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For Chinaware fragments, it is difficult to assemble them directly without considering the wonderful patterns painted on them. Given the simplicity of the Chinaware designs, each object contains similar textures and patterns. Compared to the oddly diverse appliance modeling, the difference between fragments of different Chinaware is small. The fragments are small and the fracture is flat, and there are many potential matching objects. For the Chinaware fragments’ reassembly, most of the work is still done manually. There is little available fully automatic reassembly work, and these approaches are for the reassembly of a single Chinaware. But what reality demands is the reassembly of the multi-Chinaware. Therefore, this article proposes an automatic method, whose strategy is analogous to the manual assembly, to accomplish this complex task. First, segment the contours of fracture surfaces of the fragments by the geometric feature of fracture edge; then, the contours are matched using our proposed multi-scale linear feature descriptor; given the massive fragments of multiple objects, we use the inaccurate matching strategy to build a matching set for each fracture surface contour and perform contour matching in this set. In this article, the fracture surface is segmented using the 2D slope information on the fragment edge. The descriptor proposed in the article uses distance triangle towers and chained angles to describe the “undulations” of the fracture surface. Moreover, the article uses a strict absolute-advantage-principle to reject false matching. In addition, after the initial reconstruction, we will iteratively adjust fragments according to the gap between the fragments to achieve better multi-fragment matching results. In this article, 18 porcelains, a total of 103 pieces, have been tested. Experiments are also carried out for special cases, including fragment reassembly with missing fragments and fragment reassembly with redundant fragments. The experimental results showed the effectiveness of method. However, the types of experimental data we currently have are relatively simple, and there is no way to reassemble the fragments in minutes. We hope to enable faster reassembly of more fragments in the future.

The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript. The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis, and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect Third Pole–related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in the upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the Third Pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.

BACKGROUND: There is a great demand for the extraction of organ models from three-dimensional (3D) medical images in clinical medicine diagnosis and treatment. OBJECTIVE: We aimed to aid doctors in seeing the real shape of human organs more clearly and vividly. METHODS: The method uses the minimum eigenvectors of Laplacian matrix to automatically calculate a group of basic matting components that can properly define the volume image. These matting components can then be used to build foreground images with the help of a few user marks. RESULTS: We propose a direct 3D model segmentation method for volume images. This is a process of extracting foreground objects from volume images and estimating the opacity of the voxels covered by the objects. CONCLUSIONS: The results of segmentation experiments on different parts of human body prove the applicability of this method.

Extracting 3D structures from voxel based images can make doctors more directly observe the situation of the target in the clinic, making it easier for doctors to diagnose the condition and make the medicine teaching more directly and easier to understand. For this purpose, we propose a 3D volume image segmentation method based on the max-flow/min-cut algorithm. Our segmentation method can be applied directly to 3D volume image. After users marking small amount tags (foreground and background pixels), we put forward a method to use a directed connected graph structure to represent the volume image. In the directed connected graph, in order to speed up the efficiency of the segmentation in subsequent steps, we divide each voxel node in the graph into different color ranges, and each color range match up with an auxiliary node. In order to divide the color range more finely, we propose a method to calculate the color similarity. We then use the max-flow/min-cut algorithm to segment the directed connected graph. The result of experiments performed in multiple sets of slice images shows that our proposed method improves the efficiency, reduces human error on the 3D volume image segmentation task, and the result is complete and accurate.

