Decadal prediction of Sahel rainfall: where does the skill (or lack thereof) come from?
Previous works suggest decadal predictions of Sahel rainfall could be skillful. However, the sources of such skill are still under debate. In addition, previous results are based on short validation periods (i.e. less than 50 years). In this work we propose a framework based on multi-linear regression analysis to study the potential sources of skill for predicting Sahel trends several years ahead. We apply it to an extended decadal hindcast performed with the MPI-ESM-LR model that span from 1901 to 2010 with 1 year sampling interval. Our results show that the skill mainly depends on how well we can predict the timing of the global warming (GW), the Atlantic multidecadal variability (AMV) and, to a lesser extent, the inter-decadal Pacific oscillation signals, and on how well the system simulates the associated SST and West African rainfall response patterns. In the case of the MPI-ESM-LR decadal extended hindcast, the observed timing is well reproduced only for the GW and AMV signals. However, only the West African rainfall response to the AMV is correctly reproduced. Thus, for most of the lead times the main source of skill in the decadal hindcast of West African rainfall is from the AMV. The GW signal degrades skill because the response of West African rainfall to GW is incorrectly captured. Our results also suggest that initialized decadal predictions of West African rainfall can be further improved by better simulating the response of global SST to GW and AMV. Furthermore, our approach may be applied to understand and attribute prediction skill for other variables and regions.
KeywordsDecadal climate predictions Sahel Atlantic multidecadal variability Global warming Climate variability
- Compo GP, Whitaker JS, Sardeshmukh PD, Matsui N, Allan RJ, Yin X, Gleason BE, Vose RS, Rutledge G, Bessemoulin P, Brönnimann S, Brunet M, Crouthamel RI, Grant AN, Groisman PY, Jones PD, Kruk MC, Kruger AC, Marshall GJ, Mauger M, Mok HY, Nordli Ø, Ross TF, Trigo RM, Wang XL, Woodruff SD, Worley SJ (2011) The twentieth century reanalysis project. Q J R Meteorol Soc 137:1–28CrossRefGoogle Scholar
- Ickowicz A, Ancey V, Corniaux C, Duteurtre G, Poccard-Chappuis R, Toure I, Vall E and Wane A (2012) Crop-livestock production systems in the Sahel—increasing resilience for adaptation to climate change and preserving food security. Building resilience for adaptation to climate change in the agriculture sector. FAO/OECD Rome, pp 243–276Google Scholar
- International CLIVAR Project Office (ICPO) (2011) Data and bias correction for decadal climate predictions. International CLIVAR Project Office CLIVAR Publication Series, vol 150, p 6Google Scholar
- Janicot S, Gaetani M, Hourdin F et al (2015) The recent partial recovery in Sahel rainfall: a fingerprint of greenhouse gases forcing? GEWEX 27:11–15Google Scholar
- Kandji ST, Verchot S, Mackensen J (2006) Climate change and variability in the Sahel region: impacts and adaptation strategies in the agricultural sector. World Agroforestry Centre (ICRAF) and United Nations Environment Programme (UNEP). UNEP 2006:1–48Google Scholar
- Kawase H, Abe M, Yamada Y, Takemura T, Yokohata T, Nozawa T (2010) Physical mechanism of long-term drying trend over tropical North Africa. Geophys Res Lett 37:L09706Google Scholar
- Keenlyside NS, Ba J, Mecking J, Omrani NO, Latif M, Zhang R, Msadek R (2015) North Atlantic multi-decadal variability—mechanisms and predictability. In: Chang C-P, Ghil M, Latif M, Wallace M (eds) Climate change: multidecadal and beyond. World Scientific Publishing Company, Singapore. ISBN 978-9814579926Google Scholar
- Kim HM, Websetr PJ, Curry JA (2012) Evaluation of short-term climate change prediction in mutli-model CMIP5 decadal hindcasts. Geophys Res Lett 39:L10701Google Scholar
- Müller WA, Matei D, Bersch M, Jungclaus JH, Haak H, Lohmann K, Compo GP, Sardeshmukh PD, Marotzke J (2015) A twentieth century reanalysis forced ocean model to reconstruct the North Atlantic climate variation during the 1920s. Clim Dyn 44:1935–1955. doi:10.1007/s00382-014-2267-5 CrossRefGoogle Scholar
- Terray L (2012) Evidence for multiple drivers of North Atlantic multi-decadal climate variability. Geophys Res Lett 29:L19712Google Scholar