In this study,we put forward a radiative-convective-transportive energy balance model of a gray atmosphere to examine individual roles of the greenhouse effect of water vapor,vertical convection,and atmospheric polewa...In this study,we put forward a radiative-convective-transportive energy balance model of a gray atmosphere to examine individual roles of the greenhouse effect of water vapor,vertical convection,and atmospheric poleward energy transport as well as their combined effects for a quasi-linear relationship between the outgoing longwave radiation(OLR)and surface temperature(T_(S)).The greenhouse effect of water vapor enhances the meridional gradient of surface temperature,thereby directly contributing to a quasi-linear OLR-T_(S) relationship.The atmospheric poleward energy transport decreases the meridional gradient of surface temperature.As a result of the poleward energy transport,tropical(high-latitude)atmosphere-surface columns emit less(more)OLR than the solar energy input at their respective locations,causing a substantial reduction of the meridional gradient of the OLR.The combined effect of reducing the meridional gradients of both OLR and surface temperature by the poleward energy transport also contributes to the quasi-linear OLR-T_(S) relationship.Vertical convective energy transport reduces the meridional gradient of surface temperature without affecting the meridional gradient of OLR,thereby suppressing part of the reduction to the increasing rate of OLR with surface temperature by the greenhouse effect of water vapor and poleward energy transport.Because of the nature of the energy balance in the climate system,such a quasi-linear relationship is also a good approximation for the relationship between the annual-mean net downward solar energy flux at the top of the atmosphere and surface temperature.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
According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since t...According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.展开更多
Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient...Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.展开更多
CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate ...CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.展开更多
Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Ar...Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).展开更多
To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simu...To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.展开更多
Winter precipitation over eastern China displays remarkable interannual variability,which has been suggested to be closely related to El Niño-Southern Oscillation(ENSO).This study finds that ENSO impacts on easte...Winter precipitation over eastern China displays remarkable interannual variability,which has been suggested to be closely related to El Niño-Southern Oscillation(ENSO).This study finds that ENSO impacts on eastern China precipitation patterns exhibit obvious differences in early(November-December)and late(January-February)winter.In early winter,precipitation anomalies associated with ENSO are characterized by a monopole spatial distribution over eastern China.In contrast,the precipitation anomaly pattern in late winter remarkably changes,manifesting as a dipole spatial distribution.The noteworthy change in precipitation responses from early to late winter can be largely attributed to the seasonally varying Kuroshio anticyclonic anomalies.During the early winter of El Niño years,anticyclonic circulation anomalies appear both over the Philippine Sea and Kuroshio region,enhancing water vapor transport to the entirety of eastern China,thus contributing to more precipitation there.During the late winter of El Niño years,the anticyclone over the Philippine Sea is further strengthened,while the one over the Kuroshio dissipates,which could result in differing water vapor transport between northern and southern parts of eastern China and thus a dipole precipitation distribution.Roughly the opposite anomalies of circulation and precipitation are displayed during La Niña winters.Further analysis suggests that the seasonally-varying Kuroshio anticyclonic anomalies are possibly related to the enhancement of ENSO-related tropical central-eastern Pacific convection from early to late winter.These results have important implications for the seasonal-tointerannual predictability of winter precipitation over eastern China.展开更多
One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined...One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.展开更多
This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a...This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a single peak of precipitation over the SST maximum(mode 1),symmetric double peaks of precipitation straddling the SST maximum(mode 2),and a single peak of precipitation on one side of the SST maximum(mode 3).The three modes are caused by three distinct convective activity center migration traits.Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes.When the SST gradient is large,the virtual effect may be strong enough to overcome the temperature effect,generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center.The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.展开更多
