Analysis of influence of observation operator on sequential data assimilation through soil temperature simulation with common land model

An observation operator is a bridge linking the system state vector and observations in a data assimilation system. Despite its importance, the degree to which an observation operator influences the performance of data assimilation methods is still poorly understood. This study aimed to analyze the influences of linear and nonlinear observation operators on the sequential data assimilation through soil temperature simulation using the unscented particle filter(UPF) and the common land model. The linear observation operator between unprocessed simulations and observations was first established. To improve the correlation between simulations and observations, both were processed based on a series of equations. This processing essentially resulted in a nonlinear observation operator. The linear and nonlinear observation operators were then used along with the UPF in three assimilation experiments: an hourly in situ soil surface temperature assimilation, a daily in situ soil surface temperature assimilation, and a moderate resolution imaging spectroradiometer(MODIS) land surface temperature(LST) assimilation. The results show that the filter improved the soil temperature simulation significantly with the linear and nonlinear observation operators. The nonlinear observation operator improved the UPF's performance more significantly for the hourly and daily in situ observation assimilations than the linear observation operator did, while the situation was opposite for the MODIS LST assimilation. Because of the high assimilation frequency and data quality, the simulation accuracy was significantly improved in all soil layers for hourly in situ soil surface temperature assimilation, while the significant improvements of the simulation accuracy were limited to the lower soil layers for the assimilation experiments with low assimilation frequency or low data quality.

Changes in global land surface frozen ground and freeze-thaw processes during 1950-2020 based on ERA5-Land data

Frozen ground(FG)plays an important role in global and regional climates and environments through changes in land freeze-thaw processes,which have been conducted mainly in different regions.However,the changes in land surface freeze-thaw processes under climate change on a global scale are still unclear.Based on ERA5-Land hourly land skin temperature data,this study evaluated changes in the global FG area,global land surface first freeze date(FFD),last freeze date(LFD)and frost-free period(FFP)from 1950 to 2020.The results show that the current FG areas(1991-2020 mean)in the Northern Hemisphere(NH),Southern Hemisphere(SH),and globe are 68.50×10^(6),9.03×10^(6),and 77.53×10^(6)km^(2),which account for 72.4%,26.8%,and 60.4%of the exposed land(excluding glaciers,ice sheets,and water bodies)in the NH,SH and the globe,respectively;further,relative to 1951-1980,the FG area decreased by 1.9%,8.8%,and 2.8%,respectively.Seasonally FG at lower latitudes degrades to intermittently FG,and intermittently FG degrades to non-frozen ground,which caused the global FG boundary to retreat to higher latitudes from 1950 to 2020.The annual FG areas in the NH,SH,and globe all show significant decreasing trends(p<0.05)from 1950 to 2020 at-0.32×10^(6),-0.22×10^(6),and-0.54×10^(6)km^(2)per decade,respectively.The FFP prolongation in the NH is mainly influenced by LFD advance,while in the SH it is mainly controlled by FFD delay.The prolongation trend of FFP in the NH(1.34 d per decade)is larger than that in the SH(1.15 d per decade).

Spatial differences of ice volume across High Mountain Asia

Advanced knowledge of glacier ice volume is vital for water resource assessment.Previous studies have focused on the estimation of ice volume,but the quantitative understanding of the spatial variability of ice volume across High Mountain regions is currently lacking.Here,we used global-scale ice thickness,debris cover and equilibrium line data to analyse ice-volume differences at various scales across High Mountain Asia(HMA).The results showed that 6.3%of the HMA glaciers are covered by debris,with debris area and volume accounting for 9%and 13.8%of the total glacier area and volume,respectively.An average debris-cover volume ratio of 13%was observed.The spatial distribution of ice volume across the HMA varies considerably from region to region.The ice volume is predominately distributed on north-facing slopes and accounts for approximately 38%of the total.It is very common in Altay and Sayan,East Tian Shan,West Kunlun,East Kunlun and Qilian Shan.Meanwhile,ice volumes in the Himalayas and Hengduan Shan are mainly distributed on the southeast aspect.Relative weight functions showed that glacier area,maximum length and average thickness are closely related to ice volume,with average relative weights of 63.7%,22.5%and 9.8%,respectively.This study is important for the evolution of glacier volume and water resource assessment.