Analysis of Predictability of a Large-scale Short-duration Heavy Precipitation Process in Nanchang City

Based on the observation data of automatic stations and sounding data,the circulation characteristics and physical quantities of a large-scale short-duration heavy precipitation process in Nanchang City on July 7,2020 were diagnosed and analyzed,and the ability of several numerical forecasting products to predict this process was tested.The results show that the short-duration heavy precipitation process was triggered in the process of the subtropical high changing from lifting to the north to retreating to the south under the weather background of the confrontation between the northerly flow behind the trough and the strong southwest warm and wet flow on the north side of the subtropical high.The strong southwest warm and wet flow provided abundant water vapor,and the southern pressing of the lower energy front and the invasion of the cold air near the surface layer provided unstable energy and dynamic conditions for the heavy precipitation.The changing trend of the subtropical high from lifting to the north to retreating to the south during 08:00 to 20:00 on July 7 was not predicted by numerical forecast,and there was a large deviation in the forecast of the time and intensity of the southern pressing of the northerly flow behind the trough,so the guidance of numerical forecast for heavy precipitation was not strong,which was not conducive to the prediction of the short-duration heavy precipitation.It was predicted that the subtropical high would move slightly to the south on July 6 compared with the previous day,and the forecast adjustment of the high-level weather system can be used as a sign of the forecast change,which needs to be paid certain attention in the daily forecast.

ANALYSIS OF CAUSATION OF ASYMMETRIC PRECIPITATION ASSOCIATED WITH SEVERE TYPHOON DAMREY

Severe typhoon Damrey moved across Hainan Island from 00:00 UTC 25 September to 00:00 UTC 27 September in 2005 and gave rise to a significant rain process during its 48-h passage.The precipitation intensity on the southern part of the island is stronger than that on the northern,showing obvious asymmetric distribution.Using Tropical Rainfall Measuring Mission(TRMM) data,the associated mesoscale characteristics of the precipitation were analyzed and the formation of asymmetric rainfall distribution was investigated in the context of a subsynoptic scale disturbance,vertical wind shear and orographic factors.The results are shown as follows.(1) The subsynoptic scale system provided favorable dynamic conditions to the genesis of mesoscale rain clusters and rainbands.(2) The southern Hainan Island was located to the left of the leeward direction of downshear all the time,being favorable to the development of convection and leading to the asymmetric rainfall distribution.(3) Mountain terrain in the southern Hainan Island stimulated the genesis,combination and development of convective cells,promoting the formation of mesoscale precipitation systems and ultimately resulting in rainfall increase in the southern island.

Comparative Analysis of Climate Characteristics of Extremely Short-Time Severe Precipitation in Guizhou Based on Two Types of Rainfall Data

In order to fill the gaps of the research on the data of automatic weather stations(referred to as automatic stations)not used for the climate characteristics of extremely short-time severe precipitation in Guizhou Province,the climate characteristics of extremely short-time severe precipitation in Guizhou Province were compared and analyzed based on the hourly precipitation data of the automatic stations and the national weather stations(referred to as the national stations)from April to September during 2010-2019.The results show that the average state of maximum hourly precipitation of all stations(the automatic stations and the national stations)and national stations both are representative,but the data of all stations are more representative when the maximum hourly precipitation is extreme.The 99.5 th quantile is the most reasonable threshold of extremely short-time severe precipitation in each station.The spatial distribution of extremely short-time severe precipitation intensity in all stations and national stations is generally that the southern region is stronger than the northern region,and the intensity values are concentrated in the range of 40-50 mm/h.All stations data can better reflect the distribution characteristics of<40 and≥50 mm/h.The national stations data underestimates the precipitation intensity in the southern and northeastern marginal areas of Guizhou,and slightly exaggerates the precipitation intensity in the northern part of Guizhou.The monthly and diurnal variations of the frequency of extremely short-time severe precipitation in all stations and national stations are very obvious and the variation trend is the same,but the intensity of extremely short-time severe precipitation has no obvious monthly variation characteristics.There is no significant diurnal variation in the intensity of extremely short-time severe precipitation in all stations,but the diurnal variation in the data of national stations is significant.Since the frequency of extremely short-time severe precipitation in national stations is less,the diurnal variation in the intensity of extremely short-time severe precipitation in all stations is more statistically significant.

