We propose that the level at which the conodont species Idiognathodus simulator （Ellison 1941） （sensu stricto） first appears be selected to mark the base of the Gzhelian Stage, because we believe that this is the ...We propose that the level at which the conodont species Idiognathodus simulator （Ellison 1941） （sensu stricto） first appears be selected to mark the base of the Gzhelian Stage, because we believe that this is the optimal level by which this boundary can be correlated. This taxon has a short range and a wide distribution, as shown by correlation of glacial-eustatic cyclothems across the Kasimovian-Gzhelian boundary interval among Midcontinent North America and the Moscow and Donets basins of eastern Europe, based on scale of the cyclothems along with several aspects of biostrati- graphy. Outside of these areas, I. simulator （sensu stricto） is known also from other parts of the U.S., and is reported from the southern Urals and south-central China in its expected position between other widespread taxa. Its first appearance is consistent with the current ammonoid placement of the boundary （first appearance of Shumardites cuyleri）, and it is also compatible with certain aspects of the distribution of Eurasian fusulinid faunas （e.g., lectotype ofRauserites rossicus）.展开更多
An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoo...An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoobservations of sea surface temperature(SST),sea surface height(SSH),sea surface salinity(SSS),temperature and salinity(T/S)profiles were first generated in a free model run.Then,a series of sensitivity tests initialized with predefined bias were conducted for a one-year period;this involved a free run(CTR)and seven assimilation runs.These tests allowed us to check the analysis field accuracy against the"truth".As expected,data assimilation improved all investigated quantities;the joint assimilation of all variables gave more improved results than assimilating them separately.One-year predictions initialized from the seven runs and CTR were then conducted and compared.The forecasts initialized from joint assimilation of surface data produced comparable SST root mean square errors to that from assimilation of T/S profiles,but the assimilation of T/S profiles is crucial to reduce subsurface deficiencies.The ocean surface currents in the tropics were better predicted when initial conditions produced by assimilating T/S profiles,while surface data assimilation became more important at higher latitudes,particularly near the western boundary currents.The predictions of ocean heat content and mixed layer depth are significantly improved initialized from the joint assimilation of all the variables.Finally,a central Pacific El Ni?o was well predicted from the joint assimilation of surface data,indicating the importance of joint assimilation of SST,SSH,and SSS for ENSO predictions.展开更多
Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air poll...Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.展开更多
River floods(fluvial floods)are a global concern,inflicting substantial harm on human safety and societal progress[1].Unfortunately,river floods have been amplified by the increase in extreme precipitation events indu...River floods(fluvial floods)are a global concern,inflicting substantial harm on human safety and societal progress[1].Unfortunately,river floods have been amplified by the increase in extreme precipitation events induced by global climate warming[2,3],including the Third Pole(TP)region.Furthermore,TP is home to the most extensive glaciers and snow cover outside the Arctic and Antarctic,supplying abundant meltwater to several major Asian transboundary rivers(e.g.,Indus,Ganges-Brahmaputra,Salween,and Mekong)[4].展开更多
Based on the C-Coupler platform,the semi-unstructured Climate System Model,Synthesis Community Integrated Model version 2(SYCIM2.0),has been developed at the School of Atmospheric Sciences,Sun Yat-sen University.SYCIM...Based on the C-Coupler platform,the semi-unstructured Climate System Model,Synthesis Community Integrated Model version 2(SYCIM2.0),has been developed at the School of Atmospheric Sciences,Sun Yat-sen University.SYCIM2.0 aims to meet the demand for seamless climate prediction through accurate climate simulations and projections.This paper provides an overview of SYCIM2.0 and highlights its key features,especially the coupling of an unstructured ocean model and the tuning process.An extensive evaluation of its performance,focusing on the East Asian Summer Monsoon(EASM),is presented based on long-term simulations with fixed external forcing.The results suggest that after nearly 240 years of integration,SYCIM2.0 achieves a quasi-equilibrium state,albeit with small trends in the net radiation flux at the top-of-atmosphere(TOA)and Earth’s surface,as well as with global mean near-surface temperatures.Compared to observational and reanalysis data,the model realistically simulates spatial patterns of sea surface temperature(SST)and precipitation centers to include their annual cycles,in addition to the lower-level wind fields in the EASM region.However,it exhibits a weakened and eastward-shifted Western Pacific Subtropical High(WPSH),resulting in an associated precipitation bias.SYCIM2.0 robustly captures the dominant mode of the EASM and its close relationship with the El Niño-Southern Oscillation(ENSO)but exhibits relatively poor performance in simulating the second leading mode and the associated air–sea interaction processes.Further comprehensive evaluations of SYCIM2.0 will be conducted in future studies.展开更多
The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and trends in coupled atmosphere-hydrology simulations are...The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and trends in coupled atmosphere-hydrology simulations are identified through a bibliometric analysis, and the challenges and opportunities in this field are reviewed and summarized. Most climate models adopt the one-dimensional (vertical) land surface parameterization, which does not include a detailed description of basin-scale hydrological processes, particularly the effects of human activities on the underlying surfaces. To understand the interaction mechanism between hydrological processes and climate change, a large number of studies focused on the climate feedback effects of hydrological processes at different spatio-temporal scales, mainly through the coupling of hydrological and climate models. The improvement of the parameterization of hydrological process and the development of large-scale hydrological model in land surface process model lay a foundation for terrestrial hydrological-climate coupling simulation, based on which, the study of terrestrial hydrological-climate coupling is evolving from the traditional unidirectional coupling research to the two-way coupling study of "climate-hydrology" feedback. However, studies of fully coupled atmosphere-hydrology simulations (also called atmosphere-hydrology two-way coupling) are far from mature. The main challenges associated with these studies are: improving the potential mismatch in hydrological models and climate models; improving the stability of coupled systems; developing an effective scale conversion scheme; perfecting the parameterization scheme; evaluating parameter uncertainties; developing effective methodology for model parameter transplanting; and improving the applicability of models and high/super-resolution simulation. Solving these problems and improving simulation accuracy are directions for future hydro-climate coupling simulation research.展开更多
