This study investigated the impacts of key parameters in CAM6's deep convection and cloud physics schemes on the simulation of summer-mean precipitation over East Asia through conducting perturbed parameter ensemb...This study investigated the impacts of key parameters in CAM6's deep convection and cloud physics schemes on the simulation of summer-mean precipitation over East Asia through conducting perturbed parameter ensemble(PPE)experiments.Utilizing the experimental platform of CAM6,a suite of 128 PPE simulations spanning 19792014 were generated through simultaneously perturbing 12 selected parameters.Using EOF analysis,this study firstly extracted the first two leading modes of the precipitation simulation biases.The authors further pinpointed the most critical parameters that have the most influential effects on the precipitation simulation biases,through conducting generalized linear model analysis.The first leading mode of precipitation simulation biases is primarily influenced by parameters from the cloud physics scheme,including the linear effects of dcs and eii,and the nonlinear effect of rhminl*dcs.These parameters influence the simulated total precipitation(PrecT)mainly by altering the large-scale precipitation(PrecL).The second leading mode is predominantly governed by the convection scheme parameter dmpdz,reflecting a competition between the changes in convective precipitation(PrecC)and PrecL in response to variations in dmpdz.An increase in dmpdz induces decreased PrecC and increased PrecL in East Asia,and both of the changes collectively shape the ultimate PrecT response to the adjusted dmpdz.Lastly,it is noteworthy that the nonlinear effect due to the interaction among parameters warrants attention when concurrently adjusting multiple parameters,and the precipitation biases from the PPE simulations resemble those identified through EOF analysis on the AMIP simulations,implying our findings may provide potential reference for other AGCMs.展开更多
Previous modeling studies have made significant contributions to understanding the climatic effects of historical land use and land cover change(LULCC).However,the absence of transient land cover simulations may lead ...Previous modeling studies have made significant contributions to understanding the climatic effects of historical land use and land cover change(LULCC).However,the absence of transient land cover simulations may lead to uncertainties or inaccuracies in assessing their impacts.Further investigation of differences between fixed and transient LULCC simulations is needed.Here,we employ the Community Earth System Model(CESM)to analyze contrasting responses of mean and extreme near-surface air temperature to historical land cover change.Our results show that forest cover in Europe generally follows a linear upward trend,while East Asia experiences deforestation processes during the historical period.It is found that temperature changes do not exhibit similar seasonal variation and have regional dependence,with Europe showing more pronounced seasonal variability.It is also demonstrated that using fixed land cover simulations exaggerates the temperature responses,leading to an overestimation of temperatures.In Europe,the overestimation of mean and extreme near-surface air temperature is approximately 0.2℃ and 0.3℃,respectively.However,the overestimation is about 0.1℃ in East Asia.Besides,we further disentangle the local and nonlocal effects in the temperature changes and show that nonlocal atmospheric feedbacks dominate the temperature responses in Europe,while local and nonlocal effects exhibit similar temperature variations in East Asia.Further efforts to explore the nonlocal effects of realistic land cover change could help enhance our understanding of climatic effects of land cover change at midlatitudes.展开更多
To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) po...To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) pollution control strategies.However,currently widely-used methods,such as statistical models and numerical models,exhibit inherent limitations in identifying OPS in a timely and accurate manner.In this study,we developed a novel approach to identify OPS based on eXtreme Gradient Boosting model,Shapley additive explanation(SHAP)al-gorithm,and volatile organic compound(VOC)photochemical decay adjustment,using the meteorology and speciated pollutant monitoring data as the input.By comparing the difference in SHAP values between base sce-nario and precursor reduction scenario for nitrogen oxides(NO_(x))and VOCs,OPS was divided into NO_(x)-limited,VOCs-limited and transition regime.Using the long-lasting O_(3) pollution episode in the autumn of 2022 at the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as an example,we demonstrated large spatiotemporal heterogeneities of OPS over the GBA,which were generally shifted from NO_(x)-limited to VOCs-limited from September to October and more inclined to be VOCs-limited at the central and NO_(x)-limited in the peripheral areas.This study developed an innovative OPS identification method by comparing the difference in SHAP value before and after precursor emission reduction.Our method enables the accurate identification of OPS in the time scale of seconds,thereby providing a state-of-the-art tool for the rapid guidance of spatial-specific O_(3) control strategies.展开更多
High spatiotemporal resolution infrared radiances from FY-4A/AGRI(Advanced Geostationary Radiation Imager)can provide crucial information for rapidly developing severe convective weather.This study established a symme...High spatiotemporal resolution infrared radiances from FY-4A/AGRI(Advanced Geostationary Radiation Imager)can provide crucial information for rapidly developing severe convective weather.This study established a symmetric observation error model that differentiates between land and sea for FY-4A/AGRI all-sky assimilation,developed an all-sky assimilation scheme for FY-4A/AGRI based on hydrometeor control variables,and investigated the impacts of all-sky FY-4A/AGRI water vapor channels at different altitudes and rapid-update assimilation at different frequencies on the assimilation and forecasting of a severe convective weather event.Results show that simultaneous assimilation of two water vapor channels can enhance precipitation forecasts compared to single-channel assimilation,which is mainly attributable to a more accurate analysis of water vapor and hydrometeor information.Experiments with different assimilation frequencies demonstrate that the hourly assimilation frequency,compared to other frequencies,incorporates the high-frequency information from AGRI while reducing the impact of spurious oscillations caused by excessively high-frequency assimilation.This hourly assimilation frequency reduces the incoordination among thermal,dynamical,and water vapor conditions caused by excessively fast or slow assimilation frequencies,thus improving the forecast accuracy compared to other frequencies.展开更多
