Affected by the upper⁃level trough and strong cold air,from April 20th to 22nd,2023,significant strong cooling weather occurred in Sichuan Province and its surrounding areas. To explore the impact and mechanism of the orographic gravity wave parameterization scheme on low temperature in complex terrain areas,combining reanalysis data with SWC⁃WARR (South West Center ⁃ WRF ADAS Rapid Refresh),sensitivity experiments of the orographic gravity wave parameterization were carried out. By analyzing the simulation results,it was found that the GWD experiment could effectively improve the warm bias in temperature simulation of the CTL experiment in the central part of the western Sichuan Plateau and the Sichuan Basin. To explore the reasons for the improvement of the warm bias,by analyzing the 500 hPa horizontal wind field,it was found that the drag weakened the wind speed in the central part of the Qinghai⁃Xizang Plateau (QXP) and enhanced the westerly flow around the southern slope of the QXP,thus strengthening the wind speed in the western Sichuan Plateau. After scale separation using Barnes filtering,it was found that the change in the large⁃scale wind field was the main cause of the change in the simulated wind field. The increase in the southwesterly wind speed on the southern slope of the QXP in the GWD experiment led to an increase in cold advection,which was the main reason for the improvement of the warm bias in the western Sichuan Plateau, while the improvement of the warm bias in the Sichuan Basin was caused by the weakening of the warm advection in the southeastern part of the basin at 850 hPa.

Volatile organic compounds (VOCs) are crucial precursors for tropospheric ozone and secondary fine particulate matter (PM_2.5)，so the treatment strategies of VOCs concentrations and source emissions in data assimilation systems can significantly affect the accuracy of air pollutant forecasting. This study proposes a correlation⁃based VOCs factor to quantitatively select VOCs model variables and emission inventory items updated by observational data during the data assimilation process. The research employs the WRF⁃Chem (Weather Research and Forecasting model coupled with Chemistry) model along with the EnSRF (Ensemble Square Root Filter) data assimilation algorithm，focusing on case studies of extreme heat events in the Yangtze River Delta region from July to August，2022. Results show that updating variables through VOCs factor will give the total VOCs emissions a diurnal peak similar to ozone observations. This diurnal peak in VOCs emissions allows for more accurate correction of the systematic model underestimations in ozone forecasts. In terms of the forecasts of ozone and PM_2.5，the assimilation strategy using the VOCs factor for updating variable selection performs the best. Compared to strategies without selective updates of VOCs variables，the RMSE (Root Mean Square Error) decreases by 5.5% for ozone and 7.2% for PM_2.5.

Accurate forecasting of typhoon track and intensity is the basis of typhoon disaster reduction and prevention. In this study,a typhoon forecast model for track and intensity is developed based on the latent diffusion model (LDM). To this end,the LDM is improved,and the structural similarity (SSIM) loss and discrete Fourier transform (DFT) loss are introduced to improve the performance of VAE in reconstructing the details of meteorological variables. In addition,the Diffusion Transformer (DiT) with better scalability is used as the noise prediction network,and the pre⁃training and fine⁃tuning strategy is used to optimize the forecast model to further enhance the forecasting ability of the model. The forecast model is used to test the 6,12,18 and 24 h forecasts of nine typhoons in the northwest Pacific in 2023. The forecast results show that the improved LDM has a significant improvement in the typhoon track and intensity forecasting ability. The ensemble method can further enhance the stability and accuracy of the forecast model,especially in typhoon track forecasting. These results provide new insights and methods for future AI⁃based typhoon forecasting.

