Climatic Features Related to Eastern China Summer Rainfalls in the NCAR CCM3

The climatic features associated with the eastern China summer rainfalls (ECSR) are examined in the National Center for Atmospheric Research (NCAR) Community Climate Model Version 3 (CCM3) of the United States of America, and run with time-evolving sea surface temperature (SST) from September 1978 to August 1993. The CCM3 is shown to capture the salient seasonal features of ECSR. As many other climate models, however, there are some unrealistic projections of ECSR in the CCM3. The most unacceptable one is the erroneously intensified precipitation center on the east periphery of the Tibetan Plateau and its northeastward extension. The artificial strong rainfall center is fairly assessed by comparing with the products of the station rainfall data, Xie and Arkin (1996) rainfall data and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (Gibson et al., 1997). The physical processes involved in the formation of the rainfall center are discussed. The preliminary conclusion reveals that it is the overestimated sensible heating over and around the Tibetan Plateau in the CCM3 that causes the heavy rainfall. The unreal strong surface sensible heating over the southeast and northeast of Tibetan Plateau favors the forming of a powerful subtropical anticyclone over the eastern China. The fake enclosed subtropical anticyclone center makes the moist southwest wind fasten on the east periphery of the Tibetan Plateau and extend to its northeast. In the southeast coast of China, locating on the southeast side of the subtropical anticyclone, the southwest monsoon is decreased and even replaced by northeast wind in some cases. In the CCM3, therefore, the precipitation is exaggerated on the east periphery of the Tibetan Plateau and its northeast extension and is underestimated in the southeast coast of China. Key words Eastern China summer rainfall - Model validation - Subtropical anticyclone - Diabatic heating This study was sponsored by Chinese Academy of Sciences under grant “ Hundred Talents” for “ Validation of Coupled Climate models” and the National Natural Science Foundation of China (Grant No.49823002), and IAP innovation fund (No. 8-1204).

Summer Monsoon Rainfalls over Mid-Eastern China Lagged Correlated with Global SSTs

Some features associated with Eastern China Precipitation (ECP), in terms of mean climatology, sea-sonal cycle, interannual variability are studied based on monthly rainfall data. The rainfall behavior over Eastern China has fine spatial structure in the seasonal variation and interannual variability. The revealed characteristics of ECP motivate us dividing Eastern China into four sub—regions to quantify significant lag—correlations of the rainfalls with global sea surface temperatures (SSTs) and to study the ocean’s pre-dominant role in forcing the eastern China summer monsoon rainfalls. Lagged correlations between the mid—eastern China summer monsoon rainfalls (MECSMRs) and the global SSTs, with SST leading to rain-fall, are investigated. The most important key SST regions and leading times, in which SSTs are highly corre-lated with the MECSMRs, are selected. Part of the results confirms previous studies that show links between the MECSMRs and SSTs in the eastern equatorial Pacific associated with the El Nino — Southern Oscillation (ENSO) phenomenon. Other findings include the high lag correlations between the MECSMRs and the SSTs in the high and middle latitude Pacific Ocean and the Indian Ocean, even the SSTs over the Atlantic Ocean, with SST leading—time up to 4 years. Based on the selected SST regions, regression equa-tions are developed by using the SSTs in these regions in respective leading time. The correlation coefficient between the observed rainfalls and regressed rainfalls is over 0.85. The root mean square error (RMSE) for regressed rainfall is around 65% of the standard deviation and about 15% of the mean rainfall. The regression equation has also been evaluated in a forecasting mode by using independent data. Discussion on the consistence of the SST—rainfall correlation with circulation field is also presented. Key words Summer monsoon - Rainfall - SST - Regression This work was jointed supported by Chinese Academy of Sciences under Grant “Hundred Talents” for “Validation of Coupled Climate models” and by U.S. Department of Energy under Grant DEFG0285ER 60314 to SUNY at Stony Brook. The authors are grateful to Professor R. D. Cess at SUNY, Stony Brook for his supports.

