The environmental analysis and site selection of mussel and large yellow croaker aquaculture areas based on high resolution remote sensing

Mussel aquaculture and large yellow croaker aquaculture areas and their environmental characteristics in Zhoushan were analyzed using satellite data and in-situ surveys.A new two-step remote sensing method was proposed and applied to determine the basic environmental characteristics of the best mussel and large yellow croaker aquaculture areas.This methodology includes the first step of extraction of the location distribution and the second step of the extraction of internal environmental factors.The fishery ranching index(FRI1,FRI2)was established to extract the mussel and the large yellow croaker aquaculture area in Zhoushan,using Gaofen-1(GF-1)and Gaofen-6(GF-6)satellite data with a special resolution of 2 m.In the second step,the environmental factors such as sea surface temperature(SST),chlorophyll a(Chl-a)concentration,current and tide,suspended sediment concentration(SSC)in mussel aquaculture area and large yellow croaker aquaculture area were extracted and analyzed in detail.The results show the following three points.(1)For the extraction of the mussel aquaculture area,FRI1 and FRI2 are complementary,and the combination of FRI1 and FRI2 is suitable to extract the mussel aquaculture area.As for the large yellow croaker aquaculture area extraction,FRI2 is suitable.(2)Mussel aquaculture and the large yellow croaker aquaculture area in Zhoushan are mainly located on the side near the islands that are away from the eastern open waters.The water environment factor template suitable for mussel and large yellow croaker aquaculture was determined.(3)This two-step remote sensing method can be used for the preliminary screening of potential site selection for the mussels and large yellow croaker aquaculture area in the future.the fishery ranching index(FRI1,FRI2)in this paper can be applied to extract the mussel and large yellow croaker aquaculture areas in coastal waters around the world.

High-Resolution Remote Sensing Imagery for the Recognition of Traditional Villages

Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.

Flexible,high-density,laminated ECoG electrode array for high spatiotemporal resolution foci diagnostic localization of refractory epilepsy

High spatiotemporal resolution brain electrical signals are critical for basic neuroscience research and high-precision focus diagnostic localization,as the spatial scale of some pathologic signals is at the submillimeter or micrometer level.This entails connecting hundreds or thousands of electrode wires on a limited surface.This study reported a class of flexible,ultrathin,highdensity electrocorticogram(ECoG)electrode arrays.The challenge of a large number of wiring arrangements was overcome by a laminated structure design and processing technology improvement.The flexible,ultrathin,high-density ECoG electrode array was conformably attached to the cortex for reliable,high spatial resolution electrophysiologic recordings.The minimum spacing between electrodes was 15μm,comparable to the diameter of a single neuron.Eight hundred electrodes were prepared with an electrode density of 4444 mm^(-2).In focal epilepsy surgery,the flexible,high-density,laminated ECoG electrode array with 36 electrodes was applied to collect epileptic spike waves inrabbits,improving the positioning accuracy of epilepsy lesions from the centimeter to the submillimeter level.The flexible,high-density,laminated ECoG electrode array has potential clinical applications in intractable epilepsy and other neurologic diseases requiring high-precision electroencephalogram acquisition.

Data processing of the Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system and application to South China Sea data

The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.

The application of very high resolution satellite image in urban vegetation cover investigation:a case study of Xiamen City

With the technological improvements of satellite sensors, we will acquire more information about the earth so that we have reached a new application epoch of observation on earth environmental change and cartography. But with the enhancement of spatial resolution, some questions have arisen in the application of using traditional image processing and classification methods. Aiming for such questions, we studied the application of IKONOS very high resolution image (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the difference between the very high resolution image and traditional low spatial resolution image at classification, information abstraction etc. It is an advantageous test for the large-scale application of very high resolution data in the future.

Level study on fractal characteristics of tidal creeks and information of seashell habitats in the Gaizhou Beach based on high-resolution satellite images

The fractal characteristics of tidal creeks in the Gaizhou Beach are analyzed based on high-resolution images fusionof Landsat TM and ERS2, and then the graphic models and characteristics of converse information tree of tidalcreeks in the Gaizhou Beach are established. A calculation model is established based on the above results, and at thesame time, quantitative calculation of the evolution characteristics and the diversity between the northern and thesouthern parts of the Gaizhou Beach is carried out. By the supervised classification of these images, distribution andareas of high tidal flats, middle tidal flats and low tidal flats in the Gaizhou Beach are studied quantitatively, and imagecharactistics of seashell habitats in the Gaizhou Beach and the correlation between mudflat distribution and seashellhabitats are studied. At last, the engineering problems in the Gaizhou Beach are discussed.