In recent years，the technique of estimating typhoon intensity using typhoon cloud scene types has been widely used in operational forecasting，but whether the cloud scene types correlate with the typhoon track has not been analyzed. In this paper，typhoons occurring in the Northwest Pacific during the four⁃year period of 2019-2022 are selected，and the cloud scene type data obtained based on the advanced Dvorak technique are used to analyze the frequency of six types of cloud scenes at different stages of the typhoon's life span，as well as the characteristics of cloud scene types occurring at different typhoon movement directions. The results show that all types of cloud scenes may appear when the typhoon is moving toward the northwest，and each type of cloud scene has the possibility to appear in any moving direction，but each type has its most likely mainstream moving direction. The occurrence of different cloud scene types varies with seasons，and their frequency also changes when the typhoon experiences a sudden shift in its track during its life cycle. As the intensity of a typhoon increases，its movement direction alters，and the dominant cloud scene types appearing in its moving directions also change. During the tropical depression stage，cloud scene mainly reflects the asymmetric structure of the typhoon. Once the typhoon reaches its full intensity，the cloud scene shifts to a more symmetric structure，and the track becomes more concentrated in the northwest direction. This indicates that there is a coevolutionary relationship between typhoon cloud scene types and their intensity and track.

This study analyzes the climatology of Integrated Kinetic Energy (IKE) and its interdecadal variations of tropical cyclones (TCs) over the Western North Pacific (WNP) from July to October during the period of 1981-2017.The results show that the distribution of TC IKE resembles a log⁃normal distribution，with 75% of TC IKE records lower than 89.38 TJ.In terms of spatial distribution，the area with high IKE is mainly concentrated to the east of China Taiwan and the Philippines，and west of 160°E，while the average IKE in the South China Sea is relatively low.The whole period is divided into two subperiods (P1: 1981-1998，P2: 1999-2017) to examine the interdecadal variations of IKE. The results show that during the P2 period，TC IKE exhibits a slight upward trend，with a decrease in the proportion of TCs with IKE lower than 50 TJ and an increase in the proportion of TCs with IKE within the range of 50–150 TJ.In terms of spatial distribution，the areas with increased IKE extend from the southeastern part of the WNP in a northwest direction. Meanwhile，the location of maximum IKE has shifted poleward，moving closer to the East Asian coastal regions.These changes of IKE are related to environmental factors. The increase in the low⁃level relative vorticity，the rise in mid⁃level humidity,the decrease in vertical wind shear，and the relatively lower static stability provide favorable dynamical and thermodynamic conditions for the development of TCs. The upward trend of IKE for landfalling TCs over China is more pronounced than that over the WNP basin，which is primarily attributed to the combined effect of the changes in TC trajectory and environmental conditions.

Isentropic analysis is a method that distinguishes high⁃entropy ascending air masses from low⁃entropy descending air masses through equivalent potential temperature ({\theta }_e)，effectively revealing the thermodynamic and dynamic structural characteristics of the atmosphere. In this study，we conducted high⁃resolution numerical simulations of the 2019 Northwest Pacific Super Typhoon Lekima using the fully compressible mesoscale numerical model (WRF V4.0) and analyzed the evolution characteristics of Lekima within the isentropic framework based on the simulation data. It has been found that the isentropic framework can effectively reflect the formation of the upper⁃level warm⁃core structure during the rapid intensification (RI) phase of Lekima，the significant decrease in relative humidity in the eye region，and the corresponding ascending motions in the primary and secondary eyewalls during the formation of concentric eyewalls. These findings indicate that the isentropic framework can capture the key structural changes during the rapid intensification and eyewall replacement processes of typhoons. Compared to the physical coordinate system，its advantage lies in not requiring the prior determination of the typhoon's center position. Based on isentropic analysis，this study further examined the energetics characteristics during the development and evolution of Lekima. The ability of Lekima to extract energy from the ocean and its corresponding heat engine efficiency gradually increased during its development and intensification，reaching a peak during the RI phase. Although it slightly declined during the eyewall replacement process，it remained at a relatively high level. This suggested

that Lekima efficiently converted latent heat into mechanical energy during its rapid intensification and eyewall replacement processes，sustaining its intense dynamical structure.

