The ERA5-Land reanalysis product is an important global data for surface variables, and its error assessment in drought monitoring is of great significance for further improving drought early warning ability and reducing disaster risk. Based on daily precipitation grid data from the National Meteorological Information Center during 1981-2020, combined with the standardized precipitation index (SPI), the error characteristics of the Land component of the Fifth Generation of European Reanalysis (ERA5-Land) precipitation data from the European Centre for Medium-Range Weather Forecasts (ECMWF) in monitoring drought in the Yellow River Basin and its sub-basins were evaluated quantitatively, and overestimate or underestimate of precipitation and the ability of describing drought characteristics of ERA5-Land precipitation products in different regions on different time scales were explored. The results show that the ERA5-Land precipitation products are obviously overestimated in the Yellow River Basin, especially in the upper reaches, followed by the middle reaches, and in the lower reaches errors are relatively small. At different time scales, the ability of ERA5-Land precipitation products to reflect dry and wet conditions is obviously different, and the difference increases with the increase of time scale. For drought events in the Yellow River Basin, the ERA5-Land precipitation products have obvious overestimation of drought frequency and underestimation of drought duration. In the upper reaches, drought intensity and severity are mainly overestimated, while in the middle and lower reaches, drought intensity and severity are obviously underestimated. Although the ERA5-Land precipitation products can effectively capture the spatial distribution of typical drought events, the description of drought areas of different grades is not accurate. Therefore, when using ERA5-Land precipitation products for drought monitoring, it is necessary to pay special attention to its overestimation or underestimation.
Drought disaster is one of the most frequent meteorological disasters in the Gannan Plateau, which seriously affects agricultural and animal husbandry production and ecological environment security in this region. Monthly precipitation and air temperature data from 31 meteorological stations in the Gannan Plateau and its surrounding areas from 1973 to 2022 are used to characterize meteorological drought employing the Standardized Precipitation Evapotranspiration Index (SPEI), and the temporal and spatial distribution of drought and its variations on annual and seasonal scales in the Gannan Plateau are analyzed by using Mann-Kendall test and Sen’s slope estimation methods. Results show that the annual SPEI in the Gannan Plateau presented significant downward trend with an obvious turning point in 1986, and the whole Gannan Plateau tended to be dry in the past 50 years. There were seasonal differences in the variation trend of drought, and the trend of drought intensified in summer and autumn, but in spring and winter it mitigated. In addition, there were spatial differences in the trend of annual and seasonal SPEI. In summer, it presented drought intensification trend in the middle and eastern regions of the Gannan Plateau, and in spring it showed similar to that in summer, but the area and degree of drought intensification were obviously smaller than that in summer. While in winter, it showed drought decreasing trend in the whole region. There were obvious spatial differences in the frequency of drought with different levels in the Gannan Plateau at the annual and seasonal scales. Light drought occurred frequently in the central and eastern parts of the Gannan Plateau, while medium and severe drought occurred frequently in the southern part of the Gannan Plateau, and the frequency of serious drought was less across the whole regions. Overall, the frequency of drought in the western was less than that in the central and eastern parts of the Gannan Plateau.
Under the background of global warming, studying the characteristics of dry-wet climate changes in the Shiyang Rive Basin and their influence on vegetation coverage has significant importance for the ecological environment construction of the basin. Based on the precipitation temperature homogenization index (S) in the Shiyang River Basin from 1971 to 2020, the spatial-temporal changes of the dry-wet climate in the basin were analyzed from the aspects of drought station frequency ratio, drought frequency, and more. Combined with the Normalized Differential Vegetation Index (NDVI) remote sensing data, the influence of dry-wet change on NDVI was analyzed. The results showed that the inter-annual and seasonal S indices showed an increasing trend in the Shiyang River Basin over the past 50 years, with the most pronounced increase in summer. The drought degree and drought occurrence area have shown a decreasing trend in the basin. The intensity of drought in the midstream and downstream were more severe compared to the upstream, with higher drought frequencies in the downstream. The annual NDVI increased with the alleviation of drought, the increase of precipitation and decrease of temperature. The precipitation in the early and middle period of growth, as well as the temperature in the middle period had a great influence on the annual NDVI. In February, May and July, the NDVI had a lag effect in response to drought.
In order to understand the characteristics of vegetation change in East China, based on the Global Land Surface Satellite Leaf Area Index (GLASS LAI) remote sensing data from 1982 to 2016, the spatial and temporal variation characteristics of vegetation leaf area index (LAI) in East China over the past 35 years were studied using trend analysis method, the correlation between vegetation LAI and climatic factors (temperature, precipitation and solar radiation) was analyzed using the partial correlation method, and the dominant climatic factors of LAI changes in different regions were explored. Results are as follows: (1) The annual average LAI in East China ranged from 0.05 to 7.20, and the multi-year average annual maximum LAI ranged from 0.04 to 8.60, both showing a decreasing trend from south to north. (2) The overall annual average LAI and annual maximum LAI in East China in the last 35 years showed a fluctuating increase trend, with growth rates of 0.007 9 (p<0.05) and 0.022 6 (p<0.05) per year, respectively. Although the LAI in the northern part of East China was lower than that in the southern part, the increasing trend was obvious in the last 35 years; the LAI in the southern part of East China was higher, but there was a decreasing trend in some regions. (3) The pixels with significant increasing trend of annual mean LAI and annual maximum LAI accounted for 60.9% and 60.5% of the whole region, respectively, and were mainly located in the north of Jianghuai regions. In contrast, the pixels with significant decreasing trend of annual mean LAI and annual maximum LAI accounted for 8.9% and 6.4%, respectively, which were concentrated in northern Zhejiang and southern Jiangsu. (4) There were differences in the major climate factors affecting annual mean LAI and annual maximum LAI changes in different regions. As for annual mean LAI, the regions mainly affected by temperature and precipitation accounted for 13.9%, and the regions mainly affected by solar radiation accounted for 10.0%. As to annual maximum LAI, there was 26.5% region dominated by temperature, and they were mainly distributed in the south-central part of the study area.
