Time of emergence of anthropogenic warming signals in the Northeast Asia assessed from multi-regional climate models
- 135 Downloads
Time of Emergence (ToE) is the time at which the signal of climate change emerges from the background noise of natural climate variability, and can provide useful information for climate change impacts and adaptations. This study examines future ToEs for daily maximum and minimum temperatures over the Northeast Asia using five Regional Climate Models (RCMs) simulations driven by single Global Climate Model (GCM) under two Representative Concentration Pathways (RCP) emission scenarios. Noise is defined based on the interannual variability during the present-day period (1981-2010) and warming signals in the future years (2021-2100) are compared against the noise in order to identify ToEs. Results show that ToEs of annual mean temperatures occur between 2030s and 2040s in RCMs, which essentially follow those of the driving GCM. This represents the dominant influence of GCM boundary forcing on RCM results in this region. ToEs of seasonal temperatures exhibit larger ranges from 2030s to 2090s. The seasonality of ToE is found to be determined majorly by noise amplitudes. The earliest ToE appears in autumn when the noise is smallest while the latest ToE occurs in winter when the noise is largest. The RCP4.5 scenario exhibits later emergence years than the RCP8.5 scenario by 5-35 years. The significant delay in ToEs by taking the lower emission scenario provides an important implication for climate change mitigation. Daily minimum temperatures tend to have earlier emergence than daily maximum temperature but with low confidence. It is also found that noise thresholds can strongly affect ToE years, i.e. larger noise threshold induces later emergence, indicating the importance of noise estimation in the ToE assessment.
Key wordsTime of emergence regional climate models RCP scenarios Northeast Asia
Unable to display preview. Download preview PDF.
- Bindoff, N. L., and Coauthors, 2013: Detection and attribution of climate change: From global to regional. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the IPCC. Cambridge University Press, 867-952.Google Scholar
- Christensen, J. H., and Coauthors, 2007: Regional climate projections. In Climate Change, 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC. Cambridge University Press, 847–940.Google Scholar
- Christensen, J. H., and Coauthors, 2013: Climate phenomena and their relevance for future regional climate change. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the IPCC, Cambridge University Press, 1217–1308.Google Scholar
- King, A. M., M. T. Black, S.-K. Min, E. M. Fischer, D. M. Mitchell, L. J. Harrington, and S. E. Perkins-Kirkpatrick, 2016: Emergence of heat extremes attributable to anthropogenic influences. Geophys. Res. Lett., published online, doi:10.1002/2015GL067448.Google Scholar
- Min, S.-K., Y. H. Kim, M. K. Kim, and C. Park, 2014: Assessing human contribution to the summer 2013 Korean heat wave, In: Explaining extreme events of 2013 from a climate perspective. Bull. Amer. Meteor. Soc., 95, S48–S51.Google Scholar
- Seneviratne, S. I., and Coauthors, 2012: Changes in climate extremes and their impacts on the natural physical environment. In Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the IPCC. Cambridge University Press, Cambridge, 109–230.Google Scholar
- Suh, M.-S., and Coauthors, 2016: Projection of fine-scale climate change using muli-regional climate models and ensembles over South Korea based on four RCP scenarios. Part 1. Surface air temperature. Asia-Pac. J. Atmos. Sci., 52, doi:10.1007/s13143-016-0017-9.Google Scholar