Coupled bio-chemo-hydro-mechanical modeling of microbially induced calcite precipitation process considering biomass encapsulation using a micro-scale relationship

Geomaterials with inferior hydraulic and strength characteristics often need improvement to enhance their engineering behaviors.Traditional ground improvement techniques require enormous mechanical effort or synthetic chemicals.Sustainable stabilization technique such as microbially induced calcite precipitation(MICP)utilizes bacterial metabolic processes to precipitate cementitious calcium carbonate.The reactive transport of biochemical species in the soil mass initiates the precipitation of biocement during the MICP process.The precipitated biocement alters the hydro-mechanical performance of the soil mass.Usually,the flow,deformation,and transport phenomena regulate the biocementation technique via coupled bio-chemo-hydro-mechanical(BCHM)processes.Among all,one crucial phenomenon controlling the precipitation mechanism is the encapsulation of biomass by calcium carbonate.Biomass encapsulation can potentially reduce the biochemical reaction rate and decelerate biocementation.Laboratory examination of the encapsulation process demands a thorough analysis of associated coupled effects.Despite this,a numerical model can assist in capturing the coupled processes influencing encapsulation during the MICP treatment.However,most numerical models did not consider biochemical reaction rate kinetics accounting for the influence of bacterial encapsulation.Given this,the current study developed a coupled BCHM model to evaluate the effect of encapsulation on the precipitated calcite content using a micro-scale semiempirical relationship.Firstly,the developed BCHM model was verified and validated using numerical and experimental observations of soil column tests.Later,the encapsulation phenomenon was investigated in the soil columns of variable maximum calcite crystal sizes.The results depict altered reaction rates due to the encapsulation phenomenon and an observable change in the precipitated calcite content for each maximum crystal size.Furthermore,the permeability and deformation of the soil mass were affected by the simultaneous precipitation of calcium carbonate.Overall,the present study comprehended the influence of the encapsulation of bacteria on cement morphology-induced permeability,biocement-induced stresses and displacements.

Different El Niño Flavors and Associated Atmospheric Teleconnections as Simulated in a Hybrid Coupled Model

A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.

Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

Spatial Inhomogeneity of Atmospheric CO_(2) Concentration and Its Uncertainty in CMIP6 Earth System Models

This paper provides a systematic evaluation of the ability of 12 Earth System Models(ESMs)participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)to simulate the spatial inhomogeneity of the atmospheric carbon dioxide(CO_(2))concentration.The multi-model ensemble mean(MME)can reasonably simulate the increasing trend of CO_(2) concentration from 1850 to 2014,compared with the observation data from the Scripps CO_(2) Program and CMIP6 prescribed data,and improves upon the CMIP5 MME CO_(2) concentration(which is overestimated after 1950).The growth rate of CO_(2) concentration in the northern hemisphere(NH)is higher than that in the southern hemisphere(SH),with the highest growth rate in the mid-latitudes of the NH.The MME can also reasonably simulate the seasonal amplitude of CO_(2) concentration,which is larger in the NH than in the SH and grows in amplitude after the 1950s(especially in the NH).Although the results of the MME are reasonable,there is a large spread among ESMs,and the difference between the ESMs increases with time.The MME results show that regions with relatively large CO_(2) concentrations(such as northern Russia,eastern China,Southeast Asia,the eastern United States,northern South America,and southern Africa)have greater seasonal variability and also exhibit a larger inter-model spread.Compared with CMIP5,the CMIP6 MME simulates an average spatial distribution of CO_(2) concentration that is much closer to the site observations,but the CMIP6-inter-model spread is larger.The inter-model differences of the annual means and seasonal cycles of atmospheric CO_(2) concentration are both attributed to the differences in natural sources and sinks of CO_(2) between the simulations.

Modified Malkmus band model for clear-sky atmospheric transmittance calculation

The Malkmus band model has been widely used in remote sensing and climate studies. However, its accuracy is not high. To solve this problem, a modified Malkmus band model was proposed by introducing a correction item. The HITRAN (High-resolution TRANsmission) 2008 database and the atmospheric models provided by the Air Force Geophysics Laboratory (AFGL) were used to calculate the molecular transmittances. By fitting the calculated transmittances to those by MODTRAN (MODerate resolution atmospheric TRANsmission) package with the least-squares method, the fitting coefficients of the correction item were obtained under different atmosphere models. The experimental results show that the root mean square errors (RMSE) of the modified model are significantly less than that of the traditional Malkmus band model by 1-2 orders of magnitude. In addition, the modified method is suitable for different atmospheric models and molecules.