With global warming, the extreme precipitation events increase significantly, leading to serious natural disasters. The Qinghai-Tibet Plateau is a sensitive region to global climate change, and the analysis of extreme precipitation events in this region is conducive to providing theoretical reference for plateau climate prediction and disaster prevention and reduction. Based on the daily precipitation data from 68 meteorological stations of central and eastern Tibetan Plateau during 1961-2017, the percentile threshold method, linear tendency estimation method and extreme precipitation index were used to comprehensively analyze the temporal and spatial distribution characteristics of extreme precipitation in this region, and to explore the contribution of precipitation with different intensities to the total precipitation. The results show that the extreme precipitation indexes decreased from southeast to northwest in the central and eastern part of the Qinghai-Tibet Plateau as a whole, and the total precipitation and extreme precipitation in the southeastern part of the plateau were high, but the influence of precipitation change in this area on the increase of total precipitation was small. In the past 57 years, the extreme precipitation indexes showed an overall increasing trend. Among them, total precipitation and its intensity, heavy precipitation, 1-day maximum precipitation and continuous five-day maximum precipitation showed a significant increasing trend. The climatic tendency rate of heavy precipitation was greater than that of extremely heavy precipitation, and the proportion of heavy precipitation to total precipitation obviously increased, while the proportion of extremely heavy precipitation decreased slightly, which indicated that the contribution of heavy precipitation to total precipitation increase is greater than that of extremely heavy precipitation. The trend spatial distributions of heavy precipitation, heavy rainfall days and moderate rain days were basically agree with total precipitation and its intensity, and the significant increase area distributed in the northeast part of the region, which led to the increase of total precipitation and extreme precipitation in the central and eastern parts of the plateau.
It is of great significance to study the climatic characteristics of heavy snowfall in winter over the Qinghai-Tibet Plateau for winter precipitation prediction and snow disaster prevention in the Qinghai-Tibetan Plateau. Based on the daily precipitation data from 99 meteorological observation stations in the Qinghai-Tibetan Plateau in winter (from November to February of the following year) during 1961-2021, the spatial distribution and temporal variation characteristics of heavy snowfall and heavy snowfall days in early and late winter over the Qinghai-Tibetan Plateau and their relationship with sea surface temperature (SST) in different basins and Arctic oscillation (AO) were analyzed by using linear tendency estimation, correlation analysis and ensemble empirical mode decomposition methods. The results show that there were more snowfall processes with larger magnitude in early winter, while snowfall in late winter were more frequent and lasted longer duration in the Qinghai-Tibetan Plateau during 1961-2021. Both heavy snowfall and heavy snowfall days in early winter showed a "less-more-less-more" variation, while heavy snowfall and heavy snowfall days showed a significant increasing trend in late winter. The contribution rate of heavy snowfall and heavy snowfall days in early winter was significantly greater than that in late winter. The central and eastern parts of the plateau are areas with high value of heavy snowfall in early and late winter, and heavy snowfall in the northeast side was also large in early winter. The sea surface temperature anomalies in the tropical Indian Ocean, the north Atlantic Ocean and the Pacific Ocean were important factors affecting heavy snowfall in winter in the Qinghai-Tibetan Plateau. There was a significant positive correlation between heavy snowfall in early winter and SST in tropical middle-east Pacific Ocean and the western tropical Indian Ocean, while the positive correlation between heavy snowfall in late winter and SST in the tropical Indian Ocean, the northwestern Pacific Ocean and the north Atlantic Ocean was the most significant. Since the mid-1990s, the Indian Ocean dipole has changed from a weak positive correlation to a significant positive correlation with heavy snowfall in early winter, and the Arctic oscillation anomaly has an important impact on heavy snowfall in late winter, and both have always shown a stable positive correlation.
In order to strengthen the understanding of the low visibility impact events on the navigation meteorological conditions of the Yangtze River trunk line and improve the level of weather forecast for channel impact, using observational data from the National Meteorological Station and ERA5 reanalysis data (the fifth ECMWF reanalysis), we conducted an analysis of the spatiotemporal distribution characteristics of fog days at 51 stations along the Yangtze River, as well as the weather conditions and meteorological element changes during fog occurrences. The main findings are as follows: (1) Most stations along the river experienced a high incidence of fog from November to next January. The Sichuan and Chongqing area exhibited a consistently high fog occurrence throughout the year, while in the Hubei-Anhui Plain region fog incidents are frequent in spring. Thick fog and heavy fog predominantly occurred during the late-night and early morning hours, with strong fog typically occurring about 2 hours later. (2) In winter, fog along the Yangtze River primarily occurred in the Sichuan section (Yibin-Chongqing), the southwest and central sections of Chongqing (Chongqing-Wanzhou), followed by the Anhui section (Anqing-Hexian) and the Jiangsu section (Dantu-Taicang). (3)When fog was present along the river, the average 10-minute wind speed ranged from 0 to 3 m·s-1, occasionally exceeding 4 m·s-1. Northerly wind is the main wind, followed by easterly wind and westerly wind.(4) Mountainous areas along the Yangtze River exhibited a high proportion of rain and fog, with a notable frequency of thick fog, which was strongly correlated with precipitation. In contrast, in plain areas, radiation fog in early morning was more prevalent, and the occurrence of thick fog was often not directly linked to precipitation. The proportion of rain and fog in the eastern plain area was similar to that in mountainous areas, with relatively minor station-to-station fluctuations. (5) Strong fog weather events were associated with four primary near-surface weather situations: the low-pressure rear type, low-pressure trough type, weak high-pressure type, and high-pressure bottom type. Among them, the weak high-pressure type had the highest incidence, followed by the low-pressure trough type, while low-pressure rear type and high-pressure bottom type were less common.
