As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates th...As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates the models’capability to simulate and predict the Madden-Julian Oscillation(MJO).Three versions of the Beijing Climate Center Climate System Model(BCC-CSM)are used to conduct historical simulations and re-forecast experiments(referred to as EXP1,EXP1-M,and EXP2,respectively).In simulating MJO characteristics,the newly-developed high-resolution BCC-CSM outperforms its predecessors.In terms of MJO prediction,the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M,and further to 24 days in EXP2.Within the first forecast week,the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill.However,during forecast weeks 2–3,EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3.Particularly at initial phases 2–3,EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection,leading to the highest prediction skill of the MJO.Our results reveal that,during the participation of the CMA models in the S2S Project,both the improved model initialization and updated model physics played positive roles in improving MJO prediction.Future efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times.展开更多
An exceptionally prolonged heavy snow event(PHSE)occurred in southern China from 10 January to 3 February 2008,which caused considerable economic losses and many casualties.To what extent any dynamical model can predi...An exceptionally prolonged heavy snow event(PHSE)occurred in southern China from 10 January to 3 February 2008,which caused considerable economic losses and many casualties.To what extent any dynamical model can predict such an extreme event is crucial for disaster prevention and mitigation.Here,we found the three S2S models(ECMWF,CMA1.0 and CMA2.0)can predict the distribution and intensity of precipitation and surface air temperature(SAT)associated with the PHSE at 10-day lead and 10−15-day lead,respectively.The success is attributed to the models’capability in forecasting the evolution of two important low-frequency systems in the tropics and mid-latitudes[the persistent Siberian High and the suppressed phase of the Madden−Julian Oscillation(MJO)],especially in the ECMWF model.However,beyond the 15-day lead,the three models show almost no skill in forecasting this PHSE.The bias in capturing the two critical circulation systems is responsible for the low skill in forecasting the 2008 PHSE beyond the 15-day lead.On one hand,the models cannot reproduce the persistence of the Siberian High,which results in the underestimation of negative SAT anomalies over southern China.On the other hand,the models cannot accurately capture the suppressed convection of the MJO,leading to weak anomalous southerly and moisture transport,and therefore the underestimation of precipitation over southern China.The Singular Value Decomposition(SVD)analyses between the critical circulation systems and SAT/precipitation over southern China shows a robust historical relation,indicating the fidelity of the predictability sources for both regular events and extreme events(e.g.,the 2008 PHSE).展开更多
As an important atmospheric circulation system in the mid-high latitudes of East Asia,the Northeast China cold vortex(NCCV)substantially influences weather and climate in this region.So far,systematic assessment on th...As an important atmospheric circulation system in the mid-high latitudes of East Asia,the Northeast China cold vortex(NCCV)substantially influences weather and climate in this region.So far,systematic assessment on the performance of numerical prediction of the NCCVs has not been carried out.Based on the Beijing Climate Centre(BCC)and the ECMWF model hindcast and forecast data that participated in the Sub-seasonal to Seasonal(S2S)Prediction Project,this study systematically examines the performance of both models in simulating and forecasting the NCCVs at the sub-seasonal timescale.The results demonstrate that the two models can effectively capture the seasonal variations in the intensity,active days,and spatial distribution of NCCVs;however,the duration of NCCVs is shorter and the intensity is weaker in the models than in the observations.Diagnostic analysis shows that the differences in the intensity and location of the East Asian subtropical westerly jet and the wave train pattern from North Atlantic to East Asia may be responsible for the deficient simulation of NCCV events in the S2S models.Nonetheless,in the deterministic forecasts,BCC and ECMWF provide skillful prediction on the anomalous numbers of NCCV days and intensity at a lead time of 4-5(5-6)pentads,and the skill limit of the ensemble mean is 1-2 pentads longer than that of individual members.In the probabilistic forecasts of daily NCCV activities,BCC and ECMWF exhibit a forecasting skill of approximately 7 and 11 days,respectively;both models show seasonal dependency in the simulation performance and forecast skills of NCCV events,with better performance in winter than in summer.The results from this study provide helpful references for further improvement of the S2S prediction of NCCVs.展开更多