Variation Diagnosis and Regional Comparison of Different Intensity of Rainfalls and Their Contribution to Total Rainfall in China in the Context of Global Warming

Using the data of 545 meteorological stations in 1961-2015,according to the rainfall intensity classification standard issued by the China Meteorological Administration,the rainfall events were divided into six intensities: light rain,moderate rain,heavy rain,torrential rain,downpour and heavy downpour. The latter three were recorded as total torrential rain,and all the six were recorded as the total rainfall. In terms of the interannual rainfall and rainy days,the whole China was regarded as an object. Firstly,the annual rainfall and rainy day of different intensity of rainfalls of 545 stations in 1961-2015 were calculated. Then,the variation trend of rainfall and rainy days was calculated. Finally,the variation trend of contribution of different intensity of rainfalls and rainy days to total rainfall and rainy days were diagnosed. It obtained the following results.( i) The light rain in China was declining from 1961 to 2015,and the trend values of light rain and rainy days were-411. 44 mm/yr and-136. 99 d/yr,respectively. Heavy rain and total heavy rainfall showed an increasing trend,with rainfall and rainy day trends of 127. 02 and 463. 94 mm/yr and 7. 93 and 4. 24 d/yr,respectively. The total rainfall showed a ' hockey' phenomenon of ' first rise,then decline',and the trend values of rainfall and rainy days were 204. 29 mm/yr and-95. 81 d/yr,respectively. Except the northern region,the rainfall in most parts of China was dominated by increasing trends and was moving towards extremes.( ii) In terms of rainfall contribution rate,the contribution of light rain to total rainfall showed a declining trend,and the trend values of rainfall and rainy day contribution were both-0. 11%/yr. The contribution of other intensity rainfalls to total rainfall showed an increasing trend. The contribution of torrential rain to the total torrential rain showed a declining trend. The contribution trends of rainfall and rainy days were-0. 06% and-0. 03%/yr,respectively. The contribution of downpour and heavy downpour to total torrential rain showed an increasing trend,indicating the intensity of torrential rain in China is increasing. Although the contribution rate of different intensity of rainfalls to total rainfall was different in different areas of China,the contribution rate of heavy rainfall to total rainfall in most areas showed an increasing trend.( iii) Through comparing the rainfall and rainy days of six different intensity of rainfalls,it can be found that China’s heavy rainfall events are increasing and the rainfall intensity is developing towards extremes.

INSTABILITY OF THE TELECONNECTION OF SUMMER RAINFALLS BETWEEN NORTH CHINA AND INDIA

Summer rainfall variations in North China closely relate to that in India. It seems that an alternation of signs of“＋, -, ＋” exists in the geographical pattern of the correlation in summer rainfall from North China to India through the Tibetan Plateau. However, it appears that the teleconnection of summer rainfall variations between North China and India is unstable. Over 1945 - 1974, the correlation coefficient （hereafter as CC） is as large as 0.7. In contrast, the CC is about -0.3 over 1827-1856. Further studies, based on observations starting from 1813, showed that the correlation is strong when summer rainfalls in both North China and India are large, and vice versa. In order to find what induce the change of the teleconnection, variations of summer rainfall in both North China and India, mean sea surface temperature （SST） in the eastern equatorial Pacific and the frequency of ENSO events were examined in relation to the change of the teleconnection. The result showed that the teleconnection appears weak when the mean SST is high and the frequency ofLa Nifia events is low; the teleconnection is strong when the mean SST is low and the frequency ofLa Nina events is high. At last, it is notable that La Nifia happens in only 3 years during the recent 30 years from 1976 to 2005 and the teleconnection becomes weak too.

Natural hazards in Romania induced by heavy rainfalls in 1996-1997

Romania is one of the European countries most frequently affected by natural hazards due to its position within the alpine orogenic system and against the main atmospheric pressure centres.Hence the impact of exogenous factors that trigger strong earthquakes with several epicentres, and of exogenous or climate-driven factors with extreme climatic phenomena causing frequent floods, mass movements, soil erosion, droughts, hailstorms and strong winds. This paper deals mainly with natural disasters cased by the variability of climatic conditions (mostly by precipitations) in the years 1996 and 1997, their temporal and spatial distributions and the way they affected human life. In point of rainfall distribution and the ensuing natural hazards, the mentioned period shows two distinct intervals: December, 1996-March 1997 (mass movements) and June-August, 1997 (floods, hailstorm,Strong wind,landslides, soil erosion).

The statistical prediction of East African rainfalls using quasi-biennial oscillation phases information

A simple correlation method and a quasi-biennial oscillation (QBO)/rainfall composite analysis were used to examine the teleconnections be-tween the seasonal rainfall anomalies of March through May (long-rains) over East Africa and the different QBO phases in the stratospheric zonal winds, and also explore the predictive potential of the long rainy season using infor-mation about the phases of the QBO for the pe-riod 1979-2003. We study the spatial correlation patterns statistically to understand the climatic associations between the equatorial strato-spheric zonal wind and regional rainfall at the interannual time scale. The aim of this analysis is to establish whether this global signal can be employed as predictor variable in the long-range forecasts. Principal component analysis (PCA) is employed in the first instance to reduce the large dimensionality of the predictant (monthly rainfall data), to retain the time series of the principal components (PCs) and to delineate the rain gauge network of East Africa into homo-geneous zones. Spatial patterns of the factor loading were used to delineate East Africa into 11 homogeneous zones.

