Plant life form determines spatiotemporal variability and climate response of plant seed rain in subtropical forests

Spatiotemporal variation of seed rain reflects the response of plants in terms of their reproductive strategy to environmental gradients.In this study,we collected seeds from four sites in the Dalaoling Nature Reserve,Hubei Province,China,between 2011 and 2014,measured seed output and seed mass as seed rain traits,and compared their interannual and elevational variation.Then,we ran phylogenetic generalized mixed linear models(PGLMMs) to explore the effects of temperature and precipitation as well as interspecific differences on seed rain,and fitted the best regression models for seed rain vs.weather of canopy and understory species.The results showed no correlation between values of seed output and seed mass.However,the variation of the two traits showed significantly positive correlation.Seed output of canopy species generally decreased with increasing elevation,and showed significant interannual difference;however,seed output of understory species and seed mass for both canopy and understory species did not show consistency tends along elevational or in interannual variation.Seed output was significantly affected by temperature and precipitation,while seed mass mainly varied due to interspecific differences.Weather explained more the variation of the seed output of canopy species than that of understory species,with R^(2) values of 43.0%and 29.9%,respectively.These results suggested that canopy plants contributed more to the reproductive dynamics of the whole communities,and the canopy's buffer effect on the underground weakened the response of understory plants to weather variation in terms of their reproductive strategy.

RAIN-128算法的中间相遇攻击

RAIN是一族SPN结构的轻量级分组密码算法,该算法具有软硬件实现效率高、安_全性强等特点。中间相遇攻击被广泛应用于分组密码算法的安全性分析中。该文通过分析RAIN-128的结构特性和截断差分特征,利用差分枚举技术分别构造了4轮和6轮中间相遇区分器,给出了8轮及10轮的中间相遇攻击。当攻击轮数为8轮时,预计算阶段的时间复杂度为2^(68)次8轮RAIN-128加密,存储复杂度为2^(75)bit,在线攻击阶段的时间复杂度为2^(109)次8轮加密,数据复杂度是2^(72)个选择明文;当攻击轮数为10轮时,预计算阶段的时间复杂度为2^(214)次10轮加密,存储复杂度为2^(219)bit,在线攻击阶段的时间复杂度为2^(109)次10轮加密,数据复杂度是2^(72)个选择明文,分析结果显示,RAIN-128可以抵抗中间相遇攻击,并具有较高的安全冗余。

Diagnosis of the Kinetic Energy of the“21·7”Extreme Torrential Rainfall Event in Henan Province,China

An extreme torrential rain(ETR)event occurred in Henan Province,China,during 18-21 July 2021.Based on hourly rain-gauge observations and ERA5 reanalysis data,the ETR was studied from the perspective of kinetic energy(K),which can be divided into rotational wind(V_(R))kinetic energy(K_(R)),divergent wind kinetic energy(K_(D)),and the kinetic energy of the interaction between the divergent and rotational winds(K_(RD)).According to the hourly precipitation intensity variability,the ETR process was divided into an initial stage,a rapid increase stage,and maintenance stage.Results showed that the intensification and maintenance of ETR were closely related to the upper-level K,and most closely related to the upperlevel K_(R),with a correlation coefficient of up to 0.9.In particular,the peak value of hourly rainfall intensity lagged behind the K_(R) by 8 h.Furthermore,diagnosis showed that K transformation from unresolvable to resolvable scales made the ETR increase slowly.The meridional rotational wind(u_(R))and meridional gradient of the geopotential(φ)jointly determined the conversion of available potential energy(APE)to K_(R) through the barotropic process,which dominated the rapid enhancement of K_(R) and then caused the rapid increase in ETR.The transportation of K by rotational wind consumed K_(R),and basically offset the K_(R) produced by the barotropic process,which basically kept K_(R) stable at a high value,thus maintaining the ETR.

