Representing Model Uncertainty in Weather and Climate Prediction

Palmer, Tim; Shutts, G. J.; Hagedorn, Renate; Doblas‐Reyes, F. J.; Jung, Thomas; Leutbecher, Martin

doi:10.1146/annurev.earth.33.092203.122552

Cited by 302 publications

(248 citation statements)

References 36 publications

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“…Although some limitations still exist (e.g. Palmer et al, 2005;, the recent increase in model resolutions (e.g. Prodhomme et al, 2016a), the improvement of initialization procedures (e.g.…”

Section: Introductionmentioning

confidence: 99%

A coupled human–natural system to assess the operational value of weather and climate services for agriculture

Liu

Giuliani

Castelletti

2017

Hydrol. Earth Syst. Sci.

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Abstract. Recent advances in weather and climate (W&C) services are showing increasing forecast skills over seasonal and longer timescales, potentially providing valuable support in informing decisions in a variety of economic sectors. Quantifying this value, however, might not be straightforward as better forecast quality does not necessarily imply better decisions by the end users, especially when forecasts do not reach their final users, when providers are not trusted, or when forecasts are not appropriately understood. In this study, we contribute an assessment framework to evaluate the operational value of W&C services for informing agricultural practices by complementing traditional forecast quality assessments with a coupled human-natural system behavioural model which reproduces farmers' decisions. This allows a more critical assessment of the forecast value mediated by the end users' perspective, including farmers' risk attitudes and behavioural factors. The application to an agricultural area in northern Italy shows that the quality of state-ofthe-art W&C services is still limited in predicting the weather and the crop yield of the incoming agricultural season, with ECMWF annual products simulated by the IFS/HOPE model resulting in the most skillful product in the study area. However, we also show that the accuracy of estimating crop yield and the probability of making optimal decisions are not necessarily linearly correlated, with the overall assessment procedure being strongly impacted by the behavioural attitudes of farmers, which can produce rank reversals in the quantification of the W&C services operational value depending on the different perceptions of risk and uncertainty.

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“…Although some limitations still exist (e.g. Palmer et al, 2005;, the recent increase in model resolutions (e.g. Prodhomme et al, 2016a), the improvement of initialization procedures (e.g.…”

Section: Introductionmentioning

confidence: 99%

A coupled human–natural system to assess the operational value of weather and climate services for agriculture

Liu

Giuliani

Castelletti

2017

Hydrol. Earth Syst. Sci.

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“…Of course these parameterizations may be highly idealized, and their shortcomings contribute substantially to model inaccuracies (e.g. Harrison et al, 1999;Palmer, 2001;Palmer et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…Palmer et al, 2005). However, there is no such separation between the small and resolved scales of atmospheric motion.…”

Section: Introductionmentioning

confidence: 99%

“…However, there is no such separation between the small and resolved scales of atmospheric motion. Accordingly, a deterministic parameterization specifies at best a mean influence of the unresolved scales, conditional on the resolved prognostic variables, whereas nature provides an unpredictable realization more-or-less near the parameterized value (Palmer et al, 2005;Wilks, 2005). It is therefore natural to extend parameterizations to include explicitly stochastic influences, i.e.…”

Section: Introductionmentioning

confidence: 99%

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‘Superparameterization’ and statistical emulation in the Lorenz '96 system

Wilks

2012

Quart J Royal Meteoro Soc

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An idealized 'superparameterization', or abbreviated but dynamically explicit representation of small-scale influences on the conventionally resolved larger scales of a dynamical model, is constructed within the Lorenz '96 system. The feasibility of abstracting the greater portion of its information content using computationally much faster statistical summaries, or emulators, is investigated through integration of a large number of ensemble forecasts. Even though based on an extremely small training-sample size, consistent with an assumed high computational expense for running a full superparameterization, some of the statistical emulator formulations perform nearly as well as the superparameterization forecast ensembles. As in previous studies, better forecast characteristics are generally achieved when autocorrelated random forcing is included, both in the otherwise deterministic superparameterization and in its statistical emulators.

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“…They do not only improve the ensemble spread, but also correct systematic model errors and represent model uncertainty (see, for example, [25]). Stochastic parametrisations include stochastically perturbed physical parametrisation tendencies [3,27], stochastic kinetic energy back-scatter [2,30], cellular automata [1,25], quasi-equilibrium statistical mechanics parametrisations (for example [28]), stochastic differential equations (for example [11,13]) and Markov chains (for example [4,14]). Stochastic forcings are often introduced into the numerical model (for example [2,3,30]) to represent sub-grid-scale variability explicitly.…”

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confidence: 99%

Rounding errors may be beneficial for simulations of atmospheric flow: results from the forced 1D Burgers equation

Dueben

Dolaptchiev

2015

Theor. Comput. Fluid Dyn.

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Inexact hardware can reduce computational cost, due to a reduced energy demand and an increase in performance, and can therefore allow higher-resolution simulations of the atmosphere within the same budget for computation. We investigate the use of emulated inexact hardware for a model of the randomly forced 1D Burgers equation with stochastic sub-grid-scale parametrisation. Results show that numerical precision can be reduced to only 12 bits in the significand of floating-point numbers-instead of 52 bits for double precisionwith no serious degradation in results for all diagnostics considered. Simulations that use inexact hardware on a grid with higher spatial resolution show results that are significantly better compared to simulations in double precision on a coarser grid at similar estimated computing cost. In the second half of the paper, we compare the forcing due to rounding errors to the stochastic forcing of the stochastic parametrisation scheme that is used to represent sub-grid-scale variability in the standard model setup. We argue that stochastic forcings of stochastic parametrisation schemes can provide a first guess for the upper limit of the magnitude of rounding errors of inexact hardware that can be tolerated by model simulations and suggest that rounding errors can be hidden in the distribution of the stochastic forcing. We present an idealised model setup that replaces the expensive stochastic forcing of the stochastic parametrisation scheme with an engineered rounding error forcing and provides results of similar quality. The engineered rounding error forcing can be used to create a forecast ensemble of similar spread compared to an ensemble based on the stochastic forcing. We conclude that rounding errors are not necessarily degrading the quality of model simulations. Instead, they can be beneficial for the representation of sub-grid-scale variability.

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Representing Model Uncertainty in Weather and Climate Prediction

Cited by 302 publications

References 36 publications

A coupled human–natural system to assess the operational value of weather and climate services for agriculture

A coupled human–natural system to assess the operational value of weather and climate services for agriculture

‘Superparameterization’ and statistical emulation in the Lorenz '96 system

Rounding errors may be beneficial for simulations of atmospheric flow: results from the forced 1D Burgers equation

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