Accurate and reliable cropland surface information is of vital importance for agricultural planning and food security monitoring. As several global land cover datasets have been independently released, an inter-compar...Accurate and reliable cropland surface information is of vital importance for agricultural planning and food security monitoring. As several global land cover datasets have been independently released, an inter-comparison of these data products on the classification of cropland is highly needed. This paper presents an assessment of cropland classifications in four global land cover datasets, i.e., moderate resolution imaging spectrometer （MODIS） land cover product, global land cover map of 2009 （GlobCover2009）, finer resolution observation and monitoring of global cropland （FROM-GC） and 30-m global land cover dataset （GlobeLand30）. The temporal coverage of these four datasets are circa 2010. One of the typical agricultur- al regions of China, Shaanxi Province, was selected as the study area. The assessment proceeded from three aspects： accuracy, spatial agreement and absolute area. In accuracy assessment, 506 validation samples, which consist of 168 cropland samples and 338 non-cropland ones, were automatically and systematically selected, and manually interpreted by referencing high-resolution images dated from 2009 to 2011 on Google Earth. The results show that the overall accuracy （OA） of four datasets ranges from 61.26 to 80.63%. GlobeLand30 dataset, with the highest accuracy, is the most accurate dataset for cropland classification. The cropland spatial agreement （mainly located in the plain ecotope of Shaanxi） and the non-cropland spatial agreement （sparsely distributed in the south and middle of Shaanxi） of the four datasets only makes up 33.96% of the whole province. FIROM-GC and GlobeLand30, obtaining the highest spatial agreement index of 62.40%, have the highest degree of spatial consistency. In terms of the absolute area, MODIS underestimates the cropland area, while GlobCover2009 significantly overestimates it. These findings are of value in revealing to which extent and on which aspect that these global land cover datasets may agree with each other at small scale on each ecotope region. The approaches taken in this study could be used to derive a fused cropland classification dataset.展开更多
The tropical Pacific has begun to experience a new type of El Nio, which has occurred particularly frequently during the last decade, referred to as the central Pacific(CP) El Nio. Various coupled models with differen...The tropical Pacific has begun to experience a new type of El Nio, which has occurred particularly frequently during the last decade, referred to as the central Pacific(CP) El Nio. Various coupled models with different degrees of complexity have been used to make real-time El Nio predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Nio and how much is common to both this type and the conventional Eastern Pacific(EP)-type El Nio. In this study, the deterministic performance of an El Nio–Southern Oscillation(ENSO) ensemble prediction system is examined for the two types of El Nio. Ensemble hindcasts are run for the nine EP El Nio events and twelve CP El Nio events that have occurred since 1950. The results show that(1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times;(2) the systematic forecast biases come mostly from the prediction of the CP events; and(3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Nio. Further improvements to coupled atmosphere–ocean models in terms of CP El Nio prediction should be recognized as a key and high-priority task for the climate prediction community.展开更多
A nested circulation model system based on the Princeton ocean model （POM） is set up to simulate the currentmeter data from a bottom-mounted Acoustic Doppler Profiler （ADP） deployed at the 30 m depth in the Lunan...A nested circulation model system based on the Princeton ocean model （POM） is set up to simulate the currentmeter data from a bottom-mounted Acoustic Doppler Profiler （ADP） deployed at the 30 m depth in the Lunan（South Shandong Province, China） Trough south of the Shandong Peninsula in the summer of 2008, and to study the dynamics of the circulation in the southwestern Huanghai Sea （Yellow Sea）. The model has reproduced well the observed subtidal current at the mooring site. The results of the model simulation suggest that the bottom topography has strong steering effects on the regional circulation in summer. The model simulation shows that the Subei （North Jiangsu Province, China）coastal current flows north- ward in summer, in contrast to the southeastward current in the center of the Lunan Trough measured by the moored currentmeter. The analyses of the model results suggest that the southeastward current at the mooring site in the Lunan Trough is forced by the westward wind-driven current along the Lunan coast, which meets the northward Subei coastal current at the head of the Haizhou Bay to flow along an offshore path in the southeastward direction in the Lunan Trough. Analysis suggests that the Subei coastal current, the Lunan coastal current, and the circulation in the Lunan Trough are independent current systems con- trolled by different dynamics. Therefore, the current measurements in the Lunan Trough cannot be used to represent the Subei coastal current in general.展开更多
Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of...Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of the United Nations General Assembly in September 2020,President Xi Jinping announced that China would adopt more vigorous policies and measures against climate change.展开更多
In recent decades,a greening tendency due to increased vegetation has been noted around the Taklimakan Desert(TD),but the impact of such a change on the local hydrological cycle remains uncertain.Here,we investigate t...In recent decades,a greening tendency due to increased vegetation has been noted around the Taklimakan Desert(TD),but the impact of such a change on the local hydrological cycle remains uncertain.Here,we investigate the response of the local hydrological cycle and atmospheric circulation to a green TD in summer using a pair of global climate model(Community Earth System Model version 1.2.1)simulations.With enough irrigation to support vegetation growth in the TD,the modeling suggests first,that significant increases in local precipitation are attributed to enhanced local recycling of water,and second,that there is a corresponding decrease of local surface temperatures.On the other hand,irrigation and vegetation growth in this low-lying desert have negligible impacts on the large-scale circulation and thus the moisture convergence for enhanced precipitation.It is also found that the green TD can only be sustained by a large amount of irrigation water supply since only about one-third of the deployed water can be“recycled”locally.Considering this,devising a way to encapsulate the irrigated water within the desert to ensure more efficient water recycling is key for maintaining a sustainable,greening TD.展开更多
Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and ...Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and risk management in ag- ricultural and disaster-related decision-making at many concerned agencies. Currently concerned agencies mostly rely on field surveys to obtain crop loss information and compensate farmers＇ loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. The results from such methods suffer from inaccuracy, subjectiveness, untimeliness, and lack of reproducibility. Recent studies have demonstrated that Earth observation （EO） data could be used in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. However, there is no operational decision support system, which employs such EO-based data and algorithms for operational flood-related crop decision-making. This paper describes the development of an EO-based flood crop loss assessment cyber-service system, RF-CLASS, for supporting flood-related crop statistics and insurance decision-making. Based on the service-orientated architecture, RF-CLASS has been implemented with open interoperability specifications to facilitate the interoperability with EO data systems, particularly the National Aeronautics and Space Administration （NASA） Earth Observing System Data and Information System （EOSDIS）, for automatically fetching the input data from the data systems. Validated EO algorithms have been implemented as web services in the system to operationally produce a set of flood-related products from EO data, such as flood frequency, flooded acreage, and degree of crop damage, for supporting decision-making in flood statistics and flood crop insurance policy. The system leverages recent advances in the remote sensing-based flood monitoring and assessment, the near-real-time availability of EO data, the service-oriented architecture, geospatial interoperability standards, and the standard-based geospatial web service technology. The prototypical system has automatically generated the flood crop loss products and demonstrated the feasibility of using such products to improve the agricultural decision-making. Evaluation of system by the end-user agencies indicates that significant improvement on flood-related crop decision-making has been achieved with the system.展开更多
