Climate Models: Strengths & Shortcomings
A climate model is a complex combination of equations and variables which simulates past and projected climate processes.
In research and decision-making, climate models are useful in determining the effects of specific climatic feedbacks on other processes within the climate system.
There are limitations inherent in climate modelling.
Atmospheric flows tend to be chaotic (McFarlane 2011: 482). Model forecasts may be susceptible to error because of insufficient or deficient observations and/or defects within the model (McFarlane 2011: 482); e.g. inadequate comprehension and observation of (i) the processes controlling CO2 absorption by the ocean and land, and (ii) their response to fluctuations in atmospheric CO2, and (iii) their reaction to climatic changes (Friedlingstein et al 2014). When one uses equations to construct estimates of reality, mistakes in those estimations could lead to errors within and from the model (McFarlane 2011: 484). Where climate processes cannot be calculated by and must be defined within the model, i.e. parameterized, one cannot always be sure about the extent to which this method depicts such processes accurately (McFarlane 2011: 485), let alone the manner in which they interact with the model’s resolved processes (McFarlane 2011: 487).
Different climate models give different results for some variables and/or locations.
Possible explanations include the innate chaos of the climate, differences in gridcell sizes and/or spatial resolution used, the gridding technique adopted, different sizes of time steps selected, difference in computational power, the number of climatic processes included as inputs, the quality of forecasts entered into the model, the intrinsic uncertainties of parameterisation, mistakes in bias correction, and the infrequency of the climate process sought to be simulated (CarbonBrief 2018).
Given the close relationship between parameterizability and the spatial resolution permitted by model computing power, I have generally high trust in climate models at the gridcell and continental scales.
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References:
CarbonBrief. (2018). ‘Q&A: How do climate models work?’ https://www.carbonbrief.org/qa-how-do-climate-models-work
Friedlingstein, P., M. Meinshausen, V.K. Arora, C.D. Jones, A. Anav, S.K. Liddicoat, and R. Knutti. (2014). ‘Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks’. Journal of Climate 27(2) 2014, pp.511–526.
McFarlane, N. (2011). ‘Parameterizations: representing key processes in climate models without resolving them’. Wiley Interdisciplinary Reviews: Climate Change 2(4) 2011, pp.482–497.