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Relationship between sea surface salinity and ocean circulation and climate change

Science China Earth Sciences 2019年第5期62卷 771-782页

作者： Yan DU Yuhong ZHANG Jiancheng SHI State Key Laboratory of Tropical Oceanography South China Sea Institute of Oceanology Chinese Academy of Sciences University of Chinese Academy of Sciences State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences

Based on Argo sea surface salinity(SSS) and the related precipitation(P), evaporation(E), and sea surface height data sets, the climatological annual mean and low-frequency variability in SSS in the global ocean and their relationship with ocean circulation and climate change were analyzed. Meanwhile, together with previous studies, a brief retrospect and prospect of seawater salinity were given in this work. Freshwater flux(E-P) dominated the mean pattern of SSS, while the dynamics of ocean circulation modulated the spatial structure and low-frequency variability in SSS in most regions. Under global warming, the trend in SSS indicated the intensification of the global hydrological cycle, and featured a decreasing trend at low and high latitudes and an increasing trend in subtropical regions. In the most recent two decades, global warming has slowed down, which is called the"global warming hiatus". The trend in SSS during this phase, which was different to that under global warming, mainly indicated the response of the ocean surface to the decadal and multi-decadal variability in the climate system, referring to the intensification of the Walker Circulation. The significant contrast of SSS trends between the western Pacific and the southeastern Indian Ocean suggested the importance of oceanic dynamics in the cross-basin interaction in recent decades. Ocean Rossby waves and the Indonesian Throughflow contributed to the freshening trend in SSS in the southeastern Indian Ocean, while the increasing trend in the southeastern Pacific and the decreasing trend in the northern Atlantic implied a long-term linear trend under global warming. In the future, higher resolution SSS data observed by satellites, together with Argo observations, will help to extend our knowledge on the dynamics of mesoscale eddies, regional oceanography, and climate change.

关键词： Sea surface salinity Ocean circulation Climate change multi-scale interaction

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CFD simulation of internal-loop airlift reactor using EMMS drag model

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Particuology 2015年第2期13卷 124-132页

作者： Tingting Xu Xuedong Jiang Ning Yang Jiahua Zhu State Key Laboratory of multi-Phase Complex Systems Institute of Process EngineeringChinese Academy of Sciences University of Chinese Academy of Sciences Department of Chemical Engineering Xi'an Jiaotong University School of Chemical Engineering Sichuan University

The simulation of internal-loop airlift reactors is challenging because complex meso-scale structures exist in different sections of the reactor, separated by the draft tube. This paper reports on the computational fluid dynamics （CFD） simulation of internal-loop airlift reactors using a new drag model derived from the dual-bubble-size （DBS） model, an extended energy-minimization multi-scale （EMMS） approach for gas-liquid flows. Compared with the traditional Schiller-Naumann （S-N） correlation, the new model improves the simulation of gas holdup in the riser and downcomer significantly. In particular, gas holdup and circulation of two-phase flow can be modeled successfully using the new model, whereas traditional drag models such as the S-N correlation show an absence of gas in the downcomer. The simulation demonstrates the advantage and potential of this new model for internal-loop airlift reactors.

关键词： Computational fluid dynamics Internal-loop Airlift multi-scale multiphase flow Hydrodynamics

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A Water/Land Segmentation Algorithm Based on an Improved Chan-Vese Model with Edge Constraints of Complex Wavelet Domain

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Chinese Journal of Electronics 2015年第2期24卷 361-365页

作者： MAO Chenglin WAN Shouhong YUE Lihua XIA Yu School of Computer Science and Technology University of Science and Technology of China

A novel model for segmentation of water/land in Synthetic aperture radar(SAR) images is presented. The proposed model calculates the global matrix of oriented gradient of histograms on wavelet subbands based on the multi-scale property, shift invariance and directional selectivity of Complex wavelet transform(CWT), then acquires edge information by thresholding the matrix. It improves the traditional Chan-vese(CV) model by adding the constraint of extracted edge information. A new water/land segmentation algorithm is then proposed based on the new model. The performance of proposed method is compared with some other existing algorithms and the experimental results confirm its effectiveness.

