Kinetic models of natural gas combustion in an internal combustion engine

In this study, combustion of methane was simulated using four kinetic models of methane in CHEMKIN 4.1.1 for 0-D closed internal combustion （IC） engine reactor. Two detailed （GRIMECH3.0 ＆ UBC MECH2.0） and two reduced （One step ＆ Four steps） models were examined for various IC engine designs. The detailed models （GRIMECH3.0, ＆ UBC MECH2.0） and 4-step models successfully predicted the combustion while global model was unable to predict any combustion reaction. This study illustrated that the detailed model showed good concordances in the prediction of chamber pressure, temperature and major combustion species profiles. The detailed models also exhibited the capabilities to predict the pollutants formation in an IC engine while the reduced schemes showed failure in the prediction of pollutants emissions. Although, there are discrepancies among the profiles of four considered model, the detailed models （GRIMECH3.0 ＆ UBC MECH2.0） produced the acceptable agreement in the species prediction and formation of pollutants.

Nucleation of Supercooled Water by Neutrons: Latitude Dependence and Implications for Cloud Modelling

It has recently been shown that incident particles, neutrons, can initiate the freezing in a supercooled water volume. This new finding may have ramifications for the interpretation of both experimental data on the nucleation of laboratory samples of supercooled water and perhaps more importantly on the interpretation of ice nucleation involved in cloud physics. For example, if some fraction of the cloud nucleation previously attributed to dust, soot, or aerosols has been caused by cosmogenic neutrons, fresh consideration is required in the context of climate models. Moreover, as cosmogenic neutrons, most being muon-induced, have much greater flux at high latitudes, estimates of ice nucleates in these regions may be larger than required to accurately model cloud and condensation properties. This discrepancy has been pointed out in IPCC reports. Our paper discusses the connection between the new concept of neutrons nucleating supercooled water and the need for a new source of nucleation in high latitude clouds, ideally causing others to review current data, or to analyse future data with this idea in mind. .

A viscoelastic-plastic constitutive model with Mohr-Coulomb yielding criterion for sea ice dynamics

A new viscoelastic-plastic （VEP） constitutive model for sea ice dynamics was developed based on continuum mechanics. This model consists of four components： Kelvin-Vogit viscoelastic model, Mohr-Coulomb yielding criterion, associated normality flow rule for plastic rehololgy, and hydrostatic pressure. The numerical simulations for ice motion in an idealized rectangular basin were made using smoothed particle hydrodynamics （SPH） method, and compared with the analytical solution as well as those based on the modified viscous plastic（VP） model and static ice jam theory. These simulations show that the new VEP model can simulate ice dynamics accurately. The new constitutive model was further applied to simulate ice dynamics of the Bohai Sea and compared with the traditional VP, and modified VP models. The results of the VEP model are compared better with the satellite remote images, and the simulated ice conditions in the JZ20-2 oil platform area were more reasonable.

一种支持MDD的ICES-Modeling建模语言和建模工具

随着模型驱动体系结构的理论和技术的不断发展,模型已成为软件开发的核心元素。因此,支持模型驱动体系结构的建模语言和建模工具成为研究热点。本文提出一种支持模型驱动的软件开发的ICES-Modeling建模语言,该语言融合了现有的建模方法的一些思想,可以有效地描述领域内的概念,概念与概念之间的关系。还针对该建模语言,设计并开发了建模工具,该建模工具具有支持建模语言的定义,方便模型的理解,支持多角度建模等特点。

LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project

The datasets of two Ocean Model Intercomparison Project(OMIP)simulation experiments from the LASG/IAP Climate Ocean Model,version 3(LICOM3),forced by two different sets of atmospheric surface data,are described in this paper.The experiment forced by CORE-II(Co-ordinated Ocean–Ice Reference Experiments,Phase II)data(1948–2009)is called OMIP1,and that forced by JRA55-do(surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis)data(1958–2018)is called OMIP2.First,the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described.Second,the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation.We find that the mean states,interannual variabilities,and long-term linear trends can be reproduced well by the two experiments.The differences between the two datasets are also discussed.Finally,the usage of these data is described.These datasets are helpful toward understanding the origin system bias of the fully coupled model.

A coupled ice-ocean model for the Bohai SeaⅡ.Case study

The coupled ice- ocean model for the Bohai Sea is used for simulating the freezing, melting, and variation of ice cover and the heat bal- ance at the sea- ice, air- ice, and air- sea interfaces of the Bohai Sea during the entire winter in 1998￣1999 and 2000￣2001. The cou- pled model is forced by real time numerical weather prediction fields. The results show that the thermodynamic effects of atmosphere and ocean are very important for the evolvement of ice in the Bohai Sea, especially in the period of ice freezing and melting. Ocean heat flux plays a key role in the thermodynamic coupling. The simulation also presents the different thermodynamic features in the ice covered region and the marginal ice zone. Ice thickness, heat budget at the interface, and surface sea temperature, etc. between the two representative points are discussed.

