FY-3E:The First Operational Meteorological Satellite Mission in an Early Morning Orbit

Fengyun-3 E(FY-3E),the world’s first early-morning-orbit meteorological satellite for civil use,was launched successfully at the Jiuquan Satellite Launch Center on 5 July 2021.The FY-3E satellite will fill the vacancy of the global early-morning-orbit satellite observation,working together with the FY-3C and FY-3D satellites to achieve the data coverage of early morning,morning,and afternoon orbits.The combination of these three satellites will provide global data coverage for numerical weather prediction(NWP)at 6-hour intervals,effectively improving the accuracy and time efficiency of global NWP,which is of great significance to perfect the global earth observing system.In this article,the background and meteorological requirements for the early-morning-orbit satellite are reviewed,and the specifications of the FY-3E satellite,as well as the characteristics of the onboard instrumentation for earth observations,are also introduced.In addition,the ground segment and the retrieved geophysical products are also presented.It is believed that the NWP communities will significantly benefit from an optimal temporal distribution of observations provided by the early morning,mid-morning,and afternoon satellite missions.Further benefits are expected in numerous applications such as the monitoring of severe weather/climate events,the development of improved sampling designs of the diurnal cycle for accurate climate data records,more efficient monitoring of air quality by thermal infrared remote sensing,and the quasicontinuous monitoring of the sun for space weather and climate.

Polarimetric Meteorological Satellite Data Processing Software Classification Based on Principal Component Analysis and Improved K-Means Algorithm

With the increasing variety of application software of meteorological satellite ground system, how to provide reasonable hardware resources and improve the efficiency of software is paid more and more attention. In this paper, a set of software classification method based on software operating characteristics is proposed. The method uses software run-time resource consumption to describe the software running characteristics. Firstly, principal component analysis (PCA) is used to reduce the dimension of software running feature data and to interpret software characteristic information. Then the modified K-means algorithm was used to classify the meteorological data processing software. Finally, it combined with the results of principal component analysis to explain the significance of various types of integrated software operating characteristics. And it is used as the basis for optimizing the allocation of software hardware resources and improving the efficiency of software operation.

Study on Massive Vegetation Data Processing of FY-3 Based on RAM (h)

The vegetation data of the Fengyun meteorological satellite are segmented according to the latitude and longitude, and can be written into 648 blocks. However, the vegetation data processing efficiency is low because the data belongs to massive data. This paper presents a data processing method based on RAM (h) for Fengyun-3 vegetation data. First of all, we introduce the Locality-Aware model to segment the input data, then locate the data based on geographic location, and finally fuse the independent data based on geographical location. Experimental results show that the proposed method can effectively improve the data processing efficiency.

Precise Forecast and Application of Time Delay Receiving Schedule for a New Generation of Polar Orbit Meteorological Satellite

In order to finely predict the receiving schedule of the new generation of polar orbit meteorological satellite time-delay data and solve the problem of rapid positioning of lost data, this paper studies and proposes the satellite data recording and satellite program-controlled program, and designs the delay data receiving timeline precision forecasting method. It is concluded that the detection load of polar orbit meteorological satellite in our country has developed from single load to multiple loads, and the detection data need to be downloaded to the ground for processing and application. And as the satellite load increases and the accuracy of each payload detection and channel increases, the amount of probing data will further increase, which in turn will require further increase of the speed of data transmission in the earth. Due to the limitation of the space data transmission frequency band, under the prior art system, the increase of the satellite data transmission rate is limited. On the basis of understanding the working principle of Fengyun-3, the new transmission system will be implemented in terms of data source compression, channel coding, modulation and polarization multiplexing by exploring new weather transmission systems for meteorological satellites in the future upgrade and at the same time analyze ways to avoid inter-satellite interference in order to solve the contradiction between the increase of data volume and the resource of terrestrial data transmission in the existing system.

Classification of Meteorological Satellite Ground System Applications

Meteorological satellite ground application system carries a large number of applications. These applications deal with a variety of tasks. In order to classify these applications according to the resource consumption and improve the rational allocation of system resources, this paper introduces several application analysis algorithms. Firstly, the requirements are abstractly described, and then analyzed by hierarchical clustering algorithm. Finally, the benchmark analysis of resource consumption is given. Through the benchmark analysis of resource consumption, we will give a more accurate meteorological satellite ground application system.

Research on Exception of Meteorological Satellite Ground System Application Based on Resource Bottleneck

Meteorological satellite ground application system resources are limited. Abnormal satellite missions often lead to hopple of system resources. In order to analyze the problem, this paper presents an anomaly analysis method for meteorological satellite ground system based on resource bottleneck. Through the CPU, memory and I/O, several types of resources in-depth were analyzed to find the bottleneck caused by the problem, thus providing recommendations for application optimization. Experimental analysis shows that the proposed method can reasonably analyze the resource bottleneck of CPU, memory and I/O, and draw a good conclusion. To solve the meteorological satellite application system application anomaly caused by the bottleneck of the problem, the application of optimization to a certain extent plays a positive role.

A Parallelization Research for FY Satellite Rainfall Estimate Day Knock off Product Algorithm

With the development of satellite remote sensing technology, more and more requirements are put forward on the timeliness and stability of the satellite weather service system. The FY satellite rainfall estimate day knock off product algorithm runs longer, about 20 minutes, which affects the estimated rainfall product generated timeliness. Research and development of parallel optimization algorithms based on the needs of satellite meteorological services and their effectiveness in practical applications are necessary ways to enhance the high-performance and high-availability capabilities of satellite meteorological services. So aiming at this problem, we started the parallel algorithm research based on the analysis of precipitation estimation algorithm. Firstly, we explained the steps of precipitation estimated date knock off product algorithm;secondly, we analyzed the four main calculation module calculating the amount of algorithms;thirdly, multithreaded parallel algorithm and MPI parallelization was designed. Finally, the multithreaded parallel and MPI parallelization were realized. Experimental results show that the multithreaded parallel and MPI parallelization algorithm could greatly improve the overall degree of computational efficiency. And, MPI parallelization mode has a higher operating efficiency. The performance of parallel processing is closely related to the architecture of the computer. From the perspective of service scheduling and product algorithms, the MPI parallelization approach is adopted to achieve the purpose of improving service quality.

FY-3G Satellite Instruments and Precipitation Products:First Report of China’s Fengyun Rainfall Mission In-Orbit

Precipitation is one of the most important parameters in Earth system but is hard to measure.China began to develop satellites dedicated to precipitation measurements in the second generation of the FengYun polarorbiting meteorological satellite program(FY-3).The first of total 2 rainfall missions scheduled,FY-3G,was successfully launched on 16 April 2023 and became the world’s third satellite to measure precipitation with space-borne radar after the tropical rainfall measuring mission in 1997 and global precipitation measurement core observatory in 2014.In this manuscript,we illustrate the platform of FY-3G and instruments mounted in great detail,with additional information about ground segments,designed sensor-based products,and retrieval of geophysical parameters.During the 4 months after launch,the specifications of the platform and instruments are under inspection as calibration and validation are carefully conducted.The first images captured by FY-3G are encouraging,and initial results show a strong capability for providing insights into all kinds of precipitation phenomena.The important work of data processing,such as data assimilation,data fusion between space-based and ground-based radar,and that between polar and geostationary satellites,as well as future applications in weather modification,has been prepared in advance.As a pioneer of China’s rainfall missions,FY-3G greatly improves our ability to provide global precipitation measurements,understand Earth’s water and energy cycle,and forecast extreme events for the benefit of society.