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%.
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.
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.
The heavy precipitation occurred in the northeastern region of Liaodong Peninsula from 20:00 on 3 to 14:00 on 5 August 2017, with the daily rainfall breaking historical records. Based on observations from automatic weather stations, radiosonde and Doppler weather radars, FY-2G temperature of brightness blackbody product, and European Centre for Medium-Range Weather Forecasts ERA5 reanalysis data, diagnostic analyses are made on the torrential rain processes in Liaodong Peninsula during 3-5 August 2017. The synoptic background, mesoscale environment and triggering mechanism of the mesoscale convective systems (MCSs) are focused. The results show there were two stages of this extreme rainstorm and it was influenced by upper trough, low-level shear line, the warm and moist flows in the border of the subtropical high near Japan, the intrusion of north cold-dry current, and the surface convergence line. The differences in short-term heavy precipitation between the two stages are significant, which is closely related to the low-level moisture, vertical shear of the environmental wind, and the intensity of frontogenesis. When there is abundant low-level moisture, large vertical shear of the horizontal wind, and strong frontogenesis, there is more precipitation. Frontogenesis process in the lower layer and the coupling dynamic structure of positive vorticity center and the divergence center over Liaodong Peninsula, further uplift the air, thus enable those initial convective cells to move northeastward alongside the shear line, to merge and develop, promoting higher organization and more stronger of the convection system. As shown on the surface wind field in Liaodong Peninsula, there were two north-south convergence lines and at their meeting location, convective cells merged and intensified, which was the main cause of extreme short-term heavy precipitation (hourly precipitation ≥50 mm). The surface convergence line was formed by the cold-dry current from the northeastern of Liaodong Peninsula spreading southwestward and the southerly airflow on its eastern side. In addition, the terrain blocking effect and the cold pool effect caused by heavy precipitation promoted the southward extension of the northeasterly or northerly air flow, and the backward propagation of convective cells, which was conducive to the maintenance and intensification of heavy precipitation.
The comparative analysis of local physical processes of rainfall with different intensities under similar circulation background is an effective way to improve the accurate forecasting ability of heavy precipitation events in the region. Based on multi-source data, this paper analyzed the thresholds of physical quantities of sudden increase of rainfall intensity during three heavy rainfall processes under the background of cold vortex in Tianjin on June 28 (hereinafter abbreviated as the “6·28” process), July 1 (hereinafter abbreviated as the “7·1” process) and July 26 (hereinafter abbreviated as the “7·26” process) in 2022. The results show that during the "6·28" process, the synergistic effects of extremely strong water vapor convergence (-8.0×10-7 g·hPa-1·cm-2·s-1), low lifting condensation level (962 hPa), and deep warm cloud layer (4.0 km), combined with the mesoscale vortices triggered by cold pool outflow and low-level convergence, as well as low-quality storms and the training effects, collectively resulted in a maximum rainfall intensity increase of 96.6 mm·h-1.During the “7·26” process, the higher ambient temperatures (32.1 ℃) and convective effective potential energy (CAPE) (2 464 J·kg-1) promoted the vertical development of high quality storms. However, the increasing proportion of ice phase particles limited the increase in rainfall intensity (88.8 mm·h-1). During the “7·1” process, the weak vertical wind shear (1.3 m·s-1) and insufficient cold pool strength (21.9 ℃) were impossible to trigger new convection, with the lowest increase in rainfall intensity (55.3 mm·h-1). There are common thresholds of physical quantities before the sudden increase in rainfall intensity in the three processes: the CAPE greater than 1 200 J·kg-1, the warm cloud layer thickness greater than 3.1 km, total atmospheric precipitable water greater than 47.5 mm, and the occurrence time of the surface convergence line being 1.5-2.0 h ahead of the occurrence time of heavy precipitation. The correlation coefficient between ET, CR, VIL and rainfall intensity increment exceeded 0.90, while the correlation coefficient between dew point change in the first hour and rainfall intensity increment was -0.90 during the extreme heavy rainfalls.