Cyclic di-guanosine monophosphate (c-di-GMP) is a ubiquitous second messenger, i.e. essential to bacterial adaptation to environments. Cellular c-di-GMP level is regulated by the diguanylate cyclases and the phosphodiesterases, and the signal transduction depends on its receptors. In Xanthomonas oryzae pv. oryzae strain PXO99A, 37 genes were predicted to encode GGDEF, EAL, GGDEF/EAL, HD-GYP, FleQ, MshE, PilZ, CuxR, Clp, and YajQ proteins that may be involved in c-di-GMP turnover or function as c-di-GMP receptors. Although the functions of some of these genes have been studied, but the rest have not been extensively studied. Here, we deleted these 37 genes from PXO99A and analyzed the virulence, motility, biofilm, and EPS production of these mutants. Our results show that most of these genes are required for PXO99A virulence, motility, biofilm formation, or exopolysaccharide production. Although some of them have been reported in previous studies, we found four novel genes (gedpX8, gdpX11, pliZX4, and yajQ) are implicated in X. oryzae pv. oryzae virulence. Our data demonstrate that c-di-GMP signaling is vital for X. oryzae pv. oryzae virulence and some virulence-related factors production, but there is no positive correlation between them in most cases. Taken together, our systematic research provides a new light to understand the c-di-GMP signaling network in X. oryzae pv. oryzae.

Cyanogenic glucosides (CNglcs) play an important role in plant defense response; however, the mechanism of regulation of CNglc synthesis by the external environment and endogenous hormones is largely unclear. In this study, we found that jasmonates (JAs) promoted the synthesis of CNglcs by activating the expression of CNglc biosynthesis genes in Lotus japonicus. Several differentially expressed basic helix–loop–helix (bHLH) family genes related to the synthesis of CNglcs were identified by RNA-seq. LjbHLH7 can directly activate the expression of CYP79D3 gene, the first step of CNglc synthesis, by binding to the G-box sequence of its promoter. Transgenic plants overexpressing LjbHLH7 exhibited higher relative CNglc content and enhanced insect resistance compared with the wild type. Furthermore, the transcriptional activity of LjbHLH7 was suppressed by the interaction with the L. japonicus JASMONATE-ZIM DOMAIN protein LjJAZ4. Based on these results, we propose that LjbHLH7 acts as an activator and LjJAZ4 acts as a repressor of JA-induced regulation of CNglc biosynthesis in L. japonicus.

The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset using an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products; the water vapor, surface pressure and ozone from ERA5 reanalysis data; and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data were evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimates at 10 km scale were −11.5 W m−2, 113.5 W m−2 and 0.92, respectively. When the estimated instantaneous SSR data were upscaled to 90 km, its error was clearly reduced, with RMSE decreasing to 93.4 W m−2 and R increasing to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The dataset is available at https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

Agrobacterium tumefaciens can cause crown gall tumors by transferring both an oncogenic piece of DNA (T-DNA) and several effector proteins into a wide range of host plants. For the translocated effector VirE3 multiple functions have been reported. It acts as a transcription factor in the nucleus binding to the Arabidopsis thaliana pBrp TFIIB-like protein to activate the expression of VBF, an F-box protein involved in degradation of the VirE2 and VIP1 proteins, facilitating Agrobacterium-mediated transformation. Also VirE3 has been found at the plasma membrane, where it could interact with VirE2. Here, we identified AtJAZ8 in a yeast two-hybrid screening with VirE3 as a bait and confirmed the interaction by pull-down and bimolecular fluorescence complementation assays. We also found that the deletion of virE3 reduced Agrobacterium virulence in a root tumor assay. Overexpression of virE3 in Arabidopsis enhanced tumorigenesis, whereas overexpression of AtJAZ8 in Arabidopsis significantly decreased the numbers of tumors formed. Further experiments demonstrated that AtJAZ8 inhibited the activity of VirE3 as a plant transcriptional regulator, and overexpression of AtJAZ8 in Arabidopsis activated AtPR1 gene expression while it repressed the expression of AtPDF1.2. Conversely, overexpression of virE3 in Arabidopsis suppressed the expression of AtPR1 whereas activated the expression of AtPDF1.2. Our results proposed a novel mechanism of counter defense signaling pathways used by Agrobacterium, suggesting that VirE3 and JAZ8 may antagonistically modulate the salicylic acid/jasmonic acid (SA/JA)-mediated plant defense signaling response during Agrobacterium infection.