Spatiotemporal characteristics of seed rain and soil seed bank of artificial Caragana korshinskii Kom. forest in the Tengger Desert, China

Vegetation restoration and reconstruction are effective approaches to desertification control and achieving social and economic sustainability in desert areas.However,the self-succession ability of native plants during the later periods of vegetation restoration remains unclear.Therefore,this study was conducted to bridge the knowledge gap by investigating the regeneration dynamics of artificial forest under natural conditions.The information of seed rain and soil seed bank was collected and quantified from an artificial Caragana korshinskii Kom.forest in the Tengger Desert,China.The germination tests were conducted in a laboratory setting.The analysis of species quantity and diversity in seed rain and soil seed bank was conducted to assess the impact of different durations of sand fixation(60,40,and 20 a)on the progress of vegetation restoration and ecological conditions in artificial C.korshinskii forest.The results showed that the top three dominant plant species in seed rain were Echinops gmelinii Turcz.,Eragrostis minor Host.,and Agropyron mongolicum Keng.,and the top three dominant plant species in soil seed bank were E.minor,Chloris virgata Sw.,and E.gmelinii.As restoration period increased,the density of seed rain and soil seed bank increased first and then decreased.While for species richness,as restoration period increased,it gradually increased in seed rain but decreased in soil seed bank.There was a positive correlation between seed rain density and soil seed bank density among all the three restoration periods.The species similarity between seed rain or soil seed bank and aboveground vegetation decreased with the extension of restoration period.The shape of the seeds,specifically those with external appendages such as spines and crown hair,clearly had an effect on their dispersal,then resulting in lower seed density in soil seed bank.In addition,precipitation was a crucial factor in promoting rapid germination,also resulting in lower seed density in soil seed bank.Our findings provide valuable insights for guiding future interventions during the later periods of artificial C.korshinskii forest,such as sowing and restoration efforts using unmanned aerial vehicles.

Mesoscale and Microphysical Characteristics of a Double Rain Belt Event in South China on May 10–13,2022

A second rain belt sometimes occurs ahead of a frontal rain belt in the warm sector over coastal South China,leading to heavy precipitation.We examined the differences in the mesoscale characteristics and microphysics of the frontal and warm sector rain belts that occurred in South China on May 10–13,2022.The southern rain belt occurred in an environment with favorable mesoscale conditions but weak large-scale forcing.In contrast,the northern rain belt was related to low-level horizontal shear and the surface-level front.The interaction between the enhanced southeasterly winds and the rainfall-induced cold pool promoted the persistent growth of convection along the southern rain belt.The convective cell propagated east over the coastal area,where there was a large temperature gradient.The bow-shaped echo in this region may be closely related to the rear-inflow jet.By contrast,the initial convection of the northern rain belt was triggered along the front and the region of low-level horizontal shear,with mesoscale interactions between the enhanced warm-moist southeasterly airflow and the cold dome associated with the earlier rain.The terrain blocked the movement of the cold pool,resulting in the stagnation of the frontal convective cell at an early stage.Subsequently,a meso-γ-scale vortex formed during the rapid movement of the convective cell,corresponding to an enhancement of precipitation.The representative raindrop spectra for the southern rain belt were characterized by a greater number and higher density of raindrops than the northern rain belt,even though both resulted in comparable hourly rainfalls.These results help us better understand the characteristics of double rain belts over South China.

Effect Evaluation of CBL Combined with Rain Classroom Teaching Method in Medical Statistics

Objective: To explore the application effect of CBL combined with rain classroom teaching method in medical statistics courses. Methods: The undergraduate students of medical imaging technology in 2019 and 2020 in a university were selected as the research objects. A cluster sampling method was used to select 79 undergraduate students from 2019 in the control group and 75 undergraduate students from 2020 in the experimental group. Traditional teaching method and CBL combined with rain classroom teaching method was used in the control group and experimental group respectively. The final examination scores of the two groups were compared. In experimental group, the correlation between the average score in the rain classroom and the final examination score was tested, and the teaching effect was evaluated. Results: The average score of final examination in experimental group and control group was 79.13 ± 10.32 points and 71.54 ± 14.752 points, respectively, which had a statistically significant difference (Z = 2.586, P = 0.012);the final examination scores of the students in the experimental group were positively correlated with the average scores of the rain classroom (r = 0.372, P = 0.001), and the proportion of satisfaction in the experimental group was 94.7%. Conclusion: The CBL combined with rain classroom teaching method can improve the teaching effectiveness of medical statistics courses.