In order to strengthen the application of densified automatic station data in rainstorm forecast in the eastern Helan Mountain foothills, based on hourly surface meteorological observations and ERA5 reanalysis data, 17 rainstorm events in this area from 2016 to 2021 were classified into cold-warm air convergence type, warm-sector type, and weak cold air intrusion type, according to the intensity of cold air. The precipitation distribution, circulation characteristics, and the evolution of surface meteorological elements were then comparatively analyzed. The results show that cold-warm air convergence rainstorms are characterized by a deep upper-level trough and an extensive low-level high-humidity zone, but with relatively weak southerly winds and water vapor flux. These storms exhibit a wide precipitation area and high average rainfall, but the precipitation efficiency is lower than that of warm-sector rainstorms. Warm-sector rainstorms have the strongest low-level southerly winds and moisture flux, but the upper-level divergence is the weakest and the high-humidity zone is fragmented. These storms are marked by high precipitation efficiency, strong locality, and extreme intensity. In weak cold air intrusion rainstorms, the low-level warm and moist conditions are better than in the cold-warm air convergence type, and the precipitation and convective intensity which triggered by upper-level cold air are stronger than those of the cold-warm air convergence type. One hour before the onset of precipitation, all three types of rainstorms exhibit temperature drop, pressure rise, and increased wind speed, with temperature changes being the most significant, while dew point temperature varies between cases. In the five hours prior to precipitation, temperature decreased and relative humidity increased, with the most pronounced changes occurring one hour before rainfall onset. After precipitation began, these variables tended to stabilize. However, the timing and magnitude of temperature drops and the rate of relative humidity increase differed among the storm types. Dew point temperature first increased and then decreased, peaking from 1 hour before to 2 hours after rainfall onset. Wind speed variations also differed across storm types. The indicators developed in this study performed best for warm-sector type rainstorms, achieving a TS (threat score) of 48.65%, followed by the cold-warm air convergence type, with the weakest performance in the weak cold air intrusion type. The prediction accuracy of humidity, pressure, and dew point temperature indicators was relatively high (mostly exceeding 50.00%, some over 55.00%), indicating potential for enhancing rainstorm monitoring and early warning. In contrast, indicators based on temperature change (less than 50.00%) and wind speed variation (around 30.00%) showed weaker predictive capability, indicating the need for further optimization.
Study of the influence of urbanization on the climate environment can provide a basis for urban adaptation to climate change. Based on the data of meteorological stations in urban and suburban areas of Xi’an from 1961 to 2022, the impacts of urbanization in different stages on local climate were analyzed by comparison between urban and suburban areas, linear tendency estimation and Mann-Kendall (M-K) test. The results show that the urban heat island (UHI) effect in Xi’an has been significantly enhanced since the 1990s, and it was stronger in winter and spring. The UHI exhibits distinct diurnal and seasonal variations. The relatively stable high-value and low-value periods occur from 21:00 on the same day to 06:00 the next day, and from 11:00 to 16:00, respectively. The maximum value in winter appears 2-3 hours earlier than that in summer, while it ends 2-3 hours later than in summer. The contribution rate of urbanization development to the minimum temperature (Tmin) was greater than that to the maximum temperature (Tmax). The contribution rate of urbanization development to Tmax, Tmin and diurnal temperature range (DTR) was the largest in spring, while that to average temperature (Tave) was the largest in summer. The urban rain island (URI) effect primarily occurs during winter and spring. During the rapid urbanization period (1991-2022), the URI effect intensified, characterized by increased frequency and intensity of moderate-to-heavy precipitation in urban areas, alongside a reduction in light precipitation. The urban turbidity island (UTI) and urban dry island (UDI) effects were more pronounced in both winter and spring. For the entire year, the absolute difference in sunshine duration (SD) between urban and suburban areas during the rapid urbanization period was 0.73 h, and the absolute difference in relative humidity (RH) was 4.38%. The contribution rate of urbanization development to SD and RH was the largest in spring and summer, respectively.
To explore the spatiotemporal evolution of climate comfort in Guizhou Province and support regional tourism development planning, this study utilized daily meteorological data from 77 national stations spanning from 1974 to 2023. Two evaluation models, the comprehensive comfort index (CCI) and the outdoor weather comfort index (OWCI), were employed in combination with the least squares method, Pearson correlation analysis, and Mann-Kendall (M-K) mutation test. The results indicate that both indices effectively capture the spatiotemporal characteristics of climate comfort across Guizhou. The CCI is more effective at reflecting long-term climate variability and incorporates clothing adjustment capacity, making it more suitable for annual-scale assessments. In contrast, the OWCI responds more responsive to environmental meteorological conditions change and performs better at the monthly scale. Climate comfort days showed a significant increase in March and November, and a significant decrease from June to September. The proportion of stations with a significant increasing trend in climate comfort days is highest in March, while the proportion of stations with a significant decreasing trend is highest in July and August. Overall, climate comfort is favorable in southern low-altitude areas from January to March and November to December, in western high-altitude regions from May to September, and across most of the province in April and October.
