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. .

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.

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.

Progress in the Development and Application of Climate Ocean Models and Ocean-Atmosphere Coupled Models in China

A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed with these models. While the history of model development is briefly reviewed, emphasis has been put on the achievements made in the last five years. Advances in model development are described along with a summary on scientific issues addressed by using these models. The focus of the review is the climate ocean models and the associated coupled models, including both global and regional models, developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed.

A Coupled General Circulation Model for the Tropical Pacific Ocean and Global Atmosphere

On the basis of Zeng's theorehcal design, a coupled general circulation model(CGCM) is develO￣ with itscharacteristics different from other CGCMs such as the unified vertical coordinates and subtraction of the standard stratification for both atmosphere and ocean, available energy consideration,and so on.The oceanic comPOnent is a free surface tropical Pacific Ocean GCM betWeen 30W and 30'S with horizontal grid spacing of ic in latitude and 2°in longitude,and with 14 vertical layers.The atmospheric component is a global GCM with low-resolution of 4°in lahtude and 5°in longitude,and tWo layers of equal mass in the verhcal between the surfaCe and 200 hFa.The atmospheric GCM includes comprehensive physical processes.The coupled model is subjected to seasonally-varying cycle.Several coupling experiments,ranging from straight forward coupling without flux correction to one with flux correchon,and to so-called predictor-corrector monthly coupling(PCMC),are conducted tO show the esistence and final controlling of the climate drift in the coupled system.After removing the climate drift with the PCMC SCheme,the coupled model is integrated for more than twenty years.The results show reasonable simulations of the anneal mean and its seasollal cycle of the atmospheric and￣ante circulahon.The model also ProduCeS the coherent intermnual variations of the climate system, manifesting the observed EI Nifio/Southern OSCillation(ENSO).

The Application of Flux-Form Semi-Lagrangian Transport Scheme in a Spectral Atmosphere Model

A flux-form semi-Lagrangian transport scheme （FFSL） was implemented in a spectral atmospheric GCM developed and used at IAP/LASG. Idealized numerical experiments show that the scheme is good at shape preserving with less dissipation and dispersion, in comparison with other conventional schemes, hnportantly, FFSL can automatically maintain the positive definition of the transported tracers, which was an underlying problem in the previous spectral composite method （SCM）. To comprehensively investigate the impact of FFSL on GCM results, we conducted sensitive experiments. Three main improvements resulted： first, rainfall simulation in both distribution and intensity was notably improved, which led to an improvement in precipitation frequency. Second, the dry bias in the lower troposphere was significantly reduced compared with SCM simulations. Third, according to the Taylor diagram, the FFSL scheme yields simulations that are superior to those using the SCM： a higher correlation between model output and observation data was achieved with the FFSL scheme, especially for humidity in lower troposphere. However, the moist bias in the middle and upper troposphere was more pronounced with the FFSL scheme. This bias led to an over-simulation of precipitable water in comparison with reanalysis data. Possible explanations, as well as solutions, are discussed herein.

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.

Applying Artificial Neural Networks to Modeling the Middle Atmosphere

An artificial neural network （ANN） is used to model the middle atmosphere using a large number of TIMED/SABER limb sounding temperature profiles. A three-layer feed-forward network is chosen based on the back-propagation （BP） algorithm. Latitude, longitude, and height are chosen as the input vectors of the network while temperature is the output vector. The temperature observations during the period from 13 January through 16 March 2007, which are in the same satellite yaw, are taken as samples to train an ANN. Results suggest that the network has high quality for modeling spatial variations of temperature. Quantitative comparisons between the ANN outputs and those from the popular empirical NRLMSISE-00 model illustrate their generally consistent features and some specific differences. The NRLMSISE-00 model＇s zonal mean temperatures are too high by ～6 K-10 K near the stratopause, and the amplitude and phase of the planetary wave number 1 activity are different in some respects from the ANN simulations above 45-50 km, suggesting improvement is needed in the NRLMSISE-00 model for more accurate simulation near and above the stratopause.

Influence of moderate-to-strong anisotropic non-Kolmogorov turbulence on intensity fluctuations of a Gaussian–Schell model beam in marine atmosphere

The scintillation index（SI） of a Gaussian–Schell model（GSM） beam in a moderate-to-strong anisotropic nonKolmogorov turbulent atmosphere is developed based on the extended Rytov theory. The on-axis SI in a marine atmosphere is higher than that in a terrestrial atmosphere, but the off-axis SI exhibits the opposite trend. The on-axis SI first increases and then begins to decrease and saturate as the turbulence strength increases. Turbulence inner and outer scales have different effects on the on-axis SI in different turbulent fluctuation regions. The anisotropy characteristic of atmospheric turbulence leads to the decline in the on-axis SI, and the rise in the off-axis SI. The on-axis SI can be lowered by increasing the anisotropy of turbulence, wavelength, and source partial coherence before entering the saturation attenuation region. The developed model may be useful for evaluating ship-to-ship/shore free-space optical communication system performance.