Annual influenza B virus epidemics and outbreaks cause severe influenza diseases in humans and pose a threat to public health. China is an important epidemic area of influenza B viruses. However, the spatial, temporal...Annual influenza B virus epidemics and outbreaks cause severe influenza diseases in humans and pose a threat to public health. China is an important epidemic area of influenza B viruses. However, the spatial, temporal transmission pathways and the demography history of influenza B viruses in China remain unknown. We collected the haemagglutinin gene sequences sampled of influenza B virus in China between 1973 and 2018. A Bayesian Markov chain Monte Carlo phylogeographic discrete approach was used to infer the spatial and temporal phylodynamics of influenza B virus. The Bayesian phylogeographic analysis of influenza B viruses showed that the North subtropical and South subtropical zones are the origins of the Victoria and Yamagata lineage viruses, respectively. Furthermore, the South temperate and North subtropical zones acted as transition nodes in the Victoria lineage virus dispersion network and that the North subtropical and Mid subtropical zones acted as transition nodes in the Yamagata lineage virus dispersion network. Our findings contribute to the knowledge regarding the spatial and temporal patterns of influenza B virus outbreaks in China.展开更多
As an important secondary photochemical pollutant,peroxyacetyl nitrate(PAN)has been studied over decades,yet its simulations usually underestimate the corresponding observations,especially in polluted areas.Recent obs...As an important secondary photochemical pollutant,peroxyacetyl nitrate(PAN)has been studied over decades,yet its simulations usually underestimate the corresponding observations,especially in polluted areas.Recent observations in north China found unusually high concentrations of PAN during wintertime heavy haze events,but the current model still cannot reproduce the observations,and researchers speculated that nitrous acid(HONO)played a key role in PAN formation.For the first time we systematically assessed the impact of potential HONO sources on PAN formation mechanisms in eastern China using the Weather Research and Forecasting/Chemistry(WRF-Chem)model in February of 2017.The results showed that the potential HONO sources significantly improved the PAN simulations,remarkably accelerated the RO x(sum of hydroxyl,hydroperoxyl,and organic peroxy radicals)cycles,and resulted in 80%–150%enhancements of PAN near the ground in the coastal areas of eastern China and 10%–50%enhancements in the areas around 35–40°N within 3 km during a heavy haze period.The direct precursors of PAN were aldehyde and methylglyoxal,and the primary precursors of PAN were alkenes with C>3,xylenes,propene and toluene.The above results suggest that the potential HONO sources should be considered in regional and global chemical transport models when conducting PAN studies.展开更多
A double-plume convective parameterization scheme is revised to improve the precipitation simulation of a global model(Global-to-Regional Integrated Forecast System;GRIST).The improvement is achieved by considering th...A double-plume convective parameterization scheme is revised to improve the precipitation simulation of a global model(Global-to-Regional Integrated Forecast System;GRIST).The improvement is achieved by considering the effects of large-scale dynamic processes on the trigger of deep convection.The closure,based on dynamic CAPE,is improved accordingly to allow other processes to consume CAPE under the more restricted convective trigger condition.The revised convective parameterization is evaluated with a variable-resolution model setup(110–35 km,refined over East Asia).The Atmospheric Model Intercomparison Project(AMIP)simulations demonstrate that the revised convective parameterization substantially delays the daytime precipitation peaks over most land areas,leading to an improved simulated diurnal cycle,evidenced by delayed and less frequent afternoon precipitation.Meanwhile,changes to the threshold of the trigger function yield a small impact on the diurnal amplitude of precipitation because of the consistent setting of dCAPE-based trigger and closure.The simulated mean precipitation remains reasonable,with some improvements evident along the southern slopes of the Tibetan Plateau.The revised scheme increases convective precipitation at the lower levels of the windward slope and reduces the large-scale precipitation over the upper slope,ultimately shifting the rainfall peak southward,which is in better agreement with the observations.展开更多
Hyperspectral sensors provide the potential for direct estimation of pasture feed quality attributes. However, remote sensing retrieval of digestibility and fibre (lignin and cellulose) content of vegetation has prove...Hyperspectral sensors provide the potential for direct estimation of pasture feed quality attributes. However, remote sensing retrieval of digestibility and fibre (lignin and cellulose) content of vegetation has proven to be challenging since tissue optical properties may not be propagated to the canopy level in mixed cover types. In this study, partial least squares regression on spectra from HyMap and Hyperion imagery were used to construct predictive models for estimation of crude protein, digestibility, lignin and cellulose concentration in temperate pastures. HyMap and Hyperion imagery and field spectra were collected over four pasture sites in southern Victoria, Australia. Co-incident field samples were analyzed with wet chemistry methods for crude protein, lignin and cellulose concentration, and digestibility was calculated from fiber determinations. Spectral data were subset based on sites and time of year of collection. Reflectance spectra were extracted from the hyperspectral imagery and collated for analysis. Six different transformations including derivatives and continuum removal were applied to the spectra to enhance absorption features sensitive to the quality attributes. The transformed reflectance spectra were then subjected to partial least squares regression, with full cross-validation “leave-one-out” technique, against the quality attributes to assess effects of the spectral transformations and post-atmospheric smoothing techniques to construct predictive models. Model performance between spectrometers, subsets and attributes were assessed using a coefficient of variation (CV), —the interquantile (IQ) range of the attribute values divided by the root mean square error of prediction (RMSEP) from the models. The predictive models with the highest CVs were obtained for digestibility for all spectra types, with HyMap the highest. However, models with slightly lower CVs were obtained for crude protein, lignin and cellulose. The spectral regions for diagnostic wavelengths fell within the chlorophyll well, red edge, and 2000-2300 nm ligno-cellulose-protein regions, with some wavelengths selected between the 1600 and 1800 nm region sensitive to nitrogen, protein, lignin and cellulose. The digestibility models with the highest CV’s had confidence intervals corresponding to ±5% digestibility, which constitutes approximately 30% of the measured range. The cellulose and lignin models with the highest CV’s also had similar confidence intervals but the slopes of the prediction lines were substantially less than 1:1 indicating reduced sensitivity. The predictive relationships established here could be applied to categorizing pasture quality into range classes and to determine whether pastures are above or below for example threshold values for livestock productivity benchmarks.展开更多