The commencement of the tropical Asian summer monsoon(TASM)in May is a crucial phase in its seasonal evolution,with critical implications for agriculture and water resources.Based on observational and reanalysis data,...The commencement of the tropical Asian summer monsoon(TASM)in May is a crucial phase in its seasonal evolution,with critical implications for agriculture and water resources.Based on observational and reanalysis data,this study finds that the relationship between El Nino-Southern Oscillation(ENSO)and monsoon commencement experiences a notable interdecadal strengthening after 1976/77.While the response of tropical tropospheric temperature to ENSO remains largely unchanged,ENSO induces a stronger Walker circulation,a more pronounced equatorial Rossby wave,and an intensified extratropical Rossby wave train after 1976/77.These enhanced atmospheric processes,which directly reinforce the ENSO-TASM commencement relationship,are likely driven by interdecadal shifts in the structure and variance of ENSO.Post-1976/77,ENSO displays increased variance and a more coherent structure,with more pronounced sea surface temperature anomalies in the western North Pacific and subtropical North Pacific.Given the limitations of observational data,a 1000-year piControl experiment further confirms the role of ENSO variance changes in strengthening its influence on monsoon commencement.Our findings underscore the critical influence of evolving ENSO characteristics on climate anomalies such as monsoon commencement,offering potential insights for short-term climate prediction.展开更多
Both natural and human-induced disturbances affect the normal functioning and services of mangrove ecosystems.To address the consequences of intense human and climatic disturbances on sedimentation and carbon burial,s...Both natural and human-induced disturbances affect the normal functioning and services of mangrove ecosystems.To address the consequences of intense human and climatic disturbances on sedimentation and carbon burial,sediment cores from the last remaining mangrove Kandelia obovata forest and an adjacent mudflat in the densely populated and typhoon-prone Zhujiang(Pearl)River estuary of China,were analyzed using methods including^(210)Pb dating andδ^(13)C analysis.Results indicate that after damming in the 1950s,during 1960-1980,the natural establishment of K.obovata forests initiated the insitu sedimentation.As these forests matured during 1980-1990,they significantly boosted siltation in the region on mudflat.During 1990-2015,the invasion of Spartina alterniflora and land reclamation for aquaculture caused infiltration of coarse sediments and the impacts of typhoons were recorded within the K.obovata forest,while no clear typhoon record was observed on the mudflat.Since 2015,reforestation efforts with S.apetala that began in 1999 have reversed the effects of earlier deforestation.Over time,mangroves established a rapid autochthonous carbon burial that grew as the forests age,potentially surpassing the influx of allochthonous carbon due to deforestation.The reforestation also immediately improved carbon burial on the mudflat,which stabilized after a decade due to the rapid growth and high biomass of S.apetala.Overall,the K.obovata forest demonstrated a stronger sedimentation and carbon burial capabilities than the mudflat,with a surplus of 35.2 Mg C/hm^(2)in soil organic carbon stock and 1.0 Mg C/(hm^(2)·a)in burial rate.Organic matter dissolved in soil was mainly humus-like components,and mangrove inputs likely increased the degree of humification.This study offered direct evidence regarding the impact of multiple disturbances on local and regional sedimentation and carbon burial,and future management strategies.展开更多
Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiote...Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.展开更多
This study investigates the width of the secondary eyewall(SE)immediately following its formation in tropical cyclones with surface environmental winds aligned and counter-aligned with environmental vertical wind shea...This study investigates the width of the secondary eyewall(SE)immediately following its formation in tropical cyclones with surface environmental winds aligned and counter-aligned with environmental vertical wind shear(VWS),using idealized numerical experiments.Results reveal that the SE develops greater radial extent when surface winds align with VWS compared to counter-aligned conditions.In alignment configurations,shear-enhanced surface winds on the right flank amplify surface enthalpy fluxes,thereby elevating boundary-layer entropy within the downshear outer-core region.Subsequently,more vigorous outer rainbands develop,inducing marked acceleration of tangential winds in the outer core preceding SE formation.The resultant radial expansion of supergradient winds near the boundary-layer top triggers widespread convective activity immediately beyond the inner core.Progressive axisymmetrization of this convective forcing ultimately generates an expansive SE structure.展开更多
Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphys...Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphysical processes such as raindrop evaporation and cloud water accretion in a double-moment six-class cloud microphysics scheme were revised to enhance the simulation of low clouds using the Global-Regional Integrated Forecast System(GRIST)model. The validation of the revised scheme using a single-column version of the GRIST demonstrated a reasonable reduction in liquid water biases. The revised parameterization simulated medium-and low-level cloud fractions that were in better agreement with the observations than the original scheme. Long-term global simulations indicate the mitigation of the originally overestimated low-level cloud fraction and cloud-water mixing ratio in mid-to high-latitude regions,primarily owing to enhanced accretion processes and weakened raindrop evaporation. The reduced low clouds with the revised scheme showed better consistency with satellite observations, particularly at mid-and high-latitudes. Further improvements can be observed in the simulated cloud shortwave radiative forcing and vertical distribution of total cloud cover. Annual precipitation in mid-latitude regions has also improved, particularly over the oceans, with significantly increased large-scale and decreased convective precipitation.展开更多
Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many f...Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many fail to capture the coherent multivariate evolution within the coupled ocean-atmosphere system of the tropical Pacific.To address this three-dimensional(3D)limitation and represent ENSO-related ocean-atmosphere interactions more accurately,a novel this 3D multivariate prediction model was proposed based on a Transformer architecture,which incorporates a spatiotemporal self-attention mechanism.This model,named 3D-Geoformer,offers several advantages,enabling accurate ENSO predictions up to one and a half years in advance.Furthermore,an integrated gradient method was introduced into the model to identify the sources of predictability for sea surface temperature(SST)variability in the eastern equatorial Pacific.Results reveal that the 3D-Geoformer effectively captures ENSO-related precursors during the evolution of ENSO events,particularly the thermocline feedback processes and ocean temperature anomaly pathways on and off the equator.By extending DL-based ENSO predictions from one-dimensional Niño time series to 3D multivariate fields,the 3D-Geoformer represents a significant advancement in ENSO prediction.This study provides details in the model formulation,analysis procedures,sensitivity experiments,and illustrative examples,offering practical guidance for the application of the model in ENSO research.展开更多
Due to the high elevation and cold climate of the Tibetan Plateau,the western region retains extensive snow cover during the summer,which can exhibit rapid variability over the course of just a few days.This study uti...Due to the high elevation and cold climate of the Tibetan Plateau,the western region retains extensive snow cover during the summer,which can exhibit rapid variability over the course of just a few days.This study utilizes numerical experiments to investigate the atmospheric response to extreme Tibetan Plateau snow cover(TPSC)events on a subseasonal timescale during summer.The results indicate that the subseasonal variations in TPSC exert limited impact on nonlocal atmospheric circulation and temperature during this period.Nevertheless,local surface energy and atmospheric temperature exhibit rapid cooling responses to increased snow cover.Specifically,an increase in snow cover over the western Tibetan Plateau leads to a sharp rise in surface albedo,resulting in a reduction in land surface energy and a negative response in the diabatic heating rate from the surface to 350 hPa locally.This negative diabatic heating response subsequently causes a decline in both surface and overlying atmospheric temperatures.The temperature response is confined to the western Tibetan Plateau and extends vertically from the surface to approximately 350 hPa.These extreme TPSC events and their associated atmospheric impacts occur within a two-week timescale.展开更多
Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimila...Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.展开更多
A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study em...A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.展开更多
During the boreal summer,intraseasonal oscillations exhibit significant interannual variations in intensity over two key regions:the central-western equatorial Pacific(5°S-5°N,150°E-150°W)and the s...During the boreal summer,intraseasonal oscillations exhibit significant interannual variations in intensity over two key regions:the central-western equatorial Pacific(5°S-5°N,150°E-150°W)and the subtropical Northwestern Pacific(10°-20°N,130°E-175°W).The former is well-documented and considered to be influenced by the ENSO,while the latter has received comparatively less attention and is likely influenced by the Pacific Meridional Mode(PMM),as suggested by partial correlation analysis results.To elucidate the physical processes responsible for the enhanced(weakened)intraseasonal convection over the subtropical northwestern Pacific during warm(cold)PMM years,the authors employed a moisture budget analysis.The findings reveal that during warm PMM years,there is an increase in summer-mean moisture over the subtropical northwestern Pacific.This increase interacts with intensified vertical motion perturbations in the region,leading to greater vertical moisture advection in the lower troposphere and consequently resulting in convective instability.Such a process is pivotal in amplifying intraseasonal convection anomalies.The observational findings were further verified by model experiments forced by PMM-like sea surface temperature patterns.展开更多
Persistent(5-day or longer)extreme cold events(ECEs)over northeastern China during the boreal winter of 1979–2020 are investigated using daily minimum temperature(Tmin)from the China Meteorological Data Network.The e...Persistent(5-day or longer)extreme cold events(ECEs)over northeastern China during the boreal winter of 1979–2020 are investigated using daily minimum temperature(Tmin)from the China Meteorological Data Network.The extreme cooling area and intensity indices associated with the ECEs exhibit a dominant 10–40-day periodicity,indicating a close link with atmospheric intraseasonal oscillations(ISOs).The ECEs are categorized into W-and N-type.In the former,the low-frequency cooling associated with the ISO first penetrates into the western boundary of the northeastern China domain and later occupies the entire domain at its peak phase.The upper-tropospheric circulation associated with this type is characterized by a northwest–southeast-oriented Rossby wave train,expanding from the Ural Mountains to the western Pacific Ocean.In the latter,the cooling invades the northern boundary first and then penetrates into the entire domain.The upper tropospheric precursory signal associated with this type is a zonally oriented negative geopotential height anomaly,which slowly moves southward.A downward-propagating signal is observed in the stratospheric potential vorticity field prior to the peak cooling,implying a possible stratospheric impact.In addition to the W-and N-types,ECEs can also occur in a localized region near either at the northern or southern boundary of the domain.展开更多