Towards Robust Rain Removal with Unet

Image deraining has become a hot topic in the field of computervision. It is the process of removing rain streaks from an image to reconstructa high-quality background. This study aims at improving the performance ofimage rain streak removal and reducing the disruptive effects caused by rain.To better fit the rain removal task, an innovative image deraining method isproposed, where a kernel prediction network with Unet++ is designed andused to filter rainy images, and rainy-day images are used to estimate thepixel-level kernel for rain removal. To minimize the gap between synthetic andreal data and improve the performance in real rainy image handling, a lossfunction and an effective data optimization method are suggested. In contrastwith other methods, the loss function consists of Structural Similarity Indexloss, edge loss, and L1 loss, and it is adopted to improve performance. Theproposed algorithm can improve the Peak Signal-to-Noise ratio by 1.3% whencompared to conventional approaches. Experimental results indicate that theproposed method can achieve a better efficiency and preserve more imagestructure than several classical methods.

Predecessor Rain Events in the Yangtze River Delta Region Associated with South China Sea and Northwest Pacific Ocean(SCS-WNPO)Tropical Cyclones

Predecessor rain events(PREs) in the Yangtze River Delta(YRD) region associated with the South China Sea and Northwest Pacific Ocean(SCS-WNPO) tropical cyclones(TCs) are investigated during the period from 2010 to 2019.Results indicate that approximately 10% of TCs making landfall in China produce PREs over the YRD region;however,they are seldom forecasted. PREs often occur over the YRD region when TCs begin to be active in the SCS-WNPO with westward paths, whilst the cold air is still existing or beginning to be present. PREs are more likely to peak in June and September. The distances between the PRE centers and the parent TC range from 900 to 1700 km. The median value of rain amounts and the median lifetime of PREs is approximately 200 mm and 24 h, respectively. Composite results suggest that PREs form in the equatorward jet-entrance region of the upper-level westerly jet(WJ), where a 925-hPa equivalent potential temperature ridge is located east of a 500-hPa trough. Deep moisture is transported from the TC vicinity to the remote PREs region. The ascent of this deep moist air in front of the 500-hPa trough and frontogenesis beneath the equatorward entrance region of the WJ is advantageous for the occurrence of PREs in the YRD region. The upper-level WJ may be affected by the subtropical high and westerly trough in the Northwest Pacific Ocean, and the occurrence of PREs may favor the maintenance of the upper-level WJ. The upper-level outflow of TCs in the SCS plays a secondary role.

Analysis, Variability and Rainfall Prediction in Sub-Saharan Africa: The Case of the Lake Guiers in Senegal

The aim of this article is to predict the rainfall evolution of a sub-Saharan area in which one of the most important freshwater resources is located: Lake Guiers. Characterized by short seasonal rains of three months, it experienced a long period of drought in the 1970s. We begin by analyzing the temporal distribution of the rainfall including the variability of the data, with a view to predicting a possible return. For this reason, we present here univariate modeling results of rainfall series collected on three stations in the area. The challenge lies in the adequacy of the parameters for the monthly rainfall series, which generates more or less significant forecast errors on the learning bases because of the missing data. This later motivated their conversion to moving average series. On the other hand, the normality of the latter seems to be rejected by the D’Agostino test. Student’s and Mann-Whitney’s tests confirmed the homogeneity. The autocorlograms show the presence of autoregressive terms in the data. Dickey-Fuller and Mann-Kendall tests reveal both trend and seasonality. The stationarity tests of Dickey-Fuller, Phillips-Perron and KPSS have shown that they are non-stationary. As a result, we did an ARIMA modeling method using the Box-Jenkins [1] method with the R software, which involves estimating model parameters, tests of significance, analysis of residualss, selection according to information criteria and forecasts. The results obtained during the learning-test phase showed a quasi-similarity of the base-tests in all the series except for that of Louga.

Analysis of Rainstorm Process in South China from September 7 to 8, 2022

Based on the NCEP data of the United States, a rainstorm process in South China during September 7 to 8, 2022 was studied. Synoptic method is a qualitative and empirical forecasting method. The results show that: In early September 2022, the cold air behind the trough line from northeast China to North China can directly drive southward and invade South China from the east road. Typhoon Hinnamnor is located in the saddle field between the mainland subtropical high and the offshore subtropical high. It moves northward on the west side of the coastal subtropical high, affecting the Taiwan Island and the coastal areas of East China. During September 7-8, the wave trough of the 925 hPa Easterly wave was located near 110°E. Easterly jet existed in the southeast of South China. The center of the easterly jet was located to the east of Hainan Island, which could transport abundant water vapor from the sea surface to the sky over South China. The precipitable water in the whole layer of the atmosphere decreased from the southern coastal areas to the north, reaching more than 50 mm in southern China, of which most of the South China Sea, Hainan Island and parts of the western part of Guangdong Province exceeded 60 mm, providing sufficient water vapor supply. The circulation field with convergence at low level and divergence at high level is conducive to vertical uplift to form precipitation.