Climate change and air pollution are primarily caused by the combustion and utilization of fossil fuels.Both climate change and air pollution cause health problems.Based on the development of China,it is extremely imp...Climate change and air pollution are primarily caused by the combustion and utilization of fossil fuels.Both climate change and air pollution cause health problems.Based on the development of China,it is extremely important to explore the synergies of the energy transition,CO_(2) reduction,air pollution control,and health improvement under the target of carbon peaking before 2030 and carbon neutrality before 2060.This study introduces the policy evolution and research progress related to energy,climate change,and the environment in China and proposes a complete energy-climate-air-health mechanism framework.Based on the MESSAGE-GLOBIOM integrated assessment model,emission inventory and chemical transport model,and exposure-response function,a comprehensive assessment method of energy-climate-air-health synergies was established and applied to quantify the impacts of Chinese Energy Interconnection Carbon Neutrality(CEICN)scenario.The results demonstrate that,by 2060,the SO_(2),NO_(x) and PM_(2.5) emissions are estimated to be reduced by 91%,85%,and 90%respectively compared to the business-as-usual(BAU)scenario.The direct health impacts brought by achieving the goal of carbon neutrality will drive the proactive implementation of more emission reduction measures and bring greater benefits to human health.展开更多
Based on the Beijing Climate Center’s land surface model BCC_AVIM(Beijing Climate Center Atmosphere-Vegetation Interaction Model),the ensemble Kalman filter(EnKF)algorithm has been used to perform an assimilation exp...Based on the Beijing Climate Center’s land surface model BCC_AVIM(Beijing Climate Center Atmosphere-Vegetation Interaction Model),the ensemble Kalman filter(EnKF)algorithm has been used to perform an assimilation experiment on the Moderate Resolution Imaging Spectroradiometer(MODIS)land surface temperature(LST)product to study the influence of satellite LST data frequencies on surface temperature data assimilations.The assimilation results have been independently tested and evaluated by Global Land Data Assimilation System(GLDAS)LST products.The results show that the assimilation scheme can effectively reduce the BCC_AVIM model simulation bias and the assimilation results reflect more reasonable spatial and temporal distributions.Diurnal variation information in the observation data has a significant effect on the assimilation results.Assimilating LST data that contain diurnal variation information can further improve the accuracy of the assimilation analysis.Overall,when assimilation is performed using observation data at 6-hour intervals,a relatively good assimilation result can be obtained,indicated by smaller bias(<2.2K)and root-mean-square-error(RMSE)(<3.7K)and correlation coefficients larger than 0.60.Conversely,the assimilation using 24-hour data generally showed larger bias(>2.2K)and RMSE(>4K).Further analysis showed that the sensitivity of assimilation effect to diurnal variations in LST varies with time and space.The assimilation using observations with a time interval of 3 hours has the smallest bias in Oceania and Africa(both<1K);the use of 24-hour interval observation data for assimilation produces the smallest bias(<2.2K)in March,April and July.展开更多
The spread of H5 highly pathogenic avian influenza viruses poses serious threats to the poultry industry,wild bird ecology and human health.Circulation of H5 viruses between poultry and wild birds is a significant pub...The spread of H5 highly pathogenic avian influenza viruses poses serious threats to the poultry industry,wild bird ecology and human health.Circulation of H5 viruses between poultry and wild birds is a significant public health threat in China.Thus,viral migration networks in this region need to be urgently studied.Here,we conducted molecular genetic analyses of the hemagglutinin genes of H5 highly pathogenic avian influenza viruses in multiple hosts from 2000 to 2018 in China.Our aim was to clarify the roles of different hosts in the evolution of H5 viruses.We used a flexible Bayesian statistical framework to simulate viral space diffusion and continuous-time Markov chains to infer the dynamic evolutionary process of spatiotemporal dissemination.Bayesian phylogeographic analysis of H5 viruses showed for the first time that H5 viruses in poultry and wild birds were present in Guangdong Province.Furthermore,Guangdong,Jiangsu,Shanghai and Hunan acted as the epicenters for the spread of various H5 subtypes viruses in poultry,and Henan,Shanghai,Hong Kong and Inner Mongolia acted as epicenters for the spread of various H5 subtypes viruses in wild birds.Thus,H5 viruses exhibited distinct evolutionary dynamics in poultry and wild birds.Our findings extend our understanding of the transmission and spread of highly pathogenic H5 avian influenza viruses in China.展开更多
The outbreak of coronavirus disease 2019(COVID-19)has had a considerable impact on every industrial sector.As a pillar of economic development,the energy sector is experiencing difficult times during the global pandem...The outbreak of coronavirus disease 2019(COVID-19)has had a considerable impact on every industrial sector.As a pillar of economic development,the energy sector is experiencing difficult times during the global pandemic.This paper reviews the impact of the pandemic on the global energy sector in terms of demand,price,employment,government policy,countermeasures,and academic research,and focuses on the two largest energy countries in the world:China and the United States.Although the virus has dramatically impacted the energy sector,action to address climate issues has not been suspended,but has become more urgent than ever.Experts have pointed out that it is time to promote the transition to clean energy vigorously.Thus,here we discuss progress towards clean energy transition,including bioenergy,mineral resources for clean energy techniques,batteries,and electrolyzers.The results indicate that supply chain stability,energy storage,and policymaking during the epidemic period and post-epidemic period are significant challenges for the transition to clean energy.However,the transition can also bring new opportunities for employment,economic recovery,and the human living environment.展开更多
文摘We propose that the level at which the conodont species Idiognathodus simulator （Ellison 1941） （sensu stricto） first appears be selected to mark the base of the Gzhelian Stage, because we believe that this is the optimal level by which this boundary can be correlated. This taxon has a short range and a wide distribution, as shown by correlation of glacial-eustatic cyclothems across the Kasimovian-Gzhelian boundary interval among Midcontinent North America and the Moscow and Donets basins of eastern Europe, based on scale of the cyclothems along with several aspects of biostrati- graphy. Outside of these areas, I. simulator （sensu stricto） is known also from other parts of the U.S., and is reported from the southern Urals and south-central China in its expected position between other widespread taxa. Its first appearance is consistent with the current ammonoid placement of the boundary （first appearance of Shumardites cuyleri）, and it is also compatible with certain aspects of the distribution of Eurasian fusulinid faunas （e.g., lectotype ofRauserites rossicus）.