Tropospheric ozone pollution has been worsened over most regions of China,adversely affecting human health and ecosystems.The long-term ozone concentration depends largely upon atmospheric circulations.Here,we conduct...Tropospheric ozone pollution has been worsened over most regions of China,adversely affecting human health and ecosystems.The long-term ozone concentration depends largely upon atmospheric circulations.Here,we conducted meteorological adjustment to quantitatively assess the influences of meteorological factors on the ozone evolution in China's seven city clusters during thewarm season(April to October)from 2013 to 2020.Our analysis indicated that northern and eastern regions experienced ozone increases driven by emission changes.Southern regions,particularly the Pearl River Delta(PRD),exhibited ozone rise primarily due to meteorological conditions despite emission changes.In the Sichuan Basin(SCB)and Central Yangtze River Plain(CYP),where ozone levels decreased,meteorological conditions played a significant role in suppressing the ascent of ozone.Empirical orthogonal functions(EOF)analyses suggested that the spatiotemporal trend ofmeteorologyassociated ozone was strongly correlated with the variation of East Asian Trough(EAT),South Asian High(SAH)and the western Pacific subtropical high(WPSH).The top three EOF patterns explained 33.4%,21.8%,and 16.0%of the total variance inmeteorology-associated ozone.Absolute principal component scores-multiple linear regression(APCS-MLR)analyse quantitatively identified that enhanced EAT and SAH with a northward location of WPSH were favourable to surface ozone formation in central and eastern regions,but unfavourable to ozone formation in edge regions such as SCB.展开更多
The discrepancy in the trends of the global zonal mean(GZM)intensity of the Hadley circulation(HCI)between reanalysis data and model simulations has been a problem for understanding the changes in HCI and the influenc...The discrepancy in the trends of the global zonal mean(GZM)intensity of the Hadley circulation(HCI)between reanalysis data and model simulations has been a problem for understanding the changes in HCI and the influence of external forcings.To understand the reason for this discrepancy,this study investigates the trends of intensity of regional HCI of the Northern Hemisphere over the eastern Pacific(EPA),western Pacific(WPA),Atlantic(ATL),Africa(AFR),the Indian Ocean(IDO),and residual area(RA),based on six reanalysis datasets and 13 CMIP6 models.In reanalysis data,the trends in regional HCI over EPA and ATL(WPA and AFR)contribute to(partially offset)the increasing trend in GZM HCI,while the trends in regional HCI over IDO are different in different reanalysis data.The CMIP6 models skillfully reproduce the trends in regional HCI over EPA,ATL,WPA,and AFR,but simulate notable decreasing trends in regional HCI over IDO,which is a key reason for the opposite trends in GZM HCI between reanalysis data and models.The discrepancy in IDO can be attributed to differences in the simulation of diabatic heating and zonal friction between reanalysis data and models.Optimal fingerprint analysis indicates that anthropogenic(ANT)and non-greenhouse gas(NOGHG)forcings are the dominant drivers of the HCI trends in the EPA and ATL regions.In the WPA(AFR)region,NOGHG(ANT)forcing serves as the primary driver.The findings contribute to improving the representation of regional HCI trends in models and improving the attribution of external forcings.展开更多
In 2021,Cempaka,a tiny tropical cyclone,made landfall in China.As the TC intensified prior to landfall,the tropical cyclone size measured with precipitation decreased significantly.A numerical simulation was conducted...In 2021,Cempaka,a tiny tropical cyclone,made landfall in China.As the TC intensified prior to landfall,the tropical cyclone size measured with precipitation decreased significantly.A numerical simulation was conducted to examine the possible processes modulating the storm size.Azimuthally mean potential vorticity(PV)was found to decrease mainly in the middle to upper troposphere between 50-and 80-km radii.The PV budget results indicate that the advection and generation of mean PV associated with asymmetric processes,rather than the symmetric processes,primarily contributed to the decrease in mean PV.These asymmetric processes leading to a negative PV tendency were likely associated with inactive outer rainbands.In contrast,the tangential winds simultaneously expanded radially outward,possibly related to inner-core diabatic heating.The findings here emphasize the importance of outer rainband activity in tropical cyclone size change.展开更多
基金jointly supported by the National Key Research and Development Program of China [grant number 2022YFF0802004]the Excellent Youth Natural Science Foundation of Jiangsu Province [grant number BK20230061]the Joint Open Project of KLME&CIC-FEMD[grant number KLME202501]。
文摘This study investigated the impacts of key parameters in CAM6's deep convection and cloud physics schemes on the simulation of summer-mean precipitation over East Asia through conducting perturbed parameter ensemble(PPE)experiments.Utilizing the experimental platform of CAM6,a suite of 128 PPE simulations spanning 19792014 were generated through simultaneously perturbing 12 selected parameters.Using EOF analysis,this study firstly extracted the first two leading modes of the precipitation simulation biases.The authors further pinpointed the most critical parameters that have the most influential effects on the precipitation simulation biases,through conducting generalized linear model analysis.The first leading mode of precipitation simulation biases is primarily influenced by parameters from the cloud physics scheme,including the linear effects of dcs and eii,and the nonlinear effect of rhminl*dcs.These parameters influence the simulated total precipitation(PrecT)mainly by altering the large-scale precipitation(PrecL).The second leading mode is predominantly governed by the convection scheme parameter dmpdz,reflecting a competition between the changes in convective precipitation(PrecC)and PrecL in response to variations in dmpdz.An increase in dmpdz induces decreased PrecC and increased PrecL in East Asia,and both of the changes collectively shape the ultimate PrecT response to the adjusted dmpdz.Lastly,it is noteworthy that the nonlinear effect due to the interaction among parameters warrants attention when concurrently adjusting multiple parameters,and the precipitation biases from the PPE simulations resemble those identified through EOF analysis on the AMIP simulations,implying our findings may provide potential reference for other AGCMs.