This study analyzed the precipitation characteristics and circulation background of the heavy rainfall event in eastern Sichuan on July 26,2023,using China Meteorological Administration Multi⁃source Merged Precipitation Analysis System (CMPAS) and ERA5 reanalysis data from the European Centre for Medium⁃Range Weather Forecasts. Sensitivity experiments were conducted using the WRF V4.2.2 mesoscale numerical model. The model performance was quantitatively assessed using correlation coefficients ( CC),root mean square error ( RMSE),and threat score ( TS). The study explored the impact and mechanisms of subgrid orographic gravity wave drag (OGWD) on the heavy rainfall event. Additionally,the Barnes filter was applied to perform scale separation of the circulation fields,enabling a detailed analysis of the influence of circulation at different scales on the precipitation process. The results indicate that the WRF model simulates the precipitation area too far eastward,but the inclusion of OGWD significantly improves the precipitation location bias. Orographic gravity wave drag primarily affects the wind field: at mid⁃to⁃upper levels of the troposphere,it weakens the northwesterly winds behind the plateau vortex, at lower levels of the troposphere,it weakens the southeasterly winds transporting moisture into the Sichuan Basin,resulting in a reduction of the northerly winds along the northern and western edges of the basin. This change alters the location of the mesoscale convergence zone,thereby improving the precipitation location bias.

This study examines an atmospheric bore formed from the collision between a gust front (GF) and a sea breeze (SB) over the Bohai sea coast of China during the night of June 12-13，2018，and discusses the role of atmospheric bore on upstream convection initiation (CI). Based on radar data，ground⁃based observations，and high⁃resolution numerical simulations，the findings indicate that the SB establishes a stable boundary layer (SBL) offshore，while the GF associated with the eastward⁃moving mesoscale convective system (MCS) undergoes a transformation due to their interaction. Initially characterized as a density current，the GF gradually evolves into a non⁃undular bore exhibiting gravity wave properties and eventually to an undular one. The undular bore then propagates within favorable trapping layers associated with the SB，lifting air parcels with high convective available potential energy (CAPE) within the SBL. This process initiates convection upstream and further sustains the MCS. Due to the widespread occurrence of GFs and SBs over the eastern coastal regions of China during the warm season，their interactions provide the possibility for bore formation under various boundary layer conditions，thereby playing a crucial role in the occurrence and development of intense convection both at night and during the daytime.

The Cloud⁃Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) is the world's first satellite to retrieve vertical structure information of the Earth's atmosphere. Since its launch in 2006，CALIPSO has provided high⁃precision vertical atmospheric profile data through its onboard Cloud⁃Aerosol Lidar with Orthogonal Polarization (CALIOP). It offers valuable support for studies on the global atmospheric environment and cloud microphysical properties. In this study，based on CALIPSO's Greenland blowing snow products from 2006 to 2023，we statistically and analytically characterize the spatial and temporal distributions of blowing snow frequency，layer depth，and layer optical depth over the 18 years and explore the relationship between surface wind speeds and blowing snow layer height and layer optical depth. The results reveal significant seasonal and spatial variations in blowing snow frequency across Greenland. December to February is the high⁃frequency period for blowing snow events，with some regions experiencing blowing snow more than 30% of the time. Spatially，high⁃frequency blowing snow areas are primarily concentrated in the northern region (30°~55°W) and the southern periphery (67°N，45°W). The blowing snow layer depth and layer optical depth range from 30 to 400 m and 0.01 to 0.8 respectively，with their spatial distributions showing strong consistency. Furthermore，the relationship between blowing snow layer depth，layer optical depth，and wind speed is nonlinear. Both parameters increase with wind speed when wind speeds are below 30 m·s^-1 but decrease as wind speeds exceed 30 m·s^-1.