Recent Progress in Numerical Atmospheric Modeling in China

This review summarizes the scientific and technical progress in atmospheric modeling in China since 2011,including the dynamical core,model physics,data assimilation,ensemble forecasting,and model evaluation strategies.In terms of the dynamical core,important efforts have been made in the improvement of the existing model formulations and in exploring new modeling approaches that can better adapt to massively parallel computers and global multiscale modeling.With regard to model physics,various achievements in physical representations have been made,especially a trend toward scale-aware parameterization for accommodating the increase of model resolution.In the field of data assimilation,a 4D-Var system has been developed and is operationally used by the National Meteorological Center of China,and its performance is promising.Furthermore,ensemble forecasting has played a more important role in operational forecast systems and progressed in many fundamental techniques.Model evaluation strategies,including key performance metrics and standardized experimental protocols,have been proposed and widely applied to better understand the strengths and weaknesses of the systems,offering key routes for model improvement.The paper concludes with a concise summary of the status quo and a brief outlook in terms of future development.

The Performance of Atmospheric Component Model R42L9 of GOALS/LASG

This paper examines the performance of an atmospheric general circulation model (AGCM) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). It is a spectral model truncated at R42(2.8125°long×1.66°lat) resolution and with nine vertical levels, and referred to as R42L9/LASG hereafter. It is also the new version of atmospheric component model R15L9 of the global ocean-atmosphere-land system (GOALS/LASG). A 40-year simulation in which the model is forced with the climatological monthly mean sea surface temperature is compared with the 40-year (1958-97) U.S. National Center for Environmental Prediction (NGEP) global reanalysis and the 22-year (1979-2000) Xie-Arkin monthly precipitation climatology. The mean DJF and JJA geographical distributions of precipitation, sea level pressure, 500-hPa geopotential height, 850-hPa and 200-hPa zonal wind, and other fields averaged for the last 30-year integration of the R42L9 model are analyzed. Results show that the model reproduces well the observed basic patterns, particularly precipitation over the East Asian region. Comparing the new model with R15L9/LASG, the old version with coarse resolution (nearly 7.5°long×4.5°lat), shows an obvious improvement in the simulation of regional climate, especially precipitation. The weaknesses in simulation and future improvements of the model are also discussed.

Performance of a Reconfigured Atmospheric General Circulation Model at Low Resolution

Paleoclimate simulations usually require model runs over a very long time. The fast integration version of a state-of-the-art general circulation model （GCM）, which shares the same physical and dynamical processes but with reduced horizontal resolution and increased time step, is usually developed. In this study, we configure a fast version of an atmospheric GCM （AGCM）, the Grid Atmospheric Model of IAP/LASG （Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics）, at low resolution （GAMIL-L, hereafter）, and compare the simulation results with the NCEP/NCAR reanalysis and other data to examine its performance. GAMIL-L, which is derived from the original GAMIL, is a finite difference AGCM with 72 × 40 grids in longitude and latitude and 26 vertical levels. To validate the simulated climatology and variability, two runs were achieved. One was a 60-year control run with fixed climatological monthly sea surface temperature （SST） forcing, and the other was a 50-yr （1950-2000） integration with observational time-varying monthly SST forcing. Comparisons between these two cases and the reanalysis, including intra-seasonal and inter-annual variability are also presented. In addition, the differences between GAMIL-L and the original version of GAMIL are also investigated.The results show that GAMIL-L can capture most of the large-scale dynamical features of the atmosphere, especially in the tropics and mid latitudes, although a few deficiencies exist, such as the underestimated Hadley cell and thereby the weak strength of the Asia summer monsoon. However, the simulated mean states over high latitudes, especially over the polar regions, are not acceptable. Apart from dynamics, the thermodynamic features mainly depend upon the physical parameterization schemes. Since the physical package of GAMIL-L is exactly the same as the original high-resolution version of GAMIL, in which the NCAR Community Atmosphere Model （CAM2） physical package was used, there are only small differences between them in the precipitation and temperature fields. Because our goal is to develop a fast-running AGCM and employ it in the coupled climate system model of IAP/LASG for paleoclimate studies such as ENSO and Australia-Asia monsoon, particular attention has been paid to the model performances in the tropics. More model validations, such as those ran for the Southern Oscillation and South Asia monsoon, indicate that GAMIL-L is reasonably competent and valuable in this regard.