基金supported by the National Key R&D Program of China(Grant No.2022YFF0801601).
文摘Previous modeling studies have made significant contributions to understanding the climatic effects of historical land use and land cover change(LULCC).However,the absence of transient land cover simulations may lead to uncertainties or inaccuracies in assessing their impacts.Further investigation of differences between fixed and transient LULCC simulations is needed.Here,we employ the Community Earth System Model(CESM)to analyze contrasting responses of mean and extreme near-surface air temperature to historical land cover change.Our results show that forest cover in Europe generally follows a linear upward trend,while East Asia experiences deforestation processes during the historical period.It is found that temperature changes do not exhibit similar seasonal variation and have regional dependence,with Europe showing more pronounced seasonal variability.It is also demonstrated that using fixed land cover simulations exaggerates the temperature responses,leading to an overestimation of temperatures.In Europe,the overestimation of mean and extreme near-surface air temperature is approximately 0.2℃ and 0.3℃,respectively.However,the overestimation is about 0.1℃ in East Asia.Besides,we further disentangle the local and nonlocal effects in the temperature changes and show that nonlocal atmospheric feedbacks dominate the temperature responses in Europe,while local and nonlocal effects exhibit similar temperature variations in East Asia.Further efforts to explore the nonlocal effects of realistic land cover change could help enhance our understanding of climatic effects of land cover change at midlatitudes.
基金supported by the Key-Area Research and Development Program of Guangdong Province(No.2020B1111360003)the National Natural Science Foundation of China(Nos.42465008 and 42105164)+2 种基金Yunnan Science and Technology Department Project(No.202501AT070239)Yunnan Science and Technology Department Youth Project(No.202401AU070202)Xianyang Rapid Response Decision Support Project for Ozone(No.YZ2024-ZB019).
文摘To curb the worsening tropospheric ozone(O_(3))pollution problem in China,a rapid and accurate identification of O_(3)-precursor sensitivity(OPS)is a crucial prerequisite for formulating effective contingency O_(3) pollution control strategies.However,currently widely-used methods,such as statistical models and numerical models,exhibit inherent limitations in identifying OPS in a timely and accurate manner.In this study,we developed a novel approach to identify OPS based on eXtreme Gradient Boosting model,Shapley additive explanation(SHAP)al-gorithm,and volatile organic compound(VOC)photochemical decay adjustment,using the meteorology and speciated pollutant monitoring data as the input.By comparing the difference in SHAP values between base sce-nario and precursor reduction scenario for nitrogen oxides(NO_(x))and VOCs,OPS was divided into NO_(x)-limited,VOCs-limited and transition regime.Using the long-lasting O_(3) pollution episode in the autumn of 2022 at the Guangdong-Hong Kong-Macao Greater Bay Area(GBA)as an example,we demonstrated large spatiotemporal heterogeneities of OPS over the GBA,which were generally shifted from NO_(x)-limited to VOCs-limited from September to October and more inclined to be VOCs-limited at the central and NO_(x)-limited in the peripheral areas.This study developed an innovative OPS identification method by comparing the difference in SHAP value before and after precursor emission reduction.Our method enables the accurate identification of OPS in the time scale of seconds,thereby providing a state-of-the-art tool for the rapid guidance of spatial-specific O_(3) control strategies.
基金supported by the National Key R&D Program of China(Grant No.2022YFC3080500)the National Natural Science Foundation of China(Grant Nos.U2142208,42475158,and 42105149)the High-Performance Computing Center of Nanjing University of Information Science&Technology for supporting this work。
文摘High spatiotemporal resolution infrared radiances from FY-4A/AGRI(Advanced Geostationary Radiation Imager)can provide crucial information for rapidly developing severe convective weather.This study established a symmetric observation error model that differentiates between land and sea for FY-4A/AGRI all-sky assimilation,developed an all-sky assimilation scheme for FY-4A/AGRI based on hydrometeor control variables,and investigated the impacts of all-sky FY-4A/AGRI water vapor channels at different altitudes and rapid-update assimilation at different frequencies on the assimilation and forecasting of a severe convective weather event.Results show that simultaneous assimilation of two water vapor channels can enhance precipitation forecasts compared to single-channel assimilation,which is mainly attributable to a more accurate analysis of water vapor and hydrometeor information.Experiments with different assimilation frequencies demonstrate that the hourly assimilation frequency,compared to other frequencies,incorporates the high-frequency information from AGRI while reducing the impact of spurious oscillations caused by excessively high-frequency assimilation.This hourly assimilation frequency reduces the incoordination among thermal,dynamical,and water vapor conditions caused by excessively fast or slow assimilation frequencies,thus improving the forecast accuracy compared to other frequencies.
