Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study...Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.展开更多
A two-dimensional energy balance climate model has been built to investigate the climate on Mars.The model takes into account the balance among solar radiation,longwave radiation,and energy transmission and can be sol...A two-dimensional energy balance climate model has been built to investigate the climate on Mars.The model takes into account the balance among solar radiation,longwave radiation,and energy transmission and can be solved analytically by Legendre polynomials.With the parameters for thermal diffusion and radiation processes being properly specified,the model can simulate a reasonable surface atmospheric temperature distribution but not a very perfect vertical atmospheric temperature distribution compared with numerical results,such as those from the Mars Climate Database.With varying solar radiation in a Martian year,the model can simulate the seasonal variation of the air temperature on Mars.With increasing dust content,the Martian atmosphere gradually warms.However,the warming is insignificant in the cold and warm scenarios,in which the dust mixing ratio varies moderately,whereas the warming is significant in the storm scenario,in which the dust mixing ratio increases dramatically.With an increasing albedo value of either the polar cap or the non-ice region,Mars gradually cools.The mean surface atmospheric temperature decreases moderately with an increasing polar ice albedo,whereas it increases dramatically with an increasing non-ice albedo.This increase occurs because the planetary albedo of the ice regions is smaller than that of the non-ice region.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
Climate change disrupts the distribution of species and restructures their richness patterns.The genus of Asian bamboo,Phyllostachys,possesses significant ecological and economic values,and represents the most species...Climate change disrupts the distribution of species and restructures their richness patterns.The genus of Asian bamboo,Phyllostachys,possesses significant ecological and economic values,and represents the most speciesrich genus in the Bambusoideae subfamily.Based on the distribution data of 46 species and 20 environmental variables,we used the MaxEnt model combined with ArcGIS calculations to simulate current and future potential richness distributions under three distinct CO_(2) emission scenarios.The results showed that the MaxEnt model had a good predictive ability,with a mean area under the working characteristic curve(AUC value)of 0.91 for all species.The main environmental variables that impacted the future distribution of most Phyllostachys species were elevation,variations of seasonal precipitation,and mean diurnal range.Phyllostachys species are currently concentrated in southeastern China.Under future climate projections,18 species exhibited significant habitat contraction across three or more future climate scenarios,but suitable habitats for other species will expand.This enhancement is most pronounced under the extreme climate scenario(2090s-SSP585),primarily driven by high species gains contributing to elevated turnover values across scenarios.The center of maximum richness will progressively shift southwestward over time.Predictive modeling of Phyllostachys richness distribution dynamics under climate change enhances our understanding of its biogeography and informs strategic introduction programs to bamboo management and augments China’s carbon sequestration capacity.展开更多
Climate warming is significantly altering the distribution of tree species,which holds crucial implications for China’s Larix species as they are important afforestation efforts.Understanding their optimal habitats a...Climate warming is significantly altering the distribution of tree species,which holds crucial implications for China’s Larix species as they are important afforestation efforts.Understanding their optimal habitats and environmental constraints is vital for predicting range shifts and guiding adaptive forest management.Previous studies prioritized changing climate impacts on horizontal range shifts of Larix,neglecting the influence of soil factors and range shift along altitudinal gradients.To address this,we applied an optimized MaxEnt model to assess current and future SSP126/SSP585 scenarios,three-dimensional habitat suitability(latitude,longitude,altitude)for four major Larix species(L.principis-rupprechtii,L.gmelinii,L.kaempferi,L.olgensis),while identifying key environmental drivers.Our results indicate that elevation and extreme moisture conditions universally constrain their distribution.Soil chemistry properties exhibited species-specific influences:cation exchange capacity critically shaped L.principis-rupprechtii and L.gmelinii ranges,whereas exchangeable aluminum determined L.kaempferi and L.olgensis distribution.Under future climate scenarios,habitat areas show divergent trajectories-L.principis-rupprechtii maximum gains 5.1%under SSP126,while L.kaempferi maximum expands 15.1%.Conversely,SSP585 triggered a 3.7% decline for L.gmelinii during the 2040s−2100s,and L.olgensis faces a net reduction to 0.4% by 2100s despite transient gains.Spatially,three species(L.kaempferi,L.gmelinii,L.olgensis)shifted northward,while L.principis-rupprechtii migrated northwest.All species distribution ascended altitudinally reflecting thermal adaptation strategies.These multidimensional insights enable targeted species selection for climate-resilient afforestation and underscore the need for soil-inclusive management planning.展开更多
Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated...Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.展开更多
