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
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
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
Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diver...Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.展开更多
This paper applies the newest emission scenarios of the sulfur and greenhouse gases, namely IPCC SRES A2 and B2 scenarios, to investigate the change of the North China climate with an atmosphere-ocean coupled general ...This paper applies the newest emission scenarios of the sulfur and greenhouse gases, namely IPCC SRES A2 and B2 scenarios, to investigate the change of the North China climate with an atmosphere-ocean coupled general circulation model. In the last three decades of the 21st century, the global warming enlarges the land-sea thermal contrast, and hence, causes the East Asian summer (winter) monsoon circulation to he strengthened (weakened). The rainfall seasonality strengthens and the summer precipitation increases significantly in North China. It is suggested that the East Asian rainy area would expand northward to North China in the last three decades of the 21st century. In addition, the North China precipitation would increase significantly in September. In July, August, and September, the interannual variability of the precipitation enlarges evidently over North China, implying a risk of flooding in the future.展开更多
Changes in the climate of the Arctic and of the Antarctic have been of great concern to the international scientific and social communities since the release in 2007 of the Intergovernmental Panel on Climate Change Fo...Changes in the climate of the Arctic and of the Antarctic have been of great concern to the international scientific and social communities since the release in 2007 of the Intergovernmental Panel on Climate Change Fourth Assessment Report （IPCC AR4）. Since then, many new findings have been reported from observations and research carried out in the Arctic and Antarctic during the fourth International Polar Year （IPY）. There is evidence that global warming is inducing rapid changes in the Arctic and Antarctic, in both a quantitative and qualitative sense, and that these regional changes could be used as indicators of global climate change. Declining Arctic sea ice could affect winter snowfall across much of the Northern Hemisphere by bringing harsher winters. Projections suggest that summertime Arctic sea ice will disappear by 2037. By the 2070s, the Antarctic ozone hole will recover to the level of the early 1980s, following the ban on the production of Freon earlier this century. With the loss of the shielding effect of the ozone hole, Antarctic surface temperatures will increase, ice sheets in East Antarctica will begin to melt, and the Antarctic sea ice will retreat. Therefore, sea level rise will become an increasingly serious issue this century. As sea surface temperature rises, the Southern Ocean will become less effective as a sink for atmospheric CO2 and the increase of surface CO2 will be faster than that in the atmosphere. Increased surface CO2 would lead to ocean acidification and affect ecological systems and food chains.展开更多
The multi-model ensemble （MME） of 20 models from the Coupled Model Intercomparison Project Phase Five （CMIP5） was used to analyze surface climate change in the 21st century under the representative con- centration...The multi-model ensemble （MME） of 20 models from the Coupled Model Intercomparison Project Phase Five （CMIP5） was used to analyze surface climate change in the 21st century under the representative con- centration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature （SAT） is 1.86℃ relative to the pre-industrial level, achieving the target to limit the global warming to 2℃. Associated with the ＂increase-peak-decline＂ greenhouse gases （GHGs） concentration path- way of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods： warming during 2006-55 and cooling during 2056-2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cool- ing period. The warming during 2006-55 is distributed globally, while the cooling during 2056-2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period.展开更多
Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always rece...Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always receive higher attention from commercial media, government departments and mountain tourists in China and abroad. At present, more than 100 glaciers have been devel- oped successfully as famous tourist destinations all over the world. However, global climate change seriously affects mountain glaciers and its surrounding environment. According to the current accelerated retreat trend, natural and cultural landscapes of some glaciers will be weakened, even disappear in the future. Climate change will also inevitably affect mountain ecosystems, and tourism routes under ice and glacier experience activities in these ecosystems. Simultaneously, the disappearance of mountain glaciers will also lead to a clear reduction of tourism and local economic benefits. Based on these reasons, this paper took Mr. Yulong Snow scenic area as an example and analyzed the retreat trend of a typical glacier. We then put forward some scientific and rational response mechanisms and adaptation models based on climate change in order to help future sustainable development of mountain glacier tourism.展开更多