Analysis of Short-term Heavy Precipitations in a Regional Heavy Rainstorm in Shannxi Province

[Objective] This study aimed to analyze the cause of the generation of short-term heavy precipitations in a regional heavy rainstorm in Shannxi Province. [Method] Taking a heavy rainstorm covering most parts of Shaanxi Province in late July 2010 as an example, data of five Doppler weather radars in Shaanxi Province were employed for a detailed analysis of the evolution of the heavy rainstorm pro- cess. [Result] Besides the good large-scale weather background conditions, the de- velopment and evolution of some mesoscale and small-scale weather systems direct- ly led to short-term heavy precipitations during the heavy rainstorm process, involv- ing the intrusion of moderate IS-scale weak cold air and presence of small-scale wind shear, convergence and adverse wind area. In addition, small-scale convection echoes were arranged in lines and formed a ＂train effect＂, which would also con- tribute to the generation of short-term heavy precipitation. [Conclusion] This study provided basic information for more clear and in-depth analysis of the formation mechanism of short-term heavy precipitations.

Short-Term Precipitation Forecasting Rolling Update Correction Technology Based on Optimal Fusion Correction

In order to improve the availability of regional model precipitation forecast, this project intends to use the measured heavy rainfall data of dense automatic stations to carry out historical precipitation in the high resolution: the Severe Weather Automatic Nowcast System (SWAN) quantitative precipitation forecast and the High-Resolution Rapid Refresh (HRRR) regional numerical model precipitation forecast in short-term nowcasting aging. Based on the error analysis, the grid fusion technology is used to establish the measured rainfall, HRRR regional model precipitation forecast, and optical flow radar quantitative precipitation forecast (QPF) three-source fusion correction scheme, comprehensively integrate the revised forecasting effect, adjust the fusion correction parameters, establish an optimal correction plan, generate a frozen rolling update revised product based on measured dense data and short-term forecast, and put it into business operation, and perform real-time effect rolling test evaluation on the forecast product.

Application of Weather Radar in Quantitative Forecast of Short-term Heavy Precipitation

Based on the C-band Doppler radar data and the hourly precipitation data of heavy precipitation in Ulanqab from 2018 to 2019,the Z-I relationship of local convective precipitation and the correlation between vertically integrated liquid water(VIL)and precipitation were studied.The heavy precipitation was divided into cumulus precipitation and cumulus mixed cloud precipitation,and different types of Z-I relationship was established to compare it with the traditional and unclassified overall optimal Z-I relationship.It shows that the estimation of different types of precipitation by different Z-I relationships was obviously better than the other two.Cumulus precipitation had a certain lag correlation with VIL,and the last 4 scanning VIL values within an hour had no indicative significance for precipitation;mixed precipitation was basically synchronized with VIL;the correlation decreased with the increase of the distance from radar,the corresponding degree of VIL and precipitation in stations within 30 km was significantly higher than that of other regional stations.A continuous non-zero VIL sequence close to a certain place can be used as a forecast indicator.Once a zero value appeared in the VIL time series,even it occurred only once,the two sequences before and after the zero value should be distinguished.

Aging behavior and mechanical properties of 6013 aluminum alloy processed by severe plastic deformation

Structural features, aging behavior, precipitation kinetics and mechanical properties of a 6013 Al–Mg–Si aluminum alloy subjected to equal channel angular pressing （ECAP） at different temperatures were comparatively investigated with that in conventional static aging by quantitative X-ray diffraction （XRD） measurements, differential scanning calorimetry （DSC） and tensile tests. Average grain sizes measured by XRD are in the range of 66-112 nm while the average dislocation density is in the range of 1.20×10^14-1.70×10^14 m^-2 in the deformed alloy. The DSC analysis reveals that the precipitation kinetics in the deformed alloy is much faster as compared with the peak-aged sample due to the smaller grains and higher dislocation density developed after ECAP. Both the yield strength （YS） and ultimate tensile strength （UTS） are dramatically increased in all the ECAP samples as compared with the undeformed counterparts. The maximum strength appears in the samples ECAP treated at room temperature and the maximum YS is about 1.6 times that of the statically peak-aged sample. The very high strength in the ECAP alloy is suggested to be related to the grain size strengthening and dislocation strengthening, as well as the precipitation strengthening contributing from the dynamic precipitation during ECAP.

