Beijing is the political, economic, cultural, and international exchange center of China, where major state events are fre-quently held in October. Cold waves and their associated weather conditions can significantly affect the meteorological support for these events, making it important to investigate their formation mechanisms. Based on ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and conventional meteorological observations, this study comparatively analyzes two re-gional cold wave events that occurred in Beijing during 16-18 October 2022 (cold wave I) and 18-20 October 2024 (cold wave II), with a focus on their circulation characteristics and formation mechanisms. The results show that both cold waves developed under the back-ground of relatively high temperatures in the preceding period. The cold wave I was mainly characterized by strong winds, whereas the cold wave II featured more intense cooling accompanied by strong winds and precipitation. The intensity of cold advection was not syn-chronized with the magnitude of temperature decrease, and under clear-sky and weak-wind conditions, diabatic processes contributed more significantly to the temperature drop. A strong surface cold high and the 3-h pressure tendency gradient were the key dynamic fac-tors responsible for the strong winds, while persistent subsidence in the boundary layer showed a positive correlation with both the in-tensity and duration of strong winds. These results provide scientific support for the forecasting and early warning of cold waves in Bei-jing during October and for meteorological services for major events.
From July 27 to August 2, 2023, an extreme heavy rainfall event occurred in North China (referred to as the “23·7” event), and significant discrepancies are found among different numerical weather prediction models. In this study, three global models and seven regional models are selected to systematically evaluate the forecast performance for this heavy rainfall event under complex terrain conditions, based on a categorical analysis of 3-hourly accumulated precipitation, combined with precipitation verification and surface wind field analysis. The results show that the global models perform relatively well in predicting precipitation of ≥0.1 mm and ≥1 mm, but with significant overforecasting, and exhibit obvious underprediction for precipitation of ≥10 mm. The regional models exhibit superior overall forecasting performance to global models, especially for precipitation of ≥10 mm, for which their forecasting skill is significantly higher. Model resolution is found to exert a considerable influence on the prediction of rainfall at different intensities. Better performance is achieved by high-resolution models compared with low-resolution models, particularly for precipitation of ≥5 mm, though exceptions do exist. With regard to the fitting of precipitation frequency distribution against precipitation intensity, regional models are demonstrated to be overall distinctly superior to global models. Analysis based on the Froude number (Fr) reveals the synergistic mechanism between terrain and wind fields. Overestimation of wind speed or underestimation of terrain height in models leads to the misrepresentation of flow-around as orographic updraft, inducing biases in the predicted precipitation location. In contrast, the characteristics of orographic lifting or flow around can be better preserved in regions with reasonable local Fr values.
The changes in snow cover on the Qinghai-Xizang Plateau have significant impacts on weather, climate, and hydrological processes. In the context of global warming, the climate change in the complex terrain area in the eastern part of the plateau shows altitude dependence, but the characteristics of snow cover changes with altitude on the plateau are still unclear. The spatio-temporal variation characteristics of snow cover frequency in the eastern Qinghai-Xizang Plateau from 2003 to 2021 and its main influencing factors were analyzed by using the daily cloud-free satellite remote sensing snow cover dataset and gridded meteorological data. The results indicate that: 1) High values of snow cover frequency are mainly located in the high-altitude mountainous areas in the southern of the study area. In the southern part of the eastern plateau in spring, the frequency of snow cover is higher than in winter, while in the inland, the frequency of snow cover is higher in winter than in spring. The frequency of snow cover generally increases first and then stabilizes with respect to altitude, reaching its peak at about 6 000 meters. Above 4 000 meters, it shows a bimodal pattern, with peaks occurring in November and from March to April; below 4 000 meters, it follows a unimodal pattern, with the peak in January. 2) Except for the significant decrease trend observed in autumn snow cover, the overall change trends of snow cover in spring, winter and the annual average are not significant. However, the snow cover in all periods in areas above 6 000 meters in altitude decreases significantly. 3) Snow cover is generally negatively correlated with temperature, being significantly in winter and spring. It is positively correlated with precipitation, with the strongest and most extensive correlations in winter. Significant positive correlations are also observed in autumn in the southern, inland, and the Qilian Mountain regions, and in spring in the southeastern and northeastern mid-to-high altitude areas. 4) Compared with past studies based on shorter time series of original MODIS snow cover data, the snow cover variation characteristics reflected by the long-term cloud-free dataset show distinct differences and greater reliability.
Evapotranspiration acts as an intermediate link in the terrestrial water and energy cycles while also serving as a crucial nexus connecting soil, vegetation, and atmospheric processes. Investigating changes in evapotranspiration holds significant scientific importance for the scientific management of water resources, addressing challenges posed by climate change, and ensuring regional eco-hydrological security. This study utilizes observational data from representative sites in the Yellow River Basin, namely the source region, the Hetao region, and the downstream region, which correspond to Haibei Station, the Semi-Arid Climate and Environment Observatory of Lanzhou University, and Yucheng Station. The purpose is to evaluate the performance of the 6th Phase of the Coupled Model Intercomparison Project (CMIP6) in simulating evapotranspiration across different regions of the Yellow River Basin. Based on this, the spatiotemporal variations of evapotranspiration across different regions of the Yellow River Basin under historical (1980-2014) and future (2026-2100) scenarios are analyzed using the multi-model ensemble mean results. The results show that the evapotranspiration derived from the CMIP6 multi-model ensemble mean exhibits good correlation and high Taylor skill scores in the source region, the Hetao region, and the downstream region of the Yellow River. Therefore, it is considered a suitable tool for investigating the spatiotemporal distribution of evapotranspiration. Furthermore, the annual evapotranspiration derived from the CMIP6 multi-model ensemble mean shows an increasing trend, with the highest change rate of 3.45 mm·(10 a)-1 identified in the source region of the Yellow River, while the increasing rates in the Hetao and downstream regions are relatively slower. Evapotranspiration shows increasing trends in spring and winter across the Yellow River Basin. However, the trends in summer and autumn exhibit spatial heterogeneity, with evapotranspiration rising in the source region but decreasing in the Hetao and downstream regions. Notably, the downstream region shows pronounced decreasing trends, with rates of 1.13 mm·(10 a)?1 and 0.73 mm·(10 a)?1 in summer and autumn, respectively. Under all future scenarios, evapotranspiration is projected to continue increasing throughout the 21st century in the source region, Hetao, and the downstream regions of the Yellow River Basin, peaking around the year 2100. As anthropogenic emissions increase, the rate of evapotranspiration increase is expected to accelerate further, with the most significant acceleration projected for the downstream region.
The source region of the Yellow River, located in the northeastern part of the Tibetan Plateau, is the largest runoff-producing area in the Yellow River Basin. Studying the future runoff variation characteristics in this region is of great significance for the rational allocation and efficient utilization of water resources in the Yellow River Basin. This study utilized observed monthly runoff data from the Tangnaihai Station during 1976-2018, gridded meteorological observation datasets, the Soil and Water Assessment Tool (SWAT) model, and four machine learning algorithm models to simulate and analyze historical runoff at Tangnaihai Station in the source region of the Yellow River. Through the evaluation of simulation results and comparison of the performance of different models, the Random Forest (RF) model was identified as the most suitable for runoff prediction in this region. Based on the RF model and meteorological data from six models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) under different emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), future runoff at Tangnaihai Station was projected and analyzed. The results show that the runoff at Tangnaihai Station in the source region of the Yellow River simulated by the SWAT model and RF model was in good agreement with the observations. The RF model achieved a coefficient of determination (R2) and Nash-Sutcliffe Efficiency (NSE) both above 0.83 during the training period, while the SWAT model achieved R2 and NSE values above 0.70 during both the calibration and validation periods. Moreover, the bias of these two models is relatively small compared with other models. Under future climate scenarios, annual precipitation in the source region of the Yellow River shows a gently fluctuating upward trend. The precipitation trend under the SSP1-2.6 scenario is relatively small, with an increase rate of 2.00 mm per decade, while under the SSP5-8.5 scenario, precipitation increases at a rate of 19.52 mm per decade, the fastest among the four emission scenarios. Under different emission scenarios, future runoff displays significant fluctuating variations. The multi-year average runoff under low emission scenarios (SSP1-2.6 and SSP2-4.5) is 673.49 m3·s-1 and 670.37 m3·s-1, representing increases of 3.37% and 2.90%, respectively, relative to the historical period. In contrast, under high emission scenarios (SSP3-7.0 and SSP5-8.5), the multi-year average runoff is 646.68 m3·s-1 and 623.08 m3·s-1, representing decreases of 0.74% and 4.36%, respectively, compared with the historical period.