Xanthomonas campestris pv. campestris (Xcc) can cause black rot in cruciferous plants worldwide. Two-component systems (TCSs) are key for bacterial adaptation to various environments, including hosts. VemR is a TCS response regulator and crucial for Xcc motility and virulence. Here, we report that RavA is the cognate histidine kinase (HK) of VemR and elucidate the signalling pathway by which VemR regulates Xcc motility and virulence. Genetic analysis showed that VemR is epistatic to RavA. Using bacterial two-hybrid experiments and pull-down and phosphorylation assays, we found that RavA can interact with and phosphorylate VemR, suggesting that RavA is the cognate HK of VemR. In addition, we found that RpoN2 and FleQ are epistatic to VemR in regulating bacterial motility and virulence. In vivo and in vitro experiments demonstrated that VemR interacts with FleQ but not with RpoN2. RavA/VemR regulates the expression of the flagellin-encoding gene fliC by activating the transcription of the rpoN2-vemR-fleQ and flhF-fleN-fliA operons. In summary, our data show that the RavA/VemR TCS regulates FleQ activity and thus influences the expression of motility-related genes, thereby affecting Xcc motility and virulence. The identification of this novel signalling pathway will deepen our understanding of Xcc-plant interactions.

In the paper, we propose a novel method to analyze the rebalancing of the free-floating bike-sharing system. First, we construct a visualization method to analyze the rebalancing of the system. Then, for the first time, we set up a coarse-grained way to study dynamics rebalancing during rush hours. Finally, we complete the empirical analysis with the real-time cycling data of the Nanjing Mobike Sharing-bike Company. The results show that: static rebalancing is weak, and dynamic rebalancing during rush hours is serious. Therefore, increasing the number of shared bikes in parking spots can ease the rebalancing. At the same time, we find that commuting to and from work is not the main factor that constitutes the rebalancing of the free-floating bike-sharing system, though the rebalancing is proportional to travel frequency.

The Qilian Mountains Scientific Expedition was launched under the framework of the Second Tibetan Plateau Scientific Expedition Program after tightening eco-environmental management in the Qilian Mountains. The expedition focused on three key areas: (1) Ecosystem diversity and security, (2) dynamic changes in glaciers and permafrost, and (3) changes in human activities and their corresponding eco-livelihood impacts. In this scientific expedition, a comprehensive investigation was conducted according to an integrated space–drone–ground-based field survey and a socioeconomic survey. More than 200 researchers participated in this expedition that lasted for 260 d and spanned 47500 km. First, investigations were performed for changes in human activities before and after tightening eco-environmental management in the Qilian Mountains. The local eco-environmental benefits and economic losses after the tightening eco-environmental management were analyzed by adopting the Integrated Valuation of Ecosystem Services and Tradeoffs model and the System of Integrated Environmental and Economic Accounting method. Additionally, the telecoupling values of the overall ecosystem services of the Qilian Mountains were estimated using an innovative method. Second, investigations were performed for several glaciers located in the Qilian Mountains to evaluate the characteristics of glacier distribution and variations in glacier changes. The glacier ice storage and annual degradation rate were further estimated using data derived from a glacier inventory and Landsat images. Moreover, the characteristics of permafrost distribution in the Qilian Mountains were comprehensively analyzed. Furthermore, an innovative method was developed to estimate ground ice storage and the annual water discharge rate from permafrost in the six river basins of the Qilian Mountains. Lastly, investigations were performed on changes in the forest line in a coupled forest and shrub ecosystem using a drone and field surveys. Further, the spatial and temporal grassland patterns and the associated productivity were analyzed. Moreover, dynamic changes in the five main lakes in the Qilian Mountains were assessed at different spatial and temporal scales, and the activities of the key rare species such as the snow leopard were monitored regularly using infrared cameras. The key findings of the Qilian Mountains Scientific Expedition were as follows: (1) The ecological service functions of the Qilian Mountains are promoted by tightening eco-environmental management; (2) the ecosystem of the Qilian Mountains is recovering under a warm and wet climate, and the population of rare species is expanding; however, localized overgrazing is causing grassland degradation in some areas; (3) the glacier loss rate is accelerating, and the contribution of glacial melt to river runoff is expected to exceed the critical point; (4) over the past 10 years, the meltwater from permafrost has been as high as 1.18 km3/a, which is equivalent to 10% of the annual runoff into the Qilian Mountain rivers; (5) the value of the overall ecosystem services in the Qilian Mountains has been estimated to be as high as 1067.6 (±160.1) billion Yuan, which is much higher than the regional economic loss observed in 2017. It is suggested that the government should markedly increase ecological compensation to achieve a win-win situation for green development regarding ecological livelihood in the Qilian Mountains. The findings from this scientific expedition provide comprehensive datasets and decision-making support for the establishment and management of the Qilian Mountain National Park and the protection of the ecosystems of the Qilian Mountains. Such expeditions can provide scientific support for watershed management in states or regions located along the Silk Road Economic Belt.

