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Under the influence of space weather, abnormal disturbances in the ionosphere will distort the ionosphere model seriously and affect the global navigation satellite system negatively. This study analyzes the ionospheric activity characteristics and the ionospheric model performance in low latitude during a strong geomagnetic storm from 7 to 9 September 2017. The research goals are to determine the abnormal behavior of the ionosphere during the geomagnetic storm and to refine the ionosphere model in the low latitude. In the experiment, the vertical total electron content (VTEC) peak value at low latitudes caused by this geomagnetic storm was significantly higher than that on the geomagnetic quiet day, and the VTEC peak value increased by approximately 75%. In the main phase of the geomagnetic storm, the degree of VTEC variation with longitude is significantly higher than that of the geomagnetic quiet day. The VTEC variation trend in the northern hemisphere is more severe than that in the southern hemisphere. In the region where VTEC decreases with longitude, the VTEC in the northern hemisphere is higher than that in the southern hemisphere on the same longitude at low latitudes, and this phenomenon is not significantly affected by the geomagnetic disturbance of the recovery phase. During the geomagnetic storm, the daily minimum value of VTEC at different latitudes was basically the same, approximately 5 TECU, indicating that the nighttime VTEC of the ionosphere in low latitudes was weakly affected by latitude and geomagnetic storms. Geomagnetic disturbances during geomagnetic storms will lead to anomalous features of the "Fountain effect" in the ionosphere at low latitudes. In addition, this geomagnetic storm event caused the accuracy of spherical harmonics (SH), polynomial, and ICE models to decrease by 7.12%, 27.87%, and 48.56%, respectively, and caused serious distortion, which is negative VTEC values fitted by the polynomial model. [ABSTRACT FROM AUTHOR]

Precipitation is a key aspect of the climate system. In this paper, the dependability of five satellite precipitation products (TRMM [Tropical Rainfall Measuring Mission] 3BV42, PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks] CDR, GSMaP [Global Satellite Mapping of Precipitation] RENALYSIS, CMORPH [Climate Prediction Center's morphing technique] BLD and CMORPH_RAW) were compared with in situ measurements over China for the period of 2005 to 2013. To completely evaluate these precipitation products, the annual, seasonal and monthly precipitation averages were calculated. Overall, the Huaihe River and Qinlin mountains are shown to have heavy precipitation to the southeast and lighter precipitation to the northwest. The comparison results indicate that Gauge correction (CMORPH_BLD) improves the quality of the original satellite products (CMORPH_RAW), resulting in the higher correlation coefficient (CC), the low relative bias (BIAS) and root mean square error (RMSE). Over China, the GSMaP_RENALYSIS outperforms other products and shows the highest CC (0.91) and lowest RMSE (0.85 mm/day) and all products except for PERSIANN_CDR exhibit underestimation. GSMaP_RENALYSIS gives the highest of probability of detection (81%), critical success index (63%) and lowest false alarm ratio (36%) while TRMM3BV42 gives the highest of frequency bias index (1.00). Over Tibetan Plateau, CMORPH_RAW demonstrates the poorest performance with the biggest BIAS (4.2 mm/month) and lowest CC (0.22) in December 2013. GSMaP_RENALYSIS displays quite consistent with in situ measurements in summer. However, GSMaP_RENALYSIS and CMORPH_RAWunderestimate precipitation over South China. CMORPH_BLD and TRMM3BV42 show consistent with high CC (>0.8) but relatively large RMSE in summer. [ABSTRACT FROM AUTHOR]

