Article Type:
Research Article

A Laboratory Study of the Benefits of Including Uncertainty Information in Weather Forecasts

Mark S. Roulston Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Mark S. Roulston in
Current site
Google Scholar
PubMed Close
,
Gary E. Bolton Laboratory for Economic Management and Auctions, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Gary E. Bolton in
Current site
Google Scholar
PubMed Close
,
Andrew N. Kleit Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Andrew N. Kleit in
Current site
Google Scholar
PubMed Close
, and
Addison L. Sears-Collins Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia

Search for other papers by Addison L. Sears-Collins in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Feb 2006
DOI:
https://doi.org/10.1175/WAF887.1
Page(s):
116–122
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

Modern operational methods of numerical weather prediction, such as “ensemble forecasting,” allow assessments of state-dependent predictability to be made. This means that forecast-specific estimates of the forecast standard errors are possible. Quantitative estimates of forecast uncertainty are often not communicated to the public as it is unclear what the value of this information will be to people who must make weather-dependent decisions. Using laboratory-based methods developed by experimental economists to study individual choice it is found that nonspecialists are able to make better decisions that increase their expected reward while reducing their exposure to risk, when provided with information about the day-to-day uncertainty associated with temperature forecasts. The experimental framework used herein may provide a useful tool for evaluating the effectiveness with which weather forecasts can be communicated to end users.

Corresponding author address: Mark S. Roulston, Met Office, FitzRoy Road, Exeter EX1 3PB, United Kingdom. Email: mark.roulston@metoffice.gov.uk

Abstract

Modern operational methods of numerical weather prediction, such as “ensemble forecasting,” allow assessments of state-dependent predictability to be made. This means that forecast-specific estimates of the forecast standard errors are possible. Quantitative estimates of forecast uncertainty are often not communicated to the public as it is unclear what the value of this information will be to people who must make weather-dependent decisions. Using laboratory-based methods developed by experimental economists to study individual choice it is found that nonspecialists are able to make better decisions that increase their expected reward while reducing their exposure to risk, when provided with information about the day-to-day uncertainty associated with temperature forecasts. The experimental framework used herein may provide a useful tool for evaluating the effectiveness with which weather forecasts can be communicated to end users.

Corresponding author address: Mark S. Roulston, Met Office, FitzRoy Road, Exeter EX1 3PB, United Kingdom. Email: mark.roulston@metoffice.gov.uk

Save
Cover Weather and Forecasting
Weather and Forecasting

  • AMS, 2002: Enhancing weather information with probability forecasts. Bull. Amer. Meteor. Soc., 83 , 450–452.

  • Arrow, K. J., 1971: Essays in the Theory of Risk-Bearing. Markham Publishing, 278 pp.

  • Cooper, D., Kagel J. H. , and Lo W. , 1999: Gaming against managers in incentive systems: Experimental results with Chinese students and Chinese managers. Amer. Econ. Rev., 89 , 781–804.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Davis, D. D., and Holt C. A. , Eds. 1992: Experimental Economics. Princeton University Press, 572 pp.

  • Houtekamer, P. L., Lefaivre L. , Derome J. , Ritchie H. , and Mitchell H. L. , 1996: A system simulation approach to ensemble prediction. Mon. Wea. Rev., 124 , 1225–1242.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kagel, J. H., and Roth A. E. , Eds. 1995: Handbook of Experimental Economics. Princeton University Press, 721 pp.

  • Molteni, F., Buizza R. , and Palmer T. N. , 1996: The ECMWF Ensemble Prediction System: Methodology and validation. Quart. J. Roy. Meteor. Soc., 122 , 73–119.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Murphy, A. H., and Winkler R. L. , 1971: Forecasters and probability forecasts: Some current problems. Bull. Amer. Meteor. Soc., 52 , 239–247.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Murphy, A. H., Lichtenstein S. , Fischhoff B. , and Winkler R. L. , 1980: Misinterpretations of precipitation probability forecasts. Bull. Amer. Meteor. Soc., 61 , 695–701.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Mylne, K. R., 2002: Decision-making from probability forecasts based on forecast value. Meteor. Appl., 9 , 307–315.

  • Palmer, T. N., 2000: Predicting uncertainty in forecasts of weather and climate. Rep. Prog. Phys., 63 , 71–116.

  • Palmer, T. N., 2002: The economic value of ensemble forecasts as a tool for risk assessment: From days to decades. Quart. J. Roy. Meteor. Soc., 128 , 747–774.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Richardson, D. S., 2001: Measures of skill and value of ensemble prediction systems, their interrelationship and the effect of ensemble size. Quart. J. Roy. Meteor. Soc., 127 , 2473–2489.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Richardson, D. S., 2003: Economic value and skill. Forecast Verification: A Practioner's Guide in Atmospheric Science, I. T. Jolliffe and D. B. Stephenson, Eds., John Wiley, 165–188.

    • Search Google Scholar
    • Export Citation

  • Roth, A. E., 2002: The economist as engineer: Game theory, experimental economics and computation as tools of design economics. Econometrica, 70 , 1341–1378.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rothschild, M., and Stiglitz J. E. , 1970: Increasing risk: 1. A definition. J. Econ. Theory, 2 , 225–243.

  • Stensrud, D. J., Brooks H. E. , Du J. , Rogers E. , and Tracton M. S. , 1999: Using ensembles for short-range forecasting. Mon. Wea. Rev., 127 , 433–446.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stewart, T. R., 1997: Forecast value: Descriptive decision studies. Economic Value of Weather and Climate Forecasts, R. W. Katz and A. H. Murphy, Eds., Cambridge University Press, 147–182.

    • Search Google Scholar
    • Export Citation

  • Suleiman, R., Budescu D. V. , Fischer I. , and Messick D. M. , 2004: Contemporary Psychological Research on Social Dilemmas. Cambridge University Press, 422 pp.

    • Search Google Scholar
    • Export Citation

  • Toth, Z., and Kalnay E. , 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125 , 3297–3319.

  • Wedekind, C., and Milinski M. , 2000: Cooperation through image scoring in humans. Science, 288 , 850–852.

  • Wong, T. F., and Yan Y. Y. , 2002: Perceptions of severe weather warnings in Hong Kong. Meteor. Appl., 9 , 377–382.

  • Zhu, Y., Toth Z. , Wobus R. , Richardson D. , and Mylne K. , 2002: The economic value of ensemble-based weather forecasts. Bull. Amer. Meteor. Soc., 83 , 73–83.

    • Crossref
    • Search Google Scholar
    • Export Citation