The Chang-63 reservoir in the Huaqing area has widely developed tight sandstone ＂thick sand layers, but not reservoirs characterized by rich in oil＂, and it is thus necessary to further study its oil and gas enrichm...The Chang-63 reservoir in the Huaqing area has widely developed tight sandstone ＂thick sand layers, but not reservoirs characterized by rich in oil＂, and it is thus necessary to further study its oil and gas enrichment law. This study builds porosity and fracture development and evolution models in different deposition environments, through core observation, casting thin section, SEM, porosity and permeability analysis, burial history analysis, and ＂four-property-relationships＂ analysis.展开更多
The simulated sea surface temperature anomaly(SSTA)over the tropical Pacific during El Ni?o–Southern Oscillation(ENSO)is investigated in three representative coupled models:CESM1-CAM5,FGOALS-s2,and FGOALS-g2.It is fo...The simulated sea surface temperature anomaly(SSTA)over the tropical Pacific during El Ni?o–Southern Oscillation(ENSO)is investigated in three representative coupled models:CESM1-CAM5,FGOALS-s2,and FGOALS-g2.It is found that there is a significant westward shift bias in reproducing the zonal distribution(ZD)of the ENSO-related SSTA in CESM1-CAM5 and FGOALS-s2,whereas the SSTA-ZD simulated by FGOALS-g2 is relatively realistic.Through examining the SSTA-ZD during both warm and cold phases of ENSO separately,the authors reveal that the SSTA-ZD simulation bias during the ENSO cycle mainly lies in the bias during the warm phase.It is noted that both the simulated zonal wind stress anomaly(τ’_x)and shortwave heat flux(SW)anomaly exhibit westward shift biases in CESM1-CAM5 and FGOALS-s2,while the counterparts in FGOALS-g2 are relatively reasonable.The westward shift biases in representingτ’_x and the SW anomaly(SWA)are attributed to the westward-shifted precipitation anomaly(PrA).It is suggested that the mean SST cold bias over the cold tongue region is the key factor behind the westward-shift bias in simulating the El Ni?o-related PrA,which leads to the westward-shiftedτ’_x and SWA.Collectively,the aforementioned anomaly fields,including the dynamic part(τ’_x)and thermodynamic part(SWA),contribute to the westward-shift bias in simulating the El Ni?o-related SSTA.This study provides clues for understanding the ZD simulation biases of ENSO-related fields;however,further in-depth investigation with more model simulations,especially the incoming CMIP6 simulations,is still needed to fully understand the ENSO SSTA-ZD simulation bias in coupled models.展开更多
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 ...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.展开更多
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...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.展开更多
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...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.展开更多
The authors examine the spatial and temporal characteristics of the simulated Pacific Decadal Oscillation （PDO） in 109 historical （i.e. all forcings） simulations derived from 25 coupled models within CMIPS. Compar...The authors examine the spatial and temporal characteristics of the simulated Pacific Decadal Oscillation （PDO） in 109 historical （i.e. all forcings） simulations derived from 25 coupled models within CMIPS. Compared with observations, most simulations successfully simulate the observed PDO pattern and its teleconnections to the SSTs in the tropical and southern Pacific. BNU-ESM, CanESM2, CCSM4, CESM 1 -FASTCHEM, FGOALS-g2, GFDL CM3, MIROCS, and NorESM 1 -M show better performance. Compared with the temporal phases of the observed PDO in the twentieth century, only five simulations -- from CNRM^CMS, CSIRO Mk3o6.0, HadCM3, and IPSL-CMSA-LR -- simulate an evolution of the PDO similar to that derived from observation, which suggests that current coupled models can barely reproduce the observed phase shifting of the PDO. To capture characteristics of the observed PDO in the twentieth century, a requirement is that all the relevant external forcings are included in the models. How to add realistic oceanic initial states into the model may be another key point.展开更多
The coupling between wind stress perturbations and sea surface temperature(SST)perturbations induced by tropical instability waves(TIWs)in the Pacific Ocean has been revealed previously and proven crucial to both the ...The coupling between wind stress perturbations and sea surface temperature(SST)perturbations induced by tropical instability waves(TIWs)in the Pacific Ocean has been revealed previously and proven crucial to both the atmosphere and ocean.However,an overlooked fact by previous studies is that the loosely defined“TIWs”actually consist of two modes,including the Yanai wave-based TIW on the equator(hereafter eTIW)and the Rossby wave-based TIW off the equator(hereafter vTIW).Hence,the individual feedbacks of the wind stress to the bimodal TIWs remain unexplored.In this study,individual coupling relationships are established for both eTIW and v TIW,including the relationship between the TIW-induced SST perturbations and two components of wind stress perturbations,and the relationship between the TIW-induced wind stress perturbation divergence(curl)and the downwind(crosswind)TIW-induced SST gradients.Results show that,due to different distributions of eTIW and vTIW,the coupling strength induced by the eTIW is stronger on the equator,and that by the vTIW is stronger off the equator.The results of any of eTIW and vTIW are higher than those of the loosely defined TIWs.We further investigated how well the coupling relationships remained in several widely recognized oceanic general circulation models and fully coupled climate models.However,the coupling relationships cannot be well represented in most numerical models.Finally,we confirmed that higher resolution usually corresponds to more accurate simulation.Therefore,the coupling models established in this study are complementary to previous research and can be used to refine the oceanic and coupled climate models.展开更多
