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 global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.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
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
Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives ...Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.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
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
The “3·31” severe squall line event in eastern China was notable for its exceptional intensity and persistence,posing significant challenges to forecast accuracy. This study analyzed the maintenance stage of th...The “3·31” severe squall line event in eastern China was notable for its exceptional intensity and persistence,posing significant challenges to forecast accuracy. This study analyzed the maintenance stage of this event using highresolution convection-permitting numerical simulations, with a focus on vorticity budgets of the environmental flow, multiscale synoptic diagnostics, and Rotunno-Klemp-Weisman(RKW) theory. These analyses aimed to elucidate the mechanisms governing the morphological transition, the generation of associated convective gales, and the prolonged maintenance of the squall line event. The results show that the numerical simulation accurately reproduced the development and evolution of the squall line, particularly its location, with surface wind errors remaining within a reasonable range. The development of a mesoscale vortex modulated the dynamic and water vapor fields, providing favorable mesoscale environmental conditions for the organization and maintenance of the squall line. Vorticity budget analysis indicates that the divergence and tilting terms were the primary contributors to vorticity tendency. After the squall line entered Jiangxi Province, it exhibited a sharper leading edge and enhanced upward motion. Dry intrusion from the mid-toupper troposphere led to rapid downward momentum transfer at the meso-γ scale, thereby generating convective gales. In addition, the enhancement of the rear-inflow jet(RIJ) was related to the pressure difference between the interior and exterior of system, which resulted from the phase change of condensate within tilted updrafts. The RIJ was orthogonal to the squall line, causing it to transform from a linear into a bowing shape. Diagnosis based on the RKW theory underscore the important roles in both low-level and deep vertical wind shear in maintenaning the squall line. The ratios of the cold pool propagation velocity to the vertical wind shear were close to 1, which balanced with the ambient horizontal vorticity that allowed the convection to remain upright, thus sustaining the squall line's intensity for an extended period. In summary, the squall line event was sustained by a favorable environment created by the environmental vortex. The dry intrusion from the mid-to-upper troposphere and intensified RIJ resulted in the severe convective winds, while the balance between cold pool and ambient vertical wind shear promoted the system's prolonged maintenance. These findings provide an effective reference for the short-range forecasting of squall lines throughout their lifecycle.展开更多
Plastic pollution and microplastics in sediments are a growing concern for marine ecosystems worldwide.We examined the vertical distribution and properties of microplastics in beach sediments of Xuwen Coral Reef Natio...Plastic pollution and microplastics in sediments are a growing concern for marine ecosystems worldwide.We examined the vertical distribution and properties of microplastics in beach sediments of Xuwen Coral Reef National Nature Reserve,in Leizhou Peninsula,Zhanjiang,China.Sediment samples were taken in seven locations at 5-cm intervals from the surface to a depth of 30 cm.The vertical distribution of microplastic particles ranged from 0 to 1340 particles per kg on average of 119.05particles per kg.The most prevalent material was fibers(76%),followed by film(12%),fragments(11.2%),and foam(0.8%).The microplastics in size of 1-2 mm constituted the largest percentage(40%)of the total,followed by those in size of<1 mm(26.4%),2-3 mm(21.2%),3-4 mm(9.6%),and 4-5 mm(2.81%).Site S1 observed maximum sizes between 1 and 2 mm,S2 reported higher availability of microplastics with sizes ranging from 0.3 to 1 mm.Six different types of polymers were identified in the investigation,and mostly were polyethylene(PE)and polypropylene(PP).In general,the observation of microplastics in deeper sediments indicates that they have the ability to last for prolonged periods in the marine environment,which may present long-term hazards to benthic creatures.In conclusion,the discovery of microplastics in deep layers of coastal sediments highlights the necessity of minimizing plastic waste and enhancing management strategies to safeguard marine environments.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
This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between th...This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.展开更多
Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate extremes.Based on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the ...Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate extremes.Based on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the influence of land–atmosphere coupling on summer extreme hot-humid events(EHHE)over southern Eurasia under different SST backgrounds.The results suggest that coupling causes near-surface air temperature increases that exceed 0.5℃.From 1961 to 2020,the frequency of EHHE has continuously increased,and is closely related to soil moisture anomalies in the northern Indian Peninsula(IDP)and the middle and lower reaches of the Yangtze River(YRB).Numerical simulations further demonstrate that land–atmosphere coupling raises the risk of EHHE by 25.4%.In a typical El Niño SST background state,intensified land–atmosphere coupling tends to produce notable increases in the frequency of EHHE.The dominant processes that land–atmosphere coupling affects the EHHE variations are evidently different between these two regions.Land surface thermal anomalies predominate in the IDP,while moisture conditions are more critical in the YRB.When warm SST anomalies exist,dry soil anomalies in the IDP are prominent,and evaporation is constrained,increasing sensible heat flux.Positive geopotential height anomalies are significant,combined with adiabatic warming induced by descending motion and a noticeable warm center in the near-surface atmosphere.The southward shift of the westerly jet enhances divergence over YRB.The anticyclonic circulation anomalies over the western Pacific are conducive to guiding moisture transport to the YRB,providing a favorable circulation background for the development of summer EHHE.展开更多
Since the mid-20th century,the Mongolian Plateau(MP)has experienced decadal droughts coupled with extreme heatwaves,severely affecting regional ecology and social development.However,the mechanisms behind these decada...Since the mid-20th century,the Mongolian Plateau(MP)has experienced decadal droughts coupled with extreme heatwaves,severely affecting regional ecology and social development.However,the mechanisms behind these decadalscale compound heatwavedrought events remain debated.Here,using reconstructions and simulations from the Community Earth System Model Last Millennium Ensemble,we demonstrate that,over the last millennium,decadal droughts on the MP occurred under both warm and cold conditions,differing from recent compound heatwavedrought events.We found that by examining temperature changes during these drought periods,the distinct influences of external forcings and internal variability can be simply and effectively distinguished.Specifically,colddry events were primarily driven by volcanic eruptions that weakened the East Asian summer monsoon and midlatitude westerlies,reducing moisture transport to the MP.In contrast,warmdry events were predominantly induced by internal variability,notably the negative phase of the Atlantic Multidecadal Oscillation and the expansion of the Barents Sea ice extent.The recent extreme compound event was probably influenced by the combined effects of anthropogenic forcings and internal variability.These findings deepen our understanding of how external forcings and internal variability affect decadal drought events on the MP and highlight that recent compound events are unprecedented in the context of the last millennium.展开更多
The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed wit...The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed with the hydrological and microstructure observations conducted in summer 2012 in the shelf sea east of Hainan Island, in South China Sea(SCS). The deep neural network model is used and incorporates the Richardson number Ri, the normalized depth D, the horizontal velocity speed U, the shear S^(2), the stratification N^(2), and the density ρ as input parameters. Comparing to the scheme without parameter D and region division, the depth-dependent scheme improves the prediction of the turbulent kinetic energy dissipation rate ε. The correlation coefficient(r) between predicted and observed lgε increases from 0.49 to 0.62, and the root mean square error decreases from 0.56 to 0.48. Comparing to the traditional physics-driven parameterization schemes, such as the G89 and MG03, the data-driven approach achieves higher accuracy and generalization. The SHapley Additive Explanations(SHAP) framework analysis reveals the importance descending order of the input parameters as: ρ, D, U, N^(2), S^(2), and Ri in the whole depth, while D is most important in the upper and bottom boundary layers(D≤0.3&D≥0.65) and least important in middle layer(0.3<D<0.65). The research shows applicability of constructing deep learning-based ocean turbulent mixing parameterization schemes using limited observational data and well-established physical processes.展开更多