Zhanjiang Bay is a major aquaculture area in China with many types of mariculture products(such as oysters,fish,and shrimp).The culture area and shrimp output in Zhanjiang Bay are ranked first in China.We investigated...Zhanjiang Bay is a major aquaculture area in China with many types of mariculture products(such as oysters,fish,and shrimp).The culture area and shrimp output in Zhanjiang Bay are ranked first in China.We investigated the total organic carbon(TOC),total nitrogen(TN),TOC/TN ratio,and stable isotopes(δ^(13)C and δ^(15)N) of the fish and shrimp feed,fish and shrimp feces,and sedimentary organic matter(SOM) in and around different aquaculture areas of northeastern Zhanjiang B ay to study the impact of aquaculture activities on SOM.The average TOC contents of fish and shrimp feed were 39.20%±0.91% and 39.29%±0.21%,respectively.The average TOC content in the surface sediments of the oyster culture area,the mixed(fish and shrimp) culture area,and the cage fish farm area were 0.66%,0.88%±0.10%,and 0.58%±0.19%,respectively,which may indicate that mixed culture had a greater impact on SOM.The relatively high TOC and TN contents and relatively low TOC/TN ratios,and δ^(15)N values in the upper layer of the core sediment in the mixed culture area could also support the significant influence of mixed culture.The average δ^(13)C and δ^(15)N values of fish and shrimp feed were -20.6‰±2.2‰ and 1.8‰±1.2‰,respectively,which were different from the isotopic values of SOM in the study area.δ^(13)C and δ^(15)N values for SOM in different aquaculture areas were different from those of nearby reference stations,probably reflecting the influence of aquaculture.The δ^(13)C and δ^(15)N values in the oyster culture area(-25.9‰ and6.0‰,respectively) seemed to have reduced δ^(13)C and enriched δ^(15)N relative to those of the reference station(-24.6‰ and 5.8‰,respectively).This may reflect the influence of organic matter on oyster culture.The δ^(15)N value of the station in the mixed culture area(7.1‰±0.4‰) seemed to be relatively enriched in δ^(15)N relative to that of the reference station(6.6‰).Sedimentation and the subsequent degradation of organic matter from mixed cultures may have contributed to this phenomenon.The surface sediment at the cage fish farm area seemed to be affected by fish feces and primary production based on the indication of δ^(13)C and δ^(15)N values.The sediment core at the mixed culture region(NS6) had lower TOC/TN ratios and more positive δ^(13)C and δ^(15)N values than the sediment core at the oyster culture area,suggesting a higher proportionate contribution of marine organic matter in the mixed culture area.In summary,oyster culture,mixed culture,and cage fish culture in northeastern Zhanjiang Bay had a certain degree of impact on SOM,and mixed culture had more significant influences on SOM based on the high TOC contents and the significant vertical variations of TOC/TN ratio and δ^(15)N value in the sediment of this area.This study provides new insights into the impact of aquaculture activities on SOM content.展开更多
This study investigates the evolution of an extreme anomalous anticyclone(AA)event over Northeast Asia,which was one of the dominant circulation systems responsible for the catastrophic extreme precipitation event in ...This study investigates the evolution of an extreme anomalous anticyclone(AA)event over Northeast Asia,which was one of the dominant circulation systems responsible for the catastrophic extreme precipitation event in July 2021 in Henan,and further explores the significant impact of this AA on surface temperatures beneath it.The results indicate that this AA event over Northeast Asia was unprecedented in terms of intensity and duration.The AA was very persistent and extremely strong for 10 consecutive days from 13 to 22 July 2021.This long-lived and unprecedented AA led to the persistence of warmer surface temperatures beyond the temporal span of the pronounced 500-hPa anticyclonic signature as the surface air temperatures over land in Northeast Asia remained extremely warm through 29 July 2021.Moreover,the sea surface temperatures in the Sea of Japan/East Sea were extremely high for 30 consecutive days from 13 July to 11 August 2021,persisting well after the weakening or departure of this AA.These results emphasize the extreme nature of this AA over Northeast Asia in July 2021 and its role in multiple extreme climate events,even over remote regions.Furthermore,possible reasons for this long-lasting AA are explored,and it is suggested to be a byproduct of a teleconnection pattern over extratropical Eurasia during the first half of its life cycle,and of the Pacific-Japan teleconnection pattern during the latter half.展开更多
Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated...Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes(mainly referring to La Niña events).The occurrence of multi-year La Niña(MYLA)events has increased significantly in recent decades,and their impact on Arctic sea ice needs to be further explored.In this study,we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña(OTLA)years.The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years.This is because MYLA events tend to be accompanied by a warm Arctic-cold continent pattern with a barotropic high pressure blocked over the Urals region.Consequently,more frequent northward atmospheric rivers intrude into the BKS,intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice.However,in the early winter of OTLA years,a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere,which obstructs the atmospheric rivers to the south of Iceland.We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes.Considering the rapid climate changes in the past,more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades.展开更多
