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Clouds are significant in the global radiation budget, atmospheric circulation, and hydrological cycle. However, knowledge regarding the observed climatology of the cloud vertical structure (CVS) over Beijing is still poor. Based on high-resolution radiosonde observations at Beijing Nanjiao Weather Observatory (BNWO) during the period 2010–2017, the method for identifying CVS depending on height-resolved relative humidity thresholds is improved, and CVS estimation by radiosonde is compared with observations by millimeter-wave cloud radar and ceilometer at the same site. Good consistency is shown between the three instruments. Then, the CVS climatology, including the frequency distribution and seasonal variation, is investigated. Overall, the occurrence frequency (OF) of cloudy cases in Beijing is slightly higher than that of clear-sky cases, and the cloud OF is highest in summer and lowest in winter. Single-layer clouds and middle-level clouds are dominant in Beijing. In addition, the average cloud top height (CTH), cloud base height (CBH), and cloud thickness in Beijing are 6.2 km, 4.0 km, and 2.2 km, respectively, and show the trend of reaching peaks in spring and minimums in winter. In terms of frequency distribution, the CTH basically resides below an altitude of 16 km, and approximately 43% of the CBHs are located at altitudes of 0.5–1.5 km. The cloud OF has only one peak located at altitudes of 4–8 km in spring, whereas it shows a trimodal distribution in other seasons. The height at which the cloud OF reaches its peak is highest in summer and lowest in winter. To the best of our knowledge, the cloud properties analyzed here are the first to elucidate the distribution and temporal variation of the CVS in Beijing from a long-term sounding perspective, and these results will provide a scientific observation basis for improving the atmospheric circulation model, as well as comparisons and verifications for measurements by ground-based remote sensing equipment.

At present, satellite anomaly is mostly solved after the event, and rarely predicted in advance in satellite health management. Thus, satellite trend prediction is quietly important for avoiding the fault which perhaps affects data accuracy and service quality of satellite, and even impacts greatly on satellite safety. However, it is difficult to predict satellite operation through a simple model because satellite system is complex, and telemetry data is numerous, coupled and spatiotemporal. Therefore, this paper proposes a model combing attention mechanism and Bidirectional Long Short-term Memory (Attention-BiLSTM) with correlation telemetry to predict the situation of satellite operation. Firstly, high-dimensional K-NearestNeighbor Mutual Information (HKNN-MI) method is performed to select the related telemetry variables from multiple variables of satellite telemetry data. Secondly, we put forward to a new BiLSTM model with attention mechanism for telemetry prediction. The dataset for the research is generated and transmitted from the power system of FY3E meteorological satellite. In order to verify the superiority of the proposed model, it is compared with other method based on the same dataset in the experiment. The result shows that the method outperforms other methods due to its better accuracy and prediction precision.

Abstract:Under the background of the trouble shooting requirements of FENGYUN-3 (FY-3) meteorological satellites data acquisition in domestic and oversea ground stations, a remote fault reasoning diagnosis system is developed by Java 1.6 in eclipse 3.6 platform. The general framework is analyzed, the workflow is introduced. Based on the system, it can realize the remote and centralized monitoring of equipment running status in ground stations triggering automatic fault diagnosis and rule based fault reasoning by parsing the equipment quality logs, generating trouble tickets and importing expert experience database, providing text and graphics query methods. Through the practical verification, the system can assist knowledge engineers in remote precise and rapid fault location with friendly graphical user interface, boost the fault diagnosis efficiency, enhance the remote monitoring ability of integrity operating control system. The system has a certain practical significance to improve reliability of FY-3 meteorological satellites data acquisition.