The magnitude of El Nino determines the level of its global impact.Yet,how well our state-of-the-art models simulate this key aspect of El Nino is not well documented.Previous studies tend to ignore El Nino-Southern O...The magnitude of El Nino determines the level of its global impact.Yet,how well our state-of-the-art models simulate this key aspect of El Nino is not well documented.Previous studies tend to ignore El Nino-Southern Oscillation(ENSO)asymmetry and equate the variance of ENSO to the magnitude of El Nino.Moreover,previous evaluations are more focused on the surface manifestation of El Nino.Here,we quantify the magnitudes of El Nino and La Nina separately,both at the surface and subsurface levels.At the surface,we find that while the magnitude of La Nina events in most models is generally stronger than observed,the magnitude of El Nino is more diverse to observations.In fact,in many models,El Nino is weaker than observed.This bias in the magnitude of El Nino is more pronounced in the subsurface.We attribute this weakness in the subsurface to the generally weaker coupling strength and the apparent stronger ENSO at the surface to a lack of sufficiently strong negative feedback from the surface heat flux in the models.When normalized by the variance of ENSO,the lack of exceptionally strong El Nino events in the models is more common and pronounced.We further studied the lifespan of El Nino and La Nina events and have found that multi-year duration is not confined to just La Nina events.There are also El Nino events that last more than one year.Moreover,we have found that multi-year long La Nina events tend to occur over the decades with strong El Nino events.The study also briefly explores the impact of global warming on the duration of ENSO events through the use of a simple model and simulations by CMIP6 models.It has been found that the frequency of multi-year El Nino and La Nina events increases with global warming.展开更多
Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many ...Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.展开更多
To investigate the effect of rail pad viscoelasticity on vehicle-track-bridge coupled vibration,the fractional Voigt and Maxwell model in parallel(FVMP)was used to characterize the viscoelastic properties of the rail ...To investigate the effect of rail pad viscoelasticity on vehicle-track-bridge coupled vibration,the fractional Voigt and Maxwell model in parallel(FVMP)was used to characterize the viscoelastic properties of the rail pad based on dynamic performance test results.The FVMP model was then incorporated into the vehicle-track-bridge nonlinear coupled model,and its dynamic response was solved using a cross-iteration algorithm with a relaxation factor.Results indicate that the nonlinear coupled model achieves good convergence when the time step is less than 0.001 s,with the cross-iteration algorithm adjusting the wheel-rail force.In particular,the best convergence is achieved when the relaxation factor is within the range of 0.3-0.5.The FVMP model effectively characterizes the viscoelasticity of rail pads across a temperature range of±20℃and a frequency range of 1-1000 Hz.The viscoelasticity of rail pads significantly affects high-frequency vibrations in the coupled system,particularly around 50 Hz,corresponding to the wheel-rail coupled resonance range.Considering rail pad viscoelasticity is essential for accurately predicting track structure vibrations.展开更多
Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit signifi...Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.展开更多
The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes...The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes in ENSO forecasts,resulting in significant progress.Most deep learning-based ENSO prediction models which primarily rely solely on reanalysis data may lead to challenges in intensity underestimation in long-term forecasts,reducing the forecasting skills.To this end,we propose a deep residual-coupled model prediction(Res-CMP)model,which integrates historical reanalysis data and coupled model forecast data for multiyear ENSO prediction.The Res-CMP model is designed as a lightweight model that leverages only short-term reanalysis data and nudging assimilation prediction results of the Community Earth System Model(CESM)for effective prediction of the Niño 3.4 index.We also developed a transfer learning strategy for this model to overcome the limitations of inadequate forecast data.After determining the optimal configuration,which included selecting a suitable transfer learning rate during training,along with input variables and CESM forecast lengths,Res-CMP demonstrated a high correlation ability for 19-month lead time predictions(correlation coefficients exceeding 0.5).The Res-CMP model also alleviated the spring predictability barrier(SPB).When validated against actual ENSO events,Res-CMP successfully captured the temporal evolution of the Niño 3.4 index during La Niña events(1998/99 and 2020/21)and El Niño events(2009/10 and 2015/16).Our proposed model has the potential to further enhance ENSO prediction performance by using coupled models to assist deep learning methods.展开更多