To assess the vegetation ecological quality in the ecologically fragile region of the upper Yellow River and evaluate the effectiveness of national key ecological restoration projects, this study selected the Baiyin Section of the Yellow River Basin as the research area and delineated typical ecological functional areas, including the sandstorm control area, the irrigation area along the Yellow River, and cropland-to-forest area. Based on multi-source remote sensing data from 2000 to 2020, the vegetation ecological quality index (EQI) was constructed, and trend analysis and spatial statistical methods were employed to systematically reveal the spatiotemporal evolution characteristics and future variation trends of EQI. The results show that, during the past 21 years, the EQI of the study area exhibited a significant upward trend; the irrigation area along the Yellow River had the highest mean EQI (49.8), while the grain for green area showed the fastest growth rate (0.63 a?1), indicating that ecological projects played a key driving role in improving regional ecological quality. The EQI presented a gradient pattern of “high in the south and low in the north” accompanied by an “ecological island” phenomenon spatially; high-value areas were mainly distributed in the Yellow River irrigation area and mountainous forest regions such as Hasi Mountain and Tiaoshan Farm, whereas low-value areas were concentrated in the Jingtai-Jingyuan arid belt and the loess hilly region in the north, reflecting the combined influence of water conditions, topography, and human activities. Historical analysis indicates that 80.6% of the region experienced ecological improvement, and future projections suggest that 21.4% of the area may continue to recover, while ecological reversal risks remain in northern Pingchuan, northern Jingyuan, and southeastern Jingtai. The study demonstrates that national key ecological governance projects have achieved remarkable effectiveness in ecological protection and restoration in the Baiyin Section of the Yellow River Basin.
Accurately characterizing the spatiotemporal distribution of surface solar radiation is crucial for solar energy resource assessment and regional renewable energy planning. In this study, ground-based radiation observations in Gansu Province were used as the reference to bias-correct the hourly surface downward solar radiation from the fifth-generation ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis (ERA5) using a machine learning approach. Based on the corrected data, the spatiotemporal variability of surface downward solar radiation in Gansu Province during 2000-2024 was systematically analyzed, and annual cumulative radiation totals are quantified for each prefecture-level administrative region. The results demonstrate that the machine learning-based method significantly improves the accuracy of the ERA5. The correlation coefficient between the corrected data and ground observations increases by 12.04%, while the root mean square error decreases by 36.45%. Compared with the CARE (Cloud Remote Sensing, Atmospheric Radiation and Renewal Energy Application) satellite remote sensing product released by the Aerospace Information Research Institute, Chinese Academy of Sciences, the correlation coefficient between them reaches 0.87, and the remaining biases are mainly concentrated along the northeastern margin of the Tibetan Plateau. Over the study period, the provincial mean surface downward solar radiation is 206.73 W·m-2, corresponding to an annual cumulative total of 1 659.60 kWh·m-2, which is higher than the national average. Spatially, the radiation exhibits a distinct pattern of being higher in the northwest and lower in the southeast. The radiation in Jiuquan area reached 1 828.44 kWh·m-2, indicating excellent solar energy development potential. Moreover, no significant interannual fluctuation trend was observed across the province.
With the increasing frequency of warm-sector heavy rain events in North China, it is of great significance to study the occurrence and evolution mechanism of mesoscale convective systems during warm-sector heavy rain processes to improve the forecasting ability of warm-sector heavy rain. This research conducts a numerical simulation on the circulation background, thermodynamic structure, and moisture transportation characteristic of an extreme warm-sector rainstorm event in the Beijing-Tianjin-Hebei region using the high-resolution (3 km) WRF (Weather Research & Forecasting Model) mesoscale model, combined with the 0.25°×0.25° reanalysis data from the fifth generation global climate reanalysis dataset (ERA5) of the European Centre for Medium-Range Weather Forecasts, along with conventional and radar observation data for rapid assimilation updates. The results demonstrate that: (1) The high-resolution WRF model, which has been rapidly updated with assimilated observational data, can effectively simulate this warm-sector rainstorm process, accurately representing the radar echo characteristics and propagation mechanisms of meso-small scale systems, verifying the model’s capability to characterize key processes of warm-sector rainstorms. (2) The dynamic characteristics of this process are characterized by synergy of “three jet streams”: the 950 hPa ultra-low-level jet, the 850 hPa low-level jet, coupled with the strong divergence in the exit region on the right side of the 200 hPa upper-level jet, forming a vertical suction structure. The phased evolution characteristics of the low level (the establishment of the ultra-low-level jet, the fluctuation of the low-level jet intensity, the enhancement and maintenance of the low-level jet) are the key factors for the occurrence and maintenance of the heavy precipitation process. (3) Enhanced upward motion induced by low-level jet intensity fluctuation and convergence continuously lifts warm-moist airflow, promoting water vapor condensation and precipitation. Meanwhile, downward intrusion of mid-level weak dry air into high warm-moisture areas triggers the release of unstable energy, further intensifying the process. (4) The low-level high-humidity environment provides abundant water vapor conditions for the heavy rain. With the strengthening of the low-level southeast jet stream, water vapor from the Bohai Bay continuously flow into the Beijing-Tianjin-Hebei region. The strong accumulation of water vapor, combined with powerful dynamic conditions, is the main cause of local short-term heavy precipitation.
The formation and evolution of haze involve multi-scale atmospheric physical and chemical processes. “High humidity” is a typical pollution-related meteorological characteristic of the Sichuan Basin and an important influencing factor for haze development. Based on ERA5 reanalysis data from 2015 to 2018 and ground-based conventional environmental meteorological observations, this study systematically analyzed the evolution characteristics of water vapor and its relationship with atmospheric visibility during winter haze processes in the Sichuan Basin. The results show that: 1) The mean regional net water vapor budget during winter haze processes in the Sichuan Basin is (3.40±2.92)×106 kg·s-1, indicating an overall water vapor surplus; the western and southern boundaries are the main water vapor input pathways, the eastern boundary shows net output, and water vapor transport across the northern boundary exhibits uncertainty. 2) As the haze processes evolve from the formation to the development and persistence stages, the lower-tropospheric (below 700 hPa) water vapor content increases continuously, and the water-vapor high-value tongue extends northward with an expanding coverage. 3) The increase in lower-tropospheric water vapor facilitates the hygroscopic growth of near-surface aerosols, thereby increasing the mass extinction coefficient and consequently reducing atmospheric visibility.
The complex influence of snow cover on surface energy processes constitutes a critical source of uncertainty in wintertime numerical simulations over complex terrain and therefore warrants further investigation. Comparative simulation experiments were conducted for a snow-covered period (18-26 February) and a snow-free period (11-19 January) in 2014 over the Lanzhou New Area using the Weather Research and Forecasting (WRF) model version 4.3. Four land surface models (LSMs), SLAB, Pleim-Xiu, RUC, and NoahMP were systematically evaluated against observations from four meteorological towers to reveal the impact of snow cover on simulation accuracy and scheme sensitivity. Satisfactory performance was achieved during the snow-free period: correlation coefficients (R) of air temperature ranged from 0.80 to 0.97, with normalized centered root mean square errors (NCRMSE) of 0.27-0.60. The R of wind speed ranged from 0.46 to 0.82, and the absolute bias was generally below 0.5 m·s-1, successfully reproducing slope wind circulation. Conversely, simulation accuracy declined significantly during the snow-covered period. R of air temperature for half of the LSMs decreased below 0.80, cold biases exceeded 5.00 ℃, and NCRMSE increased to 0.38-0.79. Wind speed NCRMSE increased to 0.77-2.52, while wind direction frequency errors doubled. Taylor diagram analysis demonstrated that snow cover enhanced the sensitivity to LSMs, indicated by increased dispersion in normalized standard deviation among the schemes. NoahMP exhibited the superior performance with the lowest cold bias under snow-covered conditions (R≈0.9; NCRMSE<0.5), emphasizing the significance of accurate snow process representation for improving winter meteorological simulation in complex terrain.
