Vol.30, NO.1, 2019

Display Method:
Design and Initial Implementation of Array Weather Radar
Ma Shuqing, Chen Hongbin, Wang Guorong, Zhen Xiaoqiong, Xu Xiaoping, Li Siteng
2019, 30(1): 1-12. DOI: 10.11898/1001-7313.20190101
With the development of phased array technology and networked radars, focusing on the requirement of small-scale weather fine detection, the array weather radar (AWR) is developed, which is a distributed and highly collaborative radar. The traditional Doppler weather radar can obtain radial velocity of cloud or precipitation targets. However, single radial velocity of a spatial point cannot reflect the movement information of precipitation and atmosphere. A multi-radar network can obtain a plurality of radial velocity values using a collaborative detection method, but disadvantages are that the time difference of the same single spatial point obtained by multiple radars is high, leading to composition error of the velocity or invalid observation.The AWR comprises at least three phased array transmit-receive subarrays (subarrays for short), and the detection region of the AWR can be enlarged by increasing the number of subarrays. The AWR employs a multi-beam phase array scanning technology, which has 4 transmission beams and 64 receiving beams covering an elevation angle between 0° and 90°. And meanwhile, a 360° azimuth is covered by mechanical scanning. One volume scanning time of the AWR is 12 s which are several tenths of the traditional Doppler weather radar. Each three adjacent subarrays work as a group, which performs collaborative scanning to ensure data time differences at the same spatial point from three adjacent subarrays are less than 2 s, and then correct flow fields can be synthesized by using radial velocity of the subarrays. This is a big progress in acquiring thermodynamic information and dynamic information of precipitation targets.One AWR consisting of three subarrays has been deployed at Changsha Airport and has acquired three-dimensional velocity and intensity (reflectivity factor) data, and more fine information of small-scale weather systems may be obtained by using data. There are still a lot of problems to be solved and a lot of works to be done in the field of the AWR technology and application.
Indicators of Chilling Damage for Spring Maize Based on Heat Index in Northeast China
Wang Peijuan, Huo Zhiguo, Yang Jianying, Wu Xia
2019, 30(1): 13-24. DOI: 10.11898/1001-7313.20190102
Chilling damage is one of the most destructive disasters for spring maize in Northeast China (Heilongjiang Province, Jilin Province, and Liaoning Province). Proper indicators of spring maize chilling damage are important for understanding the spatio-temporal distribution characteristics of disaster, dynamic monitoring, early warning, and conducting risk assessment. Therefore, it is of great scientific significance for the safe production and reasonable spatial planting of spring maize in China. Daily time series of air temperature during the past 55 years (1961-2015) at 82 meteorological stations, phenology at different developmental stages of spring maize from 1981 to 2013 at 61 agro-meteorological stations, and historical chilling damage records during the past 55 years (1961-2015) are jointly used to establish chilling damage indicators of spring maize at different developmental stages. The heat index with significant biological basis is selected as a factor, and its average at different developmental stages of spring maize is calculated based on three physiological temperatures. And then, 15 heat index sets of spring maize chilling damage samples collected from historical disaster records are built in the context of the combinations of five developmental stages of spring maize (seedling to clover, clover to jointing, jointing to blossom, blossom to milk, milk to physiological maturity) and three chilling damage levels (light, moderate, and severe). Kolmogorov-Smirnov (K-S) test method is used in checking the best distribution fitting functions of the heat index sets, and 15 normal distribution functions are established by comparing three fitting functions, including normal distribution, exponent distribution, and evenly distribution. Each critical threshold of spring maize chilling damage levels at different developmental stages is determined by using the upper limit of 95% confidence interval. The rationality of the spring maize chilling damage indicator is validated by using 25 independent samples. Results show that the verification based on the spring maize chilling damage level indicators is detected to be basically consistent with historical records, with 80% assessment being thoroughly consistent and all the errors of validation samples being within one level. Meanwhile, consistent rates of chilling damage indicators for three chilling damage levels are all above 75%.