It is of great significance to scientifically assess the risk of drought disaster during the key growth period of apples to reduce the loss of apples due to drought. Based on multi-source data such as meteorological data, apple planting data, elevation, river density, and vegetation coverage data in Hebei Province, this paper systematically evaluated the characteristics of drought disaster risk during key growth period of apples in Hebei Province by analyzing the risk factors of drought disasters, the sensitivity of disaster prone environments, and the exposure of disaster bearing bodies. The results show that the total probability of drought occurrence during the sprouting and young fruit stage of apples in Hebei Province was the highest, generally above 60%, and was mainly severe drought and extreme drought. The risk of disaster causing factors was ranked from high to low as follows: germination and young fruit stage, coloring and maturity stage, fruit swelling stage, and the northwest region was a high-risk area in all stages. The sensitivity of pregnancy disaster environment showed a spatial distribution characteristic of increasing from southeast to northwest. The exposure of disaster bearing bodies was relatively high in some areas in the east and south. The regions with drought disaster risk indices greater than 0.800 during the germination young and fruit stage, fruit swelling stage, and coloring and maturity stage account for 20.8%, 8.7%, and 8.5%, respectively, and the northwest region was a high-value area of risk indices in all growth stages. The high-value, median, and low value areas of the drought disaster risk in the whole growth period of apple accounted for 14.2%, 27.2%, and 58.6% of the total area, respectively, and shows a gradually increasing trend from southeast to northwest. Therefore, it is necessary to focus on the prevention of drought disasters in high-risk areas in the northwest of Hebei Province, and provide a scientific basis for drought resistance and disaster reduction in the apple industry.
The study of the adaptability of meteorological drought indices in alpine grassland is of great significance to improve the accuracy of drought monitoring of natural vegetation on the Qinghai-Xizang Plateau, protect alpine grassland ecosystems, and promote the sustainable socio-economic development of pastoral areas. In this study, the drought monitoring accuracy of indices such as Precipitation Anomaly in Percentage (PA), Standardized Precipitation Index (SPI), Meteorological Drought Composite Index (MCI) and Palmer’s Drought Severity Index (PDSI) in the alpine grassland at the eastern edge of the Qinghai-Xizang Plateau was evaluated by using the day-by-day measured soil moisture data from 2010 to 2022, and combining with the Pearson’s correlation coefficient and the method of drought identification. The PDSI index with higher drought identification accuracy was selected for local calibration, and based on the PDSIimproved obtained from the calibration, the monthly drought conditions of the study area in 2022 were analyzed. The results show that: 1) The drought identification accuracies of the four meteorological drought indices (PA, SPI, MCI and PDSI) in the study area were 48.21%, 38.79%, 37.42% and 59.16%, respectively. Among them, the PDSI responded better to the drought condition of the alpine grassland in the study area, but in the case when the relative soil humidity was less than or equal to 60% and the number of drought days was not consecutive, it was prone to omission or over-measurement. 2) By establishing the correspondence between the relative soil humidity and the PDSI value, and performing the localized calibration of the PDSI and the threshold adjustment of drought level, the improved PDSI can improve the drought identification accuracy by 12.15%, reaching 71.31%. 3) The PDSIimproved was used to monitor the drought situation in the study area in 2022. The results show that the drought mainly occurred in the low-lying areas in the southeast of the study area at an altitude of 3 300-3 700 m, and the drought had obvious seasonal characteristics, which was mainly concentrated in winter and mainly characterized by severe drought and extreme drought.
To reveal the spatio-temporal differences and atmospheric circulation causes of summer meteorological drought in the Sichuan-Chongqing region, based on daily observational data and meteorological drought composite index (MCI) of 188 meteorological stations in Sichuan and Chongqing during 1981-2023, the spatio-temporal evolution characteristics of summer drought in Sichuan and Chongqing are analyzed. In addition, monthly reanalysis data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) and climate system monitoring indices are employed to investigate the drought formation mechanisms from the perspectives of circulation patterns, water vapor transport, westerly jet streams, and vertical motion. The results show that droughts in the Sichuan-Chongqing region exhibit strong synchronicity and significant regional differences. Drought in Sichuan mainly concentrates in June and August, while that in Chongqing is more severe from July to August. The drought centers are primarily located in the Sichuan Basin, with a certain degree of synchrony between eastern Sichuan and Chongqing, whereas the drought in the western Sichuan Plateau is relatively weak. During typical drought years, the South Asian High moves northward and strengthens, the Western Pacific Subtropical High is abnormally located further north, water vapor transport at 700 hPa is weakened, and the region is controlled by subsidence motion, resulting in significantly less precipitation. Distinct atmospheric circulation anomalies in different types of drought years are the main cause of the spatial variability of drought in the region.