From 25 to 29 November 2024, Heilongjiang Province experienced an extreme precipitation event associated with a northeast cold vortex (NECV), during which precipitation at multiple observation stations exceeded historical records. Using hourly observations from surface meteorological stations in Heilongjiang Province and ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), the evolution characteristics of the NECV and the formation mechanisms of sustained heavy precipitation were investigated. The results indicate that the cold-core structure of the NECV initially appeared in the mid-troposphere, extended downward during its development, and retreated to the mid-levels during the weakening stage. During the development and mature stages, subsidence dominated on the southern side of the vortex, while pronounced upward motion and deep moist layers were present on the northern and eastern sides. Throughout the heavy precipitation period, the precipitation center remained on the eastern side of the NECV. The southeasterly low-level jet and super low level jet acted as warm conveyor belts, continuously transporting moisture and heat to the precipitation area, and exhibited a pronounced diurnal variation, with jet intensification and downward extension of strong winds from early morning to afternoon, accompanied by significant vertical wind shear. Heavy precipitation showed a strong correspondence with the 925 hPa moisture convergence zone. The long-term maintenance of sustained moisture transport and convergence near Hegang was a necessary condition for the occurrence of extreme precipitation. In addition, terrain-induced convergence and uplift, together with the coupling of upper- and lower level jets, significantly enhanced low level ascent, leading to prolonged and extreme precipitation. Extreme precipitation mainly occurred on the windward slopes of the eastern foothills of the Xiaoxing’an Mountains.
To deepen the understanding of precipitation patterns in complex mountainous terrain, hourly precipitation data from three meteorological observation stations at different altitudes on the eastern side of the Fanjing Mountain in Guizhou Province in the flood season from May to October during 2022-2023 were used to analyze the diurnal variation characteristics of precipitation at the foot, mid-slope and summit stations. The results show that the amount and intensity of precipitation from night to morning increase with increasing altitude, while both decrease with increasing altitude from afternoon to evening. The periods with the large precipitation amount at stations on the foot and middle of the mountain occur from the late afternoon to evening, while at the summit station it concentrates from the early morning to morning. The precipitation at three stations mainly originates from rainfall events lasting from 2 to 18 hours. At the summit station, the precipitation amount during rainfall events lasting less than 8 hours is greater at night than during the day, while at the foot and mid-mountain stations, this characteristic is only observed in rainfall events lasting less than 3 hours.The peak period of precipitation shows a systematic delay with altitude increasing. From the night to the morning at the station at the foot of the mountain, then from the night to the noon at the station on the middle of the mountain, and finally transitioning from the noon to the early morning at the top station of the mountain, it exhibits a trend of “spreading from the morning to the noon and then to the early morning”. Short duration heavy precipitation (with precipitation amount greater than or equal to 25 mm) mostly occurs in the morning and has the highest frequency, while long duration precipitation has the highest proportion of precipitation amount.
To gain an in-depth understanding of the fine-scale characteristics of short-term heavy precipitation under Zhengzhou’s complex terrain, based on hourly precipitation data from national and regional stations from 2013 to 2022, conventional observation data, and high-precision geographic information data, this study systematically analyzes the multi-temporal scale variations and spatial distribution patterns of short-term heavy precipitation in Zhengzhou and quantitatively explores the relationships between precipitation intensity, frequency and topographic factors. Combining the case study of the extreme torrential rain event occurring in July 2021 (“21·7”) in Zhengzhou, the study reveals the thermodynamic mechanisms through which terrain triggers and enhances short-term heavy precipitation. The results indicate that the station-based frequency of short-term heavy precipitation in Zhengzhou shows a fluctuating increasing trend, July and August are the peak occurrence periods. The active period is between 14:00 and 20:00 (Beijing Time, the same as below), peaking from 18:00 to 20:00. The probability of daytime occurrence in mountainous areas is significantly higher than in plains. The short-term heavy precipitation events with rainfall intensity greater than or equal to 20 mm·h?¹ occur mostly in mountainous areas, whereas extreme events with rainfall intensity greater than or equal to 50 mm·h?¹ are more likely in the Zhengzhou main urban area and Xinmi City, reflecting a spatial distribution pattern where mountainous areas experience higher frequency but relatively lower intensity, while urban areas exhibit stronger extremity. Circulation classification shows that under weak synoptic-scale forcing backgrounds, the number of station occurring short-term heavy precipitation in mountainous areas is significantly greater than that in plain areas. Terrain’s influence on rainfall intensity distribution of short-term heavy precipitation is not significant, but it has a clear impact on its frequency. During the “21·7” torrential rain process, the triggering effect of the terrain convergence line and the mechanism of convective enhancement caused by the uplift on the windward slope and the thermal difference of the underlying surface are particularly prominent.
Based on hourly precipitation data from high-density regional automatic stations and national stations in Shaanxi Province during 2009-2023, the spatiotemporal characteristics of short-term heavy rainfall (hourly precipitation greater than or equal to 20.0 mm) in different regions of Shaanxi were comparatively analyzed to provide a scientific basis for refined forecasting and early warning of short-term heavy rainfall. The results show that: (1) The frequency and precipitation extremes of short-term heavy rainfall in Shaanxi generally increase from north to south, with the highest values occurring in southern Shaanxi, where the maximum hourly precipitation reaches 108.7 mm. (2) The normalized frequency of short-term heavy rainfall exhibits a significant increasing trend in the Guanzhong region; short-term heavy rainfall in all regions is mainly concentrated from June to August, with a peak in late July. From April to June and in September, short-term heavy rainfall in southern Shaanxi is significantly more frequent than that in Guanzhong and northern Shaanxi. Precipitation extremes in all three regions show increasing trends, and the occurrence time of peak extremes is progressively delayed from south to north. Precipitation intensity increases in Guanzhong and southern Shaanxi, with the maximum intensity in all regions occurring in early August. The variation characteristics of the normalized frequency of extreme short-term heavy rainfall are generally consistent with those of short-term heavy rainfall. (3) The diurnal variation of the normalized frequency of short-term heavy rainfall in all regions reaches its maximum at 19:00. Northern Shaanxi exhibits a bimodal pattern, with a primary peak during 14:00-23:00 and a secondary peak during 03:00-05:00. Guanzhong shows a unimodal pattern, with a high-frequency period from 16:00 to 01:00 of the following day. Southern Shaanxi displays pronounced nocturnal rainfall characteristics, with a high-frequency period from 16:00 to 04:00 of the following day, and short-term heavy rainfall during the late night mainly occurring in the central and western parts of the region. Compared with short-term heavy rainfall, the peak period of extreme short-term heavy rainfall is delayed by approximately 1 hour in Guanzhong and advanced by approximately 1 hour in southern Shaanxi.
Shaanxi Province is located in the northeast of the Tibetan Plateau, which is dominated by complex terrain of the Qinba Mountains, river valley and the Loess Plateau. Rainstorms are frequent and intense in Shaanxi, and often lead to floods and secondary disasters. Based on data of direct disaster reports from 2008 to 2023, this paper analyzes the spatial and temporal distribution of rainstorm floods and secondary disasters. Taking the disasters in the Qinba Mountains area as an example, this paper explores the triggering mechanism of heavy precipitation on extreme floods and secondary disasters. The results are as follows: (1) The frequency of rainstorm and flood disasters and their secondary disasters in Shaanxi Province decreases from south to north. Hanzhong and Ankang in the hinterland of the Qinba mountainous area are high-risk areas for disasters, followed by Shangluo in the eastern section of the Qinling Mountains and Yan’an in the Loess Plateau. (2) The heavy rainstorms and floods in Shaanxi Province occur mainly from July to August, and there are significant inter-annual variations, and 2013 was the year with the most frequent and severe disasters in recent years. (3) Intense and persistent heavy rain is the root cause of secondary disasters such as floods and mudslides in the Qinba mountainous area. The synoptic meteorological analysis of historical disasters indicates that the combined influence of the westward developing of the subtropical high in the middle troposphere and the eastward movement of the mid-latitude trough has continuously transported water vapor and heat to the Qinba mountainous area, and coupled with the high temperature, high humidity in the lower layer and the instability of convection, leading to the continuous occurrence of heavy rainstorms. The gap terrain of the east-west transition in the Qinba Mountains displays a significant role to increase the precipitation, forming a strong “rain pocket” in the center of rainstorm.The mountainous terrain causes surface runoff to converge rapidly, which promotes landslides and mudslides in Hanzhong and Ankang, as well as strong disasters of the damage of reservoirs and bridges and other secondary disasters.
