Abstract:With the intensification of climate change,icing disasters on power transmission lines have become increasingly frequent,particularly in mountainous regions where complex topography amplifies micrometeorological variability.Icing poses a significant threat to grid stability and power supply security.Although substantial progress has been made in understanding individual icing events,the physical mechanisms governing the rapid succession of different icing types—such as glaze ice and mixed ice accretion—on the same transmission line remain insufficiently understood.This study analyzes two consecutive icing events that occurred in December 2023 in the mountainous region of southern Anhui Province,China.Using ERA5 reanalysis data,radiosonde soundings,surface weather station observations,and tower-based ice thickness monitoring,we investigate the atmospheric conditions,micrometeorological drivers,and ice evolution patterns associated with each event.Particular attention is given to the roles of temperature structure,vertical motion,solar radiation,and vorticity dynamics in the formation and ablation of ice,as well as to the interactions between synoptic-scale circulation and terrain-induced microclimates.
The first event,dominated by glaze ice,resulted from the southward intrusion of cold air from the Baikal trough interacting with a warm,moist air mass ahead,producing a pronounced temperature inversion.A warm layer at 700 hPa above a sub-zero layer below 800 hPa facilitated the formation of supercooled water droplets that froze on contact with the conductors,reaching a maximum thickness of 14.2 mm and a peak growth rate of 9.1 mm·h^-1.In contrast,the second event was characterized by mixed ice accretion,driven by the eastward displacement of the Mongolian high and the northward extension of the western Pacific subtropical high.This circulation pattern produced a fully sub-zero temperature column and widespread snowfall,allowing both ice crystals and freezing droplets to adhere directly to the conductors,with a maximum thickness of 24.5 mm and a peak growth rate of 17.1 mm·h^-1.The presence or absence of a temperature inversion was identified as the key factor distinguishing the two icing types.Both ablation phases coincided with sharp increases in net solar radiation and the development of a characteristic vorticity structure,with positive vorticity aloft and negative vorticity near the surface,which enhanced atmospheric stability and radiative melting.The second event also involved spontaneous ice shedding due to excessive accumulation,emphasizing the need for timely manual intervention in severe cases.Vertical motion analysis revealed that glaze ice formation was linked to inversion-induced convection,while mixed ice accretion was associated with downdrafts and low-level convergence.
These results demonstrate that small-scale differences in atmospheric structure and terrain can lead to substantial variations in icing behavior.The study provides new insight into the dynamics of multi-type,multi-stage icing events in complex terrain and highlights the limitations of relying solely on standard meteorological indicators for prediction.The findings underscore the importance of combining mesoscale circulation analysis with real-time surface observations and tower-based monitoring to improve early warning systems and optimize de-icing operations.Future research should focus on integrating high-resolution numerical modeling,real-time sensor networks,and intelligent image analysis systems to better capture terrain-induced icing variability,enhance icing-type classification,and support predictive maintenance in critical grid regions.Such advancements will be essential for strengthening grid resilience under a warming climate with more frequent extreme weather events.

Abstract:Rapid global urbanization has led to the widespread replacement of natural surfaces with impervious ones,intensifying heat extremes and increasing associated health risks.Understanding how urban expansion influences thermal environments is essential for improving climate resilience and protecting public health.In this study,the Weather Research and Forecasting (WRF) model was used to investigate the impact of underlying surface changes on the urban thermal environment in Zhengzhou,China,focusing on the expansion of urban built-up areas from 2010 to 2020.Results show that urban development radiated outward from Zhengzhou's five central districts,with expansion predominantly occurring in the northern and eastern regions.Built-up land increased by 8.21%,largely at the expense of agricultural land.The WRF model accurately captured monthly temperature variations during July 2020,including the spatial contrast between warmer urban areas and cooler suburban zones.Model performance was particularly strong for nighttime temperature simulations.Numerical results indicate that the 2 m air temperature increased by 0.14 ℃ due to urban expansion over the decade,with greater warming at night than during the day.Nighttime and early morning temperatures rose by over 0.25 ℃,while daytime temperatures were less affected by land surface changes.Spatially,the most significant warming occurred in newly developed built-up areas,particularly in Jinshui and Guancheng districts,where temperature increases reached 0.50 ℃ and 0.47 ℃,respectively.Furthermore,the urban-rural temperature difference grew by 0.26 ℃—from 1.49 ℃ in 2010 to 1.75 ℃ in 2020—highlighting the intensified urban heat island (UHI) effect.The contribution of urban land expansion to UHI was most pronounced at night,with the maximum temperature increase of 0.52 ℃ occurring at 23:00 BST.