Land-atmosphere coupling is a crucial link in the exchange of mass and energy between the land surface and the atmosphere. Water vapor from soil evaporation condenses and releases latent heat during rising and cooling processes, which warms the boundary layer air and reduces atmospheric boundary layer stability, thereby promoting the initiation and development of convection, and can potentially lead to precipitation formation. An in-depth study of the spatio-temporal variation characteristics of land-atmosphere coupling is of great significance for understanding its role in global climate change. Based on the soil moisture data from the Global Land Data Assimilation System (GLDAS), the land surface reanalysis data of the European Centre for Medium-Range Weather Forecasts (ERA5-Land), and the precipitation data from the Global Precipitation Climatology Centre (GPCC) from 1950 to 2020, this study employs three land-atmosphere coupling indices: λ (reflecting the feedback efficiency of soil moisture on precipitation), ISM-LH (representing the sensitivity of latent heat flux response to soil moisture changes), and ILH-Pr (representing the sensitivity of precipitation response to latent heat flux changes) to calculate the land-atmosphere coupling strength and identify key coupling regions in the Northern Hemisphere. On this basis, the spatio-temporal characteristics of land-atmosphere coupling in the Northern Hemisphere are analyzed. The results show that the land-atmosphere coupling index ISM-LH calculated from soil moisture and latent heat flux, can best represent the coupling strength. There are five key land-atmosphere coupling regions in the Northern Hemisphere, namely the North America key coupling region (NA), the Mediterranean key coupling region (MS), the Central Asia-Mongolia key coupling region (CM), the Africa key coupling region (AF), and the South Asia key coupling region (SA). The extent of the key land-atmosphere coupling regions is widest and their coupling strength is strongest in summer, followed by spring. The lagged coupling strength between spring and summer is weaker than the concurrent coupling strength in spring or summer. During the period of 1950-2020, the coupling strength in key land-atmosphere coupling regions exhibited clear linear trends. The NA, SA, and AF key regions showed a linear weakening trend in land-atmosphere coupling strength, with the weakening trend in AF in summer being the most pronounced at the rate of -3.61/10 a (p<0.01). Conversely, the MS and CM key regions showed a strengthening trend, with the linear strengthening trend in CM in summer being the most significant at the rate of 2.28/10 a (p<0.01). The linear trends of coupling strength and precipitation showed an inverse phase relationship in the NA and MS key regions, and an in-phase relationship in the AF and SA key regions. During the same period, anomalies in land-atmosphere coupling strength and precipitation within these key coupling regions showed a significant negative correlation. The negative correlation was strongest in MS in spring, r=-0.469 (p<0.01), and strongest in AF during summer, r=-0.821 (p<0.01).
Under the background of global warming, Xinjiang has frequently experienced extreme weather and climate events. An in-depth study on the homogenization of extreme temperature will help to accurately analyze climate change characteristics and provide a basis for formulating effective climate change response strategies. Utilizing the Penalized Maximum T Test (PMT) method included in the RHtestsV5 software package, the paper selected homogenized monthly average maximum and minimum temperatures as reference sequences to conduct homogeneity tests on monthly extreme maximum and minimum temperature series from 1951 to 2022 at 105 national surface meteorological stations in Xinjiang. This analysis aimed to identify the primary causes of inhomogeneity in the monthly extreme maximum and minimum temperature series in Xinjiang, and the Quantile-Matching (QM) method was employed to adjust the inhomogeneous series. The results are as follows: 1) Among the 105 national surface meteorological stations, 26 stations exhibited breakpoints in monthly extreme minimum temperature, and 8 stations exhibited breakpoints in monthly extreme maximum temperature. Extreme minimum temperature are more susceptible to non-natural factors than extreme maximum temperatures. 2) Relocation of meteorological stations is the primary cause of breakpoints in extreme maximum and minimum temperature series. Environmental changes act as the secondary factor for extreme maximum temperature, while the causes of breakpoints in extreme minimum temperature also include instrument type replacement, environmental changes and changes in observation times. 3) The trends of annual extreme maximum and minimum temperatures throughout Xinjiang showed little difference before and after the adjustments. However, stations such as Moyu exhibited a shift from a cooling trend to a warming trend in both monthly extreme maximum and minimum temperatures. The adjusted extreme maximum and minimum temperatures in Xinjiang are more in line with the climate warming characteristics of the northwest region, and the spatial consistency of climate change has been significantly improved. 4) The changing trends of the corrected data sequences of the extreme maximum temperature at Moyu Station and the extreme minimum temperature at Korla Station are consistent with the data of the old sites, and have a better consistency with the research results of the climate warming characteristics in Xinjiang, indicating that the correction method is reliable and scientific.