In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.T...In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.This study assessed the future evolution of drought under climate change by employing the standardized moisture anomaly index(SZI)on the basis of multi-model the Coupled Model Intercomparison Project Phase 6(CMIP6)simulations under historical conditions(1970–2014)and future scenarios(shared socioeconomic pathway(SSP)1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5 for 2015–2100).The results show that precipitation–evapotranspiration anomalies are projected to first decline but then increase over time,with increased fluctuations and uncertainty under high-emission scenarios(SSP5-8.5).These trends indicate intensifying drought risks and reveal a strong influence of emission pathways on regional water cycling.Temporal analysis of SZI indicates a transition from wetting to drying under lowand medium-emission pathways(SSP1-2.6 and SSP2-4.5),whereas high-emission scenarios are characterized by persistent drying and increased variability.The significant lower-tail dependence(0.271)observed under SSP2-4.5 and SSP5-8.5 suggests that extreme droughts may be subject to nonlinear co-amplification across scenarios.The frequency of moderate and more severe drought events is expected to increase substantially,especially under SSP5-8.5,where drought occurrence is predicted to extend into spring and autumn and become more evenly distributed throughout the year.Spatially,drought duration shows significant positive autocorrelation across all scenarios,with hot spots consistently concentrated in the southern and southeastern regions of the basin.Random forest analysis,interpreted as association-based pattern attribution,indicates that meteorological variables(precipitation and potential evapotranspiration(PET))make the greatest contributions to the hot spot pattern,followed by topography and soil moisture.Among land use categories,farmland generally shows higher drought sensitivity than other land use types,as reflected by its relative contribution patterns across scenarios.The spatial pattern of drought is statistically structured by climatic forcing,surface conditions,and soil moisture status,reflecting their coupled associations with hot spot occurrence.In addition,a drought spatial uncertainty index was constructed from multi-scenario hot spot maps,revealing spatially heterogeneous structural variability throughout the basin.Correlation analysis further highlights strong internal couplings among environmental variables(e.g.,elevation-linked hydroclimatic gradients and grassland–bare soil contrasts).These findings offer a scientific basis for developing region-specific drought monitoring and adaptation strategies under future climate change conditions.展开更多
This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This m...This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.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
Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subs...Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.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 the context of global climate change,the increasing frequency of extreme weather events presents significant challenges to urban water systems.This study focuses on the Beijing section of the Beijing-Hangzhou Grand...In the context of global climate change,the increasing frequency of extreme weather events presents significant challenges to urban water systems.This study focuses on the Beijing section of the Beijing-Hangzhou Grand Canal,introduces the SEE model,and develops an integrated“comprehensive water environment simulation model”to systematically examine the path for enhancing its climate resilience.Through the coupling of multiple models(MIKE 11,MIKE URBAN,MIKE 21)and scenario simulations,this study analyzes the response mechanisms of various governance strategies under extreme climate conditions.The research proposes four specific measures to enhance resilience:dual-scenario simulation of climate and governance,identification and reinforcement of weak points in resilience,parametric modeling of ecological restoration interventions,and the development of a“digital twin canal system”.The research findings indicate that the system integration of the SEE model substantially improves the adaptability,endurance,and recovery capacity of canals in response to climate shocks,including heavy rainfall and drought.This provides a scientific foundation and a practical path for achieving long-term resilience and sustainable development of urban water systems.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
Global warming leads to climate change and hence effects tourism activities.Bioclimatic comfort indices are used to understand the changing climates of outdoor tourism.In this study,the models for the automatic calcul...Global warming leads to climate change and hence effects tourism activities.Bioclimatic comfort indices are used to understand the changing climates of outdoor tourism.In this study,the models for the automatic calculation of the tourism climate index(TCI),heat index(HI),and new summer simmer index(NSSI)from bioclimatic comfort indices are used to determine the climatic conditions of outdoor tourism.The study compared the maps generated by the models with those manually created maps in ArcGIS.In order to statistically reveal how accurately the models produced maps,the relationship between the maps obtained from QGIS and ArcGIS software was assessed by linear regression technique.As a result of the regression analysis performed on the data calculated as annual averages,the R^(2) value for all models was 1.The high R^(2) value indicates that there is a very high correlation between three different bioclimatic comfort index maps obtained fromQGIS and ArcGIS software.As a result of this situation,thesemodels produced for use in open source QGIS software can be easily used for the evaluation of tourism activities.It has been revealed that the model developed in QGIS can be used without producing maps using formulae in any GIS software.The developed models can be accessed at https://github.com/efdalkaya/QGIS_Model(accessed on 10 December 2024)in GitHub.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
