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
This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences(CAMS)climate system model(CAMS-CSM),which are contributing to phase 6 of the Coupled Model Intercomparison Pro...This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences(CAMS)climate system model(CAMS-CSM),which are contributing to phase 6 of the Coupled Model Intercomparison Project(CMIP6).The model description,experiment design and model outputs are presented.Three members’historical experiments are conducted by CAMS-CSM,with two members starting from different initial conditions,and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions.The outputs of the historical experiments are also validated using observational data.It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities,including the surface air temperature,precipitation,and the equatorial thermocline.The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM.There are still some biases in the model that need further improvement.This paper can help the users to better understand the performance and the datasets of CAMS-CSM.展开更多
An experiment using the Community Climate System Model(CCSM4), a participant of the Coupled Model Intercomparison Project phase-5(CMIP5), is analyzed to assess the skills of this model in simulating and predicting the...An experiment using the Community Climate System Model(CCSM4), a participant of the Coupled Model Intercomparison Project phase-5(CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole(IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.展开更多
A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nu...A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nucleus for European Modelling of the Ocean（NEMO）, and version 4.1 of the Los Alamos sea ice model（CICE）. The model is referred to as NUIST ESM1（NESM1）. Comprehensive and quantitative metrics are used to assess the model＇s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model＇s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific（CP）-ENSO and eastern Pacific（EP）-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation（MJO）, and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version（T159） demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.展开更多
This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Res...This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics （CMSR, IAP）, Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of E1 Nifio as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature （SST） and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate E1 Nifio and the East Asia-Pacific Pattern--are also well simulated in ICM, with realistic spatial pattern and period. The simulated E1 Nifio has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.展开更多
Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a centra...Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a central focus of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences(LASG/IAP) since the establishment of the laboratory in 1985. In China, many pioneering component models and fully coupled models of the climate system have been developed by LASG/IAP. The fully coupled climate system developed in the recent decade is named FGOALS(Flexible Global Ocean-Atmosphere-Land System Model). In this paper, an application-oriented review of the LASG/IAP FGOALS model is presented. The improved model performances are demonstrated in the context of cloud-radiation processes, Asian monsoon, ENSO phenomena, Atlantic Meridional Overturning Circulation(AMOC) and sea ice. The FGOALS model has contributed to both CMIP5(Coupled Model Intercomparison Project-phase 5) and IPCC(Intergovernmental Panel on Climate Change) AR5(the Fifth Assessment Report). The release of FGOALS data has supported the publication of nearly 500 papers around the world. The results of FGOALS are cited ~106 times in the IPCC WG1(Working Group 1) AR5. In addition to the traditional long-term simulations and projections, near-term decadal climate prediction is a new set of CMIP experiment, progress of LAGS/IAP in the development of nearterm decadal prediction system is reviewed. The FGOALS model has supported many Chinese national-level research projects and contributed to the national climate change assessment report. The crucial role of FGOALS as a modeling tool for supporting climate sciences is highlighted by demonstrating the model's performances in the simulation of the evolution of Earth's climate from the past to the future.展开更多
A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses t...A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model （FGOALS-gl） developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics （LASG/IAP）. The model presents a reasonable performance in comparison with reconstructions of surface temperature. Differentiated from significant changes in the 20th century at the global scale, changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere. Seasonally, modeled significant changes are more pronounced during the wintertime at higher latitudes. This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback. The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period, especially at decadal timescales. Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability. The model response to specified external forcings is modulated by cloud radiative forcing （CRF）. The CRF acts against the fluctuations of external forcings. Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period, but mainly in longwave radiation by a decrease in cloud amount in the ant hropogenic- forcing-dominant period.展开更多
Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation ...Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation was carried out with fixed external forcing factors （1850 Common Era. （C.E.） conditions） for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the E1 Nifio-Southem Oscillation （ENSO）, the Atlantic Multi-decadal Oscilla- tion （AMO）, the Pacific Decadal Oscillation （PDO）, and the North Atlantic Oscillation （NAO）, were compared with reanalysis datasets to evaluate the model performance. The results are as follows： 1） CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2） climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3） the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3-8 years vari- ability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natu- ral variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.展开更多
On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences （CAS-ESM-C） in simulating the E1 Nifio-Southern Oscillation （ENSO） cycle is evalu- ated, i...On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences （CAS-ESM-C） in simulating the E1 Nifio-Southern Oscillation （ENSO） cycle is evalu- ated, including the onset, development and decay of the ENSO. It is shown that, the model can reasonably simulate the annual cycle and interannual variability of sea surface temperature （SST） in the tropical Pacif- ic, as well as the seasonal phase-locking of the ENSO. The model also captures two prerequisites for the E1 Nino onset, i.e., a westerly anomaly and a warm SST anomaly in the equatorial western Pacific. Owing to too strong forcing from an extratropical meridional wind, however, the westerly anomaly in this region is largely overestimated. Moreover, the simulated thermocline is much shallower with a weaker slope. As a result, the warm SST anomaly from the western Pacific propagates eastward more quickly, leading to a faster develop- ment of an E1 Nino. During the decay stage, owing to a stronger E1Nino in the model, the secondary Gill-type response of the tropical atmosphere to the eastern Pacific warming is much stronger, thereby resulting in a persistent easterly anomaly in the western Pacific. Meanwhile, a cold anomaly in the warm pool appears as a result of a lifted thermocline via Ekman pumping. Finally, an E1 Nino decays into a La Nina through their interactions. In addition, the shorter period and larger amplitude of the ENSO in the model can be attribut- ed to a shallower thermocline in the equatorial Pacific, which speeds up the zonal redistribution of a heat content in the upper ocean.展开更多
Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food...Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food security in the southern African region. In this study, evidence for climate change impacts and adaptation strategies in rainfed agricultural systems is explored through modeling predictions of crop yield, soil moisture and excess water for potential harvesting. The study specifically presents the results of climate change impacts under rainfed conditions for maize, sorghum and sunflower using soil-water-crop model simulations, integrated based on daily inputs of rainfall and evapotranspiration disaggregated from GCM scenarios. The research targets a vast farming region dominated by heavy clay soils where rainfed agriculture is a dominant practice. The potential for improving soil water productivity and improved water harvesting have been explored as ways of climate change mitigation and adaptation measures. This can be utilized to explore and design appropriate conservation agriculture and adaptation practices in similar agro-ecological environments, and create opportunities for outscaling for much wider areas. The results of this study can suggest the need for possible policy refinements towards reducing vulnerability and adaptation to climate change in rainfed farming systems.展开更多
The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main i...The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.展开更多
Based on simulations using the University of Victoria's Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 fol...Based on simulations using the University of Victoria's Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 following the RCP 8.5 scenario and its extension. Compared to simulations without climate change, the simulation with a climate sensitivity of 3.0 K shows that in 2100, due to increased atmospheric CO2 concentrations, the simulated sea surface temperature increases by 2.7 K, the intensity of the North Atlantic deep water formation reduces by4.5 Sv, and the oceanic uptake of anthropogenic CO2 decreases by 0.8 Pg C. Climate change is also found to have a large effect on the North Atlantic's ocean column inventory of anthropogenic CO2. Between the years 1800 and 2500, compared with the simulation with no climate change, the simulation with climate change causes a reduction in the total anthropogenic CO2 column inventory over the entire ocean and in North Atlantic by 23.1% and 32.0%, respectively. A set of simulations with climate sensitivity variations from 0.5 K to 4.5 K show that with greater climate sensitivity climate change would have a greater effect in reducing the ocean's ability to absorb CO2 from the atmosphere.展开更多