This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seaso...This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 C during winter than of 4.9 C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.展开更多
Based on RegCM4,a climate model system,we simulated the distribution of the present climate(1961-1990)and the future climate(2010-2099),under emission scenarios of RCPs over the whole Pearl River Basin.From the climat...Based on RegCM4,a climate model system,we simulated the distribution of the present climate(1961-1990)and the future climate(2010-2099),under emission scenarios of RCPs over the whole Pearl River Basin.From the climate parameters,a set of mean precipitation,wet day frequency,and mean wet day intensity and several precipitation percentiles are used to assess the expected changes in daily precipitation characteristics for the 21 st century.Meanwhile the return values of precipitation intensity with an average return of 5,10,20,and 50 years are also used to assess the expected changes in precipitation extremes events in this study.The structure of the change across the precipitation distribution is very coherent between RCP4.5 and RCP8.5.The annual,spring and winter average precipitation decreases while the summer and autumn average precipitation increases.The basic diagnostics of precipitation show that the frequency of precipitation is projected to decrease but the intensity is projected to increase.The wet day percentiles(q90 and q95) also increase,indicating that precipitation extremes intensity will increase in the future.Meanwhile,the5-year return value tends to increase by 30%-45%in the basins of Liujiang River,Red Water River,Guihe River and Pearl River Delta region,where the 5-year return value of future climate corresponds to the 8-to 10-year return value of the present climate,and the 50-year return value corresponds to the 100-year return value of the present climate over the Pearl River Delta region in the 2080 s under RCP8.5,which indicates that the warming environment will give rise to changes in the intensity and frequency of extreme precipitation events.展开更多
Because of the environmental and socioeconomic impacts of anthropogenic sea level rise （SLR）, it is very important to understand the processes leading to past and present SLRs towards more reliable future SLR projec...Because of the environmental and socioeconomic impacts of anthropogenic sea level rise （SLR）, it is very important to understand the processes leading to past and present SLRs towards more reliable future SLR projections. A regional ocean general circulation model （ROGCM）, with a grid refinement in the Bohai, Yellow, and East China Seas （BYECSs）, was set up to project SLR induced by the ocean dynamic change in the 21st century. The model does not consider the contributions from ice sheets and glacier melting. Data of all forcing terms required in the model came from the simulation of the Community Climate System Model version 3.0 （CCSM3） under the International Panel on Climate Change （IPCC）-A2 scenario. Simulation results show that at the end of the 21st century, the sea level in the BYECSs will rise about 0.12 to 0.20 m. The SLR in the BYECSs during the 21st century is mainly caused by the ocean mass redistribution due to the ocean dynamic change of the Pacific Ocean, which means that water in the Pacific Ocean tends to move to the continental shelves of the BYECSs, although the local steric sea level change is another factor.展开更多
Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillatio...Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillation(NPO), which is the second most important factor determining the wintertime sea level pressure field in simulations of the pre-industrial control climate, and evaluate the NPO response to the future most reasonable global warming scenario(the A1B scenario). We reveal that while most models simulate the geographic distribution and amplitude of the NPO pattern satisfactorily, only 13 models capture both features well. However, the temporal variability of the simulated NPO could not be significantly correlated with the observations. Further analysis indicates the weakened NPO intensity for a scenario of strong global warming is attributable to the reduced lower-tropospheric baroclinicity at mid-latitudes, which is anticipated to disrupt large-scale and low-frequency atmospheric variability, resulting in the diminished transfer of energy to the NPO, together with its northward shift.展开更多