An important challenge in ensuring the long-term effectiveness of geological nuclear waste disposal is predicting the transportation of decay heat and gases released from nuclear waste canisters.In this study,thermo-h...An important challenge in ensuring the long-term effectiveness of geological nuclear waste disposal is predicting the transportation of decay heat and gases released from nuclear waste canisters.In this study,thermo-hydromechanical(THM)coupled simulations were conducted using the TOUGH + FLAC3D simulator to predict the THM behaviors of a generic nuclear waste repository over 100,000 years following closure.The designed engineered barrier system(EBS)consists of the waste canister,backfill,and concrete liner.The objective of this study is to evaluate the long-term performance of the repository in the presence of continued hydrogen(H_(2))and heat release around the canister.The simulation results show that thermal pressurization and gas accumulation significantly raise the pore pressure within the EBS and surrounding host rock,while the peak pore pressure is not likely to exceed the lithostatic stress so that there is no risk of widespread hydro-fracturing in the host rock.However,tension failure and fracturing can occur at the tunnel scale because of internal gas buildup.Meanwhile,the generated H_(2) continuously migrates outward and tends to accumulate in the concrete liner and excavation disturbed zone surrounding the tunnel because of lower capillary pressure.Nevertheless,the fluids that may contain radionuclides will not leach into the confining units over a 100,000-year time frame.Our analysis indicates that for the assumed disposal system in Opalinus Clay,the generated heat and gas can gradually be transported through the host rock without significantly disturbing the isolation characteristics of the repository.展开更多
To enhance the prediction accuracy of landslides in in Longyan City,China,this study developed a methodology for geologic hazard susceptibility assessment based on a coupled model composed of a Geographic Information ...To enhance the prediction accuracy of landslides in in Longyan City,China,this study developed a methodology for geologic hazard susceptibility assessment based on a coupled model composed of a Geographic Information System(GIS)with integrated spatial data,a frequency ratio(FR)model,and a random forest(RF)model(also referred to as the coupled FR-RF model).The coupled FR-RF model was constructed based on the analysis of nine influential factors,including distance from roads,normalized difference vegetation index(NDVI),and slope.The performance of the coupled FR-RF model was assessed using metrics such as Receiver Operating Characteristic(ROC)and Precision-Recall(PR)curves,yielding Area Under the Curve(AUC)values of 0.93 and 0.95,which indicate high predictive accuracy and reliability for geological hazard forecasting.Based on the model predictions,five susceptibility levels were determined in the study area,providing crucial spatial information for geologic hazard prevention and control.The contributions of various influential factors to landslide susceptibility were determined using SHapley Additive exPlanations(SHAP)analysis and the Gini index,enhancing the model interpretability and transparency.Additionally,this study discussed the limitations of the coupled FR-RF model and the prospects for its improvement using new technologies.This study provides an innovative method and theoretical support for geologic hazard prediction and management,holding promising prospects for application.展开更多
Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie conditio...Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.展开更多
This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and o...This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and ocean components of the coupled system are represented by the China Meteorological Administration’s Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS)and the LASG/IAP Climate system Ocean Model(LICOM),respectively.The Ocean Atmosphere Sea Ice Soil VersionH 3(OASIS3)software has been utilized for the exchange of momentum,heat,and freshwater fluxes between these two components.An assessment of the coupled model’s three-day predictions for five TCs’gales was conducted.Preliminary findings indicate that the predicted TC tracks show less sensitivity to oceanic influences than the predicted TC intensities.Significant improvement in predicting the surface TC gales has been achieved through coupling the ocean model.This improvement is attributed to the impact of the warmer ocean’s effect on TC intensification,counteracting the cooling effect of the cold wake.In summary,coupling has enhanced the model’s predictive capabilities for TC gales.A detailed assessment of the coupled model’s performance in predicting other tropical weather phenomena is forthcoming.展开更多
Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this st...Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.展开更多
In this paper,we first briefly review the history of air-sea coupled models,and then introduce the current status and recent advances of regional air-sea coupled models.In particular,we discuss the core technical and ...In this paper,we first briefly review the history of air-sea coupled models,and then introduce the current status and recent advances of regional air-sea coupled models.In particular,we discuss the core technical and scientific issues involved in the development of regional coupled models,including the coupling technique,lateral boundary conditions,the coupling with sea waves(ices),and data assimilation.Furthermore,we introduce the application of regional coupled models in numerical simulation and dynamical downscaling.Finally,we discuss the existing problems and future directions in the development of regional air-sea coupled models.展开更多