This study explores the impact of winter sea surface temperature(SST)anomalies in the Southern Indian Ocean on summer precipitation patterns in China,utilizing data from reanalysis sources and Coupled Model Intercompa...This study explores the impact of winter sea surface temperature(SST)anomalies in the Southern Indian Ocean on summer precipitation patterns in China,utilizing data from reanalysis sources and Coupled Model Intercomparison Project Phase 6(CMIP6)models.The results reveal that the Southern Indian Ocean Dipole(SIOD),characterized by contrasting SST anomalies in the northeast and southwest regions,acts as a predictor for Chinese summer precipitation patterns,namely floods in the south and drought in the north.In a positive SIOD event,the southwestern Indian Ocean exhibits warmer SSTs,while the northeastern region remains cooler.A negative SIOD event shows the opposite pattern.During the positive phase of the SIOD,the winter SST distribution strengthens the 850-hPa cross-equatorial airflow,generating a robust low-level westerly jet that enhances water vapor transport to the Bay of Bengal(BoB).These air-sea interactions maintain lower SSTs in the northeastern region,which significantly increase the land-sea temperature contrast in the Northern Hemisphere during spring and summer.This strengthened thermal gradient intensifies the southwest monsoon,establishing a strong convergence zone near the South China Sea and amplifying monsoon-driven precipitation in South China.Additionally,CMIP6 models,such as NorESM2-LM and NorCPM1,which accurately simulate the SIOD pattern,effectively capture the seasonal response of cross-equatorial airflow driven by SST anomalies of Southern Indian Ocean.The result highlights the essential role of cross-equatorial airflow generated by the SIOD in forecasting crossseasonal precipitation patterns.展开更多
Tanzania is mainly subject to a bimodal rainfall pattern,characterized by two distinct seasons:the long rains,occurring from March to May,and the short rains,which typically take place from October to December(OND).Sh...Tanzania is mainly subject to a bimodal rainfall pattern,characterized by two distinct seasons:the long rains,occurring from March to May,and the short rains,which typically take place from October to December(OND).Short rains are usually less intense but still significantly influence local agriculture.Therefore,with station-based observations and reanalysis data,the current paper examines the interannual variability of OND precipitation in Tanzania from 1993 to 2022 and explores the possible impacts from El Niño–Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)as well as the mechanisms.It is found that the Tanzania OND precipitation is above(below)normal in 1997,2006,2011,and 2019(1993,1998,2005,and 2016).The composite difference between wet(dry)years and the climatology indicates that the anomalous lower-level convergence(divergence)and upward(downward)motion are the critical circulation characters for above(below)precipitation.Further analysis indicates ENSO and the IOD are the two main oceanic systems modulating OND precipitation in Tanzania.El Niño and a positive IOD could induce easterly anomalies and weaken the Walker circulation over the Indian Ocean,consequently leading to lower-level convergence in water vapor flux,upward anomalies,and more than normal precipitation in Tanzania.In contrast,La Niña and a negative IOD produce opposite circulation anomalies and less than normal precipitation over Tanzania.Moreover,through partial correlation and Generalized Equilibrium Feedback Analysis,the individual contributions of ENSO and the IOD to circulation are investigated.It is found that although both the IOD and ENSO impact the Walker circulation,the feedback to the IOD is stronger than ENSO.These results provide critical insights into the oceanic drivers and their mechanistic pathways underlying precipitation anomalies in Tanzania.展开更多
In research on the legendary Xia Dynasty of ancient China,the famous archaeological site of Erlitou and its culture are the most debated topics.A key question is whether this ancient culture is truly related to the Xi...In research on the legendary Xia Dynasty of ancient China,the famous archaeological site of Erlitou and its culture are the most debated topics.A key question is whether this ancient culture is truly related to the Xia Dynasty.This study combines traditional literature(Xia Xiao Zheng),archaeological evidence(on alligators),and climate simulation(of autumn rains)to demonstrate that the ancient Chinese phenological calendar,Xia Xiao Zheng,likely originated in the same region as the Erlitou culture.A logical explanation of these findings is that both Xia Xiao Zheng and the Erlitou culture are indeed closely related to the Xia Dynasty.展开更多
