This study used meteorological station observation data and NCEP reanalysis data to analyze the characteristics of urban thermal environment and atmospheric circulation associated with an extreme heatwave event in the Zhengzhou Metropolitan Area from June 15 to 26,2022.Results showed that approximately 65% of meteorological stations in the Zhengzhou Metropolitan Area experienced 12 consecutive days of extreme high temperatures.On June 24,the peak of the heatwave,96% of meteorological stations recorded daily maximum temperatures exceeding 40 ℃,with several stations exceeding 45 ℃.This event was primarily influenced by a continental high-pressure system with an upper-level anticyclone,forming a structure with upper-level divergence and lower-level convergence,which supported the maintenance of a low-level warm low-pressure system,leading to the occurrence,development,and prolonged persistence of the heatwave.Significant urban heat island (UHI) effects were observed in all major cities within the Zhengzhou Metropolitan Area,greater UHI intensity at nighttime than daytime.The UHI intensity was correlated with the size of city,with Zhengzhou exhibiting significantly stronger UHI effects than other cities,reaching a nighttime UHI intensity up to 2.7 ℃.Under the combined effects of the heatwave and urban heat island,daytime human thermal stress duration was significantly extended in densely populated regions in the Zhengzhou Metropolitan Area.

This study evaluates the forecast performance of summer precipitation in Northeast China from four MODES model data products,comprehensive trend anomaly test score (Ps),anomaly sign consistency rate (Pc),anomaly correlation coefficient (ACC),and temporal correlation coefficient (TCC).The spatial distribution of anomalies between predicted and observed values from each model was analyzed.The results show that MODES data products performed well in predicting anomalous trends of summer precipitation in Northeast China.MODESv2_NCC had the highest number of stations with statistically significant positive correlations between predicted and observed summer precipitation,mainly in the Songhua River and Liao River basins,and outperformed other models.The average regional Ps and Pc for all models were 63.0 points and 50.0%,respectively,with MODESv2_ECMWF achieving the best performance (average Ps:66.4 points,Pc:51.8%).All models performed better in forecasting precipitation deficits than surpluses,with MODESv2_NCC,MODESv2_JMA,and MODESv2_NCEP showing good performance for below-normal summer precipitation forecasts in the southern region of the Songliao Basin.

Using solar radiation and conventional meteorological observation data from the Shenyang national meteorological station between 1993 and 2022,this study analyzes the changes in solar radiation and its relationship with meteorological factors in this region.The results show that both the annual total radiation and direct radiation in Shenyang have shown continuously increasing,with climate inclination rates of 237 MJ·m^-2·(10 a)^-1 and 349 MJ·m^-2·(10 a)^-1,respectively.The diffuse radiation is negatively correlated with both total radiation and direct radiation,with a climate inclination rate of -112 MJ·m^-2·(10 a)^-1.From 1993 to 2022,the total solar energy resource level in Shenyang increased from abundant to very abundant,and the direct radiation ratio level changed from high/medium to very high.Total radiation and direct radiation showed good correlations with sunshine percentage,relative humidity,and haze days at both annual and monthly scales.From 2013 to 2022,Shenyang had the highest sunshine percentage,lowest relative humidity,and fewest haze days during the 1993-2022 period.The combined effect of these three meteorological factors likely contributed to the significant increase in annual total radiation and direct radiation,and the decrease in diffuse radiation in Shenyang over the past decade.Multiple linear regression models were established using annual total radiation and monthly atmospheric transparency coefficient as dependent variables and the three meteorological factors as independent variables.The validation results of these models in both Shenyang and Chaoyang passed significance tests,with correlation coefficients between simulated and measured values of annual and monthly total radiation exceeding 0.654 and 0.965,respectively,and simulation accuracies exceeding 92% and 90%.

Based on frozen soil observation data,daily average ground temperature,daily average air temperature,and extreme minimum air temperature from six meteorological stations in Dalian city from October 1970 to April 2021,this study analyze the spatiotemporal variation characteristics of maximum frozen soil depth in Dalian over the past 51 years and explore its response to climate warming using wavelet analysis,linear regression analysis,and the Mann-Kendall (M-K) test.The results show that the maximum frozen soil depth was at a climate tendency rate of -6.9 cm/10 a,the average annual duration of frozen soil is 117 days,with a decreasing trend at the climate tendency climate tendency rate of -7.2 days/10 a.The onset of freezing is increasingly delayed,while the end date advances,with the average onset and end dates being November 20 and March 18,respectively.The maximum frozen soil depth exhibited periodic variation characteristics at 4 scales,with the 16-26 year period being the most significant.Correlation analysis reveals that ground temperature,air temperature,and extreme minimum temperature are all significantly negatively correlated with maximum frozen soil depth,with ground temperature exerting the strongest influence.

