Soil moisture (SM) is one of the key measures to understand the land-atmosphere interaction and permafrost dynamics in the Qinghai-Tibet Plateau (QTP). ERA5-Land is a new reanalysis product with high spatial resolution (9 km), which can provide long-term SM data with a large spatial coverage as well as at multi-layer soil depths. However, preliminary comparisons with in-situ data show that the ERA5-Land SM product generally underestimates the seasonal variability and demonstrate a positive bias on the QTP. In this paper, we proposed to utilize the mode decomposition method to correct such bias. Specifically, through using the variational mode decomposition (VMD), we decomposed the long time-series of ERA5-Land SM data into a series of Intrinsic Mode Functions (IMFs), and found that the SM seasonal variation can be well represented by the low-frequency modes, which were then selected to feed a regression model for the bias correction. The single-site bias correction results show that our method significantly improves the accuracy of ERA5-Land SM product with bias reduced by 0.22 m 3 /m 3 , 0.31 m 3 /m 3 , 0.15 m 3 /m 3 for alpine meadow, alpine steppe, and alpine desert sites respectively. Together with the slightly reduced accuracy but still acceptable results for the cross-site bias correction, we successfully demonstrate the potential of the mode decomposition method for the bias correction of the ERA5-Land SM product at regional scale. Our method is of great use to study climate impact on regional ecohydrological processes and the permafrost changes in the QTP region.

Wilkes Land and Totten Glacier (TG) in East Antarctica (EA) have been losing ice mass significantly since 1989. There is a lack of knowledge of long-term mass balance in the region which hinders the estimation of its contribution to global sea level rise. Here we show that this acceleration trend in TG has occurred since the 1960s. We reconstruct ice flow velocity fields of 1963–1989 in TG from the first-generation satellite images of ARGON and Landsat-1&4, and build a five decade-long record of ice dynamics. We find a persistent long-term ice discharge rate of 68 ± 1 Gt/y and an acceleration of 0.17 ± 0.02 Gt/y2 from 1963 to 2018, making TG the greatest contributor to global sea level rise in EA. We attribute the long-term acceleration near grounding line from 1963 to 2018 to basal melting likely induced by warm modified Circumpolar Deep Water. The speed up in shelf front during 1973–1989 was caused by a large calving front retreat. As the current trend continues, intensified monitoring in the TG region is recommended in the next decades.

Abstract. High accuracy reconstruction of historical ice flow velocity fields is crucial in mass balance research of the Antarctic Ice Sheet by utilizing the input-output approach. A historical flow velocity of the Western Pacific Ocean sector region of East Antarctica from 1963 to 1989 was mapped and then corrected for its velocity overestimation. In this study, we analyzed the spatial distribution of the corrected values, and further assessed the relationship between the corrected values and related factors including timespan of image pairs, ice flow velocity, the spatial acceleration of ice flow velocity, and surface slope. The results indicate that the corrected ice flow velocity points are mostly dispersed between a buffer 25 km upstream and a buffer 25 km downstream the grounding line, with the largest mean value emerging in the region between the grounding line and its 25 km downstream. The corrected values exhibit linear correlation with three conditions: 1) when the ice flow velocity range is 0 – 1586 m/y, 2) spatial acceleration is 0 – 69 (m/y)/km, and 3) the slope is 0 – 1.95 degrees and the R2 is higher than 0.7. However, the correlation between timespan and corrected values is not obvious. The corrected values for the floating region have a greater linear correlation with all three factors than the inland region. Ice flow velocity, spatial acceleration, and surface slope all have an influence on the distribution of the corrected values of the reconstructed historical ice flow velocity maps, and may further affect the assessment of the mass balance of the Antarctic Ice Sheet.

<p>Accurate assessment of the state and changes of permafrost active layer thickness (ALT) on the Qinghai-Tibet Plateau (QTP) is critical to understanding the underlying processes driven by the global climate change. The Interferometric Synthetic Aperture Radar (InSAR) technology has been proven to be a method for quantifying deformation caused by natural and degradational processes of permafrost changes. Given its high accuracy, this method has been applied to monitoring local and regional permafrost deformation in QTP. However, there is a lack of improved large-scale regional ALT mapping algorithm using the accurate InSAR deformation data. Here, we examine the complex processes where the active layer melts spatio-temporally in depth during the thawing season, and the ground subsides due to the volume difference induced by the ice - water conversion. We developed a new model that infers ALT from the surface subsidence with help of other parameters in the process. This model takes the advantage of long-term InSAR derived deformation data, including both seasonal signal and inter-annual trend. In addition, it introduces an empirical parameter to represent the contribution of the ice-water phase change with consideration of additional water contribution from other sources. We implemented the developed method in Kekexili regional of the QTP. The seasonal deformation was obtained from radar images of Sentinel-1 by using the Small Baseline Subset Interferometry (SBAS-InSAR) technology. The thawing water was estimated in combination with soil moisture, precipitation, evapotranspiration and runoff data. Based on deformation data, vegetation cover information and existing ALT products, the empirical parameter was obtained by a data-driven regression method. Finally, a new InSAR-derived permafrost ALT map in the Kekexili region from 2015 to 2020 is produced. The results show that the average ALT is of 1.94 m with a standard deviation of 0.35 m. A comparative discussion with permafrost maps produced using other methods is given.</p> <p> </p>

Abstract. Active layer thickness (ALT) is an important index to reflect the stability of permafrost. The retrieval of ALT based on Interferometric Synthetic Aperture Radar (InSAR) technology has been investigated recently in permafrost research. However, most of such studies are carried out in a limited extend and relatively short temporal coverage. The combination of temporal-spatial multi-layer soil moisture data and multi-temporal InSAR is a promising approach for the large-scale characterization of ALT. In this study, we employed Small Baseline Subset Interferometry (SBAS-InSAR) technology to obtain the seasonal surface deformation from radar images of Envisat and Sentinel-1 in a permafrost region of Qinghai-Tibet Plateau (QTP). We attempt to verify and calibrate the temporal-spatial multi-layer soil moisture product in combination with the in-situ data. Based on the land subsidence data and the temporal-spatial multi-layer soil moisture data, we further improve method to retrieve the ALT information. This paper describes the progress so far and point out the future work.

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