High Resolution Computed Tomography Scan Findings of Chest among Hospitalized COVID-19 Patients at a Dedicated Hospital in Dhaka City during the First Wave of Pandemic

Background: The use of chest imaging in COVID-19 can be especially useful for patients with moderate to severe symptoms or comorbidities. Objective: This study aimed to demonstrate the high resolution computed tomography (CT) findings observed among the coronavirus disease 2019 (COVID-19) patients presented with pneumonia and to reveal the most frequent infiltration and distribution patterns of the disease. Methodology: This was a retrospective study. This study was performed in the Department of Radiology & Imaging at Kurmitola General Hospital, Dhaka, Bangladesh. This was the first dedicated COVID-19 hospital with a bed capacity of 500 and well-equipped ICU facilities. The recorded HRCT scan data were collected in the period from April 2020 up to May 2020 during the first wave of COVID-19 in Bangladesh. As this was a retrospective study, verbal or written consent was not obtained from all potential participants or guardians. The available demographic data as well as the medical history of all data were collected and thoroughly reviewed from the record book. These patients were RT-PCR confirmed cases of COVID-19 patients presented with pneumonia and were admitted to Kurmitola General Hospital, Dhaka, Bangladesh. All these patients underwent HRCT scans of the chest. Result: A total number of 155 COVID-19 patients with HRCT scan were evaluated. The mean age with SD of the study population was 58.03 ± 14.08 years with the range of 22 to 97 years. The male and female ratio was 2.04:1. Fibrosis of the lungs and thickening of pleura were found in 38 (24.5%) cases and 33 (21.3%) cases respectively. The involvement of both lungs was found in 32 (20.6%) cases. The presence of pneumonitis and bronchiectasis were detected in 77 (49.7%) cases and 5 (3.2%) cases respectively. Left-sided mild pleural effusion was also noted in 6 (3.9%) cases. Ground glass opacity was found in different forms. The most common form was the presence of only ground glass opacities which was 63 (40.6%) cases. Bilateral ground-glass opacities were detected in 63 (40.6%) cases. Conclusion: In conclusion, HRCT scan of the chest shows the bilateral ground-glass opacities and fibrosis of the lungs with pneumonitis in most of the COVID-19 hospital admitted patients.

Structural characteristics and tectonic division of the Zambezi Delta basin in the offshore East Africa:evidences from gravity and seismic data

The Zambezi Delta basin is a passive marginal basin located on the East African coast that has good oil and gas exploration potential.Due to the special geological evolutionary background of the Beira High in the Zambezi Delta basin,it has a low gravity anomaly,and the existing seismic survey lines do not cover the whole basin;therefore,it is difficult to interpret the structural characteristics of the whole basin based solely on gravity or seismic data.Based on satellite altimetry gravity anomaly data,this study infers the distribution characteristics of faults in the Zambezi Delta basin by using the normalized vertical derivative of the total horizontal derivative(NVDR-THDR)technique.Then,constrained by seismic data,the gravity anomaly at the Moho interface is extracted by using the fast forward method of the double-interface model of the gravity anomaly,and this anomaly is then removed from the Bouguer gravity anomaly to obtain the sedimentary layer gravity anomaly.The thickness of the sedimentary strata is obtained by inversing the sedimentary basement depth of the whole basin.Then,uplifts and depressions are divided based on a sedimentary layer thickness of 3 km.This research demonstrates that the Zambezi Delta basin mainly features nearly SN-trending and NE-trending faults and that these faults exhibit east-west partitioning.The nearly SN-trending strike-slip faults controlled the sedimentary development of the basin,and the NE-trending tensile faults may have acted as migration channels for oil,gas and magma.The“overcompensation”effect of the Moho interface gravity anomaly on the gravity anomaly of the sedimentary layer is caused by the depression of the Moho interface beneath the Beira High,which results in a low gravity anomaly value for the Beira High.The pattern of uplifts and depressions trends NE and has the structural characteristics of east-west blocks.

