模式分辨率对气候模式的模拟效果具有重要影响。然而,当前模式开发对于垂直分辨率的重视不够。以ENSO(厄尔尼诺-南方涛动)遥相关为例,利用CESM(Community Earth System Model)模式,探究不同模式垂直分辨率设置下模式模拟的ENSO对平流层...模式分辨率对气候模式的模拟效果具有重要影响。然而,当前模式开发对于垂直分辨率的重视不够。以ENSO(厄尔尼诺-南方涛动)遥相关为例,利用CESM(Community Earth System Model)模式,探究不同模式垂直分辨率设置下模式模拟的ENSO对平流层、对流层影响的差异,评估模式垂直分辨率在气候模拟中的重要性。结果表明,提高垂直分辨率可以显著改进模式对ENSO遥相关的模拟能力。以ECMWF(European Centre for Medium-Range Weather Forecasts)第五代再分析数据集(ERA5)为参照,ENSO对纬向平均温度的影响在北半球中高纬地区冬季呈现出“负正负”的三极子模态。CESM默认的垂直分辨率设置(L66)不能模拟出这一模态,而提高模式垂直分辨率(L103)后则可以较好地模拟出这个模态。对于水平分布而言,L66模拟的ENSO在对流层的信号与再分析资料相比明显偏强,L103则可以显著改善。同时,L103对ENSO影响平流层的模拟效果也比L66有所改善。进一步分析发现,L103模拟的行星波从对流层向平流层的传播更强,更接近再分析资料。提高垂直分辨率可以改善模式对大气波活动以及平流层-对流层动力耦合的模拟,重视模式的研发。展开更多
Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic character...Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.展开更多
Seventy-two years of central western United States precipitation data have been analyzed for storms originating 1000 to 3000 km away from four ocean moisture sources: Arctic, North Pacific, South Pacific, and Gulfs of...Seventy-two years of central western United States precipitation data have been analyzed for storms originating 1000 to 3000 km away from four ocean moisture sources: Arctic, North Pacific, South Pacific, and Gulfs of California and Mexico. Precipitation trends were evaluated relative to precipitation phase, precipitation flux, storm track trajectory, and the sea surface temperature (SST) indices Oceanic Niño Index (ONI), and the Pacific Decadal Oscillation (PDO. The lack of correlation between SST indices with precipitation flux was evaluated. The relationships of meteorological, hydrological and snow droughts were evaluated relative to each other, to the climate change-induced temporal shifts in the timing of mountain snowpack decay, and the timing when North Pacific storm tracks shift from crossing to circumventing the Sierra Nevada Range.展开更多
Abscisic acid(ABA),hydrogen peroxide(H_(2)O_(2)) and ascorbate(AsA)–glutathione(GSH)cycle are widely known for their participation in various stresses.However,the relationship between ABA and H_(2)O_(2) levels and th...Abscisic acid(ABA),hydrogen peroxide(H_(2)O_(2)) and ascorbate(AsA)–glutathione(GSH)cycle are widely known for their participation in various stresses.However,the relationship between ABA and H_(2)O_(2) levels and the AsA–GSH cycle under drought stress in wheat has not been studied.In this study,a hydroponic experiment was conducted in wheat seedlings subjected to 15%polyethylene glycol(PEG)6000–induced dehydration.Drought stress caused the rapid accumulation of endogenous ABA and H_(2)O_(2) and significantly decreased the number of root tips compared with the control.The application of ABA significantly increased the number of root tips,whereas the application of H_(2)O_(2) markedly reduced the number of root tips,compared with that under 15%PEG-6000.In addition,drought stress markedly increased the DHA,GSH and GSSG levels,but decreased the AsA levels,AsA/DHA and GSH/GSSG ratios compared with those in the control.The activities of the four enzymes in the AsA–GSH cycle were also markedly increased under drought stress,including glutathione reductase(GR),ascorbate peroxidase(APX),monodehydroascorbate reductase(MDHAR)and dehydroascorbate reductase(DHAR),compared with those in the control.However,the application of an ABA inhibitor significantly inhibited GR,DHAR and APX activities,whereas the application of an H_(2)O_(2) inhibitor significantly inhibited DHAR and MDHAR activities.Furthermore,the application of ABA inhibitor significantly promoted the increases of H_(2)O_(2) and the application of H_(2)O_(2) inhibitor significantly blocked the increases of ABA,compared with those under 15% PEG-6000.Taken together,the results indicated that ABA and H_(2)O_(2) probably interact under drought stress in wheat;and both of them can mediate drought stress by modulating the enzymes in AsA–GSH cycle,where ABA acts as the main regulator of GR,DHAR,and APX activities,and H_(2)O_(2) acts as the main regulator of DHAR and MDHAR activities.展开更多
The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown th...The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.展开更多
