The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO)....The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO).However,there is no consensus yet on its anomalous impacts on the phase and amplitude of ENSO.Based on data during 1982-2022,results show that anomalies of the antisymmetric mode can affect the evolution of ENSO on the interannual scale via Bjerknes feedback,in which the positive(negative)phase of the antisymmetric mode can strengthen El Niño(La Niña)in boreal winter via an earlier(delayed)seasonal cycle transition and larger(smaller)annual mean.The magnitude of the SST anomalies in the equatorial eastern Pacific can reach more than±0.3◦C,regulated by the changes in the antisymmetric mode based on random sensitivity analysis.Results reveal the spatial pattern of the annual cycle associated with the seasonal phase-locking of ENSO evolution and provide new insight into the impact of the annual cycle of background SST on ENSO,which possibly carries important implications for forecasting ENSO.展开更多
The annual maximum rainfall event(AMRE)refers to the maximum consecutive five-day rainfall in a year.In North China,these events account for 15%–80%of the total summer(June–August)rainfall amount and pose a great ch...The annual maximum rainfall event(AMRE)refers to the maximum consecutive five-day rainfall in a year.In North China,these events account for 15%–80%of the total summer(June–August)rainfall amount and pose a great challenge for subseasonal-to-seasonal forecasting.Based on data analyses during 1979–2023,this study shows the interannual variability of AMRE is significantly influenced by the phase and amplitude mode of the annual cycle of the East Asian summer monsoon(EASM),characterized by two orthogonal patterns of southeasterly winds at 850 h Pa over the northwestern Pacific.The EASM phase-locked AMRE shows heavy rainfall events occurring extremely early and late in Beijing and surrounding areas,corresponding to the peak southeasterly wind anomalies in June and August.The EASM amplitude-locked AMRE exhibits extreme heavy or light rainfall over southwest areas with normal phase.Therefore,AMRE has a potential predictability on the seasonal time scale due to its phase-and amplitude-locking with the slow variation of the annual cycle of the EASM.展开更多
Accurately simulating mesoscale convective systems(MCSs)is essential for predicting global precipitation patterns and extreme weather events.Despite the ability of advanced models to reproduce MCS climate statistics,c...Accurately simulating mesoscale convective systems(MCSs)is essential for predicting global precipitation patterns and extreme weather events.Despite the ability of advanced models to reproduce MCS climate statistics,capturing extreme storm cases over complex terrain remains challenging.This study utilizes the Global–Regional Integrated Forecast System(GRIST)with variable resolution to simulate an eastward-propagating MCS event.The impact of three microphysics schemes,including two single-moment schemes(WSM6,Lin)and one double-moment scheme(Morrison),on the model sensitivity of MCS precipitation simulations is investigated.The results demonstrate that while all the schemes capture the spatial distribution and temporal variation of MCS precipitation,the Morrison scheme alleviates overestimated precipitation compared to the Lin and WSM6 schemes.The ascending motion gradually becomes weaker in the Morrison scheme during the MCS movement process.Compared to the runs with convection parameterization,the explicit-convection setup at 3.5-km resolution reduces disparities in atmospheric dynamics due to microphysics sensitivity in terms of vertical motions and horizontal kinetic energy at the high-wavenumber regimes.The explicit-convection setup more accurately captures the propagation of both main and secondary precipitation centers during the MCS development,diminishing the differences in both precipitation intensity and propagation features between the Morrison and two single-moment schemes.These findings underscore the importance of microphysics schemes for global nonhydrostatic modeling at the kilometer scale.The role of explicit convection for reducing model uncertainty is also outlined.展开更多
Measurements from a hyperspectral infrared(HIR) sounder onboard a satellite in geostationary orbit not only provide atmospheric thermodynamic information,but also can be used to infer dynamic information with high tem...Measurements from a hyperspectral infrared(HIR) sounder onboard a satellite in geostationary orbit not only provide atmospheric thermodynamic information,but also can be used to infer dynamic information with high temporal resolution.Radiance measurements from the Geostationary Interferometric Infrared Sounder(GIIRS),obtained with 15-min temporal resolution during Typhoon Maria(2018) and 30-min temporal resolution during Typhoon Lekima(2019),were used to derive three-dimensional(3D) horizontal winds by tracking the motion of atmospheric moisture.This work focused on the impact of assimilation of 3D winds on typhoon analyses and forecasts using the operational NWP model of the China Meteorological