A coupled ice-ocean model for the Bohai Sea Ⅰ. Study on model and parameter

According to the earlier international studies on the coupled iceocean model and the hydrology, meteorology, and icefeatures in the Bohai Sea, a coupled iceocean model is developed based on the National Marine EnvironmentForecast Centers (NMEFC) numerical forecasting ice model of the Bohai Sea and the Princeton ocean model (POM).In the coupled model, the transfer of momentum and heat between ocean and ice is two-way, and the change of icethickness and concentration depends on heat budget not only at the surface and bottom of ice, but also at the surfaceof open water between ices. The dynamic and thermodynamic coupling process is expatiated emphatically. Somethermodynamic parameters are discussed as well.

Design and Numerical Simulation of an Arctic Ocean Circulation and Thermodynamic Sea－Ice Model

In this paper, the first version of a new Arctic Ocean circulation and thermodynamic sea-ice model is presentedby the authors based on the framework of a twenty-layer World Oceanic general circulation model developed byZhang et al. in 1994. The model's domain covers the Arctic Ocean and Greenland-Norwegian Seas with the horizontal resolution of 200 km×200 km on a stereographic projection plane. In vertical, the model uses the Eta-coordinate(Sigma modified to have quasi-horizontal coordinate surfaces) and has ten unevenly-spaced layers to cover the deepest water column of 3000 m. Two 150-year integrations of coupling the ocean circulation model with the sea-icemodel have been performed with seasonally cyclic surface boundary conditions. The only difference between the tWoexperiments is in the model's geography. Some preliminary analyses of the experimental results have been done focused on the following aspects: (1) surface layer temperature, salinity and current; (2) the' Atlantic Layer'; (3)sea-ice cover and its seasonal variation. In comparison with the available observational data, these results are acceptable with reasonable accuracy.

Snow and sea ice thermodynamics in the Arctic:Model validation and sensitivity study against SHEBA data

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

Inter-comparisons of thermodynamic sea-ice modeling results using various parameterizations of radiative flux

Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.

Greenland Ice Sheet Contribution to Future Global Sea Level Rise based on CMIP5 Models

Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.

A hybrid Lagrangian-Eulerian numerical model for sea-ice dynamics

A hybrid Lagrangian - Eulerian （HLE） method is developed for sea ice dynamics, which combines the high computational efficiency of finite difference method （FDM） with the high numerical accuracy of smoothed particle hydrodynamics （SPH）. In this HLE model, the sea ice cover is represented by a group of Lagrangian ice particles with their own thicknesses and concentrations. These ice variables are interpolated to the Eularian gird nodes using the Gaussian interpolation function. The FDM is used to determine the ice velocities at Eulerian grid nodes, and the velocities of Lagrangian ice particles are interpolated from these grid velocities with the Gaussian function also. The thicknesses and concentrations of ice particles are determined based on their new locations. With the HLE numerical model, the ice ridging process in a rectangular basin is simulated, and the simulated results are validated with the analytical solution. This method is also applied to the simulation of sea ice dynamics in a vortex wind field. At last, this HLE model is applied to the Bohai Sea, and the simulated concentration, thickness and velocity match the satellite images and the field observed data well.

The in situ observation of modelled sea ice drift characteristics in the Bohai Sea

Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind speed, is of great significance to identify ice drift characteristics. A sea ice substitute, the so-called "modelled ice", which is made by polypropylene material with a density similar to Bohai Sea ice, is used to complete a free drift experiment in the open sea. The trajectories of isolated modelled ice, currents and wind in the Bohai Sea during non-frozen and frozen periods are obtained. The results show that the currents play a major role while the wind plays a minor role in the free drift of isolated modelled ice when the wind is mild in the Bohai Sea. The modelled ice drift is significantly affected by the ocean current and wind based on the ice–current–wind relationship established by a multiple linear regression. The modelled ice velocity calculated by the multiple linear regression is close to that of the in situ observation, the magnitude of the error between the calculated and observed ice velocities is less than12.05%, and the velocity direction error is less than 6.21°. Thus, the ice velocity can be estimated based on the observed current velocity and wind speed when the in situ observed ice velocity is missing. And the modelled ice of same thickness with a smaller density is more sensitive to the current velocity and the wind speed changes. In addition, the modelled ice drift characteristics are shown to be close to those of the real sea ice, which indicates that the modelled ice can be used as a good substitute of real ice for in situ observation of the free ice drift in the open sea, which helps solve time availability, safety and logistics problems related to in situ observation on real ice.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

Assessment of Arctic sea ice simulations in CMIP5 models using a synthetical skill scoring method

The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone.

