Understanding Uncertainties in Future Projections of Seasonal Tropical Precipitation

Abstract

Projected changes in regional seasonal precipitation due to climate change are highly uncertain, with model disagreement on even the sign of change in many regions. Using a 20-member CMIP5 ensemble under the RCP8.5 scenario, the intermodel uncertainty of the spatial patterns of projected end-of-twenty-first-century change in precipitation is found not to be strongly influenced by uncertainty in global mean temperature change. In the tropics, both the ensemble mean and intermodel uncertainty of regional precipitation change are found to be predominantly related to spatial shifts in convection and convergence, associated with processes such as sea surface temperature (SST) pattern change and land-sea thermal contrast change. The authors hypothesize that the zonal-mean seasonal migration of these shifts is driven by 1) the nonlinear spatial response of convection to SST changes and 2) a general movement of convection from land to ocean in response to SST increases. Assessment of tropical precipitation model projections over East Africa highlights the complexity of regional rainfall changes. Thermodynamically driven moisture increases determine the magnitude of the long rains (March-May) ensemble mean precipitation change in this region, whereas model uncertainty in spatial shifts of convection accounts for almost all of the intermodel uncertainty. Moderate correlations are found across models between the long rains precipitation change and patterns of SST change in the Pacific and Indian Oceans. Further analysis of the capability of models to represent present-day SSTrainfall links, and any relationship with model projections, may contribute to constraining the uncertainty in projected East Africa long rains precipitation.

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

“…Bush et al, 2015;Kim et al, 2016) to contributing to uncertainty in projections of future tropical rainfall (e.g. Kent et al, 2015). By examining the behaviour of modelled tropical rainfall at a wide range of spatial and temporal scales, we can hope to shed light on the way in which such biases develop.…”

“…Levine and Turner, 2012) and can contribute to uncertainty in projections of future tropical rainfall (e.g. Kent et al, 2015). Deep convection parametrizations in these models often produce very intermittent rainfall at the level of the model's time step and gridscale, and also produce a poor representation of the processes and timing associated with the diurnal cycle of convection over land (e.g.…”

Future Precipitation Projections over Central and Southern Africa and the Adjacent Indian Ocean: What Causes the Changes and the Uncertainty?

“…We use output from simulations of the twentieth century and the twenty-first century [under the representative concentration pathway 8.5 (RCP8.5) emissions scenario] from 20 models [those used in Kent et al (2015, (Meehl et al 2007;Taylor et al 2012) (see Table 1). We consider both the MMM of the 20 chosen CMIP5 models and the spread of model projections across the 20-model ensemble, to address aims 1 and 2 and aim 3, respectively.…”

“…Most previous analyses have focused on the MMM projected change quantities; however, Rowell et al (2015) highlighted the importance of understanding the mechanisms of change within individual models and concluded that further investigation should be aimed at developing expert judgment of process-based mechanisms and their reliability of projections (Rowell et al 2015).…”

Climate Change Preparedness: A Knowledge and Attitudes Study in Southern Nigeria

“…Additionally, the projected population growth rate in Nigeria to 2050, 5.2%, is more than double that of the world average (1.9%) creating greater demand for water [11]. It should be noted that projected changes in seasonal rainfall due to climate change are highly uncertain [12]. Additionally, increased rainfall intensity generates greater run-off, limiting the amount available for use.…”