Using conventional ground-based meteorological observations, the China Meteorological Administration (CMA) best-track dataset of tropical cyclones (TCs), the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEP/NCAR) reanalysis data, and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, statistical and composite analyses were conducted for tropical cyclone remote precipitation (TRP) events affecting Zhumadian during 2001-2023. The results show that TRP events in Zhumadian mainly occur from mid to late July and in August, and most of them are associated with the TC intensification or mature stages. According to the spatial distribution characteristics of TC center locations, the TRP events are classified into two types. Composite analyses indicate that the primary circulation systems influencing TRP in Zhumadian include the TC， subtropical high， and midlatitude westerly trough configuration, as well as upper- and lower-level jet streams. The background differences between the two TRP types are mainly reflected in the relative positions of the TC, subtropical high, and westerly trough, as well as in the moisture transport pathways. At 24 hours prior to TRP occurrence, both types exhibit a circulation pattern characterized by upper-level divergence and lower-level convergence, but the intensity is weaker than that at the time of TRP occurrence. Further analysis reveals that the relative positions of the key influencing systems and whether a remote TC can establish an effective moisture transport channel with the local region play a decisive role in the occurrence of TRP. Meanwhile, the vertical motion induced by the coupling of upper- and lower-level jet streams is the key dynamical factor controlling TRP intensity. Based on these results, forecasting approaches for the two types of TRP events in Zhumadian are summarized.
To investigate the formation mechanisms of heavy precipitation during landfalling typhoons, explore the application of high-resolution data in persistent heavy rainfalls, and analyze the synergistic effects of dynamic and thermodynamic factors, the observational characteristics and thermodynamic causes of the torrential rainstorm process that occurred in the Beijing-Tianjin-Hebei region from 29 July to 1 August 2023, were analyzed using ground meteorological station precipitation data, reanalysis data from the European Centre for Medium-Range Weather Forecasts, raindrop spectrum data, and dual-polarization radar data. The results are as follows: 1) The high-pressure dam formed by the subtropical high and the continental high-pressure ridge blocked the residual circulation of the Typhoon Doksuri, and the east-high-west-low circulation configuration provided a stable circulation background for the torrential rain. 2) Raindrop spectrum analysis revealed precipitation dominated by small raindrops with high number concentrations. The normalized number concentration increased with rain intensity, indicating that the torrential rainfall was primarily driven by high particle concentration, presenting typical tropical precipitation characteristics. 3) Frontogenesis, driven by shear deformation and horizontal divergence, triggered secondary frontal circulation, generating intense vertical motions that prolonged rainfall duration. 4) Latent heat release enhanced upward motion and moisture convergence through positive feedback, synergizing with frontogenesis to sustain the rainstorm. The relationship among the three indicates that the microphysical characteristics of small raindrops with high number concentration are regulated by the warm cloud collision-coalescence and breakup, and the frontogenesis effect provides the conditions for dynamic uplift, while the release of latent heat of condensation further strengthens the dynamic circulation by heating the atmosphere, thus forming a “microphysics-dynamics-thermodynamics” coupled mechanism for rainstorm intensification.
The plateau vortex is one of the important weather systems causing heavy rainfall and short-duration intense precipitation in Qinghai Province. Based on the plateau vortex dataset, precipitation observation data of meteorological stations in Qinghai, and the ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) from 1979 to 2021, this study investigates the proportion of plateau vortex days, plateau vortex precipitation, and environmental field characteristics over Qinghai by using the plateau vortex precipitation correlation method and dynamic composite analysis method. The results show that the spatial distribution of the proportion of plateau vortex days in Qinghai increases from northeast to southwest, with an annual maximum of 15.37%. The annual maximum proportion of plateau vortex precipitation to total precipitation reaches 37.92%. The annual maximum proportion of plateau vortex extreme precipitation days to the total extreme precipitation days is observed in southwestern Qinghai (63.69%). Meanwhile, the annual maximum proportion of plateau vortex extreme precipitation days to plateau vortex days occurs in the region from eastern Haixi Prefecture to southern Hainan Prefecture (10.73%). Although the number of plateau vortex days is relatively small in these areas, such systems often induce intense precipitation. The larger proportion of plateau vortex days over Qinghai is mainly concentrated in the period from April to October, and the eastward movement of plateau vortices exerts a more significant impact on precipitation. The frequency of heavy rain dynamically composited relative to the plateau vortex center shows an asymmetric distribution (wider in the zonal direction and narrower in the meridional direction). Heavy rain occurrences are predominantly concentrated in the northeastern and southeastern quadrants, with the maximum frequency occurring within a distance of 0.50-1.25 latitude degrees from the vortex center.
To gain an in-depth understanding of the circulation characteristics, formation mechanisms, and transport features of strong wind-dust weather processes, this paper employs conventional meteorological observation data and ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Combined with simulations from the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model, as well as observational data from aerosol lidar, and wind profiler radar observations, a comparative analysis is conducted on two severe dust events that occurred in the Hexi Corridor during the spring of 2023 (the 20 March event and the 18 April event). The results are as follows: (1) The 20 March event followed a westerly pathway, triggered by the southward movement of split cold air behind a Mongolian cyclone; the 18 April event took a northwesterly route, driven by a Mongolian cyclone and an associated cold front moving southward. (2) Both events involved long?range transport of pollutants. In the 20 March event, particulate matter transported externally played a dominant role, whereas in the 18 April event, dust particles generated locally constituted the primary dust source. (3) During the early stage of external dust input, the 18 April event exhibited faster long-range transport of dust particles, a significantly lower proportion of coarse particles, and a lower depolarization ratio compared with the 20 March event. However, during the outbreak phase, the near-surface replenishment of dust particles was more pronounced in the 18 April event.
Investigating the response routine of saltwater intrusion-drought compound risk to climate change provides a scientific basis for safeguarding regional water supply security. This study focuses on the Modaomen waterway in the Pearl River Estuary. Utilizing daily drought data from the Guangdong section of the Xijiang River Basin and salinity monitoring data from the Guangchang Pumping Station in the Modaomen Estuary, this study applies a compound risk assessment model to calculate, evaluate, and project the saltwater intrusion-drought compound risk index for Modaomen. The results show that the chloride concentration in the Modamen waterway of the Pearl Rver Estuary has a significant nonlinear negative correlation with the 8-day antecedent average drought index in the Guangdong section of the Xijiang River Basin. When the drought index is less than or equal to -0.69, the threshold condition for saltwater intrusion is met.The saltwater intrusion-drought compound events risk index in Modaomen is higher from November to March of the following year, with the peak risk occurring from mid-December to late January of the next year. Under the future medium emission scenario (SSP2-4.5), the saltwater intrusion-drought compound events risk index shows a marked increasing trend in autumn, most notably in November, followed by spring. From 1970 to 2099, the saltwater intrusion-drought compound events risk index in Modaomen of the Pearl River Estuary generally shows a fluctuating upward trend. Compared with the recent 20-year period (2001-2020), the risk index will increase by 1.9%, 8.4%, and 9.6% in the near-term (2021-2040), mid-term (2041-2060), and late-21st-century (2080-2099), respectively. The start dates of saltwater intrusion-drought compound events will advance by more than 10 days, and the end dates will delay by more than 9 days in different future periods. Under future climate change scenarios, the duration of compound saltwater intrusion and drought events in the Pearl River Estuary will lengthen, the cross-seasonal risk will show an increasing trend, and the probability of such events occurring consecutively in autumn, winter, and spring will rise significantly.