Prediction of the Asian-Australian Monsoon Interannual Variations with the Grid-Point Atmospheric Model of IAP LASG(GAMIL)

Seasonal prediction of Asian-Australian monsoon （A-AM） precipitation is one of the most important and challenging tasks in climate prediction. In this paper, we evaluate the performance of Grid Atmospheric Model of IAP LASG （GAMIL） on retrospective prediction of the A-AM interannual variation （IAV）, and determine to what extent GAMIL can capture the two major observed modes of A-AM rainfall IAV for the period 1979-2003. The first mode is associated with the turnabout of warming （cooling） in the Nifio 3.4 region, whereas the second mode leads the warming/cooling by about one year, signaling precursory conditions for ENSO. We show that the GAMIL one-month lead prediction of the seasonal precipitation anomalies is primarily able to capture major features of the two observed leading modes of the IAV, with the first mode better predicted than the second. It also depicts the relationship between the first mode and ENSO rather well. On the other hand, the GAMIL has deficiencies in capturing the relationship between the second mode and ENSO. We conclude： （1） successful reproduction of the E1 Nifio-excited monsoon-ocean interaction and E1 Nifio forcing may be critical for the seasonal prediction of the A-AM rainfall IAV with the GAMIL; （2） more efforts are needed to improve the simulation not only in the Nifio 3.4 region but also in the joining area of Asia and the Indian-Pacific Ocean; （3） the selection of a one-tier system may improve the ultimate prediction of the A-AM rainfall IAV. These results offer some references for improvement of the GAMIL and associated seasonal prediction skill.

Prediction model for atmospheric corrosion of 7005-T4 aluminum alloy in industrial and marine environments

Accelerated corrosion tests of the 7005-T4 aluminum alloy were conducted to determine a suitable service life prediction method by using alternating wet–dry cycles in three kinds of solutions. The morphology and composition analysis of the corrosion product revealed that slight corrosion occurred on the surfaces of the samples immersed in a 0.25 wt% Na_2S_2O_8 solution. However, pitting corrosion occurred on the surfaces of the samples immersed in a 3.5 wt% NaCl solution, whereas exfoliation corrosion occurred on the surfaces of the samples immersed in a mixture of 0.25 wt% Na_2S_2O_8 and 3.5 wt% NaCl solutions. A power exponent relationship was observed between the mass loss and exposure time of the 7005-T4 aluminum alloy immersed in the three kinds of solutions. In the mixture of 0.25 wt% Na_2S_2O_8 and 3.5 wt% NaCl solutions, the mass loss of the aluminum alloy yielded the maximum value. Based on the calculation of the correlation coefficients, the alternating wet–dry procedure in a 3.5 wt% NaCl solution could be used to predict the corrosion behavior of 7005-T4 aluminum alloy exposed in the atmosphere of Qingdao, China. The prediction model is as follows: T = 104.28×t^(0.91), where T is the equivalent time and t is the exposure time.

Dynamical Framework of IAP Nine-Level Atmospheric General Circulation Model

The dynamical framework of the nine-level version of the IAP AGCM is presented in this paper. The emphasis of the model's description is put on the following two aspects:(1) A model's standard atmosphere, which is a satisfactory approximation to the observed troposphere and lower stratosphere standard atmosphere, is introduced into the equations of the model to permit a more accurate calculation of the vertical transport terms, especially near the tropopause; (2) The vertical levels of the model are carefully selected to guarantee a smooth dependence of layer thickness upon pressure in order to reduce the truncation error involved in the unequal interval vertical finite-differencing. For testing the model, two kinds of linear baroclinic Rossby-Haurwitz waves, one of which has a dynamically stable vertical structure and the other has a relatively unstable one, are constructed to provide initial conditions for numerical experiments. The two waves have been integrated for more than 300 days and 100 days respectively by using the model and both of them are propagating westward with almost identical phase-speed during the time period of the integrations. No obvious change of the wave patterns is found at the levels in the model's troposphere. The amplitudes of both two waves at the uppermost level, however, exhibit rather significant oscillation with time, of which the periods are exactly 20 days and 25 days espectively.The explanation of this interesting phenomena is still under investigation.