基金supported jointly by the Natural Science Foundation of Yunnan Province(Grant No.202501CF070059)the National Natural Science Foundation of China(Grant No.42205021)+5 种基金the Yunnan Provincial Science and Technology Department(Grant Nos.202505AB350001 and202403AP140009)the Yunnan Southwest United Graduate School Science and Technology Special Project(Award No.202302AP370003)the Scientific Research Fund Project of Yunnan Education Department(Grant No.2025Y0111)the Practical Innovation Project of Postgraduate Students in the Academic Degree of Yunnan University(Grant No.KC-24248868)the Practical Innovation Project of Postgraduate Students in the Professional Degree of Yunnan University(Grant No.ZC-24248604)the Youth Science and Technology Fund Project of Gansu Province(Grant No.24JRRA1186)。
文摘The commencement of the tropical Asian summer monsoon(TASM)in May is a crucial phase in its seasonal evolution,with critical implications for agriculture and water resources.Based on observational and reanalysis data,this study finds that the relationship between El Nino-Southern Oscillation(ENSO)and monsoon commencement experiences a notable interdecadal strengthening after 1976/77.While the response of tropical tropospheric temperature to ENSO remains largely unchanged,ENSO induces a stronger Walker circulation,a more pronounced equatorial Rossby wave,and an intensified extratropical Rossby wave train after 1976/77.These enhanced atmospheric processes,which directly reinforce the ENSO-TASM commencement relationship,are likely driven by interdecadal shifts in the structure and variance of ENSO.Post-1976/77,ENSO displays increased variance and a more coherent structure,with more pronounced sea surface temperature anomalies in the western North Pacific and subtropical North Pacific.Given the limitations of observational data,a 1000-year piControl experiment further confirms the role of ENSO variance changes in strengthening its influence on monsoon commencement.Our findings underscore the critical influence of evolving ENSO characteristics on climate anomalies such as monsoon commencement,offering potential insights for short-term climate prediction.
基金Supported by the National Natural Science Foundation of China(No.U21A6001)the Guangdong Natural Science Foundation Youth Enhancement Program(No.2024A1515030206)the China Meteorological Administration Climate Change Special Program(No.QBZ202301)。
文摘Both natural and human-induced disturbances affect the normal functioning and services of mangrove ecosystems.To address the consequences of intense human and climatic disturbances on sedimentation and carbon burial,sediment cores from the last remaining mangrove Kandelia obovata forest and an adjacent mudflat in the densely populated and typhoon-prone Zhujiang(Pearl)River estuary of China,were analyzed using methods including^(210)Pb dating andδ^(13)C analysis.Results indicate that after damming in the 1950s,during 1960-1980,the natural establishment of K.obovata forests initiated the insitu sedimentation.As these forests matured during 1980-1990,they significantly boosted siltation in the region on mudflat.During 1990-2015,the invasion of Spartina alterniflora and land reclamation for aquaculture caused infiltration of coarse sediments and the impacts of typhoons were recorded within the K.obovata forest,while no clear typhoon record was observed on the mudflat.Since 2015,reforestation efforts with S.apetala that began in 1999 have reversed the effects of earlier deforestation.Over time,mangroves established a rapid autochthonous carbon burial that grew as the forests age,potentially surpassing the influx of allochthonous carbon due to deforestation.The reforestation also immediately improved carbon burial on the mudflat,which stabilized after a decade due to the rapid growth and high biomass of S.apetala.Overall,the K.obovata forest demonstrated a stronger sedimentation and carbon burial capabilities than the mudflat,with a surplus of 35.2 Mg C/hm^(2)in soil organic carbon stock and 1.0 Mg C/(hm^(2)·a)in burial rate.Organic matter dissolved in soil was mainly humus-like components,and mangrove inputs likely increased the degree of humification.This study offered direct evidence regarding the impact of multiple disturbances on local and regional sedimentation and carbon burial,and future management strategies.
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106800]an Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311024001]+3 种基金a project supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2023SP209]a Research Council of Norway funded project(MAPARC)[grant number 328943]a Nansen Center´s basic institutional funding[grant number 342624]the high-performance computing support from the School of Atmospheric Science at Sun Yat-sen University。
文摘Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.
基金jointly supported by the National Natural Science Foundation of China[grant numbers U2342202,42175005,and 42175016]the Qing Lan Project[grant number R2023Q06]。
文摘This study investigates the width of the secondary eyewall(SE)immediately following its formation in tropical cyclones with surface environmental winds aligned and counter-aligned with environmental vertical wind shear(VWS),using idealized numerical experiments.Results reveal that the SE develops greater radial extent when surface winds align with VWS compared to counter-aligned conditions.In alignment configurations,shear-enhanced surface winds on the right flank amplify surface enthalpy fluxes,thereby elevating boundary-layer entropy within the downshear outer-core region.Subsequently,more vigorous outer rainbands develop,inducing marked acceleration of tangential winds in the outer core preceding SE formation.The resultant radial expansion of supergradient winds near the boundary-layer top triggers widespread convective activity immediately beyond the inner core.Progressive axisymmetrization of this convective forcing ultimately generates an expansive SE structure.
