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.

Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6

Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

Assessment of earthquake-induced landslide hazard zoning using the physics-environmental coupled Model

In order to prevent and mitigate disasters,it is crucial to immediately and properly assess the spatial distribution of landslide hazards in the earthquake-affected area.Currently,there are primarily two categories of assessment techniques:the physical mechanism-based method(PMBM),which considers the landslide dynamics and has the advantages of effectiveness and proactivity;the environmental factor-based method(EFBM),which integrates the environmental conditions and has high accuracy.In order to obtain the spatial distribution of landslide hazards in the affected area with near realtime and high accuracy,this study proposed to combine the PMBM based on Newmark method with EFBM to form Newmark-Information value model(N-IV),Newmark-Logic regression model(N-LR)and Newmark-Support Vector Machine model(N-SVM)for seismic landslide hazard assessment on the Ludian Mw 6.2 earthquake in Yunnan.The predicted spatial hazard distribution was compared with the actual cataloged landslide inventory,and frequency ratio(FR),and area under the curve(AUC)metrics were used to verify the model's plausibility,performance,and accuracy.According to the findings,the model's accuracy is ranked as follows:N-SVM>N-LR>N-IV>Newmark.With an AUC value of 0.937,the linked N-SVM was discovered to have the best performance.The research results indicate that the physics-environmental coupled model(PECM)exhibits accuracy gains of 46.406%(N-SVM),30.625%(N-LR),and 22.816%(N-IV)when compared to the conventional Newmark technique.It shows varied degrees of improvement from 2.577%to 12.446%when compared to the single EFBM.The study also uses the Ms 6.8 Luding earthquake to evaluate the model,showcasing its trustworthy in forecasting power and steady generalization.Since the suggested PECM in this study can adapt to complicated earthquake-induced landslides situations,it aims to serve as a reference for future research in a similar field,as well as to help with emergency planning and response in earthquakeprone regions with landslides.

Evaluation of East Asian Climatology as Simulated by Seven Coupled Models

Using observation and reanalysis data throughout 1961-1990, the East Asian surface air temperature, precipitation and sea level pressure climatology as simulated by seven fully coupled atmosphere-ocean models, namely CCSR/NIES, CGCM2, CSIRO-Mk2, ECHAM4/OPYC3, GFDL-R30, HadCM3, and NCAR-PCM, are systematically evaluated in this study. It is indicated that the above models can successfully reproduce the annual and seasonal surface air temperature and precipitation climatology in East Asia, with relatively good performance for boreal autumn and annual mean. The models' ability to simulate surface air temperature is more reliable than precipitation. In addition, the models can dependably capture the geographical distribution pattern of annual, boreal winter, spring and autumn sea level pressure in East Asia. In contrast, relatively large simulation errors are displayed when simulated boreal summer sea level pressure is compared with reanalysis data in East Asia. It is revealed that the simulation errors for surface air temperature, precipitation and sea level pressure are generally large over and around the Tibetan Plateau. No individual model is best in every aspect. As a whole, the ECHAM4/OPYC3 and HadCM3 performances are much better, whereas the CGCM2 is relatively poorer in East Asia. Additionally, the seven-model ensemble mean usually shows a relatively high reliability.

Improved ENSO Forecasts by Assimilating Sea Surface Temperature Observations into an Intermediate Coupled Model

A simple method for initializing intermediate coupled models （ICMs） using only sea surface temperature （SST） anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984-2003 and the period 1997-2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.

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.

Fluid Flow and Solidification Simulation in Beam Blank Continuous Casting Process With 3D Coupled Model

Based on turbulent theory, a 3D coupled model of fluid flow and solidification was built using finite difference method and used to study the influence of superheating degree and casting speed on fluid flow and solidification, analyze the interaction between shell and molten steel, and compare the temperature distribution under different technological conditions. The results indicate that high superheating degree can lengthen the liquid-core depth and make the crack and breakout possible, so suitable superheating should be controlled within 35℃ according to the simulation results. Casting speed which is one of the most important technological parameters of improving production rate, should be controlled between 0. 85 m/min and 1.05 m/min and the caster has great potential in the improvement of blank quality.

Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction

A four-dimensional variational （4D-Var） data assimilation method is implemented in an improved intermediate coupled model （ICM） of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The ＂observation＂ of the SST anomaly, which is sampled from a ＂truth＂ model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction.

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.

