A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau

In this study, a new rain type classification algorithm for the Dual-Frequency Precipitation Radar(DPR) suitable over the Tibetan Plateau(TP) was proposed by analyzing Global Precipitation Measurement(GPM) DPR Level-2 data in summer from 2014 to 2020. It was found that the DPR rain type classification algorithm(simply called DPR algorithm) has mis-identification problems in two aspects in summer TP. In the new algorithm of rain type classification in summer TP,four rain types are classified by using new thresholds, such as the maximum reflectivity factor, the difference between the maximum reflectivity factor and the background maximum reflectivity factor, and the echo top height. In the threshold of the maximum reflectivity factors, 30 d BZ and 18 d BZ are both thresholds to separate strong convective precipitation, weak convective precipitation and weak precipitation. The results illustrate obvious differences of radar reflectivity factor and vertical velocity among the three rain types in summer TP, such as the reflectivity factor of most strong convective precipitation distributes from 15 d BZ to near 35 d BZ from 4 km to 13 km, and increases almost linearly with the decrease in height. For most weak convective precipitation, the reflectivity factor distributes from 15 d BZ to 28 d BZ with the height from 4 km to 9 km. For weak precipitation, the reflectivity factor mainly distributes in range of 15–25 d BZ with height within 4–10 km. It is also shows that weak precipitation is the dominant rain type in summer TP, accounting for 40%–80%,followed by weak convective precipitation(25%–40%), and strong convective precipitation has the least proportion(less than 30%).

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 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.

Temporal Variability of Extreme Precipitation in Jiangxi during 1961-2018

Using 58 years (1961 to 2018) of daily rainfall data, this study focuses on determining trends in the annual and seasonal precipitation extremes of Jiangxi, China, by choosing four extreme precipitation indices, including strong precipitation amount (SPA), mean precipitation intensity (MPI), strong precipitation days (SPD), and strong precipitation frequency (SPF). The monotonic trends are tested by using the Mann-Kendall test for the trends and Sen’s method for the magnitude of the trends. The effective sample size (ESS) method was used to eliminate the influence of serial correlation in the Mann-Kendall test. The results indicated that station Zixi had the strongest extreme precipitation, while Wanzai had the weakest. The trends for each index showed an obvious regional feature over Jiangxi. Increasing trends in annual extreme precipitation indices were found at almost all stations, and the annual variability of the extreme precipitation indices was pronounced, especially for the mean precipitation intensity and the strong precipitation frequency;the majority of these positive trends were shown by the statistical tests. In spring, four indices exhibited significant increasing trends in Northeast and Southwest Jiangxi;however, in summer, only MPI had a remarkable positive trend across almost all of Jiangxi. For the other indices, few stations had remarkable trends. In autumn, MPI and SPF showed remarkable increasing trends in most regions of Jiangxi, while SPA and SPD showed increasing trends at only 6 stations and 3 stations, respectively, which were scattered in the northern and middle parts. In winter, the stations with remarkable upward trends in SPA and SPD were mainly located in the middle of the region, whereas the significant patterns of MPI and SPF were located in the south and middle of the region.

The Analysis on the Temporal and Spatial Variation of Strong Precipitation Caused Flood and Agricultural Disaster Loss in Huaihe River Basin of Anhui Province during Meiyu Period of 2007

