Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

Abstract

Abstract. We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern standalone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135 × 10 4 km 2 ) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101 × 10 4 km 2 ). However the uncertainty (1 to 128 × 10 4 km 2 ) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using airtemperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 • C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

Simulating the roles of crevasse routing of surface water and basal friction on the surge evolution of Basin 3, Austfonna ice cap

“…5c), estimations of statistical quality of the simulated crevasse field with the observationally derived map are necessary. We calculated the Kappa coefficient (K) (Wang et al, 2016) to quantify the agreement, but this is not trivial as almost any two maps will be significantly different, with large sample sizes (> 62 483) (Monserud and Leemans, 1992). We achieve moderate agreement (Cohen, 1960), (K = 0.45) when resampling the two maps with a 1.5 × 1.5 km smoothing window and substantial agreement (K = 0.71) with a 4.6 × 4.6 km smoothing window.…”

Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site

“…Onedimensional models of subsurface water and energy transport that incorporate freezing phenomena have a long history; comprehensive reviews are provided by (Kurylyk et al, 2014;Kurylyk and Watanabe, 2013;Walvoord and Kurylyk, 2016). Those one-dimensional models have been adapted to model the impacts of climate warming on permafrost thaw and the associated hydrological changes at regional and pan-Arctic scales (Jafarov et al, 2012;Slater and Lawrence, 2013;Koven et al, 2013;Gisnås et al, 2013;Chadburn et al, 2015;Wang et al, 2016;Guimberteau et al, 2018;Wang et al, 2019;Tao et al, 2018;Yi et al, 2019). At the smaller scales and higher spatial resolutions required to assess local impacts, processes that can be neglected at larger scales come into play creating additional modeling challenges (Painter et al, 2013).…”

Effect of climate and thaw depth on alpine vegetation variations at different permafrost degrading stages in the Tibetan Plateau, China

“…Compared with high-latitude permafrost, permafrost in the Tibetan Plateau is warmer and shallower (Wu and Zhang 2008;Wu, Zhang, and Liu 2010;Yang et al 2010). Therefore, permafrost in the Tibetan Plateau is more sensitive to air temperature changes and it is considered the key indicator for climate and environment changes (Wang et al 2016). During recent decades, a significant climate warming occurred on the Tibetan Plateau and the increase in temperature came earlier and faster than in other parts of China (Pan and Li 1996;Liu and Chen 2000;Wang et al 2000;Cheng and Wu 2007;Kuang and Jiao 2016;Lu, Zhao, and Wu 2017).…”