This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to se...This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM(ECMWF) is the hindcast initiated two(three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.展开更多
This paper presents a statistical scheme for the seasonal forecasting of North China's surface air temperature (NCSAT) during winter. Firstly, a prediction model for an decrease or increase of winter NCSAT is esta...This paper presents a statistical scheme for the seasonal forecasting of North China's surface air temperature (NCSAT) during winter. Firstly, a prediction model for an decrease or increase of winter NCSAT is established, whose predictors are available for no later than the previous September, as this is the most favorable month for seasonal forecasting up to two months ahead.The predicted NCSAT is then derived as the sum of the predicted increment of NCSAT and the previous NCSAT. The scheme successfully predicts the interannual and the decadal variability of NCSAT. Additionally, the advantages of the prediction scheme are discussed.展开更多
Features of the dominant modes of surface air temperature(SAT)on the intraseasonal timescale over the mid-highlatitude Eurasia(MHE)during boreal summer(June-September)are investigated based on the ERA5 reanalysis data...Features of the dominant modes of surface air temperature(SAT)on the intraseasonal timescale over the mid-highlatitude Eurasia(MHE)during boreal summer(June-September)are investigated based on the ERA5 reanalysis data from 1979 to 2016.The intraseasonal variability(ISV)of SAT over MHE is primarily characterized by an eastward propagation along 60°N,which is found to impact the regional weather in China,including summertime extreme hot and cool events.The forecast skill and potential predictability of the ISV of SAT over MHE are assessed for 5 dynamical models that have participated in the subseasonal-to-seasonal(S2 S)prediction project,by analyzing12 years’(1999-2010)model reforecast/hindcast data.By using the principal component(PC)index of the leading intraseasonal SAT modes as a predictand,we found that the forecast skill for ISV of SAT can reach out to 11-17 days,and the ECMWF model exhibits the best score.All the S2 S models tend to show 1)a relatively higher skill for strong intraseasonal oscillation(ISO)cases,2)a systematic underestimate of the amplitude of the SAT ISV signal,and 3)different skills during different phases of ISO cases.Analysis of potential predictability based on the perfectmodel assumption reveals a 4-6-day skill gap for most models,and the skill gap also varies among different phases of ISO events.The results imply the need for continued development of operational forecasting systems to improve the actual prediction skills for the ISV of SAT over MHE.展开更多
AIM: To identify hepatitis C virus(HCV) core protein epitopes recognized by HLA-A2 restricted cytotoxic T lymphocyte (CTL). METHODS: Utilizing the method of computer prediction followed by a 4h(51)Cr release assay con...AIM: To identify hepatitis C virus(HCV) core protein epitopes recognized by HLA-A2 restricted cytotoxic T lymphocyte (CTL). METHODS: Utilizing the method of computer prediction followed by a 4h(51)Cr release assay confirmation. RESULTS: The results showed that peripheral blood mononuclear cells (PBMC) obtained from two HLA-A2 positive donors who were infected with HCV could lyse autologous target cells labeled with peptide "ALAHGVRAL (core 150-158)". The rates of specific lysis of the cells from the two donors were 37.5% and 15.8%, respectively. Blocking of the CTL response with anti-CD4 mAb caused no significant decrease of the specific lysis. But blocking of CTL response with anti-CD8 mAb could abolish the lysis. CONCLUSION: The peptide (core 150-158) is the candidate epitope recognized by HLAA2 restricted CTL.展开更多
Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)liste...Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)listed the S2S prediction project that was initiated by WMO programs three years ago as one of its key tasks.After five years of research,significant progress has been made on the mechanisms of the East Asian monsoon(EAM)S2S variability,related impact of climate change,as well as the predictability on the S2S timescale of numerical models.The S2S variability of the EAM is closely linked to extreme persistent climate events in China and is an important target for seasonal climate prediction.However,under the influence of global warming and the interactions among climate systems,the S2S variability of the EAM is so complex that its prediction remains a great challenge.This paper reviews the past achievement and summarizes the recent progress in research of the EAM S2S variability and prediction,including characteristics of the main S2S modes of the EAM,their impact on the extreme events in China,effects of external and internal forcing on the S2S variability,as well as uncertainties of climate models in predicting the S2S variability,with a focus on the progress achieved by the S2S research team of the Chinese Academy of Meteorological Sciences.The present bottlenecks,future directions,and critical research recommendations are also analyzed and presented.展开更多