The prediction skill of Arctic Oscillation (AO) in the decadal experiments with the Beijing Climate Center Climate System Model version 1.1 (BCC_CSM1.1) is assessed. As compared with the observations and historical ex...The prediction skill of Arctic Oscillation (AO) in the decadal experiments with the Beijing Climate Center Climate System Model version 1.1 (BCC_CSM1.1) is assessed. As compared with the observations and historical experiments, the contribution of initialization for climate model to predict the seasonal scale AO and its interannual variations is estimated. Results show that the spatial correlation coefficient of AO mode simulated by the decadal experiment is higher than that in the historical experiment. The two groups of experiments reasonably reproduce the characteristics that AO indices are the strongest in winter and the weakest in summer. Compared with historical experiments, the correlation coefficient of the monthly and winter AO indices are higher in the decadal experiments. In particular, the correlation coefficient of monthly AO index between decadal hindcast and observation reached 0.1 significant level. Furthermore, the periodicity of the monthly and spring AO indices are achieved only in the decadal experiments. Therefore, the initial state of model is initialized by using sea temperature data may help to improve the prediction skill of AO in the decadal prediction experiments to some extent.展开更多
A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and...A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.展开更多
In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly explo...In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.展开更多
The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to e...The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to evaluate probable species’ distribution under climate change and contribute to decision-making to define efficient management strategies. A model was developed to forecast which habitat was most likely appropriate for the Dalbergia odorifera. We screened the main climatic variables that describe the current geographic distribution of the species based on maximum entropy modelling (Maxent). We subsequently assessed its potential future distribution under moderate (RCP2.6) and severe (RCP8.5) climate change scenarios for the years 2050 and 2070. The precipitation ranges of the wettest month and the warmest quarter are the primary limiting factors for the current distribution of D. odorifera among the climatic predictors. Climate change will be expected to have beneficial effects on the distribution range of D. odorifera. In conclusion, the main limits for the distribution of D. odorifera are determined by the level of precipitation and human activities. The results of this study indicate that the coasts of southern China and Chongqing will play a key role in the protection and restoration of D. odorifera in the future.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives ...Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.展开更多
采用累积频率的统计方法和Community Climate Model 3(CCM3)模拟的10年逐日降水结果,分析了模拟的夏季极端降水事件的时空分布特征.结果表明,CCM3模拟的极端降水阈值的大值区主要在我国黄河和长江流域的上游、印度半岛及其邻近海域和孟...采用累积频率的统计方法和Community Climate Model 3(CCM3)模拟的10年逐日降水结果,分析了模拟的夏季极端降水事件的时空分布特征.结果表明,CCM3模拟的极端降水阈值的大值区主要在我国黄河和长江流域的上游、印度半岛及其邻近海域和孟加拉湾及其北部地区.CCM3能够模拟出我国长江流域极端降水量与极端降水日数显著增加的趋势.对极端降水平均强度、降水日数以及极端降水量与总降水量比值的经验正交函数(EOF)分析可知,我国大部分地区的极端降水基本呈现同相变化,且以长江和黄河中游地区较为显著.CCM3模式基本能够模拟出观测到的极端降水阈值与总降水、极端降水日数及其距平的高空间相关性.展开更多
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 the National Key Research and Development Program of China(Grant No.2019YFC1510001)the National Natural Science Foundation of China(Grant No.91637210)+1 种基金the Basic Research Fund of CAMS(Grant No.2018Z007)the Jiangsu Collaborative Innovation Center for Climate Change。
文摘This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences(CAMS)climate system model(CAMS-CSM),which are contributing to phase 6 of the Coupled Model Intercomparison Project(CMIP6).The model description,experiment design and model outputs are presented.Three members’historical experiments are conducted by CAMS-CSM,with two members starting from different initial conditions,and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions.The outputs of the historical experiments are also validated using observational data.It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities,including the surface air temperature,precipitation,and the equatorial thermocline.The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM.There are still some biases in the model that need further improvement.This paper can help the users to better understand the performance and the datasets of CAMS-CSM.
基金the National Basic Research Program of China(973 Program)(No.2012CB956000)the Strategic Priority Project of Chinese Academy of Sciences(No.XDA11010301)+2 种基金the National Natural Science Foundation of China(Nos.41421005,U1406401)the Public Welfare Grant of China Meteorological Administration(No.GYHY201306018)the Global Change and Air-Sea Interactions of State Oceanic Administration(No.GASI-03-01-01-05)
文摘An experiment using the Community Climate System Model(CCSM4), a participant of the Coupled Model Intercomparison Project phase-5(CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole(IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.