Rainfall Monitoring Using a Microwave Links Network:A Long-Term Experiment in East China

The first long-term rainfall monitoring experiment using the commercial microwave links(CMLs)network in East China is introduced.The network,located in Jiangyin,Jiangsu Province,consists of 49 links with frequencies ranging from 15 GHz to 26 GHz and lengths from 1.14 km to 4.78 km.An OTT PARSIVEL disdrometer is deployed to refine the local rain-induced attenuation relationship,and the CML observations are compared simultaneously with five rain gauges.The inversion parameters of the CML are optimized by minimizing the error of the accumulated rainfall of historical rainfall events.The inversion results show that the daily accumulated rainfall retrieved by the CMLs agrees well with the rain gauge measurements.As an opportunistic approach to monitor near-surface rainfall with high spatiotemporal representativeness and accuracy,the CML network can be used to monitor and forecast urban flood disasters,especially in regions where the widepread deployment of conventional meteorological instruments is impractical.

Analysis of Precipitation Anomaly and a Failed Prediction During the Dragon-boat Rain Period in 2022

This study investigates the possible causes for the precipitation of Guangdong during dragon-boat rain period(DBRP) in 2022 that is remarkably more than the climate state and reviews the successes and failures of the prediction in2022. Features of atmospheric circulation and sea surface temperature(SST) are analyzed based on several observational datasets for nearly 60 years from meteorological stations and the NCEP/NCAR Global Reanalysis Data. Results show that fluctuation of the 200-h Pa westerly wind as well as the westerly jet is strengthened due to the propagation of wave energy, leading to strong updraft over southern China. Activities of a subtropical high and a shear line provide favorable conditions for the transport of moisture to Guangdong. With the support of powerful southwest winds, extreme precipitation is induced. ENSO is a good indicator of atmospheric circulation at mid-and high-levels during the DBRP in2022 but it performs badly at low levels. During recent years, the influence of ENSO on precipitation during the DBRP has decreased obviously. The SSTA of tropical southeast Atlantic(SEA) in spring may become the key indicator. During the years with warm SEA, wave trains propagate from northwest to southeast over Eurasia with energy enhancing the westerly jet, conducive to updraft over southern China and the occurrence of heavy precipitation. Meanwhile, the Rossby wave is triggered over Maritime Continent by heat sources of southern Atlantic-western Indian Ocean through the Gill response. Thus, strong transport of moisture and heavy rainfall occur.

Thermodynamics and Microphysical Characteristics of an Extreme Rainfall Event Under the Influence of a Low-level Jet over the South China Coast

In this paper,the data of Automatic Weather Stations(AWSs),ERA5 reanalysis,sounding,wind profile radar,and dual-polarization radar are used to study an extreme rainfall event in the south China Coast on 11 to 12 May 2022 from the aspects of thermodynamics and microphysical characteristics under the influence of low-level jets(LLJs).Results show that:(1)The extreme rainfall event can be divided into two stages:the first stage(S1)from 0000 to 0600 LST on May 12 and the second stage(S2)from 0700 to 1700 LST on the same day.During S1,the rainfall is mainly caused by the upper-level shortwave trough and the boundary layer jet(BLJ),characterized by strong upward motion on the windward side of mountains.In S2,the combined influence of the BLJ and synoptic-system-related low-level jet(SLLJ)increases the vertical wind shear and vertical vorticity,strengthening the rainstorm.In combination with the effect of topography,a warm and humid southwest flow continuously transports water vapor to farther north,resulting in a significant increase in rainfall over the study area(on the terrain’s windward slope).From S1 to S2,the altitude of a divergence center in the upper air decreases obviously.(2)The rainfalls in the two stages are both associated with the mesoscale convergence line(MCL)on the surface,and the wind field from the mesoscale outflow boundary(MOB)in S1 is in the same direction as the environmental winds.Due to a small area of convergence that is left behind the MOB,convection moves eastward quickly and causes a short duration of heavy rainfall.In S2,the convergence along the MOB is enhanced,which strengthens the rainfall and leads to strong outflows,further enhancing the surface convergence near the MOB and forming a positive feedback mechanism.It results in a slow motion of convection and a long duration of heavy rainfall.(3)In terms of microphysics,the center of a strong echo in S1 is higher than in S2.The warm-rain process of the oceanic type characterizes both stages,but the convective intensity in S2 is significantly stronger than that in S1,featuring bigger drop sizes and lower concentrations.It is mainly due to the strengthening of LLJs,which makes small cloud droplets lift to melting levels,enhancing the ice phase process(riming process),producing large amounts of graupel particles and enhancing the melting and collision processes as they fall,resulting in the increase of liquid water content(LWC)and the formation of large raindrops near the surface.