The Spring Maize Drought Index in Northeast China Based on Meteorological Drought Index
Song Yanling, Wang Jianlin, Tian Jinfeng, Peng Mingxi
2019, 30(1): 25-34. DOI: 10.11898/1001-7313.20190103
Drought is the main disaster which influences spring maize over Northeast China, and spring maize yields are often affected by large regional and sustainable drought seriously. The decreasing effects can be described with meteorological drought index or agriculture drought index. Using the soil relative moisture data and county spring maize yield, as well as meteorological drought index SWAP (standardized weighted average of precipitation), a new spring maize drought index (IMD) is proposed, which can reflect the decreasing maize yield induced by drought. Using soil moisture data, the spring maize drought limit is firstly researched based on SWAP. Results show in different stages of spring maze growth, SWAP thresholds are different, which are -0.9 for sowing and seeding stage, -1.0 for seeding and elongating stage, -1.2 for elongating and flowering stage, and -0.7 for flowering and maturity of spring maize. In other words, the growth of spring maize can be influenced when SWAP is moderate drought. A new spring maize drought index is researched based SWAP and SWAP limits. And results also show there is a good relationship between spring maize drought index and the provincial crop area affected by drought, especially in drought years. The coefficient between spring maize drought index and the provincial crop area affected by drought is 0.69 in Liaoning, and 0.73 in Jilin, as well as 0.64 in Heilongjiang, which indicates the new spring maize drought index can indicate actual maize drought. Finally, the classification of drought is divided using the county spring maize yields. The drought grades are defined according to the corresponding decrease of spring maize yield, light drought for (3%, 5%] decrease, moderate drought for (5%, 10%] decrease, severe drought for (10%, 20%] decrease, and extreme drought when the spring maize yield decrease is more than 20%. As a result, when light drought, moderate drought, severe drought and extreme drought happens, the spring maize drought index range is (3.2, 4.2], (4.2, 6.7], (6.7, 11.7], and above 11.7. The research could provide effective method for drought prevention and disaster reduction.
Process Grade Indicator Construction and Evolution Characteristics of Late Rice Flood in Hunan
Wang Tianying, Huo Zhiguo, Yang Jianying, Li Xuhui, Wu Li, Zhang Guixiang
2019, 30(1): 35-48. DOI: 10.11898/1001-7313.20190104
Focusing on the late rice in Hunan, daily precipitation data during 1961-2010 from 68 meteorological stations and phenophase data from 17 agrometeorological observation stations in Hunan are analyzed, and 125 late rice flood process precipitation samples are recognized, including disasters of 3 growth stages (transplanting-tillering, jointing-booting, blooming-maturity) and 3 flood grades (light, moderate, severe). Quantile-quantile plot, Shapiro-Wilk test and Student's t-distribution are employed for the suitability test and critical value calculation of flood process precipitation samples from each flood disaster sample sets. And then, late rice flood disaster grade indicators during different growth periods are determined by critical values and verified by independent samples. Temporal-spatial evolution characteristics of late rice flood disaster in Hunan are analyzed based on the constructed flood level indicators, M-K test and ArcGIS. Results show that, there is high consistency between indicator verification result and history record, indicating the constructed flood level indicators can reflect the actual late rice flood disaster situation. Thresholds of the same flood grade in different growth periods are different, ascending from transplanting-tillering stage, jointing-booting stage to blooming-maturity stage. Main occurrence years of Hunan late rice flood are 1961, 1969, 1980, 1987, 1988, 1994 and 1997. Late rice flood disaster is most serious in the 1960s and the 1990s, and the total flood frequency mutated in 1994 and declined afterwards. The total flood frequency of late rice is highest in transplanting-tillering stage, followed by jointing-booting stage, and blooming-maturity stage is the lowest. Light flood has the highest incidence rate during blooming-maturity period, while moderate and severe flood both has the highest incidence rate during jointing-booting period. The total flood frequency during transplanting-tillering and blooming-maturity periods decrease after the year of 2000, but are still similar to the 1990s during jointing-booting stage. The flood-prone areas are located in Chenzhou and Yueyang, severe floods mainly located in mountain area in Loudi and Chenzhou, and areas with relatively less flood are mainly located in central and southern Hunan (the Hengshao Basin). The occurrence of late rice flood disaster gradually decreases from the 1960s to the 1980s, then increases in the 1990s, and decreases in the 2000s. The flood-prone area of each grade and total all moves from the north to the south in Hunan these years.