Background 4D ultrasound images of human fetal heart are important for medical applications such as evaluation of fetal heart function and early diagnosis of congenital heart diseases. However, due to the high noise and low contrast characteristics in fetal ultrasound images, denoising and enhancements are important. Methods In this paper, a special method framework for denoising and enhancing is proposed. It consists of a 4D-NLM (non-local means) denoising method for 4D fetal heart ultrasound image sequence, which takes advantage of context similar information in neighboring images to denoise the target image, and an enhancing method called the Adaptive Clipping for Each Histogram Pillar (ACEHP), which is designed to enhance myocardial spaces to distinguish them from blood spaces. Results Denoising and enhancing experiments show that 4D-NLM method has better denoising effect than several classical and state-of-the-art methods such as NLM and WNNM. Similarly, ACEHP method can keep noise level low while enhancing myocardial regions better than several classical and state-of-the-art methods such as CLAHE and SVDDWT. Furthermore, in the volume rendering after the combined "4D-NLM+ACEHP" processing, the cardiac lumen is clear and the boundary is neat. The Entropy value that can be achieved by our method framework (4D-NLM+ACEHP) is 4.84. Conclusions Our new framework can thus provide important improvements to clinical fetal heart ultrasound images.

The Pan-Third Pole includes the Tibetan Plateau and the northern intracontinental arid region of Asia, extending to the Caucasus Mountains in the west and the western Loess Plateau in the east. This region covers 20 million square kilometers and affects the environment inhabited by three billion people. Two special projects have been implemented to provide important scientific support for eco-environmental refining and sustainable economic and social development of the Pan-Third Pole region, with the Tibetan Plateau as its core: the Second Tibetan Plateau Scientific Expedition Program (a national special project) and the Pan-Third Pole Environmental Change and Construction of the Green Silk Road (hereinafter referred to as the Silk Road and Environment), a strategic pilot science and technology project (Category A) of the Chinese Academy of Science. The Pan-Third Pole big data system is an important data support platform for these two major research programs and has several purposes: the storage, management, analysis, mining and sharing of scientific data for various disciplines, such as resources, the environment, ecology and atmospheric science of the Pan-Third Pole; preparation of key scientific data products of the Pan-Third Pole; the gradual development of functions such as online big data analysis and model application; the construction of a cloud-based platform to integrate data, methods, models; and services for Pan-Third Pole research and promote application of big data technology in scientific research in the region. This paper demonstrates in detail various aspects of the Pan-Third Pole big data system, including the system architecture, data resource integration and big data analysis methods. The system improves big data processing capability in geoscience, serves as a new paradigm of geoscience research driven by big data and facilitates scientific research of the Earth system of the Pan-Third Pole.