Observations and modeling of the ice-ocean conditions in the coastal Chukchi and Beaufort Seas

The Chukchi and Beaufort Seas include several important hydrological features： inflow of the Pacific water, Alaska coast current （ ACC ）, the seasonal to perennial sea ice cover, and landfast ice ＇along the Alaskan coast. The dynamics of this coupled ice-ocean system is important for both regional scale oceanography and large-scale global climate change research. A mumber of moorings were deployed in the area by JAMSTEC since 1992, and the data revealed highly variable characteristics of the hydrological environment. A regional high-resolution coupled ice-ocean model of the Chukchi and Beaufort Seas was established to simulate the ice-ocean environment and unique seasonal landfast ice in the coastal Beaufort Sea. The model results reproduced the Beaufort gyre and the ACC. The depthaveraged annual mean ocean currents along the Beaufort Sea coast and shelf hreak compared well with data from four moored ADCPs, but the simulated velocity had smaller standard deviations, which indicate small-scale eddies were frequent in the region. The model resuits captured the sea,real variations of sea ice area as compared with remote sensing data, and the simulated sea ice velocity showed an ahnost stationary area along the Beaufort Sea coast that was similar to the observed landfast ice extent. It is the combined effects of the weak oceanic current near the coast, a prevailing wind with an onshore component, the opposite direction of the ocean current, and the blocking hy the coastline that make the Beaufort Sea coastal areas prone to the formation of landfast ice.

Comprehensive two-dimensional river ice model based on boundary-fitted coordinate transformation method

River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.

Mean Climatic Characteristics in High Northern Latitudes in an Ocean-Sea Ice-Atmosphere Coupled Model

Emphasizing the model's ability in mean climate reproduction in high northern latitudes, results from an ocean-sea ice-atmosphere coupled model are analyzed. It is shown that the coupled model can simulate the main characteristics of annual mean global sea surface temperature and sea level pressure well, but the extent of ice coverage produced in the Southern Hemisphere is not large enough. The main distribution characteristics of simulated sea level pressure and temperature at 850 hPa in high northern latitudes agree well with their counterparts in the NCEP reanalysis dataset, and the model can reproduce the Arctic Oscillation (AO) mode successfully. The simulated seasonal variation of sea ice in the Northern Hemisphere is rational and its main distribution features in winter agree well with those from observations. But the ice concentration in the sea ice edge area close to the Eurasian continent in the inner Arctic Ocean is much larger than the observation. There are significant interannual variation signals in the simulated sea ice concentration in winter in high northern latitudes and the most significant area lies in the Greenland Sea, followed by the Barents Sea. All of these features agree well with the results from observations.

An Arctic Sea Ice Simulation Using an Ocean-Ice Coupled Model

This paper evaluates the simulation of Arctic sea ice states using an ocean-ice coupled model that employs LASG/IAP(the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/the Institute of Atmospheric Physics) Climate Ocean Model(LICOM) and the sea-ice model from the Bergen Climate Model(BCM).It is shown that the coupled model can reasonably reproduce the major characteristics of the mean state,annual cycle,and interannual variability of the Arctic sea ice concentration.The coupled model also shows biases that were generally presented in other models,such as the underestimation of summer sea ice concentration and thickness as well as the unsatisfactory sea ice velocity.Sensitivity experiments indicate that the insufficient performance of the ocean model at high latitudes may be the main reason for the biases in the coupled model.The smoother and the fake "island",which had to be used due to the model's grid in the North Pole region,likely caused the ocean model's weak performance.Sea ice model thermodynamics are also responsible for the sea ice simulation biases.Therefore,both the thermodynamic module of the sea ice component and the model grid of the ocean component need to be further improved.

Improved sea-ice radiative processes in a global coupled climate model

The NASA Goddard Institute for Space Studies (GISS) coupled global climatemodel was used to investigate the sensitivity of sea ice to improved representations of sea-iceradiative processes: (1) a more sophisticated surface albedo scheme and (2) the penetration of solarradiation in sea ice. The results show that the large-scale sea-ice conditions are very sensitiveto the aforementioned parameteriza-tions. Although the more sophisticated surface albedo schemeproduces a more realistic seasonal cycle of the surface albedo as compared with the baselinesimulation, the resulting higher albedo relative to the baseline simulation generates much more andthicker ice in the arctic. The penetration of solar radiation in sea-ice itself tends to reduce theice cover and thickness in the entire arctic and the western antarctic, and increase the ice coverand thickness in the eastern antarctic. The combination of (1) and (2) significantly improves thesimulations of the average ice thickness and its spatial distribution in the arctic. The atmosphericresponses associated with sea-ice changes were also discussed. While improvements are seen,particularly of the ice thickness distribution, there are still some unrealistic aspects that willrequire further improvements to the sea-ice component.