Numerical models play an important role in convective-scale forecasting,and dual-polarization radar observations can provide detailed microphysical data.In this study,we implement a direct assimilation operator for du...Numerical models play an important role in convective-scale forecasting,and dual-polarization radar observations can provide detailed microphysical data.In this study,we implement a direct assimilation operator for dual-polarization radar data using the hydrometeor background error covariance(HBEC)in the China Meteorological Administration MESO-scale weather forecasting system(CMA-MESO,formerly GRAPES-MESO)and conducted assimilation and forecasting experiments with X-band and S-band dual-polarization radar data on two cases.The results indicate that the direct assimilation of dual-polarization radar data enhanced the microphysical fields and the thermodynamic structure of convective systems to some extent based on the HBEC,thereby improving precipitation forecasts.Among the sensitivity tests of microphysical parameterization schemes,including the LIUMA scheme,the THOMPSON scheme,and the WSM6scheme(WRF Single-Moment 6-class),we find that the greatest improvement in the equivalent potential temperature,relative humidity,wind,and accumulated precipitation forecasts occurred in the experiment using the WSM6 scheme,as the distribution of solid precipitation particles was closer to the hydrometeor classification algorithm from the dualpolarization radar observations in our cases.展开更多
Clustered heavy precipitation(CHP)events can severely impact human society,infrastructure,and natural ecosystems.Consequently,short-term climate prediction of CHP events is vital for the prevention and mitigation of a...Clustered heavy precipitation(CHP)events can severely impact human society,infrastructure,and natural ecosystems.Consequently,short-term climate prediction of CHP events is vital for the prevention and mitigation of associated hazards.Employing year-to-year increment(DY)and multiple linear regression approaches,this study developed a seasonal prediction model for pre-summer(i.e.,May and June)CHP frequency in South China(SC)during 1981–2022.Three robust predictor factors were identified:March sea surface temperature in Southwestern Atlantic,early-winter snow depth in East Europe,and winter soil moisture in Central Asia.Three predictors exert substantial impacts on presummer precipitation in SC via modulation of an anomalous anticyclone(cyclone)over the(subtropical)western North Pacific.In leave-one-out cross-validation test during 1981–2022,the prediction model exhibited reasonable performance in predicting the interannual and interdecadal variations and trends of CHP days.The temporal correlation coefficient(TCC)was 0.66 between the observations and predictions.In the independent hindcast for 2013–2022,the TCC was as high as 0.85.Moreover,coherent covariations were observed between the frequency and the amounts of CHP,with a TCC of 0.99 for 1981–2022.Those three predictors show good performance in forecasting CHP amounts over SC,with a TCC of 0.68 between the predictions and observations in the cross-validation test during 1981–2022 and of 0.86 in the independent hindcasts during 2013–2022.Notably,the predictors also showed good predictive skill for years with high CHP occurrence(e.g.,1998 and 2019).The predicted high-incidence areas of heavy precipitation days were highly consistent with observations,with a pattern correlation coefficient of 0.44(0.55)for 1998(2019).This study provides valuable insights to improve seasonal prediction of pre-summer CHP frequency in SC.展开更多
This study focuses on an extreme rainfall event in East China during the mei-yu season,in which the capital city(Nanjing)of Jiangsu Province experienced a maximum 14-h rainfall accumulation of 209.6 mm and a peak hour...This study focuses on an extreme rainfall event in East China during the mei-yu season,in which the capital city(Nanjing)of Jiangsu Province experienced a maximum 14-h rainfall accumulation of 209.6 mm and a peak hourly rainfall of 118.8 mm.The performance of two sets of convection-permitting ensemble forecast systems(CEFSs),each with 30 members and a 3-km horizontal grid spacing,is evaluated.The CEFS_ICBCs,using multiple initial and boundary conditions(ICs and BCs),and the CEFS_ICBCs Phys,which incorporates both multi-physics schemes and ICs/BCs,are compared to the CMA-REPS(China Meteorological Administration-Regional Ensemble Prediction System)with a coarser 10-km grid spacing.The two CEFSs demonstrate more uniform rank histograms and lower Brier scores(with higher resolution),improving precipitation intensity predictions and providing more reliable probability forecasts,although they overestimate precipitation over Mt.Dabie.It is challenging for the CEFSs to capture the evolution of mesoscale rainstorms that are known to be related to the errors in predicting the southwesterly low-level winds.Sensitivity experiments reveal that the microphysics and radiation schemes introduce considerable uncertainty in predicting the intensity and location of heavy rainfall in and near Nanjing and Mt.Dabie.In particular,the Asymmetric Convection Model 2(ACM2)planetary boundary layer scheme combined with the Pleim-Xiu surface layer scheme tends to produce a biased northeastward extension of the boundary-layer jet,contributing to the northeastward bias of heavy precipitation around Nanjing in the CEFS_ICBCs.展开更多
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 by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
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supported by the National Natural Science Foundation of China(Grant No.U2342208)support from NSF/Climate Dynamics Award#2025057。
文摘Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.