Strengthening of aluminium alloy 7005 through imposition of severe plastic deformation supplemented by different ageing treatments

Strengthening of aluminium alloys 7xxx through the imposition of severe plastic deformation supplemented by ageing treatments is a challenge due to the limited workability of these alloys in cold deformation regimes.This study aims to comprehensively investigate the strengthening of aluminium alloy 7005 through the imposition of severe plastic deformation supplemented by two different ageing treatments:pre-deformation artificial ageing or postdeformation natural ageing.For this purpose,microstructure evolutions of the alloy processed through mentioned procedures were studied using X-ray diffraction and scanning electron microscopy while the alloy strengthening was evaluated using Vickers hardness measurement.Results show that a superlative strengthening is obtained through the imposition of severe plastic deformation supplemented by post-deformation natural ageing.For instance,the yield strength of the alloy increases to more than 400 MPa,about one-third greater than the counterpart amount after the usual T6 treatment.This superlative strength mainly occurs due to refinement of grains,an increase of dislocation density and an increase of volume fraction of the precipitates that appeared during natural ageing.Considering the applied models,it is inferred that the increase of volume fraction of precipitates that appeared during natural ageing has a determinative role in the strengthening of the alloy.

Effects of dynamic recrystallization and strain-induced dynamic precipitation on the corrosion behavior of partially recrystallized Mg-9Al-lZn alloys

The corrosion susceptibility of recrystallized and un-recrystallized grains in equal channel angular pressed(ECAPed)Mg-9Al-lZn(AZ91)alloys immersed in chloride containing media was investigated through immersion testing and an electrochemical microcell technique coupledwith high resolution techniques such as scanning Kelvin probe force microscopy(SKPFM),transmission electron microscopy(TEM),andelectron backscatter diffraction(EBSD).During ECAP,dynamic recrystallization(DRX)and strain-induced dynamic precipitation(SIDP)simultaneously occurred,resulting in a bimodal grain structure of original elongated coarse grains and newly formed equiaxed fine grainswith a large volume fraction ofβ-Mg17Al12 precipitates.Corrosion preferentially initiates and propagates in the DRXed grains,owing tothe greater microchemistry difference between theβ-Mg17Al12 precipitates formed at the DRXed grain boundaries and the adjacentα-Mgmatrix,which induces a strong microgalvanic coupling between these phases.Additionally,the weaker basal texture of the DRXed grainsalso makes these grains more susceptible to electrochemical reactions than the highly textured un-DRXed grains.The influence of dynamicrecrystallization and dynamic precipitation was also studied in ECAPed alloys with differenl levels of deformation strain through corrosion andelectrochemical techniques.Increasing the strain level led to a more uniform corrosion with a shallow penetration depth,lower corrosion ratevalues,and higher protective ability of the oxide film.Furthermore,higher levels of strain resulted in greater hardness values of the ECAPedalloys.The superior corrosion resistance and strength of the ECAPed alloys with increasing strain level was attributed to the combination ofsmaller DRXed grain size,higher DRX ratio,and higher volume fraction of uniformly distributed fineβ-Mg17Al12 precipitates.c 2020 Published by Elsevier B.V.on behalf of Chongqing University.