[Objective] The research aimed to analyze temporal and spatial variation of strong precipitation caused flood and agricultural disaster loss in Huaihe River basin of Anhui Province during Meiyu period of 2007.[Method] On the basis of rainfalls of each station in Huaihe River basin of Anhui,rainfall data during Meiyu period of 2007 and flood disaster data in the same period,the temporal and spatial distribution characteristics of strong precipitation caused flood during Meiyu period of 2007 and its harm on agriculture were analyzed.The variation rule,distribution characteristics of strong precipitation during Meiyu period in Huaihe River basin of Anhui and its relationship with agricultural disaster loss were discussed.[Result] During Meiyu period of 2007 in Huaihe River basin of Anhui,the rainstorm was more,and the rainfall was large.The precipitation variation showed 'three-peak' trend.Rainfall in Huaihe River basin during Meiyu period of 2007 was greatly more than that homochronously in Yangtze River basin.The rain area over 400.0 mm during Meiyu period mainly located in Huaihe River basin,and the rain area over 600.0 mm mainly located from area along Huaihe River to central Huaibei.The rainfall during Meiyu period gradually decreased toward south and north by the north bank of Huaihe River as the symmetry axis.The rainfall in area along Huaihe River showed wavy distribution in east-west direction.The flood disaster loss index and disaster area of crops in Huaihe River basin of Anhui both increased as rainfall in Meiyu period.[Conclusion] The research provided theoretical basis for flood prevention,disaster reduction and agricultural flood-avoiding development in Huaihe River basin.

Comparative Analysis of Two Short-time Strong Precipitation Processes

By means of conceptual model prediction, two short-time strong precipitation processes in Xiamen on June 12th and 14th, 2008 were analyzed from the aspects of real precipitation, weather situation, physical parameter and radar echo. The results showed that two short-time strong precipitation processes had complete different weather backgrounds, so physical quantities which could reflect atmospheric thermal and dynamic characteristic were different, as well as the characteristic and evolution process of radar echo, and it revealed that two short-time strong precipitation processes in Xiamen had various formation mechanisms and evolution processes. Therefore, many data should be combined to grasp different vantage points in precipitation forecast.

ON STRONG SIGNALS OF MONTHLY PRECIPITATION ANOMALIES IN EARLY RAINING SEASON OF GUANGDONG AND CONCEPTUAL MODELS OF PREDICTION

Reanalysis data from NCEP/NCAR are used to systematically study preceding signals of monthly precipitation anomalies in the early raining season of Guangdong province, from the viewpoints of 500-hPa geopotential height field, outgoing longwave radiation (OLR) field, sea surface temperature (SST) and fourteen indexes of general circulation depicting atmosphere activity at high, middle and low latitutes. Being multiple tools of information, a number of conceptual models are formulated that are useful for prediction of the magnitude of monthly precipitation (drought, flood and normal conditionss).

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.

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.

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%.

MGCPN:An Efficient Deep Learning Model for Tibetan Plateau Precipitation Nowcasting Based on the IMERG Data

The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP) impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address such a challenge,we introduce a model called Multisource Generative Adversarial Network-Convolutional Long Short-Term Memory(GAN-ConvLSTM) for Precipitation Nowcasting(MGCPN),which utilizes data products from the Integrated Multi-satellite Retrievals for global precipitation measurement(IMERG) data,offering high spatiotemporal resolution precipitation forecasts for upcoming periods ranging from 30 to 300 min.The results of our study confirm that the implementation of the MGCPN model successfully addresses the problem of underestimating and blurring precipitation results that often arise with increasing forecast time.This issue is a common challenge in precipitation forecasting models.Furthermore,we have used multisource spatiotemporal datasets with integrated geographic elements for training and prediction to improve model accuracy.The model demonstrates its competence in generating precise precipitation nowcasting with IMERG data,offering valuable support for precipitation research and forecasting in the TP region.The metrics results obtained from our study further emphasize the notable advantages of the MGCPN model;it outperforms the other considered models in the probability of detection(POD),critical success index,Heidke Skill Score,and mean absolute error,especially showing improvements in POD by approximately 33%,19%,and 8% compared to Convolutional Gated Recurrent Unit(ConvGRU),ConvLSTM,and small Attention-UNet(SmaAt-UNet) models.