During the winter of 2021/2022, the low SST (Sea Surface Temperature) in the equatorial Middle Eastern Pacific Ocean led to low temperature and increased precipitation in Guizhou Province. But the number of freezing days was generally lower, showing a phased distribution characteristic of weak in the early stage and strong in the later stage. Based on the daily observation data of 84 national meteorological stations in Guizhou Province, the reanalysis data of NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) and the SST data of NOAA (National Oceanic and Atmospheric Administration), the causes of freezing stages characteristics were analyzed from the aspects of SST field, height field, wind field, temperature field and water vapor condition. The results show that the southern branch frontal zone of the upper level was generally weak in the early stage and strong in the later stage, which provided a favorable large-scale circulation background for the freezing stage characteristics of Guizhou Province. After January 26, 2022, the stable maintenance of shear line in lower troposphere, and the abnormal strong of northerly airflow, which made the 0 ℃ isotherm moved southward obviously. At the same time, with the continuous enhancement of the southerly airflow, the water vapor convergence in the lower troposphere is also rapidly enhanced, and the unstable stratification and ascending motion of the low-level convergence and mid-level divergence were maintained, which provided favorable water vapor conditions for the stage characteristics of freezing in Guizhou Province. In the temperature field, the warm layer was relatively deep in the early stage, and the cold air was weak in the early stage and strong in the later stage, which provided favorable temperature conditions for the characteristics of freezing in Guizhou Province. However, due to the absence of the inversion layer in the whole winter, the intensity of the 3 regional freezing processes was relatively weak.
Based on ground conventional observation data and intensive observation data from automatic weather stations, cloud images of FY-2G satellite, Doppler radar data and ERA5 reanalysis data, the mesoscale synoptic characteristics of a extremely rainstorm process caused by convergence line frontogenesis in eastern and northern Guizhou on 10 May 2021 were analyzed, and the formation mechanism was preliminary discussed. The results show that the extremely rainstorm process occurred under the background of low vortex shear, and the strong southerly wind at low level transported abundant water vapor and unstable energy for the occurrence and development of the mesoscale convective system, the surface convergence line and its frontogenesis provided triggerring condition for the rainstorm. The rainstorm areas mainly occurred in the large gradient areas of temperature black body (TBB), in which were located on the west or south side of the low value center of cloud cluster TBB, and they appeared a strip-shaped distribution in east-west direction along the surface convergence line. The strongest precipitation occurred at the merging stage of convective cloud cluster. The frontogenesis caused by the convergence line frequently triggered convective cells on the west side of the convergence line, and the new convective cells moved and developed eastward along the surface convergence line, which continuously affected the eastern and northern regions of Guizhou Province. At two stages of the strongest precipitation, the warm cloud and overhang structure characteristics of radar echo were obvious. The surface convergence line and its frontogenesis, the cooling and increasing pressure generated by the upstream precipitation and continuously strengthening southerly wind were conducive to the enhancement of water vapor convergence in rainstorm areas. In the vertical direction, the ascending branches of meridional and zonal mesoscale secondary circulation were located near the extremely rainstorm center, which was conducive to the maintenance and enhancement of mesoscale convective system.
Two consecutive squall lines affected Zhejiang Province on 25 April 2022, causing a large-range wind disaster. The study of the occurrence and development of continuous squall lines is of important reference value for the forecast of such catastrophic weather. The development process and mechanism of two consecutive squall lines are analyzed by using ERA5 reanalysis data, observations of surface automatic meteorological stations, blackbody brightness temperature (TBB) and doppler radar data. The results show that the two consecutive squall lines (named “squall line 1” and “squall line 2”, according to the sequence of squall lines) developed in the upper jet stream divergence area, in front of the middle-level trough and in the warm zone in the south side of the low vortex at the lower level and at the top of the southwest jet stream axis. The squall line 1 was a medium β scale squall line triggered by the upper dry intrusion and the weak cold front near the surface in the early stage. The meso-scale convergence line caused by the bottom outflow and the strong inflow of southeast wind over the Hangzhou Bay and the vertical wind shear at the lower level promoted the squall line to strengthen gradually during its movement. The squall line 2 rose from the middle β scale to the middle α scale during the primary to mature stage. It was related to the migration of the upstream convective system in the early stage. Its formation was related to the migration of the upstream convective system in the early stage, affected by the upper dry intrusion, the vertical wind shear at the lower level, the convergence line of the weak cold front behind the squall line 1 and the merging of the upstream echoes, the upscaling phenomenon occurred in the mature stage. When the vertical wind shear decreased and the northern segment of the squall line 2 moved into the sea faster, the squall line 2 broke.
The research on the distribution of cloud water content and its evolution rules has important significance for the exploitation and utilization of regional cloud water resources. The paper analyzed the temporal variation characteristics of liquid water path (LWP) and integrated water vapor (IWV) in central Guanzhong Plain by using observation data of MWP967KV ground-based microwave radiometer at Jinghe station of Shaanxi Province from October 2017 to December 2020. Combined with ground precipitation and Doppler weather radar observation data, the development and evolution characteristics of water vapor and liquid water before precipitation in various cloud systems were compared by some cases study. The results indicate that the IWV exhibits obviously seasonal variations in central Guanzhong Plain, with the highest in summer, followed by autumn and spring, and the lowest in winter. Specifically, the peak appears in July, and the valley appears in December. The LWP is higher in autumn and summer, in winter it is the lowest. Notably, the peak is in September, and the valley is in December. The distribution of the IWV and LWP exhibits a single peak and single valley pattern over the course of a day, but the occurring time of their peak and valley is different. The diurnal maximum of the IWV occurs from 07:00 to 08:00 in summer and autumn, 23:00 in spring and 13:00 in winter, while the diurnal minimum of the IWV occurs at about 12:00 in spring, summer and autumn, 22:00 in winter. The diurnal maximum of the LWP occurs from 07:00 to 09:00 in spring, summer and autumn, while in winter it is slightly late (10:00). The diurnal minimum of the LWP appears at the nighttime in all seasons. The growth time of cloud water content before precipitation is different for different types of cloud systems. On average, the development time of stratiform cloud systems is 15.6 hours, and for other cumulus cloud systems it is 9.0 hours. In the initial stage, the IWV in both cloud systems varies prior to the LWP, and the fluctuation amplitude is increasingly violent as precipitation approaches. Additionally, the LWP in both cloud systems firstly exhibits a sudden violent increase before the rainfall being triggered, and the IWV and LWP in stratiform cloud system vary greatly in different seasons as precipitation is triggered. In the afternoon, the duration of strong convection developing is short, with an average time of 30 minutes. In the initial stage of development and before precipitation, the LWP varies and jumps sharply at the first.