基金supported by the Research Innovation Program for college graduates of Jiangsu Province (CXLX13 487)
文摘A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nucleus for European Modelling of the Ocean（NEMO）, and version 4.1 of the Los Alamos sea ice model（CICE）. The model is referred to as NUIST ESM1（NESM1）. Comprehensive and quantitative metrics are used to assess the model＇s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model＇s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific（CP）-ENSO and eastern Pacific（EP）-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation（MJO）, and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version（T159） demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.
基金supported by the National Basic Research Program of China (Grant Nos.2012CB955604 and 2014CB953903)the National Natural Sciences Foundation of China (Grant No.41375112)
文摘This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics （CMSR, IAP）, Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of E1 Nifio as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature （SST） and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate E1 Nifio and the East Asia-Pacific Pattern--are also well simulated in ICM, with realistic spatial pattern and period. The simulated E1 Nifio has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.
基金supported by the National Natural Science Foundation of China (Grant No. 41330423, 41420104006 & 41530426 )the International Partnership Program of Chinese Academy of Sciences under Grant No.134111KYSB20160031
文摘Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a central focus of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences(LASG/IAP) since the establishment of the laboratory in 1985. In China, many pioneering component models and fully coupled models of the climate system have been developed by LASG/IAP. The fully coupled climate system developed in the recent decade is named FGOALS(Flexible Global Ocean-Atmosphere-Land System Model). In this paper, an application-oriented review of the LASG/IAP FGOALS model is presented. The improved model performances are demonstrated in the context of cloud-radiation processes, Asian monsoon, ENSO phenomena, Atlantic Meridional Overturning Circulation(AMOC) and sea ice. The FGOALS model has contributed to both CMIP5(Coupled Model Intercomparison Project-phase 5) and IPCC(Intergovernmental Panel on Climate Change) AR5(the Fifth Assessment Report). The release of FGOALS data has supported the publication of nearly 500 papers around the world. The results of FGOALS are cited ~106 times in the IPCC WG1(Working Group 1) AR5. In addition to the traditional long-term simulations and projections, near-term decadal climate prediction is a new set of CMIP experiment, progress of LAGS/IAP in the development of nearterm decadal prediction system is reviewed. The FGOALS model has supported many Chinese national-level research projects and contributed to the national climate change assessment report. The crucial role of FGOALS as a modeling tool for supporting climate sciences is highlighted by demonstrating the model's performances in the simulation of the evolution of Earth's climate from the past to the future.
基金supported by the Major State Basic Research Development Program of China(973 Program)under Grant No.2010CB951903the National Natural Science Foundation of China under Grant Nos.40890054,41205043,and 41105054
文摘A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model （FGOALS-gl） developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics （LASG/IAP）. The model presents a reasonable performance in comparison with reconstructions of surface temperature. Differentiated from significant changes in the 20th century at the global scale, changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere. Seasonally, modeled significant changes are more pronounced during the wintertime at higher latitudes. This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback. The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period, especially at decadal timescales. Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability. The model response to specified external forcings is modulated by cloud radiative forcing （CRF）. The CRF acts against the fluctuations of external forcings. Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period, but mainly in longwave radiation by a decrease in cloud amount in the ant hropogenic- forcing-dominant period.
基金Under the auspices of National Basic Research Program of China(No.2010CB950102)Strategic and Special Frontier Project of Science and Technology of Chinese Academy of Sciences(No.XDA05080800)+3 种基金National Natural Science Foundation of China(No.41371209,41420104002)Special Research Fund for Doctoral Discipline of Higher Education Institutions(No.20133207110015)Natural Science Foundation of Jiangsu Higher Education Institutions(No.14KJA170002)Priority Academic Program Development of Jiangsu Higher Education Institutions(No.164320H101)
文摘Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation was carried out with fixed external forcing factors （1850 Common Era. （C.E.） conditions） for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the E1 Nifio-Southem Oscillation （ENSO）, the Atlantic Multi-decadal Oscilla- tion （AMO）, the Pacific Decadal Oscillation （PDO）, and the North Atlantic Oscillation （NAO）, were compared with reanalysis datasets to evaluate the model performance. The results are as follows： 1） CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2） climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3） the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3-8 years vari- ability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natu- ral variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.