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 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Jiangxi Meteorological Bureau Project (JXCX202304,JX2024Y01)Geological Disaster Prevention and Control Project of Jiangxi Provincial Department of Natural Resources(B360000030004)+1 种基金Key Research and Development Project of Jiangxi Province (20243BBH81005)Weather Review Project of China Meteorological Administration (FPZJ2025-066)。
文摘The “3·31” severe squall line event in eastern China was notable for its exceptional intensity and persistence,posing significant challenges to forecast accuracy. This study analyzed the maintenance stage of this event using highresolution convection-permitting numerical simulations, with a focus on vorticity budgets of the environmental flow, multiscale synoptic diagnostics, and Rotunno-Klemp-Weisman(RKW) theory. These analyses aimed to elucidate the mechanisms governing the morphological transition, the generation of associated convective gales, and the prolonged maintenance of the squall line event. The results show that the numerical simulation accurately reproduced the development and evolution of the squall line, particularly its location, with surface wind errors remaining within a reasonable range. The development of a mesoscale vortex modulated the dynamic and water vapor fields, providing favorable mesoscale environmental conditions for the organization and maintenance of the squall line. Vorticity budget analysis indicates that the divergence and tilting terms were the primary contributors to vorticity tendency. After the squall line entered Jiangxi Province, it exhibited a sharper leading edge and enhanced upward motion. Dry intrusion from the mid-toupper troposphere led to rapid downward momentum transfer at the meso-γ scale, thereby generating convective gales. In addition, the enhancement of the rear-inflow jet(RIJ) was related to the pressure difference between the interior and exterior of system, which resulted from the phase change of condensate within tilted updrafts. The RIJ was orthogonal to the squall line, causing it to transform from a linear into a bowing shape. Diagnosis based on the RKW theory underscore the important roles in both low-level and deep vertical wind shear in maintenaning the squall line. The ratios of the cold pool propagation velocity to the vertical wind shear were close to 1, which balanced with the ambient horizontal vorticity that allowed the convection to remain upright, thus sustaining the squall line's intensity for an extended period. In summary, the squall line event was sustained by a favorable environment created by the environmental vortex. The dry intrusion from the mid-to-upper troposphere and intensified RIJ resulted in the severe convective winds, while the balance between cold pool and ambient vertical wind shear promoted the system's prolonged maintenance. These findings provide an effective reference for the short-range forecasting of squall lines throughout their lifecycle.
基金Supported by the Southern Marine Science and Engineering Guangdong Laboratory、Zhanjiang(No.ZJW-2019-08)APN、CRRP2019-09MYOnodera、Shinichi Onodera、and the SCS Scholar Grant(No.002029002008/2019)。
文摘Plastic pollution and microplastics in sediments are a growing concern for marine ecosystems worldwide.We examined the vertical distribution and properties of microplastics in beach sediments of Xuwen Coral Reef National Nature Reserve,in Leizhou Peninsula,Zhanjiang,China.Sediment samples were taken in seven locations at 5-cm intervals from the surface to a depth of 30 cm.The vertical distribution of microplastic particles ranged from 0 to 1340 particles per kg on average of 119.05particles per kg.The most prevalent material was fibers(76%),followed by film(12%),fragments(11.2%),and foam(0.8%).The microplastics in size of 1-2 mm constituted the largest percentage(40%)of the total,followed by those in size of<1 mm(26.4%),2-3 mm(21.2%),3-4 mm(9.6%),and 4-5 mm(2.81%).Site S1 observed maximum sizes between 1 and 2 mm,S2 reported higher availability of microplastics with sizes ranging from 0.3 to 1 mm.Six different types of polymers were identified in the investigation,and mostly were polyethylene(PE)and polypropylene(PP).In general,the observation of microplastics in deeper sediments indicates that they have the ability to last for prolonged periods in the marine environment,which may present long-term hazards to benthic creatures.In conclusion,the discovery of microplastics in deep layers of coastal sediments highlights the necessity of minimizing plastic waste and enhancing management strategies to safeguard marine environments.
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National Natural Science Foundation of China(42275030, U2242206, 41730964)Joint Research Project for Meteorological Capacity Improvement (22NLTSZ002)+4 种基金National Key Research and Development Program (2018YFC1506006)China Meteorological Administration Project for Innovation and Development (CXFZ2022J009, CXFZ2022J031)Key Innovation Team of Climate Prediction of China Meteorological Ministration (CMA2023ZD03)Shandong Provincial Natural Science Foundation (ZR2023QD086)UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund。
文摘This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.
基金supported by the National Science Foundation of China(Grant Nos.42088101 and 42275172).