The Global Precipitation Measurement (GPM) mission provides high-resolution precipitation estimates globally. However, their accuracy needs to be accessed for algorithm enhancement and hydro-meteorological applications. This study applies data from 388 gauges in Nepal to evaluate the spatial-temporal patterns presented in recently-developed GPM-Era satellite-based precipitation (SBP) products, i.e., the Integrated Multi-satellite Retrievals for GPM (IMERG), satellite-only (IMERG-UC), the gauge-calibrated IMERG (IMERG-C), the Global Satellite Mapping of Precipitation (GSMaP), satellite-only (GSMaP-MVK), and the gauge-calibrated GSMaP (GSMaP-Gauge). The main results are as follows: (1) GSMaP-Gauge datasets is more reasonable to represent the observed spatial distribution of precipitation, followed by IMERG-UC, GSMaP-MVK, and IMERG-C. (2) The gauge-calibrated datasets are more consistent (in terms of relative root mean square error (RRMSE) and correlation coefficient (R)) than the satellite-only datasets in representing the seasonal dynamic range of precipitation. However, all four datasets can reproduce the seasonal cycle of precipitation, which is predominately governed by the monsoon system. (3) Although all four SBP products underestimate the monsoonal precipitation, the gauge-calibrated IMERG-C yields smaller mean bias than GSMaP-Gauge, while GSMaP-Gauge shows the smaller RRMSE and higher R-value; indicating IMERG-C is more reliable to estimate precipitation amount than GSMaP-Gauge, whereas GSMaP-Gauge presents more reasonable spatial distribution than IMERG-C. Only IMERG-C moderately reproduces the evident elevation-dependent pattern of precipitation revealed by gauge observations, i.e., gradually increasing with elevation up to 2000 m and then decreasing; while GSMaP-Gauge performs much better in representing the gauge observed spatial pattern than others. (4) The GSMaP-Gauge calibrated based on the daily gauge analysis is more consistent with detecting gauge observed precipitation events among the four datasets. The high-intensity related precipitation extremes (95th percentile) are more intense in regions with an elevation below 2500 m; all four SBP datasets have low accuracy (40%) the frequency of extreme events at most of the stations across the country. This work represents the quantification of the new-generation SBP products on the southern slopes of the central Himalayas in Nepal.

National Tibetan Plateau Data Center (TPDC) is one of the first 20 national data centers authorized by the Ministry of Science and Technology of China in 2019 . It is the only data center in China with the most complete scientific data for the Tibetan Plateau and surrounding regions. There are more than 1700 datasets covering many disciplines such as geography, atmospheric science, cryospheric science, hydrology, ecology, geology, geophysics, natural resource science, social economy, and other fields. All data are sorted and integrated in a strict way accordance with the data standards specified by TPDC and the relevant data acquisition specifications. The mission of the data center is to establish a big data center for Third-Pole Earth System Sciences to integrate ThirdPole data resources, particularly those obtained through the implementation of the Third-Pole "Super Monitoring" plan; to develop cutting edge observation technology for extreme environments; and to build a comprehensive and intelligent Internet of Things (IoT) observation system for the Pan-Third Pole region. These developments will facilitate the modeling of environmental changes in the Pan-Third Pole with improved accuracy and performance, as well as support decision-making for sustainable development of the Pan-Third Pole region.TPDC complies with the “findable, accessible, interoperable and reusable (FAIR)” data sharing principles, in which, the scientific data and metadata can be 'findable' by anyone for exploring and using, can be 'accessible' for being examined, can be 'interoperable' for being analyzed and integrated with comparable data through the use of common vocabulary and formats, can be 'reusable' for public as a result of robust metadata, provenance information and clear usage license. Under the guidance of FAIR data sharing principle, Pan-Third big data system provides online sharing manner for data users, supplemented by offline sharing manner, with bilingual data sharing in Chinese and English.TPDC has joined WMO (World Meteorological Organization) to promote the project of Integrated Global Cryosphere Information System (IGCryoIS), aiming to collect and share multi-source data in global regions where data is difficult to obtain. Recently TPDC and NSIDC (National Snow and Ice Data Center) officially signed a memorandum of collaboration on data sharing and research to start comprehensive cooperation. TPDC is strengthening cooperation with the international data organizations (e.g. CODATA, WDS) and providing data support for the international science programs of the Tibetan Plateau (e.g. TPE, ANSO). TPDC is applying to become a recommended data repository for the international mainstream journals so as to encourage data authors to share their well-documented, useful and preserved data by giving them credit and recognition. In a word, TPDC stores, integrates, analyses, excavates and publishes scientific data such as resources, environment, ecology and atmosphere in Pan-third polar region, gathers Pan-third polar core data resources, forms Pan-third polar key scientific data products, and gradually develops online large data analysis, model application and other functions. Furthermore, a cloud service platform will be built for the extensive integration of data, methods, models and services in Pan-Third Pole Science and to promote the application of large data methods in Pan-Third Pole Science Research.