基金The Strategic Priority Research Program of Chinese Academy of Sciences under contract No.XDA05110201the National Basic Research Program(973 Program) of China under contract No.2010CB951901
文摘On the basis of more than 200-year control run, the performance of the climate system model of Chinese Academy of Sciences （CAS-ESM-C） in simulating the E1 Nifio-Southern Oscillation （ENSO） cycle is evalu- ated, including the onset, development and decay of the ENSO. It is shown that, the model can reasonably simulate the annual cycle and interannual variability of sea surface temperature （SST） in the tropical Pacif- ic, as well as the seasonal phase-locking of the ENSO. The model also captures two prerequisites for the E1 Nino onset, i.e., a westerly anomaly and a warm SST anomaly in the equatorial western Pacific. Owing to too strong forcing from an extratropical meridional wind, however, the westerly anomaly in this region is largely overestimated. Moreover, the simulated thermocline is much shallower with a weaker slope. As a result, the warm SST anomaly from the western Pacific propagates eastward more quickly, leading to a faster develop- ment of an E1 Nino. During the decay stage, owing to a stronger E1Nino in the model, the secondary Gill-type response of the tropical atmosphere to the eastern Pacific warming is much stronger, thereby resulting in a persistent easterly anomaly in the western Pacific. Meanwhile, a cold anomaly in the warm pool appears as a result of a lifted thermocline via Ekman pumping. Finally, an E1 Nino decays into a La Nina through their interactions. In addition, the shorter period and larger amplitude of the ENSO in the model can be attribut- ed to a shallower thermocline in the equatorial Pacific, which speeds up the zonal redistribution of a heat content in the upper ocean.
文摘Improving agricultural water productivity, under rainfed or irrigated conditions, holds significant scope for addressing climate change vulnerability. It also offers adaptation capacity needs as well as water and food security in the southern African region. In this study, evidence for climate change impacts and adaptation strategies in rainfed agricultural systems is explored through modeling predictions of crop yield, soil moisture and excess water for potential harvesting. The study specifically presents the results of climate change impacts under rainfed conditions for maize, sorghum and sunflower using soil-water-crop model simulations, integrated based on daily inputs of rainfall and evapotranspiration disaggregated from GCM scenarios. The research targets a vast farming region dominated by heavy clay soils where rainfed agriculture is a dominant practice. The potential for improving soil water productivity and improved water harvesting have been explored as ways of climate change mitigation and adaptation measures. This can be utilized to explore and design appropriate conservation agriculture and adaptation practices in similar agro-ecological environments, and create opportunities for outscaling for much wider areas. The results of this study can suggest the need for possible policy refinements towards reducing vulnerability and adaptation to climate change in rainfed farming systems.
基金supported by the National Basic Research Program of China (973 Program) under No. 2010CB951903the National Science Foundation of China under Grant No. 41105054, 41205043the China Meteorological Administration under Grant No.GYHY201106022, GYHY201306048, CMAYBY2012-001
文摘The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.
基金supported by National Natural Science Foundation of China (41276073)the Fundamental Research Funds for the Central Universities (2102XZZX012)
文摘Based on simulations using the University of Victoria's Earth System Climate Model, we analyzed the responses of the ocean carbon cycle to increasing atmospheric CO2 levels and climate change from 1800 to 2500 following the RCP 8.5 scenario and its extension. Compared to simulations without climate change, the simulation with a climate sensitivity of 3.0 K shows that in 2100, due to increased atmospheric CO2 concentrations, the simulated sea surface temperature increases by 2.7 K, the intensity of the North Atlantic deep water formation reduces by4.5 Sv, and the oceanic uptake of anthropogenic CO2 decreases by 0.8 Pg C. Climate change is also found to have a large effect on the North Atlantic's ocean column inventory of anthropogenic CO2. Between the years 1800 and 2500, compared with the simulation with no climate change, the simulation with climate change causes a reduction in the total anthropogenic CO2 column inventory over the entire ocean and in North Atlantic by 23.1% and 32.0%, respectively. A set of simulations with climate sensitivity variations from 0.5 K to 4.5 K show that with greater climate sensitivity climate change would have a greater effect in reducing the ocean's ability to absorb CO2 from the atmosphere.