文摘Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate extremes.Based on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the influence of land–atmosphere coupling on summer extreme hot-humid events(EHHE)over southern Eurasia under different SST backgrounds.The results suggest that coupling causes near-surface air temperature increases that exceed 0.5℃.From 1961 to 2020,the frequency of EHHE has continuously increased,and is closely related to soil moisture anomalies in the northern Indian Peninsula(IDP)and the middle and lower reaches of the Yangtze River(YRB).Numerical simulations further demonstrate that land–atmosphere coupling raises the risk of EHHE by 25.4%.In a typical El Niño SST background state,intensified land–atmosphere coupling tends to produce notable increases in the frequency of EHHE.The dominant processes that land–atmosphere coupling affects the EHHE variations are evidently different between these two regions.Land surface thermal anomalies predominate in the IDP,while moisture conditions are more critical in the YRB.When warm SST anomalies exist,dry soil anomalies in the IDP are prominent,and evaporation is constrained,increasing sensible heat flux.Positive geopotential height anomalies are significant,combined with adiabatic warming induced by descending motion and a noticeable warm center in the near-surface atmosphere.The southward shift of the westerly jet enhances divergence over YRB.The anticyclonic circulation anomalies over the western Pacific are conducive to guiding moisture transport to the YRB,providing a favorable circulation background for the development of summer EHHE.
基金supported by the National Natural Science Foundation of China(Grant Nos.42130604)the National Key Research and Development Program of China(Grant No.2023YFF0804704)+2 种基金the National Natural Science Foundation of China(Grant Nos.42105044)Swedish STINT(Grant No.CH2019-8377)the Priority Academic Program Development of Jiangsu Higher Education Institutions(Grant No.164320H116)。
文摘Since the mid-20th century,the Mongolian Plateau(MP)has experienced decadal droughts coupled with extreme heatwaves,severely affecting regional ecology and social development.However,the mechanisms behind these decadalscale compound heatwavedrought events remain debated.Here,using reconstructions and simulations from the Community Earth System Model Last Millennium Ensemble,we demonstrate that,over the last millennium,decadal droughts on the MP occurred under both warm and cold conditions,differing from recent compound heatwavedrought events.We found that by examining temperature changes during these drought periods,the distinct influences of external forcings and internal variability can be simply and effectively distinguished.Specifically,colddry events were primarily driven by volcanic eruptions that weakened the East Asian summer monsoon and midlatitude westerlies,reducing moisture transport to the MP.In contrast,warmdry events were predominantly induced by internal variability,notably the negative phase of the Atlantic Multidecadal Oscillation and the expansion of the Barents Sea ice extent.The recent extreme compound event was probably influenced by the combined effects of anthropogenic forcings and internal variability.These findings deepen our understanding of how external forcings and internal variability affect decadal drought events on the MP and highlight that recent compound events are unprecedented in the context of the last millennium.
基金Supported by the National Natural Science Foundation of China(No.42276019)the Guangdong Provincial Observation and Research Station for Tropical Ocean Environment in Western Coastal Waters(No.GSTOEW)。
文摘The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed with the hydrological and microstructure observations conducted in summer 2012 in the shelf sea east of Hainan Island, in South China Sea(SCS). The deep neural network model is used and incorporates the Richardson number Ri, the normalized depth D, the horizontal velocity speed U, the shear S^(2), the stratification N^(2), and the density ρ as input parameters. Comparing to the scheme without parameter D and region division, the depth-dependent scheme improves the prediction of the turbulent kinetic energy dissipation rate ε. The correlation coefficient(r) between predicted and observed lgε increases from 0.49 to 0.62, and the root mean square error decreases from 0.56 to 0.48. Comparing to the traditional physics-driven parameterization schemes, such as the G89 and MG03, the data-driven approach achieves higher accuracy and generalization. The SHapley Additive Explanations(SHAP) framework analysis reveals the importance descending order of the input parameters as: ρ, D, U, N^(2), S^(2), and Ri in the whole depth, while D is most important in the upper and bottom boundary layers(D≤0.3&D≥0.65) and least important in middle layer(0.3<D<0.65). The research shows applicability of constructing deep learning-based ocean turbulent mixing parameterization schemes using limited observational data and well-established physical processes.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(U2442202)+1 种基金Key Innovation Team of China Meteorological Administration“Climate Change Detection and Response”(CMA2022ZD03)National Key Research and Development Program of China(2023YFF0805104)。
文摘This study explores the impact of winter sea surface temperature(SST)anomalies in the Southern Indian Ocean on summer precipitation patterns in China,utilizing data from reanalysis sources and Coupled Model Intercomparison Project Phase 6(CMIP6)models.The results reveal that the Southern Indian Ocean Dipole(SIOD),characterized by contrasting SST anomalies in the northeast and southwest regions,acts as a predictor for Chinese summer precipitation patterns,namely floods in the south and drought in the north.In a positive SIOD event,the southwestern Indian Ocean exhibits warmer SSTs,while the northeastern region remains cooler.A negative SIOD event shows the opposite pattern.During the positive phase of the SIOD,the winter SST distribution strengthens the 850-hPa cross-equatorial airflow,generating a robust low-level westerly jet that enhances water vapor transport to the Bay of Bengal(BoB).These air-sea interactions maintain lower SSTs in the northeastern region,which significantly increase the land-sea temperature contrast in the Northern Hemisphere during spring and summer.This strengthened thermal gradient intensifies the southwest monsoon,establishing a strong convergence zone near the South China Sea and amplifying monsoon-driven precipitation in South China.Additionally,CMIP6 models,such as NorESM2-LM and NorCPM1,which accurately simulate the SIOD pattern,effectively capture the seasonal response of cross-equatorial airflow driven by SST anomalies of Southern Indian Ocean.The result highlights the essential role of cross-equatorial airflow generated by the SIOD in forecasting crossseasonal precipitation patterns.