基金The National Key Research and Development Program of China under contract Nos 2016YFA0602102 and2016YFC1401702the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)under contract No.GML2019ZD0306+1 种基金the National Natural Science Foundation of China under contract No.41306005CAS Pioneer Hundred Talents Program Startup Fund by South China Sea Institute of Oceanology under contract No.Y9SL011001。
文摘An ensemble optimal interpolation(EnOI)data assimilation method is applied in the BCCCSM1.1 to investigate the impact of ocean data assimilations on seasonal forecasts in an idealized twin experiment framework.Pseudoobservations of sea surface temperature(SST),sea surface height(SSH),sea surface salinity(SSS),temperature and salinity(T/S)profiles were first generated in a free model run.Then,a series of sensitivity tests initialized with predefined bias were conducted for a one-year period;this involved a free run(CTR)and seven assimilation runs.These tests allowed us to check the analysis field accuracy against the"truth".As expected,data assimilation improved all investigated quantities;the joint assimilation of all variables gave more improved results than assimilating them separately.One-year predictions initialized from the seven runs and CTR were then conducted and compared.The forecasts initialized from joint assimilation of surface data produced comparable SST root mean square errors to that from assimilation of T/S profiles,but the assimilation of T/S profiles is crucial to reduce subsurface deficiencies.The ocean surface currents in the tropics were better predicted when initial conditions produced by assimilating T/S profiles,while surface data assimilation became more important at higher latitudes,particularly near the western boundary currents.The predictions of ocean heat content and mixed layer depth are significantly improved initialized from the joint assimilation of all the variables.Finally,a central Pacific El Ni?o was well predicted from the joint assimilation of surface data,indicating the importance of joint assimilation of SST,SSH,and SSS for ENSO predictions.
基金supported by the National Natural Science Foundation of China(42277087,42130708,42471021,42277482,and 42361144876)the Natural Science Foundation of Guangdong Province(2024A1515012550)+3 种基金the Hainan Institute of National Park grant(KY-23ZK01)the Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan(JC2022011)the Shenzhen Science and Technology Program(JCYJ20240813112106009 and ZDSYS20220606100806014)the Scientific Research Start-up Funds(QD2021030C)from Tsinghua Shenzhen International Graduate School。
文摘Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.
基金supported by the National Key R&D Program of China(2024YFF0808602)the Second Tibetan Plateau Scientific Expedition and Research Program(2024QZKK0400)Tsinghua University(100008001).
文摘River floods(fluvial floods)are a global concern,inflicting substantial harm on human safety and societal progress[1].Unfortunately,river floods have been amplified by the increase in extreme precipitation events induced by global climate warming[2,3],including the Third Pole(TP)region.Furthermore,TP is home to the most extensive glaciers and snow cover outside the Arctic and Antarctic,supplying abundant meltwater to several major Asian transboundary rivers(e.g.,Indus,Ganges-Brahmaputra,Salween,and Mekong)[4].
基金funded by the National Natural Science Foundation of China(Grant Nos.U21A6001,42261144687,42175173)the Project supported by Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(Grant No.SML2023SP208)the GuangDong Basic and Applied Basic Research Foundation(2023A1515240036).
文摘Based on the C-Coupler platform,the semi-unstructured Climate System Model,Synthesis Community Integrated Model version 2(SYCIM2.0),has been developed at the School of Atmospheric Sciences,Sun Yat-sen University.SYCIM2.0 aims to meet the demand for seamless climate prediction through accurate climate simulations and projections.This paper provides an overview of SYCIM2.0 and highlights its key features,especially the coupling of an unstructured ocean model and the tuning process.An extensive evaluation of its performance,focusing on the East Asian Summer Monsoon(EASM),is presented based on long-term simulations with fixed external forcing.The results suggest that after nearly 240 years of integration,SYCIM2.0 achieves a quasi-equilibrium state,albeit with small trends in the net radiation flux at the top-of-atmosphere(TOA)and Earth’s surface,as well as with global mean near-surface temperatures.Compared to observational and reanalysis data,the model realistically simulates spatial patterns of sea surface temperature(SST)and precipitation centers to include their annual cycles,in addition to the lower-level wind fields in the EASM region.However,it exhibits a weakened and eastward-shifted Western Pacific Subtropical High(WPSH),resulting in an associated precipitation bias.SYCIM2.0 robustly captures the dominant mode of the EASM and its close relationship with the El Niño-Southern Oscillation(ENSO)but exhibits relatively poor performance in simulating the second leading mode and the associated air–sea interaction processes.Further comprehensive evaluations of SYCIM2.0 will be conducted in future studies.
基金National Key R&D Program of China,No.2017YFA0603702National Natural Science Foundation of China,No.41571019,No.41701023,No.41571028China Postdoctoral Science Foundation,No.2017M610867
文摘The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and trends in coupled atmosphere-hydrology simulations are identified through a bibliometric analysis, and the challenges and opportunities in this field are reviewed and summarized. Most climate models adopt the one-dimensional (vertical) land surface parameterization, which does not include a detailed description of basin-scale hydrological processes, particularly the effects of human activities on the underlying surfaces. To understand the interaction mechanism between hydrological processes and climate change, a large number of studies focused on the climate feedback effects of hydrological processes at different spatio-temporal scales, mainly through the coupling of hydrological and climate models. The improvement of the parameterization of hydrological process and the development of large-scale hydrological model in land surface process model lay a foundation for terrestrial hydrological-climate coupling simulation, based on which, the study of terrestrial hydrological-climate coupling is evolving from the traditional unidirectional coupling research to the two-way coupling study of "climate-hydrology" feedback. However, studies of fully coupled atmosphere-hydrology simulations (also called atmosphere-hydrology two-way coupling) are far from mature. The main challenges associated with these studies are: improving the potential mismatch in hydrological models and climate models; improving the stability of coupled systems; developing an effective scale conversion scheme; perfecting the parameterization scheme; evaluating parameter uncertainties; developing effective methodology for model parameter transplanting; and improving the applicability of models and high/super-resolution simulation. Solving these problems and improving simulation accuracy are directions for future hydro-climate coupling simulation research.