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
A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM...A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.展开更多
From 1981 to 2010, the effects of climate change on evapotranspiration of the alpine ecosystem and the regional difference of effects in the Tibetan Plateau （TP） were studied based on the Lund-Potsdam-Jena dynamic v...From 1981 to 2010, the effects of climate change on evapotranspiration of the alpine ecosystem and the regional difference of effects in the Tibetan Plateau （TP） were studied based on the Lund-Potsdam-Jena dynamic vegetation model and data from 80 meteorological stations. Changes in actual evapotranspiration （AET） and water balance in TP were analyzed. Over the last 30 years, climate change in TP was characterized by significantly increased temperature, slightly increased precipitation, and decreased potential evapotranspiration （PET）, which was significant before 2000. AET exhibited increasing trends in most parts of TP. The difference between precipitation and AET decreased in the southeastern plateau and increased in the northwestern plateau. A decrease in atmospheric water demand will lead to a decreased trend in AET. However, AET in most regions increased because of increased precipitation. Increased precipitation was observed in 86% of the areas with increased AET, whereas decreased precipitation was observed in 73% of the areas with decreased AET.展开更多
基金the University of Milan for funding the“ProForesta”project through the 2020 Research Support Planthe“Ente Parco Nazionale dell'Appennino Tosco-Emiliano”for having financed the project“First urgent measures to promote the adaptation of the silver fir forests of the Tuscan-Emilian Apennine National Park to the effects of climate change”。
文摘Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies.This study models the dynamics of Italian silver fir(Abies alba)forests under varying climate change scenarios using the forest gap model FORMIND.Focusing on three distinct silver fir provenances(Western Alps,Northern Apennines,and Southern Apennines),the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways(RCPs).The individual-based model FORMIND was parameterized and validated with field data for each of the provenances,demonstrating its ability to accurately reproduce key forest metrics and dynamics.Our results reveal significant differences in expected growth patterns,productivity,metabolism,and carbon storage capacity among the silver fir provenances in pure and mixed stands.In the simulations,the Northern Apennines provenance showed higher biomass production(biomass>10%±1%)and carbon uptake(net primary productivity,NPP>8%±1%)at the end of the century compared to the Western Alps provenance in the pure provenance(PP)and no regeneration scenario.Conversely,the Southern Apennines provenance showed higher biomass(biomass>5%–10%)and NPP(>15%–18%)in mixed provenance(MP)and regeneration scenarios.These results show that genetic diversity strongly affects forest growth and resilience to environmental changes.Hence,it should be included as a predictor variable in forest models.The study also demonstrates the resilience of silver fir to climatic stressors,emphasizing its potential as a robust species in multiple forest contexts.The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling,enabling more accurate and reliable predictions under climate change scenarios.The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies,in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.
基金jointly funded by the National Natural Science Foundation of China (Grant 41505042)the National Program on Global Change and Air–Sea Interaction (Grant GASIIPOVAI-03)+1 种基金the National Basis Research Program of China (Grants 2015CB953601, 2014CB953903)the Fundamental Research Funds for the Central Universities
文摘A two-dimensional energy balance climate model has been built to investigate the climate on Mars.The model takes into account the balance among solar radiation,longwave radiation,and energy transmission and can be solved analytically by Legendre polynomials.With the parameters for thermal diffusion and radiation processes being properly specified,the model can simulate a reasonable surface atmospheric temperature distribution but not a very perfect vertical atmospheric temperature distribution compared with numerical results,such as those from the Mars Climate Database.With varying solar radiation in a Martian year,the model can simulate the seasonal variation of the air temperature on Mars.With increasing dust content,the Martian atmosphere gradually warms.However,the warming is insignificant in the cold and warm scenarios,in which the dust mixing ratio varies moderately,whereas the warming is significant in the storm scenario,in which the dust mixing ratio increases dramatically.With an increasing albedo value of either the polar cap or the non-ice region,Mars gradually cools.The mean surface atmospheric temperature decreases moderately with an increasing polar ice albedo,whereas it increases dramatically with an increasing non-ice albedo.This increase occurs because the planetary albedo of the ice regions is smaller than that of the non-ice region.