Change monitoring of distribution in time series models is an important issue. This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series, which is based on a weighe...Change monitoring of distribution in time series models is an important issue. This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series, which is based on a weighed empirical process of residuals with weights equal to the regressors. The asymptotic properties of our monitoring statistic are derived under the null hypothesis of no change in distribution. The finite sample properties are investigated by a simulation. As it turns out, the procedure is not only able to detect distributional changes but also changes in the regression coefficient and mean, Finally, we apply the statistic to a groups of financial data.展开更多
The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is n...The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is no simple way to reconcile them. So, simple climate models, like statistical-dynamical models (SDMs), appear to be useful in this context. This kind of models is essentially mechanistic, being directed towards understanding the dependence of a particular mechanism on the other parameters of the problem. In this paper, the utility of SDMs for studies of climate change is discussed in some detail. We show that these models are an indispensable part of hierarchy of climate models.展开更多
Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping...Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.展开更多
Egypt suffers from the impacts of climate change. Adaption plans should solve the shortage in water resources and increase the use of renewable energy. Detailed data on rainfall as non conventional water and detailed ...Egypt suffers from the impacts of climate change. Adaption plans should solve the shortage in water resources and increase the use of renewable energy. Detailed data on rainfall as non conventional water and detailed data on potential renewable energy are important. The added value of this research is to investigate the suitability of satellite data locally in North Sinai in Egypt. The Tropical Rainfall Measuring Mission (TRMM) satellites and available data from ground rain gauges are studied at North Sinai of Egypt. Local multiplication factors and correlation equations on a monthly basis were developed based on short term historical data. General equation based on short term data was developed to enhance TRMM data for the rainy season to minimize spatial and temporal errors. This equation would be very useful, especially in the ungauged areas in North Sinai to adjust TRMM rainfall data. TRMM data are spatially distributed, so it enhances the hydrology models for runoff estimation. This runoff could be used as non conventional water resource. The runoff was estimated in the RasSudr area in the 2010 storm to be 3.6 (m3/s). The hydropower of this runoff was estimated and ranged from 15,135 to 57,352 (kWh). The solar energy is studied from (NASA) satellite data. The monthly averaged solar energy was estimated to get possible generated power from the solar panel at locations of rainfall ground stations. The generated solar energy would supply self-sufficient energy for ground stations measuring instruments rather than batteries. The results show that a small solar panel project of 200 (m2) could safe electric network power by generating about 20,385 (kWh/year). The results of this study could help in enhancing adapting plans for climate change and runoff estimation model that needs grid data, especially in the area lacking ground data.展开更多
Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global L...Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.展开更多
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 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 Laoshan Laboratory[grant number LSKJ202202403]the National Natural Science Foundation of China[grant number 42030410]+1 种基金additionally supported by the Startup Foundation for Introducing Talent of NUISTJiangsu Innovation Research Group[grant number JSSCTD202346]。
文摘Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.
基金supported by the Key Project of the Chinese Academy of Sciences(KZCX2-SW-210)the Key Project of the Chinese Academy of Sciences(KZCX2-203)the National Key Programme for Developing Basic Sciences(G1998040904).
文摘This paper applies the newest emission scenarios of the sulfur and greenhouse gases, namely IPCC SRES A2 and B2 scenarios, to investigate the change of the North China climate with an atmosphere-ocean coupled general circulation model. In the last three decades of the 21st century, the global warming enlarges the land-sea thermal contrast, and hence, causes the East Asian summer (winter) monsoon circulation to he strengthened (weakened). The rainfall seasonality strengthens and the summer precipitation increases significantly in North China. It is suggested that the East Asian rainy area would expand northward to North China in the last three decades of the 21st century. In addition, the North China precipitation would increase significantly in September. In July, August, and September, the interannual variability of the precipitation enlarges evidently over North China, implying a risk of flooding in the future.