基金supported by the National High-Tech R&D Program of China (2012AA12A408)the Independent Scientific Research of Tsinghua University,China (20131089277,553302001)
文摘Accurate and reliable cropland surface information is of vital importance for agricultural planning and food security monitoring. As several global land cover datasets have been independently released, an inter-comparison of these data products on the classification of cropland is highly needed. This paper presents an assessment of cropland classifications in four global land cover datasets, i.e., moderate resolution imaging spectrometer （MODIS） land cover product, global land cover map of 2009 （GlobCover2009）, finer resolution observation and monitoring of global cropland （FROM-GC） and 30-m global land cover dataset （GlobeLand30）. The temporal coverage of these four datasets are circa 2010. One of the typical agricultur- al regions of China, Shaanxi Province, was selected as the study area. The assessment proceeded from three aspects： accuracy, spatial agreement and absolute area. In accuracy assessment, 506 validation samples, which consist of 168 cropland samples and 338 non-cropland ones, were automatically and systematically selected, and manually interpreted by referencing high-resolution images dated from 2009 to 2011 on Google Earth. The results show that the overall accuracy （OA） of four datasets ranges from 61.26 to 80.63%. GlobeLand30 dataset, with the highest accuracy, is the most accurate dataset for cropland classification. The cropland spatial agreement （mainly located in the plain ecotope of Shaanxi） and the non-cropland spatial agreement （sparsely distributed in the south and middle of Shaanxi） of the four datasets only makes up 33.96% of the whole province. FIROM-GC and GlobeLand30, obtaining the highest spatial agreement index of 62.40%, have the highest degree of spatial consistency. In terms of the absolute area, MODIS underestimates the cropland area, while GlobCover2009 significantly overestimates it. These findings are of value in revealing to which extent and on which aspect that these global land cover datasets may agree with each other at small scale on each ecotope region. The approaches taken in this study could be used to derive a fused cropland classification dataset.
基金supported by the National Program for Support of Top-notch Young Professionalsthe National Natural Science Foundation of China (Grant No. 41576019)J.-Y. YU was supported by the US National Science Foundation (Grant No. AGS-150514)
文摘The tropical Pacific has begun to experience a new type of El Nio, which has occurred particularly frequently during the last decade, referred to as the central Pacific(CP) El Nio. Various coupled models with different degrees of complexity have been used to make real-time El Nio predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Nio and how much is common to both this type and the conventional Eastern Pacific(EP)-type El Nio. In this study, the deterministic performance of an El Nio–Southern Oscillation(ENSO) ensemble prediction system is examined for the two types of El Nio. Ensemble hindcasts are run for the nine EP El Nio events and twelve CP El Nio events that have occurred since 1950. The results show that(1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times;(2) the systematic forecast biases come mostly from the prediction of the CP events; and(3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Nio. Further improvements to coupled atmosphere–ocean models in terms of CP El Nio prediction should be recognized as a key and high-priority task for the climate prediction community.
基金The 973 Project of China under contract No.2012CB95600the National Natural Science Foundation of China under contract Nos 40888001 and 41176019+1 种基金the Chinese Academy of Sciences under contract No. KZCX2-YW-JS204Qingdao Municipal under contract No.10-3-3-38jh
文摘A nested circulation model system based on the Princeton ocean model （POM） is set up to simulate the currentmeter data from a bottom-mounted Acoustic Doppler Profiler （ADP） deployed at the 30 m depth in the Lunan（South Shandong Province, China） Trough south of the Shandong Peninsula in the summer of 2008, and to study the dynamics of the circulation in the southwestern Huanghai Sea （Yellow Sea）. The model has reproduced well the observed subtidal current at the mooring site. The results of the model simulation suggest that the bottom topography has strong steering effects on the regional circulation in summer. The model simulation shows that the Subei （North Jiangsu Province, China）coastal current flows north- ward in summer, in contrast to the southeastward current in the center of the Lunan Trough measured by the moored currentmeter. The analyses of the model results suggest that the southeastward current at the mooring site in the Lunan Trough is forced by the westward wind-driven current along the Lunan coast, which meets the northward Subei coastal current at the head of the Haizhou Bay to flow along an offshore path in the southeastward direction in the Lunan Trough. Analysis suggests that the Subei coastal current, the Lunan coastal current, and the circulation in the Lunan Trough are independent current systems con- trolled by different dynamics. Therefore, the current measurements in the Lunan Trough cannot be used to represent the Subei coastal current in general.
基金supported by the National Natural Science Foundation of China(72140004).
文摘Achieving carbon neutrality is crucial in dealing with climate change and containing the increase in global temperature at below 1.5℃compared with preindustrial levels.During the general debate at the 75th session of the United Nations General Assembly in September 2020,President Xi Jinping announced that China would adopt more vigorous policies and measures against climate change.
基金This work was supported by the National Key Research Project of China(Grant No.2018YFC 1507001).
文摘In recent decades,a greening tendency due to increased vegetation has been noted around the Taklimakan Desert(TD),but the impact of such a change on the local hydrological cycle remains uncertain.Here,we investigate the response of the local hydrological cycle and atmospheric circulation to a green TD in summer using a pair of global climate model(Community Earth System Model version 1.2.1)simulations.With enough irrigation to support vegetation growth in the TD,the modeling suggests first,that significant increases in local precipitation are attributed to enhanced local recycling of water,and second,that there is a corresponding decrease of local surface temperatures.On the other hand,irrigation and vegetation growth in this low-lying desert have negligible impacts on the large-scale circulation and thus the moisture convergence for enhanced precipitation.It is also found that the green TD can only be sustained by a large amount of irrigation water supply since only about one-third of the deployed water can be“recycled”locally.Considering this,devising a way to encapsulate the irrigated water within the desert to ensure more efficient water recycling is key for maintaining a sustainable,greening TD.