Systematically investigating drought evolution characteristics and vegetation responses to drought is crucial for drought prevention, disaster mitigation, water resource management, and policy formulation. Our study focuses on Xinjiang, Qinghai, and Gansu provinces in mid-western Northwest China. Using the CN05.1 dataset from 1963 to 2022 to calculate the standardized precipitation evapotranspiration index (SPEI), combined with the normalized difference vegetation index (NDVI) from 2003 to 2022, we applied run theory, Theil-Sen slope estimator, Mann-Kendall trend test, and regression analysis to analyze drought evolution across multiple temporal scales and explore drought impacts on vegetation. The results indicate that over the past 60 years, the study area exhibited a drying trend on decadal and interannual scales, with 1998 identified as a significant drought mutation year. Pronounced drying trends were observed in eastern and southern Xinjiang, the Qaidam Basin, and the Hexi Corridor, where light and moderate droughts were predominant. The Hexi Corridor experienced a significantly higher frequency of moderate droughts (greater than 15.00%) than other regions. Drought variability exhibited periodic characteristics of 12-year, 30-year, and 46-year cycles, with notable seasonal differences. In spring, summer, and autumn, the mid-western Northwest China showed significant drying trends, with the most rapid decline in autumn (SPEI rate: -0.034 yr?1). The Hexi Corridor exhibited SPEI decline rates below -0.030 yr?1 across all three seasons, indicating high risks of consecutive droughts, alongside prolonged duration, higher peak intensity, and mean drought intensity. The Tarim Basin also faced severe drought conditions in spring and autumn. Drought exerted measurable impacts on vegetation dynamics. Compared to 2003-2012, NDVI degradation areas increased by approximately 3.52% during 2013-2022. Over the past two decades, vegetation degradation was concentrated in western Xinjiang, eastern and southern Qinghai, where NDVI and SPEI were positively correlated.
Drought stress is a major limiting factor for crop growth. Investigating the photosynthetic characteristics and physiological drought resistance mechanisms of spring maize (Zea mays L.) at the seedling stage is crucial for enhancing drought resilience and promoting crop yield. In this study, taking spring maize as the research object and using pot experiments, four gradients of control treatment (referred to as “CK” treatment), mild drought (T1), moderate drought (T2), and severe drought (T3) were set up to study the photosynthetic physiological characteristics and drought resistance mechanism at the seven-leaf stage of spring maize under different drought degrees. The results show that drought stress significantly reduced both the net photosynthetic rate (Pn) and the maximum net photosynthetic rate (Pnmax) of spring maize leaves. Under moderate and severe drought conditions, the initial slope (α0), the dark respiration rate (Rd), and the apparent quantum efficiency (AQE) of the light response curve decreased significantly, while the light saturation coefficient (γ0) increased markedly, indicating the light energy utilization rate of the leaves decreased significantly. The transpiration rate (Tr) gradually decreased with increasing of drought intensity, the water use efficiency (WUE) significantly enhanced under moderate drought but sharply reduced under severe drought. Stomatal conductance (Gs) progressively declined with drought stress intensification. Stomatal limitation was identified as the primary factor reducing photosynthetic rate under mild and moderate drought conditions, with non-uniform stomatal closure phenomenon under mild drought. Under severe drought condition, intercellular CO2 concentration (Ci) significantly increased, and the stomatal limitation value (Ls) decreased dramatically, demonstrating the dominance of non-stomatal limitation.