Based on conventional meteorological observation data,FY-4A satellite data and ERA5 reanalysis data,this study analyzes the large-scale environmental background,dynamical conditions,as well as the forcing mechanism of meso-β scale deep convective cloud clusters and their feedback mechanism associated with a heavy rainfall event over the Bohai Rim region during 5-7 July,2022.The results show that under the joint influence of an upper-level trough and Western Pacific subtropical high,low-level shear line and low-level vortex provided favorable dynamic conditions for the development of convective cloud clusters during this heavy rainfall process.Within the cloud cluster group,meso-β scale deep convective cloud clusters formed and developed into multiple mesoscale rain bands.The cloud-top brightness temperature (TBB) of these deep convective clouds was below -52 ℃,with heavy precipitation generally occurring in regions of large TBB gradients near the cloud cluster peripheries.The interaction of unstable stratification,water vapor flux convergence,and slantwise updrafts further enhanced the intensification and maintenance of deep convective cloud clusters.Moreover,the centers of convective condensation latent heating and the convergence zones of the divergent component of Q vector showed good correspondence with heavy rainfall centers,which indicating that convective condensation latent heat release within and around the deep convective cloud clusters strengthened the upward motion,thereby affecting rainfall intensity.deep convective cloud clusters enhanced updraft intensity through convective condensation latent heating,thereby affecting precipitation intensity.

Daily respiratory disease consultation records and meteorological data from Wuhai City from 2016 to 2021 were analyzed to assess the influence of meteorological conditions on respiratory health.Spearman correlation analysis was used to identify temperature as a high-impact meteorological factor of respiratory diseases in the region.Generalized additive models (GAMs) and distributional lag nonlinear models (DLNMs) were employed to estimate the attributable fractions (AFs) of temperature to the number of consultation scores (AFs) and to identify vulnerable population groups.The results showed that both low and high temperatures had an immediate effect on respiratory disease visits,with low temperatures having a more dominant and prolonged impact.The peak AF range for the total population was -10 ~ 7 ℃,accounting for 50.2% of total AFs.Sudden temperature changes during seasonal transitions were significantly associated with increased respiratory disease visits,and the diurnal temperature range (DTR) of 8~16 ℃ had a significant immediate effect.Females were found to be more sensitive to temperature fluctuations.

Using ozone monitoring data and meteorological data in Hohhot city from 2018 to 2022,this study analyzes the O₃ concentration variation characteristics.Models with relating meteorological factors to predict daily maximum 8-h average O₃ concentration (ρ(O₃-8h)) were established using Light Gradient Boosting Machine (Light-GBM),Extreme Gradient Boosting (XGBoost),Random Forest (RF),and Long Short-Term Memory networks (LSTM).A comparison of model performance metrics was conducted to identify the optimal model,which was validated.The results showed that over the past five years,O₃ concentration in Hohhot City (ρ(O₃-8h) exceeded 160 μg·m^-3 from April to October,with the most exceedance days in June and July,followed by May and August.Among the model input factors,daily maximum temperature contributes the most to the prediction of (ρ(O₃-8h),accounting for 44%.The LightGBM model provided the best simulation results,with overall model performance ranking from highest to lowest as follows: LightGBM> LSTM> XGBoost> RF.The locally constructed ozone meteorological condition assessment index showed a correlation coefficient up to 0.86 with (ρ(O₃-8h),an improvement of 17.81% over the China Meteorological Administration's ozone meteorological condition assessment index.This demonstrates its effectiveness in assessing meteorological condition influences on O₃ concentration variations in Hohhot City.

Using daily meteorological station data from Hubei province,NCEP reanalysis data,and climate indices,this study analyzes the anomalous climate characteristics and their causes during the Meiyu season (May 31-July 8) and midsummer (July 9-August 31) in Hubei province in 2022.The results show that the onset of the Meiyu season was abnormally early with an extended duration in Hubei province in 2022.However,precipitation was unevenly distributed with unstable intensity and overall deficit in rainfall.After the Meiyu season,temperature was abnormally high,with heatwaves that were exceptionally persistent and intense,breaking historical records in the province's meteorological observation history.The early northward shift of the East Asian subtropical westerly jet and the Western Pacific subtropical high (WPSH),combined with adjustments in mid-latitude and high-latitude circulation systems,were the primary reasons for the significantly early onset of the Meiyu season despite poor moisture conditions in Hubei province.Under the combined influence of multiple external forcing signals,including the continuing development of a double-peak La Niña event and warm sea surface temperature anomalies in the Indian Ocean and equatorial Atlantic,jointly contributed to enhanced subsidence in the East Asian subtropical region via the Hadley circulation,resulting in significantly stronger high pressure in this area.During midsummer,the westward extension and intensification of the WPSH along with the abnormal eastward expansion of the South Asian high,caused Hubei province to remain under the prolonged influence of deep warm high-pressure system,leading to persistent,extreme,hot,and high-temperature weather.