基金supported by the National Natural Science Foundation of China[grant numbers 42105030 and 42105066]the Ministry of Commerce,People’s Republic of China.
文摘Tanzania is mainly subject to a bimodal rainfall pattern,characterized by two distinct seasons:the long rains,occurring from March to May,and the short rains,which typically take place from October to December(OND).Short rains are usually less intense but still significantly influence local agriculture.Therefore,with station-based observations and reanalysis data,the current paper examines the interannual variability of OND precipitation in Tanzania from 1993 to 2022 and explores the possible impacts from El Niño–Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)as well as the mechanisms.It is found that the Tanzania OND precipitation is above(below)normal in 1997,2006,2011,and 2019(1993,1998,2005,and 2016).The composite difference between wet(dry)years and the climatology indicates that the anomalous lower-level convergence(divergence)and upward(downward)motion are the critical circulation characters for above(below)precipitation.Further analysis indicates ENSO and the IOD are the two main oceanic systems modulating OND precipitation in Tanzania.El Niño and a positive IOD could induce easterly anomalies and weaken the Walker circulation over the Indian Ocean,consequently leading to lower-level convergence in water vapor flux,upward anomalies,and more than normal precipitation in Tanzania.In contrast,La Niña and a negative IOD produce opposite circulation anomalies and less than normal precipitation over Tanzania.Moreover,through partial correlation and Generalized Equilibrium Feedback Analysis,the individual contributions of ENSO and the IOD to circulation are investigated.It is found that although both the IOD and ENSO impact the Walker circulation,the feedback to the IOD is stronger than ENSO.These results provide critical insights into the oceanic drivers and their mechanistic pathways underlying precipitation anomalies in Tanzania.
基金National Key Research and Development Program of China,No.2023YFF0804704National Natural Science Foundation of China,No.42130604,No.42105044+1 种基金Major Projects of the Ministry of Education's Key Research Bases of Humanities and Social Sciences,No.22JJD770020Social Scienceof Northwest University,No.21XNFH007。
文摘In research on the legendary Xia Dynasty of ancient China,the famous archaeological site of Erlitou and its culture are the most debated topics.A key question is whether this ancient culture is truly related to the Xia Dynasty.This study combines traditional literature(Xia Xiao Zheng),archaeological evidence(on alligators),and climate simulation(of autumn rains)to demonstrate that the ancient Chinese phenological calendar,Xia Xiao Zheng,likely originated in the same region as the Erlitou culture.A logical explanation of these findings is that both Xia Xiao Zheng and the Erlitou culture are indeed closely related to the Xia Dynasty.