To reveal the response characteristics of different underlying surfaces to climate change in the Taklamakan Desert, this paper adopts linear trend analysis, the Mann-Kendall test, and correlation analysis to comparatively investigate the meridional variation characteristics of surface meteorological elements in this region over the past 30 years, based on the meteorological observation data from three stations located in the northern margin (Luntai), hinterland (Tazhong), and southern margin (Minfeng) of the desert during 1997-2024. The results are as follows: (1) Significant regional differences exist in the interannual variations of all meteorological elements. Temperatures in Luntai and Tazhong first decreased and then increased, while Minfeng experienced continuous warming, with Tazhong showing the fastest rate of increase. Precipitation significantly decreased in Luntai, slightly increased in Tazhong, and first increased and then decreased in Minfeng. Wind speeds significantly increased in Luntai, while Tazhong and Minfeng exhibited phased turning points. Sunshine duration significantly decreased only in Minfeng, and slightly increased at the other two stations. Relative humidity slightly increased in Luntai and Tazhong, while slightly decreasing in Minfeng. (2) Seasonal variations exhibited distinct regional patterns: Luntai showed pronounced autumn warming, significant wind speed increases in four seasons, and relative humidity increases in spring; Tazhong exhibited marked summer warming, substantial spring-summer wind speed fluctuations, and summer-autumn relative humidity increases; Minfeng demonstrated significant spring warming, pronounced sunshine duration decreases in four seasons, and autumn-winter relative humidity decreases. Precipitation at all three stations concentrated in summer, with Tazhong exhibiting the highest proportion (approximately 64%) of summer precipitation. (3) The correlations among various meteorological elements also exhibited regional differences: temperature and relative humidity showed a negative correlation at all three stations, while relative humidity and precipitation presented a positive correlation; temperature and precipitation were positively correlated at Luntai and Minfeng Stations but negatively correlated (-0.33) at Tazhong Station; temperature and wind speed showed a negative correlation at Luntai Station, a positive correlation at Tazhong Station, and nearly no correlation at Minfeng Station; temperature and sunshine duration were positively correlated at Luntai Station but negatively correlated at both Tazhong and Minfeng Stations. These differences highlight the complexity of climate change over different underlying surfaces in arid regions.
The macro- and micro-structural characteristics of rainstorm cloud clusters exhibit pronounced variations under different geographical environments and synoptic circulation conditions. The Inner Mongolia section of the Yellow River Basin is a semi-arid region characterized by complex topography and highly transient, intense rainstorms. Utilizing Precipitation Measurement Radar (PMR) data from the Fengyun-3G (FY-3G) satellite, combined with ERA5 (ECMWF Reanalysis version 5) reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), this study conducts a comprehensive analysis of the three-dimensional structure of cloud clusters and their circulation background during the rainstorm event on August 8 2024 over the Yellow River Basin in Inner Mongolia. The results indicate that the rainstorm occurred under the combined influence of a strong subtropical high and a westerly trough, with the 700 hPa low-level jet, pronounced vertical wind shear, and strong ascending motion of warm and moist air providing favorable dynamic conditions for rainfall formation. Both stratiform and convective cloud clusters coexisted in the precipitation system. The convective clouds exhibited higher average particle number concentration, effective particle diameter, and precipitation rate compared with stratiform clouds, and the vertical distributions of particle number concentration and effective diameter corresponded well with the unstable energy field. Enhanced reflectivity zones were observed above and below the 0 ℃ layer, and the latent heat release of convective clouds at approximately 5 km altitude was about twice that of stratiform clouds, indicating that convective cloud clusters were the primary contributors to this extreme rainstorm and played a decisive role in precipitation efficiency and intensity. The cloud-top height of the precipitation system increased gradually from west to east, and the horizontal distributions of cloud-top height and 0 ℃ level height in the extreme rainfall region were closely related to topographic variations.
Typhoon Doksuri (No.2305) caused an extremely rare torrential rainfall over Putian City, Fujian Province. Based on multi-source observational data, including surface meteorological observational data of Fujian Province, radar and satellite data, as well as reanalysis data from ECMWF (European Centre for Medium-Range Weather Forecasts), the stages and intensity characteristics of the extreme rainfall induced by Typhoon Doksuri were analyzed. The main conclusions are as follows: The entire rainfall process was consisted of three seamlessly-linked stages. The first stage was the typhoon eyewall rainstorm, which had the characteristics of intense short-term rainfall and uniform spatial distribution. The second stage was the spiral rainband rainstorm, which was characterized by significant differences in hourly rainfall intensity and distinct rain peaks. The third stage was the monsoon-enhanced rainstorm, with the characteristics of a wide range of heavy rain and a long duration. The heavy rain in Putian caused by Typhoon Doksuri exhibits remarkable extremeness, with specific manifestations as follows: extremely intense heavy rainfall, a wide impact range of extremely heavy rainfall, large cumulative rainfall, high frequency of short-term heavy precipitation, and long duration. Among these, the 24-hour rainfall at Putian Station reached 561.7 mm, breaking the historical record of Fujian Province, and its extreme characteristics are particularly prominent. The continuous maintenance of typhoon warm shear line, low-level southerly jet and monsoon system is an important weather background for the three stages of rainstorm to achieve “seamless connection”. The uplift and contraction of the southerly jet caused by the terrain of Xinghua Plain “surrounded by mountains on three sides and opening to the south” is an important factor for the rainstorm center to be located in the Xinghua Plain to the northeast mountainous area.
Aiming at a significant heavy rainfall event that occurred in Inner Mongolia in July 2021, the paper conducfed a set of convection-allowing ensemble prediction (CAEP) experiments to evaluate its forecasting capability for intense precipitation processes, and compared the results with the global ensemble forecasts from the European Center for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environmental Prediction Global Ensemble Forecast System (NCEP-GEFS), and the China Meteorological Administration Regional Ensemble Prediction System (CMA-REPS). The results show that the ensemble mean of global ensemble forecasts tended to underestimate the intensity of heavy precipitation centers, although ECMWF provided relatively accurate predictions of their locations. Both CMA-REPS and CAEP precipitation intensities forecasts close to observations but with some positional deviations, whereas NCEP-GEFS performed poorly in forecasting both the location and intensity of heavy rainfall. The Probability Matching Ensemble Mean (PM) effectively improved the simulated precipitation intensity compared with the traditional ensemble mean, leading to a notable increase in the threat score (TS), particularly for ECMWF and CAEP. The CAEP outperformed both global and regional ensemble forecasts in predicting the magnitude and temporal evolution of single-station precipitation. Objective verification indicated that ECMWF, CMA-REPS, and CAEP ensemble members exhibited certain forecasting capability for 25 mm·(6 h)-1 precipitation, while NCEP-GEFS performed poorly. For 60 mm·(6 h)-1 precipitation, CAEP achieved the highest TS, the lowest Brier score, and the highest AROC score among the ensemble systems, demonstrating its superior capability in forecasting heavy rainfall over the Inner Mongolia region.
The Tongchang Reservoir in southern Xinjiang is a medium-sized river-blocking reservoir in the Kuche River Basin, where heavy rainfall is the primary factor contributing to reservoir-induced floods. Studying the quantitative meteorological and hydrological indicators of the reservoir is of great significance for the flood warning and prediction of the reservoir. Based on hourly precipitation data from 19 automatic weather stations in the Kuche River Basin, the three-source integrated precipitation product (China Meteorological Administration Multi-source Merged Precipitation Analysis System, CMPAS), as well as the inflow volume and water level of the reservoir, nine flood events caused by heavy rainfalls in the reservoir were selected and classified into circulation types, and the meteorological and hydrological characteristics of two typical rain and flood events in the reservoir were analyzed. The results are as follows: (1) The circulation patterns of the rain-flood processes in the reservoir can be classified into two types: low vortex (trough)-shear line type (the type I) and low vortex (trough)-cyclone type (the type II). (2) The intensity of precipitation, the rainfall area, and the duration all determine the rate of water level rise in the reservoir. The type I process is characterized by short-term heavy precipitation and rapid water level rise, while the type II process is characterized by long-duration weak precipitation and slow water level rise. The water level rise speed during the type I process is faster than that during the type II process. (3) The increase in the inflow into the reservoir is related to the magnitude of the hourly areal rainfall. When the hourly areal rainfall is less than 0.5 mm, the variation range of the inflow into the reservoir is not significant, while the hourly areal rainfall is greater than 2.0 mm, the inflow into the reservoir increases significantly. (4) The water level rise of the reservoir has a lagging response to the meteorological conditions. For the type I process，the start time of water level rise and the occurrence time of the peak inflow of the reservoir are 3-4 hours behind the start time of precipitation, and the occurrence time of the highest water level in the reservoir is 4 to 5 hours later than the starting time of precipitation, and 1 to 2 hours later than the peak inflow flood into the reservoir. The start time of the flood rise during the type II process, the peak inflow, and the time when the highest water level occurs are all later than those during the type I process to varying degrees.