基金supported by grants from the National Aeronautics and Space Administration Applied Science Program,USA (NNX12AQ31G,NNX14AP91G,PI:Dr.Liping Di)
文摘Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and risk management in ag- ricultural and disaster-related decision-making at many concerned agencies. Currently concerned agencies mostly rely on field surveys to obtain crop loss information and compensate farmers＇ loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. The results from such methods suffer from inaccuracy, subjectiveness, untimeliness, and lack of reproducibility. Recent studies have demonstrated that Earth observation （EO） data could be used in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. However, there is no operational decision support system, which employs such EO-based data and algorithms for operational flood-related crop decision-making. This paper describes the development of an EO-based flood crop loss assessment cyber-service system, RF-CLASS, for supporting flood-related crop statistics and insurance decision-making. Based on the service-orientated architecture, RF-CLASS has been implemented with open interoperability specifications to facilitate the interoperability with EO data systems, particularly the National Aeronautics and Space Administration （NASA） Earth Observing System Data and Information System （EOSDIS）, for automatically fetching the input data from the data systems. Validated EO algorithms have been implemented as web services in the system to operationally produce a set of flood-related products from EO data, such as flood frequency, flooded acreage, and degree of crop damage, for supporting decision-making in flood statistics and flood crop insurance policy. The system leverages recent advances in the remote sensing-based flood monitoring and assessment, the near-real-time availability of EO data, the service-oriented architecture, geospatial interoperability standards, and the standard-based geospatial web service technology. The prototypical system has automatically generated the flood crop loss products and demonstrated the feasibility of using such products to improve the agricultural decision-making. Evaluation of system by the end-user agencies indicates that significant improvement on flood-related crop decision-making has been achieved with the system.
基金partially supported by the National Research Program of the Ministry of Science and Technology of the People’s Republic of China(2016YFA0600104)donations from Delos Living LLC and the Cyrus Tang Foundation to Tsinghua University.
文摘Annual influenza B virus epidemics and outbreaks cause severe influenza diseases in humans and pose a threat to public health. China is an important epidemic area of influenza B viruses. However, the spatial, temporal transmission pathways and the demography history of influenza B viruses in China remain unknown. We collected the haemagglutinin gene sequences sampled of influenza B virus in China between 1973 and 2018. A Bayesian Markov chain Monte Carlo phylogeographic discrete approach was used to infer the spatial and temporal phylodynamics of influenza B virus. The Bayesian phylogeographic analysis of influenza B viruses showed that the North subtropical and South subtropical zones are the origins of the Victoria and Yamagata lineage viruses, respectively. Furthermore, the South temperate and North subtropical zones acted as transition nodes in the Victoria lineage virus dispersion network and that the North subtropical and Mid subtropical zones acted as transition nodes in the Yamagata lineage virus dispersion network. Our findings contribute to the knowledge regarding the spatial and temporal patterns of influenza B virus outbreaks in China.
基金This work was partially supported by the National Key Research and Development Program of China(No.2017YFC0209801)the National Natural Science Foundation of China(Nos.91544221,41575124)the National Research Program for Key Issues in Air Pollution Control(Nos.DQGG0102,DQGG0103).
文摘As an important secondary photochemical pollutant,peroxyacetyl nitrate(PAN)has been studied over decades,yet its simulations usually underestimate the corresponding observations,especially in polluted areas.Recent observations in north China found unusually high concentrations of PAN during wintertime heavy haze events,but the current model still cannot reproduce the observations,and researchers speculated that nitrous acid(HONO)played a key role in PAN formation.For the first time we systematically assessed the impact of potential HONO sources on PAN formation mechanisms in eastern China using the Weather Research and Forecasting/Chemistry(WRF-Chem)model in February of 2017.The results showed that the potential HONO sources significantly improved the PAN simulations,remarkably accelerated the RO x(sum of hydroxyl,hydroperoxyl,and organic peroxy radicals)cycles,and resulted in 80%–150%enhancements of PAN near the ground in the coastal areas of eastern China and 10%–50%enhancements in the areas around 35–40°N within 3 km during a heavy haze period.The direct precursors of PAN were aldehyde and methylglyoxal,and the primary precursors of PAN were alkenes with C>3,xylenes,propene and toluene.The above results suggest that the potential HONO sources should be considered in regional and global chemical transport models when conducting PAN studies.
基金supported by the National Key R&D Program of China on the Monitoring,Early Warning,and Prevention of Major Natural Disasters(Grant Nos.2018YFC1507005 and 02017YFC1502202)。
文摘A double-plume convective parameterization scheme is revised to improve the precipitation simulation of a global model(Global-to-Regional Integrated Forecast System;GRIST).The improvement is achieved by considering the effects of large-scale dynamic processes on the trigger of deep convection.The closure,based on dynamic CAPE,is improved accordingly to allow other processes to consume CAPE under the more restricted convective trigger condition.The revised convective parameterization is evaluated with a variable-resolution model setup(110–35 km,refined over East Asia).The Atmospheric Model Intercomparison Project(AMIP)simulations demonstrate that the revised convective parameterization substantially delays the daytime precipitation peaks over most land areas,leading to an improved simulated diurnal cycle,evidenced by delayed and less frequent afternoon precipitation.Meanwhile,changes to the threshold of the trigger function yield a small impact on the diurnal amplitude of precipitation because of the consistent setting of dCAPE-based trigger and closure.The simulated mean precipitation remains reasonable,with some improvements evident along the southern slopes of the Tibetan Plateau.The revised scheme increases convective precipitation at the lower levels of the windward slope and reduces the large-scale precipitation over the upper slope,ultimately shifting the rainfall peak southward,which is in better agreement with the observations.