基金National Natural Science Foundation of China (41790471, 41175065)National Key Research and Development Program of China (2016YFA0602200, 2012CB955203, 2013CB430202).
文摘The prediction skill of Arctic Oscillation (AO) in the decadal experiments with the Beijing Climate Center Climate System Model version 1.1 (BCC_CSM1.1) is assessed. As compared with the observations and historical experiments, the contribution of initialization for climate model to predict the seasonal scale AO and its interannual variations is estimated. Results show that the spatial correlation coefficient of AO mode simulated by the decadal experiment is higher than that in the historical experiment. The two groups of experiments reasonably reproduce the characteristics that AO indices are the strongest in winter and the weakest in summer. Compared with historical experiments, the correlation coefficient of the monthly and winter AO indices are higher in the decadal experiments. In particular, the correlation coefficient of monthly AO index between decadal hindcast and observation reached 0.1 significant level. Furthermore, the periodicity of the monthly and spring AO indices are achieved only in the decadal experiments. Therefore, the initial state of model is initialized by using sea temperature data may help to improve the prediction skill of AO in the decadal prediction experiments to some extent.
基金supported by the National Natural Science Foundation of China(Grant Nos.42150204 and 2288101)supported by the China National Postdoctoral Program for Innovative Talents(BX20230045)the China Postdoctoral Science Foundation(2023M730279)。
文摘A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.
基金This study was supported by the National Natural Science Foundation of China(Grant No.U2342228)the National Key Program for Developing Basic Sciences(Grant No.2020YFA0608902)+1 种基金the National Natural Science Foundation of China(Grant Nos.92358302,and 42242018)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0500303).
文摘In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.
基金the National Natural Science Foundation of China(NSFC 31761143002,NSFC 3207178)China Postdoctoral Science Foundation(2022M710405)the National Forest and Grassland Genetic Recourse(No.2005DKA21003).
文摘The influence of global climate change on endangered species is of growing concern, especially for rosewood species that are in urgent need of protection and restoration. Ecological niche models are commonly used to evaluate probable species’ distribution under climate change and contribute to decision-making to define efficient management strategies. A model was developed to forecast which habitat was most likely appropriate for the Dalbergia odorifera. We screened the main climatic variables that describe the current geographic distribution of the species based on maximum entropy modelling (Maxent). We subsequently assessed its potential future distribution under moderate (RCP2.6) and severe (RCP8.5) climate change scenarios for the years 2050 and 2070. The precipitation ranges of the wettest month and the warmest quarter are the primary limiting factors for the current distribution of D. odorifera among the climatic predictors. Climate change will be expected to have beneficial effects on the distribution range of D. odorifera. In conclusion, the main limits for the distribution of D. odorifera are determined by the level of precipitation and human activities. The results of this study indicate that the coasts of southern China and Chongqing will play a key role in the protection and restoration of D. odorifera in the future.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
基金supported by the National Natural Science Foundation of China(Grant No.U2342208)support from NSF/Climate Dynamics Award#2025057。
文摘Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.
文摘采用累积频率的统计方法和Community Climate Model 3(CCM3)模拟的10年逐日降水结果,分析了模拟的夏季极端降水事件的时空分布特征.结果表明,CCM3模拟的极端降水阈值的大值区主要在我国黄河和长江流域的上游、印度半岛及其邻近海域和孟加拉湾及其北部地区.CCM3能够模拟出我国长江流域极端降水量与极端降水日数显著增加的趋势.对极端降水平均强度、降水日数以及极端降水量与总降水量比值的经验正交函数(EOF)分析可知,我国大部分地区的极端降水基本呈现同相变化,且以长江和黄河中游地区较为显著.CCM3模式基本能够模拟出观测到的极端降水阈值与总降水、极端降水日数及其距平的高空间相关性.