A comprehensive understanding of the spatio-temporal characteristics of extreme precipitation and exploring its key influencing factors can help better defend against the adverse effects of extreme precipitation. Based on the standardized daily precipitation data from 58 national meteorological stations in Gansu Province from 1961 to 2022, the spatio-temporal characteristics of extreme precipitation in Gansu Province were analyzed by using 12 extreme precipitation indices, and the contribution rate of large-scale climate factors to extreme precipitation was quantified using the Geodetector. The results are as follows: 1) In the past 62 years, the consecutive dry days (CDD) and consecutive wet days (CWD) in Gansu Province showed a decreasing trend, while the other indices representing intensity and frequency of extreme precipitation showed mainly insignificant increases. The frequency of extreme precipitation events had the highest increasing rate of 2.38 times·(10 a)-1. The extreme precipitation presented a significant increasing and intensifying trend, with an abrupt change detected around 2010 in the Hexi region. The extreme precipitation events in Gansu Province occurs from March to November, especially in July and August. The months with an increasing and strengthening trend of extreme precipitation are predominant, and in June the rate of increase is the maximum. 2) The stations where the extreme precipitation indices showed an increasing trend are mainly located in the most of Hexi region and Lanzhou, the central and northern parts of Baiyin, Linxia, the southeastern part of Longdong region, and the southern part of Longnan. 3) The Indian Ocean Basin-Wide Index and Nino Eastern Pacific index contribute the most to extreme precipitations in the Hexi region (29%) and the Hedong region (33%), respectively. The warming of sea surface temperature in the tropical Indian Ocean is conducive to an increase and intensification of extreme precipitation in the Hexi region, while the Eastern Pacific El Niño event is unfavorable for the occurrence and development of extreme precipitation in the Hedong region. Moreover, the contribution rate of two-factor interaction to extreme precipitation is significantly greater than that of single-factor action.
The synoptic classification of short-duration heavy rainfall (SDHR) circulation patterns is of great significance for improving forecasting and early warning capabilities, as well as enhancing meteorological disaster prevention and mitigation. Based on hourly precipitation data from May to September during 2005-2022 and ERA5 reanalysis data, this study employs the obliquely rotated T-mode principal component analysis to investigate the circulation patterns, precipitation characteristics, and environmental parameter differences associated with SDHR events in the Shaying River Basin. The results indicate that SDHR events during the warm season can be categorized into five circulation types: the pre-trough southwesterly flow pattern, the southwesterly flow pattern on the periphery of the subtropical high (STH), the northwesterly flow pattern, the low vortex shear pattern, and the typhoon low pressure pattern. Among them, the pre-trough southwesterly flow pattern occurs most frequently, while the typhoon low pressure pattern is the least. In terms of precipitation intensity, the pre-trough southwesterly flow pattern shows a relatively uniform distribution; the southwesterly flow pattern on the periphery of the STH exhibits strong local characteristics; the northwesterly flow pattern produces stronger precipitation in the southwest; the low vortex shear pattern features higher intensity in the northern and central parts; and the typhoon low pressure pattern shows maxima mainly in the western and northern high-altitude areas. Regarding precipitation probability, the low vortex shear pattern exhibits higher probabilities in mountainous areas and northern regions, whereas the other four types display opposite spatial tendencies. On the monthly scale, the pre-trough southwesterly flow pattern dominates in May, the northwesterly flow pattern prevails in June, both the pre-trough southwesterly flow pattern and low vortex shear pattern are dominant in July, the northwesterly flow pattern becomes most prominent in August, and both the southwesterly flow pattern on the periphery of the STH and pre-trough southwesterly flow pattern are predominant in September. The diurnal variations reveal that the pre-trough southwesterly flow pattern, the southwesterly flow pattern on the periphery of the STH, and the low vortex shear pattern exhibit bimodal structures with differences in peak frequency and duration; the northwesterly flow pattern shows a single afternoon peak, while the typhoon low pressure pattern has no obvious diurnal variation. Analysis of individual physical parameter indicates that the southwesterly flow pattern on the periphery of the STH and the typhoon low pressure pattern are characterized by abundant water vapor; both the southwesterly flow pattern on the periphery of the STH and the northwesterly flow pattern feature significant thermal instability, manifested as high convective available potential energy (CAPE) and a large 850-500 hPa temperature difference; the low vortex shear pattern and the typhoon low pressure pattern exhibit strong low-level convergence and upward motion; and all five circulation types are associated with weak vertical wind shear. Joint probability density analysis of environmental parameters further reveals that different SDHR types tend to develop under distinct combinations of thermodynamic and dynamic conditions, corresponding to different precipitation formation mechanisms.
Convective cloud systems, characterized by complex and variable structures, are key targets for atmospheric water resource exploitation through artificial rain enhancement in the South China. Reasonably evaluating the seeding operation process through numerical models and further studying their catalytic mechanisms is a necessary approach to establishing and improving seeding operation techniques, and it is also an effective means to assess the actual effects of artificial rain enhancement operations. In this study, based on the Weather Research and Forecasting (WRF) model coupled with a silver iodide (AgI) seeding module, a catalytic simulation was conducted for the case of the artificial rainfall enhancement experiment in Gutian, Fujian Province on May 4, 2021. The catalytic mechanism of AgI nucleation, the impact of the catalysis on the macro and micro characteristics of the cloud system, the precipitation mechanism, and the evaluation of the rainfall enhancement effect were analyzed. Numerical simulation results indicate that the dispersed AgI particles spread in a band-like patterns within the clouds. During the initial catalytic stage (09:00-11:00 UTC), the increment of ground precipitation increased slowly. Then (from 11:00 to 13:00 UTC), the precipitation increment increased significantly and showed sharp fluctuations, after 13:00 UTC, the increment of precipitation was mainly negative. Deposition nucleation was identified as the dominant AgI activation mechanism, sustaining effective catalysis for approximately 40 minutes. After AgI was dispersed, it mainly increased the number concentration of ice crystals through sublimation nucleation (by 3 to 9 particles per liter). The majority of the increased ice crystals transformed into snow crystals, and then the melting of these snow crystals increased the mass concentration of raindrops in the cloud. The impact of seeding persisted for about four hours, resulting in an absolute increase in precipitation ranging from -0.78 to 1.24 mm, the rainfall enhancement rate was approximately -8.3% to 12.1%, and the total precipitation increase was 4.64×105 tons. The rainfall enhancement effect was significant.
Lodging is a major meteorological disaster that significantly affects the yield of summer maize. Investigating the impact of lodging during the milk stage on water use efficiency (WUE) and yield is crucial for accurately assessing lodging-induced losses and guiding summer maize production. Based on crop, meteorological, disaster survey, and CO2/H2O flux data collected at the Zhengzhou Agro-meteorological Experimental Station during the 2016-2017 growing seasons, this study constructed models of net ecosystem productivity (NEP) and evapotranspiration (ET) to simulate the population-level WUE. A wind-induced lodging event that occurred in Zhengzhou on August 25, 2016 was analyzed using the model validated by 2017 observations. The results show that under normal conditions, the simulated WUE values agreed well with flux observations, with a mean absolute error of -0.08 mg C·g-1 H2O and a relative error of -5.39%. After lodging, the simulated WUE values were markedly lower than those under non-lodging conditions, with a daily average decrease of 0.31 mg C·g-1 H2O, corresponding to a reduction of 20.37%. At the yield level, WUE decreased by 3.87%. Both NEP and ET declined following lodging, with a larger reduction in NEP than in ET, leading to a decrease in WUE. Lodging also reduced the hundred-grain weight by 2.8% and the grain weight per plant by 10.8%, resulting in an overall yield reduction of approximately 5.0%.
Under climate warming, asymmetric day-night temperature increases and atmospheric CO2 concentration rising are two key features altering the distribution of water and heat resources, driving changes in the planting structure and boundaries of the three major grain crops (wheat, corn, and rice). Studying their responses to global warming is vital for food security. Using high-density meteorological station data, the paper analyzes thermal resource changes before and after 1990 during a 30-year period and their possible impacts on the potential planting areas of China’s three major grain crops using statistical method. In addition, the results from multi-site “Free-air temperature increase (FATI) under field conditions” and “Open-top chamber (OTC) experiments with controlled temperature and CO2” are summarized, and combined with the literature meta-analysis method to explore the effects of climate warming on the growth periods and yields of the three major crops. Results are as follows: 1) Agricultural thermal resources in China are generally increasing, with the duration of the farming period and accumulated temperature significantly rising, and the frost-free period extending. The number of extreme hot days has generally increased, and in some regions (such as Shaanxi, Gansu and Ningxia), the number of extreme cold days during the farming period has also increased, intensifying the risk of extreme meteorological disasters. 2) The northern boundaries of the three major crop-growing areas have shifted northward to varying degrees, resulting in an increase in the potential suitable planting area. 3) In the early stage of climate warming, it is beneficial for winter wheat to grow. However, excessive warming will lead to earlier development, increased frost risk, shorter growth period and reduced yield for spring wheat. Although an increase in CO2has a yield-enhancing effect, it is difficult to offset the adverse impacts induced by high temperatures. 4) Climate warming shortens the growth period of corn, reduces the number of grains per ear and the weight of 1 000 grains, thereby inhibiting the formation of yield. Nighttime warming further exacerbates the decline in yield. The effect of increasing CO2 concentration on corn growth and yield is limited, with warming being the dominant factor. 5) Warming alone has an inhibitory effect on the yield of early rice but a promoting effect on that of late rice. Warming for early rice reduces the yield-increasing effect of CO2, while for late rice it shows a synergistic promotion and increasing the yield.