This study comparatively analyzes PM_2.5 mass concentration and surface meteorological conditions between an urban site (Nanjiao Station) and a suburban site (Shangdianzi Station) during an aerosol pollution episode in Beijing from January 21 to 24,2022.The causes of this episode were investigated using vertical extinction coefficients,radiosonde meteorological data,and backward trajectories.Results show that the average PM_2.5 mass concentration at the urban station during the pollution period was 118.5 μg·m^-3,with significantly higher concentration levels and longer duration than that at the suburban station.Aerosol transport was observed above the urban station,with high aerosol extinction coefficient areas subsiding toward the surface,resulting in increased ground-level aerosol concentrations.The pollution episode began under southerly winds,transporting aerosol pollutants from southern Beijing toward Nanjiao Station.The pollution was exacerbated by a combination of meteorological conditions including decreased near-surface wind speed,increased relative humidity,and the formation and downward movement of temperature inversion layers.During the pollution episode,wind speeds at the urban station were notably lower than those at the suburban station,resulting in poorer dispersion conditions.Under relatively stable emission sources,variations in meteorological conditions during the pollution period served as good indicators of pollution.

Radiosonde data from October 2021 to September 2022 were used to evaluate the data quality of two types of ground-based microwave radiometers (MWRs),MWP967KV MWR at Xingtai station and QFW-6000A MWR at Tangshan station,in Hebei province.The analysis focused on temperature and humidity retrieval errors at different altitudes,seasons,day-night transitions,and precipitation conditions.The frequency and average intensity of temperature inversions were calculated,and the sensitivity of MWR temperature profile data was analyzed.The results show that the quality of MWR temperature and humidity data is significantly influenced by altitude,season,and diurnal factors,with notable differences between the two instrument types.Under non-precipitation conditions,temperature data quality at 4-8 km and relative humidity data quality at 1-4 km were relatively better; during precipitation,the data quality of both temperature and humidity deteriorated for both instruments.Both MWR types were insensitive to slight temperature changes and their temperature profiles unable to effectively reflect weak temperature inversions,suggesting the need for retrieval algorithm optimization to improve inversion detection performance.

This study utilizes grape yield data and corresponding meteorological data from Hebei province from 1981 to 2020.Based on the historical meteorological impact index of crop yield abundance,two methods-maximum probability method and weighted average method-were applied to develop grape yield forecasting models for dynamic yield prediction analysis.Model validation results show that the accuracy rates of yield abundance trend prediction were 77.8% and 84.4% for the maximum probability method and the weighted average method,respectively,while the quantitative forecasting accuracy rates were 83.1% and 90.3%,respectively.Model evaluation results indicated that during 15 yield abundance trend forecasts over 5 years,the maximum probability method had 5 errors,while the weighted average method had 3 errors,with quantitative forecasting accuracy rates of 89.9% and 94.0%,respectively.The weighted average method based on the historical meteorological impact index of crop yield abundance performed better in forecasting grape yield in Hebei province.

Daily meteorological data including average temperature,maximum temperature,minimum temperature,and sunshine hours in Liuzhou from October 2020 to November 2022,along with development period,grain-filling rate,and yield structure data of late rice (Yexiang Youlisi) from staggered sowing experiments conducted from 2020 to 2022,were analyzed to determine the effects of meteorological conditions on grain-filling rate and yield structure of late rice.Results showed that the grain-filling rate during 11-20 days after flowering was extremely significantly positively correlated (P<0.01) with average temperature,maximum temperature,and minimum temperature,and significantly positively correlated (P<0.05) with sunshine hours.The grain-filling rate during 21-30 days after flowering was only significantly positively correlated (P<0.05) with maximum temperature,while other meteorological factors did not reach significant correlation.By establishing regression equations between grain-filling rate and average temperature,maximum temperature,minimum temperature,and sunshine hours,the calculated agrometeorological service indicators for the grain-filling period of late rice in Guangxi indicated that the lower threshold values for 5-day average temperature,maximum temperature,and sunshine hours during the grain-filling period were 19.5 ℃,26.7 ℃,and 21.2 h,respectively; and the optimum values were 25.0 ℃,35.9 ℃,and 41.0 h,respectively.

Based on Sentinel-5p satellite imagery data, this study analyzes the spatial and temporal distribution of annual and monthly average NO₂ column concentration in Henan Province in 2022.The fast-decay inverse distance hotspot analysis method is applied to identify NO₂ hotspot areas. The results show that NO₂ column concentration in Henan Province exhibits high concentration in winter and spring but low in summer, with a U-shaped temporal symmetry. Spatially, NO₂ column concentration exhibit higher concentration in the northeast and lower in the southwest, with high values concentrated mainly in the urban districts of Anyang, Hebi, Xinxiang, and Zhengzhou along the Taihang Mountains. The fast-decay inverse distance hotspot analysis method effectively detects NO₂ hotspot areas across multiple scales, facilitating further investigation and verifying of NO₂ emission sources.