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In order to determine the most suitable turbulence model for studying the aerodynamic performance of bus, the effects of different turbulence models on the aerodynamic characteristics of bus were investigated. A comparative analysis was conducted on five turbulence models (IDDES, DDES, DES, LES, URANS). The pressure distribution on the cross section at x=0 and y=0 is also analyzed for each model. The results reveal that IDDES accurately captures the negative pressure at the rear of the bus and predicts the pressure gradients more effectively than other models. IDDES also captures more vortices at the head of the bus and predicts the wake flow more widely than other models. DDES has obvious shedding phenomenon in the wake flow, while IDDES provides a relatively smooth airflow trajectory, but its prediction of airflow trajectory at a distance is less clear. Through quantitative and qualitative analyses of the aerodynamic characteristics of bus under different turbulence models, it can be concluded that IDDES is the most suitable turbulence model to study the aerodynamic characteristics of bus.

Domain size can have significant impact on regional modeling results, but few studies examined the sensitivities of simulated aerosol impact to regional domain size. This study investigates the regional modeling sensitivities of aerosol impact on the East Asian summer monsoon (EASM) to domain size. The simulations with two different domain sizes demonstrate consistently that aerosols induce the cooling of the lower troposphere that leads to the anticyclone circulation anomalies and thus the weakening of EASM moisture transport. The aerosol-induced adjustment of monsoonal circulation results in an alternate increase and decrease pattern of precipitation over China. Domain size has a great influence on the simulated meteorological fields. For example, the simulation with larger domain size produces weaker EASM circulation, which also affects aerosol distributions significantly. This leads to the difference of simulated strength and area extent of aerosol-induced changes of lower-tropospheric temperature and pressure, which further results in different distributions of circulation and precipitation anomalies over China. For example, over southeastern China, aerosols induce the increase (decrease) of precipitation from the smaller-domain (larger-domain) simulation. Different domain sizes consistently simulate an aerosol-induced increase in precipitation around 30∘ N over eastern China. This study highlights the important influence of domain size on regional modeling results of aerosol impact on circulation and precipitation, which may not be limited to East Asia. More generally, this study also implies that proper modeling of meteorological fields with appropriate domain size is one of the keys to simulating robust aerosol climatic impact.

Biogenic volatile organic compounds (BVOCs) simulated by current air quality and climate models still have large uncertainties, which can influence atmospheric chemistry and secondary pollutant formation. These modeling sensitivities are primarily due to two sources. One originates from different treatments in the physical and chemical processes associated with the emission rates of BVOCs. The other is errors in the specification of vegetation types and their distribution over a specific region. In this study, the version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) updated by the University of Science and Technology of China (USTC version of WRF-Chem) from the public WRF-Chem(v3.6) is used. The modeling results over eastern China with different versions (v1.0, v2.0, v3.0) of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in WRF-Chem are examined or documented. Sensitivity experiments with these three versions of MEGAN and two vegetation datasets are conducted to investigate the difference of three MEGAN versions in modeling BVOCs and its dependence on the vegetation distributions. The experiments are also conducted for spring (April) and summer (July) to examine the seasonality of the modeling results. The results indicate that MEGAN v3.0 simulates the largest amount of biogenic isoprene emissions over eastern China. The different performance among MEGAN versions is primarily due to their different treatments of applying emission factors and vegetation types. In particular, the results highlight the importance of considering the sub-grid vegetation fraction in estimating BVOC emissions over eastern China, which has a large area of urbanization. Among all activity factors, the temperature-dependent factor dominates the seasonal change of activity factor in all three versions of MEGAN, while the different response to the leaf area index (LAI) change determines the difference among the three versions in seasonal variation of BVOC emissions. The simulated surface ozone concentration due to BVOCs can be significantly different (ranging from 1 to more than 10 ppbv in some regions) among the experiments with three versions of MEGAN, which is mainly due to their impacts on surface VOCs and NOx concentrations. Theoretically MEGAN v3.0 that is coupled with the land surface scheme and considers the sub-grid vegetation effect should overcome previous versions of MEGAN in WRF-Chem. However, considering uncertainties of retrievals and anthropogenic emissions over eastern China, it is still difficult to apply satellite retrievals of formaldehyde and/or limited sparse in situ observations to constrain the uncertain parameters or functions in BVOC emission schemes and their impacts on photochemistry and ozone production. More accurate vegetation distribution and measurements of biogenic emission fluxes and species concentrations are still needed to better evaluate and optimize models.