Estimation of meteorological drought indices based on AgMERRA precipitation data and station-observed precipitation data

Meteorological drought is a natural hazard that can occur under all climatic regimes. Monitoring the drought is a vital and important part of predicting and analyzing drought impacts. Because no single index can represent all facets of meteorological drought, we took a multi-index approach for drought monitoring in this study. We assessed the ability of eight precipitation-based drought indices（SPI（Standardized Precipitation Index）, PNI（Percent of Normal Index）, DI（Deciles index）, EDI（Effective drought index）, CZI（China-Z index）, MCZI（Modified CZI）, RAI（Rainfall Anomaly Index）, and ZSI（Z-score Index）） calculated from the station-observed precipitation data and the Ag MERRA gridded precipitation data to assess historical drought events during the period 1987–2010 for the Kashafrood Basin of Iran. We also presented the Degree of Dryness Index（DDI） for comparing the intensities of different drought categories in each year of the study period（1987–2010）. In general, the correlations among drought indices calculated from the Ag MERRA precipitation data were higher than those derived from the station-observed precipitation data. All indices indicated the most severe droughts for the study period occurred in 2001 and 2008. Regardless of data input source, SPI, PNI, and DI were highly inter-correlated（R^2=0.99）. Furthermore, the higher correlations（R^2=0.99） were also found between CZI and MCZI, and between ZSI and RAI. All indices were able to track drought intensity, but EDI and RAI showed higher DDI values compared with the other indices. Based on the strong correlation among drought indices derived from the Ag MERRA precipitation data and from the station-observed precipitation data, we suggest that the Ag MERRA precipitation data can be accepted to fill the gaps existed in the station-observed precipitation data in future studies in Iran. In addition, if tested by station-observed precipitation data, the Ag MERRA precipitation data may be used for the data-lacking areas.

Spatial-temporal Analysis and Prediction of Precipitation Extremes: A Case Study in the Weihe River Basin, China

Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical for the flood prevention and water resources planning and management.In this study,daily precipitation data(1957–2019)were collected from 24 meteorological stations in the Weihe River Basin(WRB),Northwest China and its surrounding areas.We first analyzed the spatial-temporal change of precipitation extremes in the WRB based on space-time cube(STC),and then predicted precipitation extremes using long short-term memory(LSTM)network,auto-regressive integrated moving average(ARIMA),and hybrid ensemble empirical mode decomposition(EEMD)-LSTM-ARIMA models.The precipitation extremes increased as the spatial variation from northwest to southeast of the WRB.There were two clusters for each extreme precipitation index,which were distributed in the northwestern and southeastern or northern and southern of the WRB.The precipitation extremes in the WRB present a strong clustering pattern.Spatially,the pattern of only high-high cluster and only low-low cluster were primarily located in lower reaches and upper reaches of the WRB,respectively.Hot spots(25.00%–50.00%)were more than cold spots(4.17%–25.00%)in the WRB.Cold spots were mainly concentrated in the northwestern part,while hot spots were mostly located in the eastern and southern parts.For different extreme precipitation indices,the performances of the different models were different.The accuracy ranking was EEMD-LSTM-ARIMA>LSTM>ARIMA in predicting simple daily intensity index(SDII)and consecutive wet days(CWD),while the accuracy ranking was LSTM>EEMD-LSTM-ARIMA>ARIMA in predicting very wet days(R95 P).The hybrid EEMD-LSTM-ARIMA model proposed was generally superior to single models in the prediction of precipitation extremes.

Spatiotemporal analysis of drought variability based on the standardized precipitation evapotranspiration index in the Koshi River Basin, Nepal

Drought is an inevitable condition with negative impacts in the agricultural and climatic sectors,especially in developing countries.This study attempts to examine the spatial and temporal characteristics of drought and its trends in the Koshi River Basin(KRB)in Nepal,using the standardized precipitation evapotranspiration index(SPEI)over the period from 1987 to 2017.The Mann-Kendall test was used to explore the trends of the SPEI values.The study illustrated the increasing annual and seasonal drought trends in the KRB over the study period.Spatially,the hill region of the KRB showed substantial increasing drought trends at the annual and seasonal scales,especially in summer and winter.The mountain region also showed a significant increasing drought trend in winter.The drought characteristic analysis indicated that the maximum duration,intensity,and severity of drought events were observed in the KRB after 2000.The Terai region presented the highest drought frequency and intensity,while the hill region presented the longest maximum drought duration.Moreover,the spatial extent of drought showed a significant increasing trend in the hill region at the monthly(drought station proportion of 7.6%/10 a in August),seasonal(drought station proportion of 7.2%/10 a in summer),and annual(drought station proportion of 6.7%/10 a)scales.The findings of this study can assist local governments,planners,and project implementers in understanding drought and developing appropriate mitigation strategies to cope with its impacts.

