Validation of the multi-satellite merged sea surface salinity in the South China Sea

Sea surface salinity(SSS)is an essential variable of ocean dynamics and climate research.The Soil Moisture and Ocean Salinity(SMOS),Aquarius,and Soil Moisture Active Passive(SMAP)satellite missions all provide SSS measurements.The European Space Agency(ESA)Climate Change Initiative Sea Surface Salinity(CCI-SSS)project merged these three satellite SSS data to produce CCI L4SSS products.We validated the accuracy of the four satellite products(CCI,SMOS,Aquarius,and SMAP)using in-situ gridded data and Argo floats in the South China Sea(SCS).Compared with in-situ gridded data,it shows that the CCI achieved the best performance(RMSD:0.365)on monthly time scales.The RMSD of SMOS,Aquarius,and SMAP(SMOS:0.389;Aquarius:0.409;SMAP:0.391)are close,and the SMOS takes a slight advantage in contrast with Aquarius and SMAP.Large discrepancies can be found near the coastline and in the shelf seas.Meanwhile,CCI with lower RMSD(0.295)perform better than single satellite data(SMOS:0.517;SMAP:0.297)on weekly time scales compared with Argo floats.Overall,the merged CCI have the smallest RMSD among the four satellite products in the SCS on both weekly time scales and monthly time scales,which illustrates the improved accuracy of merged CCI compared with the individual satellite data.

Fault diagnosis method of link control system for gravitational wave detection

To maintain the stability of the inter-satellite link for gravitational wave detection,an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed.Different from the traditional fault diagnosis optimization algorithms,the fault intelligent learning method pro-posed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong cou-pling nonlinearity.By constructing a two-layer learning network,the method enables efficient joint diagnosis of fault areas and fault parameters.The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s,and the fault diagnosis efficiency is improved by 99.8%compared with the traditional algorithm.

Multi-Satellite and Sensor Derived Trends and Variation of Snow Water Equivalent on the High-Latitudes of the Northern Hemisphere

Utilizing more than 30 years of satellite-microwave sensor derived snow water equivalent data on the high-latitudes of the northern hemisphere we investigate regional trends and variations relative to elevation. On the low-elevation tundra regions encircling the Arctic we find high statistically significant trends of snow water equivalent. Across the high Arctic Siberia and Far East Russia through North America and northern Greenland we find increasing trends of snow water equivalent with local region variations in strength. Yet across the high Arctic of western Russia through Norway we find decreasing trends of snow water equivalent of varying strength. Power density spectra identify significant power at quasi-biennial and associated lunar nodal cycles. These cycles of the upper atmosphere circulation, ENSO and ocean circulation perturbations from tides forms the causative linkage between increasing snow water equivalent on low-elevation tundra landscapes and decreasing coastal sea ice cover as part of the Arctic system energy and mass cycles.

Simulation of Multi-satellite GNSS Reflected Signals and Design of Simulator

Using GNSS-R technology for remote sensing of surface parameters has become a new trend in the field of remote sensing.With the rapid development of GNSS-R technology,GNSS-R simulation has become one of the new hot spots.Now the researches of the GNSS-R simulation are all the simulations that consider a single star or a single frequency point,and in actual applications,the signal captured by the receiver is often the reflected signals of multiple stars.In view of this situation,from the perspective of multi-satellite simulation,this paper gives the model of GNSS-R multi-satellite ocean simulation on the basis of analyzing the remote sensing principle,reflection signal model and simulation principle of GNSS-R technology.Based on the GNSS-R multi-satellite ocean simulation model and the fast parallel computing capability of GPU,the GNSS-R multi-satellite ocean simulator was designed.Finally,the direct and reflected signals generated by the GNSS-R multi-satellite simulator were tested and verified.The results show that the positioning result of the direct signal meets the positioning accuracy requirements;The delay-related power results obtained from the simulated two-satellite reflected signals processing are in good agreement with the theoretical model,and the correlation coefficients are all above 0.99;The generated signals are used for GNSS-R height measurement technology,the height measurement error is about 1.4~1.8 m,which is in line with the accuracy of the C/A code ranging receiver;And the parallel operation of the GPU for multi-satellite simulation calculation is 800—900 times higher than the traditional CPU calculation.It proves that the proposed model and the designed simulator are feasible and accurate.

COMPUTING RESOURCE SHARING IN GROUND SYSTEM OF MULTI-SATELLITE AND MULTI-SENSOR REMOTE SENSING

A scheme is proposed to elevate the limitation of the ground application system of mono-satellite-sensor under the requirement of remote sensing satellite ground application system.In the resource-sharing, for instance caculating resource, a simple phototype of caculating-resource is proposed through analyzing resource assignment, application assignment, body structure, and so on. In order to improve the ability of assignment, realize the favorable utility, management,and maintenance, the phototype is improved by using datagrid calculation according to the requirement and character of actual application. The phototype can be taken as the foundation of calculation frame of remote sensing ground application system of multi-satellite and multi-sensor.