基金National Natural Science Foundation of China(42375153,42105153,42205157)Development of Science and Technology at Chinese Academy of Meteorological Sciences(2023KJ038)。
文摘Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphysical processes such as raindrop evaporation and cloud water accretion in a double-moment six-class cloud microphysics scheme were revised to enhance the simulation of low clouds using the Global-Regional Integrated Forecast System(GRIST)model. The validation of the revised scheme using a single-column version of the GRIST demonstrated a reasonable reduction in liquid water biases. The revised parameterization simulated medium-and low-level cloud fractions that were in better agreement with the observations than the original scheme. Long-term global simulations indicate the mitigation of the originally overestimated low-level cloud fraction and cloud-water mixing ratio in mid-to high-latitude regions,primarily owing to enhanced accretion processes and weakened raindrop evaporation. The reduced low clouds with the revised scheme showed better consistency with satellite observations, particularly at mid-and high-latitudes. Further improvements can be observed in the simulated cloud shortwave radiative forcing and vertical distribution of total cloud cover. Annual precipitation in mid-latitude regions has also improved, particularly over the oceans, with significantly increased large-scale and decreased convective precipitation.
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金Supported by the Laoshan Laboratory(No.LSKJ202202402)the National Natural Science Foundation of China(No.42030410)+2 种基金the Startup Foundation for Introducing Talent of Nanjing University of Information Science&Technology,and Jiangsu Innovation Research Group(No.JSSCTD 202346)supported by the China National Postdoctoral Program for Innovative Talents(No.BX20240169)the China Postdoctoral Science Foundation(No.2141062400101)。
文摘Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many fail to capture the coherent multivariate evolution within the coupled ocean-atmosphere system of the tropical Pacific.To address this three-dimensional(3D)limitation and represent ENSO-related ocean-atmosphere interactions more accurately,a novel this 3D multivariate prediction model was proposed based on a Transformer architecture,which incorporates a spatiotemporal self-attention mechanism.This model,named 3D-Geoformer,offers several advantages,enabling accurate ENSO predictions up to one and a half years in advance.Furthermore,an integrated gradient method was introduced into the model to identify the sources of predictability for sea surface temperature(SST)variability in the eastern equatorial Pacific.Results reveal that the 3D-Geoformer effectively captures ENSO-related precursors during the evolution of ENSO events,particularly the thermocline feedback processes and ocean temperature anomaly pathways on and off the equator.By extending DL-based ENSO predictions from one-dimensional Niño time series to 3D multivariate fields,the 3D-Geoformer represents a significant advancement in ENSO prediction.This study provides details in the model formulation,analysis procedures,sensitivity experiments,and illustrative examples,offering practical guidance for the application of the model in ENSO research.
基金supported by the National Key R&D Program of China[grant number 2022YFF0801603]the Natural Science Foundation of China[grant number 41905074].
文摘Due to the high elevation and cold climate of the Tibetan Plateau,the western region retains extensive snow cover during the summer,which can exhibit rapid variability over the course of just a few days.This study utilizes numerical experiments to investigate the atmospheric response to extreme Tibetan Plateau snow cover(TPSC)events on a subseasonal timescale during summer.The results indicate that the subseasonal variations in TPSC exert limited impact on nonlocal atmospheric circulation and temperature during this period.Nevertheless,local surface energy and atmospheric temperature exhibit rapid cooling responses to increased snow cover.Specifically,an increase in snow cover over the western Tibetan Plateau leads to a sharp rise in surface albedo,resulting in a reduction in land surface energy and a negative response in the diabatic heating rate from the surface to 350 hPa locally.This negative diabatic heating response subsequently causes a decline in both surface and overlying atmospheric temperatures.The temperature response is confined to the western Tibetan Plateau and extends vertically from the surface to approximately 350 hPa.These extreme TPSC events and their associated atmospheric impacts occur within a two-week timescale.
基金sponsored by the National Natural Science Foundation of China[grant number U2442218]。
文摘Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.
基金supported by the National Natural Science Foundation of China [grant number 42030605]the National Key R&D Program of China [grant number 2020YFA0608004]。
文摘A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.
基金supported by the National Natural Science Foundation of China [grant number 42088101]。
文摘During the boreal summer,intraseasonal oscillations exhibit significant interannual variations in intensity over two key regions:the central-western equatorial Pacific(5°S-5°N,150°E-150°W)and the subtropical Northwestern Pacific(10°-20°N,130°E-175°W).The former is well-documented and considered to be influenced by the ENSO,while the latter has received comparatively less attention and is likely influenced by the Pacific Meridional Mode(PMM),as suggested by partial correlation analysis results.To elucidate the physical processes responsible for the enhanced(weakened)intraseasonal convection over the subtropical northwestern Pacific during warm(cold)PMM years,the authors employed a moisture budget analysis.The findings reveal that during warm PMM years,there is an increase in summer-mean moisture over the subtropical northwestern Pacific.This increase interacts with intensified vertical motion perturbations in the region,leading to greater vertical moisture advection in the lower troposphere and consequently resulting in convective instability.Such a process is pivotal in amplifying intraseasonal convection anomalies.The observational findings were further verified by model experiments forced by PMM-like sea surface temperature patterns.
基金supported by the National Natural Science Foundation of China(Grant Nos.42088101 and 42075032).