Administration(CMA-MESO),and improved understanding of the potential benefits of assimilating dynamic information from geostationary sounder data with higher temporal resolution.The standard deviation of the observations minus simulations revealed that the accuracy of the derived 3D winds with 15-min resolution was higher than that of derived winds with 30-min resolution.Experiments showed that the assimilation system can effectively absorb the information of the derived 3D winds,and that dynamic information from clear-sky areas can be transferred to typhoon areas.In typhoon prediction,assimilation of the derived 3D winds had greatest influence on the typhoon track,and less influence on the maximum wind speed.Assimilation of the derived 3D winds reduced the average track error by 17.4% for Typhoon Maria(2018) and by 3.5% for Typhoon Lekima(2019) during their entire 36-h forecasts initiated at different times.Assimilation of GIIRS dynamic information can substantially improve forecasts of heavy precipitation by CMAMESO.Results indicate that the assimilation of dynamic information from high-temporal-resolution geostationary HIR sounder data adds value for improved numerical weather prediction.展开更多
The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzho...The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzhou RDP(19th Hangzhou Asian Games Research Development Project on Convective-scale Ensemble Prediction and Application)testbed,with the LBCs respectively sourced from National Centers for Environmental Prediction(NCEP)Global Forecast System(GFS)forecasts with 33 vertical levels(Exp_GFS),Pangu forecasts with 13 vertical levels(Exp_Pangu),Fuxi forecasts with 13 vertical levels(Exp_Fuxi),and NCEP GFS forecasts with the vertical levels reduced to 13(the same as those of Exp_Pangu and Exp_Fuxi)(Exp_GFSRDV).In general,Exp_Pangu performs comparably to Exp_GFS,while Exp_Fuxi shows slightly inferior performance compared to Exp_Pangu,possibly due to its less accurate large-scale predictions.Therefore,the ability of using data-driven networks to efficiently provide LBCs for convective-scale ensemble forecasts has been demonstrated.Moreover,Exp_GFSRDV has the worst convective-scale forecasts among the four experiments,which indicates the potential improvement of using data-driven networks for LBCs by increasing the vertical levels of the networks.However,the ensemble spread of the four experiments barely increases with lead time.Thus,each experiment has insufficient ensemble spread to present realistic forecast uncertainties,which will be investigated in a future study.展开更多
基金jointly supported by the National Natural Science Foundation of China [grant numbers U2242205 and 41830969]the S&T Development Fund of CAMS [grant number 2023KJ036]the Basic Scientific Research and Operation Foundation of CAMS [grant number 2023Z018]。
文摘The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO).However,there is no consensus yet on its anomalous impacts on the phase and amplitude of ENSO.Based on data during 1982-2022,results show that anomalies of the antisymmetric mode can affect the evolution of ENSO on the interannual scale via Bjerknes feedback,in which the positive(negative)phase of the antisymmetric mode can strengthen El Niño(La Niña)in boreal winter via an earlier(delayed)seasonal cycle transition and larger(smaller)annual mean.The magnitude of the SST anomalies in the equatorial eastern Pacific can reach more than±0.3◦C,regulated by the changes in the antisymmetric mode based on random sensitivity analysis.Results reveal the spatial pattern of the annual cycle associated with the seasonal phase-locking of ENSO evolution and provide new insight into the impact of the annual cycle of background SST on ENSO,which possibly carries important implications for forecasting ENSO.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.U2242205 and 42375033)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0105)+1 种基金the Basic Scientific Research and Operation Foundation of CAMS(2023Z018)the S&T Development Fund of CAMS(Grant No.2023KJ036)。
文摘The annual maximum rainfall event(AMRE)refers to the maximum consecutive five-day rainfall in a year.In North China,these events account for 15%–80%of the total summer(June–August)rainfall amount and pose a great challenge for subseasonal-to-seasonal forecasting.Based on data analyses during 1979–2023,this study shows the interannual variability of AMRE is significantly influenced by the phase and amplitude mode of the annual cycle of the East Asian summer monsoon(EASM),characterized by two orthogonal patterns of southeasterly winds at 850 h Pa over the northwestern Pacific.The EASM phase-locked AMRE shows heavy rainfall events occurring extremely early and late in Beijing and surrounding areas,corresponding to the peak southeasterly wind anomalies in June and August.The EASM amplitude-locked AMRE exhibits extreme heavy or light rainfall over southwest areas with normal phase.Therefore,AMRE has a potential predictability on the seasonal time scale due to its phase-and amplitude-locking with the slow variation of the annual cycle of the EASM.
