The predictability, irreversibility and deep uncertainty of cryospheric change

doi:10.12006/j.issn.1673-1719.2021.247

Abstract

Abstract:

The IPCC AR6 Working Group I gives new understandings of the predictability, irreversibility and deep uncertainty of various elements of the climate system. This paper summarizes the above three aspects of cryospheric changes in global and regional scales. In general, on the hemispheric and global scales, regardless of the emission scenario, all cryospheric elements could have certain predictability in the 21st century, i.e., they all change in the direction of melting or degradation, mostly irreversible. However, on the regional scale, short time scales and long-term commitment, different cryospheric elements may exhibit large internal variability, poor predictability and even deep uncertainty.

Key words: Cryosphere, IPCC AR6, Interpretation, Knowledge advances, Knowledge gaps

XIAO Cun-De, YANG Jiao, ZHANG Tong, SU Bo, WANG Lei, XU Qian, YAN Zhan, HAO Hai-Rui, HUANG Yi. The predictability, irreversibility and deep uncertainty of cryospheric change[J]. Climate Change Research, 2022, 18(1): 1-11.

Figures/Tables 5

Fig. 1 Arctic sea-ice historical records and CMIP6 projections (a) absolute anomaly of monthly-mean Arctic sea-ice area during 1979-2019 relative to the average monthly-mean Arctic sea-ice area during 1979-2008, (b) sea-ice concentration in the Arctic for March and September, respectively. First column: absolute change in sea-ice concentration between these two decades, with grid lines indicating non-significant differences. Second column: number of available CMIP6 models that simulate a mean sea-ice concentration above 15% for the decade 2045-2054

Fig. 2 (a) changes in mean elevation of the Greenland ice sheet from 2010 to 2017 as measured by CryoSat 2 radar altimeter, (b) model averages of elevation changes of the Greenland ice sheet in 2093-2100 based on MIROC5 climate model output simulations under the RCP8.5 scenario, (c) elevation changes of the Antarctic ice sheet from 1978 to 2017 as measured by satellite altimeters, (d) model averages for 2061-2100 Antarctic ice sheet elevation changes based on NorESM1-M climate model output simulations under the RCP8.5 scenario

Fig. 3 Global and regional glacier mass evolution between 1901 and 2100 relative to glacier mass in 2015

Fig. 4 Simulated versus observed permafrost extent and permafrost volume change by warming level. (a) Diagnosed Northern Hemisphere permafrost extent (area with perennially frozen ground at 15 m depth, or at the deepest model soil level if this is above 15 m) for 1979-1998, estimates of current permafrost extents based on physical evidence and reanalyses are indicated as black symbols (data from references [24,25,26]); (b) Simulated global permafrost volume change between the surface and 3 m depth as a function of the simulated GSAT change, from the first ensemble members of a selection of scenarios, for available CMIP6 models

Fig. 5 (a) Simulated CMIP6 and observed[29] snow cover extent (in millions of km2) for 1981-2014. Boxes and whiskers with outliers represent monthly mean values for the individual CMIP6 models averaged over 1981-2014, with the blue bar indicating the median of the CMIP6 multi-model ensemble for that period. The observed inter-annual distribution over the period is represented in green, with the yellow bar indicating the median. (b) Spring (March to May) Northern Hemisphere snow cover extent against GSAT (relative to the 1995-2014 average) for the CMIP6 Tier 1 scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5), with linear regressions. Each data point is the mean for one CMIP6 simulation (first ensemble member for each available model) in the corresponding temperature bin

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