文摘Persistent(5-day or longer)extreme cold events(ECEs)over northeastern China during the boreal winter of 1979–2020 are investigated using daily minimum temperature(Tmin)from the China Meteorological Data Network.The extreme cooling area and intensity indices associated with the ECEs exhibit a dominant 10–40-day periodicity,indicating a close link with atmospheric intraseasonal oscillations(ISOs).The ECEs are categorized into W-and N-type.In the former,the low-frequency cooling associated with the ISO first penetrates into the western boundary of the northeastern China domain and later occupies the entire domain at its peak phase.The upper-tropospheric circulation associated with this type is characterized by a northwest–southeast-oriented Rossby wave train,expanding from the Ural Mountains to the western Pacific Ocean.In the latter,the cooling invades the northern boundary first and then penetrates into the entire domain.The upper tropospheric precursory signal associated with this type is a zonally oriented negative geopotential height anomaly,which slowly moves southward.A downward-propagating signal is observed in the stratospheric potential vorticity field prior to the peak cooling,implying a possible stratospheric impact.In addition to the W-and N-types,ECEs can also occur in a localized region near either at the northern or southern boundary of the domain.
基金supported by the National Natural Science Foundation of China(No.42377095)the Open Research Fund Program of Plateau Atmosphere and Environment Key Laboratory of Sichuan Province(No.PAEKL-2024-K01)Xianyang Key Research and Development Program(No.L2022ZDYFSF040).
文摘Tropospheric ozone pollution has been worsened over most regions of China,adversely affecting human health and ecosystems.The long-term ozone concentration depends largely upon atmospheric circulations.Here,we conducted meteorological adjustment to quantitatively assess the influences of meteorological factors on the ozone evolution in China's seven city clusters during thewarm season(April to October)from 2013 to 2020.Our analysis indicated that northern and eastern regions experienced ozone increases driven by emission changes.Southern regions,particularly the Pearl River Delta(PRD),exhibited ozone rise primarily due to meteorological conditions despite emission changes.In the Sichuan Basin(SCB)and Central Yangtze River Plain(CYP),where ozone levels decreased,meteorological conditions played a significant role in suppressing the ascent of ozone.Empirical orthogonal functions(EOF)analyses suggested that the spatiotemporal trend ofmeteorologyassociated ozone was strongly correlated with the variation of East Asian Trough(EAT),South Asian High(SAH)and the western Pacific subtropical high(WPSH).The top three EOF patterns explained 33.4%,21.8%,and 16.0%of the total variance inmeteorology-associated ozone.Absolute principal component scores-multiple linear regression(APCS-MLR)analyse quantitatively identified that enhanced EAT and SAH with a northward location of WPSH were favourable to surface ozone formation in central and eastern regions,but unfavourable to ozone formation in edge regions such as SCB.
基金the National Key Research and Development Program of China[grant number 2022YFF0801704].
文摘The discrepancy in the trends of the global zonal mean(GZM)intensity of the Hadley circulation(HCI)between reanalysis data and model simulations has been a problem for understanding the changes in HCI and the influence of external forcings.To understand the reason for this discrepancy,this study investigates the trends of intensity of regional HCI of the Northern Hemisphere over the eastern Pacific(EPA),western Pacific(WPA),Atlantic(ATL),Africa(AFR),the Indian Ocean(IDO),and residual area(RA),based on six reanalysis datasets and 13 CMIP6 models.In reanalysis data,the trends in regional HCI over EPA and ATL(WPA and AFR)contribute to(partially offset)the increasing trend in GZM HCI,while the trends in regional HCI over IDO are different in different reanalysis data.The CMIP6 models skillfully reproduce the trends in regional HCI over EPA,ATL,WPA,and AFR,but simulate notable decreasing trends in regional HCI over IDO,which is a key reason for the opposite trends in GZM HCI between reanalysis data and models.The discrepancy in IDO can be attributed to differences in the simulation of diabatic heating and zonal friction between reanalysis data and models.Optimal fingerprint analysis indicates that anthropogenic(ANT)and non-greenhouse gas(NOGHG)forcings are the dominant drivers of the HCI trends in the EPA and ATL regions.In the WPA(AFR)region,NOGHG(ANT)forcing serves as the primary driver.The findings contribute to improving the representation of regional HCI trends in models and improving the attribution of external forcings.
基金jointly supported by the National Natural Science Foundation of China[grant numbers U2342202 and 42175005]the Qing Lan Project[grant number R2023Q06]。
文摘In 2021,Cempaka,a tiny tropical cyclone,made landfall in China.As the TC intensified prior to landfall,the tropical cyclone size measured with precipitation decreased significantly.A numerical simulation was conducted to examine the possible processes modulating the storm size.Azimuthally mean potential vorticity(PV)was found to decrease mainly in the middle to upper troposphere between 50-and 80-km radii.The PV budget results indicate that the advection and generation of mean PV associated with asymmetric processes,rather than the symmetric processes,primarily contributed to the decrease in mean PV.These asymmetric processes leading to a negative PV tendency were likely associated with inactive outer rainbands.In contrast,the tangential winds simultaneously expanded radially outward,possibly related to inner-core diabatic heating.The findings here emphasize the importance of outer rainband activity in tropical cyclone size change.