文摘Hyperspectral sensors provide the potential for direct estimation of pasture feed quality attributes. However, remote sensing retrieval of digestibility and fibre (lignin and cellulose) content of vegetation has proven to be challenging since tissue optical properties may not be propagated to the canopy level in mixed cover types. In this study, partial least squares regression on spectra from HyMap and Hyperion imagery were used to construct predictive models for estimation of crude protein, digestibility, lignin and cellulose concentration in temperate pastures. HyMap and Hyperion imagery and field spectra were collected over four pasture sites in southern Victoria, Australia. Co-incident field samples were analyzed with wet chemistry methods for crude protein, lignin and cellulose concentration, and digestibility was calculated from fiber determinations. Spectral data were subset based on sites and time of year of collection. Reflectance spectra were extracted from the hyperspectral imagery and collated for analysis. Six different transformations including derivatives and continuum removal were applied to the spectra to enhance absorption features sensitive to the quality attributes. The transformed reflectance spectra were then subjected to partial least squares regression, with full cross-validation “leave-one-out” technique, against the quality attributes to assess effects of the spectral transformations and post-atmospheric smoothing techniques to construct predictive models. Model performance between spectrometers, subsets and attributes were assessed using a coefficient of variation (CV), —the interquantile (IQ) range of the attribute values divided by the root mean square error of prediction (RMSEP) from the models. The predictive models with the highest CVs were obtained for digestibility for all spectra types, with HyMap the highest. However, models with slightly lower CVs were obtained for crude protein, lignin and cellulose. The spectral regions for diagnostic wavelengths fell within the chlorophyll well, red edge, and 2000-2300 nm ligno-cellulose-protein regions, with some wavelengths selected between the 1600 and 1800 nm region sensitive to nitrogen, protein, lignin and cellulose. The digestibility models with the highest CV’s had confidence intervals corresponding to ±5% digestibility, which constitutes approximately 30% of the measured range. The cellulose and lignin models with the highest CV’s also had similar confidence intervals but the slopes of the prediction lines were substantially less than 1:1 indicating reduced sensitivity. The predictive relationships established here could be applied to categorizing pasture quality into range classes and to determine whether pastures are above or below for example threshold values for livestock productivity benchmarks.
基金supported by the GEIGC Science and Technology Project in the framework of“Research on Comprehensive Path Evaluation Methods and Practical Models for the Synergetic Development of Global Energy,Atmospheric Environment and Human Health”(grant No.20210302007).
文摘Climate change and air pollution are primarily caused by the combustion and utilization of fossil fuels.Both climate change and air pollution cause health problems.Based on the development of China,it is extremely important to explore the synergies of the energy transition,CO_(2) reduction,air pollution control,and health improvement under the target of carbon peaking before 2030 and carbon neutrality before 2060.This study introduces the policy evolution and research progress related to energy,climate change,and the environment in China and proposes a complete energy-climate-air-health mechanism framework.Based on the MESSAGE-GLOBIOM integrated assessment model,emission inventory and chemical transport model,and exposure-response function,a comprehensive assessment method of energy-climate-air-health synergies was established and applied to quantify the impacts of Chinese Energy Interconnection Carbon Neutrality(CEICN)scenario.The results demonstrate that,by 2060,the SO_(2),NO_(x) and PM_(2.5) emissions are estimated to be reduced by 91%,85%,and 90%respectively compared to the business-as-usual(BAU)scenario.The direct health impacts brought by achieving the goal of carbon neutrality will drive the proactive implementation of more emission reduction measures and bring greater benefits to human health.
文摘Based on the Beijing Climate Center’s land surface model BCC_AVIM(Beijing Climate Center Atmosphere-Vegetation Interaction Model),the ensemble Kalman filter(EnKF)algorithm has been used to perform an assimilation experiment on the Moderate Resolution Imaging Spectroradiometer(MODIS)land surface temperature(LST)product to study the influence of satellite LST data frequencies on surface temperature data assimilations.The assimilation results have been independently tested and evaluated by Global Land Data Assimilation System(GLDAS)LST products.The results show that the assimilation scheme can effectively reduce the BCC_AVIM model simulation bias and the assimilation results reflect more reasonable spatial and temporal distributions.Diurnal variation information in the observation data has a significant effect on the assimilation results.Assimilating LST data that contain diurnal variation information can further improve the accuracy of the assimilation analysis.Overall,when assimilation is performed using observation data at 6-hour intervals,a relatively good assimilation result can be obtained,indicated by smaller bias(<2.2K)and root-mean-square-error(RMSE)(<3.7K)and correlation coefficients larger than 0.60.Conversely,the assimilation using 24-hour data generally showed larger bias(>2.2K)and RMSE(>4K).Further analysis showed that the sensitivity of assimilation effect to diurnal variations in LST varies with time and space.The assimilation using observations with a time interval of 3 hours has the smallest bias in Oceania and Africa(both<1K);the use of 24-hour interval observation data for assimilation produces the smallest bias(<2.2K)in March,April and July.
基金supported by the National Research Program of the Ministry of Science and Technology of the People’s Republic of China(2016YFA0600104)by donations from Delos Living LLC and the Cyrus Tang Foundation to Tsinghua University
文摘The spread of H5 highly pathogenic avian influenza viruses poses serious threats to the poultry industry,wild bird ecology and human health.Circulation of H5 viruses between poultry and wild birds is a significant public health threat in China.Thus,viral migration networks in this region need to be urgently studied.Here,we conducted molecular genetic analyses of the hemagglutinin genes of H5 highly pathogenic avian influenza viruses in multiple hosts from 2000 to 2018 in China.Our aim was to clarify the roles of different hosts in the evolution of H5 viruses.We used a flexible Bayesian statistical framework to simulate viral space diffusion and continuous-time Markov chains to infer the dynamic evolutionary process of spatiotemporal dissemination.Bayesian phylogeographic analysis of H5 viruses showed for the first time that H5 viruses in poultry and wild birds were present in Guangdong Province.Furthermore,Guangdong,Jiangsu,Shanghai and Hunan acted as the epicenters for the spread of various H5 subtypes viruses in poultry,and Henan,Shanghai,Hong Kong and Inner Mongolia acted as epicenters for the spread of various H5 subtypes viruses in wild birds.Thus,H5 viruses exhibited distinct evolutionary dynamics in poultry and wild birds.Our findings extend our understanding of the transmission and spread of highly pathogenic H5 avian influenza viruses in China.
基金Project supported by the National Natural Science Foundation of China(No.71901184)the Fundamental Research Funds for the Central Universities,China。
文摘The outbreak of coronavirus disease 2019(COVID-19)has had a considerable impact on every industrial sector.As a pillar of economic development,the energy sector is experiencing difficult times during the global pandemic.This paper reviews the impact of the pandemic on the global energy sector in terms of demand,price,employment,government policy,countermeasures,and academic research,and focuses on the two largest energy countries in the world:China and the United States.Although the virus has dramatically impacted the energy sector,action to address climate issues has not been suspended,but has become more urgent than ever.Experts have pointed out that it is time to promote the transition to clean energy vigorously.Thus,here we discuss progress towards clean energy transition,including bioenergy,mineral resources for clean energy techniques,batteries,and electrolyzers.The results indicate that supply chain stability,energy storage,and policymaking during the epidemic period and post-epidemic period are significant challenges for the transition to clean energy.However,the transition can also bring new opportunities for employment,economic recovery,and the human living environment.
