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  • 1
    Publication Date: 2019-07-13
    Description: Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.
    Keywords: Meteorology and Climatology
    Type: GSFC-E-DAA-TN65080 , Nature Climate Change (ISSN 1758-678X) (e-ISSN 1758-6798); 9; 102-110
    Format: text
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  • 2
    Publication Date: 2019-02-01
    Description: The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs. OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations
    Type: Article , PeerReviewed
    Format: text
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  • 3
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    AMS (American Meteorological Society)
    In:  Bulletin of the American Meteorological Society, 81 (2). pp. 313-318.
    Publication Date: 2016-09-07
    Description: The Coupled Model Intercomparison Project (CMIP) was established to study and intercompare climate simulations made with coupled ocean-atmosphere-cryosphere-land GCMs. There are two main phases (CMIP1 and CMIP2), which study, respectively, 1) the ability of models to simulate current climate, and 2) model simulations of climate change due to an idealized change in forcing (a 1% per year CO2 increase). Results from a number of CMIP projects were reported at the first CMIP Workshop held in Melbourne, Australia, in October 1998. Some recent advances in global coupled modeling related to CMIP were also reported. Presentations were based on preliminary unpublished results. Key outcomes from the workshop were that 1) many observed aspects of climate variability are simulated in global coupled models including the North Atlantic oscillation and its linkages to North Atlantic SSTs, El Niño-like events, and monsoon interannual variability; 2) the amplitude of both high- and low-frequency global mean surface temperature variability in many global coupled models is less than that observed, with the former due in part to simulated ENSO in the models being generally weaker than observed, and the latter likely to be at least partially due to the uncertainty in the estimates of past radiative forcing; 3) an El Niño-like pattern in the mean SST response with greater surface warming in the eastern equatorial Pacific than the western equatorial Pacific is found by a number of models in global warming climate change experiments, but other models have a more spatially uniform or even a La Niña-like, response; 4) flux adjustment, by definition, improves the simulation of mean present-day climate over oceans, does not guarantee a drift-free climate, but can produce a stable base state in some models to enable very long term (1000 yr and longer) integrations-in these models it does not appear to have a major effect on model processes or model responses to increasing CO2; and 5) recent multicentury integrations show that a stable surface climate can be attained without flux adjustment (though still with some systematic simulation errors).
    Type: Article , PeerReviewed
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  • 4
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    AGU (American Geophysical Union)
    In:  Eos: Transactions, 78 . pp. 445-446.
    Publication Date: 2016-12-22
    Type: Article , NonPeerReviewed
    Format: text
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