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.

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.

Decoy State Quantum Key Distribution via Beam-Wandering Modeled Atmosphere Channel

We investigate the decoy state quantum key distribution via the atmosphere channels. We consider the efficient decoy state method with one-signal state and two-decoy states. Our results show that the decoy state method works even in the channels with fluctuating transmittance. Nevertheless, the key generation rate will be dra-matically decreased by atmosphere turbulence, which sheds more light on the characterization of atmosphere turbulence in realistic free-space based quantum key distributions.

An Environmental Risk Evaluation Method Employing Atmospheric Dispersion Models and GIS

This study aims to develop a method for evaluating the environmental risk of harmful chemical substances released from specific sources, using two atmospheric dispersion models and GIS (Geographic Information Systems). In the first stage of evaluation, ADMER was used to conduct a wide-area evaluation which covered the entire area of the evaluation target region. In the second stage, METI-LIS was used to conduct a detailed limited-area evaluation which targeted the vicinity of sources. In this study, incinerators were selected as sources and dioxins were selected as harmful chemical substances. The area selected for evaluation was the Tokyo Metropolis in Japan, and the evaluation method proposed in this study was used to evaluate environmental risk. Through the use of atmospheric dispersion models and GIS, the behavior of dioxins emitted into the atmosphere from incinerators was estimated. By superimposing atmospheric levels and population data, the amounts of dioxins that humans exposed to were found. Additionally, by superimposing deposition amounts and land use data, the amounts of dioxins accumulated in each land environment were found. Conducting these steps enabled the impact of dioxins on humans and the environment to be grasped quantitatively and visually, and the risk that dioxins emitted from incinerators pose to the environment to be evaluated.

New Developments on Existence and Uniqueness of Solutions to Some Models in Atmospheric Dynamics

This survey is concerned with the new developments on existence and uniqueness of solutions of some basic models in atmospheric dynamics, such as two-and three-dimensional quasi-geostrophic models and three-dimensional balanced model. The main aim of this paper is to introduce some results about the global and local (with respect to time) existence of solutions given by the authors in recent years, but others' important contributions and the literature on this subject are also quoted. We discuss briefly the relationships among the existence and uniqueness, physical instability and computational instability. In the appendixes, some key mathematical techniques in obtaining our results are presented, which are of vital importance to other problems in geophysical fluid dynamics as well.

A Hybrid Coupled Model for the Pacific Ocean–Atmosphere System.Part I: Description and Basic Performance

A hybrid coupled model （HCM） is constructed for El Nifio-Southern Oscillation （ENSO）-related modeling studies over almost the entire Pacific basin.An ocean general circulation model is coupled to a statistical atmospheric model for interannual wind stress anomalies to represent their dominant coupling with sea surface temperatures.In addition,various relevant forcing and feedback processes exist in the region and can affect ENSO in a significant way; their effects are simply represented using historical data and are incorporated into the HCM,including stochastic forcing of atmospheric winds,and feedbacks associated with freshwater flux,ocean biology-induced heating （OBH）,and tropical instability waves （TIWs）.In addition to its computational efficiency,the advantages of making use of such an HCM enable these related forcing and feedback processes to be represented individually or collectively,allowing their modulating effects on ENSO to be examined in a clean and clear way.In this paper,examples are given to illustrate the ability of the HCM to depict the mean ocean state,the circulation pathways connecting the subtropics and tropics in the western Pacific,and interannual variability associated with ENSO.As satellite data are taken to parameterize processes that are not explicitly represented in the HCM,this work also demonstrates an innovative method of using remotely sensed data for climate modeling.Further model applications related with ENSO modulations by extratropical influences and by various forcings and feedbacks will be presented in Part Ⅱ of this study.

Simulation of Typhoon Muifa using a mesoscale coupled atmosphere–ocean model

A mesoscale coupled atmosphere–ocean model has been developed based on the GRAPES（Global and Regional Assimilation and Prediction System） regional typhoon model（GRAPES_TYM） and ECOM-si（estuary, coast and ocean model（semi-implicit））. Coupling between the typhoon and ocean models was conducted by exchanging wind stress, heat, moisture fluxes, and sea surface temperatures（SSTs） using the coupler OASIS3.0. Numerical prediction experiments were run with and without coupling for the case of Typhoon Muifa in the western North Pacific. To investigate the impact of using more accurate SST information on the simulation of the track and the intensity of Typhoon Muifa, experiments were also conducted using increased SST resolution in the initial condition field of the control test. The results indicate that increasing SST resolution in the initial condition field somewhat improved the intensity forecast, and use of the coupled model improved the intensity forecast significantly, with mean absolute errors in maximum wind speed within 48 and 72 h reduced by 32% and 20%, respectively. Use of the coupled model also resulted in less pronounced over-prediction of the intensity of Typhoon Muifa by the GRAPES_TYM. Moreover, the effects of using the coupled model on the intensity varied throughout the different stages of the development of Muifa owing to changes in the oceanic mixed layer depth. The coupled model had pronounced effects during the later stage of Muifa but had no obvious effects during the earlier stage. The SSTs predicted by the coupled model decreased by about 5–6℃ at most after the typhoon passed, in agreement with satellite data. Furthermore, based on analysis on the sea surface heat flux, wet static energy of the boundary layer, atmospheric temperature, and precipitation forecasted by the coupled model and the control test, the simulation results of this coupled atmosphere–ocean model can be considered to reasonably reflect the primary mechanisms underlying the interactions between tropical cyclones and oceans.