Improved spatiotemporal resolution of anti-scattering super-resolution label-free microscopy via synthetic wave 3D metalens imaging

Super-resolution(SR)microscopy has dramatically enhanced our understanding of biological processes.However,scattering media in thick specimens severely limits the spatial resolution,often rendering the images unclear or indistinguishable.Additionally,live-cell imaging faces challenges in achieving high temporal resolution for fast-moving subcellular structures.Here,we present the principles of a synthetic wave microscopy(SWM)to extract three-dimensional information from thick unlabeled specimens,where photobleaching and phototoxicity are avoided.SWM exploits multiple-wave interferometry to reveal the specimen’s phase information in the area of interest,which is not affected by the scattering media in the optical path.SWM achieves~0.42λ/NA resolution at an imaging speed of up to 106 pixels/s.SWM proves better temporal resolution and sensitivity than the most conventional microscopes currently available while maintaining exceptional SR and anti-scattering capabilities.Penetrating through the scattering media is challenging for conventional imaging techniques.Remarkably,SWM retains its efficacy even in conditions of low signal-to-noise ratios.It facilitates the visualization of dynamic subcellular structures in live cells,encompassing tubular endoplasmic reticulum(ER),lipid droplets,mitochondria,and lysosomes.

Earthquake-triggered landslide interpretation model of high resolution remote sensing imageries based on bag of visual word

Traditional visual interpretation is often inefficient due to its excessively workload professional knowledge and strong subjectivity.Therefore,building an automatic interpretation model on high spatial resolution remote sensing images is the key to the quick and efficient interpretation of earthquake-triggered landslides.Aiming at addressing this problem,a landslide interpretation model of high-resolution images based on bag of visual word(BoVW)feature was proposed.The high-resolution images were pre-processed,and then BoVW feature and support vector machine(SVM)was adopted to establish an automatic landslide interpretation model.This model was further compared with the currently widely used Histogram of Oriented Gradient(HoG)feature extraction model.In order to test the effectiveness of the method,typical landslide images were selected to construct a landslide sample library,which was subsequently utilized as the foundation for conducting an experimental study.The results show that the accuracy of landslide extraction using this method reaches as high as 89%,indicating that the method can be used for the automatic interpretation of landslides in disaster-prone areas,and has high practical value for regional disaster prevention and damage reduction.

A Cloud Framework for High Spatial Resolution Soil Moisture Mapping from Radar and Optical Satellite Imageries

Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.

Perspective of Chinese GF-1 high-resolution satellite data in agricultural remote sensing monitoring

High-resolution satellite data have been playing an important role in agricultural remote sensing monitoring. However, the major data sources of high-resolution images are not owned by China. The cost of large scale use of high resolution imagery data becomes prohibitive. In pace of the launch of the Chinese ＂High Resolution Earth Observation Systems＂, China is able to receive superb high-resolution remotely sensed images （GF series） that equalizes or even surpasses foreign similar satellites in respect of spatial resolution, scanning width and revisit period. This paper provides a perspective of using high resolution remote sensing data from satellite GF-1 for agriculture monitoring. It also assesses the applicability of GF-1 data for agricultural monitoring, and identifies potential applications from regional to national scales. GF-1＇s high resolution （i.e., 2 m/8 m）, high revisit cycle （i.e., 4 days）, and its visible and near-infrared （VNIR） spectral bands enable a continuous, efficient and effective agricultural dynamics monitoring. Thus, it has gradually substituted the foreign data sources for mapping crop planting areas, monitoring crop growth, estimating crop yield, monitoring natural disasters, and supporting precision and facility agriculture in China agricultural remote sensing monitoring system （CHARMS）. However, it is still at the initial stage of GF-1 data application in agricultural remote sensing monitoring. Advanced algorithms for estimating agronomic parameters and soil quality with GF-1 data need to be further investigated, especially for improving the performance of remote sensing monitoring in the fragmented landscapes. In addition, the thematic product series in terms of land cover, crop allocation, crop growth and production are required to be developed in association with other data sources at multiple spatial scales. Despite the advantages, the issues such as low spectrum resolution and image distortion associated with high spatial resolution and wide swath width, might pose challenges for GF-1 data applications and need to be addressed in future agricultural monitoring.

