Methodological aspects of the validation of decadal predictions

Gangstø, Reidun; Weigel, Andreas; Liniger, Mark A.; Appenzeller, Christof

doi:10.3354/cr01135

Cited by 31 publications

(29 citation statements)

References 50 publications

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“…As it is difficult to obtain robust forecast quality estimates with such limited samples2544, this paper only discusses results from those systems with a higher frequency of start dates. However, a systematic comparison of the results with both samples suggests that a 5-year interval sampling allows estimating the level of skill, although the estimates contain spurious maxima along the forecast time due to the poor sampling of the start dates25.…”

Section: Resultsmentioning

confidence: 99%

Initialized near-term regional climate change prediction

et al. 2013

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Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth's temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions.

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Section: Resultsmentioning

confidence: 99%

Initialized near-term regional climate change prediction

et al. 2013

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“…Finally, while a sufficient amount of verification data is, at least in principle, available for the validation of short‐term weather forecasts, sample sizes get smaller as we move to long lead‐times of several months or even years. The situation gets even more complicated for the recently evolving field of decadal forecasting, where sample sizes are so small that a classical verification may not be feasible at the present time (Mason, ; Gangsto et al ., ).…”

Section: Challengesmentioning

confidence: 99%

Progress and challenges in forecast verification

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Weigel

et al. 2013

Meteorological Applications

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Verification scientists and practitioners came together at the 5 th International Verification Methods Workshop in Melbourne, Australia, in December 2011 to discuss methods for evaluating forecasts within a wide variety of applications. Progress has been made in many areas including improved verification reporting, wider use of diagnostic verification, development of new scores and techniques for difficult problems, and evaluation of forecasts for applications using meteorological information. There are many interesting challenges, particularly the improvement of methods to verify high resolution ensemble forecasts, seamless predictions spanning multiple spatial and temporal scales, and multivariate forecasts. Greater efforts are needed to make best use of new observations, forge greater links between data assimilation and verification, and develop better and more intuitive forecast verification products for end-users.

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“…The most appropriate way to achieve this, especially for regional predictions, is a research question, and several methods could be considered (e.g. Gangstø et al, 2013;Kruschke et al, 2015).…”

Section: Trendsmentioning

confidence: 99%

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

et al. 2016

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Abstract. The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al

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Methodological aspects of the validation of decadal predictions

Cited by 31 publications

References 50 publications

Initialized near-term regional climate change prediction

Initialized near-term regional climate change prediction

Progress and challenges in forecast verification

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

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