基金supported by the National Natural Science Foundation of China (Grant nos.40531007,41230529)the National High-tech Research & Development Program of China (Grant no.2008AA121703)+3 种基金the International Cooperation Project supported by Ministry of Science and Technology of China (Grant no.2009DFA22920)the International Cooperation Project supported by Chinese Arctic and Antarctic Administration (Grant nos.IC201013,IC201114,IC201201,and IC201308)the Chinese Polar Environmental Comprehensive Investigation and Assessment Programs (Grant nos.CHINARE2012-01-04-02,CHINARE2012-02-01,and CHINARE2012-03-04-02)the Ocean Public Welfare Scientific Research Project of China (Grant no.2004DIB5J178)
文摘Changes in the climate of the Arctic and of the Antarctic have been of great concern to the international scientific and social communities since the release in 2007 of the Intergovernmental Panel on Climate Change Fourth Assessment Report （IPCC AR4）. Since then, many new findings have been reported from observations and research carried out in the Arctic and Antarctic during the fourth International Polar Year （IPY）. There is evidence that global warming is inducing rapid changes in the Arctic and Antarctic, in both a quantitative and qualitative sense, and that these regional changes could be used as indicators of global climate change. Declining Arctic sea ice could affect winter snowfall across much of the Northern Hemisphere by bringing harsher winters. Projections suggest that summertime Arctic sea ice will disappear by 2037. By the 2070s, the Antarctic ozone hole will recover to the level of the early 1980s, following the ban on the production of Freon earlier this century. With the loss of the shielding effect of the ozone hole, Antarctic surface temperatures will increase, ice sheets in East Antarctica will begin to melt, and the Antarctic sea ice will retreat. Therefore, sea level rise will become an increasingly serious issue this century. As sea surface temperature rises, the Southern Ocean will become less effective as a sink for atmospheric CO2 and the increase of surface CO2 will be faster than that in the atmosphere. Increased surface CO2 would lead to ocean acidification and affect ecological systems and food chains.
基金supported by National Basic Research Program of China(973 Program,Grant No.2010CB951903)the National Natural Science Foundation of China(Grant Nos.41105054,41175074,and 41205043)China Meteorological Administration(Grant No.GYHY201306048 and CMAYBY2012-001)
文摘The multi-model ensemble （MME） of 20 models from the Coupled Model Intercomparison Project Phase Five （CMIP5） was used to analyze surface climate change in the 21st century under the representative con- centration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature （SAT） is 1.86℃ relative to the pre-industrial level, achieving the target to limit the global warming to 2℃. Associated with the ＂increase-peak-decline＂ greenhouse gases （GHGs） concentration path- way of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods： warming during 2006-55 and cooling during 2056-2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cool- ing period. The warming during 2006-55 is distributed globally, while the cooling during 2056-2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period.
基金funded by the open fund (SKLCS2011-04) from Stake Key Laboratory of Cryospheric Sciences and National Social Science Foundation of China(12BJY127)
文摘Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always receive higher attention from commercial media, government departments and mountain tourists in China and abroad. At present, more than 100 glaciers have been devel- oped successfully as famous tourist destinations all over the world. However, global climate change seriously affects mountain glaciers and its surrounding environment. According to the current accelerated retreat trend, natural and cultural landscapes of some glaciers will be weakened, even disappear in the future. Climate change will also inevitably affect mountain ecosystems, and tourism routes under ice and glacier experience activities in these ecosystems. Simultaneously, the disappearance of mountain glaciers will also lead to a clear reduction of tourism and local economic benefits. Based on these reasons, this paper took Mr. Yulong Snow scenic area as an example and analyzed the retreat trend of a typical glacier. We then put forward some scientific and rational response mechanisms and adaptation models based on climate change in order to help future sustainable development of mountain glacier tourism.
文摘This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 C during winter than of 4.9 C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.
