Evaluation of short‐term climate change prediction in multi‐model CMIP5 decadal hindcasts
Hyemi Kim, Peter J. Webster, Judith A. Curry
Abstract
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Hyemi Kim, Peter J. Webster, Judith A. Curry
Abstract
Open-access reader
This study assesses the CMIP5 decadal hindcast/forecast simulations of seven state‐of‐the‐art ocean‐atmosphere coupled models. Each decadal prediction consists of simulations over a 10 year period each of which are initialized every five years from climate states of 1960/1961 to 2005/2006. Most of the models overestimate trends, whereby the models predict less warming or even cooling in the earlier decades compared to observations and too much warming in recent decades. All models show high prediction skill for surface temperature over the Indian, North Atlantic and western Pacific Oceans where the externally forced component and low‐frequency climate variability is dominant. However, low prediction skill is found over the equatorial and North Pacific Ocean. The Atlantic Multidecadal Oscillation (AMO) index is predicted in most of the models with significant skill, while the Pacific Decadal Oscillation (PDO) index shows relatively low predictive skill. The multi‐model ensemble has in general better‐forecast quality than the single‐model systems for global mean surface temperature, AMO and PDO.
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This study assesses the CMIP5 decadal hindcast/forecast simulations of seven state‐of‐the‐art ocean‐atmosphere coupled models. Each decadal prediction consists of simulations over a 10 year period each of which are initialized every five years from climate states of 1960/1961 to 2005/2006. Most of the models overestimate trends, whereby the models predict less warming or even cooling in the earlier decades compared to observations and too much warming in recent decades. All models show high prediction skill for surface temperature over the Indian, North Atlantic and western Pacific Oceans where the externally forced component and low‐frequency climate variability is dominant. However, low prediction skill is found over the equatorial and North Pacific Ocean. The Atlantic Multidecadal Oscillation (AMO) index is predicted in most of the models with significant skill, while the Pacific Decadal Oscillation (PDO) index shows relatively low predictive skill. The multi‐model ensemble has in general better‐forecast quality than the single‐model systems for global mean surface temperature, AMO and PDO.
Key concepts: Hindcast, Climatology, Pacific decadal oscillation, Environmental science, Climate model, Atlantic multidecadal oscillation, Sea surface temperature, Climate change