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.
基金supported by the National Science Foundation of China(32201643)the Key Research Projects of Yibin,research and integrated demonstration and key technologies for smart bamboo industry(YBZD2024-1).
文摘Climate change disrupts the distribution of species and restructures their richness patterns.The genus of Asian bamboo,Phyllostachys,possesses significant ecological and economic values,and represents the most speciesrich genus in the Bambusoideae subfamily.Based on the distribution data of 46 species and 20 environmental variables,we used the MaxEnt model combined with ArcGIS calculations to simulate current and future potential richness distributions under three distinct CO_(2) emission scenarios.The results showed that the MaxEnt model had a good predictive ability,with a mean area under the working characteristic curve(AUC value)of 0.91 for all species.The main environmental variables that impacted the future distribution of most Phyllostachys species were elevation,variations of seasonal precipitation,and mean diurnal range.Phyllostachys species are currently concentrated in southeastern China.Under future climate projections,18 species exhibited significant habitat contraction across three or more future climate scenarios,but suitable habitats for other species will expand.This enhancement is most pronounced under the extreme climate scenario(2090s-SSP585),primarily driven by high species gains contributing to elevated turnover values across scenarios.The center of maximum richness will progressively shift southwestward over time.Predictive modeling of Phyllostachys richness distribution dynamics under climate change enhances our understanding of its biogeography and informs strategic introduction programs to bamboo management and augments China’s carbon sequestration capacity.
基金supported by the National Key Research and Development Program of China(2022YFD2200501).
文摘Climate warming is significantly altering the distribution of tree species,which holds crucial implications for China’s Larix species as they are important afforestation efforts.Understanding their optimal habitats and environmental constraints is vital for predicting range shifts and guiding adaptive forest management.Previous studies prioritized changing climate impacts on horizontal range shifts of Larix,neglecting the influence of soil factors and range shift along altitudinal gradients.To address this,we applied an optimized MaxEnt model to assess current and future SSP126/SSP585 scenarios,three-dimensional habitat suitability(latitude,longitude,altitude)for four major Larix species(L.principis-rupprechtii,L.gmelinii,L.kaempferi,L.olgensis),while identifying key environmental drivers.Our results indicate that elevation and extreme moisture conditions universally constrain their distribution.Soil chemistry properties exhibited species-specific influences:cation exchange capacity critically shaped L.principis-rupprechtii and L.gmelinii ranges,whereas exchangeable aluminum determined L.kaempferi and L.olgensis distribution.Under future climate scenarios,habitat areas show divergent trajectories-L.principis-rupprechtii maximum gains 5.1%under SSP126,while L.kaempferi maximum expands 15.1%.Conversely,SSP585 triggered a 3.7% decline for L.gmelinii during the 2040s−2100s,and L.olgensis faces a net reduction to 0.4% by 2100s despite transient gains.Spatially,three species(L.kaempferi,L.gmelinii,L.olgensis)shifted northward,while L.principis-rupprechtii migrated northwest.All species distribution ascended altitudinally reflecting thermal adaptation strategies.These multidimensional insights enable targeted species selection for climate-resilient afforestation and underscore the need for soil-inclusive management planning.
基金Supported by the National Key Research and Development Program of China(No.2023YFD2400800)the Laoshan Laboratory(Nos.LSKJ202203801,LSKJ202203204)+4 种基金the Natural Science Foundation of Shandong Province(Nos.ZR2023MD127,ZR2021MD075)the Central Public-interest Scientific Institution Basal Research Fund CAFS(Nos.2023TD28,20603022023012)the National Natural Science Foundation of China(No.32373107)the China Agriculture Research System(No.CARS-50)the Taishan Scholars Program。
文摘Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.