In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems： the Lorenz model, which possesses a single characteristic time scale, and the c...In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems： the Lorenz model, which possesses a single characteristic time scale, and the coupled Lorenz model, which possesses two different characteristic time scales. The limit of predictability is defined here as the time at which the error reaches 95% of its saturation level; nonlinear behaviors of the error growth are therefore involved in the definition of the limit of predictability. Our results show that the logarithmic function performs well in describing the relationship between the limit of predictability and initial error in both models, although the coefficients in the logarithmic function were not constant across the examined range of initial errors. Compared with the Lorenz model, in the coupled Lorenz model in which the slow dynamics and the fast dynamics interact with each other--there is a more complex relationship between the limit of predictability and initial error. The limit of predictability of the Lorenz model is unbounded as the initial error becomes infinitesimally small; therefore, the limit of predictability of the Lorenz model may be extended by reducing the amplitude of the initial error. In contrast, if there exists a fixed initial error in the fast dynamics of the coupled Lorenz model, the slow dynamics has an intrinsic finite limit of predictability that cannot be extended by reducing the amplitude of the initial error in the slow dynamics, and vice versa. The findings reported here reveal the possible existence of an intrinsic finite limit of predictability in a coupled system that possesses many scales of time or motion.展开更多
This study evaluates the fidelity of Arctic and Antarctic oscillations（AO and AAO for short,respectively） in the coupled general circulation models participating in the Fourth Assessment Report of Intergovernmental ...This study evaluates the fidelity of Arctic and Antarctic oscillations（AO and AAO for short,respectively） in the coupled general circulation models participating in the Fourth Assessment Report of Intergovernmental Panel on Climate Change（IPCC AR4）.The AO and AAO during 1970-1999 in 24 models are analyzed and compared with that in ERA-40 and NCEP-1.Models＇ performance is seasonally dependent,with best reproducibility of both spatial structure and trend in winter.In most models,the spatial pattern and temporal trend of AAO during this period are more delicately simulated than AO.After picking out models with better performance according to the Taylor diagram,we find that their ensemble mean can obviously improve models＇ reproducibility.The AO and AAO in the Special Report on Emission Scenarios（SRES） A1B Projection during the 21st century are also briefly analyzed.The results reveal that both the AO and AAO indices keep increasing during 1970-2099,with a steadier pace of AO than AAO.The spatial difference of sea level pressure between 2060-2089 and 1970-1999 shows decreased values in polar regions,and increased values in midlatitudes.The results manifest that the ozone recovery during the mid 21st century may not weaken such a trend.展开更多
文摘The Chang-63 reservoir in the Huaqing area has widely developed tight sandstone ＂thick sand layers, but not reservoirs characterized by rich in oil＂, and it is thus necessary to further study its oil and gas enrichment law. This study builds porosity and fracture development and evolution models in different deposition environments, through core observation, casting thin section, SEM, porosity and permeability analysis, burial history analysis, and ＂four-property-relationships＂ analysis.
基金supported by the National Key Research and Development Program of China Grant No. 2019YFC1510004Natural Science Foundation of Jiangsu Province Grant No. BK20190781+2 种基金the General Program of Natural Science Foundation of Jiangsu Higher Education Institutions Grant No. 19KJB170019the open fund of State Key Laboratory of Loess and Quaternary Geology Grant No. SKLLQG1802the LASG Open Project。
文摘The simulated sea surface temperature anomaly(SSTA)over the tropical Pacific during El Ni?o–Southern Oscillation(ENSO)is investigated in three representative coupled models:CESM1-CAM5,FGOALS-s2,and FGOALS-g2.It is found that there is a significant westward shift bias in reproducing the zonal distribution(ZD)of the ENSO-related SSTA in CESM1-CAM5 and FGOALS-s2,whereas the SSTA-ZD simulated by FGOALS-g2 is relatively realistic.Through examining the SSTA-ZD during both warm and cold phases of ENSO separately,the authors reveal that the SSTA-ZD simulation bias during the ENSO cycle mainly lies in the bias during the warm phase.It is noted that both the simulated zonal wind stress anomaly(τ’_x)and shortwave heat flux(SW)anomaly exhibit westward shift biases in CESM1-CAM5 and FGOALS-s2,while the counterparts in FGOALS-g2 are relatively reasonable.The westward shift biases in representingτ’_x and the SW anomaly(SWA)are attributed to the westward-shifted precipitation anomaly(PrA).It is suggested that the mean SST cold bias over the cold tongue region is the key factor behind the westward-shift bias in simulating the El Ni?o-related PrA,which leads to the westward-shiftedτ’_x and SWA.Collectively,the aforementioned anomaly fields,including the dynamic part(τ’_x)and thermodynamic part(SWA),contribute to the westward-shift bias in simulating the El Ni?o-related SSTA.This study provides clues for understanding the ZD simulation biases of ENSO-related fields;however,further in-depth investigation with more model simulations,especially the incoming CMIP6 simulations,is still needed to fully understand the ENSO SSTA-ZD simulation bias in coupled models.
基金This research was jointly supported by the Chinese Academy of Sciences(CAS)under Grant No.KZCX3-SW-221by the National Natural Science Foundation of China under Grant No.40405015+1 种基金by the Chinese Ministry of Science and Technology under Grant No.2001BA611B(part 1)by the CAS“Hundred Talent Project"funding awarded to Gao Yongqi.
文摘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.
基金This work was jointly supported by the National Natural Science Foundation of China （Grant Nos. 40523001, 40221503, 40675050）Major State Basic Research Development Program of China under Grant Nos. 2005CB321703, 2006CB403603the International Partnership Creative Group entitled ＂The Climate System Model Development and Application Studies＂.
文摘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.
基金supported by the National Key Research&Development Program of China(Grant Nos.2017YFC1404100 and 2017YFC1404104)the National Natural Science Foundation of China(Grant Nos.41775100 and 41830964)。
文摘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.