To examine localized thermal impacts more precisely,the Urban Planetary Boundary Layer Model (UPBLM),driven by WRF outputs,was applied to simulate thermal conditions in the rapidly developing Beilonghu area.Sensitivity experiments under different land use planning scenarios revealed that the inclusion of water bodies in urban layouts slightly mitigated local warming,providing a cooling effect of approximately 0.17 ℃ at 12:00 BST.These findings underscore the role of urban expansion in intensifying thermal environments and demonstrate that strategic urban planning can partially alleviate these effects.This study offers valuable insights for the development of climate-resilient and sustainable cities.However,limitations remain:this study does not consider the effects of variations in building morphology on urban heat dynamics,and further researcher is needed to elucidate the underlying mechanisms by which changes in urban surface characteristics influence thermal environments.

Abstract:Clouds play a crucial role in modulating the earth-atmosphere energy budget through their radiative cooling and heating effects.They are among the most significant yet uncertain components in climate projections due to their diverse types and complex cloud-radiation interactions.The surface shortwave cloud radiative effect (F_CRE),defined as the difference between all-sky and clear-sky surface shortwave radiation,serves as a key indicator of the cloud-induced cooling effect.However,F_CRE exhibits considerable variability and uncertainty across cloud types,attributable to large differences in macrophysical,microphysical,and optical cloud properties.Moreover,the dominant factors controlling these effects remain insufficiently understood for different cloud types.This study analyzes the F_CRE characteristics and their driving factors for eight distinct cloud types—shallow cumulus (Cu),stratus (St),altocumulus (Ac),altostratus (As),cirrostratus (Cs),cirrus (Ci),congestus (Co),and deep convective clouds (Dc)—using 14 years of 15-minute resolution cloud-type classification and concurrent surface shortwave radiation measurements from the central facility of the Southern Great Plains in the United States.A new metric,relative F_CRE(F_RCRE),is introduced to complement F_CRE and to reduce angular dependence effects.Using the XGBoost (extreme gradient boosting) framework and SHAP (Shapley additive explanation) values,the study interprets the dominant factors and uncertainties associated with both F_CRE and F_RCRE across cloud types.Key findings include:1) While F_CRE magnitudes exhibit statistically significant positive correlations with cloud fraction and albedo and a negative correlation with solar zenith angle across all cloud types,detailed analysis reveals complex,nonlinear relationships that vary by cloud type.2) At the 95% confidence level,F_CRE amplitudes range from -350 to 206 W·m^-2 for low cloud fraction/albedo clouds (Cu,Ac,and Ci),from -926 to 371 W·m^-2 for intermediate types (St,Cs,As),and from -1 172 to 289 W·m^-2 for high cloud fraction/albedo clouds (Co and Dc),indicating substantial inter-cloud-type variability.3) The proposed F_RCRE metric—functionally similar to F_CRE—has three dominant predictors:cloud fraction,cloud albedo,and direct irradiance.F_RCRE minimizes the influence of solar zenith angle and reduces uncertainty by 2.6% to 66.0% (mean reduction of 10.7%) compared to F_CRE,with the most notable improvement observed for convective cloud types.4) For high cloud fraction/albedo clouds (Co and Dc),cloud albedo is the dominant driver of F_RCRE,whereas for low cloud fraction/albedo clouds (Cu,Ac,and Ci),cloud fraction is more influential.These results highlight both the similarities and differences between F_CRE and F_RCRE,demonstrate the value of F_RCRE in reducing uncertainty in estimating cloud radiative effects,and offer a refined understanding of cloud-radiation interactions.This study provides important insights for improving the representation of cloud-radiative processes in climate models.

