Arctic warming revealed by multiple CMIP6 models: evaluation of historical simulations and quantification of future projection uncertainties

View More View Less
  • 1 Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, 200438, Shanghai, China;
  • 2 Innovation Center of Ocean and Atmosphere System, Zhuhai Fudan Innovation Research Institute, Zhuhai, 518057, China;
  • 3 Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science and Technology (NUIST), Nanjing, Jiangsu 210044, China;
  • 4 Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden;
  • 5 Regional Climate Group, Department of Earth Sciences, University of Gothenburg, S-405 30 Gothenburg, Sweden;
  • 6 Atmospheric and Environmental Research Inc., Lexington, MA, USA;
  • 7 Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
© Get Permissions
Restricted access

Abstract

The Arctic has experienced a warming rate higher than the global mean in the past decades, but previous studies show that there are large uncertainties associated with future Arctic temperature projections. In this study, near-surface mean temperatures in the Arctic are analyzed from 22 models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). Compared with the ERA5 reanalysis, most CMIP6 models underestimate the observed mean temperature in the Arctic during 1979–2014. The largest cold biases are found over the Norwegian Sea, the Barents Sea, and the Kara Sea. Under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, the multi-model ensemble mean of 22 CMIP6 models exhibits significant Arctic warming in the future and the warming rate is more than twice higher than rates in the global/Northern Hemisphere. Model uncertainty is the largest contributor to the overall uncertainty in projections, which accounts for 55.4% of the total uncertainty at the start of projections in 2015 and remains at 32.9% at the end of projections in 2095. Internal variability uncertainty accounts for 39.3% of the total uncertainty at the start of projections but decreases to 6.5% at the end of the 21st century, while scenario uncertainty rapidly increases from 5.3% to 60.7% over the period from 2015-2095. It is found that the largest model uncertainties are consistent with the oceanic regions with cold biases in the models, which is connected with excessive sea ice area caused by the weak Atlantic poleward heat transport. These results suggest that the CMIP6 models’ simulation and projection of the Arctic near-surface temperature still exist large inter-model spread and uncertainties, and there are different behaviors over the ocean and land in the Arctic. Future research needs to pay more attention to the different characteristics and mechanisms of Arctic Ocean and land warming to reduce the spread.

Corresponding author: Prof. Qinglong You, Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Room 5002-1,Environmental Science Building, No.2005 Songhu Road, Yangpu 200438, Shanghai, China. Email: qlyou@fudan.edu.cn; yqingl@126.com

Abstract

The Arctic has experienced a warming rate higher than the global mean in the past decades, but previous studies show that there are large uncertainties associated with future Arctic temperature projections. In this study, near-surface mean temperatures in the Arctic are analyzed from 22 models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). Compared with the ERA5 reanalysis, most CMIP6 models underestimate the observed mean temperature in the Arctic during 1979–2014. The largest cold biases are found over the Norwegian Sea, the Barents Sea, and the Kara Sea. Under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, the multi-model ensemble mean of 22 CMIP6 models exhibits significant Arctic warming in the future and the warming rate is more than twice higher than rates in the global/Northern Hemisphere. Model uncertainty is the largest contributor to the overall uncertainty in projections, which accounts for 55.4% of the total uncertainty at the start of projections in 2015 and remains at 32.9% at the end of projections in 2095. Internal variability uncertainty accounts for 39.3% of the total uncertainty at the start of projections but decreases to 6.5% at the end of the 21st century, while scenario uncertainty rapidly increases from 5.3% to 60.7% over the period from 2015-2095. It is found that the largest model uncertainties are consistent with the oceanic regions with cold biases in the models, which is connected with excessive sea ice area caused by the weak Atlantic poleward heat transport. These results suggest that the CMIP6 models’ simulation and projection of the Arctic near-surface temperature still exist large inter-model spread and uncertainties, and there are different behaviors over the ocean and land in the Arctic. Future research needs to pay more attention to the different characteristics and mechanisms of Arctic Ocean and land warming to reduce the spread.

Corresponding author: Prof. Qinglong You, Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Room 5002-1,Environmental Science Building, No.2005 Songhu Road, Yangpu 200438, Shanghai, China. Email: qlyou@fudan.edu.cn; yqingl@126.com
Save