The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested tha...The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.展开更多
Drought events have become more frequent and intense over East Asia in recent decades,leading to huge socioeconomic impacts.Although the droughts have been studied extensively by cases or for individual regions,their ...Drought events have become more frequent and intense over East Asia in recent decades,leading to huge socioeconomic impacts.Although the droughts have been studied extensively by cases or for individual regions,their leading variability and associated causes remain unclear.Based on the Standardized Precipitation Evapotranspiration Index(SPEI)and ERA5 reanalysis product from 1979 to 2020,this study evealuates the severity of spring droughts in East Asia and investigates their variations and associated drivers.The results indicate that North China and Mongolia have experienced remarkable trends toward dryness during spring in recent decades,while southwestern China has witnessed an opposite trend toward wetness.The first Empirical Orthogonal Function mode of SPEI variability reveals a similar seesawing pattern,with more severe dryness in northwestern China,Mongolia,North China,South Korea,and Japan but increased wetness in Southwestern China and southeast Asia.Further investigation reveals that the anomalously dry(wet)surface in North(Southwestern)China is significantly associated with anomalously high(low)temperature,less(more)precipitation,and reduced(increased)soil moisture during the previous winter and early spring,regulated by an anomalous anticyclone(cyclone)and thus reduced(increased)water vapor convergence.The spring dry-wet pattern in East Asia is also linked to cold sea surface temperature anomalies in the central-eastern Pacific.The findings of this study have important implications for improving the prediction of spring drought events in East Asia.展开更多
基金part supported by grants from the National Natural Science Foundation of China(Grant Nos.42222502 and 42075028)grants from the National Science Foundation(AGS-2032542 and AGS-2202875)。
文摘In this study,we put forward a radiative-convective-transportive energy balance model of a gray atmosphere to examine individual roles of the greenhouse effect of water vapor,vertical convection,and atmospheric poleward energy transport as well as their combined effects for a quasi-linear relationship between the outgoing longwave radiation(OLR)and surface temperature(T_(S)).The greenhouse effect of water vapor enhances the meridional gradient of surface temperature,thereby directly contributing to a quasi-linear OLR-T_(S) relationship.The atmospheric poleward energy transport decreases the meridional gradient of surface temperature.As a result of the poleward energy transport,tropical(high-latitude)atmosphere-surface columns emit less(more)OLR than the solar energy input at their respective locations,causing a substantial reduction of the meridional gradient of the OLR.The combined effect of reducing the meridional gradients of both OLR and surface temperature by the poleward energy transport also contributes to the quasi-linear OLR-T_(S) relationship.Vertical convective energy transport reduces the meridional gradient of surface temperature without affecting the meridional gradient of OLR,thereby suppressing part of the reduction to the increasing rate of OLR with surface temperature by the greenhouse effect of water vapor and poleward energy transport.Because of the nature of the energy balance in the climate system,such a quasi-linear relationship is also a good approximation for the relationship between the annual-mean net downward solar energy flux at the top of the atmosphere and surface temperature.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research[grant number 2020B0301030004]the National Natural Science Foundation of China[grant number 91937302].
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.
基金supported by the National Natural Science Foundation of China[grant numbers 41975048,42030605,and 42175069]the Natural Science Foundation of Jiangsu Province[grant number BK20191404]the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA17010105].
基金support from the National Natural Science Foundation of China (Grant Nos. 41975105 and 42375022)。
文摘According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.
基金supported by the Natural Science Foundation of China(Grant Nos.42088101 and 42205149)Zhongwang WEI was supported by the Natural Science Foundation of China(Grant No.42075158)+1 种基金Wei SHANGGUAN was supported by the Natural Science Foundation of China(Grant No.41975122)Yonggen ZHANG was supported by the National Natural Science Foundation of Tianjin(Grant No.20JCQNJC01660).
文摘Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.
