Entity

Time filter

Source Type


Gao Y.,Nanjing University of Information Science and Technology | Chen Y.,Nanjing University of Information Science and Technology | Jiang Y.,Jiangsu Meteorological Observatory | Peng T.,Institute of Heavy Rain
Shuikexue Jinzhan/Advances in Water Science | Year: 2015

Hydrological simulations are affected by the parameters derived from DEM, which describes the water-shed features. Xitiaoxi River basin was selected to simulate two runoff processes in Jun and Aug to Sep 2011 using the HEC-HMS model with ASTER 30 m DEM, SRTM 90 m DEM and DEM resample data as input for HEC-geoHMS to derive the basin characteristics. The results showed that, the simulated and observed flood were fitting well and the efficiency coefficients of the model were all larger than 0.82, Uni-modal flood showed a better performance in runoff simulation than multi-modal flood. The efficiency coefficients of model based on SRTM 90 m was larger than based on ASTER 30 m DEM and resampled 90 m DEM. The efficiency coefficients of model based on resampled DEM had nonlinear relationship with DEM resolution. The relative error of HEC-HMS simulations based on ASTER 30 m DEM and SRTM 90 m DEM had a difference of 3%-5%. The relative error of simulations based on the SRTM 90 m DEM and the resampled 90 m DEM had a difference of 2%-4%. The maximum difference between the relative error of HEC-HMS simulations based on the resampled 90 m DEM was 11%. ©, 2015, Science Press. All right reserved. Source


Wei J.,Nanjing University of Information Science and Technology | Zhu W.,Nanjing University of Information Science and Technology | Liu D.,Jiangsu Meteorological Observatory | Han X.,Suzhou Meteorological Observatory of Jiangsu Province
Advances in Meteorology | Year: 2016

Based on the surface meteorological data of Jiangsu Province during 1980-2012, the climatic characteristics and the trends of haze were analyzed. The results indicated that during 1980-2012 haze days increased; in particular, severe and moderate haze days significantly increased. In the northern and coastal cities of Jiangsu Province China, haze days showed a significant increase. Haze often appeared in fall and winter and rarely in summer in the study area. It also occurred more often inland, and less along the coast. Haze occurred more often in June due to straw burning in the harvest time. The haze day increased during the 1990s over southern and southwestern Jiangsu Province; in central and northern Jiangsu, haze day increased after 2000. The continuous, regional, and regional continuous haze days all showed increasing trends. As the urban area expanded each year, industrial emissions, coal consumption, and car ownership increased accordingly, resulting in regional temperature increase and relative humidity decrease, which formed the urban heat island and dry island effects. Hence, haze formation and maintenance conditions became more favorable for more haze days, which led to the increase of haze days, and the significant increases of continuous, regional, and regional continuous haze days. © 2016 Jiansu Wei et al. Source


Lu Z.,Nanjing University of Information Science and Technology | Li K.,Nanjing University of Information Science and Technology | Yang T.,Jiangsu Meteorological Observatory | Guo W.,Nanjing University of Information Science and Technology | Wang J.,Nanjing University of Information Science and Technology
International Journal of Control and Automation | Year: 2015

Predictive functional control and multivariate PI predictive functional control is presented based on state space equation for non-linear, fast time-varying, multivariable coupling near-space vehicle attitude control system. Transforming nonlinear optimal problems into online optimization in the linear time-invariant systems and solve the control law in a rolling way. Lyapunov's second stability theorem proved that the solved control law can ensure a certain degree of robustness of the closed-loop system. Tuning parameters of multivariable PI predictive functional controller based on particle swarm optimization algorithm. Designed near-space vehicle attitude controller and simulate it. Results show that both of the two control strategy can get good control performance, comparatively, multivariable PI predictive functional control has a better control effect. It has the advantages of non-overshoots, faster response, and smaller steady state error etc. © 2015 SERSC. Source


Yang T.,Jiangsu Meteorological Observatory | Lu Z.,Nanjing University of Information Science and Technology | Hu J.,South-Central University for Nationalities
Mathematical Problems in Engineering | Year: 2013

In recent years, air pollution control has caused great concern. This paper focuses on the primary pollutant SO2 in the atmosphere for analysis and control. Two indicators are introduced, which are the concentration of SO2 in the emissions (PSO2) and the concentration of SO2 in the atmosphere (ASO2). If the ASO2 is higher than the certain threshold, then this shows that the air is polluted. According to the uncertainty of the air pollution control systems model, H ∞ control theory for the air pollution control systems is used in this paper, which can change the PSO2 with the method of improving the level of pollution processing or decreasing the emissions, so that air pollution system can maintain robust stability and the indicators ASO2 are always operated within the desired target. © 2013 Tingya Yang et al. Source


Su T.,CAS Institute of Atmospheric Physics | Xue F.,CAS Institute of Atmospheric Physics | Sun H.,Jiangsu Meteorological Observatory | Zhou G.,CAS Institute of Atmospheric Physics
Acta Oceanologica Sinica | Year: 2015

On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences (CAS-ESM-C) in simulating the El Niño-Southern Oscillation (ENSO) cycle is evaluated, including the onset, development and decay of the ENSO. It is shown that, the model can reasonably simulate the annual cycle and interannual variability of sea surface temperature (SST) in the tropical Pacific, as well as the seasonal phase-locking of the ENSO. The model also captures two prerequisites for the El Niño onset, i.e., a westerly anomaly and a warm SST anomaly in the equatorial western Pacific. Owing to too strong forcing from an extratropical meridional wind, however, the westerly anomaly in this region is largely overestimated. Moreover, the simulated thermocline is much shallower with a weaker slope. As a result, the warm SST anomaly from the western Pacific propagates eastward more quickly, leading to a faster development of an El Niño. During the decay stage, owing to a stronger El Niño in the model, the secondary Gill-type response of the tropical atmosphere to the eastern Pacific warming is much stronger, thereby resulting in a persistent easterly anomaly in the western Pacific. Meanwhile, a cold anomaly in the warm pool appears as a result of a lifted thermocline via Ekman pumping. Finally, an El Niño decays into a La Niña through their interactions. In addition, the shorter period and larger amplitude of the ENSO in the model can be attributed to a shallower thermocline in the equatorial Pacific, which speeds up the zonal redistribution of a heat content in the upper ocean. © 2015, The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg. Source

Discover hidden collaborations