Lake level change in the Tibetan Plateau is an important indicator for regional and global climate changes. We use altimeter data from Cryosat-2, SARAL, ICESat, and Jason-2 to detect lake level changes at different spatial and temporal resolutions over 2003-2017 (Jason-3 data in 2017 for validation). Cryosat-2's SARIn mode provides precise water level time series over 59 lakes. SARAL's waveforms are retracked to generate near monthly, high-quality measurements at 31 lakes. Jason-2 provides a reference for removing inter-altimeter biases, enabling coherent records over lakes with Jason-2 passes. After a decade of rise since the ICESat record of 2003, the lake levels of Nam Co, Selin Co, Ngangzi Co, and Chibuzhang Co became flat in 2014-2016 and started to fluctuate or decline after 2016. Such positive-flat-negative trends are consistent with the trend variations of mass change from Gravity Recovery and Climate Experiment (GRACE). SARAL detected persistent lake level declines over 2013-2016 in southern Tibet that may signify the onset of decadal reduced flows of the Yarlung Tsangpo and Brahmaputra River that could affect the water supply for their downstream regions in India and Bangladesh. Cryosat-2 and Jason-2 detected sudden lake level rises and falls around Zhuonai, Kusai, and Salt Lake associated with a 2011 lake outburst, which is confirmed by lake volume changes from two Landsat-7 images. With a careful processing and calibration, multiple altimeters allow for determining and cross-validating long-term and episodic lake level changes unachievable by a single altimeter.
With strong support from European Space Agency (ESA), Shanghai Astronomical Observatory (SHAO) organized a tracking and orbit determination trails using Chinese VLBI Network (CVN) to track Mars Express, the first Mars probe launched by ESA. Using a high-resolution VLBI software correlator and Doppler measurement system developed in-house, two sets of tracking data, VLBI and Doppler, were acquired. The trials represent the first successful foray held in China to track a probe about 360 million kilometers away from the Earth. The tracking data are analyzed using a Mars satellite orbit determination software system developed at SHAO. The results show that the accuracy of 5 s integrated three-way-Doppler data is about 0.3 mm/s, or roughly the same accuracy as ESA's tracking data. Position discrepancies between the Doppler-based orbit solution of 8 h arc-length (about 1 orbital revolution) and ESA's reconstructed orbit are of the order of several hundred meters. In preparing for the Russia-China co-sponsored Mars exploration mission Phobos-Grunt-YingHuo, simulations were carried out to evaluate the achievable orbital accuracy levels and the contributions of VLBI and Doppler data respectively. Results show that Doppler data provide better orbit accuracy, so that for VLBI to be able to provide kilometer level orbit solutions, the accuracy of VLBI measurement needs to be improved by at least one order of magnitude.
VLBI, MEX, orbit determination
Citation:Cao J F, Huang Y, Hu X G, et al. Mars Express tracking and orbit determination trials with Chinese VLBI network.
S U M M A R YFormulas are derived that relate the strength of the crosstalk noise in supergather migration images to the variance of time, amplitude and polarity shifts in encoding functions. A supergather migration image is computed by migrating an encoded supergather, where the supergather is formed by stacking a large number of encoded shot gathers. Analysis reveals that for temporal source static shifts in each shot gather, the crosstalk noise is exponentially reduced with increasing variance of the static shift and the square of source frequency. This is not too surprising because larger time shifts lead to less correlation between traces in different shot gathers, and so should tend to reduce the crosstalk noise. Analysis also reveals that combining both polarity and time statics is a superior encoding strategy compared to using either polarity statics or time statics alone.Signal-to-noise (SNR) estimates show that SNR stand. = √ G S for a standard migration image and SNR super = √ G I for an image computed by migrating a phase-encoded supergather; here, G is the number of traces in a shot gather, I is the number of stacking iterations in the supergather and S is the number of encoded/blended shot gathers that comprise the supergather. If the supergather can be uniformly divided up into Q unique sub-supergathers, then the resulting SNR of the final image is SNR sub-super = √ QG I , which means that we can enhance image quality but at the expense of Q times more cost. The importance of these formulas is that they provide a precise understanding between different phase encoding strategies and image quality.Finally, we show that iterative migration of phase-encoded supergathers is a special case of passive seismic interferometry. We suggest that the crosstalk noise formulas can be helpful in designing optimal strategies for passive seismic interferometry and efficient extraction of Green's functions from simulated supergathers.
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