基金supported by the General Project of Top-Design of Multi-Scale Nature-Social ModelsData Support and Decision Support System for NSFC Carbon Neutrality Major Project(42341202)the Basic Scientific Research Fund of the Chinese Academy of Meteorological Sciences(2021Z014)。
文摘CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.
基金supported by the Chinese–Norwegian Collaboration Projects within Climate Systems jointly funded by the National Key Research and Development Program of China (Grant No.2022YFE0106800)the Research Council of Norway funded project,MAPARC (Grant No.328943)+2 种基金the support from the Research Council of Norway funded project,COMBINED (Grant No.328935)the National Natural Science Foundation of China (Grant No.42075030)the Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX23_1314)。
文摘Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).
基金supported by the Chinese-Norwegian Collaboration Projects within Climate Systems jointly funded by the National Key Research and Development Program of China (Grant No.2022YFE0106800)the Research Council of Norway funded project MAPARC (Grant No.328943)+2 种基金the support from the Research Council of Norway funded project BASIC (Grant No.325440)the Horizon 2020 project APPLICATE (Grant No.727862)High-performance computing and storage resources were performed on resources provided by Sigma2 - the National Infrastructure for High-Performance Computing and Data Storage in Norway (through projects NS8121K,NN8121K,NN2345K,NS2345K,NS9560K,NS9252K,and NS9034K)。
文摘To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.
基金supported by the National Key R&D Program of China (2022YFF0801602)the High-Performance Computing Center of Nanjing University of Information Science and Technology for their support of this work
文摘Winter precipitation over eastern China displays remarkable interannual variability,which has been suggested to be closely related to El Niño-Southern Oscillation(ENSO).This study finds that ENSO impacts on eastern China precipitation patterns exhibit obvious differences in early(November-December)and late(January-February)winter.In early winter,precipitation anomalies associated with ENSO are characterized by a monopole spatial distribution over eastern China.In contrast,the precipitation anomaly pattern in late winter remarkably changes,manifesting as a dipole spatial distribution.The noteworthy change in precipitation responses from early to late winter can be largely attributed to the seasonally varying Kuroshio anticyclonic anomalies.During the early winter of El Niño years,anticyclonic circulation anomalies appear both over the Philippine Sea and Kuroshio region,enhancing water vapor transport to the entirety of eastern China,thus contributing to more precipitation there.During the late winter of El Niño years,the anticyclone over the Philippine Sea is further strengthened,while the one over the Kuroshio dissipates,which could result in differing water vapor transport between northern and southern parts of eastern China and thus a dipole precipitation distribution.Roughly the opposite anomalies of circulation and precipitation are displayed during La Niña winters.Further analysis suggests that the seasonally-varying Kuroshio anticyclonic anomalies are possibly related to the enhancement of ENSO-related tropical central-eastern Pacific convection from early to late winter.These results have important implications for the seasonal-tointerannual predictability of winter precipitation over eastern China.
基金supported by the National Natural Science Foundation of China (Grant No. 41888101)。
文摘One of the basic characteristics of Earth's modern climate is that the Northern Hemisphere(NH) is climatologically warmer than the Southern Hemisphere(SH). Here, model performances of this basic state are examined using simulation results from 26 CMIP6 models. Results show that the CMIP6 models underestimate the contrast in interhemispheric surface temperatures on average(0.8 K for CMIP6 mean versus 1.4 K for reanalysis data mean), and that there is a large intermodel spread, ranging from -0.7 K to 2.3 K. A box model energy budget analysis shows that the contrast in interhemispheric shortwave absorption at the top of the atmosphere, the contrast in interhemispheric greenhouse trapping, and the crossequatorial northward ocean heat transport, are all underestimated in the multimodel mean. By examining the intermodel spread, we find intermodel biases can be tracked back to biases in midlatitude shortwave cloud forcing in AGCMs. Models with a weaker interhemispheric temperature contrast underestimate the shortwave cloud reflection in the SH but overestimate the shortwave cloud reflection in the NH, which are respectively due to underestimation of the cloud fraction over the SH extratropical ocean and overestimation of the cloud liquid water content over the NH extratropical continents.Models that underestimate the interhemispheric temperature contrast exhibit larger double ITCZ biases, characterized by excessive precipitation in the SH tropics. Although this intermodel spread does not account for the multimodel ensemble mean biases, it highlights that improving cloud simulation in AGCMs is essential for simulating the climate realistically in coupled models.