A Hybrid Coupled Ocean–Atmosphere Model and Its Simulation of ENSO and Atmospheric Responses

A new hybrid coupled model(HCM) is presented in this study, which consists of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model. The ocean component is the intermediate ocean model(IOM)of the intermediate coupled model(ICM) used at the Institute of Oceanology, Chinese Academy of Sciences(IOCAS). The atmospheric component is ECHAM5, the fifth version of the Max Planck Institute for Meteorology atmospheric general circulation model. The HCM integrates its atmospheric and oceanic components by using an anomaly coupling strategy. A100-year simulation has been made with the HCM and its simulation skills are evaluated, including the interannual variability of SST over the tropical Pacific and the ENSO-related responses of the global atmosphere. The model shows irregular occurrence of ENSO events with a spectral range between two and five years. The amplitude and lifetime of ENSO events and the annual phase-locking of SST anomalies are also reproduced realistically. Despite the slightly stronger variance of SST anomalies over the central Pacific than observed in the HCM, the patterns of atmospheric anomalies related to ENSO,such as sea level pressure, temperature and precipitation, are in broad agreement with observations. Therefore, this model can not only simulate the ENSO variability, but also reproduce the global atmospheric variability associated with ENSO, thereby providing a useful modeling tool for ENSO studies. Further model applications of ENSO modulations by ocean–atmosphere processes, and of ENSO-related climate prediction, are also discussed.

Boreal Winter Rainfall Anomaly over the Tropical Indo-Pacific and Its Effect on Northern Hemisphere Atmospheric Circulation in CMIP5 Models

Experimental outputs of 11 Atmospheric Model Intercomparison Project （AMIP） models from phase 5 of the Coupled Model Intercomparison Project （CMIP5） are analyzed to assess the atmospheric circulation anomaly over Northern Hemisphere induced by the anomalous rainfall over tropical Pacific and Indian Ocean during boreal winter.The analysis shows that the main features of the interannual variation of tropical rainfall anomalies,especially over the Central Pacific （CP） （5°S-5°N,175°E-135°W） and Indo-western Pacific （IWP） （20°S-20°N,110°-150°E） are well captured in all the CMIP5/AMIP models.For the IWP and western Indian Ocean （WIO） （10°S-10°N,45°-75°E）,the anomalous rainfall is weaker in the 11 CMIP5/AMIP models than in the observation.During El Ni（n）o/La Ni（n）a mature phases in boreal winter,consistent with observations,there are geopotential height anomalies known as the Pacific North American （PNA） pattern and Indo-western Pacific and East Asia （IWPEA） pattern in the upper troposphere,and the northwestern Pacific anticyclone （cyclone） （NWPA） in the lower troposphere in the models.Comparison between the models and observations shows that the ability to simulate the PNA and NWPA pattern depends on the ability to simulate the anomalous rainfall over the CP,while the ability to simulate the IWPEA pattern is related to the ability to simulate the rainfall anomaly in the IWP and WIO,as the SST anomaly is same in AMIP experiments.It is found that the tropical rainfall anomaly is important in modeling the impact of the tropical Indo-Pacific Ocean on the extratropical atmospheric circulation anomaly.

Analysis and Evaluation of the Global Aerosol Optical Properties Simulated by an Online Aerosol-coupled Non-hydrostatic Icosahedral Atmospheric Model

Aerosol optical properties are simulated using the Spectral Radiation Transport Model I~）r Aerosol Species （SPRINTARS） coupled with the Non-hydrostatic ICosahedral Atmospheric Model （NICAM）. The 3-year global mean all-sky aerosol optical thickness （AOT） at 550 nm, theAngstr/Sm Exponent （AE） based on AOTs at 440 and 870 nm, and the single scattering albedo （SSA） at 550 nm are estimated at 0.123, 0.657 and 0.944, respectively. For each aerosol species, the mean AOT is within the range of the AeroCom models. Both the modeled all-sky and clear-sky results are compared with observations from the Moderate Resolution Imaging Spectroradiometer （MODIS） and the Aerosol Robotic Network （AERONET）. The simulated spatiotemporal distributions of all-sky AOTs can generally reproduce the MODIS retrievals, and the correlation and model skill can be slightly improved using the clear-sky results over most land regions. The differences between clear-sky and all-sky AOTs are larger over polluted regions. Compared with observations from AERONET, the modeled and observed all-sky AOTs and AEs are generally in reasonable agreement, whereas the SSA variation is not well captured. Although the spatiotemporal distributions of all-sky and clear-sky results are similar, the clear-sky results are generally better correlated with the observations. The clear-sky AOT and SSA are generally lower than the all-sky results, especially in those regions where the aerosol chemical composition is contributed to mostly by sulfate aerosol. The modeled clear-sky AE is larger than the all-sky AE over those regions dominated by hydrophilic aerosol, while the＇opposite is found over regions dominated by hydrophobic aerosol.

