Improved Atlantic winter blocking in a climate model

By Adam A. Scaife, D. Copsey, C. Gordon, C. Harris, T. Hinton, Sarah P. E. Keeley, Alan O'Neill, M. Roberts, K. Williams. 2011

243 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/52ec0f76373624eab0452855fe9e78778d43faf8

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Citations in the corpus

Simulating regime structures in weather and climate prediction models (2012, background): “5 of 6 [Scaife et al., 2011], suggesting improved atmospheric resolution may still provide considerable benefits.”
A methodology for the comparison of blocking climatologies across indices, models and climate scenarios (2012, background): “…frequency is a characteristic of many general circulation models (D’Andrea et al. 1998; Scaife et al. 2010; Woollings et al. 2010) and could be due to low resolution (and so weak eddy fluxes) or a mean state problem, for example, due to sea-surface temperature biases (Scaife et al. 2010, 2011).”
Bidimensional Diagnostics, Variability, and Trends of Northern Hemisphere Blocking (2012, methodology): “1 2012 American Meteorological Society Unauthenticated | Downloaded 08/01/22 12:17 PM UTC reported, at least for one climate model (Scaife et al. 2011).”
Persistent Extratropical Regimes and Climate Extremes (2015, background): “In some models, however, the biases in blocking and other regimes have been much reduced, probably through a combination of increased vertical as well as horizontal model resolution and improved parameterisations [11–16].”
Predictability of the quasi‐biennial oscillation and its northern winter teleconnection on seasonal to decadal timescales (2014, background): “The ocean resolution is 0.25° globally in both latitude and longitude with 75 quasi-horizontal levels [Scaife et al., 2011].”
High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6 (2016, result): “There are many examples from previous studies (e.g. Scaife et al., 2011; Bellucci et al., 2010) where these biases become much more evident in the coupled context compared to the forced atmosphere simulations.”
High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign (2014, unknown): “…resolution simulations can produce representative data for global mean properties, but their limitations for studying regional effects and temporal variability are becoming more obvious (Roberts et al., 2009; Shaffrey et al., 2009; Scaife et al., 2011; Delworth et al., 2012; Kinter et al., 2013).”
Towards multi-resolution global climate modeling with ECHAM6–FESOM. Part I: model formulation and mean climate (2015, background): “Second, a location bias of the Gulf Stream/North Atlantic Current can result in an atmospheric circulation bias which in turn affects Euro-Atlantic blocking (Keeley et al. 2012; Scaife et al. 2011).”
Atmospheric blocking in a high resolution climate model: influences of mean state, orography and eddy forcing (2013, background): “Coupled models in particular can have much larger blocking biases, which in some cases are linked to sea surface temperature biases arising from errors in the ocean model (Scaife et al., 2011).”
Tropical rainfall, Rossby waves and regional winter climate predictions (2017, background): “This resolution is necessary to reduce key biases in the ocean and atmosphere and give a realistic winter blocking climatology in the model (Scaife et al., 2011).”
Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review (2016, methodology): “Despite this, an experimental coupled forecast system currently being developed at the UK Met Office exhibits modest skill in predicting the wintertime NAO from initializations in November [Scaife et al., 2011, 2014].”
Unified Modeling and Prediction of Weather and Climate: A 25-Year Journey (2012, background): “…chemistry for air quality predictions) and growing evidence that improvements to the resolution and initialization of coupled climate models are required to accurately capture important modes of atmospheric and oceanic variability on monthly to decadal time scales (e.g., Scaife et al. 2011).”
The predictability of the extratropical stratosphere on monthly time‐scales and its impact on the skill of tropospheric forecasts (2015, background): “In recent studies, Scaife et al. (2011) and Dunn-Sigouin and Son (2013) showed that both Coupled Model Intercomparison Project CMIP3 and CMIP5 models have significant biases in duration and frequency of the simulated blocks.”