Reconciled estimation of Antarctic ice sheet mass balance and contribution to global sea level change from 1996 to 2021

The Antarctic Ice Sheet(AIS)has been losing ice mass and contributing to global sea level rise(GSLR).Given its mass that is enough to cause~58 m of GSLR,accurate estimation of mass balance trend is critical for AIS mass loss monitoring and sea level rise forecasting.Here,we present an improved approach to reconciled solutions of mass balance in AIS and its regions from multiple contributing solutions using the input-out,altimetric,and gravimetric methods.In comparison to previous methods,such as IMBIE 2018,this approach utilizes an adaptive data aggregation window to handle the heterogeneity of the contributing solutions,including the number of solutions,temporal distributions,uncertainties,and estimation techniques.We improved the regression-based method by using a two-step procedure that establishes ensembled solutions within each method(input-output,altimetry,or gravimetry)and then estimates the method-independent reconciled solutions.For the first time,16contributing solutions from 8 Chinese institutions are used to estimate the reconciled mass balance of AIS and its regions from1996 to 2021.Our results show that AIS has lost a total ice mass of~3213±253 Gt during the period,an equivalent of~8.9±0.7 mm of GSLR.There is a sustained mass loss acceleration since 2006,from 88.1±3.6 Gt yr^(-1)during 1996–2005 to 130.7±8.4 Gt yr^(-1)during 2006–2013 and further to 157.0±9.0 Gt yr^(-1)during 2014–2021.The mass loss signal in the West Antarctica and Antarctic Peninsula is dominant and clearly presented in the reconciled estimation and contributing solutions,regardless of estimation methods used and fluctuation of surface mass balance.Uncertainty and challenges remain in mass balance estimation in East Antarctica.This reconciled estimation approach can be extended and applied for improved mass balance estimation in the Greenland Ice Sheet and mountain glacier regions.

Singular spectrum analysis for the time-variable seasonal signals from GPS in Yunnan Province

Studying the seasonal deformation in GPS time series is important to interpreting geophysical contributors and identifying unmodeled and mismodeled seasonal signals.Traditional seasonal signal extraction used the least squares method,which models seasonal deformation as a constant seasonal amplitude and phase.However,the seasonal variations are not constant from year to year,and the seasonal amplitude and phase are time-variable.In order to obtain the time-variable seasonal signal in the GPS station coordinate time series,singular spectrum analysis(SSA)is conducted in this study.We firstly applied the SSA on simulated seasonal signals with different frequencies 1.00 cycle per year(cpy),1.04 cpy and with time-variable amplitude are superimposed.It was found that SSA can successfully obtain the seasonal variations with different frequencies and with time-variable amplitude superimposed.Then,SSA is carried out on the GPS observations in Yunnan Province.The results show that the time-variable amplitude seasonal signals are ubiquitous in Yunnan Province,and the timevariable amplitude change in 2019 in the region is extracted,which is further explained by the soil moisture mass loading and atmospheric pressure loading.After removing the two loading effects,the SSA obtained modulated seasonal signals which contain the obvious seasonal variations at frequency of 1.046 cpy,it is close with the GPS draconitic year,1.040 cpy.Hence,the time-variable amplitude changes in 2019 and the seasonal GPS draconitic year in the region could be discriminated successfully by SSA in Yunnan Province.