Soil temperature and moisture are the important parameters in land surface process, and they are also important physical parameters in boundary conditions of atmospheric numerical model. This paper tried to obtain spatial-temporal evolution of soil moisture of the model through the machine learning method according to the memory characteristics of soil moisture. Considering the influence of soil temperature on soil moisture, the soil temperature and moisture of ERA5 reanalysis at depths of 0-7, 7-28, 28-100, 100-289 cm are used as predictors to predict changes of soil moisture on a monthly and seasonal scale based on convolutional neural networks (CNN). The results show that the method proposed in this paper is reliable and can effectively predict soil moisture 6 months in advance. The mean bias of predicted soil moisture in the shallow layer (0-28 cm) and deep layer (28-289 cm) is less than 0.05 and 0.02 m3·m-3, respectively. In the humid area, the mean bias is basically within 0.03 m3·m-3, showing a good effect.The prediction method and results presented in this paper can be used for both soil drought prediction and the initial and boundary conditions for numerical models.
Heilongjiang Province is the major grain production base in China, the study of drought climate characteristics in Heilongjiang Province is of great importance for scientific prevention and management of drought disasters. Based on daily temperature and precipitation data from 80 national meteorological stations in Heilongjiang Province from May to September during 1971-2020, the daily meteorological drought composite index (MCI) of Heilongjiang Province was calculated, and the spatial and temporal distribution characteristics of drought, severe drought and extreme drought days in Heilongjiang Province were analyzed. At the same time, the circulation characteristics of typical dry and wet years were further analyzed. The results show that from May to September during 1971-2020, the southern part of the Greater Hinggan Mountains and the western part of Songnen Plain in Heilongjiang Province are drought-prone areas. The number of dry days is more in the west and some areas of the central hinterland and less in the east. The inter-decadal characteristics of medium drought, severe drought and extreme drought are obvious and show a decreasing trend. The decreasing trend of medium drought was the most obvious with a rate of -1.7 d·(10 a)-1. There are significant differences in circulation patterns between typical dry years and wet years. In typical dry years, the area west of Lake Baikal is controlled by anticyclones, while Heilongjiang is controlled by the westerly jet stream, resulting in prevailing descending airflow, which is not conducive to the intersection of cold and warm air, and the water vapor transport channel is not obvious, so water vapor is difficult to reach the Heilongjiang region. Conversely, in typical wet years, the situation is the opposite.
Recently, the droughts attack frequently in the Yangtze River basin, resulting in more and more loss. To further improve regional drought risk management and drought resistance capabilities, it is of great significance to conduct research on the spatio-temporal evolution characteristics of drought in typical drought-prone areas. “Heng-Shao-Lou drought corridor” in Hunan Province is a region with most severe droughts, the standardized precipitation index (SPI) dataset based on monthly precipitation data from 33 meteorological stations in this area from 1971 to 2022 is constructed. Citing the case of Shaoyang County, run theory is applied to integrate drought events, and Gumbel-Copula is adopted to construct the joint distribution function of drought duration and severity, then the joint return periods of drought are calculated and the method is extended to the whole study area. On the basis of it, the classification standard of drought grades is established, and the spatial distribution characteristics of drought probability for each level in the whole study area are analyzed. The results show that the peaks of theoretical joint return period of drought duration and severity for the type Ⅰ and type Ⅱ in Shaoyang County are around 97 a and 27 a, respectively, which indicates that the probability of drought events with long duration and high severity is very small and far lower than that of drought events with long duration or high severity, it is a common feature of drought events in research area. Furthermore, the combination of drought duration and severity joint distribution can effectively avoid segmentation of the whole drought event when drought grades are identified by a single variable, and can evaluate the complexity and large-scale impact of drought more accurately. In the past 52 years, the slight drought occurs most frequently in western region of the “Heng-Shao-Lou drought corridor”, while the frequency of severe or extreme drought is low. Extreme drought mainly distributes in Shaoyang County, Shaodong County and Shuangfeng County.
Desertification has become a major threat to the global ecological environment, and the desertification monitoring is crucial for desertification prevention and control. Based on the Suomi/NPP (National Polar-orbiting Partnership) remote sensing data and the observation data of 8 meteorological stations during the vegetation growing season (from May to September) from 2014 to 2021 in the Qaidam Basin, the desertification difference index (DDI) was calculated by using NDVI-Albedo (Normalized Difference Vegetation Index-Albedo) feature space. Moreover, the natural discontinuity method, Sen+M-K trend analysis method, correlation analysis method, accuracy error matrix and transfer matrix analysis were also used to explore the spatial and temporal dynamic evolution of land desertification and the influence of meteorological factors to desertification in the Qaidam Basin from 2014 to 2020 during the vegetation growing season. The results are as follows: (1) The NDVI-Albedo feature space performs a high applicability in the Qaidam Basin (R2 greater than or equal to 0.65), with an overall classification accuracy of 79.38% and a Kappa coefficient of 0.62. (2) From 2014 to 2021, the degree of land desertification in the eastern and southern Qaidam Basin is lower than that in the western and central Qaidam Basin. Furthermore, DDI shows a significantly increase in some areas, especially in southern and eastern region with the increase rate of DDI over 0.01a-1. The total area of desertification land in the Qaidam Basin shows a decreasing trend with a rate of -1 173 km2·a-1. Additionally, a transforming characteristic occurs between different degrees desertification land that severe desertification lands transferred to mild desertification land. (3) Correlation analysis shows that precipitation and average relative humidity are significantly positively correlated with DDI (P<0.01), and correlation coefficients are 0.91 and 0.86, respectively, indicating that the water is the dominant factor affecting desertification in the Qaidam Basin.