关键词： Water/land segmentation Complex wavelet transform multi-scale Orientation selectivity Edge information Chan-vese model

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A higher order lattice BGK model for simulating some nonlinear partial differential equations

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Science China(Physics,Mechanics & Astronomy) 2009年第7期52卷 1053-1061页

作者： LAI HuiLin MA ChangFeng School of Mathematics and Computer Science Fujian Normal UniversityFuzhou 350007China

In this paper, we consider a one-dimensional nonlinear partial differential equation that has the form ut + αuux + βunux - γuxx + δuxxx = F(u). A higher order lattice Bhatnager-Gross-Krook (BGK) model with an amending-function is proposed. With the Chapman-Enskog expansion, different kinds of nonlinear partial differential equations are recovered correctly from the continuous Boltzmann equation. The numerical results show that this method is very effective.

关键词： nonlinear partial differential equation lattice Boltzmann model multi-scale technique Taylor series expansion Chapman-Enskog expansion

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Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment

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Computers, Materials & Continua 2018年第9期56卷 501-515页

作者： Manyu Jin Tao Wang Zexuan Ji Xiaobo Shen School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing210094China School of Computer Science and Engineering Nanyang Technology University639798Singapore

Perceptual image quality assessment(IQA)is one of the most indispensable yet challenging problems in image processing and computer vision.It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation.To further improve the prediction accuracy for the distortion of color images,in this paper,we propose a novel effective and efficient IQA model,called perceptual gradient similarity deviation(PGSD).Based on the gradient magnitude similarity,we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient.The luminance and chrominance channels are both took into account to characterize the quality degradation caused by intensity and color distortions.Finally,a multi-scale strategy is utilized and pooled with different weights to incorporate image details at different resolutions.Experimental results on LIVE,CSIQ and TID2013 databases demonstrate the superior performances of the proposed algorithm.

关键词： Image quality assessment full reference perceptual gradient similarity multi-scale standard deviation pooling

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A two-scale approach for estimating forest aboveground biomass with optical remote sensing images in a subtropical forest of Nepal

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Journal of Forestry Research 2019年第6期30卷 2119-2136页

作者： Upama A.Koju Jiahua Zhang Shashish Maharjan Sha Zhang Yun Bai Dinesh B.I.P.Vijayakumar Fengmei Yao Key Laboratory of Digital Earth Sciences Institute of Remote Sensing and Digital EarthCASBeijing 100094People’s Republic of China University of Chinese Academy of Sciences Beijing 100094People’s Republic of China International Maize and Wheat Improvement Center Kathmandu 44600Nepal The Laboratory of Forest Inventory The National Institute of Geographic and Forest InformationNancyFrance

Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carbon and forest aboveground biomass(FAGB).Different levels of detail are needed to estimate FAGB at local,regional and national scales.multi-scale remote sensing analysis from high,medium and coarse spatial resolution data,along with field sampling,is one approach often used.However,the methods developed are still time consuming,expensive,and inconvenient for systematic monitoring,especially for developing countries,as they require vast numbers of field samples for upscaling.Here,we recommend a convenient two-scale approach to estimate FAGB that was tested in our study sites.The study was conducted in the Chitwan district of Nepal using GeoEye-1(0.5 m),Landsat(30 m)and Google Earth very high resolution(GEVHR)Quickbird(0.65 m)images.For the local scale(Kayerkhola watershed),tree crowns of the area were delineated by the object-based image analysis technique on GeoEye images.An overall accuracy of 83%was obtained in the delineation of tree canopy cover(TCC)per plot.A TCC vs.FAGB model was developed based on the TCC estimations from GeoEye and FAGB measurements from field sample plots.A coefficient of determination(R2)of 0.76 was obtained in the modelling,and a value of 0.83 was obtained in the validation of the model.To upscale FAGB to the entire district,open source GEVHR images were used as virtual field plots.We delineated their TCC values and then calculated FAGB based on a TCC versus FAGB model.Using the multivariate adaptive regression splines machine learning algorithm,we developed a model from the relationship between the FAGB of GEVHR virtual plots with predictor parameters from Landsat 8 bands and vegetation indices.The model was then used to extrapolate FAGB to the entire district.This approach considerably reduced the need for field data and commercial very high resolution imagery while achie