基金the National Key R&D Program of China(Grant No.2022YFC3003902)the National Natural Science Foundation of China(Grant No.42075146).
文摘This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a single peak of precipitation over the SST maximum(mode 1),symmetric double peaks of precipitation straddling the SST maximum(mode 2),and a single peak of precipitation on one side of the SST maximum(mode 3).The three modes are caused by three distinct convective activity center migration traits.Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes.When the SST gradient is large,the virtual effect may be strong enough to overcome the temperature effect,generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center.The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.
基金supported by the National Natural Science Foundation of China[grant number 42088101] and the National Natural Science Foundation of China[grant number 42005020].
基金The National Natural Science Foundation of China under contract No.42276047the Guangdong Basic and Applied Basic Research Foundation under contract Nos 2023A1515110473 and 2021A1515110172+1 种基金the Program for Scientific Research Start-up Funds of Guangdong Ocean University under contract No.R17058the National College Student Innovation and Entrepreneurship Training Program Project under contract No.202310566007。
文摘Zhanjiang Bay is a major aquaculture area in China with many types of mariculture products(such as oysters,fish,and shrimp).The culture area and shrimp output in Zhanjiang Bay are ranked first in China.We investigated the total organic carbon(TOC),total nitrogen(TN),TOC/TN ratio,and stable isotopes(δ^(13)C and δ^(15)N) of the fish and shrimp feed,fish and shrimp feces,and sedimentary organic matter(SOM) in and around different aquaculture areas of northeastern Zhanjiang B ay to study the impact of aquaculture activities on SOM.The average TOC contents of fish and shrimp feed were 39.20%±0.91% and 39.29%±0.21%,respectively.The average TOC content in the surface sediments of the oyster culture area,the mixed(fish and shrimp) culture area,and the cage fish farm area were 0.66%,0.88%±0.10%,and 0.58%±0.19%,respectively,which may indicate that mixed culture had a greater impact on SOM.The relatively high TOC and TN contents and relatively low TOC/TN ratios,and δ^(15)N values in the upper layer of the core sediment in the mixed culture area could also support the significant influence of mixed culture.The average δ^(13)C and δ^(15)N values of fish and shrimp feed were -20.6‰±2.2‰ and 1.8‰±1.2‰,respectively,which were different from the isotopic values of SOM in the study area.δ^(13)C and δ^(15)N values for SOM in different aquaculture areas were different from those of nearby reference stations,probably reflecting the influence of aquaculture.The δ^(13)C and δ^(15)N values in the oyster culture area(-25.9‰ and6.0‰,respectively) seemed to have reduced δ^(13)C and enriched δ^(15)N relative to those of the reference station(-24.6‰ and 5.8‰,respectively).This may reflect the influence of organic matter on oyster culture.The δ^(15)N value of the station in the mixed culture area(7.1‰±0.4‰) seemed to be relatively enriched in δ^(15)N relative to that of the reference station(6.6‰).Sedimentation and the subsequent degradation of organic matter from mixed cultures may have contributed to this phenomenon.The surface sediment at the cage fish farm area seemed to be affected by fish feces and primary production based on the indication of δ^(13)C and δ^(15)N values.The sediment core at the mixed culture region(NS6) had lower TOC/TN ratios and more positive δ^(13)C and δ^(15)N values than the sediment core at the oyster culture area,suggesting a higher proportionate contribution of marine organic matter in the mixed culture area.In summary,oyster culture,mixed culture,and cage fish culture in northeastern Zhanjiang Bay had a certain degree of impact on SOM,and mixed culture had more significant influences on SOM based on the high TOC contents and the significant vertical variations of TOC/TN ratio and δ^(15)N value in the sediment of this area.This study provides new insights into the impact of aquaculture activities on SOM content.
基金the National Natural Science Foundation of China(Grant Nos.42005029 and 42130504)the Research Program on Decision Services of China Meteorological Administration(Nos.JCZX2023026 and JCZX2022021).
