An Independent Degree-eight Mars Gravity Field Model and the Expected Results from the Tianwen-1 Mission

Tianwen-1 is China's first independent interplanetary exploration mission,targeting Mars,and includes orbiting,landing,and rover phases.Similar to previous Mars missions,the Tianwen-1 orbiter was designed for polar orbits during the scientific mission period but has an exceptional eccentricity of approximately 0.59.We provide the first independent eight-degree Martian gravity field model in this paper,which was developed exclusively by a team working in China with our independent software as well,based on about two months of radiometric Doppler and range data from only the Tianwen-1 mission.This model is independent from the models created by the groups at NASA Jet Propulsion Laboratory and Goddard Space Flight Center in the United States,as well as the Centre National d'Etudes Spatiales in France.Furthermore,in order to optimize the engineering and scientific benefits,we proposed a number of potential orbits for the extended Tianwen-1 mission.In order to solve a higher-degree independent Mars gravity field model,the viability of modifying the perigee height was investigated,with the priority considerations of fuel savings and implementation hazards being controlled.

Consistency of MGEX Orbit and Clock Products

The analysis centers of the Multi-GNSS Pilot Project of the International GNSS Service provide orbit and clock products for the global navigation satellite systems(GNSSs)Global Positioning System(GPS),GLONASS,Galileo,and BeiDou,as well as for the Japanese regional Quasi-Zenith Satellite System(QZSS).Due to improved solar radiation pressure modeling and other more sophisticated models,the consistency of these products has improved in recent years.The current orbit consistency between different analysis centers is on the level of a few centimeters for GPS,around one decimeter for GLONASS and Galileo,a few decimeters for BeiDou-2,and several decimeters for QZSS.The clock consistency is about 2 cm for GPS,5 cm for GLONASS and Galileo,and 10 cm for BeiDou-2.In terms of carrier phase modeling error for precise point positioning,the various products exhibit consistencies of 2–3 cm for GPS,6–14 cm for GLONASS,3–10 cm for Galileo,and 10–17 cm for BeiDou-2.

Inversion of Venus internal structure based on geodetic data

Understanding the internal structure of Venus promotes the exploration of the evolutionary history of this planet.However,the existing research concerning the internal structure of Venus has not used any inversion methods.In this work we employed an inversion method to determine the internal structure of Venus using observational or hypothetical geodetic data;these data include mass,mean radius,mean moment of inertia and second degree tidal Love number k2.To determine the core state of Venus,we created two models of Venus,an isotropic 3-layer model with entire liquid core and an isotropic 4-layer model with liquid outer core and a solid inner core,assuming that the interior of Venus is spherically symmetric and in hydrostatic equilibrium.A series of the sensitivity analysis of interior structure parameters to the geodetic data considered in here shows that not all of the parameters can be constrained by the geodetic data from Venus.On this basis,a Markov Chain Monte Carlo algorithm was used to determine the posterior probability distribution and the optimal values of the internal structure parameters of Venus with the geodetic data.We found that the 3-layer model is more credible than the 4-layer model via currently geodetic data.For the assumption of the 3-layer model with the k2=0.295±0.066,I/MR^2=0.33±0.0165,andρ=5242.7±2.6 kg m^-3,the liquid iron-rich core of Venus has a radius of 3294+215-261km,which suggests a larger core than previous research has indicated.The average density of the mantle and liquid core of Venus are 4101+325-375and 11885+955-1242kg m~^-3,respectively.

Earth rotation parameter and variation during 2005—2010 solved with LAGEOS SLR data

Time series of Earth rotation parameters were estimated from range data measured by the satellite laser ranging technique to the Laser Geodynamics Satellites（LAGEOS）-1/2 through 2005 to 2010 using the dynamic method. Compared with Earth orientation parameter（EOP）C04, released by the International Earth Rotation and Reference Systems Service, the root mean square errors for the measured X and Y of polar motion（PM） and length of day（LOD）were 0.24 and 0.25 milliarcseconds（mas）, and 0.068 milliseconds（ms）, respectively.Compared with ILRSA EOP, the X and Y of PM and LOD were 0.27 and 0.30 mas, and 0.054 ms, respectively. The time series were analyzed using the wavelet transformation and least squares methods. Wavelet analysis showed obvious seasonal and interannual variations of LOD, and both annual and Chandler variations of PM; however, the annual variation could not be distinguished from the Chandler variation because the two frequencies were very close. The trends and periodic variations of LOD and PM were obtained in the least squares sense, and PM showed semi-annual, annual, and Chandler periods.Semi-annual, annual, and quasi-biennial cycles for LOD were also detected. The trend rates of PM in the X and Y directions were 3.17 and 1.60 mas per year, respectively, and the North Pole moved to 26.8E relative to the crust during 2005—2010. The trend rate of the LOD change was 0.028 ms per year.

Strong Spatial Aggregation of Martian Surface Temperature Shaped by Spatial and Seasonal Variations in Meteorological and Environmental Factors

Spatio-temporal variation in the Martian surface temperature(MST)is an indicator of ground level thermal processes and hence a building block for climate models.However,the distribution of MST exhibits different levels of spatial aggregation or heterogeneity,and varies in space and time.Furthermore,the effect of regional differences in meteorological or environmental factors on the MST is not well understood.Thus,we investigated the degree of spatial autocorrelation of MST across the surface of Mars globally by Moran’s I,and identified the hot spots by GetisOrd G;*.We also estimated the regional differences in the influence of seasonally dominant factors including thermal inertia(TI),albedo,surface pressure,latitude,dust and slope on MST by a geographically weighted regression model.The results indicate(1)that MST is spatially aggregated and hot and cold spots varied over time and space.(2)Hemispheric differences in topography,surface TI and albedo were primarily responsible for the hemispheric asymmetry of hot spots.(3)The dominant factors varied by geographical locations and seasons.For example,the seasonal Hadley circulation dominates at the low-latitudes and CO;circulation at the high-latitudes.(4)Regions with extreme variations in topography and low TI were sensitive to meteorological and environmental factors such as dust and CO_(2)ice.We conclude that the spatial autocorrelation of MST and the spatial and seasonal heterogeneity of influencing factors must be considered when simulating Martian climate models.This work provides a reference for further exploration of Martian climatic processes.