It is crucial for disaster prevention, mitigation, and food security to elucidate the temporal and spatial characteristics of multi-scale drought in Heilongjiang Province under the background of climate change. Based on NCEP (National Centers for Environmental Prediction) and GPCC (Global Precipitation Climatology Center) monthly grid meteorological data with a horizontal resolution of 1°×1° in Heilongjiang Province from 1961 to 2023, the standardized precipitation evapotranspiration index (SPEI) was calculated at various time scales. Additionally, the K-means clustering method was employed to divide Heilongjiang Province into three distinct zones, and the spatio-temporal characteristics of meteorological drought for multiple time scales in different zones in Heilongjiang Province from 1961 to 2023. The results show that the SPEI in Heilongjiang Province fluctuated significantly from 1961 to 2023. Notably, the SPEI in the northern mountainous region decreased markedly in April, while the SPEI in the central and western plain areas as well as the southeastern region increased at varying time scales, reflecting obvious spatial disparities in dry and wet conditions across different regions of Heilongjiang Province. Meteorological drought in Heilongjiang Province predominantly manifested as large-scale widespread occurrences, with two prominent high-frequency periods: 1967-1989 and 1999-2011. Furthermore, the spatial extent of drought in summer generally exceeded that in spring. In the recent climatic period (1991-2020), the frequency of drought in Heilongjiang Province increased and the intensity of drought intensified. And this trend poses a challenge to regional ecological security and sustainable development.
In the extreme arid region of Northwest China, the Gobi desert is widely distributed, with strong winds and abundant sand, leading to frequent disasters. A deep understanding of the basic laws of the aeolian sand-dust movement over Gobi surfaces is an important prerequisite for disaster warning and scientific prevention. Given the current difficulty in accurately predicting the instantaneous aeolian sediment transport rate, exploring the statistical laws of airflow and sand-dust characteristic physical quantities in wind-sand events, and then conducting statistical forecasting, may be a feasible way to establish a quantitative relationship between wind and sand on time scales of seconds or less. This study borrows the ideas and methods from the statistical theory of turbulence, and analyzes four field observation datasets of Gobi sand-dust movement using the Hilbert-Huang transform. The results indicate that the Hilbert marginal spectra of the time series of wind speed, kinetic energy and number of saltation sand particle, and dust concentration in the aeolian events all follow the power scaling law. The scaling exponents of variables, characterizing aeolian sand and dust motions, and wind speed range from 0.78 to 1.51 and 0.59 to 1.47, respectively.
As a hot spot of “land-atmosphere coupling”, the current study focuses on the spatial and temporal distribution of land-atmosphere coupling and the influence of hydrothermal conditions in the climate transition regions, but lacks the study on the synergistic effect of multi-factor and the difference in coupling degree among different ecosystems. Based on the station observation data, the paper focused on the coupling relationship between land surface water, thermal and ecological factors and surface fluxes, comparatively analyzed the differences in single-factor and multi-factor synergistic land-atmosphere coupling among different ecosystems, and assessed the contribution of each land surface factor to the coupling degree. The results show that in single-factor coupling, the coupling between latent heat flux and leaf area index is the strongest for sparse vegetation, and the coupling between latent heat flux and soil temperature is the strongest for farmland; the coupling between sensible heat flux and soil temperature is the strongest for grassland, forest and farmland. Multi-factor synergistic coupling is significantly better than that of single factor, and multi-factor synergistic coupling with latent heat flux is significantly enhanced in forest and sparse vegetation, and synergistic coupling with sensible heat flux is obviously enhanced in sparse vegetation. Among the contributions of each factor to the surface fluxes, in grassland system sensible and latent heat fluxes are dominated by thermal and ecological factors, respectively; in sparse vegetation system latent heat flux is co-dominated by the soil moisture factor and leaf area index, and sensible heat flux is dominated by the thermal factor; and latent heat and sensible heat fluxes are dominated by the thermal factor in farmland and forest system. Under drought conditions, the contributions of soil moisture and ecological factors to latent and sensible heat fluxes increase in most ecosystems.
It is of great significance to study the relationship between summer atmospheric heat source over the Qinghai-Xizang Plateau and its surrounding area and the number of high temperature days in the Sichuan-Chongqing Basin for summer high temperature prediction and high temperature and drought disaster prevention. Based on the daily maximum temperature data of 125 meteorological stations in the Sichuan Chongqing Basin and monthly NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) reanalysis dataset, the characteristics of summer high temperature days in the Sichuan-Chongqing Basin and relationship between the inter-annual variation of high temperature days there and atmospheric heat source over the Qinghai-Xizang Plateau and its surrounding area are discussed. The results show that the first mode of EOF decomposition of high temperature days presented a consistent type in the whole region, which can reflect the main distribution characteristic of summer high temperature days. The summer high temperature days in the basin significantly increased from 1979 to 2022, showing obvious inter-annual and inter-decadal variation characteristics. There is a close relationship between the atmospheric heat source over the eastern part and its eastern side of Qinghai-Xizang Plateau and the inter-annual variation of summer high temperature days in the basin. When the heat source over the key region of the plateau is relatively weak (strong), the corresponding high temperature days in the basin are significantly more (less). On the inter-annual scale, when the atmospheric heat source over the eastern part and its eastern side of Qinghai-Xizang Plateau is weaker than normal, the position of South Asian high shifts northeastward, and the western Pacific subtropical high shifts northwestward, The water vapor transport from the South China Sea, western Pacific, and Bay of Bengal to the basin is significantly weakened, combined with significant subsidence anomalies over the basin, resulting in less precipitation and high temperature days there. At the same time, the total cloud cover in the basin is less than normal, and the short-wave solar radiation flux reaching the ground increases significantly, resulting in a rise in ground temperature and an increase in the number of high-temperature days. When the atmospheric heat source over the eastern part of the plateau and its eastern side is relatively strong, the circulation pattern is beneficial for reducing the number of high temperature days in the basin.