This paper took winter wheat in the Huang-Huai-Hai region as the research object, where agricultural droughts occur frequently with warming climate and increasing evaporation, and defined the water shortage index (k) to classify drought year types based on the data from 1981 to 2020. Taking three stations in Henan Province as examples, this paper used the World Food Studies (WOFOST) model to analyze the cost-benefit of drought resistance under different drought year types, in order to provide a reference for improving agricultural output value and agricultural insurance business. The results show that during the study period, the three stations were easy to experience water stress with varying degrees during the growth period of winter wheat, and the drought that occurred in the middle to late stages of the growing season (from early April to harvest) had the greatest impact on yield formation. In order to ensure the safety of national food, agricultural irrigation in the study areas is the main way to keep high yields of winter wheat. According to the cost-benefit analysis, the northern region of Henan Province needs to irrigate 5 times in severe drought years, and irrigate 4 times in general drought years to achieve the maximum benefit. The water conditions in eastern Henan are relatively better than others, with a low probability of severe drought and 3 times irrigation should be needed in general drought years.
To reveal the influence mechanisms of weather patterns and meteorological factors on air pollution in arid and semi-arid regions, this study utilized the fifth-generation atmospheric reanalysis dataset (ERA5) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) from 2016 to 2022. The Self-Organizing Map (SOM) neural network was employed to classify weather patterns based on the 700 hPa geopotential height field and wind field, combined with quadratic curve fitting to analyze the nonlinear relationships between meteorological factors and pollutants in typical cities across different climatic zones of Gansu Province. The results indicate that: 1) PM10 and PM2.5 mass concentrations generally exhibit a negative correlation with temperature, while for O3 its mass concentration increases nonlinearly with rising temperature. Under low wind speeds (<1 m·s-1) and high wind speeds (>4 m·s-1), PM10 and PM2.5 mass concentrations are elevated, which attributed to local accumulation under calm conditions and dust transport under strong winds, respectively. In contrast, wind speeds between 1 and 4 m·s-1 favor precursor accumulation, leading to higher mass concentration of O3. Pollutant concentrations are generally higher under relative humidity between 25% and 75%, though regional differences exist. For instance, in Jiuquan, the PM10 concentration is higher at humidity below 25% due to frequent dust events, the PM2.5 concentration increases with the rise of relative humidity due to the hygroscopic growth effect, while O3 concentration decreases with declining humidity owing to reduced consumption under dry conditions. 2) In winter and spring, the dominant weather patterns are the southwestern high-pressure type and the eastern trough type. Under the southwestern high-pressure pattern, strong northwesterly winds in western regions create pollutant transport pathways, whereas the eastern trough pattern results in poor diffusion conditions and stable atmospheric conditions in Gansu, facilitating pollutant accumulation and significantly increasing of PM10 and PM2.5 concentrations. 3) In summer and autumn, high-pressure systems dominate, with abundant solar radiation and high temperatures elevating the boundary layer height. Coupled with warm, moist air transport, these conditions provide a favorable environment for photochemical reactions, leading to higher O3 concentrations.
Based on the hourly precipitation analysis data of the China Meteorological Administration multi-source merged precipitation analysis system (CMPAS) and the hourly precipitation data predicted by the China Meteorological Administration mesoscale weather forecast system (CMA-MESO)， the distribution characteristics of precipitation in the Beijing-Tianjin-Hebei region under special topographic conditions from June to September 2021 were analyzed, and the prediction performance of CMA-MESO was discussed. The results are as follows: (1) The observational maximum centers of mean hourly precipitation in the Beijing-Tianjin-Hebei region were primarily located in 100-600 m altitude on the windward slopes of the eastern Taihang Mountains and the southern foothills of the Yanshan Mountains, while the maximum centers predicted by the CMA-MESO were located on the side of the windward slope leaning towards the plain in front of the mountains. The observational hourly precipitation frequency and intensity were similar to precipitation amount, but the maximum center of hourly precipitation frequency was located on the windward slopes of the Taihang Mountains, leaning towards the mountainous side, while the maximum center of precipitation intensity was mainly distributed on the windward slopes in front of the mountains and the plain areas of the eastern Beijing-Tianjin-Hebei region. (2) The observational regional average hourly precipitation amount on the windward slopes in front of mountains of the Beijing-Tianjin-Hebei region exhibited a bimodal diurnal pattern, with the primary peak occurring from afternoon to evening and the secondary peak in the early morning. The primary peak predicted by the CMA-MESO was colse to observations, but the regional average hourly precipitation amount was significantly overestimated. (3) On the windward slopes in front of the mountains, the peak period of precipitation above 10 mm·h-1 occurred from the afternoon to the early morning and the early hours of the next day. The CMA-MESO forecast indicated that the precipitation above 10 mm·h-1 in the afternoon to evening period was slightly higher, while the precipitation in the early hours of the next day was slightly lower. (4) Precipitation events on the windward slopes from afternoon to early nighttime were mainly short-term precipitation events within 3 hours. The CMA-MESO taked the characteristic, but the amount of short-term precipitation events predicted by it was relatively high. (5) The CMA-MESO successfully forecasted the topographic enhancement of precipitation on the windward side of the mountains. However, the specific humidity below 850 hPa was underestimated, and the convective available potential energy value at 14:00 (Beijing Time) was significantly underestimated. These biases contributed to the existence of a negative precipitation bias center over the windward slopes.
Low-temperature spring flooding over Northeast China refers to a meteorological phenomenon characterized by persistently low temperatures and excessive precipitation in spring, primarily from March to April, which severely hinders spring agricultural operations, particularly plowing and sowing. In this paper, based on monthly temperature and precipitation data of 104 national meteorological stations in Northeast China during 1961-2020, and the monthly reanalysis data of the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), combined with the sea surface temperature and the atmospheric circulation indices with significant correlation, a case study is carried out. The low-temperature spring flooding events and their judgment indexes are defined, and the multi-factor synergy of temperature, precipitation and other factors at the cross-seasonal scale, as well as the influence mechanism of atmospheric circulation and sea surface temperature anomalies in the same period and in the early stage are preliminarily revealed. The results show that persistent cold and rainy conditions in spring are key contributors to the occurrence of such events, and the abnormal increase of accumulated precipitation in autumn in the previous year is the key factor resulting in severe low temperature and spring flood events. In addition, the negative phase of the Arctic Oscillation (AO) in the preceding winter, the stronger-than-normal Siberian High in spring, and the active Northeast China cold vortex and cold waves are important dynamical conditions. Furthermore, abnormal warming of sea surface temperatures, especially associated with El Niño events in the previous autumn and winter, is in favor of the occurrence of low-temperature spring flooding. These events are often followed by alternating drought and flood conditions in Northeast China, typically manifesting as a “drought-flood-drought” pattern during late spring to early summer, midsummer, and winter, respectively.