文摘This study investigates the evolution of an extreme anomalous anticyclone(AA)event over Northeast Asia,which was one of the dominant circulation systems responsible for the catastrophic extreme precipitation event in July 2021 in Henan,and further explores the significant impact of this AA on surface temperatures beneath it.The results indicate that this AA event over Northeast Asia was unprecedented in terms of intensity and duration.The AA was very persistent and extremely strong for 10 consecutive days from 13 to 22 July 2021.This long-lived and unprecedented AA led to the persistence of warmer surface temperatures beyond the temporal span of the pronounced 500-hPa anticyclonic signature as the surface air temperatures over land in Northeast Asia remained extremely warm through 29 July 2021.Moreover,the sea surface temperatures in the Sea of Japan/East Sea were extremely high for 30 consecutive days from 13 July to 11 August 2021,persisting well after the weakening or departure of this AA.These results emphasize the extreme nature of this AA over Northeast Asia in July 2021 and its role in multiple extreme climate events,even over remote regions.Furthermore,possible reasons for this long-lasting AA are explored,and it is suggested to be a byproduct of a teleconnection pattern over extratropical Eurasia during the first half of its life cycle,and of the Pacific-Japan teleconnection pattern during the latter half.
基金supported by the National Key R&D Program of China(Grant No.2022YFE0106300)the National Natural Science Foundation of China(Grant Nos.42105052 and 42106220)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2020B1515020025)the fundamental research funds for the Norges Forskningsråd(Grant No.328886).
文摘Arctic sea ice has undergone a significant decline in the Barents-Kara Sea(BKS)since the late 1990s.Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes(mainly referring to La Niña events).The occurrence of multi-year La Niña(MYLA)events has increased significantly in recent decades,and their impact on Arctic sea ice needs to be further explored.In this study,we investigate the relationship between sea-ice variation and different atmospheric diagnostics during MYLA and other La Niña(OTLA)years.The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years.This is because MYLA events tend to be accompanied by a warm Arctic-cold continent pattern with a barotropic high pressure blocked over the Urals region.Consequently,more frequent northward atmospheric rivers intrude into the BKS,intensifying longwave radiation downward to the underlying surface and melting the BKS sea ice.However,in the early winter of OTLA years,a negative North Atlantic Oscillation presents in the high latitudes of the Northern Hemisphere,which obstructs the atmospheric rivers to the south of Iceland.We infer that such a different response of BKS sea-ice decline to different La Niña events is related to stratospheric processes.Considering the rapid climate changes in the past,more frequent MYLA events may account for the substantial Arctic sea-ice loss in recent decades.
基金supported by the National Key R&D Program of China(Grant No.2022YFF0801603).
文摘The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.
基金National Natural Science Foundation of China(42230603,42275020)Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)+3 种基金Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(2020B1212060025)Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021001)Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,MNR(QNHX2310)Future Earth Early-Career Fellowship of the Future Earth Global Secretariat Hub China。
文摘Drought events have become more frequent and intense over East Asia in recent decades,leading to huge socioeconomic impacts.Although the droughts have been studied extensively by cases or for individual regions,their leading variability and associated causes remain unclear.Based on the Standardized Precipitation Evapotranspiration Index(SPEI)and ERA5 reanalysis product from 1979 to 2020,this study evealuates the severity of spring droughts in East Asia and investigates their variations and associated drivers.The results indicate that North China and Mongolia have experienced remarkable trends toward dryness during spring in recent decades,while southwestern China has witnessed an opposite trend toward wetness.The first Empirical Orthogonal Function mode of SPEI variability reveals a similar seesawing pattern,with more severe dryness in northwestern China,Mongolia,North China,South Korea,and Japan but increased wetness in Southwestern China and southeast Asia.Further investigation reveals that the anomalously dry(wet)surface in North(Southwestern)China is significantly associated with anomalously high(low)temperature,less(more)precipitation,and reduced(increased)soil moisture during the previous winter and early spring,regulated by an anomalous anticyclone(cyclone)and thus reduced(increased)water vapor convergence.The spring dry-wet pattern in East Asia is also linked to cold sea surface temperature anomalies in the central-eastern Pacific.The findings of this study have important implications for improving the prediction of spring drought events in East Asia.