基金Specialized Research Project for Public Welfare Industries(Meteorology)from the Ministry of Science and Technology(GYHY201406025)Specialized Project for Climate Change from China Meteorological Administration(CCSF201404,CCSF2011-25,CCSF201211CCSF 2011-25)+2 种基金Specialized Foundation for Low Carbon Development in Guangdong Province(2012-019)Foundation of Science Innovation Teams for Guangdong Meteorological Bureau(201102)Science and Technology Planning Project for Guangdong Province(2012A061400012)
文摘Based on RegCM4,a climate model system,we simulated the distribution of the present climate(1961-1990)and the future climate(2010-2099),under emission scenarios of RCPs over the whole Pearl River Basin.From the climate parameters,a set of mean precipitation,wet day frequency,and mean wet day intensity and several precipitation percentiles are used to assess the expected changes in daily precipitation characteristics for the 21 st century.Meanwhile the return values of precipitation intensity with an average return of 5,10,20,and 50 years are also used to assess the expected changes in precipitation extremes events in this study.The structure of the change across the precipitation distribution is very coherent between RCP4.5 and RCP8.5.The annual,spring and winter average precipitation decreases while the summer and autumn average precipitation increases.The basic diagnostics of precipitation show that the frequency of precipitation is projected to decrease but the intensity is projected to increase.The wet day percentiles(q90 and q95) also increase,indicating that precipitation extremes intensity will increase in the future.Meanwhile,the5-year return value tends to increase by 30%-45%in the basins of Liujiang River,Red Water River,Guihe River and Pearl River Delta region,where the 5-year return value of future climate corresponds to the 8-to 10-year return value of the present climate,and the 50-year return value corresponds to the 100-year return value of the present climate over the Pearl River Delta region in the 2080 s under RCP8.5,which indicates that the warming environment will give rise to changes in the intensity and frequency of extreme precipitation events.
基金supported by the National Natural Science Foundation of China(Grants No.41206021 and 41276018)the National Basic Research Program of China(Grant No.2012CB955601)+2 种基金the Young Scientist Foundation of the State Oceanic Administration,China(Grant No.2012251)the U.S.National Science Foundation Belmont Forum Program(Grant No.ICER-1342644)the GASI-03-01-01-09
文摘Because of the environmental and socioeconomic impacts of anthropogenic sea level rise （SLR）, it is very important to understand the processes leading to past and present SLRs towards more reliable future SLR projections. A regional ocean general circulation model （ROGCM）, with a grid refinement in the Bohai, Yellow, and East China Seas （BYECSs）, was set up to project SLR induced by the ocean dynamic change in the 21st century. The model does not consider the contributions from ice sheets and glacier melting. Data of all forcing terms required in the model came from the simulation of the Community Climate System Model version 3.0 （CCSM3） under the International Panel on Climate Change （IPCC）-A2 scenario. Simulation results show that at the end of the 21st century, the sea level in the BYECSs will rise about 0.12 to 0.20 m. The SLR in the BYECSs during the 21st century is mainly caused by the ocean mass redistribution due to the ocean dynamic change of the Pacific Ocean, which means that water in the Pacific Ocean tends to move to the continental shelves of the BYECSs, although the local steric sea level change is another factor.
基金Supported by the China National Global Change Major Research Project(No.2013CB956201)the National Science Foundation of China(NSFC)Key Project(No.41130859)+1 种基金the NSFC(Nos.41506009,41521091)the NSFC Major Project(No.41490643)
文摘Based on 22 of the climate models from phase 3 of the Coupled Model Intercomparison Project, we investigate the ability of the models to reproduce the spatiotemporal features of the wintertime North Pacific Oscillation(NPO), which is the second most important factor determining the wintertime sea level pressure field in simulations of the pre-industrial control climate, and evaluate the NPO response to the future most reasonable global warming scenario(the A1B scenario). We reveal that while most models simulate the geographic distribution and amplitude of the NPO pattern satisfactorily, only 13 models capture both features well. However, the temporal variability of the simulated NPO could not be significantly correlated with the observations. Further analysis indicates the weakened NPO intensity for a scenario of strong global warming is attributable to the reduced lower-tropospheric baroclinicity at mid-latitudes, which is anticipated to disrupt large-scale and low-frequency atmospheric variability, resulting in the diminished transfer of energy to the NPO, together with its northward shift.