基金supported by the Key Research and Development Project of Xinjiang Uygur Autonomous Region,China(2022B02049)the Major Science and Technology Special Project of Xinjiang Uygur Autonomous Region,China(2024A03007-5).
文摘In the northern Tarim River Basin,the Weigan River Basin is a critical endorheic system characterized by extreme aridity,where drought poses a major natural hazard to agricultural production and ecological stability.This study assessed the future evolution of drought under climate change by employing the standardized moisture anomaly index(SZI)on the basis of multi-model the Coupled Model Intercomparison Project Phase 6(CMIP6)simulations under historical conditions(1970–2014)and future scenarios(shared socioeconomic pathway(SSP)1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5 for 2015–2100).The results show that precipitation–evapotranspiration anomalies are projected to first decline but then increase over time,with increased fluctuations and uncertainty under high-emission scenarios(SSP5-8.5).These trends indicate intensifying drought risks and reveal a strong influence of emission pathways on regional water cycling.Temporal analysis of SZI indicates a transition from wetting to drying under lowand medium-emission pathways(SSP1-2.6 and SSP2-4.5),whereas high-emission scenarios are characterized by persistent drying and increased variability.The significant lower-tail dependence(0.271)observed under SSP2-4.5 and SSP5-8.5 suggests that extreme droughts may be subject to nonlinear co-amplification across scenarios.The frequency of moderate and more severe drought events is expected to increase substantially,especially under SSP5-8.5,where drought occurrence is predicted to extend into spring and autumn and become more evenly distributed throughout the year.Spatially,drought duration shows significant positive autocorrelation across all scenarios,with hot spots consistently concentrated in the southern and southeastern regions of the basin.Random forest analysis,interpreted as association-based pattern attribution,indicates that meteorological variables(precipitation and potential evapotranspiration(PET))make the greatest contributions to the hot spot pattern,followed by topography and soil moisture.Among land use categories,farmland generally shows higher drought sensitivity than other land use types,as reflected by its relative contribution patterns across scenarios.The spatial pattern of drought is statistically structured by climatic forcing,surface conditions,and soil moisture status,reflecting their coupled associations with hot spot occurrence.In addition,a drought spatial uncertainty index was constructed from multi-scenario hot spot maps,revealing spatially heterogeneous structural variability throughout the basin.Correlation analysis further highlights strong internal couplings among environmental variables(e.g.,elevation-linked hydroclimatic gradients and grassland–bare soil contrasts).These findings offer a scientific basis for developing region-specific drought monitoring and adaptation strategies under future climate change conditions.
基金supported by the Shihezi University High-Level Talents Research Startup Project(Project No.RCZK202521)the National Natural Science Foundation of China(Grant Nos.12271066,11871121,12171405)+1 种基金the Chongqing Natural Science Foundation Joint Fund for Innovation and Development Project(Project No.CSTB2024NSCQLZX0085)the Chongqing Normal University Foundation(Grant No.23XLB018).
文摘This paper investigates ruin,capital injection,and dividends for a two-dimensional risk model.The model posits that surplus levels of insurance companies are governed by a perturbed composite Poisson risk model.This model introduces a dependence between the two surplus levels,present in both the associated perturbations and the claims resulting from common shocks.Critical levels of capital injection and dividends are established for each of the two risks.The surplus levels are observed discretely at fixed intervals,guiding decisions on capital injection,dividends,and ruin at these junctures.This study employs a two-dimensional Fourier cosine series expansion method to approximate the finite time expected discounted operating cost until ruin.The ensuing approximation error is also quantified.The validity and accuracy of the method are corroborated through numerical examples.Furthermore,the research delves into the optimal capital allocation problem.
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supported by National Natural Science Foundation of China(72288101,72361137002,and 72101018)the Dutch Research Council(NWO Grant 482.22.01).
