PReP · Palaeocloud Reconstruction Project

Palaeocloud Reconstruction Project

Recent high-latitude warming has tracked or exceeded the upper limits of climate model uncertainty. High-latitude climate sensitivity to increasing CO2 is poorly constrained but has large impacts on global climate. An independent way to test climate simulations is through modelling of past warm periods such as the Pliocene. Pliocene studies have also found data-model mismatch at high-latitudes, and the causes are unknown. If this mismatch signals bias or error in climate models, predictions may be underestimating high-latitude climate sensitivity, with dramatic knock-on effects for climate change mitigation. Cloud is the greatest source of uncertainty in climate models and changes in cloud disproportionately impact high-latitude temperatures. My previous interdisciplinary work with climate modellers identified cloud-aerosol interactions as important feedbacks to Pliocene Arctic climate. Modelling experiments for other past warm periods have found that alteration to cloud in simulations can resolve insufficient polar amplification of temperature; however, there is no way to verify these are accurate changes to cloud simulation, as there is no method to reconstruct cloud in the distant past, and only two methods that reconstruct cloud in limited regions for the Holocene. Plant community, foliar physiognomic, and leaf micromorphological methods all have promising data suggesting correlation either directly to cloud or to light, and are thus likely candidates for cloud reconstruction. The recent availability of modern global cloud data products and global biodiversity databases (e.g. gbif.org) facilitate expansion of palaeoclimate reconstruction methods to include cloud. During this fellowship, I will conduct preliminary investigations of plant community, foliar physiognomic, and leaf micromorphological methods for reconstructing past cloud, with the aim of identifying a promising proxy for cloud in the distant past. Application of such a proxy with facilitate testing of cloud in climate models, and decrease our uncertainty in climate prediction, with implications for climate impact mitigation and strategic policy.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз