High-resolution neutronics model for ^(238)Pu production in high-flux reactors

We proposed and compared three methods(filter burnup,single energy burnup,and burnup extremum analysis)to build a high-resolution neutronics model for 238Pu production in high-flux reactors.The filter burnup and single energy burnup methods have no theoretical approximation and can achieve a spectrum resolution of up to~1 eV,thereby constructing the importance curve and yield curve of the full energy range.The burnup extreme analysis method combines the importance and yield curves to consider the influence of irradiation time on production efficiency,thereby constructing extreme curves.The three curves,which quantify the transmutation rate of the nuclei in each energy region,are of physical significance because they have similar distributions.A high-resolution neutronics model for ^(238)Pu production was established based on these three curves,and its universality and feasibility were proven.The neutronics model can guide the neutron spectrum optimization and improve the yield of ^(238)Pu by up to 18.81%.The neutronics model revealed the law of nuclei transmutation in all energy regions with high spectrum resolution,thus providing theoretical support for high-flux reactor design and irradiation production of ^(238)Pu.

Multi-resolution image segmentation based on Gaussian mixture model

Mixture model based image segmentation method, which assumes that image pixels are independent and do not consider the position relationship between pixels, is not robust to noise and usually leads to misclassification. A new segmentation method, called multi-resolution Ganssian mixture model method, is proposed. First, an image pyramid is constructed and son-father link relationship is built between each level of pyramid. Then the mixture model segmentation method is applied to the top level. The segmentation result on the top level is passed top-down to the bottom level according to the son-father link relationship between levels. The proposed method considers not only local but also global information of image, it overcomes the effect of noise and can obtain better segmentation result. Experimental result demonstrates its effectiveness.

A Modeling-Based Radar Superresolution Approach

On the basis of modeling of multiple targets and radar returning signals, a new method for radar range superresolution is introduced in this paper. This method tums the resolution of multiple closely spaced targets into an identification of the target impulse response functions. The least-square (LS) method is then used to estimate impulse resoonse functions of the targets. The concept of radar range resolution probability is also introduced.It is shown from the simulation results that the new superresolution method is much efficient, and has advantages such as having a simple structure, as well as high resolution.

A comparison of two global ocean-ice coupled models with different horizontal resolutions

A global eddy-permitting ocean-ice coupled model with a horizontal resolution of 0.25° by 0.25° is estab- lished on the basis of Modular Ocean Model version 4 （MOM4） and Sea Ice Simulator （SIS）. Simulation results are compared with those of an intermediate resolution ocean-ice coupled model with a horizontal resolution of about 1° by 1°. The results show that the simulated ocean temperature, ocean current and sea ice concentration from the eddy-permitting model are better than those from the intermediate resolu- tion model. However, both the two models have the common problem of ocean general circulation models （OGCMs） that the majority of the simulated summer sea surface temperature （SST） is too warm while the majority of the simulated subsurface summer temperature is too cold. Further numerical experiments show that this problem can be alleviated by incorporating the non-breaking surface wave-induced vertical mixing into the vertical mixing scheme for both eddy-permitting and intermediate resolution models.

HIGH RESOLUTION PARAMETRIC MODELLING FOR TWO-DIMENSIONAL RADAR TARGET USING PRONY ALGORITHM

On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.

Evaluating performance dependency of a geomorphologic instantaneous unit hydrograph-based hydrological model on DEM resolution

The digital elevation model(DEM)is a type of model that has been widely used in terrain analysis and hydrological modeling.DEM resolution influences the hydrological and geomorphologic features of delineated catchments and consequently affects hydrological simulations.This study investigated the impacts of DEM resolution on the performance of the XAJ-GIUH hydrological model,a model coupling the widely used Xinanjiang(XAJ)hydrological model with the geomorphologic instantaneous unit hydrograph(GIUH),in flood simulations in small and medium-sized catchments.To test the model performance,the model parameters were calibrated at a fine DEM resolution(30 m)and then directly transferred to the simulation runs using coarser DEMs.Afterwards,model recalibration was conducted at coarser DEM resolutions.In the simulation runs with the model parameters calibrated at the 30-m resolution,the DEM resolution slightly affected the overall shape of the simulated flood hydrographs but presented a greater impact on the simulated peak discharges in the two study catchments.The XAJ-GIUH model consistently underestimated the peak discharges when the DEM resolution became coarser.The qualified ratio of peak simulations decreased by 35%when the DEM resolution changed from 30 m to 600 m.However,model recalibration produced comparable model per-formances when DEMs with different resolutions were used.This study showed that the impact of DEM resolution on model performance can be mitigated by model recalibration to some extent,if the DEM resolution is not too coarse.

Modeling Arctic Intermediate Water: The effects of Neptune parameterization and horizontal resolution

Arctic Intermediate Water （AIW）, advected from the North Atlantic Ocean, has a potential influence on climate in the Arctic region, but is poorly simulated in coarse resolution models. In this study, a coupled ice-ocean model is used to investigate features of AIW by conducting two sensitivity experiments based on Neptune parameterization and horizontal resolution. The re- suits show that both experiments improve the modeling of temperature profiles in the western Eurasian Basin, mainly as a result of more realistic volume and heat transport through the Fram Strait. Topographical flows are well reproduced using Neptune parame- terization or a finer horizontal resolution. In the eddy-permitting model with relatively higher resolution, the velocity field is more realistic than in the Neptune parameterization model, and complex inflow and outflow belts of barotropic structure are well repro- duced. The findings of this study suggest that increased model resolution, as provided by an eddy-resolving model, is needed to reproduce realistic circulation and thermohaline structure in the Arctic, since the Rossby radius of deformation is only several kilometers in the Arctic Ocean. This paper focuses on the external heat input rather than internal mixing process, and obtains a conclusion that the heat input from the Fram Strait is a main factor to reproduce AIW in the Eurasian Basin successfully, at least for the western part.

A High Resolution Nonhydrostatic Tropical Atmospheric Model and Its Performance

A high resolution nonhydrostatic tropical atmospheric model is developed by using a ready-made regional atmospheric modeling system. The motivation is to investigate the convective activities associated with the tropical intraseasonal oscillation (ISO) through a cloud resolving calculation. Due to limitations in computing resources, a

On the Importance of High-Resolution in Large-Scale Ocean Models

Eddying global ocean models are now routinely used for ocean prediction,and the value-added of a better representation of the observed ocean variability and western boundary currents at that resolution is currently being evaluated in climate models.This overview article begins with a brief summary of the impact on ocean model biases of resolving eddies in several global ocean-sea ice numerical simulations.Then,a series of North and Equatorial Atlantic configurations are used to show that an increase of the horizontal resolution from eddy-resolving to submesoscale-enabled together with the inclusion of high-resolution bathymetry and tides significantly improve the models’abilities to represent the observed ocean variability and western boundary currents.However,the computational cost of these simulations is extremely large,and for these simulations to become routine,close collaborations with computer scientists are essential to ensure that numerical codes can take full advantage of the latest computing architecture.

The ‘Two oceans and one sea' extended range numerical prediction system with an ultra-high resolution atmosphere-ocean-land regional coupled model

The‘Two Oceans and One Sea’area(West Pacific,Indian Ocean,and South China Sea;15°S–60°N,39°–178°E)is a core strategic area for the‘21st Century Maritime Silk Road’project,as well as national defense.With the increasing demand for disaster prevention and mitigation,the importance of 10–30-day extended range prediction,between the conventional short-term(around seven days)and the climate scale(longer than one month),is apparent.However,marine extended range prediction is still a‘blank point’in China,making the early warning of marine disasters almost impossible.Here,the authors introduce a recently launched Chinese national project on a numerical forecasting system for extended range prediction in the‘Two Oceans and One Sea’area based on a regional ultra-high resolution multi-layer coupled model,including the scientific aims,technical scheme,innovation,and expected achievements.The completion of this prediction system is of considerable significance for the economic development and national security of China.

CROSS-RANGE RESOLUTION OF SYNTHETIC APERTURE RADAR BASED ON DIVING MODEL

This paper concentrates on the cross-range resolution of Synthetic Aperture Radar(SAR) based on diving model.In comparison to the azimuth resolution,the cross-range resolution can manifest the two-dimensional resolution ability of the imaging sensor SAR correctly.The diving model of SAR is an extended model from the conventional stripmap model,and the cross-range resolution expression is deduced from the equivalent linear frequency modulation pulses' compression.This expression points out that only the cross-range velocity component of the horizontal velocity contributes to the cross-range resolution.Also the cross-range resolution expressions and the performance of the conventional stripmap operation,squint side-look operation and beam circular-scanning operation are discussed.The cross-range resolution expression based on diving model will provide more general and more accurate reference.

Analysis of the Resolution of Crime Using Predictive Modeling

There has been evidence of crime in the US since colonization. In this article, we analyze the crime statistics of San Francisco and its resolution of crime recorded from January to September of the year 2018. We define resolution of crime as a target variable and study its relationship with other variables. We make several classification models to predict resolution of crime using several data mining techniques and suggest the best model for predicting resolution.

Improved Tropical Cyclone Forecasts with Increased Vertical Resolution in the TRAMS Model

The numerical simulation of typhoons has been found to be very sensitive to the vertical resolution of the model.During the updating of the TRAMS model from version 1.0 to 3.0,the horizontal resolution has been increased from 36 km to 9 km,while the vertical layer number only increased from 55 to 65 layers.The lack of high vertical resolution limits the performance of the TRAMS model in typhoon forecasting to a certain extent.In order to study the potential improvement of typhoon forecasting by increasing the vertical resolution,this paper increases the vertical resolution of the TRAMS model from 65 to 125 layers for the first time for a comparative simulation test.The results of the case study with Typhoon Hato(2017)show that the model with high vertical resolution can significantly enhance the warm structure caused by water vapor flux convergence and vertical transport,thus accurately simulating the rapid strengthening process of the typhoon.Meanwhile,the model with 125-layer vertical resolution can simulate the asymmetric structural characteristics of the wind field,which are closer to the observations and can help to reduce the bias in typhoon track forecasting.The improvement of vertical resolution is also trialed by using the batch test results of several landfalling typhoons in 2016-2017.The experimental results show that the typhoon forecast of the model becomes consistent with the observations only when the number of vertical layers of the model increases to about 125 layers,which in turn causes a large computational burden.In the next step,we will try to solve the computational burden problem caused by ultra-high vertical resolution with the top boundary nesting technique,and realize the application of high vertical resolution in the actual operation of the TRAMS model.

Equality Testing for Soil Grid Unit Resolutions to Polygon Unit Scales with DNDC Modeling of Regional SOC Pools

Matching soil grid unit resolutions with polygon unit map scales is important to minimize the uncertainty of regional soil organic carbon(SOC) pool simulation due to their strong influences on the modeling.A series of soil grid units at varying cell sizes was derived from soil polygon units at six map scales,namely,1:50 000(C5),1:200 000(D2),1:500 000(P5),1:1 000 000(N1),1:4 000 000(N4) and 1:14 000 000(N14),in the Taihu Region of China.Both soil unit formats were used for regional SOC pool simulation with a De Nitrification-DeC omposition(DNDC) process-based model,which spans the time period from 1982 to 2000 at the six map scales.Four indices,namely,soil type number(STN),area(AREA),average SOC density(ASOCD) and total SOC stocks(SOCS) of surface paddy soils that were simulated by the DNDC,were distinguished from all these soil polygon and grid units.Subjecting to the four index values(IV) from the parent polygon units,the variations in an index value(VIV,%) from the grid units were used to assess its dataset accuracy and redundancy,which reflects the uncertainty in the simulation of SOC pools.Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pools,matching their respective soil polygon unit map scales.With these optimal raster resolutions,the soil grid units datasets can have the same accuracy as their parent polygon units datasets without any redundancy,when VIV < 1% was assumed to be a criterion for all four indices.A quadratic curve regression model,namely,y = – 0.80 × 10^(–6)x^2 + 0.0228 x + 0.0211(R^2 = 0.9994,P < 0.05),and a power function model R? = 10.394?^(0.2153)(R^2 = 0.9759,P < 0.05) were revealed,which describe the relationship between the optimal soil grid unit resolution(y,km) and soil polygon unit map scale(1:10 000x),the ratio(R?,%) of the optimal soil grid size to average polygon patch size(?,km^2) and the ?,with the highest R^2 among different mathematical regressions,respectively.This knowledge may facilitate the grid partitioning of regions during the investigation and simulation of SOC pool dynamics at a certain map scale,and be referenced to other landscape polygon patches' mesh partition.

IMPACT OF VERTICAL RESOLUTION, MODEL TOP AND DATA ASSIMILATION ON WEATHER FORECASTING——A CASE STUDY

The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top,refining the vertical resolution,and the assimilation of operationally available observations,including conventional and satellite observations,on continental U.S.winter short-range weather forecasting,were investigated in this study.The initial and predicted wind and temperature profiles were analyzed against conventional observations.Generally,the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used.Negative impacts were also observed in both the initial wind and temperature profiles,over the lower troposphere.Different from the results by only raising the model top,the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used.Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill.The major improvements caused by raising the model top with refined vertical resolution,as well as those caused by data assimilation,were in both cases located in the tropopause and lower stratosphere.Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature.These negative impacts were related to the uncertainties caused by more stratospheric information,as well as to some physical processes.A case study shows that when we raise the model top,put more vertical layers in stratosphere and apply data assimilation,the precipitation scores can be slightly improved.However,more analysis is needed due to uncertainties brought by data assimilation.

Modeling Arctic Boundary Layer Cloud Streets at Grey-zone Resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds,we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiaġvik(formerly Barrow),Alaska,on 2 May 2013 and were observed by MODIS(the Moderate Resolution Imaging Spectroradiometer).The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain.We investigated the model-simulated mesoscale environment,horizontal and vertical cloud structures,boundary layer stability,and cloud properties,all of which were subsequently used to interpret the observed roll-cloud case.Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer.The clouds were stratiform-like in the mesoscale domain,but as the model resolution increased,roll-like structures,aligned along the wind field,appeared with ever smaller wavelengths.A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing.With fixed model grid spacing at 0.333 km,changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment,a stronger vertical water vapor gradient below the cloud layers,and the wavelengths of the rolls decreased slightly.In this study,only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Application of WRF 3DVar to a high-resolution model over Beijing area

To improve the weather forecasting over the Beijing area for the 2008 Olympic Games,a triple-nested(27/9/3km) WRFVar/WRF system with 3-h update cycle was established.Experiments have been done for a convective event that occurred on August 1,2006.The results showed that the high-resolution rapid update cycle gave a good precipitation forecast;the tunings of background error statistics(BES) and observation-error statistics in WRFVar improved the skill of the precipitation forecast;the BES for the fine domain(3 km) obtained by interpolation from its parent domain(9 km) can be used in 3 km WRFVar as a reasonable approximation.The user can now save a great deal of work related to the derivation of the fine mesh BES from the forecast over a period of time;the rapid update cycle with 3-h frequency has satisfied the forecast,and the update cycle with 1-h frequency was not necessary.

