Spatial modeling of permafrost distribution and properties on the Qinghai‐Tibet Plateau

Geophysical Research Letters

et al. 2019

Self Cite

Winter warming is fast than summer warming on the Qinghai-Tibet Plateau (QTP). However, no assessment of winter warming effects on permafrost has been attempted. Here we conducted hypothetical control experiments and used the Noah land surface model to evaluate the impacts of winter warming on the QTP permafrost. The results show that air temperature in winter (November-April) was increasing at a rate of 0.66°C/decade during 1980s−2000s, over double that in summer (May-October). The mean annual ground temperature of permafrost increased by 0.13°C/decade. The summer warming dominated the variations in thermal regime of permafrost before 2000. After that, the influence of winter warming on permafrost thermal regime has gradually grown and exceeded that of summer warming. Winter warming has amplified the thermal degradation of permafrost. Our findings reveal that alpine continuous permafrost on the northern QTP has experienced a prominent regional warming due to rapid winter warming since 2000. Plain Language Summary As the highest and largest permafrost region in mid-latitudes,Qinghai-Tibet Plateau (QTP) has experienced prominent winter warming in the past three decades. To date, no study has been made to assess the impacts of winter warming on the QTP permafrost. We used the Noah land surface model to investigate this effect, based on controlled experiments including a baseline representing historical climate conditions and two intentionally constituted hypothetical experiments that remove the winter (November-April) or summer (May-October) warming from the historical records. We analyzed the seasonal changes in air temperature, evaluated the effects of winter and summer warming on the changes of frozen ground in terms of several key indicators (including active layer thickness, permafrost area, mean annual ground temperature of permafrost, and maximum freezing depth of seasonally frozen ground) and investigated the possible underlying mechanism of winter warming on permafrost. The results indicate that winter warming accelerates permafrost thermal degradation. Especially since 2000, alpine continuous permafrost on the Qiangtang High Plain, Northern QTP, has undergone an obvious regional warming induced by rapid winter warming.

Section: Model and Experimentsmentioning

confidence: 99%

The Role of Winter Warming in Permafrost Change Over the Qinghai‐Tibet Plateau

Geophysical Research Letters

et al. 2019

Self Cite

“…In recent decades, many maps have been produced to estimate permafrost distribution at different scales over the QTP using statistical and (semi‐)physical methods (e.g …”

Section: Introductionmentioning

confidence: 99%

“…These maps were usually produced at very small scales (from 1:600,000 to 1:10,000,000) and used a categorical classification (such as permafrost, seasonally frozen ground and unfrozen ground) to delineate permafrost regions . More recently, due to the increased availability of high‐resolution meteorological data sets, several higher resolution (∼ 1–10 km) maps were developed which represent permafrost distribution as a binary presence or absence classification . Based on the TTOP model and improved MODIS land surface temperature, Zou et al presented a new permafrost map over the QTP with a spatial resolution of 1 km.…”

Section: Introductionmentioning

confidence: 99%

“…The overall accuracy of this map was reported to be about 82% . Applying numerical models to permafrost mapping in mountainous regions is challenging due to the need for high‐resolution meteorological data to drive the model, which is difficult to obtain …”

Section: Introductionmentioning

confidence: 99%

“…In recent decades, many maps have been produced to estimate permafrost distribution at different scales over the QTP using statistical and (semi-)physical methods (e.g. [10][11][12][13] ). These maps were usually produced at very small scales (from 1:600,000 to 1:10,000,000) and used a categorical classification (such as permafrost, seasonally frozen ground and unfrozen ground) to delineate permafrost regions.…”

mentioning

confidence: 99%

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Permafrost zonation index map and statistics over the Qinghai–Tibet Plateau based on field evidence

Cao

Permafrost & Periglacial

et al. 2019

Self Cite

Permafrost is prevalent over the Qinghai–Tibet Plateau (QTP), but mapping its distribution is challenging due to the limited availability of ground‐truth data sets and strong spatial heterogeneity in the region. Based on a recently developed inventory of permafrost presence or absence from 1475 in situ observations, we developed and trained a statistical model and used it to compile a high‐resolution (30 arc‐seconds) permafrost zonation index (PZI) map. The PZI model captures the high spatial variability of permafrost distribution over the QTP because it considers multiple controlling variables, including near‐surface air temperature downscaled from re‐analysis, snow cover days and vegetation cover derived from remote sensing. Our results showed the new PZI map achieved the best performance compared to available existing PZI and traditional categorical maps. Based on more than 1000 in situ measurements, the Cohen's kappa coefficient and overall classification accuracy were 0.62 and 82.5%, respectively. Excluding glaciers and lakes, the area of permafrost regions over the QTP is approximately 1.54 (1.35–1.66) ×106 km2, or 60.7 (54.5–65.2)% of the exposed land, while area underlain by permafrost is about 1.17 (0.95–1.35) ×106 km2, or 46 (37.3–53.0)%.

Simulating the freeze-thaw and buried ice melting process of the Longbasaba moraine dam (Himalayas) based on the heat transfer module of COMSOL Multiphysics from 1959 to 2100

Wang

et al. 2022

Preprint

Permafrost degradation poses an increasingly serious threat of glacial lake outburst floodings (GLOFs) in the Tibetan Plateau. It is therefore of great practical significance to analyze the freeze-thaw state in moraine dams and associated impacts on dam stability. We simulated the soil temperature of the Longbasaba moraine dam based on the heat transfer module of COMSOL Multiphysics. The results show that the soil temperature of the moraine dam can be adequately simulated using the COMSOL Multiphysics heat transfer module and the simulated temperature values are generally consistent with the observed trends, yielding root mean square errors (RMSEs) less than 1.58 and Nash-Sutcliffe efficiency coefficients (NSEs) between 0.66 and 0.93. The average annual increase of the active layer depth was 0.026 m/a from 1959 to 2020. The buried ice inside the moraine dam was evidently melting and the maximum buried ice thawing depth under scenarios SSP1-2.6, SSP2-4.5, and SSP5-8.5 in CMIP6 (Coupled Model Intercomparison Project Phase 6) is expected to be 11.3 m, 18.4 m, and 23.5 m, respectively, by the end of the century, which indicates a continuous deterioration of the moraine dam stability.