基金supported by the National Key R&D Program of China[grant number 2017YFA0603802]the National Natural Science Foundation of China[grant numbers 41661144005,41320104007,and 41575086]the CAS-PKU(Chinese Academy of Sciences-Peking University) Joint Research Program
文摘The authors examine the spatial and temporal characteristics of the simulated Pacific Decadal Oscillation （PDO） in 109 historical （i.e. all forcings） simulations derived from 25 coupled models within CMIPS. Compared with observations, most simulations successfully simulate the observed PDO pattern and its teleconnections to the SSTs in the tropical and southern Pacific. BNU-ESM, CanESM2, CCSM4, CESM 1 -FASTCHEM, FGOALS-g2, GFDL CM3, MIROCS, and NorESM 1 -M show better performance. Compared with the temporal phases of the observed PDO in the twentieth century, only five simulations -- from CNRM^CMS, CSIRO Mk3o6.0, HadCM3, and IPSL-CMSA-LR -- simulate an evolution of the PDO similar to that derived from observation, which suggests that current coupled models can barely reproduce the observed phase shifting of the PDO. To capture characteristics of the observed PDO in the twentieth century, a requirement is that all the relevant external forcings are included in the models. How to add realistic oceanic initial states into the model may be another key point.
基金Supported by the National Natural Science Foundation of China(No.41976012)the Key Research Program of Laoshan Laboratory(LSL)(No.LSKJ 202202502)the Strategic Priority Research Program of Chinese Academy of Sciences(CAS)(No.XDB 42000000)。
文摘The coupling between wind stress perturbations and sea surface temperature(SST)perturbations induced by tropical instability waves(TIWs)in the Pacific Ocean has been revealed previously and proven crucial to both the atmosphere and ocean.However,an overlooked fact by previous studies is that the loosely defined“TIWs”actually consist of two modes,including the Yanai wave-based TIW on the equator(hereafter eTIW)and the Rossby wave-based TIW off the equator(hereafter vTIW).Hence,the individual feedbacks of the wind stress to the bimodal TIWs remain unexplored.In this study,individual coupling relationships are established for both eTIW and v TIW,including the relationship between the TIW-induced SST perturbations and two components of wind stress perturbations,and the relationship between the TIW-induced wind stress perturbation divergence(curl)and the downwind(crosswind)TIW-induced SST gradients.Results show that,due to different distributions of eTIW and vTIW,the coupling strength induced by the eTIW is stronger on the equator,and that by the vTIW is stronger off the equator.The results of any of eTIW and vTIW are higher than those of the loosely defined TIWs.We further investigated how well the coupling relationships remained in several widely recognized oceanic general circulation models and fully coupled climate models.However,the coupling relationships cannot be well represented in most numerical models.Finally,we confirmed that higher resolution usually corresponds to more accurate simulation.Therefore,the coupling models established in this study are complementary to previous research and can be used to refine the oceanic and coupled climate models.
基金The National Natural Science Foundation of China under contract No.42250710154。
文摘The magnitude of El Nino determines the level of its global impact.Yet,how well our state-of-the-art models simulate this key aspect of El Nino is not well documented.Previous studies tend to ignore El Nino-Southern Oscillation(ENSO)asymmetry and equate the variance of ENSO to the magnitude of El Nino.Moreover,previous evaluations are more focused on the surface manifestation of El Nino.Here,we quantify the magnitudes of El Nino and La Nina separately,both at the surface and subsurface levels.At the surface,we find that while the magnitude of La Nina events in most models is generally stronger than observed,the magnitude of El Nino is more diverse to observations.In fact,in many models,El Nino is weaker than observed.This bias in the magnitude of El Nino is more pronounced in the subsurface.We attribute this weakness in the subsurface to the generally weaker coupling strength and the apparent stronger ENSO at the surface to a lack of sufficiently strong negative feedback from the surface heat flux in the models.When normalized by the variance of ENSO,the lack of exceptionally strong El Nino events in the models is more common and pronounced.We further studied the lifespan of El Nino and La Nina events and have found that multi-year duration is not confined to just La Nina events.There are also El Nino events that last more than one year.Moreover,we have found that multi-year long La Nina events tend to occur over the decades with strong El Nino events.The study also briefly explores the impact of global warming on the duration of ENSO events through the use of a simple model and simulations by CMIP6 models.It has been found that the frequency of multi-year El Nino and La Nina events increases with global warming.
基金supported by the National Natural Science Foundation of China(Grant No.42076214)Natural Science Foundation of Shandong Province(Grant No.ZR2024QD057).
文摘Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.