Based on an analysis of the existing models of CO 2 corrosion in literatures and the autoclave simulative experiments, a predictive model of corrosion rate (r corr) in CO 2/H 2S corrosion for oil tubes has been ...Based on an analysis of the existing models of CO 2 corrosion in literatures and the autoclave simulative experiments, a predictive model of corrosion rate (r corr) in CO 2/H 2S corrosion for oil tubes has been established, in which r corr is expressed as a function of pH, temperature (T), pressure of CO 2 (P CO 2) and pressure of H 2S (P H 2S). The model has been verified by experimental data obtained on N80 steel. The improved features of the predictive model include the following aspects: (1) The influence of temperature on the protectiveness of corrosion film is taken into consideration for establishment of predictive model of the r corr in CO 2/H 2S corrosion. The Equations of scale temperature and scale factor are put forward, and they fit the experimental result very well. (2) The linear relationship still exists between ln r corr and ln P CO 2 in CO 2/H 2S corrosion (as same as that in CO 2 corrosion). Therefore, a correction factor as a function of P H 2S has been introduced into the predictive model in CO 2/H 2S corrosion. (3) The model is compatible with the main existing models.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42075161).
文摘As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates the models’capability to simulate and predict the Madden-Julian Oscillation(MJO).Three versions of the Beijing Climate Center Climate System Model(BCC-CSM)are used to conduct historical simulations and re-forecast experiments(referred to as EXP1,EXP1-M,and EXP2,respectively).In simulating MJO characteristics,the newly-developed high-resolution BCC-CSM outperforms its predecessors.In terms of MJO prediction,the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M,and further to 24 days in EXP2.Within the first forecast week,the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill.However,during forecast weeks 2–3,EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3.Particularly at initial phases 2–3,EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection,leading to the highest prediction skill of the MJO.Our results reveal that,during the participation of the CMA models in the S2S Project,both the improved model initialization and updated model physics played positive roles in improving MJO prediction.Future efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times.
基金The authors greatly appreciate the professional and earnest review made by the anonymous reviewers which for sure improved the quality of our manuscript.This work was supported by the National Key R&D Program of China(Grant Nos.2018YFC1505905&2018YFC1505803)the National Natural Science Foundation of China(Grant Nos.42088101,41805048 and 41875069)Tim LI was supported by NSF AGS-1643297 and NOAA Grant NA18OAR4310298.
文摘An exceptionally prolonged heavy snow event(PHSE)occurred in southern China from 10 January to 3 February 2008,which caused considerable economic losses and many casualties.To what extent any dynamical model can predict such an extreme event is crucial for disaster prevention and mitigation.Here,we found the three S2S models(ECMWF,CMA1.0 and CMA2.0)can predict the distribution and intensity of precipitation and surface air temperature(SAT)associated with the PHSE at 10-day lead and 10−15-day lead,respectively.The success is attributed to the models’capability in forecasting the evolution of two important low-frequency systems in the tropics and mid-latitudes[the persistent Siberian High and the suppressed phase of the Madden−Julian Oscillation(MJO)],especially in the ECMWF model.However,beyond the 15-day lead,the three models show almost no skill in forecasting this PHSE.The bias in capturing the two critical circulation systems is responsible for the low skill in forecasting the 2008 PHSE beyond the 15-day lead.On one hand,the models cannot reproduce the persistence of the Siberian High,which results in the underestimation of negative SAT anomalies over southern China.On the other hand,the models cannot accurately capture the suppressed convection of the MJO,leading to weak anomalous southerly and moisture transport,and therefore the underestimation of precipitation over southern China.The Singular Value Decomposition(SVD)analyses between the critical circulation systems and SAT/precipitation over southern China shows a robust historical relation,indicating the fidelity of the predictability sources for both regular events and extreme events(e.g.,the 2008 PHSE).