关键词： Forest aboveground biomass Google Earth imagery multi-scale remote sensing Virtual plot Optical imagery

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Upscaling in situ albedo for validation of coarse scale albedo product over heterogeneous surfaces

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International Journal of Digital Earth 2017年第6期10卷 604-622页

作者： Xiaodan Wu Qing Xiao Jianguang Wen Qiang Liu Dongqin You Baocheng Dou Yong Tang State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingPeople’s Republicof China College of Resourcesand Environment University of Chinese Academy of SciencesBeijingPeople’s Republic of China Joint Center for Global Change Studies BeijingPeople’s Republic of China College of Global Change and Earth System Science Beijing Normal UniversityBeijingPeople’s Republic of China

One of the essential steps for satellite albedo validation is upscaling in situ measurements to corresponding pixel scale over relatively heterogeneous land surfaces.Although the multi-scale validation strategy is applicable for heterogeneous surfaces,the calibration of the high-resolution imagery during upscaling process is never perfect,and thus the upscaling results suffer from errors.The regression-kriging(RK)technique can compensate the calibration part by applying kriging to upscale residuals and produce more accurate upscaling results.In this paper,in situ measurements and high spatial resolution albedo imagery combined with RK technique was proposed.This method is illustrated by upscaling surface albedo from in situ measurements scale to the coarse pixel scale in the core experimental area of HiWATER,where 17 WSN nodes were deployed at heterogeneous area.The upscaling results of this method were compared with the upscaling results from multi-scale strategy.The results show that the upscaling method based on in situ measurements and high-resolution imagery combined with RK technique can capture the spatial characteristics of surface albedo better.Further,an attempt was made to expand this method in time series.Finally,a preliminary validation of the Moderate Resolution Imaging Spectroradiometer albedo product was performed as the tentative application.

关键词： Upscaling albedo heterogeneous validation in situ multi-scale

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High-thermoelectric performance of TiO_(2-x)fabricated under high pressure at high temperatures

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Journal of Materiomics 2017年第4期3卷 286-292页

作者： Haiqiang Liu Hongan Ma Taichao Su Yuewen Zhang Bing Sun Binwu Liu Lingjiao Kong Baomin Liu Xiaopeng Jia State Key Laboratory of Superhard Materials Jilin UniversityChangchun 130012China School of Materials Science and Engineering Henan Polytechnic UniversityJiaozuo 454000China

We present the work about the initiative fabrication of multi-scale hierarchical TiO2-x by our strategy,combining high pressure and high temperature(HPHT)reactive sintering with appropriate ratio of coarse Ti to nanosized TiO_(2).Ubiquitous lattice defects engineering has also been achieved in our samples by HPHT.The thermoelectric performance was significantly enhanced,and rather low thermal conductivity(1.60 W m^(-1)K^(-1))for titanium oxide was reported here for TiO1.76.Correspondingly,a high dimensionless figure of merit(zT)up to 0.33 at 700℃was realized in it.As far as we know,this value is an enhancement of 43%of the ever best result about nonstoichiometric TiO_(2)and the result is also exciting for oxide thermoelectric materials.The moderate power factor,the significantly reduced thermal conductivity and the remarkable synergy between electrical properties and thermal conductivity are responsible for the excellent thermoelectric performance.We develop a facile strategy for preparing multi-scale hierarchical TiO_(2-x)and its superior ability to optimize thermoelectric performance has been demonstrated here.