基金sponsored by the National Natural Science Foundation of China(U2442601 and U2442218)the High Performance Computing Platform of Nanjing University of Information Science&Technology(NUIST)for their support of this work。
文摘Numerical models play an important role in convective-scale forecasting,and dual-polarization radar observations can provide detailed microphysical data.In this study,we implement a direct assimilation operator for dual-polarization radar data using the hydrometeor background error covariance(HBEC)in the China Meteorological Administration MESO-scale weather forecasting system(CMA-MESO,formerly GRAPES-MESO)and conducted assimilation and forecasting experiments with X-band and S-band dual-polarization radar data on two cases.The results indicate that the direct assimilation of dual-polarization radar data enhanced the microphysical fields and the thermodynamic structure of convective systems to some extent based on the HBEC,thereby improving precipitation forecasts.Among the sensitivity tests of microphysical parameterization schemes,including the LIUMA scheme,the THOMPSON scheme,and the WSM6scheme(WRF Single-Moment 6-class),we find that the greatest improvement in the equivalent potential temperature,relative humidity,wind,and accumulated precipitation forecasts occurred in the experiment using the WSM6 scheme,as the distribution of solid precipitation particles was closer to the hydrometeor classification algorithm from the dualpolarization radar observations in our cases.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)Science and Technology Development Plan in Jilin Province of China(20230203135SF)+1 种基金National Natural Science Foundation of China(41875119)Special Fund for Innovative Development of China Meteorological Administration(CXFZ2022J007)。
文摘Clustered heavy precipitation(CHP)events can severely impact human society,infrastructure,and natural ecosystems.Consequently,short-term climate prediction of CHP events is vital for the prevention and mitigation of associated hazards.Employing year-to-year increment(DY)and multiple linear regression approaches,this study developed a seasonal prediction model for pre-summer(i.e.,May and June)CHP frequency in South China(SC)during 1981–2022.Three robust predictor factors were identified:March sea surface temperature in Southwestern Atlantic,early-winter snow depth in East Europe,and winter soil moisture in Central Asia.Three predictors exert substantial impacts on presummer precipitation in SC via modulation of an anomalous anticyclone(cyclone)over the(subtropical)western North Pacific.In leave-one-out cross-validation test during 1981–2022,the prediction model exhibited reasonable performance in predicting the interannual and interdecadal variations and trends of CHP days.The temporal correlation coefficient(TCC)was 0.66 between the observations and predictions.In the independent hindcast for 2013–2022,the TCC was as high as 0.85.Moreover,coherent covariations were observed between the frequency and the amounts of CHP,with a TCC of 0.99 for 1981–2022.Those three predictors show good performance in forecasting CHP amounts over SC,with a TCC of 0.68 between the predictions and observations in the cross-validation test during 1981–2022 and of 0.86 in the independent hindcasts during 2013–2022.Notably,the predictors also showed good predictive skill for years with high CHP occurrence(e.g.,1998 and 2019).The predicted high-incidence areas of heavy precipitation days were highly consistent with observations,with a pattern correlation coefficient of 0.44(0.55)for 1998(2019).This study provides valuable insights to improve seasonal prediction of pre-summer CHP frequency in SC.
基金supported by the National Natural Science Foundation of China(Grant Nos.42030610 and 42205006)the Startup Foundation for Introducing Talent of NUIST(2023r121)。
文摘This study focuses on an extreme rainfall event in East China during the mei-yu season,in which the capital city(Nanjing)of Jiangsu Province experienced a maximum 14-h rainfall accumulation of 209.6 mm and a peak hourly rainfall of 118.8 mm.The performance of two sets of convection-permitting ensemble forecast systems(CEFSs),each with 30 members and a 3-km horizontal grid spacing,is evaluated.The CEFS_ICBCs,using multiple initial and boundary conditions(ICs and BCs),and the CEFS_ICBCs Phys,which incorporates both multi-physics schemes and ICs/BCs,are compared to the CMA-REPS(China Meteorological Administration-Regional Ensemble Prediction System)with a coarser 10-km grid spacing.The two CEFSs demonstrate more uniform rank histograms and lower Brier scores(with higher resolution),improving precipitation intensity predictions and providing more reliable probability forecasts,although they overestimate precipitation over Mt.Dabie.It is challenging for the CEFSs to capture the evolution of mesoscale rainstorms that are known to be related to the errors in predicting the southwesterly low-level winds.Sensitivity experiments reveal that the microphysics and radiation schemes introduce considerable uncertainty in predicting the intensity and location of heavy rainfall in and near Nanjing and Mt.Dabie.In particular,the Asymmetric Convection Model 2(ACM2)planetary boundary layer scheme combined with the Pleim-Xiu surface layer scheme tends to produce a biased northeastward extension of the boundary-layer jet,contributing to the northeastward bias of heavy precipitation around Nanjing in the CEFS_ICBCs.
