Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-17T21:37:36.505Z Has data issue: false hasContentIssue false

Chapter 1 - Predictability of weather and climate: from theory to practice

Published online by Cambridge University Press:  03 December 2009

T. N. Palmer
Affiliation:
European Centre for Medium-Range Weather Forecasts, Reading
Tim Palmer
Affiliation:
European Centre for Medium-Range Weather Forecasts
Renate Hagedorn
Affiliation:
European Centre for Medium-Range Weather Forecasts
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Barnett, T. P., Pierce, D. W., Latif, M., Dommenget, D. and Saravanan, R. (1999). Interdecadal interactions between the tropics and midlatitudes in the Pacific basin. Geophys. Res. Lett., 26, 615–18CrossRefGoogle Scholar
Broecker, W. (1995). Chaotic climate. Sci. Am., November, 62–8CrossRefGoogle Scholar
Buizza, R. and Palmer, T. N. (1995). The singular vector structure of the atmospheric global circulation. J. Atmos. Sci., 52, 1434–562.0.CO;2>CrossRefGoogle Scholar
Buizza, R., Miller, M. J. and Palmer, T. N. (1999). Stochastic simulation of model uncertainties in the ECMWF Ensemble Prediction System. Quart. J. Roy. Meteor. Soc., 125, 2887–908CrossRefGoogle Scholar
Buizza, R., Houtekamer, P. L., Toth, Z., Pellerin, G., Wei, M. and Zhu, Y. (2003). Assessment of the status of global ensemble prediction. Proceedings of 2002 ECMWF Seminar on Predictability of Weather and Climate. ECMWFGoogle Scholar
Buizza, R., Houtekamer, P. L., Toth, Z., Pellerin, G., Wei, M. and Zhu, Y. (2005). A comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems. Mon. Wea. Rev., 133, 1076–97CrossRefGoogle Scholar
Courtier, P., Andersson, E., Heckley, W., et al. (1998). The ECMWF implementation of three dimensional variational assimilation (3DVAR). I: Formulation. Quart. J. Roy. Meteor. Soc., 124, 1783–808Google Scholar
Doblas-Reyes, F. J., , M. Deque and Piedlievre, J.-P. (2000). Multi-model spread and probabilistic seasonal forecasts in PROVOST. Quart. J. Roy. Meteor. Soc., 126, 2069–88CrossRefGoogle Scholar
Folland, C. K., Palmer, T. N. and Parker, D. E. (1986). Sahel rainfall and worldwide sea surface temperatures 1901–85. Nature, 320, 602–7CrossRefGoogle Scholar
Frederiksen, J. S. and Davies, A. G. (1997). Eddy viscosity and stochastic backscatter parameterizations on the sphere for atmospheric circulation models. J. Atmos. Sci., 54, 2475–922.0.CO;2>CrossRefGoogle Scholar
Griffies, S. M. and Bryan, K. (1997). A predictability study of simulated North Atlantic multidecadal variability. Clim. Dynam., 13, 459–87CrossRefGoogle Scholar
Hoffman, R. and Kalnay, E. (1983). Lagged average forecasting, alternative to Monte Carlo forecasting. Tellus, 35A, 100–18CrossRefGoogle Scholar
Houtekamer, P., Lefaivre, L., Derome, J., Ritchie, H. and Mitchell, H. (1996). A system simulation approach to ensemble prediction. Mon. Weather Rev., 124, 1225–422.0.CO;2>CrossRefGoogle Scholar
Jung, T., Palmer, T. N. and Shutts, G. J. (2005). Influence of a stochastic parameterization on the frequency of occurrence of North Pacific weather regimes in the ECMWF model. Geophys. Res. Lett., 32, L23811CrossRefGoogle Scholar
Klinker, E. and Sardeshmukh, P. D. (1992). The diagnosis of mechanical dissipation in the atmosphere from large-scale balance requirements. J. Atmos. Sci., 49, 608–272.0.CO;2>CrossRefGoogle Scholar
Khouider, B., Majda, A. J. and Katsoulakis, M. A. (2003). Coarse-grained stochastic models for tropical convection and climate. Proc. Natl. Acad. Sci. USA, 100, 11941–6CrossRefGoogle ScholarPubMed