基金Project(2023ZDZX0008)supported by the Sichuan Major Science and Technology Project,ChinaProject(52308468)supported by the National Natural Science Foundation of ChinaProject(2022JBQY009)supported by the Fundamental Research Funds for the Central Universities(Science and Technology Leading Talent Team Project),China。
文摘To investigate the effect of rail pad viscoelasticity on vehicle-track-bridge coupled vibration,the fractional Voigt and Maxwell model in parallel(FVMP)was used to characterize the viscoelastic properties of the rail pad based on dynamic performance test results.The FVMP model was then incorporated into the vehicle-track-bridge nonlinear coupled model,and its dynamic response was solved using a cross-iteration algorithm with a relaxation factor.Results indicate that the nonlinear coupled model achieves good convergence when the time step is less than 0.001 s,with the cross-iteration algorithm adjusting the wheel-rail force.In particular,the best convergence is achieved when the relaxation factor is within the range of 0.3-0.5.The FVMP model effectively characterizes the viscoelasticity of rail pads across a temperature range of±20℃and a frequency range of 1-1000 Hz.The viscoelasticity of rail pads significantly affects high-frequency vibrations in the coupled system,particularly around 50 Hz,corresponding to the wheel-rail coupled resonance range.Considering rail pad viscoelasticity is essential for accurately predicting track structure vibrations.
基金Supported by the Laoshan Laboratory(No.LSKJ 202202404)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB 42000000)+1 种基金the National Natural Science Foundation of China(NSFC)(No.42030410)the Startup Foundation for Introducing Talent of NUIST,and the Jiangsu Innovation Research Group(No.JSSCTD 202346)。
文摘Numerical models are crucial for quantifying the ocean-atmosphere interactions associated with the El Niño-Southern Oscillation(ENSO)phenomenon in the tropical Pacific.Current coupled models often exhibit significant biases and inter-model differences in simulating ENSO,underscoring the need for alternative modeling approaches.The Regional Ocean Modeling System(ROMS)is a sophisticated ocean model widely used for regional studies and has been coupled with various atmospheric models.However,its application in simulating ENSO processes on a basin scale in the tropical Pacific has not been explored.For the first time,this study presents the development of a basin-scale hybrid coupled model(HCM)for the tropical Pacific,integrating ROMS with a statistical atmospheric model that captures the interannual relationships between sea surface temperature(SST)and wind stress anomalies.The HCM is evaluated for its capability to simulate the annual mean,seasonal,and interannual variations of the oceanic state in the tropical Pacific.Results demonstrate that the model effectively reproduces the ENSO cycle,with a dominant oscillation period of approximately two years.The ROMS-based HCM developed here offers an efficient and robust tool for investigating climate variability in the tropical Pacific.
基金The National Key Research and Development Program of China under contract Nos 2024YFF0808900,2023YFF0805300,and 2020YFA0608804the Civilian Space Programme of China under contract No.D040305.
文摘The El Niño-Southern Oscillation(ENSO)is a naturally recurring interannual climate fluctuation that affects the global climate system.The advent of deep learning-based approaches has led to transformative changes in ENSO forecasts,resulting in significant progress.Most deep learning-based ENSO prediction models which primarily rely solely on reanalysis data may lead to challenges in intensity underestimation in long-term forecasts,reducing the forecasting skills.To this end,we propose a deep residual-coupled model prediction(Res-CMP)model,which integrates historical reanalysis data and coupled model forecast data for multiyear ENSO prediction.The Res-CMP model is designed as a lightweight model that leverages only short-term reanalysis data and nudging assimilation prediction results of the Community Earth System Model(CESM)for effective prediction of the Niño 3.4 index.We also developed a transfer learning strategy for this model to overcome the limitations of inadequate forecast data.After determining the optimal configuration,which included selecting a suitable transfer learning rate during training,along with input variables and CESM forecast lengths,Res-CMP demonstrated a high correlation ability for 19-month lead time predictions(correlation coefficients exceeding 0.5).The Res-CMP model also alleviated the spring predictability barrier(SPB).When validated against actual ENSO events,Res-CMP successfully captured the temporal evolution of the Niño 3.4 index during La Niña events(1998/99 and 2020/21)and El Niño events(2009/10 and 2015/16).Our proposed model has the potential to further enhance ENSO prediction performance by using coupled models to assist deep learning methods.
基金Funding was provided by the U.S.Department of Energy,Office of Nuclear Energy,Spent Fuel and Waste Disposition,under Contract Number DE-AC02-05CH11231 with Lawrence Berkeley National Laboratory(LBNL).
文摘An important challenge in ensuring the long-term effectiveness of geological nuclear waste disposal is predicting the transportation of decay heat and gases released from nuclear waste canisters.In this study,thermo-hydromechanical(THM)coupled simulations were conducted using the TOUGH + FLAC3D simulator to predict the THM behaviors of a generic nuclear waste repository over 100,000 years following closure.The designed engineered barrier system(EBS)consists of the waste canister,backfill,and concrete liner.The objective of this study is to evaluate the long-term performance of the repository in the presence of continued hydrogen(H_(2))and heat release around the canister.The simulation results show that thermal pressurization and gas accumulation significantly raise the pore pressure within the EBS and surrounding host rock,while the peak pore pressure is not likely to exceed the lithostatic stress so that there is no risk of widespread hydro-fracturing in the host rock.However,tension failure and fracturing can occur at the tunnel scale because of internal gas buildup.Meanwhile,the generated H_(2) continuously migrates outward and tends to accumulate in the concrete liner and excavation disturbed zone surrounding the tunnel because of lower capillary pressure.Nevertheless,the fluids that may contain radionuclides will not leach into the confining units over a 100,000-year time frame.Our analysis indicates that for the assumed disposal system in Opalinus Clay,the generated heat and gas can gradually be transported through the host rock without significantly disturbing the isolation characteristics of the repository.