Evaluation of Latest TMPA and CMORPH Precipitation Products with Independent Rain Gauge Observation Networks over High-latitude and Low-latitude Basins in China

The Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） and National Oceanic and Atmospheric Administration （NOAA） Climate Prediction Center （CPC） morphing technique （CMORPH） are two important multi-satellite precipitation products in TRMM-era and perform important functions in GPM-era. Both TMPA and CMORPH systems simultaneously upgraded their retrieval algorithms and released their latest version of precipitation data in 2013. In this study, the latest TMPA and CMORPH products （i.e., Version-7 real-time TMPA （T-rt） and gauge-adjusted TMPA （T-adj）, and Version- 1.0 real-time CMORPH （C-rt） and Version-l.0 gauge-adjusted CMORPH （C-adj）） are evaluated and intercompared by using independent rain gauge observations for a 12-year （2000--2011） period over two typical basins in China with different geographical and climate conditions. Results indicate that all TMPA and CMORPH products tend to overestimate precipitation for the high-latitude semiarid Laoha River Basin and underestimate it for the low-latitude humid Mishui Basin. Overall, the satellite precipitation products exhibit superior performance over Mishui Basin than that over Laoha River Basin. The C-adj presents the best performance over the high-latitude Laoha River Basin, whereas T-adj showed the best performance over the low-latitude Mishui Basin. The two gauge-adjusted products demonstrate potential in water resource management. However, the accuracy of two real-time satellite precipitation products demonstrates large variability in the two validation basins. The C-rt reaches a similar accuracy level with the gauge-adjusted satellite precipitation products in the high-latitude Laoha River Basin, and T-rt performs well in the low-latitude Mishui Basin. The study also reveals that all satellite precipitation products obviously overestimate light rain amounts and events over Laoha River Basin, whereas they underestimate the amount and events over Mishui Basin. The findings of the precision characteristics associated with the latest TMPA and CMORPH precipitation products at different basins will offer satellite pre- cipitation users an enhanced understanding of the applicability of the latest TMPA and CMORPH for water resource management, hydrologic process simulation, and hydrometeorological disaster prediction in other similar regions in China. The findings will also be useful for IMERG algorithm development and update in GPM-era.

Feasible Multiple Satellite Mission Scenarios Flying in a Constellation for Refinement of the Gravity Field Recovery

Improving the gravity field recovery in terms of error levels and more isotropic noise distribution by adding cross-track and radial information to the satellite observables has been investigated through a number of studies by a variety of satellite constellations, i.e. satellite pairs that orbit the Earth in alternative configurations than the current GRACE (Gravity Recovery And Climate Experiment) gravity mission. This contribution gives for the first time a comparative study considering the recovery of the global gravity field from three constellations flying in satellite pairs in different directions (i.e. along-track, cross-track and radial). The three constellations include: 1) Foursatellite Bender configuration (flying in two pairs) of type along-track observations, 2) Three-satellite GRAPEN (combined GRACE with Pendulum formations) configuration of type cross-alongtrack observations, 3) Four-satellite Cartwheel configuration (flying in two pairs) of type radialalong-track observations. Additionally, a GRACE mission scenario is added as a reference “comparative” mission. The orbits of all satellites are considered to fly with drag-free system, however, realistic white noise has been added to the simulated observations to mimic the error associated with the drag-free measurement. The results are analyzed in the spectral wavelength spectrum of the gravity field up to a spherical harmonics degree of n = 100 and are plotted spatially on earth maps. The results show that the Three-satellite GRAPEN constellation provides, besides its low economically launches, an improved gravity field solution with respect to the Four-satellite Bender and the Four-satellite Cartwheel constellations.

MGCPN:An Efficient Deep Learning Model for Tibetan Plateau Precipitation Nowcasting Based on the IMERG Data

The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP) impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address such a challenge,we introduce a model called Multisource Generative Adversarial Network-Convolutional Long Short-Term Memory(GAN-ConvLSTM) for Precipitation Nowcasting(MGCPN),which utilizes data products from the Integrated Multi-satellite Retrievals for global precipitation measurement(IMERG) data,offering high spatiotemporal resolution precipitation forecasts for upcoming periods ranging from 30 to 300 min.The results of our study confirm that the implementation of the MGCPN model successfully addresses the problem of underestimating and blurring precipitation results that often arise with increasing forecast time.This issue is a common challenge in precipitation forecasting models.Furthermore,we have used multisource spatiotemporal datasets with integrated geographic elements for training and prediction to improve model accuracy.The model demonstrates its competence in generating precise precipitation nowcasting with IMERG data,offering valuable support for precipitation research and forecasting in the TP region.The metrics results obtained from our study further emphasize the notable advantages of the MGCPN model;it outperforms the other considered models in the probability of detection(POD),critical success index,Heidke Skill Score,and mean absolute error,especially showing improvements in POD by approximately 33%,19%,and 8% compared to Convolutional Gated Recurrent Unit(ConvGRU),ConvLSTM,and small Attention-UNet(SmaAt-UNet) models.