Xanthomonas oryzae pv. oryzae (Xoo) is the causal agent of rice bacterial blight disease, which causes a reduction in rice production. The interaction between Xoo and rice is a model for the study of the gene-for-gene hypothesis, in which a resistance (R) gene encoding a product interacts with an effector molecule encoded by a corresponding bacterial avirulence (avr) gene. Rice XA21 functions as a plant innate immune receptor (R protein) and recognizes the avirulence protein (RaxX) of Xoo to induce the immune response and cope with pathogen attack. The sulphuration of RaxX by the tyrosine sulphotransferase RaxST is essential to its activity. The expression of raxST is regulated by the RaxH/RaxR and phoP/phoQ two-component systems. However, the regulation of raxX expression remains unclear. Here, we showed that a gene (raxM) encodes a small protein, which functions as a regulator of raxX expression. raxX and raxM are located upstream of raxST. Transcriptional analysis indicates that raxX and raxM are separately transcribed and the promoter of raxX is located at the raxM coding region. The RaxM protein regulates its own and raxX expression, and is required for the XA21-mediated immunity response. Therefore, we identified a regulator of raxX expression and of the Xoo-rice interaction. Our findings suggest that RaxX is not only regulated at the post-translational level, but also at the transcriptional level.

Accurate estimate of direct solar radiation is a prerequisite for the design of concentrated solar power thermal systems; however, direct radiation observations are very sparse compared to observations of routine meteorological variables. Therefore, this study developed a method for estimating daily direct radiation from routine observations, based mainly on a clear-sky physical model to compute clear-sky direct radiation and a parameterized formula to compute cloud transmittance from sunshine duration data. The parameters of the cloud transmittance formula were calibrated with high-quality radiation data measured in the United States. The validation results at independent stations in the United States were comparable to those at the calibration stations, indicating that the method is suitable for various climatic and geographic conditions. We applied this method to compile a long-term, high-density data set of daily direct radiation over China based on observations from 2,473 routine weather stations of the China Meteorological Administration (CMA) network. Although the root-mean-square error of the data set from the 20 CMA radiation stations at which the direct solar radiations have been observed since 1993 is about 27.3Wm(-2), the accuracy of the data set for CMA routine weather stations with less severe air pollution should be better. The newly developed data set in this study, which is available upon request, will contribute to the development of concentrated solar power thermal systems throughout China.

A fast parameterization scheme named SUNFLUX is first used in this paper to estimate instantaneous surface solar radiation (SSR) based on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard both Terra and Aqua platforms. The scheme mainly takes into account the absorption and scattering processes due to clouds, aerosols, and gas in the atmosphere. The estimated instantaneous SSR is evaluated against surface observations obtained from seven stations of the surface radiation budget network (SURFRAD), four stations in the North China Plain (NCP) and 40 stations of the baseline surface radiation network (BSRN). The statistical results for evaluation against these three data sets show that the relative root-mean-square error (RMSE) values of SUNFLUX are less than 15%, 16%, and 17%, respectively. Daily SSR is derived through temporal upscaling from the MODIS-based instantaneous SSR estimates, and is validated against surface observations. The relative RMSE values for daily SSR estimates are about 16% at the seven SURFRAD stations, four NCP stations, 40 BSRN stations, and 90 China Meteorological Administration (CMA) radiation stations. The accuracy of the scheme is generally higher than those of previous algorithms, and thus can be potentially applied on geostationary satellites for mapping high-resolution SSR data in the future.

