Hydroclimatic variability and predictability: a survey of recent research.

Koster R.D., A.K. Betts, P.A. Dirmeyer, M. Bierkens, K.E. Bennett, S.J. Déry, J.P. Evans, R. Fu, F. Hernandez, L.R. Leung, X. Liang, M. Masood, H. Savenije, G. Wang, X. Yuan
Hydrology and Earth System Science, 21, 3777–3798, doi: 10.5194/hess-21-3777-2017, 2017.


Recent research in large-scale hydroclimatic variability is surveyed, focusing on five topics: (i) variability in general, (ii) droughts, (iii) floods, (iv) land–atmosphere coupling, and (v) hydroclimatic prediction. Each surveyed topic is supplemented by illustrative examples of recent research, as presented at a 2016 symposium honoring the career of Professor Eric Wood. Taken together, the recent literature and the illustrative examples clearly show that current research into hydroclimatic variability is strong, vibrant, and multi- faceted.

Key Figure

Figure 2. It is widely assumed that large-scale SST patterns (the El Niño/La Niña patterns, for example) have an important impact on rainfall variability in regions like Australia. More proximate SSTs, however, may be just as important. This was investigated through a comparison of two 40-member ensembles of the Weather Research and Forecasting model (WRF) regional model simulations, the first using observed SSTs and the second using SSTs associated with previous La Niña events. Both ensembles employed the same atmospheric forcing along the WRF model’s lateral boundary. Shown in the plot is the inferred contribution of local SSTs to the major flooding that occurred between 10 and 20 December 2010 in Queensland, Australia. In many places, the high local SSTs (within a few hundred kilometers of the coast) accounted for more of the precipitation than did the prevailing La Niña conditions, at least at the spatial scales considered here. The analysis demonstrates limitations in hydrological predictability based solely on large-scale climate modes such as El Niño/La Niña. Controls on hydrological variability and predictability are in fact more complex. (Contact: Jason Evans. See Evans and Boyer-Souchet (2012) for further information.)

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