The CSIRO Mk3 climate system model
By H. Gordon. 2002
330 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/b473fd7ea0d021f335b8086c395d18ac152ee8b1
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- M. Webb
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- Elizabeth A. Fulton
- C. Brown
- J. Gregory
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- R. Watson
- Darren J. Kriticos
Citations in the corpus
- Origins of differences in climate sensitivity, forcing and feedback in climate models (2013, methodology): “One of the main limitations of the Gregory et al. (2004) method applied to slab models subject to CO2 doubling is the difficulty of dealing with substantial regression uncertainties in CO2 doubling experiments, a problem which is particularly acute for low sensitivity models.”
- Effects of climate‐driven primary production change on marine food webs: implications for fisheries and conservation (2010, methodology): “The GCM model we used to project ocean conditions into the future is the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 3.5 coupled atmosphere-ocean GCM (Hirst et al., 2000; Gordon et al., 2002).”
- Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models (2011, methodology): “0 (Gordon et al., 2002) global climate model with the A1B SRES emission scenarios (IPCC, 2000), available as part of the CliMond data set.”
- A climate-change risk analysis for world ecosystems (2006, background): “However, there is mounting evidence for local ecological responses even to relatively minor climate changes that have occurred during recent decades (3).”
- Integrating ensemble species distribution modelling and statistical phylogeography to inform projections of climate change impacts on species distributions (2013, unknown): “5 Gordon et al. (2002) HadGEM1 Johns et al. (2006) IPSL CM4 Marti et al. (2009) MIROC 3.2 K-1 model developers et al. (2004) 1482 Diversity and Distributions, 19, 1480–1495, ª 2013 John Wiley & Sons Ltd generalized boosted models (GBM), random forest (RF) and maximum entropy (MAX).”