This study investigated the characteristics and future changes of extreme precipitation in South China using convection⁃permitting downscaling simulations. A positive correlation was found between extreme precipitation and elevation，particularly at lower to moderate topographic heights. The relationship between extreme precipitation and temperature generally exhibited a hook⁃shaped pattern. Under a warmer climate，extreme precipitation was projected to increase more significantly at higher elevations. Regions experiencing increased extreme precipitation showed elevated levels of convective available potential energy (CAPE) and reduced convective inhibition (CIN)，indicating a more unstable atmosphere conducive to severe weather. Further analysis revealed a strong association between future changes in extreme precipitation and factors such as topographic height and large⁃scale atmospheric conditions. The rate of extreme precipitation increase was found to be between one and two times the Clausius⁃Clapeyron scaling.

Extreme heat wave events are more destructive than traditional climate events and have developed rapidly in the world in recent years. The Yangtze River Basin is a climate⁃sensitive area，so it is of great significance for event prevention and control to analyze its characteristics and evolution trend under possible future climate conditions.In the summer of 2022，the Yangtze River Basin experienced a heat wave that was unprecedented in intensity，duration，and scope.In this paper，an extreme heat wave event in the Yangtze River Basin from July 20 to August 30，2022 was simulated.Based on the combined Model Intercomparison Project Phase 6 (CMIP6) multi⁃model and multi⁃scenario set prediction results，Pseudo Global Warming (PGW) method was adopted. The changes of heat waves in the Yangtze River Basin in 2022 under SSP126，SSP245 and SSP585 scenarios were simulated and predicted.The simulation results show that: (1) the regional climate model can well reproduce the spatio⁃temporal evolution of the heat wave process in the Yangtze River Basin in 2022. (2) under different global warming scenarios (SSP126，SSP245 and SSP585)，the intensity and area of heat waves in the Yangtze River Basin in 2022 are significantly enhanced.Under SSP126，SSP245 and SSP585，the heat wave intensity increases by 3,5 and 7 ℃ respectively，and the heat wave area also doubles under SSP585. (3) under the SSP126，SSP245 and SSP585 scenarios，the West Pacific Subtropical High and the South Asian High are also increasing，while the downward long⁃wave radiation is also increasing. The increase in the area and intensity of heat waves in the Yangtze River Basin in 2022 is closely related to the changes in atmospheric circulation and radiation amount.

In the context of global warming，it is crucial to simulate the East Asian climate accurately for climate change research. The choice of parameterization scheme has a significant effect on the model performance. In this study，the multi⁃physics ensemble WRF (Weather Research and Forecasting) experiments driven by global reanalysis were conducted with a resolution of 12.5 km over CORDEX (Coordinated Regional Downscaling Experiment) East Asia in summer 2020. Different combinations of cumulus (CU)，microphysics (MP) and planetary boundary layer (PBL) parameterization schemes were set to study the effects of parameterization schemes on the regional climate simulations over East Asia in summer. The results show that the precipitation simulation in the summer of 2020 is most sensitive to cumulus scheme，followed by microphysics scheme，and the planetary boundary layer scheme has the least influence. Compared with the observed precipitation，the configuration of Modifed Tiedtke，Thompson and MYNN 2.5 in control (CTL) experiment shows the best capacity for precipitation simulation in all experiments and may be available for the simulation of East Asian summer heavy precipitation. The precipitation differences of CU experiments are related to the low⁃level circulation deviation，and the large circulation deviations of KSAS，Grell⁃Freitas and BMJ cumulus schemes are the main causes for the large⁃area precipitation biases. The simulated precipitation of different MP experiments is affected by the vertical profiles of hydrometeors，and liquid and snow particles have an important contribution to precipitation. PBL experiments affect precipitation via planetary boundary layer height and surface latent heat flux，and lower planetary boundary layer height and more upward latent heat flux usually can produce more precipitation.