THE ANALYSIS OF TROPICAL CYCLONE PRECIPITATION AFFECTING THE LIAODONG PENINSULA

1 INTRODUCTION Tropical cyclones （TCs） moving north and getting to the Liaodong Peninsula and waters of the Yellow and Bohai Seas are in their late phase of life cycle. While weakening rapidly, TCs carry a large amount of warm and humid air that forms heavy rainfall by itself on the one hand and interact with westerlies in the middle latitudes on the other. With their warm-core structure destroyed by intruded cooler air, TCs absorb baroclinic energy while it weakens and experiences extratropical transition （ET）. With right conditions and complicated topographic features of the peninsula, the transformed extratropical cyclone evolves to intensify heavy rainfall in most cases and even results in secondary disasters like storm surges. Therefore, the extratropical transition of TCs is usually responsible for more serious damage in mid-latitude areas. For the forecast of heavy rain associated with north-going TCs experiencing extratropical transition, it not only involves their own intensity and structure but also the distribution of the surrounding field and its interactions with TCs. Most of the present studies discuss TCs-inflicted heavy rains or those taking place south of the Shandong Peninsula. Focusing on intense precipitation resulted from TCs over the Liaodong Peninsula, this work analyzes the distribution of the ambient field and physical quantities hoping to help forecast TCs-related heavy rains accurately.

Analysis on a Severe Convective Weather Process of Guangxi in 2018

Based on conventional meteorological observation data and Doppler radar data,the occurrence and development mechanism of mixed severe convective weather and evolution of convective storm in Guangxi on March 4,2018 were analyzed. The results showed that the dry line was the main trigger mechanism of this severe convective weather. Instable convection stratification of cold advection at middle layer and warm advection at low layer and abundant water vapor from low-level jet provided favorable stratification and water vapor conditions for the occurrence and development of severe convection. Cold trough at middle layer,low pressure and strong vertical wind shear at middle and lower layers may be main factors for the development and maintenance of strong storm system. Squall line developed along ground convergence line,and there was bow echo on reflectivity factor chart. Moving velocity of convective system was quick,and there was gale core and velocity ambiguity on velocity map.

Analysis of Short-term Heavy Precipitation in Ulanqab City from 2017 to 2022

Based on the data of hourly precipitation in 11 national stations and 262 regional stations in Ulanqab City from 2017 to 2022,the annual,monthly and daily variations of short-term heavy precipitation in Ulanqab City were statistically analyzed.The results show that the frequency of short-term heavy precipitation in Ulanqab City was high in the south and low in the north,and was closely related to the terrain.Short-term heavy precipitation in Ulanqab City was mainly concentrated from June to August,of which it was the frequentest in July.Short-term heavy precipitation mainly occurred from the afternoon to evening,and was concentrated from 13:00 to 20:00,especially at 19:00.The rainfall in Ulanqab City ranged mainly from 20 to 30 mm,accounting for 74.7%,and the rest accounted for 25.3%.

基于时空图卷积的强对流降水临近预报研究

降水临近预报对于强对流天气的预报具有重要的支撑作用。气象业务中主要采用雷达回波外推方法解决此问题。然而,现有方法通常缺乏从序列雷达数据中有效学习的能力,导致预测精度不佳。为了解决这一问题,本文提出了一种改进的时空图卷积模型ASTGCN(A Spatio-Temporal Graph Convolution Neural Network)用于强对流降水的临近预报。利用时空图卷积网络,有效地捕获相邻雷达帧之间的时间依赖性。此外,利用注意力机制和自动编码器来增强模型捕获时空相关性的能力。结果表明,该模型可以从数据中发现隐藏的图结构,从而捕获隐藏的空间关系。与现有模型(Transformer)相比,该模型的临界成功指数(CSI)提高了28%,表明其在强对流降水临近预报方面具有优越的性能。