This study employs a distributed rainfall-runoff routing model, using minute-resolution radar quantitative precipitation estimation data and 12.5 m-resolution topographic data. Model parameters were calibrated using observed data from the Shuangxi Hydrological Station. A refined simulation was conducted to reproduce the flash flood and debris flow event that occurred in Baishi Township, Beichuan County, Mianyang City, Sichuan Province, on July 16, 2022. The model effectively retraced the runoff generation and confluence processes and analyzed the underlying causes of the disaster. Results show that the localized model performed well, with a high degree of consistency between simulated and observed water depths. The coefficient of determination (R2) reached 0.86, with a maximum water depth error of 0.25 m, a rise magnitude error of 0.59 m, and a runoff onset timing error of 0.1 h, all within acceptable margins and laying a solid foundation for subsequent analyses. From 00:00 Beijing time on July 16, 2022, Beichuan experienced 8.0 hours of continuous rainfall reaching rainstorm levels. The heaviest precipitation occurred in Baishi Township and the upstream basins of the Qingpian and Tiedong rivers, with rainstorms covering 70% of the total basin area and particularly affecting the middle and lower reaches. The maximum hourly rainfall reached 30 mm, the maximum cumulative rainfall was 120 mm, and the average rainfall in the middle and lower reaches was 88 mm. The long duration, high intensity, and wide spatial coverage of rainfall were the primary triggers of the flash flood. In addition, steep terrain gradients and narrow river channels accelerated runoff and increased water depth. Flow velocities at several locations exceeded 3.3 m·s-1. In the lower Qingpian River, water depth continued to rise for 2.0 hours, reaching a flood peak of 15.4 m that lasted for 2.6 hours, contributing significantly to the runoff at the disaster site. At Baishi Township, the peak flood depth reached 21.0 m and remained at a high level for 3.0 hours. Under complex terrain conditions, prolonged heavy rainfall triggered a large-scale flash flood in the small watershed, inundating multiple villages along the river to varying extents. The study area lies within the central Longmenshan Fault Zone and was severely impacted by the 2008 Wenchuan Earthquake. There are 23 identified hazard sites for debris flows and landslides in the basin. The intense flash flood scoured and mobilized abundant loose material, generating a catastrophic debris flow that caused devastating damage to Baishi Township.
An extreme rainstorm occurred in the northeastern region of the Sichuan Basin from 20:00 on 7 to 20:00 on 8 August 2021, with the daily rainfall and the hourly rainfall during the night rain period breaking historical records. The meteorological observation data, Doppler radar data and ERA5 reanalysis data were utilized to analyze the evolution and causes of this process. The results are as follows: 1) Before the process, the pseudo-equivalent potential temperature (θse) at 700 hPa deviated from the climate average by 2.5 standard deviations, and the specific humidity at 700, 850, and 925 hPa all deviated by more than 2 standard deviations. 2) The stable ground convergence zone and the low vortex shear system in the middle and lower layers continuously triggered new convection and constantly merged with the original convection system to form “train effect”, ensuring the maintenance and development of the original convection system; 3) The convergence of low-level warm-humid air and dry-cold air formed a stable θse front area, the meridional warm and humid updraft, together with the updraft of the zonal secondary closed circulation, provided stable energy and water vapor transportation for the convective system. The convergence wind field near 700 hPa, in combination with the blocking effect of the descending and northerly airflow in the meridional secondary circulation at the middle and lower levels, made the convective system present a quasi-stationary “backward propagation” feature, which was conducive to the formation of this extreme rainstorm.