The accurate identification of aerosol types is an important prerequisite for further research on its climatic and environmental effects. In this study, based on the observation data of ground-based dual-wavelength polarization lidar from the Semi-arid Climate and Environment Observation Station of Lanzhou University from October 2009 to November 2012, several cases were selected under four typical scenarios: clean day, anthropogenic pollutants, dust events and strong sandstorm events. The aerosol extinction coefficient, volume linear depolarization ratio and aerosol depolarization ratio were analyzed statistically, and the determination thresholds of different aerosol types were defined. The results show that the extinction coefficient of aerosol in this region is less than 0.085 km-1 on clean day. When the extinction coefficient is greater than 0.085 km-1, the volume linear depolarization ratio of anthropogenic pollutants is less than 0.07, and the corresponding aerosol depolarization ratio is less than 0.09. The volume linear depolarization ratio of polluted dust is between 0.07 and 0.22, and the aerosol depolarization ratio is between 0.09 and 0.31. The volume linear depolarization ratio of pure dust is greater than 0.22, and the aerosol depolarization ratio is greater than 0.31. In particular, when severe sandstorms occur, the volume linear depolarization ratio is greater than 0.35, and the aerosol depolarization ratio is greater than 0.49.
In order to scientifically determine the topographic relief characteristics of meteorological stations, based on the 30 m data of Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), the optimal analysis window of relief degree of land surface (RDLS) model in Sichuan Province was determined by using the mean change point analysis method. On this basis, the relief amplitude characteristics of surface meteorological observation stations in Sichuan Province were analyzed to explore the spatial pattern of the layout of meteorological stations. The results are as follows: (1) The best window for RDLS in Sichuan Province is 39 × 39 rectangular neighborhood pixels, with a corresponding area of about 1.369 km2. The established RDLS model is consistent with the trend of mountains and can capture the topographic relief of various scales, which accords with the topographic characteristics of Sichuan Province. (2) The terrain of national stations and regional stations is dominated by platforms, hills, and small undulating mountains. The proportion of national stations with small topographic undulations stations is significantly higher than that of regional stations, indicating that national stations are more representative of the region. (3) Suitable meteorological observation stations in Sichuan Province are mainly distributed the basin, in the north and west regions of the west Sichuan Plateau, as well as the eastern and southern parts of Panxi, accounting for 69.74% of the province’s total area. The analysis window area determined by the mean change point analysis method can take into consideration various geomorphic types, and the extracted RDLS can better reflect the topographic characteristics of meteorological stations, which can provide an important reference for the adaptive layout of meteorological stations and the optimization of station network.
The Three Gorges Reservoir area (TGRA), which is located in the hinterland of the Yangtze River Basin, is a typical area with frequent meteorological disasters and fragile ecological environment, especially the hourly heavy rainfall (HHR) in summer is prone to disasters due to suddenness and difficulty in prediction. Based on the hourly precipitation data in summer during 1992-2021 from the National Meteorological Information Center of China Meteorological Administration, the fine spatio-temporal distribution characteristics of HHR and heavy rainfall event (HRE) in the TGRA are investigated. The results show that the summer HHR in the TGRA has strong local features, its intensity is strong, and makes main contribution to total summer precipitation due to its high frequency. The southeastern TGRA is the center of summer HHR precipitation, frequency and intensity. In the past 30 years, the summer HHR precipitation in the TGRA has been non-significant increase. Both the diurnal variations of summer HHR precipitation and frequency in the TGRA show a bimodal pattern, with peaks appearing in the morning and afternoon, respectively, and the peak time phase is related to the terrain. Besides, the summer HREs in the TGRA are mainly short duration (1-6 hours), with precipitation mostly ranging from 20 to 60 mm, while the long duration (>12 hours) HREs seldom occur, with precipitation mostly ranging from 60 to 100 mm. Moreover, the short duration HREs mostly start in the afternoon, and most of their maximum hourly precipitation also occur in the afternoon, while the HREs with medium (7-12 hours) and long durations mostly start at night, and most of their maximum hourly precipitation occur in the morning.
Based on the detection data of airborne microwave radiometer GVR (G-band water Vapor Radiometer) and Hotwire Liquid Water Content Sensor, cloud top brightness temperature of FY-2E satellite, radar reflectivity at Tanggu station of Tianjin and FNL reanalysis data from NCEP (National Centers for Environment Prediction) and NCAR (National Center for Atmospheric Research) on 20 November 2016, the distribution characteristics of water vapor and liquid water for typical stratiform clouds in Tianjin area are analyzed. The results show that the liquid water path of stratiform clouds in Tianjin area decreases with the increase of height from the bottom of clouds, and it drops to 0 mm at the height of ice cloud and above. The integrated water vapor content gradually decreases from the ground with the increase of height, and its value holds at 0.3-0.5 cm during the level flight at 3 500 m above clouds. The density of liquid water increases firstly and then decreases with the increase of height. The liquid water detected by GVR above the cloud base (900 m) is supercooled water. During the ascent of aircraft, the supercooled water is mainly distributed at the height of 900-2 400 m, and the maximum density is 0.63 g·m-3. During the descent of aircraft, the supercooled water is mainly distributed at the height of 900-1 600 m, and the maximum density is 0.78 g·m-3. Compared with the Hotwire Liquid Water Content Sensor, GVR can better reflect the supercooled water content of clouds, the height and thickness of the supercooled layers. The water vapor in Tianjing area mainly comes from the advection transport. The water vapor density increases continuously at the height of 400 m, and accumulates obviously near the cloud base, and then decreases rapidly. Within the height of 1 400-3 000 m, the water vapor density fluctuates little. With the approaching of precipitation, the maximum value of water vapor density and its corresponding height increases during the descent of aircraft, and the thickness of the high water vapor density layer increases, which can provide some references for precipitation prediction and weather modification.