基金supported by the project of the China Geological Survey(DD20230591).
文摘To enhance the prediction accuracy of landslides in in Longyan City,China,this study developed a methodology for geologic hazard susceptibility assessment based on a coupled model composed of a Geographic Information System(GIS)with integrated spatial data,a frequency ratio(FR)model,and a random forest(RF)model(also referred to as the coupled FR-RF model).The coupled FR-RF model was constructed based on the analysis of nine influential factors,including distance from roads,normalized difference vegetation index(NDVI),and slope.The performance of the coupled FR-RF model was assessed using metrics such as Receiver Operating Characteristic(ROC)and Precision-Recall(PR)curves,yielding Area Under the Curve(AUC)values of 0.93 and 0.95,which indicate high predictive accuracy and reliability for geological hazard forecasting.Based on the model predictions,five susceptibility levels were determined in the study area,providing crucial spatial information for geologic hazard prevention and control.The contributions of various influential factors to landslide susceptibility were determined using SHapley Additive exPlanations(SHAP)analysis and the Gini index,enhancing the model interpretability and transparency.Additionally,this study discussed the limitations of the coupled FR-RF model and the prospects for its improvement using new technologies.This study provides an innovative method and theoretical support for geologic hazard prediction and management,holding promising prospects for application.
基金a U.S. Federal Railroad Administration (FRA)BAA project,titled “Mitigation of Differential Movement at Railway Transitions for High-Speed Passenger Rail and Joint Passenger/Freight Corridors”the financial support provided by the China Scholarship Council (CSC),which funded Zhongyi Liu’s and Wenjing Li’s time and research efforts for this study
文摘Nonuniform track support and differential settlements are commonly observed in bridge approaches where the ballast layer can develop gaps at crosstie-ballast interfaces often referred to as a hanging crosstie condition.Hanging crossties usually yield unfavorable dynamic effects such as higher wheel loads,which negatively impact the serviceability and safety of railway operations.Hence,a better understanding of the mechanisms that cause hanging crossties and their effects on the ballast layer load-deformation characteristics is necessary.Since the ballast layer is a particulate medium,the discrete element method(DEM),which simulates ballast particle interactions individually,is ideal to explore the interparticle contact forces and ballast movements under dynamic wheel loading.Accurate representations of the dynamic loads from the train and track superstructure are needed for high-fidelity DEM modeling.This paper introduces an integrated modeling approach,which couples a single-crosstie DEM ballast model with a train–track–bridge(TTB)model using a proportional–integral–derivative control loop.The TTB–DEM model was validated with field measurements,and the coupled model calculates similar crosstie displacements as the TTB model.The TTB–DEM provided new insights into the ballast particle-scale behavior,which the TTB model alone cannot explore.The TTB–DEM coupling approach identified detrimental effects of hanging crossties on adjacent crossties,which were found to experience drastic vibrations and large ballast contact force concentrations.
基金supported by the National Key R&D Program of China [grant number 2023YFC3008005]the Guangdong Basic and Applied Basic Research Foundation [grant numbers 2022A1515011288 and 2024A1515030210]+1 种基金the Key Innovation Team of the China Meteorological Administration [grant number CMA2023ZD08]the Guangdong Provincial Marine Meteorology Science Data Center [grant number 2024B1212070014]。
文摘This paper provides a comparative analysis of the performance of a high-resolution regional ocean-atmosphere coupled model in predicting tropical cyclone(TC)gales over the northern South China Sea.The atmosphere and ocean components of the coupled system are represented by the China Meteorological Administration’s Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS)and the LASG/IAP Climate system Ocean Model(LICOM),respectively.The Ocean Atmosphere Sea Ice Soil VersionH 3(OASIS3)software has been utilized for the exchange of momentum,heat,and freshwater fluxes between these two components.An assessment of the coupled model’s three-day predictions for five TCs’gales was conducted.Preliminary findings indicate that the predicted TC tracks show less sensitivity to oceanic influences than the predicted TC intensities.Significant improvement in predicting the surface TC gales has been achieved through coupling the ocean model.This improvement is attributed to the impact of the warmer ocean’s effect on TC intensification,counteracting the cooling effect of the cold wake.In summary,coupling has enhanced the model’s predictive capabilities for TC gales.A detailed assessment of the coupled model’s performance in predicting other tropical weather phenomena is forthcoming.