Comparative Analysis on Physical Quantity Diagnosis and Wind Profile Radar Data of Two Heavy Rainfalls

[ Objective] The research aimed to contrast physical quantity diagnosis and wind profile radar data of two heavy rainfalls. [ Method ] From circulation background, physical quantity field and wind profile radar data, we analyzed two big rainstorm weather processes （8 -9 July and August 10） in Lianyungang City in 2012. [ Result] Rainstorm generation was related to favorable large-scale circulation situation. The first-stage precipitation during 8 -9 July was warm-zone precipitation, and the precipitation at the second stage was triggered by shear line. Precipitation on August 10 was generated by typhoon low-pressure inverted trough and cold air. Sufficient water vapor content and strong water vapor transportation were favorable for generation of the heavy precipitation. Suction effect by divergence at high layer and convergence at middle and low layers was favorable for maintenance of the strong ascending motion. Occurrence of the heavy precipitation must have ascending motion condition. But it was not that the stronger the ascending motion, the stronger the rainfall intensity. Kindex and θse500 -θse 850 were closely related to rainstorm occurrence. Horizontal wind data of the wind profile radar provided fine structure of the atmospheric horizontal motion at vertical direction, could clearly display vertical structure of the wind field in rainstorm process, and directly reflected change characteristics of the wind field in precipitation process. [ Conclusion] The research could provide reference for future forecast work.

Trend and Return Level Analysis of Extreme Rainfalls in Senegal

In recent years, Senegal has been confronted with increasingly frequent and damaging extreme events. In the context of climate change, we conducted this study to characterize the trends of rainfall extremes in Senegal. In this work, we used daily rainfall data from 27 stations in Senegal from the period 1951 to 2005 (55 years). To study their linear trends, non-stationary extreme value models with time as a covariate are fitted to evaluate them. Our results indicate a decreasing trend of extreme rainfalls at most of the stations except for 5 stations. However, the decreasing trends are only significant for two stations (Thiès and Kidira), however, this can only be taken as information that climate change may have already impacted extreme rainfalls. For the 20-year and 30-year return periods, the results show that they have undergone changes, in fact for almost all stations, the trends in return periods are decreasing.

Genetic Mechanism of Water-Rich Landslide Considering Antecedent Rainfalls:A Case Study of Pingyikou Landslide in Three Gorges Reservoir Area

Water-rich slope,which could easily fail after prolonged or heavy rain,is very sensitive to rainfall.Pingyikou Landslide is a typical water-rich slope located in the Three Gorges Reservoir area of China.It was unstable because of the continuous rainfall that occurred from September to October 2017.To understand the deformation process and genetic mechanism of the landslide,the geomorphological features,geological characteristics,hydrological conditions,and rainfall characteristics were systematically studied by a detailed field investigation of the slope and monitoring of rainfall,water level,and displacement.In addition,the influence of different initial conditions on the stability of the slope was also studied through numerical simulation using measured rainfall data on the basis of which,the effect of antecedent rainfall on slope stability was studied by unsaturated seepage analysis method.The results show that the deformation of slope is strongly correlated with the rainfall and groundwater level,and this landslide is a typical rainfall-induced landslide.In the analysis of genetic mechanism of the same type of landslide,a maximum initial pore water pressure of -25 kPa as the initial condition is reasonable.And the antecedent rainfall has a greater effect on the stability of the slope,more than 10 days of antecedent rainfall should be considered when designing and controling the slope.

