多机并联火箭羽流流场及其底部热环境分析

For the problem that the plume flow field structure of a multi engine parallel rocket is complicated and the bottom thermal environment is extremely harsh, which may cause the failure of the engine structural components, the plume flow field and thermal environment at different altitudes are studied through numerical simulation. The result is compared with the measured results in flight which shows that when the rocket is flying at a low altitude, the plume of the engines do not interfere with each other. As the flight altitude increases, the plumes gradually expand and begin to interfere with each other, and finally there is an obvious backflow at the bottom of the rocket. The maximum heat flux at the moment of take off is basically the same as the measured value in flight. Before the backflow occurs, the heat flux mainly consists of radiant heat, the convective heat flow increases as the flight altitude grows, but it is also much smaller than the peak heat flow at takeoff. The result has certain guiding significance for the optimal design of engine structure thermal protection.     

Low-latitude storm time ionospheric predictions using support vector machines

The electromagnetic drift plays an important role in low-latitude storm time ionospheric dynamics. In this study we attempt to utilize the electric field data into ionospheric predictions by using support vector machine (SVM), a promising algorithm for small-sample nonlinear regressions. Taking the disturbance electric field data as input, different SVMs have been trained for three seasonal bins at two stations near the north crest of the Equatorial Ionization Anomaly (EIA). Eighteen storm events are used to check out their predicting abilities. The results show fairly good agreement between the predictions and observations. Compared with STORM, a widely used empirical correlation model, the SVM method brings a relative improvement of 23% for these testing events. Based on this study we argue that the SVM method can improve the storm time ionospheric predictions.     

Evaluation and improvement of coastal GNSS reflectometry sea level variations from existing GNSS stations in Taiwan

Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1?m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10?cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7?cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used.     

中国对外贸易与航空运输的关系测度研究

中国对外贸易长期快速持续增长,在国际市场上的比重逐年增加,恰值中国民航业的发展正处于迅猛成长期。对外贸易的发展对航空运输有直接或间接的重要影响,货物贸易的增长对航空货运需求增加,国际交流频繁也促进了航空客运的发展。基于国际贸易的动态效应理论,通过选取1982—2011年的时间序列数据,对进出口贸易总额与航空运输总周转量间的关系进行格兰杰因果检验,并构建了对外贸易与航空运输增长之间的有限分布滞后模型。分析结果表明:对外贸易与航空运输增长之间存在因果关系,其中对外贸易对航空运输增长的贡献度为0.28。     

Global ionospheric scintillations revealed by GPS radio occultation data with FY3C satellite before midnight during the March 2015 storm

Global observations of S4 amplitude scintillation index by the GPS Occultation Sounder (GNOS) on FengYun-3 C (FY3C) satellite reveal global dynamic patterns of a strong pre-midnight scintillations in F-region of the ionosphere during the St. Patrick’s Day geomagnetic super storm of 17–19 March 2015. The observed strong scintillations mainly occurred in the low latitudes, caused by equatorial plasma bubbles. During the main storm phase (March 17), the scintillations were first triggered in the New Zealand sector near 160°E longitudes, extending beyond 40°S dip latitude. They were also enhanced in the Indian sector, but significantly suppressed in East Asia near 120°E longitude and in Africa around 30°E longitude. During the initial recovery phase (March 18–19), the global scintillations were seldom observed in GNOS data. During the later recovery phase (after March 19), the scintillations recovered to the pre-storm level in Indian, African, and American sectors, but not in East Asian and any of Pacific sectors. These results closely correlate with observations of the density depletion structures by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite, and ground-based instruments. Such consistency indicates reliability of our scintillation sensing approach even in a case-by-case comparison study. The prompt penetration electric field and disturbance dynamo electric field are suggested as the main factors that control the enhancement and inhibition of the scintillations during the storm, respectively.     

High temporal resolution global PWV dataset of 2005–2016 by using a neural network approach to determine the mean temperature of the atmosphere