Analysis of Characteristics of a Heavy Rainstorm Process in Nanchang City on July 7,2020

Based on the conventional observation data,dual polarization radar data and NCEP reanalysis data,the large-scale circulation background field,mesoscale conditions and formation causes of a heavy rainstorm in Nanchang on July 7,2020 were studied.It was found that this heavy rainstorm occurred under the weather background of the confrontation between the northward air flow behind the trough and the strong southwest warm and humid air flow to the northwest of the subtropical high.The divergence at the upper level,the shear in the middle and low levels,the southward movement of cold air at the low level,unusually abundant water vapor and high unstable energy caused the heavy rainstorm weather.In this process,under the influence of continuous eastward movement of several strong echo cells,an obvious"train effect"was formed in Nanchang,so that the local rainfall was continuous and intense.Moreover,the average of VIL was about 17 kg/m 2,and its variation characteristics were consistent with the variation trend of 5-min rainfall intensity,which had a certain indicator effect on short-term heavy precipitation.The topography of the Meiling Mountain in the west of Nanchang had a great influence on the formation and precipitation distribution of the heavy rain process.There was a strong rainstorm center near the mountain,and the precipitation was obviously larger than that in the plain area.

冷涡背景下江苏强对流天气特征分析

冷涡背景下的强对流天气常错报和漏报。为了提高此类强对流天气的预报准确率,利用2013—2022年常规地面和高空观测资料以及地面区域自动站资料,运用统计分析方法,对江苏地区116次冷涡强对流的天气特征进行分析。结果表明:冷涡强对流类型主要有短时强降水、雷暴大风和混合型,其中,混合型发生频率最高(90%),最大小时雨强主要集中在30~49.9 mm/h和50~79.9 mm/h,雷暴大风风力大多为8~9级(48%),其次是10级以上(36%);对流触发时间呈双峰型分布,主要分布在夜间和午后,最高峰为00—02时;不同类型冷涡下的强对流天气既有共性特征,也存在一定的差异性;短时强降水和雷暴大风比较容易发生在沿淮、淮北地区和沿江、苏南地区这两大区域,冰雹落区则相对比较分散。

基于Himawari-8静止卫星多通道资料的重庆地区短时强降水反演研究

收集了2021年重庆地区8次区域性暴雨天气过程中地面降水强度大于等于20mm/h的数据,匹配了相应时间空间范围的Himawari-8静止气象卫星多通道资料,建立了降水强度与辐射特征一一对应的数据集。在此基础上采用单位特征空间归类分析法,选择0.64μm、1.6μm、3.9μm、6.2μm、7.3μm、10.4μm等多个通道组成二维光谱空间,反演了强降水像素点的分布范围和集群特征,并基于反演结果开展了重庆地区短时强降水识别研究。提出了一种基于卫星多通道资料的强降水落区阈值判识方案,并利用该方案对2021~2022年重庆地区的16个强对流天气个例进行了检验。结果表明,该方案能够实现全天24h、逐10min的强降水落区连续动态监测,整点及整点前10min、前30min的卫星资料对降水落区的反演准确率达到70%~80%。

江门儿童公园灾害性天气特征与防御对策

根据江门市外海气象自动站(G2123)2010—2022年风、降雨资料,结合粤港澳闪电定位系统(GHMLLS)资料,利用分类统计法,分析江门儿童公园灾害性天气特征。结果表明,儿童公园所在区域年均风速明显高于江门市区年平均风速,7—8月降雨量均大于江门市区平均值,雷电高发时段为5—9月的10时至20时。提出针对灾害性天气的防御对策,有利于保障公园工作人员和游客的人身安全。

Short-term and imminent geomagnetic anomalies of the Wenchuan M_S8.0 earthquake and exploration on earthquake forecast

The diurnal variation of the geomagnetic vertical component is exhibited mainly by changes of phase and amplitude before strong earthquakes. Based on data recorded by the network of geomagnetic observatories in China for many years, the anomalous features of the appearance time of the minima of diurnal variations （i.e, low-point time） of the geo- magnetic vertical components and the variation of their spatial distribution （i.e, phenomena of low-point displacement） have been studied before the Wenchuan Ms8.0 earthquake. The strong aftershocks after two months＇ quiescence of M6 aftershocks of the Ms8.0 event were forecasted based on these studies. There are good correlativities between these geomagnetic anoma- lies and occurrences of earthquakes. It has been found that most earthquakes occur near the boundary line of sudden changes of the low-point time and generally within four days before or after the 27th or 41st day counting from the day of the appearance of the anomaly. In addition, the imminent anomalies in diurnal-variation amplitudes near the epicentral areas have also been studied before the Wenchuan earthquake.