Archean Basement and a Paleoproterozoic Collision Orogen in the Huoqiu Area at the Southeastern Margin of North China Craton: Evidence from Sensitive High Resolution Ion Micro-Probe U-Pb Zircon Geochronology

This paper reports sensitive high resolution ion micro-probe U-Pb zircon ages for the ＂Huoqiu Group＂ and granitoids of the Early Precambrian basement in the Huoqiu area, southeastern margin of the North China Craton. The ＂Huoqiu Group＂ is similar in rock association and metamorphism to the khondalite series, apart from it containing considerable amounts of banded iron formation. All detrital zircons from the ＂Huoqiu Group＂ meta-sedimentary rocks are 3.0 Ga and 2.75 Ga, without any 2.5 Ga and younger ones, as is commonly found in Paleoproterozoic khondalite series in other areas of the North China Craton. In the Huoqiu area, 2.75 Ga and 2.56 Ga granitoids have also been identified. This basement assemblage underwent strong metamorphism during the late Paleoproterozoic （-1.84 Ga） tectonothermal event that is widely developed in the North China Craton. Thus the formation time of the ＂Huoqiu Group＂ can be constrained between 2.75 and 1.84 Ga in terms of detrital and metamorphic zircon ages. It is considered, combined with regional data, that there may be a Paleoproterozoic collision orogen extending in a NWW-SEE direction to the southern margin of the North China Craton.

Quantizing and analyzing the feature information of coastal zone based on high-resolution remote sensing image

On the basis of realization of beach information and its differentiating of high-resolution remote sensing image on coastal zone, extracting objects are carried through RS multi-scale diagnostic analysis, and fast information extraction methods and key technologies are put forward. Meanwhile image segmentation methods are set forth for objects of coastal zone. And through the application of Otsu2D to the segmentation of water area and dock and the applying of Gabor filter to the separation and extraction of construction, some typical applications of high-resolution RS image are presented in the field of coastal zone surface objects＇ recognition. Quantizing high-resolution RS information on the coastal zone proved to be of great scientific and practical significance for coastal development and management.

Generation of high resolution sea surface temperature using multi-satellite data for operational oceanography

In the present article, we introduce a high resolution sea surface temperature （SST） product generated daily by Korea Institute of Ocean Science and Technology （KIOST）. The SST product is comprised of four sets of data including eight-hour and daily average SST data of I km resolution, and is based on the four infrared （IR） satellite SST data acquired by advanced very high resolution radiometer （AVHRR）, Moderate Resolution Imaging Spectroradiometer （MODIS）, Multifunctional Transport Satellites-2 （MTSAT-2） Imager and Meteorological Imager （MI）, two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2 （AMSR2）, and WindSAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation （OI） algorithm. The root-mean-square-errors （RMSEs） of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from Ianuary to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71~C and the bias value was -0.08~C. The largest RMSE and bias were 0.86 and -0.26~C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Iapan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60~C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature （GHRSST） product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System （KOOS） as an input parameter for data assimilation.

Retrieval of High Resolution Satellite Images Using Texture Features

In this research, a content-based image retrieval （CBIR） system for high resolution satellite images has been developed by using texture features. The proposed approach uses the local binary pattern （LBP） texture feature and a block based scheme. The query and database images are divided into equally sized blocks, from which LBP histograms are extracted. The block histograms are then compared by using the Chi-square distance. Experimental results show that the LBP representation provides a powerful tool for high resolution satellite images （HRSI） retrieval.