Numerical simulations and comparative analysis for two types of storm surges in the Bohai Sea using a coupled atmosphere-ocean model

The Bohai Sea is extremely susceptible to storm surges induced by extratropical storms and tropical cyclones in nearly every season. In order to relieve the impacts of storm surge disasters on structures and human lives in coastal regions, it is very important to understand the occurring of the severe storm surges. The previous research is mostly restricted to a single type of storm surge caused by extratropical storm or tropical cyclone. In present paper, a coupled atmosphere-ocean model is developed to study the storm surges induced by two types of extreme weather conditions. Two special cases happened in the Bohai Sea are simulated successively. The wind intensity and minimum sea-level pressure derived from the Weather Research and Forecasting (WRF) model agree well with the observed data. The computed time series of water level obtained from the Regional Ocean Modeling System (ROMS) also are in good agreement with the tide gauge observations. The structures of the wind fields and average currents for two types of storm surges are analyzed and compared. The results of coupled model are compared with those from the uncoupled model. The case studies indicate that the wind field and structure of the ocean surface current have great differences between extratropical storm surge and typhoon storm surge. The magnitude of storm surge in the Bohai Sea is shown mainly determined by the ocean surface driving force, but greatly affected by the coastal geometry and bathymetry.

Development of a fine-resolution atmosphere-wave-ocean coupled forecasting model for the South China Sea and its adjacent seas

A 72-h fine-resolution atmosphere-wave-ocean coupled forecasting system was developed for the South China Sea and its adjacent seas. The forecasting model domain covers from from 15°S to 45°N in latitude and 99°E to135°E in longitude including the Bohai Sea, the Yellow Sea, the East China Sea, the South China Sea and the Indonesian seas. To get precise initial conditions for the coupled forecasting model, the forecasting system conducts a 24-h hindcast simulation with data assimilation before forecasting. The Ensemble Adjustment Kalman Filter(EAKF) data assimilation method was adopted for the wave model MASNUM with assimilating Jason-2 significant wave height(SWH) data. The EAKF data assimilation method was also introduced to the ROMS model with assimilating sea surface temperature(SST), mean absolute dynamic topography(MADT) and Argo profiles data. To improve simulation of the structure of temperature and salinity, the vertical mixing scheme of the ocean model was improved by considering the surface wave induced vertical mixing and internal wave induced vertical mixing. The wave and current models were integrated from January 2014 to October 2015 driven by the ECMWF reanalysis 6 hourly mean dataset with data assimilation. Then the coupled atmosphere-wave-ocean forecasting system was carried out 14 months operational running since November 2015. The forecasting outputs include atmospheric forecast products, wave forecast products and ocean forecast products. A series of observation data are used to evaluate the coupled forecasting results, including the wind, SHW, ocean temperature and velocity.The forecasting results are in good agreement with observation data. The prediction practice for more than one year indicates that the coupled forecasting system performs stably and predict relatively accurate, which can support the shipping safety, the fisheries and the oil exploitation.

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.

Climate-Vegetation Interannual Variability in a Coupled Atmosphere-Ocean-Land Model

The coupled models of both the Global Ocean-Atmosphere-Land System （GOALS） and the Atmosphere- Vegetation Interaction Model （GOALS-AVIM） are used to study the main characteristics of interannual variations. The simulated results are also used to investigate some significant interannual variability and correlation analysis of the atmospheric circulation and terrestrial ecosystem. By comparing the simulations of the climate model GOALS-AVIM and GOALS, it is known that the simulated results of the interannual variations of the spatial and temporal distributions of the surface air temperatures and precipitation are generally improved by using AVIM in GOALS-AVIM. The interannual variation displays some distinct characteristics of the geographical distribution. Both the Net Primary Production （NPP） and the Leap Area Index （LAI） have quasi 1-2-year cycles. Meanwhile, precipitation and the surface temperatures have 2-4- year cycles. Conditions when the spectrum density values of GOALS are less than those of GOALS-AVIM, tell us that the model coupled with AVIM enhances the simulative capability for interannual variability and makes the annual cycle variability more apparent. Using Singular Value Decomposition （SVD） analysis, the relationship between the ecosystem and the atmospheric circulation in East Asia is explored. The result shows that the strengthening and weakening of the East Asian monsoon, characterized by the geopotential heights at 500 hPa and the wind fields at 850 hPa, correspond to the spatiotemporal pattern of the NPP. The correlation between NPP and the air temperature, precipitation and solar radiation are different in interannual variability because of the variation in vegetation types.