Variability of Raindrop Size Distribution during a Regional Freezing Rain Event in the Jianghan Plain of Central China

The characteristics of the raindrop size distribution(DSD)during regional freezing rain(FR)events that occur throughout the phase change(from liquid to solid)are poorly understood due to limited observations.We investigate the evolution of microphysical parameters and the key formation mechanisms of regional FR using the DSDs from five disdrometer sites in January 2018 in the Jianghan Plain(JHP)of Central China.FR is identified via the size and velocity distribution measured from a disdrometer,the discrete Fréchet distancemethod,surface temperature,human observations,and sounding data.With the persistence of precipitation,the emergence of graupel or snowflakes significantly reduces the proportion of FR.The enhancement of this regional FR event is mainly dominated by the increase in the number concentration of raindrops but weakly affected by the diameters.To improve the accuracy of quantitative precipitation estimation for the FR event,a modified second-degree polynomial relation between the shapeμand slopeΛof gamma DSDs is derived,and a new Z-R(radar reflectivity to rain rate)relationship is developed.The mean values of mass-weighted mean diameters(D_(m))and generalized intercepts(lgN_(w))in FR are close to the stratiform results in the northern region of China.Both the melting of tiny-rimed graupels and large-dry snowflakes are a response to the formation of this regional FR process in the JHP,dominated by the joint influence of the physical mechanism of warm rain,vapor deposition,and aggregation/riming coupled with the effect of weak convective motion in some periods.

Characteristic Analysis of Short Time Heavy Rain in Yulin, China

National Centers for Environment Prediction (NCEP) reanalysis data, automatic observation data, FY-2E satellite data and Doppler radar data are used to analyze a short-time local heavy rain in Yulin city, Shaanxi, China on August 7, 2018. The result shows that the strong convective weather occurred in peripheral subtropical high over west pacific, being caused by short wave disturbance, and surface convergence lines with positive pressure variation are corresponding to areas of short-time heavy precipitation. The degree of temperature change in cold pool caused by thunderstorm may decide the intensity of a short-time rainfall, and local topography plays an important role in extreme precipitation. Local water vapour accumulation and water vapour flux convergence in the middle and lower layers support adequate moisture condition in the process. Moving direction and development direction of mesocale convective cloud are in a line to develop the train effect, leading to local short-time heavy rain in Yulin city, Shaanxi, China.

Unrolling a rain-guided detail recovery network for single-image deraining

Background Owing to the rapid development of deep networks, single-image deraining tasks have progressed significantly. Various architectures have been designed to recursively or directly remove rain, and most rain streaks can be removed using existing deraining methods. However, many of them cause detail loss, resulting in visual artifacts. Method To resolve this issue, we propose a novel unrolling rain-guided detail recovery network(URDRN) for single-image deraining based on the observation that the most degraded areas of a background image tend to be the most rain-corrupted regions. Furthermore, to address the problem that most existing deep-learningbased methods trivialize the observation model and simply learn end-to-end mapping, the proposed URDRN unrolls a single-image deraining task into two subproblems: rain extraction and detail recovery. Result Specifically, first, a context aggregation attention network is introduced to effectively extract rain streaks;thereafter, a rain attention map is generated as an indicator to guide the detail recovery process. For the detail recovery sub-network, with the guidance of the rain attention map, a simple encoder–decoder model is sufficient to recover the lost details.Experiments on several well-known benchmark datasets show that the proposed approach can achieve performance similar to those of other state-of-the-art methods.