In order to study the development law and pollution characteristics of dust weathers, two strong sandstorm processes occurring in northern China in March 2021 (the processes on March 15 and 27, referred to as “3·15” process and “3·27” process, respectively) are analyzed based on polarized mie-scattering lidar observation data and hourly urban particulate mass concentration data in Shijiazhuang and Jinan. The results are as follows: (1) When the dust arrived, the mass concentration of PM10 in the two cities increased rapidly, and the mass concentration ratio of PM2.5 and PM10 decreased rapidly. (2) The PM10 mass concentration of the two cities conformed to the normal distribution during the two processes, and the determination coefficients of the Gaussian fitting of the PM10 mass concentration in Shijiazhuang and Jinan during the “3·15” process and the “3·27” process were 0.92 and 0.76, 0.83 and 0.89, respectively. (3) During the dust outbreak period, the extinction coefficient and depolarization ratio near the ground increased significantly. (4) Due to dust sedimentation and different sources of dust, a multi-layer structure appeared during dust transport, which can be divided into near-surface dust layer, low-altitude dust layer and high-altitude dust layer. The appearance time of near-surface dust layer was basically consistent with the sharp rise time of ground particle mass concentration. (5) At the height of 195 m (close to the ground and with reliable radar data quality), the maximum depolarization ratio in Shijiazhuang and Jinan during the “3·15” process (the“3·27” process) was 0.29, 0.28 (0.23, 0.20), and the maximum extinction coefficient was 3.94, 3.84 km-1 (3.10, 1.83 km-1), respectively, which showed that the strength of dust became weaker and the large particles decreased continuously during the transport process. The time when the depolarization ratio at this height began to rise rapidly was about 1 h earlier than the time when the mass concentration of ground particles began to rise rapidly. (6) According to the pollution characteristics of dust weather, its development can be divided into four stages: the early stage, the outbreak stage, the maintenance stage and the late stage. The different stages of dust can be well identified by comprehensive use of PM10 mass concentration, PM2.5 and PM10 mass concentration ratio, extinction coefficient and depolarization ratio.
Studying the impact of precipitation on PM2.5 mass concentration in different regions can provide an important scientific support for the air quality assessment and forecast as well as pollution prevention in this region. Based on the hourly precipitation observation data and PM2.5 mass concentration monitoring data in five typical cities (Chengdu, Leshan, Yibin, Mianyang and Dazhou) of Sichuan Basin from 2016 to 2021, the scavenging effect of precipitation processes on PM2.5 was analyzed in different cities from some aspects including the occurrence time, duration, intensity of precipitation and the initial mass concentration of PM2.5. The results show that the proportion of positive scavenging processes of precipitation on PM2.5 increases with the increase of precipitation intensity or initial mass concentration of PM2.5 in Sichuan Basin, and the scavenging rate rises. Under the condition of air pollution, the scavenging effect of precipitation with intensity exceeding 1 mm·h-1 on PM2.5 improves obviously in Sichuan Basin, and the scavenging rate reaches 35.0%. The scavenging effect is positively correlated with the duration of precipitation processes, and the scavenging rate of precipitation processes with the duration more than 3 hours is 9.0%-18.0% higher than that of precipitation processes with the duration less than or equal to 3 hours. The probability of positive scavenging processes is higher in the early morning and afternoon in Sichuan Basin, and the precipitation processes in the early morning have better scavenging effect on PM2.5. In comparison, the proportion of positive scavenging processes is higher in Leshan and Yibin after the precipitation, and under different initial mass concentrations of PM2.5, the scavenging rate is significantly higher than that in other cities with the increase of precipitation duration.
In order to improve the accuracy of rainstorm forecast and reduce the disaster losses caused by rainstorm, based on the ground conventional meteorological observation data, TBB (Black Body Temperature) data from satellite images and reanalysis data from National Centers for Environmental Prediction (NCEP), the synoptic causes of a strong convective rainstorm in Yunnan in August 2017 were analyzed. The results show that the eastward movement of 500 hPa trough, the southward movement of 700 hPa shear line and the westward movement of surface cold front are the synoptic background of this precipitation process. The mesoscale convective systems (MCS) on the Meso-α and Meso-β scales directly trigger the convective rainstorm. The heavy rainfall generally happens in the region with a high gradient of TBB. The MCS is closely related to 700 hPa wind shear line where is located to the east of Mid-Yunnan. The MCS is elliptically-shaped, developing along the neighboring and backside of the wind shear line. After the wind shear line getting close and cross over the Ailao Mountain, the MCSs distribute in a belt from northwest to southeast, and develop in front of the wind shear line. The wind shear line moves fast during the daytime before crossing over the Ailao Mountain, mainly producing thunderstorm weather while it moves slowly at nighttime, and the rainfall is strong. The forecast of strong convective rainstorm should focus on the large value area of water vapor flux convergence and the area where the temperature difference between 800 hPa and 500 hPa is greater than 20 ℃. During the heavy rainfall, the whole layer atmosphere is ascending, and the heavy rainfall area maintains the dynamic pumping mechanism of convergence at lower level and divergence at middle and upper levels.