CMA-MESO模式对“21·7”河南特大暴雨的预报评估与误差分析

为分析CMA-MESO模式对2021年7月19—21日河南特大暴雨的预报性能,除了常规观测资料,还利用雷达和卫星非常规观测资料,对模拟回波和云产品开展传统和新型空间检验,以揭示对流风暴和中尺度对流系统(MCS,基于卫星红外通道)的模式预报偏差细节,并从降水形成的水汽、动力、触发和维持机制等角度分析模式误差产生的原因。结果表明:模式能较好预报雨带形态、弱回波持续时间以及主要降水发生前期和后期MCS的面积和强度演变趋势;模式偏差主要体现在低估了降水强度且未报出郑州站极端小时降水,错报主雨带小时降水演变,严重低估了对流风暴和强对流风暴的持续时间,未能报出午后MCS面积陡增的变化趋势且MCS位置预报偏西、偏北;模式降水偏差的原因主要在于水汽的模拟,模式水汽垂直分布不合理,对台风烟花和查帕卡的水汽输送均偏弱,而水汽输送不足的根源是低空急流偏弱和超低空急流脉动不足。另外,模式未能在郑州站附近预报出稳定少动的地面中尺度辐合线,加之大气层结不稳定度不足和对流不稳定能量偏低,使得对流发展不够旺盛,最终导致降水预报不足。

基于GNSS水汽和地面假相当位温观测的短时强降水阈值预报方法研究

基于2019年和2020年6—7月GNSS水汽监测网大气可降水量(PWV)资料和并址气象站的地面雨量、温、压、湿等同步观测数据,利用临界成功指数(CSI)和命中率(POD)两个检验指标,探索建立了基于PWV、6小时水汽增量(PWV*)及假相当位温距平(θ_(se)*)的短时强降水阈值预报方法,并利用2021年6—7月降水样本对该预报方法进行检验,结果显示CSI和POD分别为0.167和0.593,其评分高于目前常规业务方法对短时强降水的客观预报评分,其中约48%的短时强降水发生在预警之后的24小时内,约78%发生于48小时内。研究区域内78.6%的短时强降水样本发生在连续15小时PWV*的累积值(∑PWV*)≥75 mm且连续24小时θ_(se)*累积值(∑θ_(se)*)≥30 K的条件下;PWV高值区叠加∑PWV*和∑θ_(se)*的大值区对梅雨期短时强降水以及暴雨发生区域有较好的指示性。

2024年春运期两次极端雨雪冰冻天气过程对比分析

2024年1月31日-2月6日和2月19-25日,我国先后出现两次大范围持续性低温雨雪冰冻天气过程(分别简称过程1和过程2),对春运造成严重影响。利用多源观测和ERA5再分析资料对两次过程进行对比,重点分析了南方地区雨雪天气强度及冻雨和降水相态差异的原因。结果表明:(1)两次过程的累计降水量均有一定极端性,并伴有复杂的降水相态变化,冻雨强度和范围为2009年以来最大;过程1冻雨强度和积雪深度大于过程2,过程2冻雨范围、降水和对流强度大于过程1。(2)两次过程均发生在高空槽与低层冷空气共同作用的环流背景下,南支槽前和西太平洋副热带高压外围的西南急流稳定维持且较常年显著偏强,为两次极端雨雪冰冻天气过程提供了持续而充沛的水汽条件;暖湿气流在冷垫上的爬升以及低层风场的水平辐合是产生雨雪天气的重要动力机制,逆温层和融化层的稳定维持是出现冻雨及降水相态反复变化的关键原因。(3)两次过程不同点主要在于,过程1冻结层内温度多在-4~0℃,高于过程2,相对而言更有利于形成冻雨;逆温区狭长且少动,冻雨影响范围集中,强度大;过程2副热带高压更偏西偏北,有利于西南暖湿急流加强和北推,同时强寒潮导致冷垫较强,冷暖交汇有利于上升运动发展和降水增强;过程2融化层维持时间更长,云水含量较高,但冻结层内温度低,更有利于出现冰粒或湿雪。

Time series models in prediction of severe fever with thrombocytopenia syndrome cases in Shandong province,China

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013–2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.