Pacific Sea Surface Temperature Effect Summer Rainfall in Huanghuai, Jianghuai Region in China

Summer Precipitation in Eastern China was closely related to the global sea surface temperature field. In this paper, the impact of the main sea surface temperature anomaly on flood season precipitation in China’s Huanghuai and Jianghuai regions is examined as an external forcing factor for short-term climate prediction. Through analysis of global sea surface temperature anomalies and regional anomalies in Huanghuai and Jianghuai, a significant effect related to the main area, the North Pacific region, and the Nino3 corresponding index calculation is found. Various key areas are examined for their relevance, and finally, the mechanism of summer precipitation in two key zones, China’s Huanghuai and Jianghuai regions, is briefly discussed. The main implication is the prediction of season precipitation based on the external forcing signal of sea surface temperature anomaly in China’s Huanghuai and Jianghuai regions.

Enhancement of East African Monsoon Long Rainfall (March to May) Variability from Weekly to Annual Scale by Climatic Extremes

As global warming increasingly affects vulnerable regions such as Central East Africa, it is crucial to understand future changes in rainfall variability to reduce vulnerability. Despite the importance of rainfall variability, it has received less attention compared to changes in mean and extreme rainfall. This study evaluates the amplification of synoptic (weekly) to annual variability of East African Monsoon (EAM) Long Rainfall (March to May) by climatic extremes. Using band-pass filtered daily rainfall data, we found that EAM rainfall variability is anticipated to increase by 20% - 60% across the region under global warming conditions. The majority of the intermodal variability in Long Rain EAM rainfall forecasting is explained by differences in mean rainfall. Our results show that the synoptic variability of Long Rain for EAM rainfall is likely to amplify, resulting in more extreme rainfall events and longer dry spells under global warming. This amplification is attributed to the warming of the Indian Ocean and the associated changes in atmospheric circulation patterns. The projected increase in synoptic to annual variability of Long Rain for EAM rainfall has significant implications for water resources management and agriculture in the region, challenging policymakers to develop adaptive strategies that can mitigate the impacts of these extreme events. This study emphasizes the potential impacts of projected climate changes in rainfall variability on the East African region at all periods and underscores the need for effective adaptation strategies to ensure sustainable development.

A Feminist Reading of Hemingway’s Works-“Cat in the Rain”as an Example

As a famous American writer,there have been many different opinions on whether Hemingway is a typical masculinist writer.Through a brief analysis of the feminist consciousness in Hemingway’s works and a detailed feminist interpretation of“Cat in the Rain”,this paper holds that it is unfair and biased to stereotype Hemingway as a typical masculinist writer since there is a very strong feminist consciousness in his early works.

Fatigue Safety Assessment of Concrete Continuous Rigid Frame Bridge Based on Rain Flow Counting Method and Health Monitoring Data

The fatigue of concrete structures will gradually appear after being subjected to alternating loads for a long time,and the accidents caused by fatigue failure of bridge structures also appear from time to time.Aiming at the problem of degradation of long-span continuous rigid frame bridges due to fatigue and environmental effects,this paper suggests a method to analyze the fatigue degradation mechanism of this type of bridge,which combines long-term in-site monitoring data collected by the health monitoring system(HMS)and fatigue theory.In the paper,the authors mainly carry out the research work in the following aspects:First of all,a long-span continuous rigid frame bridge installed with HMS is used as an example,and a large amount of health monitoring data have been acquired,which can provide efficient information for fatigue in terms of equivalent stress range and cumulative number of stress cycles;next,for calculating the cumulative fatigue damage of the bridge structure,fatigue stress spectrum got by rain flow counting method,S-N curves and damage criteria are used for fatigue damage analysis.Moreover,it was considered a linear accumulation damage through the Palmgren-Miner rule for the counting of stress cycles.The health monitoring data are adopted to obtain fatigue stress data and the rain flow counting method is used to count the amplitude varying fatigue stress.The proposed fatigue reliability approach in the paper can estimate the fatigue damage degree and its evolution law of bridge structures well,and also can help bridge engineers do the assessment of future service duration.