Abstract:The Taklimakan Desert,one of China's major dust source regions,exerts significant regional and global environmental influence through its dust emission and transport processes.Understanding how different surface types—artificial green land and natural sandy land—affect dust dynamics is crucial for improving dust process modeling and optimizing wind and sand control strategies.This study compares dust transport characteristics between artificial green land (Tazhong) and natural sandy land (Xiaotang) in the Taklimakan Desert.Using Big Spring Number Eight (BSNE) gradient samplers,dust samples were collected from April 1 to July 10,2024.Horizontal dust flux and grain size distribution were systematically analyzed.The main findings are as follows:1) There was substantial spatial heterogeneity in horizontal dust flux,with Xiaotang (65.3 kg·m^-2·h^-1) exhibiting approximately 2.2 times the flux of Tazhong (29.7 kg·m^-2·h^-1),indicating stronger dust emission potential in natural sandy environments.The vertical distribution pattern at Tazhong displayed a nonlinear “decrease-increase-decrease” profile with turning points at 8 m and 63 m,deviating from the typical power-law form.In contrast,Xiaotang's flux decreased with height,following a power-law distribution.2) Dust composition was dominated by very fine sand (48.8%) and silt (40.6%),accounting for 89.4% of total particles.Both sites showed increasing silt content and finer particle sizes with height.However,Tazhong exhibited overall coarser particles,better sorting,and narrower kurtosis compared to Xiaotong.3) Gravity-driven deposition of local materials was concentrated within the lower atmospheric layer (<10 m) at both sites.Differences in land surface type and dust source primarily accounted for variations in horizontal flux and particle size distribution.Wind speed,wind direction,and vegetation conditions were key drivers of temporal variation in dust flux,which increased with wind intensity.
Future research should aim to further quantitatively assess the relative contribution of wind speed,direction,and vegetation coverage to the vertical differentiation of dust flux and particle size.Additionally,more precise source attribution and long-term fixed-site observations under extreme weather conditions—such as sandstorms—are needed to deepen understanding of surface-atmospheric interactions.These efforts will enhance the scientific basis for wind and sand control measures and help evaluate the ecological benefits of engineering interventions in the Taklamakan Desert.

Abstract:Volatile organic compounds(VOCs) emitted from chemical industrial parks pose significant threats to air quality and human health by driving ground-level ozone (O₃) formation,contributing to secondary organic aerosol (SOA) production,and influencing regional climate.Understanding the complex interplay between VOC sources,atmospheric transformations,and associated impacts is essential for designing effective pollution control strategies.This study presents a comprehensive characterization of VOCs within a large chemical industrial park in Nanjing,Jiangsu Province,China—a region facing persistent air quality challenges.Continuous,high-resolution monitoring of 123 VOC species was conducted over a 24-month period using gas chromatography-flame ionization detection/mass spectrometry (GC-FID/MS).The objectives were to:1) establish long-term VOC concentration profiles;2) quantify seasonal variations and compositional characteristics;3) identify key VOC species and their role in local O₃ formation sensitivity;4) evaluate the contribution of industrial emissions to regional ozone formation potential (OFP);and 5) assess the non-carcinogenic and carcinogenic health risks associated with chronic exposure among nearby residents.The mean total VOC (TVOC) concentration during the study period was 296.89 μg·m^-3 with notable reductions observed in the second year (December 2021—November 2022) compared with the first year.Seasonal patterns showed the highest TVOC concentrations in spring,followed by winter,summer,and autumn.Oxygenated VOCs (OVOCs),alkanes,and alkenes dominated the VOC composition.Petrochemical analysis revealed that interactions between nitrogen oxides (NO_x) and reactive VOCs strongly influenced O₃ production.Elevated nighttime NO_x and TVOC concentrations during pollution episodes decreased significantly after sunrise due to photochemical reactions,often dropping below levels observed on clean days.In summer,VOCs—particularly alkenes such as propylene,ethylene,and 1,3-butadiene—were the dominant contributors to O₃ formation,with the industrial park accounting for up to 33% of local OFP.Health risk assessment indicated significant non-carcinogenic risks throughout most of the monitoring period,except during the summer and autumn of 2022.Lifetime carcinogenic risks exceeded the acceptable threshold for several VOCs,particularly in winter 2020.Key hazardous species included 1,2-dibromoethane,1,1,2,2-tetrachloroethane,bromodichloromethane,carbon tetrachloride,1,2-dichloroethane,benzene,1,3-butadiene,and acetaldehyde.
