Atmospheric Blocking and Mean Biases in Climate Models
By Adam A. Scaife, T. Woollings, J. Knight, G. Martin, T. Hinton. 2010
215 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/89df64c8fb95e57f0d99f28c51200934035db8a5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- D. Hartmann
- Andrew Gettelman
- Richard B. Neale
- Adam A. Scaife
- C. Cagnazzo
- J. Richter
- P. Ceppi
- T. Woollings
In Global and Planetary Change
- D. Hartmann
- Andrew Gettelman
- Adam A. Scaife
- C. Cagnazzo
- Richard B. Neale
- P. Ceppi
- T. Woollings
- J. Richter
Citations in the corpus
- An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models (2020, methodology): “To provide an indication of the relative importance of each of these contributions to the overall bias, we adopt the procedure of Scaife et al. (2010).”
- Bidimensional Diagnostics, Variability, and Trends of Northern Hemisphere Blocking (2012, background): “1998), which is widely documented even for state-of-the-art models (Scaife et al. 2010).”
- Blocking and its Response to Climate Change (2018, background): “alone cannot explain the mean bias, but in converse the mean state bias can, in good models at least, often statistically ‘explain’ the blocking bias [106, 117].”
- Southern Hemisphere jet latitude biases in CMIP5 models linked to shortwave cloud forcing (2012, background): “Such biases are known to affect a number of phenomena, includ- ing the frequency of blocking anticyclones [Scaife et al., 2010], the distribution of surface wind stress and its impacts on ocean currents [Fyfe and Saenko, 2006], and the persistence of the annular modes [Barnes and Hartmann, 2010].”
- Improved Atlantic winter blocking in a climate model (2011, methodology): “The stronger geopotential height gradient in the model than observations is expected to reduce the diagnosed blocking frequency [cf. Scaife et al., 2010].”
- Atmospheric blocking in a high resolution climate model: influences of mean state, orography and eddy forcing (2013, background): “On first impression, these results seem to contradict those of Scaife et al. (2010), who showed that blocking indices applied to climate model data were largely reflecting biases in the models’ mean states rather than in the occurrence of blocking per se.”