Accurate and rapid error estimation on global gravitational field from current GRACE and future GRACE Follow-On missions

Firstly, the new combined error model of cumulative geoid height influenced by four error sources, including the inter-satellite range-rate of an interferometric laser （K-band） ranging system, the orbital position and velocity of a global positioning system （GPS） receiver and non-conservative force of an accelerometer, is established from the perspectives of the power spectrum principle in physics using the semi-analytical approach. Secondly, the accuracy of the global gravitational field is accurately and rapidly estimated based on the combined error model; the cumulative geoid height error is 1.985× 10^-1 m at degree 120 based on GRACE Level 1B measured observation errors of the year 2007 published by the US Jet Propulsion Laboratory （JPL）, and the cumulative geoid height error is 5.825 × 10^-2 m at degree 360 using GRACE Follow-On orbital altitude 250 km and inter-satellite range 50 km. The matching relationship of accuracy indexes from GRACE Follow-On key payloads is brought forward, and the dependability of the combined error model is validated. Finally, the feasibility of high-accuracy and high-resolution global gravitational field estimation from GRACE Follow-On is demonstrated based on different satellite orbital altitudes.

Recent Status of Taiji Program in China

The Taiji-1 satellite is a pilot satellite mission of Taiji program,which is used to verify Taiji’s key technology and also to testify the feasibility of Taiji roadmap.Taiji-1 was launched on 31 August 2019 and its designed mission was successfully completed.The in-orbit scientific achievements of Taiji-1 satellite in the first stage have been published and now it has entered the extended task phase.Taiji-2 will prepare all the technology needed by Taiji-3,and remove all the technical obstacles faced by Taiji-3.

Crop residue incorporation and nitrogen fertilizer effects on greenhouse gas emissions from a subtropical rice system in Southwest China

Crop residue incorporation has been widely accepted as a way to increase soil carbon(C) sequestration and sustain soil fertility in agroecosystems. However, effect of crop residue incorporation on greenhouse gas(GHG) emissions in rice paddy soils remains uncertain. A field experiment was conducted to quantify emissions of CH_4 and N_2O and soil heterotrophic respiration(RH) from a paddy rice field under five different crop residue treatments(i.e., 150 kg N ha^(-1) of synthetic N fertilizer application only [NF], 150kg N ha^(-1) of synthetic N fertilizer plus 5.3 Mg ha^(-1) wheat residue [NF-WR1], 150 kg N ha^(-1) of synthetic N fertilizer plus 10.6 Mg ha^(-1) wheat residue [NF-WR2], 75 kg N ha^(-1) of synthetic N fertilizer plus 10.6 Mg ha^(-1) wheat residue [50%NF-WR2] and 150 kg N ha^(-1) of synthetic N fertilizer plus 21.2 Mg ha^(-1) wheat residue [NF-WR3]) in southwest China. Our results showed that crop residue incorporation treatments(NF-WR1, NF-WR2, 50%NF-WR2, NF-WR3) significantly increased CH_4 emissions by at least 60%, but N_2O emissions were not enhanced and even suppressed by 25% in the NF-WR3 treatment as compared to the NF treatment. Soil RH emissions were comparable among experimental treatments, while crop residue incorporation treatments significantly increased soil carbon sequestrations relative to the NF treatment. Overall, CH_4 emissions dominated total global warming potentials(GWP) across all experimental treatments. The average yieldscaled GWPs for the NF and NF-WR1 treatments were significantly lower than for the NF-WR2, 50%NFWR2 and NF-WR3 treatments. Given the comparable yield-scaled GWPs between the NF and NF-WR1 treatments, the NF-WR1 treatment could gain net carbon sequestration as compared with the NF treatment with net soil carbon loss. Our findings suggest that the NF-WR1 treatment should be an effective option to sustain rice production while mitigating GHG emissions from the rice field in China.

