Cooling and wetting of soil decelerated ground freezingethawing processes of the active layer in Xing'an permafrost regions in Northeast China

The accelerated or decelerated freezingethawing processes of the active layer in Xing'an permafrost regions are crucial for the protection of permafrost.To better understand the freezingethawing processes of the active layer and its driving factors,according to the observation from 2017 to 2020 of soil temperature and water content in the active layer of forest and peatland in two representative hemiboreal ecosystems in the Da Xing'anling Mountains,Northeast China,the study explored in detail the effects of climatic conditions and local factors on the hydrothermal and freezingethawing processes of active layer soils.The results showed that during the freezingethawing cycles of 2017-2020,freezing and thawing start times in the peatland and forest ecosystems soils were generally delayed,and it took longer for the active layer soil to completely thaw than to freeze.The annual average soil temperature in the peatland's active layer(5-80 cm)was 0.7-2.0℃ lower than that in the forest,and the annual average soil moisture content on the peatland was 5.5%-26.7%higher than that in the forest.Compared with the forest ecosystem soils,the ground surface freezing time of the peatland was delayed by 3e10 d,and the freezing rate decreased by 1.1-1.5 cm d1,while the beginning time of thawing was advanced by 22-27 d,and the thawing rate decreased by 1.3-1.4 cm d^(-1).In the process of decreasing soil temperature and increasing soil moisture content,the freezing and thawing rate of the active layer would be reduced,decelerating the freezingethawing processes of the active layer in the process of decreasing soil temperature and increasing soil moisture content.The results provide the key original data for studying the formation and evolution of active layer and permafrost in the Xing'an permafrost regions in Northeast China and can be used to validate the prediction of ecosystem succession under the combined influences of climate change and permafrost degradation.

Detecting surface freeze/thaw states in Northeast China with passive microwave data using an improved standard deviation method

Passive microwave remote sensing datasets are widely used to observe surface freeze/thaw(F/T)states.However,current algorithms are highly affected by snow cover and complex land cover types,compromising their performance.Therefore,this study proposes an improved algorithm for daytime detection of diurnal F/T states by using Advanced Microwave Scanning Radiometer 2 data.In the daytime F/T discrimination algorithm,a microwave spectral gradient index is applied to divide the surface into snow-covered and snow-free areas.In the snow-free area,the surface temperature index is optimised to improve the accuracy of the standard deviation method(SDM)in evaluating the accuracy of the F/T state.For the nighttime dataset,the microwave standard deviation index difference values between day and night are used to detect the F/T states based on the daytime results.The accuracy of the improved algorithm reaches 88.6%and 84.5%in the daytime and at nighttime,respectively.Compared with the SDM,the accuracy is improved by 10.2%in the daytime and 5.4%at nighttime.The results demonstrate that the proposed model is able to effectively distinguish the F/T states of snow-covered surfaces.Optimising the surface temperature index can significantly improve the accuracy of the SDM.The results reveal that the proposed surface F/T detection algorithm can be applied to regions with complex land cover types.