This study highlights the necessity of long-term VOC monitoring in industrial parks and its critical role in guiding air quality management and protecting public health.Future research should prioritize:1) application of advanced source apportionment methods (e.g.,positive matrix factorization) to pinpoint and control dominant emission sources;2) detailed investigation of OVOC origins and transformation pathways to better constrain secondary pollutant formation;and 3) incorporation of vertical profile monitoring to improve understanding of atmospheric transport and enhance the accuracy of regional air quality models.

Abstract:Vegetation plays a critical role in regulating the water cycle and mediating carbon fluxes within the climate system. It responds rapidly to climate change and is highly sensitive to climate variability. In the context of accelerating global warming, particularly in the mid-to-high latitudes of Asia where warming rates are 2—3 times the global average—vegetation dynamics are expected to undergo significant changes. However, substantial uncertainties persist in projecting future vegetation changes in this region due to model biases, limitations in the spatiotemporal resolution and consistency of satellite remote sensing datasets, and variations in parametrizations of vegetation-climate feedbacks across models. This study integrates three independent satellite-based leaf area index (LAI) datasets—GLOBMAP (Version 3), GIMMS LAI3g, and GLASS—with climate and vegetation outputs from 15 CMIP5 and 19 CMIP6 models. Using a multi-model ensemble mean (MME) framework, we systematically evaluate historical and projected vegetation characteristics in the mid-to-high latitudes of Asia.
Analysis of the satellite datasets reveals that regions with sparse vegetation exhibit higher interannual variability, while dense vegetated regions show more pronounced increasing trends in LAI.Areas of high MME mean LAI, variability, and seasonal amplitude are primarily located in woodland regions at elevations below 1 200 m. Among the datasets, GLOBMAP and GLASS exhibit stronger mutual consistency.The MME approach involves simulation performance by mitigating nonlinearities in individual model outputs. Evaluation of historical simulations indicates that both CMIP5 and CMIP6 models perform best in reproducing surface air temperature, with CMIP6 models demonstrating superior accuracy overall. CMIP6 also partially corrects the overestimation of LAI seen CMIP5 simulations. Ensemble simulations (MME) outperform individual modes in reproducing historical vegetation dynamics.
Future projections under both low- and high-emission scenarios (RCP4.5/SSP2-4.5 and RCP8.5/SSP5-8.5, respectively) show consistent increases in LAI mean values, interannual variability, and seasonal amplitude, with larger changes under high-emission scenarios. Regions with higher baseline vegetation cover are projected to experience greater LAI increases. While spatial patterns of change vary, the greatest increases are projected in high-LAI regions, high-latitude zones, and East Asia. Notably, LAI increases during the warm season are more pronounced than those in the cold season, indicating enhanced seasonal growth dynamics under future warming.
This study enhances our understanding of vegetation-climate interactions in complex mid-to-high latitude ecosystems which provides key insights into model performance, vegetation sensitivity, and carbon cycle feedbacks. These findings offer a scientific basis for improving ecosystem modeling and informing regional climate adaptation and carbon management strategies.