In this paper, a novel automatic crater detection algorithm (CDA) based on traditional texture feature and random projection depth function has been proposed. By using traditional texture feature, mathematical morphology is used to identify crater initially. To further reduce the false detection rate, random projection depth function is used. For this purpose, firstly, gray level co-occurrence matrix and a novel grade level co-occurrence matrix are both used to further obtain the texture features of these candidate craters. Secondly, based on the above collected features, random projection depth function is used to refine the crater candidate detection results. LRO Narrow Angle Camera (NAC) mosaic images (1 m/pixel) and Wide-angle Camera (WAC) mosaic images (100 m/pixel) are used to test the accuracy of proposed method. The experimental results indicate our proposed method is robust to detect craters located in different terrains.

Satellite attitude jitter is a common and complex phenomenon for high-resolution satellites and it is detectable by multi-temporal image matching. This paper analyses the effect of image matching window size on jitter frequency detection. First, two simulation images with a given short time lag and line scanning frequency affected by a modelled jitter are generated based on the principle of dynamic imaging model. Then, the relative image distortions are obtained by dense image matching with different matching window size and the frequency is estimated through spectrum analysis of the obtained image distortions. The experimental results demonstrated the feasibility and reliability of high frequency jitter detection based on dense image matching, and the results indicated that the maximum detectable frequency is almost not affected by the change of image matching window size, which provided useful demonstration of image-based satellite jitter detection capacity.

Most previous modeling studies about black carbon (BC) transport and its impact over the Tibetan Plateau (TP) conducted simulations with horizontal resolutions coarser than 20 km that may not be able to resolve the complex topography of the Himalayas well. In this study, the two experiments covering all of the Himalayas with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) at the horizontal resolution of 4 km but with two different topography datasets (4 km complex topography and 20 km smooth topography) are conducted for pre-monsoon season (April 2016) to investigate the impacts of topography on modeling the transport and distribution of BC over the TP. Both experiments show the evident accumulation of aerosols near the southern Himalayas during the pre-monsoon season, consistent with the satellite retrievals. The observed episode of high surface BC concentration at the station near Mt. Everest due to heavy biomass burning near the southern Himalayas is well captured by the simulations. The simulations indicate that the prevailing upflow across the Himalayas driven by the large-scale westerly and small-scale southerly circulations during the daytime is the dominant transport mechanism of southern Asian BC into the TP, and it is much stronger than that during the nighttime. The simulation with the 4 km topography resolves more valleys and mountain ridges and shows that the BC transport across the Himalayas can overcome the majority of mountain ridges, but the valley transport is more efficient. The complex topography results in stronger overall cross-Himalayan transport during the simulation period primarily due to the strengthened efficiency of near-surface meridional transport towards the TP, enhanced wind speed at some valleys and deeper valley channels associated with larger transported BC mass volume. This results in 50 % higher transport flux of BC across the Himalayas and 30 %–50 % stronger BC radiative heating in the atmosphere up to 10 km over the TP from the simulation with the 4 km complex topography than that with the 20 km smoother topography. The different topography also leads to different distributions of snow cover and BC forcing in snow. This study implies that the relatively smooth topography used by the models with resolutions coarser than 20 km may introduce significant negative biases in estimating light-absorbing aerosol radiative forcing over the TP during the pre-monsoon season. Highlights. The black carbon (BC) transport across the Himalayas can overcome the majority of mountain ridges, but the valley transport is much more efficient during the pre-monsoon season. The complex topography results in stronger overall cross-Himalayan transport during the study period primarily due to the strengthened efficiency of near-surface meridional transport towards the TP, enhanced wind speed at some valleys and deeper valley channels associated with larger transported BC mass volume. The complex topography generates 50 % higher transport flux of BC across the Himalayas and 30 %–50 % stronger BC radiative heating in the atmosphere up to 10 km over the Tibetan Plateau (TP) than the smoother topography, which implies that the smooth topography used by the models with relatively coarse resolution may introduce significant negative biases in estimating BC radiative forcing over the TP during the pre-monsoon season. The different topography also leads to different distributions of snow cover and BC forcing in snow over the TP.