With the development of observing systems，the spatial and temporal resolutions of atmospheric observations have been improved. Data assimilation combines observations with short⁃term forecasts to provide the optimal estimate of atmospheric state. The design of the observing system has crucial influences on data assimilation and forecasts. This study investigates the impact of different observation densities and frequencies on ensemble data assimilation and subsequent forecasts，with the same number of assimilated observations. The Lorenz05 model is used for observing system simulation experiments. Results show that with the optimally tuned data assimilation parameters，for the large⁃scale Lorenz05 model with small magnitudes of model errors，the medium observing density and frequency provide the smallest forecast errors and more reliable uncertainty estimations than the high or low observing densities. With large magnitudes of model errors，the high observing density yields the best forecast results for both large⁃scale and multi⁃scale Lorenz05 models，which is mainly because the high observing density can effectively correct model errors and capture small⁃scale information for the multi⁃scale model.

Antibiotic Resistance Genes (ARGs) have been considered as an important emerging pollution in the environment. Municipal wastewater treatment plants are the critical hubs for the transmission of ARGs during the urban water cycling，but the abundance and reduction of bacteriophage⁃associated ARGs remain unexplored. We collected the raw wastewater，the influent from the biological treatment and the influent from the disinfection and determined the 10 typical bacteriophage⁃associated ARGs after bacteriophage enrichment from the water samples. We found that the 10 targeted bacteriophage⁃associated ARGs occurred in all the samples，with \mathrm{l}\mathrm{g}\left(\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{s}\right) ranging from \left(\mathrm{4.9}\pm \mathrm{0.1}\right) to \left(\mathrm{8.4}\pm \mathrm{0.1}\right). Along the municipal wastewater treatment process，the biological treatment contributed mostly to the reduction of bacteriophage⁃associated ARGs and the AAO (Anaerobic⁃Anoxic⁃Oxic)+MBR (Membrane Bio⁃reactor) performed better than the sole AAO. The induction experiment with mitomycin C verified that the bacteriophage⁃associated ARGs in the activated sludge are inducible and indicated the potential release risk of bacteriophage⁃associated ARGs during the treatment. The present study provides a novel insight into the transmission of ARGs in the wastewater and enriches the understanding of environmental transmission of ARGs.

Triple negative breast cancer (TNBC) is a highly malignant type of breast cancer with high heterogeneity，easy metastasis and drug resistance，and there is an urgent need to find effective targeted therapies. Previous studies show that the natural compound Neoantimycin A has a specific inhibitory effect on the proliferation of MDA⁃MB⁃231 cells，on the basis of which we further explore the effects of Neoantimycin A on the proliferation，cell migration，cell cycle，cytoskeleton of MDA⁃MB⁃468 and MDA⁃MB⁃453. The mechanism of Neoantimycin A on TNBC is also explored. Experimental results reveal that Neoantimycin A specifically inhibits MDA⁃MB⁃468 and MDA⁃MB⁃453 with IC50 (Half maximal inhibitory concentration) of \left(\mathrm{2.02}\pm \mathrm{0.17}\right) and \left(\mathrm{9.18}\pm \mathrm{2.23}\right)\mathrm{n}\mathrm{m}\mathrm{o}\mathrm{l}·{\mathrm{L}}^{\mathrm{⁃}\mathrm{1}}. Neoantimycin A inhibits cell migration，disrupts the cytoskeleton，blocks the cell cycle of MDA⁃MB⁃468 and MDA⁃MB⁃453 cells，and reduces the expression of cell cycle⁃related genes. Mechanistic studies reveal that Neoantimycin A disrupts the localization of K⁃Ras protein on the cell membrane and blocks the Ras/Mek/Erk signaling pathway，which might be one of the important factors contributing to the inhibition of TNBC cells. Because Neoantimycin A is effective and selective against TNBC cells，on the nanomolar scale，it is expected to be further combined with tumor⁃specific antibodies to develop into an antibody⁃drug conjugate (ADC). Our study establishes a foundation for the future transformation and development of Neoantimycin A.