[A-HW17] Hydrological Cycle and Water Environment

[AHW17-P06] Predicting future uncertainty constraints on global warming projections

*Hideo Shiogama¹, Daithi Stone², Seita Emori¹, Kiyoshi Takahashi¹, Shunsuke Mori³, Akira Maeda⁴, Myles Allen⁵ (1.National Institute for Environmental Studies, 2.Lawrence Berkeley National Laboratory, 3.Tokyo University of Science, 4.The University of Tokyo, 5.University of Oxford)

Keywords:climate change, climate change projection

Projections of global mean temperature changes (dT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by “current knowledge” of the dTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of dT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the dTs uncertainty in the 2040s by 2029, and more than 60% of the dTs uncertainty in the 2090s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2°C (3°C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.