Reliability of the CMIP3 ensemble
By J. Annan, J. Hargreaves. 2010
178 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/a77b6e6a9d8d70a890f314d850ded860b6fd7407
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
- Reto Knutti
- Gab Abramowitz
- David Masson
- C. Bishop
- Andrew J. Pitman
- Steven J. Phipps
- Ned Haughton
- Gerald A. Meehl
In Global and Planetary Change
- Reto Knutti
- Gab Abramowitz
- David Masson
- C. Bishop
- Andrew J. Pitman
- Steven J. Phipps
- Ned Haughton
- C. Tebaldi
Citations in the corpus
- A new statistical approach to climate change detection and attribution (2016, methodology): “Several paradigms have been used in the literature to compare observations with simulations coming from various models, and more precisely to describe the distance from X at which the observations are likely to be found (Annan and Hargreaves 2010; Knutti et al. 2010).”
- Weighting climate model ensembles for mean and variance estimates (2015, methodology): “Thus, if the models and observations are independently drawn from the same distribution, as in the indistinguishable paradigm, or are true replicate earths, then the expected correlation between error pairs is actually 0.5 (Annan and Hargreaves 2010; Bishop and Abramowitz 2013).”
- Challenges in Combining Projections from Multiple Climate Models (2010, methodology): “This proposal is made explicit in Tebaldi and Sansó (2009) and Annan and Hargreaves (2010). In contrast, the probabilistic method by Watterson (2008) and studies based on detection and attribution fin-”
- Climate Model Dependence and the Ensemble Dependence Transformation of CMIP Projections (2015, background): “Since CMIP ensembles conceptually represent both types of uncertainty, it is perhaps unsurprising that they have been found to be overdispersive (Annan and Hargreaves 2010; Yokohata et al. 2012; Bishop and Abramowitz 2013).”
- Climate model genealogy (2011, methodology): “The method and all conclusions are independent of whether the ensemble is interpreted as models being centered around truth or models and truth being indistinguishable, because the method only uses pairwise distances between models [Knutti et al., 2010a; Annan and Hargreaves, 2010].”
- Climate model dependence and the replicate Earth paradigm (2013, methodology): “553 554 We note that our interpretation of ensemble spread being over-dispersive (supporting the findings of 555 Annan and Hargreaves, 2010) is somewhat at odds with Jewson and Hawkins (2009), who argue 556 that the ensemble spread is too narrow.”