Refined Spatialization of 10-Day Precipitation in China Based on GPM IMERG Data and Terrain Decomposition Using the BEMD Algorithm

Continuous high spatial-resolution 10-day precipitation data are essential for crop growth services and phenological research.In this study,we first use the bidimensional empirical mode decomposition(BEMD)algorithm to decompose the digital elevation model(DEM)data and obtain high-frequency(OR3),intermediate-frequency(OR5),and low-frequency(OR8)margin terrains.Then,we propose a refined precipitation spatialization model,which uses ground-based meteorological observation data,integrated multi-satellite retrievals for global precipitation measurement(GPM IMERG)satellite precipitation products,DEM data,terrain decomposition data,prevailing precipitation direction(PPD)data,and other multisource data,to construct China's high-resolution 10-day precipitation data from2001 to 2018.The decomposition results show mountainous terrain from fine to coarse scales;and the influences of altitude,slope,and aspect on precipitation are better represented in the model after topography is decomposed.Moreover,terrain decomposition data can be added to the model simulation to improve the quality of the simulation product;the simulation quality of the model in summer is better than that in spring and autumn,and is relatively poor in winter;and OR5 and OR8 can be improved in the simulation,with better OR5 and OR8 dynamically selected.In addition,preprocessing the data before precipitation spatialization is particularly important.For example,adding 0.01to the 0 value of precipitation,multiplying the small value of precipitation less than 1 by 10,and performing the normal distributions transform(e.g.,Yeo–Johnson)on the data can improve the simulation quality.

Approach for earth observation satellite real-time and playback data transmission scheduling

The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.

Satellite group autonomous operation mechanism and planning algorithm for marine target surveillance

In terms of fast response problem of unanticipated marine target, it is necessary to design the satellite-ground-combined operation mechanism and planning algorithm for autonomous task planning. Firstly, based on the autonomous operation and task planning of remote sensing satellite group, it is divided into two parts: ground planning and satellite autonomous planning. Secondly,the satellite-ground-combined operation mechanism and operation flow for task planning are proposed after fully considering the resource characteristics and task demand characteristics of the ground and satellite. The satellite autonomous task planning algorithm based on extended contract net is designed. Through the simulation operation of the self-developed distributed simulation demonstration software, it shows that the operation mechanism can coordinate and cooperate effectively between the satellite autonomous task planning and ground planning. It can give full play to the advantages of the ground computing resources, reflect the control intention, make full use of the real-time feature and flexibility of the satellite calculation, and respond fast to the unanticipated task. Besides, it has solved problems of the untimely response of ground control on unanticipated observation task, the limitation of satellite computing resources and satellite-ground planning and coordination, which can effectively improve the responsiveness of remote sensing satellite to the observation task of maritime unanticipated target.

Columnar optical,microphysical and radiative properties of the 2022 Hunga Tonga volcanic ash plumes

The Hunga Tonga-Hunga Ha’apai eruption on January 15,2022 was one of the most explosive volcanic eruptions of the 21st century and has attracted global attention.Here we show that large numbers of the volcanic aerosols from the eruption broke through the tropopause into the lower stratosphere,forming an ash plume with an overshooting top at 25-30 km altitude.In the four days following the eruption,the ash plume moved rapidly westward for nearly 10,000 km under stable stratospheric conditions characterized by strong tropical easterlies,weak meridional winds and weak vertical motion.The intrusion of the ash plume into the stratosphere resulted in a marked increase in atmospheric aerosol loading across northern Australia,with the aerosol optical depth(AOD)observed by satellites and sun-photometers peaking at 1.5 off the coast of northeastern Australia;these effects lasted for nearly three days.The ash plume was characterized by fine-mode particles clustered at a radius of about 0.26μm,with an observed peak volume of 0.25μm^(3)μm^(-2).The impact of the ash plume associated with the Hunga Tonga eruption on the stratospheric AOD and radiative balance in the tropical southern hemisphere is remarkable,with an observed volcanic-induced perturbation of the regional stratospheric AOD of up to 0.6.This perturbation largely explains an instantaneous bottom(top)of the atmosphere radiative forcing of-105.0(-65.0)W m^(-2)on a regional scale.