Halton-type sequences from global function fields

For any prime power q and any dimension s≥1, a new construction of (t, s)-sequences in base q using global function fields is presented. The construction yields an analog of Halton sequences for global function fields. It is the first general construction of (t, s)-sequences that is not directly based on the digital method. The construction can also be put into the framework of the theory of (u, e, s)-sequences that was recently introduced by Tezuka and leads in this way to better discrepancy bounds for the constructed sequences.

Seasonal and interannual variabilities of mean velocity of Kuroshio based on satellite data

Combining sea level anomalies with the mean dynamic topography derived from the geoid of the EGM08 global gravity field model and the CLS01 mean sea surface height, this study examined the characteristics of global geostrophic surface currents and the seasonal and interannual variabilities of the mean velocity of the Kuroshio （the Kuroshio source and Kuroshio extension）. The patterns of global geostrophic surface currents we derived and the actual ocean circulation are basically the same. The mean velocity of the Kuroshio source is high in winter and low in fall, and its seasonal variability accounts for 18% of its total change. The mean velocity of the Kuroshio extension is high in summer and low in winter, and its seasonal variability accounts for 25% of its total change. The interannual variabilities of the mean velocity of the Kuroshio source and Kuroshio extension are significant. The mean velocity of the Kuroshio source and ENSO index are inversely correlated. However, the relationship between the mean velocity of the Kuroshio extension and the ENSO index is not clear. Overall, the velocity of the Kuroshio increases when La Nina occurs and decreases when E1 Nino occurs.

Air breakdown induced by the microwave with two mutually orthogonal and heterophase electric field components

The air breakdown is easily caused by the high-power microwave, which can have two mutually orthogonal and heterophase electric field components. For this case, the electron momentum conservation equation is employed to deduce the electric field power and effective electric field for heating electrons. Then the formula of the electric field power is introduced into the global model to simulate the air breakdown. The breakdown prediction from the global model agrees well with the experimental data. Simulation results show that the electron temperature is sensitive to the phase difference between the two electron field components, while the latter can affect obviously the growth of the electron density at low electron temperature amplitudes. The ionization of nitrogen and oxygen induces the growth of electron density, and the density loss due to the dissociative attachment and dissociative recombination is obvious only at low electron temperatures.

GLOBAL BIFURCATIONS IN A DISTURBED HAMILTONIAN VECTOR FIELD APPROACHING A 3:1 RESONANT POINCAR MAP (Ⅰ)

In this paper, we use a qualitative method to study global and local bifurcations in a disturbedHamiltonian vector field approaching a Poincare map in the 3:1 resonant case. We give explicitcalculation formulas to determine bifurcation parameters and draw various bifurcations and phaseportraits in the phase plane.

DTCC:Multi-level dilated convolution with transformer for weakly-supervised crowd counting

Crowd counting provides an important foundation for public security and urban management.Due to the existence of small targets and large density variations in crowd images,crowd counting is a challenging task.Mainstream methods usually apply convolution neural networks(CNNs)to regress a density map,which requires annotations of individual persons and counts.Weakly-supervised methods can avoid detailed labeling and only require counts as annotations of images,but existing methods fail to achieve satisfactory performance because a global perspective field and multi-level information are usually ignored.We propose a weakly-supervised method,DTCC,which effectively combines multi-level dilated convolution and transformer methods to realize end-to-end crowd counting.Its main components include a recursive swin transformer and a multi-level dilated convolution regression head.The recursive swin transformer combines a pyramid visual transformer with a fine-tuned recursive pyramid structure to capture deep multi-level crowd features,including global features.The multi-level dilated convolution regression head includes multi-level dilated convolution and a linear regression head for the feature extraction module.This module can capture both low-and high-level features simultaneously to enhance the receptive field.In addition,two regression head fusion mechanisms realize dynamic and mean fusion counting.Experiments on four well-known benchmark crowd counting datasets(UCF_CC_50,ShanghaiTech,UCF_QNRF,and JHU-Crowd++)show that DTCC achieves results superior to other weakly-supervised methods and comparable to fully-supervised methods.