Landerer, F., Jungclaus, J., Marotzke, J. (2006). Steric and dynamic change in response to the A1B scenario integration in the ECHAM5/MPI-OM coupled climate model. J. Phys. Oceanogr., in pressGoogle Scholar
Leith, C. (1990). Stochastic backscatter in a sub-gridscale model: plane shear mixing layer. Phys. Fluids A, 2, 297–9CrossRefGoogle Scholar
Lewis, J. M. (2005). Roots of ensemble forecasting. Mon. Weather Rev., 133, 1865–85CrossRefGoogle Scholar
Lorenz, E. N. (1963). Deterministic nonperiodic flow. J. Atmos. Sci., 42, 433–71Google Scholar
Lorenz, E. N. (1965). A study of the predictability of the 28-variable atmospheric model. Tellus, 17, 321–33CrossRefGoogle Scholar
Lorenz, E. N. (1975). Climatic predictability. In The Physical Basis of Climate and Climate Modelling. WMO GARP Publication Series No. 16. World Meteorological OrganisationGoogle Scholar
Meehl, G. A., Boer, G. J., Covey, C., Latif, M. and Stouffer, R. J. (2000). The Coupled model intercomparison project. Bull. Am. Meteorol. Soc., 81, 3132.3.CO;2>CrossRefGoogle Scholar
Miyakoda, K., Sirutis, J. and Ploshay, J. (1986). One month forecast experiments – without anomaly boundary forcings. Mon. Weather Rev., 114, 1145–762.0.CO;2>CrossRefGoogle Scholar
Molteni, F. and Palmer, T. N. (1993). Predictability and non-modal finite-time instability of the northern winter circulation. Quart. J. Roy. Meteor. Soc., 119, 269–98CrossRefGoogle Scholar
Molteni, F., Buizza, R., Petroliagis, T. and Palmer, T. N. (1996). The ECMWF ensemble prediction system: methodology and validation. Quart. J. Roy. Meteor. Soc., 122, 73–119CrossRefGoogle Scholar
Murphy, A. H. (1977). The value of climatological, categorical and probabilistic forecasts in the cost-loss ratio situation. Mon. Weather Rev., 105, 803–162.0.CO;2>CrossRefGoogle Scholar
Murphy, J. M. and Palmer, T. N. (1986). Experimental monthly long-range forecasts for the United Kingdom. II: A real time long-range forecast by an ensemble of numerical integrations. Meteorol. Mag., 115, 337–49Google Scholar
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., et al. (2004). Quantifying uncertainties in climate change using a large ensemble of global climate model predictions. Nature, 430, 768–72CrossRefGoogle Scholar
Nastrom, G. D. and Gage, K. S. (1985). A climatology of atmospheric wavenumber spectra of wind and temperature observed by commercial aircraft. J. Atmos. Sci., 42, 950–602.0.CO;2>CrossRefGoogle Scholar
Palmer, T. (1988). Medium and extended range predictability and stability of the Pacific/North American mode. Quart. J. Roy. Meteor. Soc., 114, 691–713CrossRefGoogle Scholar
Palmer, T. (2001). A nonlinear dynamical perspective on model error: a proposal for non-local stochastic-dynamic parametrisation in weather and climate prediction models. Quart. J. Roy. Meteor. Soc., 127, 279–304Google Scholar
Palmer, T. (2002). The economic value of ensemble forecasts as a tool for risk assessment: from days to decades. Quart. J. Roy. Meteor. Soc., 128, 747–74CrossRefGoogle Scholar
Palmer, T. N. and Shukla, J. (2000). Editorial to DSP/PROVOST special issue, Quart. J. Roy. Meteor. Soc., 126, 1989–90CrossRefGoogle Scholar
Palmer, T. N. and Räisänen, J. (2002). Quantifying the risk of extreme seasonal precipitation events in a changing climate. Nature, 415, 512CrossRefGoogle Scholar
Palmer, T. N., Brankovic, C., Molteni, F., et al. (1990). The European Centre for Medium-Range Weather Forecasts (ECMWF) program on extended-range prediction. Bull. Am. Meteorol. Soc., 71, 1317–302.0.CO;2>CrossRefGoogle Scholar
