A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Ni...A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.展开更多
优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入...优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入下小麦产量和N_(2)O排放变化的文献,运用随机森林建模,定量分析氮肥和秸秆还田对小麦产量和N_(2)O排放的影响,并结合情景设置进行了特定地点的小麦产量和N_(2)O排放模拟,同时评估了碳排放强度(CEE)和净生态系统经济效益(NEEB)。结果表明,建立的区域尺度小麦产量与N_(2)O排放对氮秸互作响应的随机森林模型,验证结果R^(2)分别为0.66和0.65,RMSE分别为0.70和1.11。结果表明施氮量和土壤有机质是影响小麦产量和N_(2)O排放的重要因素。综合来看,达到最大产量所需的氮肥量为208~212 kg hm^(-2),达到最小CEE所需的氮肥量为113~130 kg hm^(-2),达到最高的NEEB所需的氮肥量为202~205 kg hm^(-2),其中在6.75 t hm^(-2)的秸秆投入下施用202 kg hm^(-2)的氮肥可以获得最高的生态收益1.37万元。优化氮肥和秸秆投入具备减少作物碳排放强度并获得最大净生态环境效益的潜力。展开更多
The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using...The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide.Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences,especially for the second mode.The first AAM mode,from various seasonal sequences,coincides with the El Niño phase transition in the eastern-central Pacific.The second mode,initialized from boreal summer and autumn,leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring.Our findings hint that ENSO,as an early signal,is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes.Still,the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features.The multimodel ensemble(MME)mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features.The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes.The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.展开更多
An industrial scale propylene production via oxidative dehydrogenation of propane （ODHP） in multi-tubular re- actors was modeled. Multi-tubular fixed-bed reactor used for ODHP process, employing 10000 of small diame...An industrial scale propylene production via oxidative dehydrogenation of propane （ODHP） in multi-tubular re- actors was modeled. Multi-tubular fixed-bed reactor used for ODHP process, employing 10000 of small diameter tubes immersed in a shell through a proper coolant flows. Herein, a theory-based pseudo-homogeneous model to describe the operation of a fixed bed reactor for the ODHP to correspondence olefln over V2O5/γ-Al203 catalyst was presented. Steady state one dimensional model has been developed to identify the operation parameters and to describe the propane and oxygen conversions, gas process and coolant temperatures, as well as other pa- rameters affecting the reactor performance such as pressure. Furthermore, the applied model showed that a double-bed multitubular reactor with intermediate air injection scheme was superior to a single-bed design due to the increasing of propylene selectivity while operating under lower oxygen partial pressures resulting in propane conversion of about 37.3%. The optimized length of the reactor needed to reach 100% conversion of the oxygen was theoretically determined. For the single-bed reactor the optimized length of 11.96 m including 0.5 m of inert section at the entrance region and for the double-bed reactor design the optimized lengths of 5.72 m for the first and 7.32 m for the second reactor were calculated. Ultimately, the use of a distributed oxygen feed with limited number of injection points indicated a significant improvement on the reactor performance in terms of propane conversion and propylene selectivity. Besides, this concept could overcome the reactor run- away temperature problem and enabled operations at the wider range of conditions to obtain enhanced propyl- ene production in an industrial scale reactor.展开更多
In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and ...In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and transformation of several forms of nitrogen in the agro-eeosystem, which is affected by climate, soil, crop growth and management practices. The simulation of daily N2O fluxes, along with key daily environmental variables, was validated with three-year observations conducted in East China. The validation demonstrated that the model simulated well daily solar radiation, soil temperature and moisture, and also captured the dynamics and magnitude of accumulated rice aboveground biomass and mineral nitrogen in the soil. The simulated daily N2O emissions over all three years investigated were generally in good agreement with field observations. Particularly well simulated were the peak N2O emissions induced by fertilizations, rainfall events or mid-season drainages. The model simulation also represented closely the inter-annuM variation in N2O emission. These validations imply that the model has the capability to capture the general characteristics of N2O emission from a typical rice-wheat rotation agro-ecosystem. Sensitivity analyses revealed that the simulated N2O emission is most sensitive to the fertilizer application rate and the soil organic matter content, but it is much less sensitive to variations in soil pH and texture, temperature, precipitation and crop residue incorporation rate under local conditions.展开更多
Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projec...Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.展开更多
基金supported by the National Natural Science Foundation of China(NSFCGrant No.42275061)+3 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)the Laoshan Laboratory(Grant No.LSKJ202202404)the NSFC(Grant No.42030410)the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology.
文摘A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.