基金supported by the National Natural Science Foundation of China(Grant No.42305169)the Basic Research Fund of CAMS(Grant No.2023Y001)the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(Earth Lab)。
文摘Accurately simulating mesoscale convective systems(MCSs)is essential for predicting global precipitation patterns and extreme weather events.Despite the ability of advanced models to reproduce MCS climate statistics,capturing extreme storm cases over complex terrain remains challenging.This study utilizes the Global–Regional Integrated Forecast System(GRIST)with variable resolution to simulate an eastward-propagating MCS event.The impact of three microphysics schemes,including two single-moment schemes(WSM6,Lin)and one double-moment scheme(Morrison),on the model sensitivity of MCS precipitation simulations is investigated.The results demonstrate that while all the schemes capture the spatial distribution and temporal variation of MCS precipitation,the Morrison scheme alleviates overestimated precipitation compared to the Lin and WSM6 schemes.The ascending motion gradually becomes weaker in the Morrison scheme during the MCS movement process.Compared to the runs with convection parameterization,the explicit-convection setup at 3.5-km resolution reduces disparities in atmospheric dynamics due to microphysics sensitivity in terms of vertical motions and horizontal kinetic energy at the high-wavenumber regimes.The explicit-convection setup more accurately captures the propagation of both main and secondary precipitation centers during the MCS development,diminishing the differences in both precipitation intensity and propagation features between the Morrison and two single-moment schemes.These findings underscore the importance of microphysics schemes for global nonhydrostatic modeling at the kilometer scale.The role of explicit convection for reducing model uncertainty is also outlined.
基金supported by the National Natural Science Foundation of China(Grant No.U2142201)the Fengyun Application Pion eering Project(Grant No.FY-APP-ZX-2022.01)。
文摘Measurements from a hyperspectral infrared(HIR) sounder onboard a satellite in geostationary orbit not only provide atmospheric thermodynamic information,but also can be used to infer dynamic information with high temporal resolution.Radiance measurements from the Geostationary Interferometric Infrared Sounder(GIIRS),obtained with 15-min temporal resolution during Typhoon Maria(2018) and 30-min temporal resolution during Typhoon Lekima(2019),were used to derive three-dimensional(3D) horizontal winds by tracking the motion of atmospheric moisture.This work focused on the impact of assimilation of 3D winds on typhoon analyses and forecasts using the operational NWP model of the China Meteorological Administration(CMA-MESO),and improved understanding of the potential benefits of assimilating dynamic information from geostationary sounder data with higher temporal resolution.The standard deviation of the observations minus simulations revealed that the accuracy of the derived 3D winds with 15-min resolution was higher than that of derived winds with 30-min resolution.Experiments showed that the assimilation system can effectively absorb the information of the derived 3D winds,and that dynamic information from clear-sky areas can be transferred to typhoon areas.In typhoon prediction,assimilation of the derived 3D winds had greatest influence on the typhoon track,and less influence on the maximum wind speed.Assimilation of the derived 3D winds reduced the average track error by 17.4% for Typhoon Maria(2018) and by 3.5% for Typhoon Lekima(2019) during their entire 36-h forecasts initiated at different times.Assimilation of GIIRS dynamic information can substantially improve forecasts of heavy precipitation by CMAMESO.Results indicate that the assimilation of dynamic information from high-temporal-resolution geostationary HIR sounder data adds value for improved numerical weather prediction.
基金supported by the Strategic Research and Consulting Project of the Chinese Academy of Engineering[grant number 2024-XBZD-14]the National Natural Science Foundation of China[grant numbers 42192553 and 41922036]the Fundamental Research Funds for the Central Universities–Cemac“GeoX”Interdisciplinary Program[grant number 020714380207]。
文摘The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzhou RDP(19th Hangzhou Asian Games Research Development Project on Convective-scale Ensemble Prediction and Application)testbed,with the LBCs respectively sourced from National Centers for Environmental Prediction(NCEP)Global Forecast System(GFS)forecasts with 33 vertical levels(Exp_GFS),Pangu forecasts with 13 vertical levels(Exp_Pangu),Fuxi forecasts with 13 vertical levels(Exp_Fuxi),and NCEP GFS forecasts with the vertical levels reduced to 13(the same as those of Exp_Pangu and Exp_Fuxi)(Exp_GFSRDV).In general,Exp_Pangu performs comparably to Exp_GFS,while Exp_Fuxi shows slightly inferior performance compared to Exp_Pangu,possibly due to its less accurate large-scale predictions.Therefore,the ability of using data-driven networks to efficiently provide LBCs for convective-scale ensemble forecasts has been demonstrated.Moreover,Exp_GFSRDV has the worst convective-scale forecasts among the four experiments,which indicates the potential improvement of using data-driven networks for LBCs by increasing the vertical levels of the networks.However,the ensemble spread of the four experiments barely increases with lead time.Thus,each experiment has insufficient ensemble spread to present realistic forecast uncertainties,which will be investigated in a future study.