Effect of Temporal Resolution of NDVI on Potential Evapotranspiration Estimation and Hydrological Model Performance

Normalized difference vegetation index (NDVI) data, obtained from remote sensing information, are essential in the Shuttleworth-Wallace (S-W) model for estimation of evapotranspiration. In order to study the effect of temporal resolution of NDVI on potential evapotranspiration (PET) estimation and hydrological model performance, monthly and 10-day NDVI data set were used to estimate potential evapotranspiration from January 1985 to December 1987 in Huangnizhuang catchment, Anhui Province, China. The differences of the two calculation results were analyzed and used to drive the block-wise use of the TOPMODEL with the Muskingum-Cunge routing (BTOPMC) model to test the effect on model performance. The results show that both annual and monthly PETs estimated by 10-day NDVI are lower than those estimated by monthly NDVI. Annual PET from the vegetation root zone (PETr) lowers 9.77%-13.64% and monthly PETr lowers 3.28%-17.44% in the whole basin. PET from the vegetation interception (PETi) shows the same trend as PETr. In addition, temporal resolution of NDVI has more effect on PETr in summer and on PETi in winter. The correlation between PETr as estimated by 10-day NDVI and pan measurement (R2= 0.835) is better than that between monthly NDVI and pan measurement (R2 = 0.775). The two potential evapotranspiration estimates were used to drive the BTOPMC model and calibrate parameters, and model performance was found to be similar. In summary, the effect of temporal resolution of NDVI on potential evapotranspiration estimation is significant, but trivial on hydrological model performance.

WRF Simulations of Extreme Rainfall over Uganda’s Lake Victoria Basin: Sensitivity to Parameterization, Model Resolution and Domain Size

Rainfall extremes have strong connotations to socio-economic activities and human well-being in Uganda’s Lake Victoria Basin (LVB). Reliable prediction and dissemination of extreme rainfall events are therefore of paramount importance to the region’s development agenda. The main objective of this study was to contribute to the prediction of rainfall extremes over this region using a numerical modelling approach. The Weather Research and Forecasting (WRF) model was used to simulate a 20-day period of extremely heavy rainfall that was observed in the March to May season of 2008. The underlying interest was to investigate the performance of different combinations of cumulus and microphysical parameterization along with the model grid resolution and domain size. The model output was validated against rainfall observations from the Tropical Rainfall Measuring Mission (TRMM) using 5 metrics;the rainfall distribution, root mean square error, mean error, probability of detection and false alarm ratio. The results showed that the model was able to simulate extreme rainfall and the most satisfactory skill was obtained with a model setup using the Grell 3D cumulus scheme combined with the SBU_YLin microphysical scheme. This study concludes that the WRF model can be used for simulating extreme rainfall over western LVB. In the other 2 regions, central and eastern LVB, its performance is limited by failure to simulate nocturnal rainfall. Furthermore, increasing the model grid resolution showed good potential for improving the model simulation especially when a large domain is used.

A wavelet-based super-resolution method for multi-slice MRI

In multi-slice magnetic resonance imaging (MRI), the resolution in the slice direction is usually reduced to allow faster acquisition times and to reduce the amount of noise in each 2D slice. To address this issue, a number of super resolution (SR) methods have been proposed to improve the resolution of 3D MRI volumes. Most of the methods involve the use of prior models of the MRI data as regularization terms in an ill-conditioned inverse problem. The use of user-defined parameters produces better results for these approaches but an inappropriate choice may reduce the overall performance of the algorithm. In this paper, we present a wavelet domain SR method which uses a Gaussian scale mixture (GSM) model in a sparseness constraint to regularize the ill-posed SR inverse problem. The proposed approach also makes use of an extension of the Dual Tree Complex Wavelet Transform to provide the ability to analyze the wavelet coefficients with sub-level precision. Our results show that the 3D MRI volumes reconstructed using this approach have quality superior to volumes produced by the best previously proposed approaches.