基金Supported by the Research Project of China Meteorological Administration(CMA)Institute of Atmospheric Environment(2021SYI AEKFMS11)National Key Research and Development Program of China(2021YFA0718000)+3 种基金National Natural Science Foundation of China(42175052 and 42005037)Joint Research Project for Meteorological Capacity Improvement(22NLTSY008)CMA Special Project for Innovative Development(CXFZ2022J008)CMA Youth Innovation Team Fund(CMA2024QN06 and CMA2024QN05).
文摘As an important atmospheric circulation system in the mid-high latitudes of East Asia,the Northeast China cold vortex(NCCV)substantially influences weather and climate in this region.So far,systematic assessment on the performance of numerical prediction of the NCCVs has not been carried out.Based on the Beijing Climate Centre(BCC)and the ECMWF model hindcast and forecast data that participated in the Sub-seasonal to Seasonal(S2S)Prediction Project,this study systematically examines the performance of both models in simulating and forecasting the NCCVs at the sub-seasonal timescale.The results demonstrate that the two models can effectively capture the seasonal variations in the intensity,active days,and spatial distribution of NCCVs;however,the duration of NCCVs is shorter and the intensity is weaker in the models than in the observations.Diagnostic analysis shows that the differences in the intensity and location of the East Asian subtropical westerly jet and the wave train pattern from North Atlantic to East Asia may be responsible for the deficient simulation of NCCV events in the S2S models.Nonetheless,in the deterministic forecasts,BCC and ECMWF provide skillful prediction on the anomalous numbers of NCCV days and intensity at a lead time of 4-5(5-6)pentads,and the skill limit of the ensemble mean is 1-2 pentads longer than that of individual members.In the probabilistic forecasts of daily NCCV activities,BCC and ECMWF exhibit a forecasting skill of approximately 7 and 11 days,respectively;both models show seasonal dependency in the simulation performance and forecast skills of NCCV events,with better performance in winter than in summer.The results from this study provide helpful references for further improvement of the S2S prediction of NCCVs.
基金supported by the National Key R&D Program of China (Grant Nos. 2016YFA0602104 and 2016YFA0602102)the National Natural Science Foundation of China (Grant Nos. 41705024, 41575041, 41705039 and 41705076)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA17010105)the Startup Foundation for Introducing Talent of NUIST (Grant No. 2016r060)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM(ECMWF) is the hindcast initiated two(three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.
基金jointly supported by the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.KZCX2-YW-QN202)the National Basic Research Program of China(Grant Nos.2010CB9503042 and 2009CB421406)strategic technological program of the Chinese Academy of Sciences(Grant No.XDA05090426)
文摘This paper presents a statistical scheme for the seasonal forecasting of North China's surface air temperature (NCSAT) during winter. Firstly, a prediction model for an decrease or increase of winter NCSAT is established, whose predictors are available for no later than the previous September, as this is the most favorable month for seasonal forecasting up to two months ahead.The predicted NCSAT is then derived as the sum of the predicted increment of NCSAT and the previous NCSAT. The scheme successfully predicts the interannual and the decadal variability of NCSAT. Additionally, the advantages of the prediction scheme are discussed.
基金Supported by the National Key Research and Development Program of China(2018YFC1505803 and 2018YFC1505905)Natural Science Foundation of Jiangsu Province(BK20210660 and BK20191404)National Natural Science Foundation of China(42088101)。
文摘Features of the dominant modes of surface air temperature(SAT)on the intraseasonal timescale over the mid-highlatitude Eurasia(MHE)during boreal summer(June-September)are investigated based on the ERA5 reanalysis data from 1979 to 2016.The intraseasonal variability(ISV)of SAT over MHE is primarily characterized by an eastward propagation along 60°N,which is found to impact the regional weather in China,including summertime extreme hot and cool events.The forecast skill and potential predictability of the ISV of SAT over MHE are assessed for 5 dynamical models that have participated in the subseasonal-to-seasonal(S2 S)prediction project,by analyzing12 years’(1999-2010)model reforecast/hindcast data.By using the principal component(PC)index of the leading intraseasonal SAT modes as a predictand,we found that the forecast skill for ISV of SAT can reach out to 11-17 days,and the ECMWF model exhibits the best score.All the S2 S models tend to show 1)a relatively higher skill for strong intraseasonal oscillation(ISO)cases,2)a systematic underestimate of the amplitude of the SAT ISV signal,and 3)different skills during different phases of ISO cases.Analysis of potential predictability based on the perfectmodel assumption reveals a 4-6-day skill gap for most models,and the skill gap also varies among different phases of ISO events.The results imply the need for continued development of operational forecasting systems to improve the actual prediction skills for the ISV of SAT over MHE.