Sinking and horizontal movements are necessary parameters for assessing the potential impacts of surface subsidence in mining activities. Based on similarity criteria, the surface subsidence mechanism was studied using a physical model composed of similar materials such as sand, cement, and gypsum. With constant field geological parameters maintained in two angles of a coal seam, models of roof subsidence of composite rock were compared for different mining configurations. In accordance with observations from the physical model, it was concluded that subsidence and horizontal movement of strata near to and far from the coal seams were different and divided into five zones. The zone above a mined-out area underwent greater total subsidence compared to unexploited regions on both sides. Correlations between a subsidence curve and the height of a caving zone and the mining dip angle were obtained and verified from numerical model results. According to the roof's position relative to the goaf, the area above the goaf of the composite rock layer was divided into three regions: a curving zone, a water-conducting fracture zone, and a falling zone, to which the subsidence and movement characteristics of each area could be proposed. Compared with the subsidence and movement characteristics observed from the physical and numerical model, the acquisition of subsidence characteristics and parameters in different areas can provide an idea for improvement, innovation or proposal of a theoretical formula for subsidence prediction of composite rock formations. [ABSTRACT FROM AUTHOR]

Many physiology and bioinformatics research institutions and websites have opened their own data analysis services and other related Web services. It is therefore very important to be able to quickly and effectively select and extract features from the Web service pages to learn about and use these services. This facilitates the automatic discovery and recognition of Representational State Transfer or RESTful services. However, this task is still challenging. Following the description feature pattern of a RESTful service, the authors proposed a Feature Pattern Search and Replace (FPSR) method. First, they applied a regular expression to perform a matching lookup. Then, a custom string was used to substitute the relevant feature pattern to avoid the segmentation of its feature pattern and the loss of its feature information during the segmentation process. Experimental results showed in the visualization that FPSR obtained a clearer and more obvious boundary with fewer overlaps than the test without using FPSR, thereby enabling a higher accuracy rate. Therefore, FPSR allowed the authors to extract RESTful service page feature information and achieve better classification results. [ABSTRACT FROM AUTHOR]

Air pollution is becoming increasingly serious with rapid economic development in China, and the primary pollutant has converted from PM10 to PM2.5, which is associated with more adverse impacts on human health. Satellite remote sensing, with help of its quantitative observations over large spatial and temporal extent, has become a significant supplement to the in situ measurements. This study exploits the aerosol optical depth (AOD) product retrieved from the Medium Resolution Spectrum Imager (MERSI) onboard Fengyun-3C satellite to estimate PM2.5 estimation over the major urban areas of Chongqing, a metropolitan city in the Southwestern China. A semi-empirical model and the linear mixed effect (LME) model are combined based on in situ observations from local air quality and meteorological networks from May 2014 to May 2015. This combined model is able to explain about 90% of the variation of the estimated PM2.5, and performs better than LME model by achieving higher correlation and smaller deviations between the satellites estimated PM2.5 and in situ measurements. Benefiting from the high resolution of 1 km × 1 km, MERSI AOD achieves much more detailed spatial distribution of ground-level PM2.5 over the major urban areas of Chongqing, compared to most of concurrent satellite products, such as the MODIS L2 AOD. According to the estimation, PM2.5 concentration is higher in cold seasons than in warm seasons in Chongqing. Peak levels of PM2.5 is found in Yuzhong District, the center of Chongqing urban area, while the concentration gradually decreases in surrounding areas, indicating that air pollution in Chongqing is highly contributed by local anthropogenic emissions. [ABSTRACT FROM AUTHOR]

Metal oxide semiconductor materials have a wide range of applications in the field of solar energy conversion. In this paper, CuO was prepared directly on copper foam substrate by anodic oxidation. The effects of current density and anodizing temperature on sample preparation and performance were studied. Field emission scanning electron microscopy (FESEM) and X-ray diffractometer (XRD) had been used to determine the morphology and phase structure of the sample, and its optical and electrical properties were discussed through UV-vis spectrophotometer and electrochemical tests. In addition, the influences of experimental conditions such as current density and reaction temperature on the morphology and properties of CuO were systematically discussed. The FESEM images showed that as the anodic oxidation temperature increase, the morphology of the prepared sample changed from nanowires to leaf-like CuO nanosheets. According to the results of XRD, the structure of prepared CuO was monoclinic, and the intensity of diffraction peaks gradually increased as anodizing temperature increased. We found that the optimum current density and anodizing temperature were 20 mA cm−2 and 60 °C, respectively. The results of electrochemical indicated that the CuO electrode based on copper foam (CuO/Cu foam) prepared at the optimum exhibited the highest specific capacitance (0.1039 F cm−2) when the scan rate was 2 mV s−1. [ABSTRACT FROM AUTHOR]