Atmospheric water vapour plays an important role in phenomena related to the global hydrologic cycle and climate change. However, the rapid temporal–spatial variation in global tropospheric water vapour has not been well investigated due to a lack of long-term, high-temporal-resolution precipitable water vapour (PWV). Accordingly, this study generates an hourly PWV dataset for 272 ground-based International Global Navigation Satellite System (GNSS) Service (IGS) stations over the period of 2005–2016 using the zenith troposphere delay (ZTD) derived from global-scale GNSS observation. The root mean square (RMS) of the hourly ZTD obtained from the IGS tropospheric product is approximately 4 mm. A fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting (ECMWF ERA5) is used to obtain hourly surface temperature (T) and pressure (P), which are first validated with GNSS synoptic station data and radiosonde data, respectively. Then, T and P are used to calculate the water vapour-weighted atmospheric mean temperature (Tm) and zenith hydrostatic delay (ZHD), respectively. T and P at the GNSS stations are obtained via an interpolation in the horizontal and vertical directions using the grid-based ERA5 reanalysis dataset. Here, Tm is calculated using a neural network model, whereas ZHD is obtained using an empirical Saastamoinen model. The RMS values of T and P at the collocated 693 radiosonde stations are 1.6 K and 3.1 hPa, respectively. Therefore, the theoretical error of PWV caused by the errors in ZTD, T and P is on the order of approximately 2.1 mm. A practical comparison experiment is performed using 97 collocated radiosonde stations and 23 GNSS stations equipped with meteorological sensors. The RMS and bias of the hourly PWV dataset are 2.87/?0.16 and 2.45/0.55 mm, respectively, when compared with radiosonde and GNSS stations equipped with meteorological sensors. Additionally, preliminary analysis of the hourly PWV dataset during the EI Niño event of 2014–2016 further indicates the capability of monitoring the daily changes in atmospheric water vapour. This finding is interesting and significant for further climate research.     

Ionospheric F2-Layer critical frequency retrieved from COSMIC radio occultation: A statistical comparison with measurements from a meridional ionosonde chain over Southeast Asia

In this paper, we compared the F2-Layer critical frequency (foF2) derived from FORMOSAT-3/COSMIC radio occultation (RO) and ionosondes at Chiang Mai, Chumphon and Kototabang during the years 2008–2015 to evaluate the performance of COSMIC RO over Southeast Asia region. The results show that the time development of foF2 values derived from COSMIC RO generally agrees well with those from ionosonde measurements. However, the differences between the foF2 derived from COSMIC RO and that derived from ionosonde observations display latitudinal dependence. COSMIC RO tends to underestimate foF2 at Chiang Mai and Kototabang, which is near to the north EIA crest and the south one, respectively, while a little overestimate foF2 at Chumphon, which is close to the geomagnetic equator. COSMIC RO agrees best with ionosonde at Chumphon and worst at Chiang Mai. At each ionosonde station, the quality of COSMIC RO data degrades with the increase of solar activity. In addition, at the station Chiang Mai and Kototabang, COSMIC RO performs better in summer than in equinox and winter. Furthermore, the differences in foF2 derived from COSMIC RO and that from ionosonde measurements vary with local time, i.e., the differences in foF2 are generally smaller at night and larger in noontime when equatorial ionization anomaly (EIA) is well developed.     

Effects on winter circulation of short and long term solar wind changes

Indices of the North Atlantic Oscillation and the Arctic Oscillation show correlations on the day-to-day timescale with the solar wind speed (SWS). Minima in the indices were found on days of SWS minima during years of high stratospheric aerosol loading. The spatial distribution of surface pressure changes during 1963–2011 with day-to-day changes in SWS shows a pattern resembling the NAO. Such a pattern was noted for year-to-year variations by Boberg and Lundstedt (2002), who compared NAO variations with the geo-effective solar wind electric field (the monthly average SWS multiplied by the average southward component, i.e., negative Bz component, of the interplanetary magnetic field). The spatial distribution of the correlations of geopotential height changes in the troposphere and stratosphere with the SWS; the geo-effective electric field (SWS∗Bz); and the solar 10.7 cm flux suggests that solar wind inputs connected to the troposphere via the global electric circuit, together with solar ultraviolet irradiance acting on the stratosphere, affect regional atmospheric dynamics.     

Particle swarm optimization applied to hypersonic reentry trajectories

This paper presents the novel use of the particle swarm optimization(PSO)to generate the end-to-end trajectory for hypersonic reentry vehicles in a quite simple formulation.The velocitydependent bank angle profile is developed to reduce the search space of unknown parameters based on the constrained PSO algorithm.The path constraints are enforced by setting the fitness function to be infinite on condition that the particles violate the maximum allowable values.The PSO algorithm also provides a much easier means to satisfy the terminal conditions by adding penalty terms to the fitness function.Furthermore,the approximate reentry landing footprint is fast constructed by incorporating an interpolation model into the standardized bank angle profiles.Numerical simulations demonstrate that the PSO method is a feasible and flexible tool to generate the end-to-end trajectory and landing footprint for hypersonic reentry vehicles.