Exploring the spatial and temporal distribution characteristics of heat resources utilization efficiency of summer maize in growth season could provide theoretical basis for the adjustment of summer maize variety layout and guarantee of a high and stable maize yield. Based on the daily meteorological data of 15 agricultural meteorological observation stations from 1981 to 2019, and the observation data of the growing period of summer maize and wheat in the later crop rotation in Hebei Province, the regression analysis and spatial interpolation methods are used to analyze the spatial and temporal variations of heat resources utilization efficiency of summer maize in growth season under climate change. The results show that the potential growing days of summer maize in Hebei Province had no significant change from 1981 to 2019, while the potential accumulated temperature increased significantly (P<0.05). The utilization efficiency of heat resources during growth season increased significantly (P<0.05), the utilization efficiency of growing days increased from 80.4% in 1981 to 94.5% in 2019, and the utilization efficiency of accumulated temperature increased from 84.5% in 1981 to 94.9% in 2019. The potential growing days and accumulated temperature of summer maize were more in the south and less in the north, and the utilization efficiency of growing days and accumulated temperature were lower in the south and higher in the north. There was higher utilization efficiency (more than 95%) of growing days and accumulated temperature in Langfang, while in Handan the utilization efficiency of growing days was lower (less than 85%). The accumulated temperature of summer maize increased at a rate of 19.6 ℃·d·(10 a)-1 before anthesis and 58.7 ℃·d·(10 a)-1 after anthesis. The increase rate of accumulated temperature after anthesis was obviously higher than that before anthesis, and the ratio of accumulated temperature showed an obvious downward trend, it fell 28.5% from 1.6 in 1981 to 1.1 in 2019. The results demonstrate that the utilization efficiency of climate resources of summer maize in the southern Hebei had some space for improvement. The medium and late maturing varieties with a longer growing season could be selected, and the varieties with a longer filling stage could be selected for breeding or cultivation, so as to make full use of the heat conditions in the growing season and improve maize yield.
In order to scientifically manage grape being covered with soil to over winter, based on the ground temperature observation data of 10 vineyards at the eastern foot of the Helan Mountain in Ningxia in the winter of 2021/2022, the variation characteristics of daily mean ground temperature and the thermal diffusivity of 10-20 cm soil in different vineyards at the eastern foot of the Helan Mountain were analyzed. The results are show that in winter, the soil temperature decreased firstly and then increased, and soil temperature increased with the increase of depth. The temperature fluctuation of deep soil was smaller than that of surface soil, and the changing trend also lagged behind that of surface soil. The heat conduction method can well simulate the soil temperature of 10 cm and 20 cm in the eastern foot of the Helan Mountain in winter, and the effect of 20 cm soil temperature is the best, with the regression correction coefficient reaching 0.947 5. The soil thermal diffusivity (k) of vineyards in the eastern foot of the Helan Mountain in winter was generally higher. There were some differences of k value in each vineyard, the soil thermal diffusivities of Hedong Manor in Dawukou district at the north end of the producing region and St. Louis winery in Yongning county to the east were small, and the average k value was 6.11×10-6 and 4.53×10-6 m2·s-1, respectively. However, the thermal diffusivities in Guanlan Winery, Xige Winery, Legacy Peak Estate, Hennessy Winery near the Helan Mountain, D.F.Yuxing Winery and Pink Carrin Winery at the southern end of the producing region were larger, with average k values of 11.08×10-6 to 14.94×10-6 m2·s-1. The average k values of Emperial Horse and Meiyu Wineries were 9.63×10-6 and 8.52×10-6 m2·s-1, respectively.
In order to seek a suitable irrigation water source in the Tao river irrigation area of Dingxi of Gansu Province, this study adopts a completely randomized treatment design and sets three irrigation water sources including local shallow underground water and the Tao river irrigation and their alternative irrigation, among the underground water irrigation as a control treatment, and the effects of different irrigation water sources on celery growth characteristics, water consumption, yield, water use efficiency and economic benefits are explored in semi-arid region. The results show that compared with underground water irrigation, the plant height of celery under the Tao river irrigation and alternative irrigation both underground water and the Tao river decreases by 6.07 cm and 3.33 cm, the stem thicknesses decrease by 1.22 mm and 0.78 mm, the soil water storage decrease by 1.27% and 1.98%, the yields of celery decrease by 15.08% and 1.57%, the water use efficiency decrease by 15.53% and 2.46%, and the irrigation water use efficiency decrease by 15.46% and 2.01%, respectively, while the total water consumption increase by 0.09% and 0.47%, and the net income of celery increase by 3.1% and 18.0%, respectively. The increase of celery yields is the most obvious under the underground water irrigation, but its water cost is the most expensive, so its economic benefit is lower. Although the celery yields and water use efficiency under the alternative irrigation are slightly lower than that under the underground water irrigation, the water cost reduced greatly, so the economic benefit is the highest. The water cost under the Tao river irrigation is low, but its economic benefit increase slightly due to all indexes of celery decreasing significantly (P<0.05). In summary, the alternative irrigation both underground water and the Tao river can be used as a feasible and effective irrigation mode to increase production and income of farmers in the Tao river irrigation area of Dingxi.
Soil temperature reflects the thermal state of soil and plays a crucial role in the exchange of surface energy, and it directly influences the water and heat redistribution of soil. In alpine mountainous area, the hydrological and energy transfers are more special and complex. Therefore, it is essential to simulate accurately soil temperature in investigating hydrological cycles in alpine mountainous areas. CLM 5.0 (Community Land Model 5.0) is the latest version of the CLM model, which is one of the most advanced land surface process models in the world. In this paper, the soil temperature simulation performance of CLM 5.0 is evaluated based on the measured data of 9 typical observation stations in the upper reaches of the Heihe River Basin. The results are as follows: (1) CLM 5.0 can well simulate the annual and inter-annual changes of soil temperature in alpine mountainous areas, but the simulated values are generally underestimated. (2) The simulation performance of CLM 5.0 on soil temperature in alpine meadow is slightly higher than that in grassland, and it in shallow soil layers is better than in deep soil layers. (3) CLM 5.0 exhibits greater underestimation to soil temperature in the non-growth period than in the growth period, and greater underestimation under frozen state than under unfrozen state. (4) The underestimation of CLM 5.0 simulated soil temperature in the non-growth period is mainly due to the underestimation of soil temperature under frozen state, which results from errors in estimating soil ice. These results provide insights for future applications and improvements of CLM 5.0 in alpine mountainous areas.