文摘优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入下小麦产量和N_(2)O排放变化的文献,运用随机森林建模,定量分析氮肥和秸秆还田对小麦产量和N_(2)O排放的影响,并结合情景设置进行了特定地点的小麦产量和N_(2)O排放模拟,同时评估了碳排放强度(CEE)和净生态系统经济效益(NEEB)。结果表明,建立的区域尺度小麦产量与N_(2)O排放对氮秸互作响应的随机森林模型,验证结果R^(2)分别为0.66和0.65,RMSE分别为0.70和1.11。结果表明施氮量和土壤有机质是影响小麦产量和N_(2)O排放的重要因素。综合来看,达到最大产量所需的氮肥量为208~212 kg hm^(-2),达到最小CEE所需的氮肥量为113~130 kg hm^(-2),达到最高的NEEB所需的氮肥量为202~205 kg hm^(-2),其中在6.75 t hm^(-2)的秸秆投入下施用202 kg hm^(-2)的氮肥可以获得最高的生态收益1.37万元。优化氮肥和秸秆投入具备减少作物碳排放强度并获得最大净生态环境效益的潜力。
基金supported by the National Natural Science Foundation of China(Grant Nos.U2242206,41975094 and 41905062)the National Key Research and Development Program on monitoring,Early Warning and Prevention of Major Natural Disaster(Grant Nos.2017YFC1502302 and 2018YFC1506005)+1 种基金the Basic Research and Operational Special Project of CAMS(Grant No.2021Z007)the Met Office Climate Science for Service Partnership(CSSP)China.
文摘The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide.Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences,especially for the second mode.The first AAM mode,from various seasonal sequences,coincides with the El Niño phase transition in the eastern-central Pacific.The second mode,initialized from boreal summer and autumn,leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring.Our findings hint that ENSO,as an early signal,is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes.Still,the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features.The multimodel ensemble(MME)mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features.The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes.The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.
文摘An industrial scale propylene production via oxidative dehydrogenation of propane （ODHP） in multi-tubular re- actors was modeled. Multi-tubular fixed-bed reactor used for ODHP process, employing 10000 of small diameter tubes immersed in a shell through a proper coolant flows. Herein, a theory-based pseudo-homogeneous model to describe the operation of a fixed bed reactor for the ODHP to correspondence olefln over V2O5/γ-Al203 catalyst was presented. Steady state one dimensional model has been developed to identify the operation parameters and to describe the propane and oxygen conversions, gas process and coolant temperatures, as well as other pa- rameters affecting the reactor performance such as pressure. Furthermore, the applied model showed that a double-bed multitubular reactor with intermediate air injection scheme was superior to a single-bed design due to the increasing of propylene selectivity while operating under lower oxygen partial pressures resulting in propane conversion of about 37.3%. The optimized length of the reactor needed to reach 100% conversion of the oxygen was theoretically determined. For the single-bed reactor the optimized length of 11.96 m including 0.5 m of inert section at the entrance region and for the double-bed reactor design the optimized lengths of 5.72 m for the first and 7.32 m for the second reactor were calculated. Ultimately, the use of a distributed oxygen feed with limited number of injection points indicated a significant improvement on the reactor performance in terms of propane conversion and propylene selectivity. Besides, this concept could overcome the reactor run- away temperature problem and enabled operations at the wider range of conditions to obtain enhanced propyl- ene production in an industrial scale reactor.
基金supported by the Chinese Academy of Sciences (KZCX2-YW-204, KSCX3-SW-440, KZCX1-SW-01)the National Natural Science Foundation of China (40425010, 40331014)+1 种基金the European Union (NitroEurope IP 017841)the Helmholtz Society via the Sino-German Joint Laboratory project ENTRANCE
文摘In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and transformation of several forms of nitrogen in the agro-eeosystem, which is affected by climate, soil, crop growth and management practices. The simulation of daily N2O fluxes, along with key daily environmental variables, was validated with three-year observations conducted in East China. The validation demonstrated that the model simulated well daily solar radiation, soil temperature and moisture, and also captured the dynamics and magnitude of accumulated rice aboveground biomass and mineral nitrogen in the soil. The simulated daily N2O emissions over all three years investigated were generally in good agreement with field observations. Particularly well simulated were the peak N2O emissions induced by fertilizations, rainfall events or mid-season drainages. The model simulation also represented closely the inter-annuM variation in N2O emission. These validations imply that the model has the capability to capture the general characteristics of N2O emission from a typical rice-wheat rotation agro-ecosystem. Sensitivity analyses revealed that the simulated N2O emission is most sensitive to the fertilizer application rate and the soil organic matter content, but it is much less sensitive to variations in soil pH and texture, temperature, precipitation and crop residue incorporation rate under local conditions.
文摘Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.