Abstract:Surface air temperature changes in Antarctica are a critical aspect of global climate change research.In recent years,certain regions of the Antarctic continent have experienced significant warming and an increase in extreme weather events,which have severely impacted ice shelf stability and the mass balance of the Antarctic ice sheet.Rising temperatures accelerate ice sheet degradation,thereby contributing to global sea level rise.These changes underscore the urgency of gaining a deeper understanding of Antarctic temperature variability.Temperature changes across Antarctica exhibit complex spatial and temporal patterns,and substantial uncertainties remain regarding future climate projections.Over the past two decades,surface air temperatures in Antarctica have undergone notable shifts,particularly marked by an increase in the frequency of extreme warm events,drawing considerable attention from the scientific community.This paper reviews recent progress on Antarctic temperature variability,focusing on two primary aspects:long-term temperature trends and extreme temperature events.It discusses their spatiotemporal characteristics,associated meteorological and climatic backgrounds,and links to large-scale atmospheric circulation anomalies.Significant regional differences exist in temperatures trends across the continent.West Antarctica,especially during winter and spring,has experienced pronounced warming.The Antarctic Peninsula,in particular,is warming rapidly,with an annual mean temperature trend of approximately 0.5 ℃ per decade and recorded extreme high temperatures exceeding 10 ℃.In contrast,temperature trends in inland East Antarctica remain relatively modest.These temperature variations are largely influenced by atmospheric circulation,which governs the meridional transport temperature of heat and moisture.Previous studies have demonstrated that tropical Pacific sea surface temperature anomalies can trigger Rossby wave propagation,which in turn modulates atmospheric circulation around Antarctica.This teleconnection mechanism is responsible for contrasting warming and cooling patterns in West and East Antarctica,respectively,primarily through warm or cold air advection.
Research into the drivers of extreme high-temperature events indicates strong associations with specific atmospheric circulation anomalies and topographic effects.Such events have increased not only on the Antarctic Peninsula but also in parts of inland East Antarctica.During these events,advection is the dominant process influencing temperature anomalies.Moreover,short-term regional circulation anomalies can induce extreme temperature episodes.Local topographic features,particularly in the Antarctic Peninsula,which extends into the midlatitude westerly belt,play a critical role in modifying airflow by blocking,lifting,or redirecting air masses,thereby affecting surface temperature.Despite considerable progress in understanding Antarctic surface temperature changes,observational limitations,especially across the Antarctic Plateau,continue to constrain research.Sparse station coverage in these interior regions hampers the study of interannual to decadal temperature variability.Nevertheless,the latest research provides valuable insights into the dynamics of Antarctic temperature changes and their broader climatic implications.

Abstract:In recent years,the frequency of extreme precipitation events in North China has exhibited a notable upward trend,highlighting the need to understand their spatiotemporal variability and driving mechanisms.Previous studies have identified an out-of-phase relationship between sea surface temperature (SST) anomalies in the tropical eastern Pacific and the tropical Atlantic.This study investigates the relationship between extreme summer precipitation days in North China and the tropical eastern Pacific-Atlantic SST anomaly dipole,with the goal of elucidating its underlying physical mechanisms and contributing to improved disaster prevention and mitigation strategies.Using high-resolution daily precipitation data from CN05.1 (1979—2021),monthly SST data from ERSST V5,and atmospheric reanalysis data from ERA5,extreme precipitation days are defined based on the 90th percentile threshold.Empirical orthogonal function (EOF) analysis reveals that the SST anomaly dipole is the leading mode of tropical eastern Pacific-Atlantic SST variability during boreal summer.In its positive (negative) phase,SSTs in the eastern tropical Pacific are anomalously cold (warm),while those in the tropical Atlantic are anomalously warm (cold),corresponding to an increase (decrease) in extreme summer precipitation days in North China.Mechanistically,the positive phase of the tropical eastern Pacific-Atlantic SST anomaly dipole is associated with an intensified Walker circulation and enhanced SSTs in the tropical western Pacific,which in turn amplify the local Hadley circulation and induce an anomalous anticyclonic circulation over the Northwest Pacific.These anomalies strengthen the East Asian summer monsoon,promoting moisture transport and convergence over North China.Concurrently,warming in the tropical Atlantic enhances local convection,while upper-tropospheric convergence and positive vorticity anomalies over western Europe and the Mediterranean trigger a quasi-stationary wave train.This wave train propagates eastward,resulting in an upper-tropospheric anticyclonic anomaly over North China and Northeast Asia,further supporting sustained upward motion and extreme precipitation in the region.These results demonstrate a robust strong linkage between the tropical eastern Pacific-Atlantic SST anomaly dipole and extreme summer precipitation days in North China.However,further investigation is required to determine whether this dipole structure is modulated by ENSO development and to identify which tropical ocean basin plays a dominant role in this relationship.Additionally,a westward shift in the region of strongest correlation with tropical Atlantic SST anomalies is observed from the preceding winter to the following summer,raising questions about the drives of this migration.It also remains unclear whether this relationship exhibits decadal-scale variability.These open questions warrant further exploration in future research.