Anomalies of Precursory Group and Grouped Strong Earthquakes in the Sichuan-Yunnan Region

Three methods of extracting the information of anomalies of a precursory group are put forward, i.e., the mathematical analyses of the synthetic information of earthquake precursors (S), the inhomogeneous degree of precursory groups (ID) and the values of short-term and impending anomaly in near-source area (NS). Using these methods, we calculate the observational data of deformation, underground fluid and hydrochemical constituents obtained from different seismic stations in the Sichuan-Yunnan region and conclude that the synthetic precursory anomalies of a single strong earthquake with M S6.0 differ greatly from those of the grouped strong earthquakes, for the anomalous information of precursory groups are more abundant. The three methods of extracting the synthetic precursory anomaly and the related numerical results can be applied into the practice of prediction to the grouped strong earthquakes in the Sichuan-Yunnan region. Inhomogeneous degree (ID) of synthetic precursory anomaly can be identified automatically because it takes the threshold of distributive characteristics of the anomalies of precursory group as its criterion for anomaly.

Comparative Analysis of Strong Convection Process of Convective Cold Cloud and Convective Warm Cloud Type

On the night of April 20, 2017, there was a heavy rain in Longyan City, accompanied by strong convective weather such as strong lightning, short-term heavy precipitation, and 6 - 8 thunderstorms. The three-hour rain intensity and the six-hour rain intensity of Shanghang Tongxian Township and Nanyang Town were once in a century. Through the use of radar, radar wind profile and lightning locator data, the process can be divided into two phases: The first stage is the strong precipitation stage of Changting Datong Town during the 20 - 22 periods on the 20th. The process is accompanied by short-term heavy precipitation (59.7 mm/h), strong lightning activity, and 6 - 8 thunderstorm gales. It is a convective cold cloud dominated precipitation. The second stage is the strong precipitation stage of Shanghang Tongxian Township on the 21st, 02 - 04, and the short-term strong precipitation intensity reaches 75.7 mm/h, but the lightning and wind activity are weak, which is the convective warm cloud-oriented precipitation. There are significant differences in the strong convective weather between the two phases in the same background. The analysis shows that the strong echo of the first stage radar (above 60 dBz) is block-shaped southward, the speed of movement is fast, the height of the echo top is high, and the rear nascent monomer forms a train effect. In the second stage, the southwest-northeast-oriented convective zone moves to the northeast direction, forming the train effect of the echo zone. The center intensity is above 50 dBz, the echo top height is low, and the precipitation center moves slowly. This caused a large amount of accumulated rainfall. In this paper, the radar data is used to analyze the heavy rainfall process on the west coast of the straits, which has certain indication significance for the predictability of strong convective weather.

Recurrence anomaly of ground water behavior before strong earthquakes in North China

By analyzing the relationship between ground water behavior and strong seismic activity during the past more than 20 years in North China, we have found similar water level descending variation of a part of wells in the short-term stage before several strong earthquakes. The characteristics of anomaly are: at the beginning, water level dropped abruptly or accelerated to drop; then it turned to slow rising with a smaller amplitude than that of descending; earthquakes occurred during the slow-rising process of water level, and at that time or before earthquake occurrence, water level rose with a large amplitude. Among more than 100 wells in North China, the descending anomalies were not recorded for many times, but similar variation processes of water level were noted at different wells before several strong earthquakes, which proves that seismic precursory anomalies of ground water are of certain recurrence features, occurring repeatedly before different strong earthquakes. Therefore, it is necessary to study the genesis of this type of anomaly and its relationship with strong seismic activity.