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The "Best Available Tools" for Predicting Climate Change
Volume 17, Number 3: 15 January 2014

In introducing their recent study of the subject, Siam et al. (2013) write that "general circulation models (GCMs) are the best available tools to predict climate change associated with future scenarios of greenhouse gas concentrations." Unfortunately, however, they also state that "an analysis of their outputs reveals that these models do not accurately reproduce the past and current climates," noting that "this is particularly the case for hydrological variables (e.g., precipitation) that show large inconsistency, especially over Africa," citing in this regard the analysis of Christensen et al. (2007).

In further discussing this problem, they add that "many uncertainties lie behind the choice of a downscaling method, which may amplify inherent errors in GCM outputs and increase uncertainties associated with climate change predictions of the hydrological cycle at smaller scale, such as over river basins," citing Boe et al. (2009). And they additionally indicate that "these errors are reflected in the disagreement between GCM predictions on [both] the sign and magnitude of changes in river runoff over major African basins," citing the studies of Strzepek and Yates (1996), Conway and Hulme (1996), Yates and Strzepek (1998), Nohara et al. (2006) and Kim et al. (2008).

With respect to their own work on the subject, the three researchers evaluated the hydrological cycle hindcasts of 28 GCMs of the CMIP3 and CMIP5 projects, finding that most of them "simulate a strong bias in the hydrological cycle over the Congo and Upper Blue Nile basins by overestimating precipitation and runoff compared to observations." As for why this is so, they say that "several reasons that are under investigation could be responsible for improving the hydrological cycle simulation," specifically highlighting those that are associated with increasing horizontal model resolution.

In light of all of the frustrations associated with this undertaking, one can only hope that some modeling group will ultimately succeed in this endeavor. Until that time, however ... (fill in your own thoughts on the matter).

Sherwood, Keith and Craig Idso

Boe, J., Terray, L., Martin, E. and Habets, F. 2009. Projected changes in components of the hydrological cycle in French river basins during the 21st century. Water Resources Research 45: 10.1029/2008WR007437.

Christensen, J.H., Hewitson, B., Busuioc, A., Chen, A., Gao, X., Held, I., Jones, R., Kolli, R.K., Kwon, W.-T., Laprise, R., Magaña Rueda, V., Mearns, L., Menéndez, C.G., Räisänen, J., Rinke, A., Sarr, A. and Whetton, P. 2007. Regional climate projections. In: Solomon, S. Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor M. and Miller, H.L. (Eds.) Climate Change 2007: The Physical Science Basis. Cambridge University Press, Cambridge, United Kingdom, pp. 847-940.

Conway, D. and Hulme, M. 1996. The impacts of climate variability and future climate change in the Nile basin on water resources in Egypt. International Journal of Water Resources Development 12: 277-296.

Kim, U., Kaluarachchi, J.J. and Smakhtin, V.U. 2008. Climate change impacts on hydrology and water resources of the upper Blue Nile River basin, Ethiopia. International Water Management Institute Research Report 126, 27 pp.

Nohara, D., Kitoh, A., Hosaka, M. and Oki, T. 2006. Impact of climate change on river runoff. Journal of Hydrometeorology 7: 1076-1089.

Siam, M.S., Demory, M.-E. and Eltahir, E.A.B. 2013. Hydrological cycles over the Congo and Upper Blue Nile basins: Evaluation of general circulation model simulations and reanalysis products. Journal of Climate 26: 8881-8894.

Strzepek, K. and Yates, D.N. 1996. Economic and social adaptations to climate change impacts on water resources: A case study of Egypt. International Journal of Water Resources Development 12: 229-244.

Yates, D.N. and Strzepek, K.M. 1998. An assessment of integrated climate change impacts on the agricultural economy of Egypt. Climatic Change 38: 261-287.