Abstract:With the rapid advancement of industrialization and urbanization,global climate change has accelerated,marked not only by rising temperatures but also by more frequent extreme weather events such as heat waves,intense precipitation,and prolonged droughts.These changes pose significant challenges to human societies.As a critical component of agricultural production,cropland is highly sensitive to climatic variations,thereby influencing the sustainability of food systems.In recent years,cropland area in China has exhibited a fluctuating trend;however,few studies have systematically investigated its response to recent climate change.In this study,we utilize high-resolution land cover and meteorological reanalysis dataset to assess the spatiotemporal response of cropland area in China to variations in temperature and precipitation from 2000 to 2019.A fixed-effects regression model is employed to isolate the climatic effects by controlling for human factors such as policy interventions.Our findings indicate that China has been undergoing a shift toward warmer and drier conditions.The relationship between cropland area and climatic variables is non-linear:higher temperatures and moderate precipitation are generally favorable for cropland expansion.Compared with precipitation,temperature exerts a stronger influence,contributing to a 1.22% increase in cropland area during the study period.Specifically,reductions in the frequency of cold days (daily mean temperature below -10 ℃) and increases in hot days (above 30 ℃) contributed 0.67% and 0.31%,respectively,to cropland expansion.However,the growing frequency of extreme rainfall events,particularly during the later stages of crop growth,has had a significant negative impact on cropland.These results highlight the importance of accounting for extreme weather events when evaluating cropland dynamics.Moreover,human factors,especially policy-related land use changes,remain crucial.In regions with high cropland quality,such as southern China and the middle and lower reaches of the Yangtze River,policy-driven losses may counteract the positive climatic effects on cropland.Going forward,maintaining cropland quantity should be balanced with ensuring its quality to support sustainable agricultural development.

Abstract:From July 29 to August 1,2023,an extreme rainstorm struck North China (hereafter the “23.7” North China rainstorm).The event was characterized by exceptional duration,extensive spatial coverage,and unprecedented intensity,with multiple historical rainfall records broken.The Haihe River basin experienced its first basin-wide flood since 1963,affecting more than 1 million people.This disaster was ranked as the most significant weather and climate event among China's top ten domestic events of 2023.To investigate the multiscale interaction mechanisms of this extreme event—specifically how synoptic-scale systems mediated the transfer of dynamics and energy from large-scale circulation,organized and sustained mesoscale convective structures,triggered localized meso-β/γ-scale activity,and ultimately produced extreme precipitation—we analyzed surface and upper-air observational datasets together with NCEP FNL 1°×1° reanalysis data.Potential function and stream function diagnostics,along with dynamic and thermodynamic analyses,were employed to examine the evolution of synoptic-scale systems and associated variations in moisture,dynamics,and thermodynamics.Key findings include:1) A “chain-like” configuration formed among the tropical monsoon system,the residual circulation of Typhoon Doksuri,and the subtropical high.The northward movement of Doksuri’s remnant low established a transcontinental moisture corridor from eastern China to North China,sustaining anomalously strong water vapor transport from the tropical Indian Ocean,South China Sea,and Northwest Pacific.This unprecedented moisture convergence provided critical conditions for extreme precipitation.2) Synoptic-scale systems exerted pivotal control through adjustments of mid- to high-latitude upper-level circulation,particularly variations in the position and intensity of the westerly jet.These changes enhanced anticyclonic vorticity and upper-level divergence over North China,inducing “high-level suction” that propagated upward motion downward into the lower troposphere.Coupled with cyclonic convergence generated by southeastern low-level jets,this vertical circulation reinforced deep convection across the region.
The role of diabatic heating was further examined using the apparent heat source Q₁ and moisture sink Q₂.Combined with full-form vorticity,vertical velocity,and potential tendency equations,diagnostics revealed that substantial diabatic heating during the rainfall process provided strong positive feedback,intensifying the vertical dynamic structure of the rainstorm system and deepening the geopotential height anomalies over North China.This feedback further strengthened the precipitation environment,sustaining the prolonged and intense rainfall.Overall,the rainstorm was dynamically driven,with thermal processes providing secondary reinforcement.