关键词： High pressure High temperature multi-scale TiO_(2-x) Thermoelectric Integrated phonon scattering

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Using machine learning to predict habitat suitability of sloth bears at multiple spatial scales

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Ecological Processes 2021年第1期10卷 634-645页

作者： Tahir Ali Rather Sharad Kumar Jamal Ahmad Khan Department of Wildlife Sciences Aligarh Muslim UniversityAligarhUttar Pradesh 202002India The Corbett Foundation 81-88Atlanta BuildingNariman PointMumbaiMaharashtra 400021India

Background:Habitat resources occur across the range of spatial scales in the environment.The environmental resources are characterized by upper and lower limits,which define organisms’distribution in their communities.Animals respond to these resources at the optimal spatial scale.Therefore,multi-scale assessments are critical to identifying the correct spatial scale at which habitat resources are most influential in determining the specieshabitat relationships.This study used a machine learning algorithm random forest(RF),to evaluate the scaledependent habitat selection of sloth bears(Melursus ursinus)in and around Bandhavgarh Tiger Reserve,Madhya Pradesh,India.Results:We used 155 spatially rarified occurrences out of 248 occurrence records of sloth bears obtained from camera trap captures(n=36)and scats located(n=212)in the field.We calculated focal statistics for 13 habitat variables across ten spatial scales surrounding each presence-absence record of sloth bears.Large(>5000 m)and small(1000–2000 m)spatial scales were the most dominant scales at which sloth bears perceived the habitat features.Among the habitat covariates,farmlands and degraded forests were the essential patches associated with sloth bear occurrences,followed by sal and dry deciduous forests.The final habitat suitability model was highly accurate and had a very low out-of-bag(OOB)error rate.The high accuracy rate was also obtained using alternate validation matrices.Conclusions:Human-dominated landscapes are characterized by expanding human populations,changing landuse patterns,and increasing habitat fragmentation.Farmland and degraded habitats constitute~40%of the landform in the buffer zone of the reserve.One of the management implications may be identifying the highly suitable bear habitats in human-modified landscapes and integrating them with the existing conservation landscapes.

关键词： Bandhavgarh Melursus ursinus multi-scale Habitat selection Random forest Sloth bear Species distribution models

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Constructal optimization of twice Y-shaped assemblies of fins by taking maximum thermal resistance minimization as objective

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Science China(Technological Sciences) 2010年第10期53卷 2756-2764页

作者： XIE ZhiHui, CHEN LinGen & SUN FengRui Postgraduate School, Naval University of Engineering, Wuhan 430033, China Postgraduate School Naval University of Engineering Wuhan China

In this paper,constructal optimization of the twice Y-shaped assemblies of fins with six freedom degrees (characteristic parameters of geometry) is performed by employing finite element method and taking dimensionless maximum thermal resistance as a performance index,and the heat transfer performance of the twice Y-shaped assemblies of fins under various conditions with different freedom degrees are analyzed. The results show that the twice assemblies can improve the heat transfer performance of Y-shaped fin remarkably,and the minimum maximum thermal resistance of the twice Y-shaped assemblies of fins decreases by 36.37% compared with that of once Y-shaped assembly of fins. It is also proved again that the larger the number of freedom degrees for evolving is,the more perfect the system performance is. The effects of different characteristic parameters of geometry on the performance of the twice Y-shaped assemblies of fins are different,one should pay different attention to these parameters in practical engineering designs. The effects of two angles on the maximum thermal resistance are larger,but the optima of the two angles are robust. The effects of two height ratios on the maximum thermal resistance are more remarkable than those of two thickness ratios.

关键词： constructal theory fin multi-scale enhanced heat transfer generalized thermodynamic optimization

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