黄河流域生态保护迈向高质量发展的特征——植被绿度、生产力和降水利用效率的差异性变化

Globally,vegetation has been changing dramatically.The vegetation-water dynamic is key to understanding ecosystem structure and functioning in water-limited ecosystems.Continual satellite monitoring has detected global vegetation greening.However,a vegetation greenness increase does not mean that ecosystem functions increase.The intricate interplays resulting from the relationships between vegetation and precipitation must be more adequately comprehended.In this study,satellite data,for example,leaf area index(LAI),net primary production(NPP),and rainfall use efficiency(RUE),were used to quantify vegetation dynamics and their relationship with rainfall in different reaches of the Yellow River Basin(YRB).A sequential regression method was used to detect trends of NPP sensitivity to rainfall.The results showed that 34.53%of the YRB exhibited a significant greening trend since 2000.Among them,20.54%,53.37%,and 16.73%of upper,middle,and lower reach areas showed a significant positive trend,respectively.NPP showed a similar trend to LAI in the YRB upper,middle,and lower reaches.A notable difference was noted in the distributions and trends of RUE across the upper,middle,and lower reaches.Moreover,there were significant trends in vegetation-rainfall sensitivity in 16.86%of the YRB’s middle reaches—14.08%showed negative trends and 2.78%positive trends.A total of 8.41%of the YRB exhibited a marked increase in LAI,NPP,and RUE.Subsequently,strategic locations reliant on the correlation between vegetation and rainfall were identified and designated for restoration planning purposes to propose future ecological restoration efforts.Our analysis indicates that the middle reach of the YRB exhibited the most significant variation in vegetation greenness and productivity.The present study underscores the significance of examining the correlation between vegetation and rainfall within the context of the high-quality development strategy of the YRB.The outcomes of our analysis and the proposed ecological restoration framework can provide decision-makers with valuable insights for executing rational basin pattern optimization and sustainable management.

Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

Research progress on the water vapor channel within the Yarlung Zsangbo Grand Canyon, China

The Second Tibetan Plateau Scientific Expedition and Research Program tasked a research team with the“Investigation of the water vapor channel of the Yarlung Zsangbo Grand Canyon(INVC)”in the southeastern Tibetan Plateau(TP).This paper summarizes the scientific achievements obtained from the data collected by the INVC observation network and highlights the progress in investigating the development of heavy rainfall events associated with water vapor changes.The rain gauge network of the INVC can represent the impacts of the Yarlung Zsangbo Grand Canyon(YGC)topography on precipitation at the hourly scale.The microphysical characteristics of the precipitation in the YGC are different than those in the lowland area.The GPM-IMERG(Integrated MultisatellitE Retrievals for Global Precipitation Measurement)satellite precipitation data for the YGC region should be calibrated before they are used.The meridional water vapor flux through the YGC is more important than the zonal flux for the precipitation over the southeastern TP.The decreased precipitation around the YGC region is partly due to the decreased meridional water vapor flux passing through the YGC.High-resolution numerical models can benefit precipitation forecasting in this region by using a combination of specific schemes that capture the valley wind and water vapor flux along the valley floor.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

Assessment of Seasonal Rainfall Prediction in Ethiopia: Evaluating a Dynamic Recurrent Neural Network to Downscale ECMWF-SEAS5 Rainfall

Seasonal rainfall plays a vital role in both environmental dynamics and decision-making for rainfed agriculture in Ethiopia, a country often impacted by extreme climate events such as drought and flooding. Predicting the onset of the rainy season and providing localized rainfall forecasts for Ethiopia is challenging due to the changing spatiotemporal patterns and the country's rugged topography. The Climate Hazards Group Infra Red Precipitation with Station Data(CHIRPS), ERA5-Land total precipitation and temperature data are used from 1981–2022 to predict spatial rainfall by applying an artificial neural network(ANN). The recurrent neural network(RNN) is a nonlinear autoregressive network with exogenous input(NARX), which includes feed-forward connections and multiple network layers, employing the Levenberg Marquart algorithm. This method is applied to downscale data from the European Centre for Medium-range Weather Forecasts fifth-generation seasonal forecast system(ECMWF-SEAS5) and the Euro-Mediterranean Centre for Climate Change(CMCC) to the specific locations of rainfall stations in Ethiopia for the period 1980–2020. Across the stations, the results of NARX exhibit strong associations and reduced errors. The statistical results indicate that, except for the southwestern Ethiopian highlands, the downscaled monthly precipitation data exhibits high skill scores compared to the station records, demonstrating the effectiveness of the NARX approach for predicting local seasonal rainfall in Ethiopia's complex terrain. In addition to this spatial ANN of the summer season precipitation, temperature, as well as the combination of these two variables, show promising results.

Analysis of the effect of the 2021 Semeru eruption on water vapor content and atmospheric particles using GNSS and remote sensing

Mount Semeru,an active volcano in East Java,Indonesia,erupted on December 4,2021,following extreme rainfall that caused an avalanche of hot pyroclastic flows and lava.The tropospheric conditions and dominant particle components in the atmosphere can be monitored using Global Navigation Satellite System(GNSS)technology and remote sensing satellites.GNSS signal propagation delay in Precise Point Positioning(PPP)processing can be used to determine Zenith Tropospheric Delay(ZTD)and Precipitable Water Vapor(PWV)variables so that atmospheric conditions can be generated.In addition,by using remote sensing satellite data,it is possible to obtain rainfall data with high temporal resolution as well as the dominant particle and gas content values during eruptions.During the eruption period,the high value of PWV was dominated by the high intensity of precipitation during the rainy season.High rainfall before the eruption caused activity inside the mountain to increase,which occurred in avalanche type eruption.Apart from that,the atmosphere around Semeru was also dominated by SO_(2)content,which spreaded for tens of kilometers.SO_(2)content began to be detected significantly by remote sensing sensors on December 7,2021.In this study,deformation and atmospheric monitoring were also carried out using low-cost GNSS at the Semeru Monitoring Station on September 9-15,2022.The results of the ZTD and ZWD values show the dominance of the wet component,which is directly proportional to rainfall activity in this period.