基金Supported by the National Natural Science Foundation of China(Grant No.11301291)the Open Fund of State Key Laboratory of Remote Sensing Science of China(Grant No.OFSLRSS201206)
文摘Change monitoring of distribution in time series models is an important issue. This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series, which is based on a weighed empirical process of residuals with weights equal to the regressors. The asymptotic properties of our monitoring statistic are derived under the null hypothesis of no change in distribution. The finite sample properties are investigated by a simulation. As it turns out, the procedure is not only able to detect distributional changes but also changes in the regression coefficient and mean, Finally, we apply the statistic to a groups of financial data.
文摘The cause-effect relationship is not always possible to trace in GCMs because of the simultaneous inclusion of several highly complex physical processes. Furthermore, the inter-GCM differences are large and there is no simple way to reconcile them. So, simple climate models, like statistical-dynamical models (SDMs), appear to be useful in this context. This kind of models is essentially mechanistic, being directed towards understanding the dependence of a particular mechanism on the other parameters of the problem. In this paper, the utility of SDMs for studies of climate change is discussed in some detail. We show that these models are an indispensable part of hierarchy of climate models.
基金Supported by the National Natural Science Foundation of China (No.41171346,No. 41071286)the Fundamental Research Funds for the Central Universities (No. 20102130103000005)the National 973 Program of China (No. 2007CB714402‐5)
文摘Discriminant space defining area classes is an important conceptual construct for uncertainty characterization in area-class maps.Discriminant models were promoted as they can enhance consistency in area-class mapping and replicability in error modeling.As area classes are rarely completely separable in empirically realized discriminant space,where class inseparabil-ity becomes more complicated for change categorization,we seek to quantify uncertainty in area classes(and change classes)due to measurement errors and semantic discrepancy separately and hence assess their relative margins objectively.Experiments using real datasets were carried out,and a Bayesian method was used to obtain change maps.We found that there are large differences be-tween uncertainty statistics referring to data classes and information classes.Therefore,uncertainty characterization in change categorization should be based on discriminant modeling of measurement errors and semantic mismatch analysis,enabling quanti-fication of uncertainty due to partially random measurement errors,and systematic categorical discrepancies,respectively.
文摘Egypt suffers from the impacts of climate change. Adaption plans should solve the shortage in water resources and increase the use of renewable energy. Detailed data on rainfall as non conventional water and detailed data on potential renewable energy are important. The added value of this research is to investigate the suitability of satellite data locally in North Sinai in Egypt. The Tropical Rainfall Measuring Mission (TRMM) satellites and available data from ground rain gauges are studied at North Sinai of Egypt. Local multiplication factors and correlation equations on a monthly basis were developed based on short term historical data. General equation based on short term data was developed to enhance TRMM data for the rainy season to minimize spatial and temporal errors. This equation would be very useful, especially in the ungauged areas in North Sinai to adjust TRMM rainfall data. TRMM data are spatially distributed, so it enhances the hydrology models for runoff estimation. This runoff could be used as non conventional water resource. The runoff was estimated in the RasSudr area in the 2010 storm to be 3.6 (m3/s). The hydropower of this runoff was estimated and ranged from 15,135 to 57,352 (kWh). The solar energy is studied from (NASA) satellite data. The monthly averaged solar energy was estimated to get possible generated power from the solar panel at locations of rainfall ground stations. The generated solar energy would supply self-sufficient energy for ground stations measuring instruments rather than batteries. The results show that a small solar panel project of 200 (m2) could safe electric network power by generating about 20,385 (kWh/year). The results of this study could help in enhancing adapting plans for climate change and runoff estimation model that needs grid data, especially in the area lacking ground data.
基金funded by the National Natural Science Foundation of China (42174030)Major Science and Technology Program for Hubei Province (Grant No.2022AAA002)+2 种基金Special fund of Hubei Luojia Loboratory (220100020)the National Natural Science Foundation of China under Grant 42304031the China Postdoctoral Science Foundation 2022M722441。
文摘Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.