A Regional Air-Sea Coupled Model and Its Application over East Asia in the Summer of 2000

A regional air-sea coupled model, comprising the Regional Integrated Environment Model System （RIEMS） and the Princeton Ocean Model （POM） was developed to simulate summer climate features over East Asia in 2000. The sensitivity of the model＇s behavior to the coupling time interval （CTI）, the causes of the sea surface temperature （SST） biases, and the role of air-sea interaction in the simulation of precipitation over China are investigated. Results show that the coupled model can basically produce the spatial pattern of SST, precipitation, and surface air temperature （SAT） with five different CTIs respectively. Also, using a CTI of 3, 6 or 12 hours tended to produce more successful simulations than if using 1 and 24 hours. Further analysis indicates that both a higher and lower coupling frequency result in larger model biases in air-sea heat flux exchanges, which might be responsible for the sensitivity of the coupled model＇s behavior to the CTI. Sensitivity experiments indicate that SST biases between the coupled and uncoupled POM occurring over the China coastal waters were due to the mismatch of the surface heat fluxes produced by the RIEMS with those required by the POM. In the coupled run, the air-sea feedbacks reduced the biases in surface heat fluxes, compared with the uncoupled RIEMS, consequently resulted in changes in thermal contrast over land and sea and led to a precipitation increase over South China and a decrease over North China. These results agree well observations in the summer of 2000.

Simulation of double cold cores of the 35°N section in the YellowSea with a wave-tide-circulation coupled model

Based on the MASNUM wave-tide-circulation coupled numerical model, the temperature structure along 35°N in the Yellow Sea was simulated and compared with the observations. One of the notable features of the temperature structure along 35°N section is the double cold cores phenomena during spring and summer. The double cold cores refer to the two cold water centers located near 122°E and 125°E from the depth of 30m to bottom. The formation, maintenance and disappearance of the double cold cores are discussed. At least two reasons make the temperature in the center (near 123°E) of the section higher than that near the west and east shores in winter. One reason is that the water there is deeper than the west and east sides so its heat content is higher. The other is invasion of the warm water brought by the Yellow Sea Warm Current (YSWC) during winter.This temperature pattern of the lower layer (from 30m to bottom) is maintained through spring and summer when the upper layer (0 to 30m) is heated and strong thermocline is formed. Large zonal span of the 35°N section (about 600 km) makes the cold cores have more opportunity to survive. The double cold cores phenomena disappears in early autumn when the west cold core vanishes first with the dropping of the thermocline position.

A coupled model of TiN inclusion growth in GCr15SiMn during solidification in the electroslag remelting process

TiN inclusions observed in an ingot produced by electroslag remelting （ESR） are extremely harmful to GCrl5SiMn steel. Therefore, accurate predictions of the growth size of these inclusions during steel solidification are significant for clean ESR ingot production. On the basis of our previous work, a coupled model of solute microsegregation and TiN inclusion growth during solidification has been established. The results demonstrate that compared to a non-coupled model, the coupled model predictions of the size of TiN inclusions are in good agreement with experimental results using scanning electron microscopy with energy disperse spectroscopy （SEM-EDS）. Because of high cooling rate, the sizes of TiN inclusions in the edge area of the ingots are relatively small compared to the sizes in the center area. During the ESR process, controlling the content of Ti in the steel is a feasible and effective method of decreasing the sizes of TiN inclusions.

An Examination of the Predictability of Tropical Cyclone Genesis in High-Resolution Coupled Models with Dynamically Downscaled Coupled Data Assimilation Initialization

Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses to local warm sea surface temperatures and feedbacks,with aid from coherent coupled initialization.This study uses three sets of highresolution regional coupled models(RCMs)covering the Asia−Pacific(AP)region initialized with local observations and dynamically downscaled coupled data assimilation to evaluate the predictability of TC genesis in the West Pacific.The APRCMs consist of three sets of high-resolution configurations of the Weather Research and Forecasting−Regional Ocean Model System(WRF-ROMS):27-km WRF with 9-km ROMS,and 9-km WRF with 3-km ROMS.In this study,a 9-km WRF with 9-km ROMS coupled model system is also used in a case test for the predictability of TC genesis.Since the local sea surface temperatures and wind shear conditions that favor TC formation are better resolved,the enhanced-resolution coupled model tends to improve the predictability of TC genesis,which could be further improved by improving planetary boundary layer physics,thus resolving better air−sea and air−land interactions.