Spatiotemporal Characteristics of Rainfall over Different Terrain Features in the Middle Reaches of the Yangtze River Basin during the Warm Seasons of 2016–20

Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variations over the middle reaches of the Yangtze River basin.For all three types of terrain(i.e.,mountain,foothill,and plain),the amount of TR and SDHR both maximize in June/July,and the contribution of SDHR to TR(CST)peaks in August(amount:23%;frequency:1.74%).Foothill rainfall is characterized by a high TR amount and a high CST(in amount);mountain rainfall is characterized by a high TR frequency but a small CST(in amount);and plain rainfall shows a low TR amount and frequency,but a high CST(in amount).Overall,stations with high TR(amount and frequency)are mainly located over the mountains and in the foothills,while those with high SDHR(amount and frequency)are mainly concentrated in the foothills and plains close to mountainous areas.For all three types of terrain,the diurnal variations of both TR and SDHR exhibit a double peak(weak early morning and strong late afternoon)and a phase shift from the early-morning peak to the late-afternoon peak from May to August.Around the late-afternoon peak,the amount of TR and SDHR in the foothills is larger than over the mountains and plains.The TR intensity in the foothills increases significantly from midnight to afternoon,suggesting that thermal instability may play an important role in this process.

Comparison of Adaptive Simulation Observation Experiments of the Heavy Rainfall in South China and Sichuan Basin

This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying the sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations improve the prediction of jet streams, strong winds, and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transport. In the Sichuan Basin, adaptive observations refine water vapor transport and adjust vortex dynamics. This research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.

Local Torrential Rainfall Event within a Mei-Yu Season Mesoscale Convective System:Importance of Back-Building Processes

An extreme rainfall event occurred over Hangzhou,China,during the afternoon hours on 24 June 2013.This event occurred under suitable synoptic conditions and the maximum 4-h cumulative rainfall amount was over 150 mm.This rainfall event had two major rainbands.One was caused by a quasi-stationary convective line,and the other by a backbuilding convective line related to the interaction of the outflow boundary from the first rainband and an existing low-level mesoscale convergence line associated with a mei-yu frontal system.The rainfall event lasted 4 h,while the back-building process occurred in 2 h when the extreme rainfall center formed.So far,few studies have examined the back-building processes in the mei-yu season that are caused by the interaction of a mesoscale convergence line and a convective cold pool.The two rainbands are successfully reproduced by the Weather Research and Forecasting(WRF)model with fourlevel,two-way interactive nesting.In the model,new cells repeatedly occur at the west side of older cells,and the backbuilding process occurs in an environment with large CAPE,a low LFC,and plenty of water vapor.Outflows from older cells enhance the low-level convergence that forces new cells.High precipitation efficiency of the back-building training cells leads to accumulated precipitation of over 150 mm.Sensitivity experiments without evaporation of rainwater show that the convective cold pool plays an important role in the organization of the back-building process in the current extreme precipitation case.

Flume experiments to study fine-grain migration and its impact on slope stability

Fine grains migration is a primary cause of landslides and debris flows.This study investigates the effect of fine-grain migration on slope failure through flume experiments,focusing on the spatiotemporal characteristics and mechanisms of slope stability.A series of artificial rainfall flume experiments with varying rainfall intensities and slopes were conducted using soil samples collected from Wei Jia Gully.The experiments monitored pore-water pressure,grain migration,and failure sequences.Grain-size distribution parameters(μand Dc)were analyzed to understand the migration path and accumulation of fine grains.The experiments reveal that fine-grain migration significantly alters soil structure,leading to random blockage and interconnection of internal pore channels.These changes result in fluctuating pore-water pressure distributions and uneven fine-grain accumulation,critical factors in slope stability.Slope failures occur randomly and intermittently,influenced by fine-grain content in runoff and resulting pore-water pressure variations.This study highlights that fine-grain migration plays a vital role in slope stability,with significant implications for predicting and mitigating slope failures.The stochastic nature of fine-grain migration and its impact on soil properties should be incorporated into predictive models to enhance their accuracy and reliability.

Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.