This study demonstrates that the “23.7” North China rainstorm exhibited distinct synoptic-scale dynamic-thermodynamic mechanisms compared to historical events.While resembling CISK-like processes,initiation occurred aloft,with anticyclonic divergence from the westerly jet triggering mid-level convection.Subsequent enhancement of low-level convergence by a jet-trough interaction activated lower-tropospheric convection,leading to vertical coupling of cumulus activity that reinforced the rainfall environment across North China.Unlike classical CISK,where boundary-layer frictional convergence initiates convection,this event was initiated by upper-tropospheric forcing.From a scale-interaction perspective,the stable coupling of upper- and lower-level jets differed from mechanisms observed in the 2012 Beijing “7.21” rainstorm or the 1996 North China event.Although sharing large-scale circulation similarities with the 2021 Henan rainstorm,the“21.7”event differed in emphasizing mid-lower tropospheric dual-jet and latent heat dynamics.These mechanistic differences explain the extreme features of the “23.7” event,including its broader spatial extent,larger cumulative rainfall,stronger hourly intensity,and prolonged duration.

Abstract:Tropical cyclones (TCs) are among the most destructive natural hazards in the Northwest Pacific,and accurate prediction of their intensity—particularly during rapid intensification (RI)—remains a major challenge.RI is strongly influenced by oceanic thermal conditions,including elevated sea surface temperature (SST) and abundant upper-ocean heat content (OHC),which provide the energy required for TC intensification.The Kuroshio current in the East China Sea,characterized by strong thermal inertia,can exert a significant influence on TC intensity.When RI occurs near coastal regions,short warning lead times and limited disaster mitigation capacity can result in severe impacts.Therefore,understanding how the East China Sea Kuroshio modulates TC intensity is critical for improving forecasts and reducing disaster risk.
Typhoon Hinnamnor,the 11th TC of 2022,weakened during its initial northward movement but underwent a pronounced RI episode upon crossing the main axis of the East China Sea Kuroshio.To investigate the mechanisms responsible,we combined observational datasets and numerical simulations.Hourly ERA-5 reanalysis,daily NOAA OISST SST data,and the IBTrACS best-track dataset were used,along with multi-member ensemble simulations from the Weather Research and Forecasting (WRF) model,to diagnose the key processes involved.
Results show that during the RI phase,the TC center was located far from the upper-level trough and jet stream,while environmental vertical wind shear remained relatively strong (>8 m·s^-1),both typically unfavorable for intensification.However,the SST anomaly over the Kuroshio region reached 1—3 ℃,providing substantial surface heat flux.The 26 ℃ isotherm depth extended to 85—110 m,and positive temperature anomalies of approximately 2.5 ℃ persisted to 250 m depth prior to RI,indicating considerable OHC capable of buffering typhoon-induced surface cooling.These anomalous thermal conditions in the Kuroshio region likely played a decisive role in sustaining Hinnamnor's RI despite unfavorable atmospheric conditions.
A statistical analysis of TCs crossing the key Kuroshio region from 1980 to 2022 further reveals that the highest TC frequency occurred in August and September.The proportion of intensifying TCs peaked in August and was lowest in October and November.The decline in intensification probability from September onward corresponds to a marked seasonal decrease in OHC along the Kuroshio's main axis in the East China Sea.