Diurnal variation of surface PM2.5 concentration (diurnal PM2.5) could dramatically affect aerosol radiative and health impacts and can also well reflect the physical and chemical mechanisms of air pollution formation and evolution. So far, diurnal PM2.5 and its modeling capability over East China have not been investigated and therefore are examined in this study. Based on the observations, the normalized diurnal amplitude of surface PM2.5 concentrations averaged over East China is weakest (∼1.2) in winter and reaches ∼1.5 in other seasons. The diurnal PM2.5 shows the peak concentration during the night in spring and fall and during the daytime in summer. The simulated diurnal PM2.5 with WRF-Chem and its contributions from multiple physical and chemical processes are examined in the four seasons. The simulated diurnal PM2.5 with WRF-Chem is primarily controlled by planetary boundary layer (PBL) mixing and emission variations and is significantly overestimated against the observation during the night. This modeling bias is likely primarily due to the inefficient PBL mixing of primary PM2.5 during the night. The simulated diurnal PM2.5 is sensitive to the PBL schemes and vertical-layer configurations with WRF-Chem. Besides the PBL height, the PBL mixing coefficient is also found to be the critical factor determining the PBL mixing of pollutants in WRF-Chem. With reasonable PBL height, the increase in the lower limit of the PBL mixing coefficient during the night can significantly reduce the modeling biases in diurnal PM2.5 and also the mean concentrations, particularly in the major cities of East China. It can also reduce the modeling sensitivity to the PBL vertical-layer configurations. The diurnal variation and injection height of anthropogenic emissions also play roles in simulating diurnal PM2.5, but the impact is relatively smaller than that from the PBL mixing. This study underscores that more efforts are needed to improve the boundary mixing process of pollutants in models with observations of PBL structure and mixing fluxes in addition to PBL height, in order to simulate reasonably the diurnal PM2.5 over East China. The diurnal variation and injection height of anthropogenic emissions must also be included to simulate the diurnal PM2.5 over East China.

The rapid advancement of global navigation satellite system (GNSS) occultation technology in recent years has made it one of the most advanced space-based remote sensing technologies of the 21st century. GNSS radio occultation has many advantages, including all-weather operation, global coverage, high vertical resolution, high precision, long-term stability, and self-calibration. Data products from GNSS occultation sounding can greatly enhance ionospheric observations and contribute to space weather monitoring, forecasting, modeling, and research. In this study, GNSS occultation sounder (GNOS) results from a radio occultation sounding payload aboard the Fengyun 3 C (FY3-C) satellite were compared with ground-based ionosonde observations. Correlation coefficients for peak electron density (NmF2) derived from GNOS Global Position System (GPS) and Beidou navigation system (BDS) products with ionosonde data were higher than 0.9, and standard deviations were less than 20 %. Global ionospheric effects of the strong magnetic storm event in March 2015 were analyzed using GNOS results supported by ionosonde observations. The magnetic storm caused a significant disturbance in NmF2 level. Suppressed daytime and nighttime NmF2 levels indicated mainly negative storm conditions. In two longitude section zones of geomagnetic inclination between 40 and 80∘, the results of average NmF2 observed by GNOS and ground-based ionosondes showed the same basic trends during the geomagnetic storm and confirmed the negative effect of this storm event on the ionosphere. The analysis demonstrates the reliability of the GNSS radio occultation sounding instrument GNOS aboard the FY3-C satellite and confirms the utility of ionosphere products from GNOS for statistical and event-specific ionospheric physical analyses. Future FY3 series satellites and increasing numbers of Beidou navigation satellites will provide increasing GNOS occultation data on the ionosphere, which will contribute to ionosphere research and forecasting applications.