Integrating cross-sensor high spatial resolution satellite images to detect subtle forest vegetation change in the Purple Mountains,a national scenic spot in Nanjing,China

Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution remote sensing images can be used to detect subtle vegetation changes.The major objective of this study was to map and quantify forest vegetation changes in a national scenic location,the Purple Mountains of Nanjing,China,using multi-temporal cross-sensor high spatial resolution satellite images to identify the main drivers of the vegetation changes and provide a reference for sustainable management.We used Quickbird images acquired in 2004,IKONOS images acquired in 2009,and WorldView2 images acquired in 2015.Four pixel-based direct change detection methods including the normalized difference vegetation index difference method,multi-index integrated change analysis(MIICA),principal component analysis,and spectral gradient difference analysis were compared in terms of their change detection performances.Subsequently,the best pixel-based detection method in conjunction with object-oriented image analysis was used to extract subtle forest vegetation changes.An accuracy assessment using the stratified random sampling points was conducted to evaluate the performance of the change detection results.The results showed that the MIICA method was the best pixel-based change detection method.And the object-oriented MIICA with an overall accuracy of 0.907 and a kappa coefficient of 0.846 was superior to the pixel-based MIICA.From 2004 to 2009,areas of vegetation gain mainly occurred around the periphery of the study area,while areas of vegetation loss were observed in the interior and along the boundary of the study area due to construction activities,which contributed to 79%of the total area of vegetation loss.During 2009–2015,the greening initiatives around the construction areas increased the forest vegetation coverage,accounting for 84%of the total area of vegetation gain.In spite of this,vegetation loss occurred in the interior of the Purple Mountains due to infrastructure development that caused conversion from vegetation to impervious areas.We recommend that:(1)a local multi-agency team inspect and assess law enforcement regarding natural resource utilization;and(2)strengthen environmental awareness education.

High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization

In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary layer(PBL)physics using double nesting with large grid ratios(15:1 and 9:1).The sensitivity of the precipitation forecast was examined through three PBL schemes:the Yonsei University Scheme,the Mellor−Yamada−Nakanishi Niino Level 2.5(MYNN)scheme,and the Mellor−Yamada−Janjic scheme.The PBL effects on boundary layer structures,convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations.The results indicated that in single coarser grids(15 km and 9 km),the extreme rainfall amount was largely underestimated with all three PBL schemes.In the inner 1-km grid,the underestimated intensity was improved;however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain−Fritsch cumulus scheme,significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall.MYNN,with the weakest vertical mixing,produced the shallowest and most humid inversion layer with the lowest lifting condensation level,but stronger wind fields and upward motions from the top of the boundary layer to upper levels.These factors all facilitate the development of deep convection and moisture transport for intense precipitation,and result in its most realistic prediction of the primary rainfall peak.

High Resolution Mass Spectrometry for the Recognition and Structural Characterization of a New Antimicrobial Compound

Identification of novel specialized metabolites or bioactive compounds represents the main objective in the research field of natural product leads and drug discovery. Mass spectrometry (MS) provides a central tool to expedite and make more efficient the discovery and isolation phases, while minimizing the waste of resources on rediscovery of known compounds. MS contributes acutely to elucidation and identification of numerous species because it allows molecular mass and structural features determination. In particular, identification of the elemental composition of a precursor ion of interest by accurate mass measurement and investigation of dissociative processes undergone by the molecule, represent a worthy methodology to access the structure assignment. The aim of this study was to discover and identify novel antibacterial drugs from microbial source in a jungle of already known compounds. The focus of this paper is on the analytical strategy that permitted the disclosure of a new compound, otherwise confused with other substances. Emphasis is placed on the interpretation of the ESI-MS/MS fragmentation pattern that combined with high resolution mass determination, allowed step by step to properly deduce the exact molecular formula of an unknown component with a molecular weight higher than 1500 Daltons.

Computational Performance of the High-Resolution Atmospheric Model FAMIL

This paper describes the model speed and model In/Out (I/O) efficiency of the high-resolution atmospheric general circulation model FAMIL (Finite-volume Atmospheric Model of IAP/LASG) at the National Supercomputer Center in Tianjin, China, on its Tianhe-1A supercomputer platform. A series of three-model-day simulations were carried out with standard Aqua Planet Experiment (APE) designed within FAMIL to obtain the time stamp for the calculation of model speed, simulation cost, and model I/O efficiency. The results of the simulation demonstrate that FAMIL has remarkable scalability below 3456 and 6144 cores, and the lowest simulation costs are 1536 and 3456 cores for 12.5 km and 6.25 km resolutions, respectively. Furthermore, FAMIL has excellent I/O scalability and an efficiency of more than 80% on 6 I/Os and more than 99% on 1536 I/Os.