Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- Chapter 1 Predictability of weather and climate: from theory to practice
- Chapter 2 Predictability from a dynamical meteorological perspective
- Chapter 3 Predictability – a problem partly solved
- Chapter 4 The Liouville equation and atmospheric predictability
- Chapter 5 Application of generalised stability theory to deterministic and statistical prediction
- Chapter 6 Ensemble-based atmospheric data assimilation
- Chapter 7 Ensemble forecasting and data assimilation: two problems with the same solution?
- Chapter 8 Approximating optimal state estimation
- Chapter 9 Predictability past, predictability present
- Chapter 10 Predictability of coupled processes
- Chapter 11 Predictability of tropical intraseasonal variability
- Chapter 12 Predictability of seasonal climate variations: a pedagogical review
- Chapter 13 Predictability of the North Atlantic thermohaline circulation
- Chapter 14 On the predictability of flow-regime properties on interannual to interdecadal timescales
- Chapter 15 Model error in weather and climate forecasting
- Chapter 16 Observations, assimilation and the improvement of global weather prediction – some results from operational forecasting and ERA-40
- Chapter 17 The ECMWF Ensemble Prediction System
- Chapter 18 Limited-area ensemble forecasting: the COSMO-LEPS system
- Chapter 19 Operational seasonal prediction
- Chapter 20 Weather and seasonal climate forecasts using the superensemble approach
- Chapter 21 Predictability and targeted observations
- Chapter 22 The attributes of forecast systems: a general framework for the evaluation and calibration of weather forecasts
- Chapter 23 Predictability from a forecast provider's perspective
- Chapter 24 Ensemble forecasts: can they provide useful early warnings?
- Chapter 25 Predictability and economic value
- Chapter 26 A three-tier overlapping prediction scheme: tools for strategic and tactical decisions in the developing world
- Chapter 27 DEMETER and the application of seasonal forecasts
- Index
- Plate section
- References
Chapter 23 - Predictability from a forecast provider's perspective
Published online by Cambridge University Press: 03 December 2009
- Frontmatter
- Contents
- List of contributors
- Preface
- Chapter 1 Predictability of weather and climate: from theory to practice
- Chapter 2 Predictability from a dynamical meteorological perspective
- Chapter 3 Predictability – a problem partly solved
- Chapter 4 The Liouville equation and atmospheric predictability
- Chapter 5 Application of generalised stability theory to deterministic and statistical prediction
- Chapter 6 Ensemble-based atmospheric data assimilation
- Chapter 7 Ensemble forecasting and data assimilation: two problems with the same solution?
- Chapter 8 Approximating optimal state estimation
- Chapter 9 Predictability past, predictability present
- Chapter 10 Predictability of coupled processes
- Chapter 11 Predictability of tropical intraseasonal variability
- Chapter 12 Predictability of seasonal climate variations: a pedagogical review
- Chapter 13 Predictability of the North Atlantic thermohaline circulation
- Chapter 14 On the predictability of flow-regime properties on interannual to interdecadal timescales
- Chapter 15 Model error in weather and climate forecasting
- Chapter 16 Observations, assimilation and the improvement of global weather prediction – some results from operational forecasting and ERA-40
- Chapter 17 The ECMWF Ensemble Prediction System
- Chapter 18 Limited-area ensemble forecasting: the COSMO-LEPS system
- Chapter 19 Operational seasonal prediction
- Chapter 20 Weather and seasonal climate forecasts using the superensemble approach
- Chapter 21 Predictability and targeted observations
- Chapter 22 The attributes of forecast systems: a general framework for the evaluation and calibration of weather forecasts
- Chapter 23 Predictability from a forecast provider's perspective
- Chapter 24 Ensemble forecasts: can they provide useful early warnings?
- Chapter 25 Predictability and economic value
- Chapter 26 A three-tier overlapping prediction scheme: tools for strategic and tactical decisions in the developing world
- Chapter 27 DEMETER and the application of seasonal forecasts
- Index
- Plate section
- References
Summary
For a forecast provider, predictability means striking a balance between the needs of an end user to make decisions and the limitations of what is scientifically possible. Scientifically the best information is probabilistic, normally generated from ensemble forecasts, but to make effective use of this information we need to understand the decision-making process of the user. This chapter will discuss some of the issues related to the calculation of relevant probabilities, and how to transmit that information to users and help them with decision-making.
Introduction
Predictability is not a new issue for forecast providers, such as the UK Met Office. Forecasters have always dealt with uncertainty, usually describing it subjectively with terms such as ‘mainly in the north-west’, or ‘a risk of patchy fog affecting the airfield, but you should get in OK’. The second example here immediately shows an understanding by the forecaster of the decision which the pilot has to make, and many forecasters' daily jobs involve providing bespoke services to individual customers. By understanding those customers' businesses, forecasters are able to provide them with information on some of the risks and uncertainties which impinge on their activities and affect their decision-making, and tune their forecasts accordingly. Nevertheless, two major changes in recent years are altering the way we deal with forecast uncertainty. First, new methods, such as ensemble prediction, are improving the ability of forecast providers to assess uncertainty quantitatively, in an objective and verifiable fashion.
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- Information
- Predictability of Weather and Climate , pp. 596 - 613Publisher: Cambridge University PressPrint publication year: 2006
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