Erhai Lake is a subtropical highland shallow lake on the southeast margin of the Tibetan Plateau, which is influenced by both South Asian and East Asian summer monsoons. Based on 4 years of continuous eddy covariance (EC) data over Erhai Lake, the monsoon effect on water–atmosphere exchange processes is investigated by comparing the energy and CO2 flux patterns and their main drivers during pre-monsoon (March–April), monsoon (May–October) and post-monsoon (November–December) periods. The results show that the atmospheric properties display a large difference during the three different periods. There is a negative difference between water surface and air temperature (T) during the pre-monsoon period, while a positive T during the post-monsoon period. The diurnal sensible heat flux (Hs) is larger during the post-monsoon period, while the latent heat flux (LE) is larger during the monsoon period. The monthly average Hs and heat storage (Q) in the lake remain negative during the pre-monsoon period and the early monsoon period, and they become positive in the middle monsoon period, which indicates that the lake absorbs heat at first and releases it subsequently. LE plays a dominating role in the energy partitioning of the lake. The Bowen ratio is higher during the post-monsoon period. The uptake of CO2 flux is observed in the middle of the day during monsoon and post-monsoon periods. The ΔT is the main driver for Hs and the effect of ΔT is increased as timescales are extended from half-hourly to monthly. The wind speed has a weak effect on Hs but a strong effect on LE and CO2 fluxes. Similar main drivers for Hs are found during the pre-monsoon and post-monsoon periods, which is also found for CO2 flux, indicating a large impact of the monsoon on the heat and carbon exchange processes over Erhai Lake.

The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new-generation payloads on board the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. FY-3C GNOS, on board the FY-3 series C satellite launched in September 2013, was designed to acquire setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou Navigation Satellite System (BDS) and the US Global Positioning System (GPS). So far, the GNOS measurements and atmospheric and ionospheric data products have been validated and evaluated and then been used for atmosphere- and ionosphere-related scientific applications.This paper reviews the FY-3C GNOS instrument, RO data processing, data quality evaluation, and preliminary research applications according to the state-of-the-art status of the FY-3C GNOS mission and related publications. The reviewed data validation and application results demonstrate that the FY-3C GNOS mission can provide accurate and precise atmospheric and ionospheric GNSS (i.e., GPS and BDS) RO profiles for numerical weather prediction (NWP), global climate monitoring (GCM), and space weather research (SWR). The performance of the FY-3C GNOS product quality evaluation and scientific applications establishes confidence that the GNOS data from the series of FY-3 satellites will provide important contributions to NWP, GCM, and SWR scientific communities.

The Global Navigation Satellite System (GNSS) radio occultation (RO) technique is widely used to observe the atmosphere for applications such as numerical weather prediction and global climate monitoring. The ionosphere is a major error source to RO at upper stratospheric altitudes, and a linear dual-frequency bending angle correction is commonly used to remove the first-order ionospheric effect. However, the higher-order residual ionospheric error (RIE) can still be significant, so it needs to be further mitigated for high-accuracy applications, especially from 35 km altitude upward, where the RIE is most relevant compared to the decreasing magnitude of the atmospheric bending angle. In a previous study we quantified RIEs using an ensemble of about 700 quasi-realistic end-to-end simulated RO events, finding typical RIEs at the 0.1 to 0.5 µrad noise level, but were left with 26 exceptional events with anomalous RIEs at the 1 to 10 µrad level that remained unexplained. In this study, we focused on investigating the causes of the high RIE of these exceptional events, employing detailed along-ray-path analyses of atmospheric and ionospheric refractivities, impact parameter changes, and bending angles and RIEs under asymmetric and symmetric ionospheric structures. We found that the main causes of the high RIEs are a combination of physics-based effects – where asymmetric ionospheric conditions play the primary role, more than the ionization level driven by solar activity – and technical ray tracer effects due to occasions of imperfect smoothness in ionospheric refractivity model derivatives. We also found that along-ray impact parameter variations of more than 10 to 20 m are possible due to ionospheric asymmetries and, depending on prevailing horizontal refractivity gradients, are positive or negative relative to the initial impact parameter at the GNSS transmitter. Furthermore, mesospheric RIEs are found generally higher than upper-stratospheric ones, likely due to being closer in tangent point heights to the ionospheric E layer peaking near 105 km, which increases RIE vulnerability. In the future we will further improve the along-ray modeling system to fully isolate technical from physics-based effects and to use it beyond this work for additional GNSS RO signal propagation studies.

