Estimating the decadal predictability of a coupled AOGCM

By Holger Pohlmann, M. Botzet, M. Latif, Andreas Roesch, Martin Wild, P. Tschuck. 2004

172 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/d2615e8cbd8bb63bd4b703c0decd27b76b8c4602

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Citations in the corpus

Arctic-North Atlantic Interactions and Multidecadal Variability of the Meridional Overturning Circulation (2005, background): “Furthermore, there is no significant correlation between the SLP over the central Arctic and the MOI (Pohlmann et al. 2004).”
What is the current state of scientific knowledge with regard to seasonal and decadal forecasting? (2012, background): “Furthermore, predictability studies show much less potential skill for PDV than AMV (Collins 2002, Boer 2004, Pohlmann et al 2004, Branstator and Teng 2010).”
Will Arctic sea ice thickness initialization improve seasonal forecast skill? (2014, background): “Analysis of idealized “perfect model” experiments with coupled GCMs provides a setting where perfect knowledge of the initial model state exists and forecast quality is not aﬀected by model bias [e.g., Collins , 2002; Pohlmann et al. , 2004].”
Two Limits of Initial-Value Decadal Predictability in a CGCM (2010, background): “More details on the A1B ensemble are available in Teng and Branstator (2010). The Commitment ensemble also has 40 members and uses the same initial states as the A1B ensemble.”
Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review (2016, background): “…predictability of the AMOC several years to decades in advance (see Figure 14a) [Griffies and Bryan, 1997a, 1997b; Collins and Sinha, 2003; Pohlmann et al., 2004; Collins et al., 2006; Hawkins and Sutton, 2008; Msadek et al., 2010], but the degree of predictability is found to depend on…”
Variability of the Atlantic meridional overturning circulation in CCSM4 (2012, unknown): “The latter is due to suggested potential predictability associated with AMOC and upper-ocean temperatures on decadal time scales (e.g., Griffies and Bryan 1997; Pohlmann et al. 2004; Msadek et al. 2010; Branstator and Teng 2010).”
A verification framework for interannual-to-decadal predictions experiments (2012, unknown): “The initial studies, and those to follow, suggested predictability of the AMOC to 10 or 20 years, and also indicated that some extreme states may be more predictable (Grifﬁes and Bryan 1997; Collins et al. 2006; Pohlmann et al. 2004; Msadek et al. 2010; Teng et al. 2011).”
How does internal variability influence the ability of CMIP5 models to reproduce the recent trend in Southern Ocean sea ice extent (2012, background): “Idealized model studies have shown high potential predictability at decadal time scales in the Southern180 Ocean (e.g. Latif et al., 2010), i.e. models have deterministic decadal variability, in particular for surface temperatu es (Pohlmann et al., 2004).”
Seasonal Prediction of Arctic Sea Ice Extent from a Coupled Dynamical Forecast System (2013, background): “In addition, the prognostic potential predictability (PPP; Pohlmann et al. 2004; Holland et al. 2011) is also analyzed.”
A Review of the Role of the Atlantic Meridional Overturning Circulation in Atlantic Multidecadal Variability and Associated Climate Impacts (2019, background): “In many CGCM control simulations, the AMOC indeed exhibits enhanced decadal potential predictability, which is sensitive to the amplitudes of simulatedmultidecadal AMOC variability in individual models and the initial oceanic conditions (e.g., Branstator & Teng, 2014; Collins et al., 2006; Griffies ”
Towards multi-resolution global climate modeling with ECHAM6–FESOM. Part I: model formulation and mean climate (2015, methodology): “This definition is slightly different from the ones used in Boer (2000) and Pohlmann et al. (2004) in the way the noise contribution to the variance fraction σ 2m/σ 2 is corrected for; in our case the DPP is normalized such that it can take the whole range of values between 0 and 1 for any m > 1,…”
Initializing Decadal Climate Predictions with the GECCO Oceanic Synthesis: Effects on the North Atlantic (2009, methodology): “A lag of a few years between the Atlantic MOC and the North Atlantic SST was also found in a multicentury control experiment with ECHAM5–MPI-OM (Latif et al. 2004).”
Challenges and Prospects in Ocean Circulation Models (2019, methodology): “Decadal Prediction The possibility of using coupled climatemodels for forecasting on decadal timescales was first explored in several perfect model and potential predictability studies (Griffies and Bryan, 1997; Boer, 2004; Pohlmann et al., 2004; Collins et al., 2006) and was soon thereafter tested ”