基金the National Nature Science Foundation of China,No.39800121
文摘AIM: To identify hepatitis C virus(HCV) core protein epitopes recognized by HLA-A2 restricted cytotoxic T lymphocyte (CTL). METHODS: Utilizing the method of computer prediction followed by a 4h(51)Cr release assay confirmation. RESULTS: The results showed that peripheral blood mononuclear cells (PBMC) obtained from two HLA-A2 positive donors who were infected with HCV could lyse autologous target cells labeled with peptide "ALAHGVRAL (core 150-158)". The rates of specific lysis of the cells from the two donors were 37.5% and 15.8%, respectively. Blocking of the CTL response with anti-CD4 mAb caused no significant decrease of the specific lysis. But blocking of CTL response with anti-CD8 mAb could abolish the lysis. CONCLUSION: The peptide (core 150-158) is the candidate epitope recognized by HLAA2 restricted CTL.
基金Supported by the National Natural Science Foundation of China(41830969)the Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0105)+2 种基金National Natural Science Foundation of China(42005131)Basic Scientific Research and Operation Fund of the Chinese Academy of Meteorological Sciences(CAMS)(2021Z004)Science and Technology Development Fund of CAMS(2020KJ009 and 2020KJ012)。
文摘Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)listed the S2S prediction project that was initiated by WMO programs three years ago as one of its key tasks.After five years of research,significant progress has been made on the mechanisms of the East Asian monsoon(EAM)S2S variability,related impact of climate change,as well as the predictability on the S2S timescale of numerical models.The S2S variability of the EAM is closely linked to extreme persistent climate events in China and is an important target for seasonal climate prediction.However,under the influence of global warming and the interactions among climate systems,the S2S variability of the EAM is so complex that its prediction remains a great challenge.This paper reviews the past achievement and summarizes the recent progress in research of the EAM S2S variability and prediction,including characteristics of the main S2S modes of the EAM,their impact on the extreme events in China,effects of external and internal forcing on the S2S variability,as well as uncertainties of climate models in predicting the S2S variability,with a focus on the progress achieved by the S2S research team of the Chinese Academy of Meteorological Sciences.The present bottlenecks,future directions,and critical research recommendations are also analyzed and presented.
基金TheResearchProjectofTubularGoodsRe searchCenterofChinaNationalPetroleumCorporation (No .2 3 5 2 4)andtheResearchProjectofHenanUniversityofScienceandTechnology (No .2 0 0 10 1)
文摘Based on an analysis of the existing models of CO 2 corrosion in literatures and the autoclave simulative experiments, a predictive model of corrosion rate (r corr) in CO 2/H 2S corrosion for oil tubes has been established, in which r corr is expressed as a function of pH, temperature (T), pressure of CO 2 (P CO 2) and pressure of H 2S (P H 2S). The model has been verified by experimental data obtained on N80 steel. The improved features of the predictive model include the following aspects: (1) The influence of temperature on the protectiveness of corrosion film is taken into consideration for establishment of predictive model of the r corr in CO 2/H 2S corrosion. The Equations of scale temperature and scale factor are put forward, and they fit the experimental result very well. (2) The linear relationship still exists between ln r corr and ln P CO 2 in CO 2/H 2S corrosion (as same as that in CO 2 corrosion). Therefore, a correction factor as a function of P H 2S has been introduced into the predictive model in CO 2/H 2S corrosion. (3) The model is compatible with the main existing models.