文摘Vehicle electrification,an important method for reducing carbon emissions from road transport,has been promoted globally.In this study,we analyze how individuals adapt to this transition in transportation and its subsequent impact on urban structure.Considering the varying travel costs associated with electric and fuel vehicles,we analyze the dynamic choices of households concerning house locations and vehicle types in a two-dimensional monocentric city.A spatial equilibrium is developed to model the interactions between urban density,vehicle age and vehicle type.An agent-based microeconomic residential choice model dynamically coupled with a house rent market is developed to analyze household choices of home locations and vehicle energy types,considering vehicle ages and competition for public charging piles.Key findings from our proposed models show that the proportion of electric vehicles(EVs)peaks at over 50%by the end of the first scrappage period,accompanied by more than a 40%increase in commuting distance and time compared to the scenario with only fuel vehicles.Simulation experiments on a theoretical grid indicate that heterogeneity-induced residential segregation can lead to urban sprawl and congestion.Furthermore,households with EVs tend to be located farther from the city center,and an increase in EV ownership contributes to urban expansion.Our study provides insights into how individuals adapt to EV transitions and the resulting impacts on home locations and land use changes.It offers a novel perspective on the dynamic interactions between EV adoption and urban development.
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Sponsored by 2025 Postgraduate Teaching Reform Project of North China University of Technology。
文摘In the context of global climate change,the increasing frequency of extreme weather events presents significant challenges to urban water systems.This study focuses on the Beijing section of the Beijing-Hangzhou Grand Canal,introduces the SEE model,and develops an integrated“comprehensive water environment simulation model”to systematically examine the path for enhancing its climate resilience.Through the coupling of multiple models(MIKE 11,MIKE URBAN,MIKE 21)and scenario simulations,this study analyzes the response mechanisms of various governance strategies under extreme climate conditions.The research proposes four specific measures to enhance resilience:dual-scenario simulation of climate and governance,identification and reinforcement of weak points in resilience,parametric modeling of ecological restoration interventions,and the development of a“digital twin canal system”.The research findings indicate that the system integration of the SEE model substantially improves the adaptability,endurance,and recovery capacity of canals in response to climate shocks,including heavy rainfall and drought.This provides a scientific foundation and a practical path for achieving long-term resilience and sustainable development of urban water systems.
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.
文摘Global warming leads to climate change and hence effects tourism activities.Bioclimatic comfort indices are used to understand the changing climates of outdoor tourism.In this study,the models for the automatic calculation of the tourism climate index(TCI),heat index(HI),and new summer simmer index(NSSI)from bioclimatic comfort indices are used to determine the climatic conditions of outdoor tourism.The study compared the maps generated by the models with those manually created maps in ArcGIS.In order to statistically reveal how accurately the models produced maps,the relationship between the maps obtained from QGIS and ArcGIS software was assessed by linear regression technique.As a result of the regression analysis performed on the data calculated as annual averages,the R^(2) value for all models was 1.The high R^(2) value indicates that there is a very high correlation between three different bioclimatic comfort index maps obtained fromQGIS and ArcGIS software.As a result of this situation,thesemodels produced for use in open source QGIS software can be easily used for the evaluation of tourism activities.It has been revealed that the model developed in QGIS can be used without producing maps using formulae in any GIS software.The developed models can be accessed at https://github.com/efdalkaya/QGIS_Model(accessed on 10 December 2024)in GitHub.
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.
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.
文摘A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.
基金The "Strategic Priority Research Program" of the Chinese Academy of Sciences,No.XDA05090304Project for Public Service from Ministry of Environmental Protection of China,No.201009056National Key Technology Research and Development Program,No.2009BAC61B05
文摘From 1981 to 2010, the effects of climate change on evapotranspiration of the alpine ecosystem and the regional difference of effects in the Tibetan Plateau （TP） were studied based on the Lund-Potsdam-Jena dynamic vegetation model and data from 80 meteorological stations. Changes in actual evapotranspiration （AET） and water balance in TP were analyzed. Over the last 30 years, climate change in TP was characterized by significantly increased temperature, slightly increased precipitation, and decreased potential evapotranspiration （PET）, which was significant before 2000. AET exhibited increasing trends in most parts of TP. The difference between precipitation and AET decreased in the southeastern plateau and increased in the northwestern plateau. A decrease in atmospheric water demand will lead to a decreased trend in AET. However, AET in most regions increased because of increased precipitation. Increased precipitation was observed in 86% of the areas with increased AET, whereas decreased precipitation was observed in 73% of the areas with decreased AET.