The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the new-generation payloads onboard the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. The GNOS was designed for acquiring setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou System (BDS) and the US Global Positioning System (GPS). An ultra-stable oscillator with 1 s stability (Allan deviation) at the level of 10−12 was installed on the FY-3C GNOS, and thus both zero-difference and single-difference excess phase processing methods should be feasible for FY-3C GNOS observations. In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing, in order to investigate the zero-difference feasibility for this new instrument, which after its launch in September 2013 started to use BDS signals from five geostationary orbit (GEO) satellites, five inclined geosynchronous orbit (IGSO) satellites and four medium Earth orbit (MEO) satellites. We used a 3-month set of GNOS BDS RO data (October to December 2013) for the evaluation and compared atmospheric bending angle and refractivity profiles, derived from single- and zero-difference excess phase data, against co-located profiles from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. We also compared against co-located refractivity profiles from radiosondes. The statistical evaluation against these reference data shows that the results from single- and zero-difference processing are reasonably consistent in both bias and standard deviation, clearly demonstrating the feasibility of zero differencing for GNOS BDS RO observations. The average bias (and standard deviation) of the bending angle and refractivity profiles were found to be about 0.05 to 0.2 % (and 0.7 to 1.6 %) over the upper troposphere and lower stratosphere. Zero differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise. The validation results indicate that GNOS can provide, on top of GPS RO profiles, accurate and precise BDS RO profiles both from single- and zero-difference processing. The GNOS observations by the series of FY-3 satellites are thus expected to provide important contributions to numerical weather prediction and global climate change analysis.

Iron antimonide (FeSb_{2}) with peculiar colossal thermopower of about −45 mV/K at 10 K is a mysterious material, and a unified microscopic description of this phenomenon is far from being achieved. Combining angle-resolved photoemission spectroscopy (ARPES) and ab initio calculations, we find that the intricate electronic structure of FeSb_{2} consists of two bands near the Fermi energy: the weakly dispersing strongly renormalized α band and the holelike β band that intersect at Γ and Y points of the Brillouin zone. In addition, we found the surface state originated from the bulk β band. While both bulk bands upshift towards the Fermi level upon raising of the temperature, the weakly dispersing surface states vanish above 100 K. The structural distortions and/or a mixture of the localized low-spin state with the delocalized high-spin state populated with temperature could be responsible for this temperature dependence. Our study reveals that the sizable renormalization of the nondispersing α band and the hybridization with the holelike β band cause the local increase of the density of states, consequently raising the colossal thermopower in FeSb_{2}.

ZiYuan-3 (ZY-3), launched in January 09, 2012, is China's first civilian high-resolution stereo mapping satellite. ZY-3 is equipped with three-line scanners (nadir, backward and forward) for stereo mapping, the resolutions of the panchromatic (PAN) stereo mapping images are 2.1-m at nadir looking and 3.6-m at tilt angles of ±22° forward and backward looking, respectively. The stereo base-height ratio is 0.85-0.95. Compared with stereo mapping from two views images, three-line arrays images of ZY-3 can be used for DSM generation taking advantage of one more view than conventional photogrammetric methods. It would enrich the information for image matching and enhance the accuracy of DSM generated. The primary result of positioning accuracy of ZY-3 images has been reported, while before the massive mapping applications of utilizing ZY-3 images for DSM generation, the performance evaluation of DSM extraction from three-line arrays imagery of ZY-3 has significant meaning for the routine mapping applications. The goal of this research is to clarify the mapping performance of ZY-3 three-line arrays scanners on china’s first civilian high-resolution stereo mapping satellite of ZY-3 through the accuracy evaluation of DSM generation. The comparison of DSM product in different topographic areas generated with three views images with different two views combination images of ZY-3 would be presented. Besides the comparison within different topographic study area, the accuracy deviation of the DSM products with different grid size including 25-m, 10-m and 5-m is delineated in order to clarify the impact of grid size on accuracy evaluation.

The integration of digital aerial photogrammetry and Light Detetion And Ranging (LiDAR) is an inevitable trend in Surveying and Mapping field. We calculate the external orientation elements of images which identical with LiDAR coordinate to realize automatic high precision registration between aerial images and LiDAR data. There are two ways to calculate orientation elements. One is single image spatial resection using image matching 3D points that registered to LiDAR. The other one is Position and Orientation System (POS) data supported aerotriangulation. The high precision registration points are selected as Ground Control Points (GCPs) instead of measuring GCPs manually during aerotriangulation. The registration experiments indicate that the method which registering aerial images and LiDAR points has a great advantage in higher automation and precision compare with manual registration.