Abstract:Rear rainstorms associated with landfalling typhoons pose significant challenges for meteorological forecasting,with their underlying dynamical mechanisms remaining insufficiently understood.During the landfall and subsequent northward movement of Typhoon Doksuri (2305) in 2023,an intense rear rainstorm produced extreme rainfall over Fujian Province.This study investigates the synoptic-scale circulation patterns before and after Doksuri's landfall using a combination of observational data and numerical simulations.Results show that the coupling between two distinct low-level jets—a synoptic-scale low-level jet (SLLJ) in the mid-troposphere and a boundary layer jet (BLJ) induced by the Taiwan Strait's channeling effect—significantly amplified vertical motion and precipitation in the rear sector of the typhoon.Numerical experiments further reveal that:1)After landfall,orographic influences rapidly weakened the low-level vortex,whereas the mid-level circulation persisted,forming an SLLJ.The SLLJ dynamically coupled with the BLJ generated by the terrain-induced channel effect.Their vertical alignment formed a three-dimensional structure characterized by strong low-level convergence in the BLJ's exit region and enhanced mid-level divergence in the SLLJ's entrance region.This vertical configuration promoted intense and persistent upward motion,creating favorable conditions for deep convection and rainstorm development.2)Sensitivity experiments demonstrate that the strength of this coupling—and its amplification of rainfall—depends primarily on the relative intensities of the BLJ and SLLJ.These in turn are modulated by the Taiwan Strait's topography and the intensity of the typhoon's primary circulation.The BLLJ is predominantly enhanced by the “channel effect” of the Taiwan Strait,while a stronger typhoon core circulation supports the formation of a more intense SLLJ.Environmental moisture content mainly influences total precipitation but has limited impact on the jet intensities or the coupling mechanism.Overall,the coupling of the double low-level jets plays a key role in intensifying rear-sector rainfall during Doksuri's post-landfall evolution,highlighting the importance of vertical jet interaction in the forecasting of extreme precipitation events associated with landfalling typhoons.

Abstract:Traditional precipitation forecast verification methods often rely on binary event testing,which presents three major limitations. First,precipitation thresholds can assign adjacent precipitation amounts to different categories,leading to large discontinuities in scoring results. While multi-threshold statistical methods are suitable for continuous single-point forecasts or multi-point forecasts at a given time,they cannot quantitatively evaluate single-point forecasts at a specific time. Second,the double penalty problem-where small spatial or temporal mismatches between forecasts and observations result in both false positives and false negatives-can produce scores substantially lower than forecasters subjective assessments. This issue is particularly pronounced for kilometer-scale,high-resolution forecasts,where binary verification methods may fail to reflect the actual improvements in forecasting skill or provide actionable feedback for model developers and forecasters. To address these challenges,Zhang et al.(2024) proposed a general evaluation method for cross-scale precipitation forecasts—the Precipitation Accuracy Score (PAS)—which reduces score discontinuity caused by threshold partitioning and incorporates both spatial distribution and deviation magnitude into the evaluation. PAS can access single-point forecasts and provide timely,meaningful feedback to forecasters. However,as a point-to-point method,PAS still cannot fully eliminate the double penalty problem. Spatial verification techniques,such as neighborhood-based approaches,have been shown to alleviate this issue,particularly for high-resolution and heavy precipitation.
In this study,we enhance the PAS framework by incorporating a neighborhood-based weighting scheme that matches forecast and observation grids using distance-weighted scoring. This modification aims to mitigate the double penalty problem while retaining sensitivity to forecast location accuracy. The method was applied to National Meteorological Center's intelligent grid analysis data to evaluate the Jiangsu local refined weather analysis and forecasting system during the 2021 flood season. Performance was compared with established cross-scale metrics,including RMSE,structural similarity (SSIM),peak signal-to-noise ratio (PSNR),and the stable equitable error in probability space(SEEPS).
The main findings are as follows:1) The neighborhood-based PAS effectively reduces the double penalty effect caused by positional errors,representing a rational improvement to the original PAS method. 2) Both PAS and neighborhood-based PAS show strong correlations with established cross-scale metrics,confirming their reliability. 3) Compared with RMSE,these methods better balance sensitivity to high-intensity precipitation. Compared with SSIM and PSNR,they offer greater interpretability and produce results more consistent with forecaster's subjective assessments. 4) Relative to SEEPS,the neighborhood-based PAS retains the ability to detect and distinguish heavy precipitation,while mitigating the severe double penalty associated with such events in the original PAS.
In summary,the neighborhood-based method PAS represents a meaningful enhancement of the original PAS method,providing a reliable and interpretable cross-scale tool for precipitation forecast verification. It aligns well with forecasters' practical needs and show strong potential for operational applications.