The variation trend and potential causes of short-term heavy rainfall (STHR) in Jiangxi Province were studied to enhance the forecasting and early-warning capabilities about extreme precipitation events, particularly for STHR. Baud on hourly precipitation data from 84 national meteorological stations in Jiangxi Province during 1979-2019 and ERA5 atmospheric reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), anomaly normalization, linear tendency estimation, the Mann-Kendall test, and correlation analysis were employed to investigate the variation trend of STHR in Jiangxi Province and its potential influencing factors. The results are as follows: (1) STHR in Jiangxi Province exhibits distinct seasonal characteristics. From April to September, the frequency and proportion of such events account for 95.7% and 92.4% of the annual totals, respectively. (2) According to the hourly rainfall（R）, STHR was classified into three levels: 20≤R<30 mm, 30≤R<50 mm, and R≥50 mm, referred to as levels I, Ⅱ, and Ⅲ, respectively. The spatial distribution of levels I and Ⅱ shows higher frequencies in the eastern regions than in the western regions, with great activity observed over mountainous terrain than over plains and basins. By contrast, level III STHR exhibits no distinct spatial pattern. On the whole, the annual frequency and annual proportion of STHR across all levels show an increasing trend, with a significant shift observed at the onset of the 21st century. (3) The anomaly of high precipitable water vapor and the anomaly of low-level atmospheric pseudo-equivalent potential temperature were significantly positively correlated with the annual mean frequency anomaly and annual proportion anomaly of STHR in Jiangxi Province. Moreover, the correlation coefficient gradually decreases as the intensity level of STHR increases. Composite analysis of strong and weak STHR years indicate that when the Western Pacific Subtropical High and the Ural High are abnormally strong, accompanied by an anomalously strong low-level southwesterly flow, the frequency of STHR events in Jiangxi Province increases; conversely, the opposite circulation configuration leads to fewer STHR occurrences.
Extreme snowstorms with freezing rain are rare in Inner Mongolia, and studying such weather is of great significance for forecasting and disaster prevention. Based on the conventional meteorological observation data, ERA5 reanalysis data of the European Centre for Medium-Range Weather Forecasts and Doppler radar data of Tongliao, Inner Mongolia, the environmental conditions and causes of an extreme snowstorm with freezing rain in the southeast of Inner Mongolia on November 5-6 in 2023 were analyzed. The main conclusions are as follows: The 500 hPa upper-air cold vortex, the 700 hPa warm shear line, the 850 hPa easterly jet stream and the northward-moving surface Jianghuai cyclone were the main influencing systems of this process. When the freezing rain occurred, the vertical direction showed a “cold-warm-cold” stratification structure. There was a melting layer at 925-875 hPa, and a bright band of the 0 ℃ layer was observed on the radar base reflectivity imagery. The supercooled water particles and ice crystals entered the melting layer through the 0 ℃ layer bright band, and then fell to the ground, which conformed to the characteristics of melting freezing rain. The mid-level southwest jet climbed over the lower-level easterly cold cushion, generating strong dynamic frontogenesis, which provided robust dynamic lifting conditions for the extreme snowstorm. The existence and long-term maintenance of strong upward motion were important conditions for the extreme snowstorm. The maximum specific humidity in the lower layer over the blizzard area reached 4-6 g·kg-1, and long-lasting strong water vapor convergence in the lower layer provided sufficient moisture for the extreme snowfall. In summary, the extreme snowstorm with freezing rain in the southeast of Inner Mongolia was the result of the interaction between the upper and low level systems, the vertical uplifting mechanism triggered by dynamic frontogenesis, and the continuous water vapor transport.
To improve the accuracy of summer regional rainstorm forecast and the precision of affected area prediction in Zhejiang Province, this study utilizes precipitation observations from 75 national meteorological stations in Zhejiang Province, the fifth-generation ERA5 reanalysis data (0.25°×0.25°) from the European Centre for Medium-Range Weather Forecasts from 2010 to 2023, and the ObjectiveConsensus Forecast (OCF) model precipitation products (0.05°×0.05°) from 2020 to 2023, to analyze 187 summer regional rainstorm events in Zhejiang, conduct synoptic classification, adjust OCF model products for different precipitation types, and verify the correction effects. The results indicate that: 1) The frequency matching method significantly improves precipitation forecasts through categorical adjustment, with downward corrections for precipitation of 30 mm or below and upward compensations for precipitation more than 30 mm. The threat score (TS) for rainstorms and above increased by 4.2%, and the hit rate improved by 14.3%. 2) Based on synoptic classification, rainstorms are categorized into six types, including stationary front rainband, warm shear, subtropical high, typhoon, typhoon inverted trough and cold trough. The correction performance of frequency matching varies significantly among different rainstorm types. Specifically, for warm shear, typhoon inverted trough, and cold trough types rainstorms, the TS increased by 11.8%, 39.1% and 15.4% (with the OCF model completely missing these events), respectively, while the hit rate for typhoon inverted trough type rainstorm improved to 60.0%, and the missing rates for warm shear and cold trough type rainstorms decreased by 20.0% and 26.0%, respectively. 3) The classification correction strategy effectively enhanced the TS and hit rate of various types of rainstorm forecasts, and significantly improved the prediction accuracy of rainstorm areas.
High spatiotemporal resolution wind profile radar data are of significant value in the nowcasting and early warning of short-duration heavy precipitation. Based on conventional meteorological observations, regional automatic station data, reanalysis data from the National Centers for Environmental Prediction (NCEP), and wind profile radar network observations, this study analyzes the first large-scale heavy rainstorm event in Shandong Province following the onset of the 2023 flood season. The results indicate that, this event was jointly influenced by an upper-level trough, a low vortex, a low-level jet (LLJ), and a mesoscale shear line. Convection on June 27 occurred in the warm sector, while short-duration heavy rainfall on June 28 was primarily induced by the low vortex. The heavy precipitation mainly occurred on the right side of the mesoscale shear line, within regions of positive vorticity advection and above convergence centers. The vertical configuration of low-level convergence and upper-level divergence provided favorable dynamic conditions for strong convection. Variations in the near-surface wind field below 1 km were indicative of heavy rainfall. The downward extension of the LLJ and enhanced horizontal wind perturbations were positively correlated with precipitation intensity. Within 1 hour prior to the onset of heavy rainfall, both the LLJ index and vertical wind shear increased significantly. Before the cessation of rainfall, vertical wind shear weakened rapidly, and strong low-level shear appeared near the surface. Wind profile radar showed clear advantages in identifying precursor signatures for nowcasting short-duration heavy rainfall events.
To enhance the effectiveness of thunderstorm gale warning signals and achieve a scientific balance between accuracy and lead time, this study systematically evaluates the warning signals based on observation data from 245 automatic weather stations in Shanghai from 2016 to 2023 and warning signals issued by nine district meteorological stations, using the percentile method and synoptic classification. Results show that thunderstorm gales mainly occur from April to August, with the highest frequency in July; their diurnal variation is characterized by frequent occurrence from afternoon to nighttime; extremely strong gales are prone to appear in coastal and riverside areas; and the issuance of warning signals generally precedes the peak occurrence of gales by about 1 hour. The overall effectiveness score is 14.1 points (out of 100), and the average score for extremely strong thunderstorm gales is 28.2 points, with the warm shear type scoring the highest (49.2 points) and the stationary front shear type the lowest (12.1 points). During subtropical high-edge and stationary front shear processes, the western Pacific subtropical high tends to be stronger and displaced westward. Case studies indicate that extremely strong thunderstorm gales associated with the upper-level cold vortex under the influence of the northeast cold vortex achieve relatively higher scores. However, similar to other processes, when the wind force reaches beaufort scale force 12 or above, warnings are often issued later than the actual occurrence. Subtropical high-edge gales have a relatively wide impact range, and warnings are generally issued in a timely manner across districts, resulting in overall higher effectiveness scores.
It is of great significance to study the formation mechanisms of extreme rain-to-snow weathers under the background of explosive cyclones for improving winter precipitation forecasting and snow disaster prevention. Based on conventional meteorological observation data and ERA5 reanalysis data, this paper compares and analyzes the causes and characteristics of two extreme rain-to-snowstorm processes in Liaoning Province from November 6 to 9, 2021 (Process I), and from November 5 to 7, 2023 (Process II), from the perspectives of influencing systems, water vapor conditions, dynamic mechanisms, and thermal effects. The results show that the combined influence of an upper-level cold vortex and a surface explosive cyclone is the key factor in the formation and development of both events. The coupling of upper and lower level jet streams provides strong dynamic support for extreme precipitation, with heavy rain and snow mainly occurring on the northern side of the surface cyclone. Conditional symmetric instability is identified as the primary dynamic mechanism. Well-developed frontal zones in the lower troposphere, together with the alignment of water vapor convergence zones and fronts, are conducive to the occurrence of heavy precipitation. The phase differences among low-level uplift motion, frontal zones, and water vapor convergence zones are the main reasons for the differences in precipitation center intensity between the two events. The combined effects of dynamic and moisture conditions, along with thermal structures, determine the phase of precipitation. Specifically, the intensity of low-level cold fronts and the timing of cold air intrusion significantly influence the phase transition of precipitation and the spatial distribution of rain and snow.