Studying the basic characteristics of sudden rainfall events in mountainous areas, along with the local circulations induced by dynamic and thermodynamic processes, is of great significance for improving the accuracy and timeliness of forecasting sudden heavy rainstorms in such environments. This paper investigates two sudden rainfall events in the mountainous region of Mianyang, China, based on the china multi-source merged precipitation analysis system (CMPAS), black body temperature (TBB) data from the FY-2G satellite, and ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Diagnostic analyses and numerical simulations were conducted using equations representing flow around, up, and over mountains.The results indicate that both sudden torrential rainfall events in mountainous areas occurred under the influence of the western Pacific subtropical high within a weak synoptic-scale environment. The convergence of cold and warm air masses, combined with favorable moisture supply and high-temperature conditions, served as the primary triggers for the rainstorms. Cross-mountain airflow induced by terrain obstruction generated both around and over flow motions. Within the rainfall zone, these processes enhanced vertical ascent and localized vortices. When weak cold air intruded, flow over dominated, and the combined effects of ascending and deflected flows created favorable dynamic conditions for the initiation and intensification of the sudden rainstorms. In contrast, under strong cold air influence, the contributions of around and over flows to heavy rainfall were significantly reduced. The around and over flows within the rainstorm area were coupled with the intensity of precipitation. During the rainfall process, the cessation of surface heat input led to a significant weakening of thermal disturbances near the rainfall area, preventing the formation of local circulation in the western basin, resulting in weakened around and over flows, and the disappearance of the convergence zone, which led to a noticeable reduction in simulated precipitation and the disappearance of the heavy precipitation center. Numerical simulations for both events demonstrated that latent heat played a more critical role than sensible heat in driving precipitation.
Based on ground automatic station, multi-band weather radar and sounding data, and the fifth generation atmospheric reanalysis ERA5 from the European Centre for Medium-Range Weather Forecasts (ECMWF), the environmental conditions, mesoscale characteristics and maintenance mechanisms of a rare squall line weather process in Yunnan Province on 7 July 2022 were analyzed. The results show that this squall line occurred within the convergence zone of the continental high and subtropical high, with environmental conditions characterized by strong convective available potential energy, moderate vertical wind shear, and significant intrusion of high-level dry and cold air. Changes in C-band radar reflectivity and radial velocity were closely associated with the occurrence of strong surface winds and hail. The squall line exhibited distinct features, with a pronounced inflow jet near the surface layer, accompanied by velocity ambiguity and gust front characteristics. The hail cells exhibited characteristics such as three-body scattering, midlevel convergence, and storm-top divergence. High spatial and temporal resolution observations from the X-band dual-polarization phased array radar showed that mature hail clouds had a strong reflectivity factor exceeding 55 dBZ. At the same time, a prominent differential reflectivity (ZDR) column was observed near the strong updraft, with vertical extension exceeding the height of the wet-bulb temperature 0 ℃ layer. Dual-polarization parameters further indicated that precipitation occurred during the hailfall process. The analysis found that the long-term maintenance of ground convergence lines, the coexistence of strong updrafts and tilted downdrafts within the storm, and the coupling of low-level convergence with high-level divergence was the main mechanisms sustaining this squall line.
Liupan Mountain is an important component of the Loess Plateau-Sichuan-Yunnan ecological barrier and a key water-retaining forest base in Northwest China. To further enhance the understanding of the macro- and microphysical characteristics of orographic clouds and to support scientific weather modification operations, this study investigates a mixed stratiform orographic cloud process that occurred in the Liupan Mountain area from August 21 to 23, 2020. The analysis is based on comprehensive observations from a high-mountain meteorological station at an elevation of 2 842 m, using instruments such as a fog drop spectrometer, raindrop spectrometer, and millimeter-wave cloud radar. The results show that this precipitation system was significantly influenced by orographic effects. The increases in cloud-top height and vertical thickness were approximately equal to the average mountain elevation of 2 162 m. During the period of peak rainfall, the raindrop number concentration, maximum diameter, mean diameter, and liquid water content reached maximum values of 970 m-3, 4.25 mm, 1.23 mm, and 1.36 g·m-3, respectively. The raindrop size distribution was better represented by the Gamma distribution than by the Marshall-Palmer distribution. Based on cloud microphysical data, the cloud system was divided into three mesoscale cloud regions. The widths of regions 2 and 3 were both approximately 400 km. Compared with region 2, region 3 exhibited higher liquid water content, larger mean volume diameter, and larger mean effective diameter, resulting in approximately twice the amount of precipitation.