Initial Error-induced Optimal Perturbations in ENSO Predictions, as Derived from an Intermediate Coupled Model

The initial errors constitute one of the main limiting factors in the ability to predict the E1 Nino-Southem Oscillation （ENSO） in ocean-atmosphere coupled models. The conditional nonlinear optimal perturbation （CNOP） approach was em- ployed to study the largest initial error growth in the E1 Nino predictions of an intermediate coupled model （ICM）. The optimal initial errors （as represented by CNOPs） in sea surface temperature anomalies （SSTAs） and sea level anomalies （SLAs） were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nifia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of E1 Nino, the E1 Nino event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier （SPB） phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly, weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events.

Coupled modeling of tumour angiogenesis, tumour growth,and blood perfusion

This paper proposes a more realistic mathematical simulation method to investigate the dynamic process of tumour angio-genesis by fully coupling the vessel growth,tumour growth and associated blood perfusion.The tumour growth and angiogenesis are coupled by the chemical microenvironment and the cell-matrix interaction.The haemodynamic calculation is carried out on the new vasculature,and an estimation of vessel collapse is made according to the wall shear stress criterion.The results are consistent with physiological observations,and further confirm the application of the coupled model feedback mechanism.The model is available to examine the interactions between angiogenesis and tumour growth,to study the change in the dynamic process of chemical environment and the vessel remodeling.

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.

The Coupled Model Predictability of the Western North Pacific Summer Monsoon with Different Leading Times

Leading time length is an important issue for modeling seasonal forecasts. In this study, a comparison of the interannual predictability of the Western North Pacific (WNP) summer monsoon between different leading months was performed by using one-, four-, and sevenmonth lead retrospective forecasts (hindcasts) of four coupled models from Ensembles-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) for the period of 1960 2005. It is found that the WNP summer anomalies, including lower-tropospheric circulation and precipitation anomalies, can be well predicted for all these leading months. The accuracy of the four-month lead prediction is only slightly weaker than that of the one-month lead prediction, although the skill decreases with the increase of leading months.

An ocean-land-atmosphere coupled model for tropical cyclone landfall processes: The multi-layer ocean model and its verification

POM (Princeton ocean model) tentatively taken as the ocean part of an ocean-land atmosphere coupled modcl is verified for the ultimate purpose of studying the landfall process of tropical cyclone (TC) in the western North Pacific. The POM is tested with monthly mean wind stress in the summer and given lateral boundary conditions. The results indicate that the equilibrium state of the ocean is in accordance with the climate mean, with the error in sea surface temperature (salinity) less than 0.5 ℃ (0.5). The simulated occan currents are reasonable as well.Several numerical experiments are designed to verify the oceanic response to a stationary or moving TC. It is found that the results agree fairly well with the previous work, including both the drop magnitude and the distribution ofsca temperature. Compared with the simple two-layer ocean model used by some other studies, the response of the ocean to a TC is more logical here. The model is also verified in a real case with a TC passing the neighborhood of a buoy station. It is shown that the established ocean model can basically reproduce the sea surface temperature change as observed.

Introduction to the Regional Coupled Model WRF4-LICOM: Performance and Model Intercomparison over the Western North Pacific

Regional coupled modeling is one of the frontiers of regional climate modeling,but intercomparison has not been well coordinated.In this study,a community regional climate model,WRF4,with a resolution of 15 km,was coupled with a high-resolution(0.1°)North Pacific Ocean model(LICOM_np).The performance of the regional coupled model,WRF4_LICOM,was compared to that of another regional coupled model,RegCM4_LICOM,which was a coupling of version 4 of the Regional Climate Model(RegCM4)with LICOM_np.The analysis focused on the 2005 western North Pacific summer monsoon rainfall.The results showed that the regional coupled models with either RegCM4 or WRF4 as their atmospheric model component simulated the broad features over the WNP reasonably well.Quantitative intercomparison of the regional coupled simulations exhibited different biases for different climate variables.RegCM4_LICOM exhibited smaller biases in its simulation of the averaged June–July–August SST and rainfall,while WRF4_LICOM better captured the tropical cyclone(TC)intensity,the percentage contributions of rainfall induced by TCs to the total rainfall,and the diurnal cycle of rainfall and stratiform percentages,especially over land areas.The different behaviors in rainfall simulated by the two models were partly ascribed to the behaviors in the simulated western North Pacific subtropical high(WNPSH).The stronger(weaker)WNPSH in WRF4_LICOM(RegCM4_LICOM)was driven by overestimated(underestimated)diabatic heating,which peaked at approximately 450 hPa over the region around the Philippines in association with different condensation–radiation processes.Coupling of WRF4 with LIOCM is a crucial step towards the development of the next generation of regional earth system models at the Chinese Academy of Sciences.

Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.