the northern hemisphere winter. Mon. Wea. Rev. 109: 784-812.

Wedi, N. P., Polichtchouk, I., Dueben, P., Anantharaj, V. G., Bauer, P., Boussetta, S., et al. (2020). A baseline for global weather and climate simulations at 1 km resolution. Journal of Advances in Modeling Earth Systems, 12, e2020MS002192.

Weisheimer, A., Corti, S., Palmer, T., & Vitart, F. (2014). Addressing model error through atmospheric stochastic physical parametrizations: Impact on the coupled ECMWF seasonal forecasting system. Philosophical Transactions of the Royal Society A, 372(2018), 20130290.



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