文摘模式分辨率对气候模式的模拟效果具有重要影响。然而,当前模式开发对于垂直分辨率的重视不够。以ENSO(厄尔尼诺-南方涛动)遥相关为例,利用CESM(Community Earth System Model)模式,探究不同模式垂直分辨率设置下模式模拟的ENSO对平流层、对流层影响的差异,评估模式垂直分辨率在气候模拟中的重要性。结果表明,提高垂直分辨率可以显著改进模式对ENSO遥相关的模拟能力。以ECMWF(European Centre for Medium-Range Weather Forecasts)第五代再分析数据集(ERA5)为参照,ENSO对纬向平均温度的影响在北半球中高纬地区冬季呈现出“负正负”的三极子模态。CESM默认的垂直分辨率设置(L66)不能模拟出这一模态,而提高模式垂直分辨率(L103)后则可以较好地模拟出这个模态。对于水平分布而言,L66模拟的ENSO在对流层的信号与再分析资料相比明显偏强,L103则可以显著改善。同时,L103对ENSO影响平流层的模拟效果也比L66有所改善。进一步分析发现,L103模拟的行星波从对流层向平流层的传播更强,更接近再分析资料。提高垂直分辨率可以改善模式对大气波活动以及平流层-对流层动力耦合的模拟,重视模式的研发。
基金The authors gratefully acknowledge the financial support of National NaturalScience Foundation of China(Grant No.41972276)Natural Science Foundation of Fujian Province,China(Grant No.2020J06013)"Foal Eagle Program"Youth Top-notch Talent Project of Fujian Province,China(Grant No.00387088).
文摘Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.
文摘Seventy-two years of central western United States precipitation data have been analyzed for storms originating 1000 to 3000 km away from four ocean moisture sources: Arctic, North Pacific, South Pacific, and Gulfs of California and Mexico. Precipitation trends were evaluated relative to precipitation phase, precipitation flux, storm track trajectory, and the sea surface temperature (SST) indices Oceanic Niño Index (ONI), and the Pacific Decadal Oscillation (PDO. The lack of correlation between SST indices with precipitation flux was evaluated. The relationships of meteorological, hydrological and snow droughts were evaluated relative to each other, to the climate change-induced temporal shifts in the timing of mountain snowpack decay, and the timing when North Pacific storm tracks shift from crossing to circumventing the Sierra Nevada Range.
基金This research was funded by the National Key Research and Development Program of China(2023YFD2301505).
文摘Abscisic acid(ABA),hydrogen peroxide(H_(2)O_(2)) and ascorbate(AsA)–glutathione(GSH)cycle are widely known for their participation in various stresses.However,the relationship between ABA and H_(2)O_(2) levels and the AsA–GSH cycle under drought stress in wheat has not been studied.In this study,a hydroponic experiment was conducted in wheat seedlings subjected to 15%polyethylene glycol(PEG)6000–induced dehydration.Drought stress caused the rapid accumulation of endogenous ABA and H_(2)O_(2) and significantly decreased the number of root tips compared with the control.The application of ABA significantly increased the number of root tips,whereas the application of H_(2)O_(2) markedly reduced the number of root tips,compared with that under 15%PEG-6000.In addition,drought stress markedly increased the DHA,GSH and GSSG levels,but decreased the AsA levels,AsA/DHA and GSH/GSSG ratios compared with those in the control.The activities of the four enzymes in the AsA–GSH cycle were also markedly increased under drought stress,including glutathione reductase(GR),ascorbate peroxidase(APX),monodehydroascorbate reductase(MDHAR)and dehydroascorbate reductase(DHAR),compared with those in the control.However,the application of an ABA inhibitor significantly inhibited GR,DHAR and APX activities,whereas the application of an H_(2)O_(2) inhibitor significantly inhibited DHAR and MDHAR activities.Furthermore,the application of ABA inhibitor significantly promoted the increases of H_(2)O_(2) and the application of H_(2)O_(2) inhibitor significantly blocked the increases of ABA,compared with those under 15% PEG-6000.Taken together,the results indicated that ABA and H_(2)O_(2) probably interact under drought stress in wheat;and both of them can mediate drought stress by modulating the enzymes in AsA–GSH cycle,where ABA acts as the main regulator of GR,DHAR,and APX activities,and H_(2)O_(2) acts as the main regulator of DHAR and MDHAR activities.
基金supported by the National Key R&D Program of China(Grant No.2019YFA0606703)the National Natural Science Foundation of China(Grant No.41975116)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.Y202025)。
文摘The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.