Photosynthetically active radiation (PAR) is the critical forcing data in ecological and agricultural fields. Remote sensing can be utilized to derive spatiotemporally continuous PAR. Empirical algorithms can be used to quickly retrieve surface PAR data sets, but their accuracy cannot be guaranteed in regions without local calibration. Physical algorithms generally incorporate all relevant physical processes and can be used globally, but their computational efficiency is often low. In this paper, an efficient algorithm is developed to calculate surface PAR by combining a clear-sky PAR model and the parameterizations for cloud transmittances. In the algorithm, the transmittances for water vapor, ozone, Rayleigh, aerosol, and cloud are each handled across the whole PAR band (400–700 nm). In addition, the contribution of the multiple reflections between surface ground and the atmosphere are also expressly considered. The new algorithm is applied to estimate instantaneous PAR with inputs from Moderate Resolution Imaging Spectroradiometer (MODIS) products onboard both Terra and Aqua platforms. The daily PAR is estimated from these two instantaneous values by an upscaling method. The instantaneous and daily PAR estimates were validated with in situ data collected in the USA and China. The results indicate that the new algorithm, based on MODIS products, can effectively retrieve PAR with root mean square errors (RMSE) of about 40 W m − 2 and 15 W m − 2 at instantaneous and daily-mean time scales, respectively. These performances are generally better than those of previous studies.

Global radiation over China decreased between the 1960s and 1990, since when it has remained stable. As the total cloud cover has continued to decrease since the 1960s, variations in aerosols were suggested in previous studies to be the primary cause for variations in global radiation over China. However, the effect of aerosols on global radiation on a decadal scale has not been physically quantified over China. In this study, aerosol optical depth (AOD) data since 1980 are estimated by combining horizontal visibility data at stations in China and AOD observed by the moderate resolution imaging spectroradiometer (MODIS). It is found that the AOD exhibits decadal changes, with two decreasing periods (before the end of 1980s and after 2006) and one increasing period (from 1990 to 2006). With the derived AOD, a clear-sky model is then applied to quantify the role of aerosols in the variations in global radiation over China. The results show that aerosol direct effect cannot fully explain the decadal variations in the global radiation over China between 1980 and 2010, though it has a considerable effect on global radiation climatology. There are significant differences between the trends of clear-sky global radiation impacted by aerosols and those of all-sky global radiation impacted by aerosols and clouds, and the correlation coefficient for the comparison is very low. Therefore, the variations in all-sky global radiation over China are likely to be due to changes in cloud properties and to interactions between clouds and aerosols.

The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset with an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products, the water vapor, surface pressure and ozone from ERA5 reanalysis data, and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data was evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimate at 10 km scale were −11.5 W m−2, 113.5 W m−2, and 0.92, respectively. The error was clearly reduced when the data were upscaled to 90 km; RMSE decreased to 93.4 W m−2 and R increased to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The data set is available at https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

Background: In some medical applications (e.g., virtual surgery), standard human organ models are very important and useful. Now that real human body slice image sets have been collected by several countries, it is possible to obtain real standard organ models. Introduction: Understanding how to abandon the traditional model construction method of Photoshop sketching slice by slice and directly extracting 3D models from volume images has been an interesting and challenging issue. In this paper, a 3D color volume image matting method has been proposed to segment human body organ models. Methods: First, the scope of the known area will be expanded by means of propagation. Next, neighborhood sampling to find the best sampling for voxels in an unknown region will be performed and then the preliminary opacity using the sampling results will be calculated. Results: The final result will be obtained by applying local smoothing to the image. Conclusion: From the experimental results, it has been observed that our method is effective for real standard organ model extraction.