Located in the middle zone between the Tibetan Plateau and the Bay of Bengal, the Indian Peninsula and the Indo-China Peninsula, the Bengal region is the first region affected by the outbreak of the Asian monsoon. The change of water vapor in the Bengal region is of great significance to the climate of South Asia and East Asia. The causes and possible physical processes of the atmospheric precipitable water (APW) change in summer (June-September) in the Bengal region are analyzed using the ERA5 reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF) and sea surface temperature data from the National Oceanic and Atmosphere Administration (NOAA) from 1979 to 2020. The results show that APW in the Bengal region is the largest at the same latitude in southern Asia. The summer APW accounts for more than 50% of the whole year, and the average summer APW presents a significant increase trend. According to the whole layer water vapor budgets and water vapor budget vertical profiles of the four boundaries of the Bengal region, the trends of the whole layer water vapor budgets of the eastern and southern boundaries are favorable to the increase of APW there, while the trends of the whole layer water vapor budgets of the western and northern boundaries are unfavorable to the increase of APW there. The summer APW in the Bengal region is negatively correlated with the interdecadal Pacific oscillation (IPO) on both inter-annual and inter-decadal scales. When the IPO is in its positive phase, in the lower troposphere, the westerly (easterly) wind anomaly prevails in the equatorial Pacific (equatorial Indian Ocean), while it is the opposite in the upper troposphere, indicating a weakening of the Walker circulation over the Indian and Pacific Oceans. The Gill-type anticyclonic circulation anomaly is observed in the lower troposphere in the north and south sides of the equatorial Indian Ocean. The Indian monsoon is weak, and a northwest wind anomaly prevails from the Arabian Peninsula to the Bengal region. The westerly airflow is not conducive to the transport of water vapor to the Bengal region, while the sinking airflow accompanying the anticyclonic circulation is not conducive to the convergence of water vapor in this region, resulting in the reduction of APW in the Bengal region. On the contrary, when the IPO is in a negative phase, it is favorable for the increase of APW in the Bengal region in summer.
The climate in the Yellow River Basin has undergone significant changes in recent years, which has a significant impact on surface hydrological and ecological processes in the basin. Studying the spatial and temporal variation of evapotranspiration in the Yellow River Basin is indicative for understanding deeply land-atmosphere interactions and regional water resources management. In this paper, the appliability of ERA5-Land evapotranspiration in the Yellow River Basin was evaluated using in-situ observations of Haibei, SACOL (Semi-Arid Climate and Environment Observatory) and Yucheng stations which are selected as representative stations from the source region, Hetao region and the lower reach of the Yellow River Basin, respectively. Then based on monthly latent heat flux from ERA5-Land data, the spatial and temporal variation of evapotranspiration in the Yellow River Basin in the past 42 years (1980-2021) are analyzed using EOF (Emipirical Orthogonal Function), power spectrum and regression analysis methods. The results show that ERA5-Land data can reflect the variation characteristics of evapotranspiration at Haibei, SACOL and Yucheng stations with good correlation and small error and root mean square deviation, which is applicable for the analysis on spatial and temporal variation of evapotranspiration in the Yellow River Basin. There are multi-timescale variations of evapotranspiration in different regions of the Yellow River Basin, with significant oscillation periods of main 5 a and 15 a, and obvious inter-annual and inter-decadal variations. The first mode in different regions of the Yellow River Basin characterizes the consistency in spatial distribution, which decreases around 2004. The second mode is dipole distribution, indicating the reverse change in space. The deceleration of evapotranspiration in the Yellow River Basin in the past 42 years is not same in different regions, with the fastest rate of -3.74 mm·a-1 in the lower reaches and -2.82 mm·a-1 in the Hetao area, while the deceleration in the source area is relatively gentle. The summer evapotranspiration variability is the largest, and the deceleration is faster in the Hetao area and the lower reaches. The winter evapotranspiration variability is smaller, but the source area has the largest winter evapotranspiration deceleration of -0.48 mm·a-1.
In order to make an in-depth study of urban thermal environment of Zhengzhou, the temporal evolution and spatial distribution characteristics of urban heat island effect are analyzed based on the MODIS land surface temperature product (MYD21A1), and the causes and driving mechanism of urban heat island effect are discussed from both natural and anthropogenic factors in combination with the data of land use/land cover types and Zhengzhou statistical yearbooks. The results show that there is no significant difference in the spatial distribution of annual mean heat island intensity between day and night in Zhengzhou, and the areas with stronger heat island intensity or above are mainly in the main urban area. The temporal variation of heat island effect in Zhengzhou has diurnal and seasonal differences. During the daytime, the proportion of heat island area increased insignificantly in spring and significantly in summer, and decreased insignificantly in autumn and winter. In spring, summer and autumn, the proportion of heat island area at night increased insignificantly, while in winter, the heat island effect was weak and there was no obvious change characteristics. The inter-annual variation of urban heat island proportion index of Zhengzhou was consistent with heat island intensity. The urban heat island proportion index during daytime and nighttime was higher in summer, then in spring, autumn and winter in turn. The heat island effect of different land use/land cover types was obviously different, with the highest in urban and rural building land, followed by cultivated land, and the lowest in woodland and water area. There is a negative correlation between vegetation coverage and land surface temperature. Solar radiation intensity has a positive driving effect on urban heat island effect, and population density, GDP and built-up area are all positively correlated with urban land surface temperature.