基金jointly funded by the National Natural Science Foundation of China(NSFC)[grant number 42130608]the China Postdoctoral Science Foundation[grant number 2024M753169]。
文摘Arctic sea ice is an important component of the global climate system and has experienced rapid changes during in the past few decades,the prediction of which is a significant application for climate models.In this study,a Localized Error Subspace Transform Kalman Filter is employed in a coupled climate system model(the Flexible Global Ocean–Atmosphere–Land System Model,version f3-L(FGOALS-f3-L))to assimilate sea-ice concentration(SIC)and sea-ice thickness(SIT)data for melting-season ice predictions.The scheme is applied through the following steps:(1)initialization for generating initial ensembles;(2)analysis for assimilating observed data;(3)adoption for dividing ice states into five thickness categories;(4)forecast for evolving the model;(5)resampling for updating model uncertainties.Several experiments were conducted to examine its results and impacts.Compared with the control experiment,the continuous assimilation experiments(CTNs)indicate assimilations improve model SICs and SITs persistently and generate realistic initials.Assimilating SIC+SIT data better corrects overestimated model SITs spatially than when only assimilating SIC data.The continuous assimilation restart experiments indicate the initials from the CTNs correct the overestimated marginal SICs and overall SITs remarkably well,as well as the cold biases in the oceanic and atmospheric models.The initials with SIC+SIT assimilated show more reasonable spatial improvements.Nevertheless,the SICs in the central Arctic undergo abnormal summer reductions,which is probably because overestimated SITs are reduced in the initials but the strong seasonal cycle(summer melting)biases are unchanged.Therefore,since systematic biases are complicated in a coupled system,for FGOALS-f3-L to make better ice predictions,oceanic and atmospheric assimilations are expected required.
基金supported by Knowledge Innovation Program of Chinese Academy of Sciences (Grant Nos. KZCX2-EW-208 and KZCX2-YW-Q11-02)the MOST of China (Grant No. 2011CB403504)National Natural Science Foundation of China (Grant No. 41076009)
文摘In this paper,we first briefly review the history of air-sea coupled models,and then introduce the current status and recent advances of regional air-sea coupled models.In particular,we discuss the core technical and scientific issues involved in the development of regional coupled models,including the coupling technique,lateral boundary conditions,the coupling with sea waves(ices),and data assimilation.Furthermore,we introduce the application of regional coupled models in numerical simulation and dynamical downscaling.Finally,we discuss the existing problems and future directions in the development of regional air-sea coupled models.
基金sprovided jointly by the 973 Program (Grant No.2010CB950400)National Natural Science Foundation of China (Grant Nos. 40805022 and 40821092)
文摘In this study, the relationship between the limit of predictability and initial error was investigated using two simple chaotic systems： the Lorenz model, which possesses a single characteristic time scale, and the coupled Lorenz model, which possesses two different characteristic time scales. The limit of predictability is defined here as the time at which the error reaches 95% of its saturation level; nonlinear behaviors of the error growth are therefore involved in the definition of the limit of predictability. Our results show that the logarithmic function performs well in describing the relationship between the limit of predictability and initial error in both models, although the coefficients in the logarithmic function were not constant across the examined range of initial errors. Compared with the Lorenz model, in the coupled Lorenz model in which the slow dynamics and the fast dynamics interact with each other--there is a more complex relationship between the limit of predictability and initial error. The limit of predictability of the Lorenz model is unbounded as the initial error becomes infinitesimally small; therefore, the limit of predictability of the Lorenz model may be extended by reducing the amplitude of the initial error. In contrast, if there exists a fixed initial error in the fast dynamics of the coupled Lorenz model, the slow dynamics has an intrinsic finite limit of predictability that cannot be extended by reducing the amplitude of the initial error in the slow dynamics, and vice versa. The findings reported here reveal the possible existence of an intrinsic finite limit of predictability in a coupled system that possesses many scales of time or motion.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 40523001 and 40631005Chinese Academy of Sciences under Grant Nos. KZCX2-YW-Q1-02 and KZCX2-YW-Q11-05
文摘This study evaluates the fidelity of Arctic and Antarctic oscillations（AO and AAO for short,respectively） in the coupled general circulation models participating in the Fourth Assessment Report of Intergovernmental Panel on Climate Change（IPCC AR4）.The AO and AAO during 1970-1999 in 24 models are analyzed and compared with that in ERA-40 and NCEP-1.Models＇ performance is seasonally dependent,with best reproducibility of both spatial structure and trend in winter.In most models,the spatial pattern and temporal trend of AAO during this period are more delicately simulated than AO.After picking out models with better performance according to the Taylor diagram,we find that their ensemble mean can obviously improve models＇ reproducibility.The AO and AAO in the Special Report on Emission Scenarios（SRES） A1B Projection during the 21st century are also briefly analyzed.The results reveal that both the AO and AAO indices keep increasing during 1970-2099,with a steadier pace of AO than AAO.The spatial difference of sea level pressure between 2060-2089 and 1970-1999 shows decreased values in polar regions,and increased values in midlatitudes.The results manifest that the ozone recovery during the mid 21st century may not weaken such a trend.