Palmer, T. N., Molteni, F., Mureau, R., Buizza, R., Chapelet, P. and Tribbia, J. (1993). Ensemble prediction. In ECMWF 1992 Seminar: Validation of Models over Europe. ECMWFGoogle Scholar
Palmer, T. N., Brankovic, C. and Richardson, D. S. (2000). A probability and decision-model analysis of PROVOST seasonal multimodel ensemble integrations. Quart. J. Roy. Meteor. Soc., 126, 2013–34CrossRefGoogle Scholar
Palmer, T. N., Alessandri, A., Andersen, U., et al. (2004). Development of a European multi-model ensemble system for seasonal to inter-annual prediction. Bull. Am. Meteorol. Soc., 85, 853–72CrossRefGoogle Scholar
Palmer, T. N., Shutts, G. J., Hagedorn, R., Doblas-Reyes, F. J., Jung, T. and Leutbecher, M. (2005). Representing model uncertainty in weather and climate prediction. Ann. Rev. Earth Planet. Sci., 33, 163–93CrossRefGoogle Scholar
Reynolds, C. and Palmer, T. N. (1998). Decaying singular vectors and their impact on analysis and forecast correction. J. Atmos. Sci., 55, 3005–232.0.CO;2>CrossRefGoogle Scholar
Rodwell, M. J. and Palmer, T. N. (2006). Assessing model physics with initial forecast tendencies: application to climate change uncertainty. Quart. J. Roy. Meteor. Soc., SubmittedGoogle Scholar
Shukla, J. and Wallace, J. M. (1983). Numerical simulation of the atmospheric response to equatorial Pacific sea surface temperature anomalies. J. Atmos. Sci., 40, 1613–302.0.CO;2>CrossRefGoogle Scholar
Shutts, G. J. (2005). A kinetic energy backscatter algorithm for use in ensemble prediction systems. Quart. J. Roy. Meteor. Soc., 131, 3079–102CrossRefGoogle Scholar
Shutts, G. J. and , T. N. Palmer (2004). The use of high-resolution numerical simulations of tropical circulation to calibrate stochastic physics schemes. In Proceedings of ECMWF Workshop on Intra-seasonal Variability. ECMWFGoogle Scholar
Shutts, G. J. and , T. N. Palmer (2006). Convective forcing fluctuations in a cloud-resolving model: relevance to the stochastic parametrization problem. J. Clim., in pressGoogle Scholar
Smith, D. M., Colman, A. W., Cusack, S., Folland, C. K., Ineson, S. and Murphy, J. M. (2006). Predicting surface temperature for the coming decade using a global climate model. Nature, in pressGoogle Scholar
Stainforth, D. A., Aina, T., Christensen, C., et al. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433, 403–6CrossRefGoogle ScholarPubMed
Stockdale, T. N., Anderson, D. L. T., Alves, J. O. S. and Balmaseda, M. A. (1998). Global seasonal rainfall forecasts using a coupled ocean-atmosphere model. Nature, 392, 370–3CrossRefGoogle Scholar
Straus, D. M. and Shukla, J. (2000). Distinguishing between the SST-forced variability and internal variability in mid-latitudes: analysis of observations and GCM simulations. Quart. J. Roy. Meteor. Soc., 126, 2323–50CrossRefGoogle Scholar
Toth, Z. and Kalnay, E. (1993). Ensemble forecasting at NMC: the generation of perturbations. Bull. Am. Meteorol. Soc., 74, 2317–302.0.CO;2>CrossRefGoogle Scholar
Vitart, F. (2004). Monthly forecasting at ECMWF. Mon. Weather Rev., 132, 2761–79CrossRefGoogle Scholar
Waliser, A., Arpagaus, M., Leutbecher, M. and Appenzeller, C. (2006). The impact of moist singular vectors and horizontal resolution on short-range limited-area ensemble forecasts for two European winter storms. Mon. Weather Rev., in pressCrossRefGoogle Scholar
Wilson, S. (2000). Launching the Argo armada. Oceanus, 42, 17–19Google Scholar
Wolfram, S. (2002). A New Kind of Science. Wolfram Media IncGoogle Scholar
Zebiak, S. and Cane, M. (1987). A model of the El Niño-Southern Oscillation. Mon. Weather Rev., 115, 2262–782.0.CO;2>CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×