Improved algorithm of atmospheric refraction error in Longley-Rice channel model

Longley-Rice channel model modifies the atmospheric refraction by the equivalent earth radius method, which is simple calculation but is not accurate. As it only uses the horizontal difference, but does not make use of the vertical section information, it does not agree with the actual propagation path. The atmospheric refraction error correction method of the Longley-Rice channel model has been improved. The improved method makes use of the vertical section information sufficiently and maps the distance between the receiver and transmitter to the radio wave propagation distance, It can exactly reflect the infection of propagation distance for the radio wave propagation loss. It is predicted to be more close to the experimental results by simulation in comparison with the measured data. The effectiveness of improved methods is proved by simulation.

Two-moment Bulk Stratiform Cloud Microphysics in the Grid-point Atmospheric Model of IAP LASG (GAMIL)

A two-moment bulk stratiform microphysics scheme, including recently developed physically-based droplet activation/ice nucleation parameterizations has been implemented into the Grid-point Atmospheric Model of IAP LASG （GAMIL） as an effort to enhance the model＇s capability to simulate aerosol indirect effects. Unlike the previous one-moment cloud microphysics scheme, the new scheme produces a reasonable rep- resentation of cloud particle size and number concentration. This scheme captures the observed spatial variations in cloud droplet number concentrations. Simulated ice crystal number concentrations in cirrus clouds qualitatively agree with in situ observations. The longwave and shortwave cloud forcings are in better agreement with observations. Sensitivity tests show that the column cloud droplet number concentrations calculated from two different droplet activation parameterizations are similar. However, ice crystal number concentration in mixed-phased clouds is sensitive to different heterogeneous ice nucleation formulations. The simulation with high ice crystal number concentration in mixed-phase clouds has less liquid water path and weaker cloud forcing. ~rthermore, ice crystal number concentration in cirrus clouds is sensitive to different ice nucleation parameterizations. Sensitivity tests also suggest that the impact of pre-existing ice crystals on homogeneous freezing in old clouds should be taken into account.

Spatial and Temporal Variations in the Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in China

The aging timescale of particles is a key parameter in determining their impacts on air quality,human health,and climate.In this study,a one-year simulation of the age distributions of the primary and secondary inorganic fine particulate matter(PM_(2.5))components was conducted over China using an age-resolved Community Multiscale Air Quality(CMAQ)model.The results indicate that primary PM_(2.5)(PPM)and ammonium mainly originate from fresh local emissions,with approximately 60%-80%concentrated in 0-24 h age bins in most of China throughout the year.The average age is about15-25 h in most regions in summer,but increases to 40-50 h in southern region of China and the Sichuan Basin(SCB)in winter.Sulfate is more aged than PPM,indicating an enhanced contribution from regional transport.Aged sulfate with atmospheric age>48 h account for 30%-50%of total sulfate in most regions and seasons,and the concentrations in the>96 h age bin can reach up to 15μg·m-3 in SCB during winter.Dramatic seasonal variations occur in the Yangtze River Delta,Pearl River Delta,and SCB,with highest average age of 60-70 h in winter and lowest of 40-45 h in summer.The average age of nitrate is 20-30 h in summer and increases to 40-50 h in winter.The enhanced deposition rate of nitric acid vapor combined with the faster chemical reaction rate of nitrogen oxides leads to a lower atmospheric age in summer.Additionally,on pollution days,the contributions of old age bins(>24 h)increase notably for both PPM and secondary inorganic aerosols in most cities and seasons,suggesting that regional transport plays a vital role during haze events.The age information of PM_(2.5),provided by the age-resolved CMAQ model,can help policymakers design effective emergent emission control measures to eliminate severe haze episodes.

Simple General Atmospheric Circulation and Climate Models with Memory

This article examines some general atmospheric circulation and climate models in the context of the notion of “memory”. Two kinds of memories are defined： statistical memory and deterministic memory. The former is defined through the autocorrelation characteristic of the process if it is random （chaotic）, while for the latter, a special memory function is introduced. Three of the numerous existing models are selected as examples. For each of the models, asymptotic （at t →∞） expressions are derived. In this way, the transients are filtered out and that which remains concerns the final behaviour of the models.

Basic Pattern in Atmospheric Turbulence Model

From the controlling equations of atmosphere motion, Prandtl's mixing length theory is used to derive the atmospheric turbulence models, such as Burgers equation model and Burgers-KdV equation model. And then the projective Riccati equations are applied to solve these atmospheric turbulence models, where much more patterns are obtained, including solitary wave pattern, singular pattern, and so on.