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Initialized near-term regional climate change prediction.

Doblas-Reyes FJ, Andreu-Burillo I, Chikamoto Y, García-Serrano J, Guemas V, Kimoto M, Mochizuki T, Rodrigues LR, van Oldenborgh GJ - Nat Commun (2013)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain. francisco.doblas-reyes@ic3.cat

ABSTRACT
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.

No MeSH data available.


Multi-model ensemble spread for the near-surface temperature.Ratio between the spread and the RMSE of the ensemble mean for Init (a) and NoInit (b) for the predictions averaged over forecast years 2–5. A combination of temperatures from GHCN/CAMS47 air temperature over land, ERSST48 and GISTEMP 1200 (ref. 49) over the polar areas is used as a reference.
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f5: Multi-model ensemble spread for the near-surface temperature.Ratio between the spread and the RMSE of the ensemble mean for Init (a) and NoInit (b) for the predictions averaged over forecast years 2–5. A combination of temperatures from GHCN/CAMS47 air temperature over land, ERSST48 and GISTEMP 1200 (ref. 49) over the polar areas is used as a reference.

Mentions: The spatial distribution of the spread shows that the CMIP5 multi-model overestimates the temperature spread (Fig. 5) over the North Atlantic and the Arctic, and underestimates it over the North Pacific and most continental areas, both for Init and NoInit. The spread overestimation agrees with the results found for the indices in Fig. 1 and has not been thoroughly documented to date. Sufficiently reliable predictions, which require a calibrated ensemble spread, can be made taking into account the systematic errors in the model variability in a sort of calibration a posteriori45. However, the calibration a priori of the ensemble is more desirable than a post-processing of the predictions. This is an aspect that requires careful attention in the implementation of multi-model operational systems such as the ones that are currently planned34 to satisfy the reliability requirements of the climate services and climate adaptation communities.


Initialized near-term regional climate change prediction.

Doblas-Reyes FJ, Andreu-Burillo I, Chikamoto Y, García-Serrano J, Guemas V, Kimoto M, Mochizuki T, Rodrigues LR, van Oldenborgh GJ - Nat Commun (2013)

Multi-model ensemble spread for the near-surface temperature.Ratio between the spread and the RMSE of the ensemble mean for Init (a) and NoInit (b) for the predictions averaged over forecast years 2–5. A combination of temperatures from GHCN/CAMS47 air temperature over land, ERSST48 and GISTEMP 1200 (ref. 49) over the polar areas is used as a reference.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3644073&req=5

f5: Multi-model ensemble spread for the near-surface temperature.Ratio between the spread and the RMSE of the ensemble mean for Init (a) and NoInit (b) for the predictions averaged over forecast years 2–5. A combination of temperatures from GHCN/CAMS47 air temperature over land, ERSST48 and GISTEMP 1200 (ref. 49) over the polar areas is used as a reference.
Mentions: The spatial distribution of the spread shows that the CMIP5 multi-model overestimates the temperature spread (Fig. 5) over the North Atlantic and the Arctic, and underestimates it over the North Pacific and most continental areas, both for Init and NoInit. The spread overestimation agrees with the results found for the indices in Fig. 1 and has not been thoroughly documented to date. Sufficiently reliable predictions, which require a calibrated ensemble spread, can be made taking into account the systematic errors in the model variability in a sort of calibration a posteriori45. However, the calibration a priori of the ensemble is more desirable than a post-processing of the predictions. This is an aspect that requires careful attention in the implementation of multi-model operational systems such as the ones that are currently planned34 to satisfy the reliability requirements of the climate services and climate adaptation communities.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain. francisco.doblas-reyes@ic3.cat

ABSTRACT
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.

No MeSH data available.