Total precipitable water (TPW) is an important key factor in the global water cycle and climate change. The knowledge of TPW characteristics at spatial and temporal scales could help us to better understand our changing environment. Currently, many algorithms are available to retrieve TPW from optical and microwave sensors. There are still no available TPW data over land from FY-3D MWRI, which was launched by China in 2017. However, the TPW product over land is a key element for the retrieval of many ecological environment parameters. In this paper, an improved algorithm was developed to retrieve TPW over land from the brightness temperature of FY-3D MWRI. The major improvement is that surface emissivity, which is a key parameter in the retrieval of TPW in all-weather conditions, was developed and based on an improved algorithm according to the characteristics of FY-3D MWRI. The improvement includes two aspects, one is selection of appropriate ancillary data in estimating surface emissivity parameter Δε18.7/Δε23.8 in clear sky conditions, and the other is an improvement of the Δε18.7/Δε23.8 estimation function in cloudy conditions according to the band configuration of FY-3D MWRI. Finally, TPW retrieved was validated using TPW observation from the SuomiNet GPS and global distributed Radiosonde Observations (RAOB) networks. According to the validation, TPW retrieved using observations from FY-3D MWRI and ancillary data from Aqua MODIS had the best quality. The root mean square error (RMSE) and correlation coefficient between the retrieved TPW and observed TPW from RAOB were 5.47 and 0.94 mm, respectively. [ABSTRACT FROM AUTHOR]

Chengdu is a typical basin city of Southwest China with rare observations of remote sensing measurements. To assess the climate change and establish a region aerosol model, a deeper understanding of the separated volume size distribution (VSD) and complex refractive index (CRI) is required. In this study, we employed the sub-mode VSD and CRI in Chengdu based on the three years observation data to investigate the sub-mode characteristics and climate effects. The annual average fraction of the fine-mode aerosol optical depth (AODf) is 92%, which has the same monthly tendency as the total AOD. But the coarse-mode aerosol optical depth (AODc) has little variation in different months. There are four distinguishing modes of VSD in Chengdu; the median radii are 0.17 μm ± 0.05, 0.31 μm ± 0.12, 1.62 μm ± 0.45, 3.25 μm ± 0.99, respectively. The multi-year average and seasonal variations of fine- and coarse-mode VSD and CRI are also analyzed to characterize aerosols over this region. The fine-mode single scattering albedos (SSAs) are higher than the coarse-mode ones, which suggests that the coarse-mode aerosols have a stronger absorbing effect on solar light than the small-size aerosol particles in Chengdu. [ABSTRACT FROM AUTHOR]

The fine-mode aerosol optical depth (AODf) is an important parameter for the environment and climate change study, which mainly represents the anthropogenic aerosols component. The Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) instrument can detect polarized signal from multi-angle observation and the polarized signal mainly comes from the radiation contribution of the fine-mode aerosols, which provides an opportunity to obtain AODf directly. However, the currently operational algorithm of Laboratoire d'Optique Atmosphérique (LOA) has a poor AODf retrieval accuracy over East China on high aerosol loading days. This study focused on solving this issue and proposed a grouped residual error sorting (GRES) method to determine the optimal aerosol model in AODf retrieval using the traditional look-up table (LUT) approach and then the AODf retrieval accuracy over East China was improved. The comparisons between the GRES retrieved and the Aerosol Robotic Network (AERONET) ground-based AODf at Beijing, Xianghe, Taihu and Hong_Kong_PolyU sites produced high correlation coefficients (r) of 0.900, 0.933, 0.957 and 0.968, respectively. The comparisons of the GRES retrieved AODf and PARASOL AODf product with those of the AERONET observations produced a mean absolute error (MAE) of 0.054 versus 0.104 on high aerosol loading days (AERONET mean AODf at 865 nm = 0.283). An application using the GRES method for total AOD (AODt) retrieval also showed a good expandability for multi-angle aerosol retrieval of this method. [ABSTRACT FROM AUTHOR]