Comparative Study of Different Error Correction Methods on Model Output Wind Field
Zeng Xiaoqing, Xue Feng, Yao Li, Zhao Shengrong
2019, 30(1): 49-60. DOI: 10.11898/1001-7313.20190105
The meshing forecast products is an important direction for the future development of China Meteorological Administration. With the development of the grid forecast business and approaching of Beijing Olympic Winter Games in 2022, the forecast of the wind is very important. In order to promptly correct forecast results using grid observation fusion products, grid forecasting products with higher resolution and accuracy are obtained, and the high-frequency grid wind fusion products generated by the HRCLDAS (High Resolution China Meteorological Administration Land Data Assimilation System) system of National Meteorological Information Center as observations are studied. Eight different error correction methods and two different wind field models are used to correct European Centre for Medium-Range Weather Forecasts (ECMWF) 10 m wind forecast field. The test sample time is selected from 1 January 2017 to 28 February 2017, and from 1 June 2017 to 31 July 2017, and two forecast simulations are conducted. In each trial, 24 h corrected forecast test is carried out for two start times at 1400 BT and 2000 BT, and eight different correction methods are used to correct the prediction of ECMWF 10 m wind forecast field. Grid forecast verification is performed on grid results. At the same time, grid prediction results from 8 corrected methods is interpolated to 2400 national surface meteorological stations and station forecast verification is performed on grid results. From the grid verification result and site verification result of two trials, using the latest observations as a predictor, wind forecast effects of 3-6 h is significantly improved. For the correction of the wind direction, the correction effects are slightly improved. Results show that the two-factor model with dynamic coefficient has the best correction effects on the average absolute error, accuracy and absolute error distribution frequency of both grid and site test. Sliding modeling allows the correction model to follow the trend of ECMWF 10 m wind forecast system error. After the optimal method is corrected, the wind speed error in most parts of South China, East China and North China is below 1 m·s-1, especially the large error is significantly reduced, and the wind direction error is also reduced. However, there are still some mean absolute error of 1-3 m·s-1 in the Qinghai-Tibet Plateau, central Xinjiang and Inner Mongolia. Due to local effects of the wind, the correction field of the interpolation to the site still has a certain gap with the actual situation of the site. If prediction result fusion technology is carried out, it is expected that there will be better grid prediction results.
The Application of Recurrent Neural Network to Nowcasting
Han Feng, Long Mingsheng, Li Yuean, Xue Feng, Wang Jianmin
2019, 30(1): 61-69. DOI: 10.11898/1001-7313.20190106
Radar extrapolation is an important means in nowcasting. The radar extrapolation methods widely used in China include COTREC and Optical Flow, by which two consecutive echoes are used to diagnose the advection velocity within rain analyses, involving the solution of Lagrangian persistence equation. A new method RNN(recurrent neural network) is applied in nowcasting. Using PredRNN(predictive RNN), by modeling historical radar data, the prediction of radar echo in the next hour is given. PredRNN consists of ST-LSTM unit, which is an improvement of LSTM. One advantage of using PredRNN is the operation of the state accumulation and the hidden layer output is replaced by convolution. Therefore, the neurons not only can get timing relationships, but also extract spatial features like convolutional layers. Another advantage is the addition of new spatial memory, which can enhance the transportation of the spatial feature information in different layers. In order to test the model performance, two radars of Daxing District of Beijing and Guangzhou are analyzed. The radar echo is pre-processed through quality controlling to remove isolated echo, abnormal echo, invalid radial and echo below 15 dBZ and ground echo, and then the combined reflectivity (CR) is made by 0-5 layers of data. To examine the applicability of the PredRNN, a contrast experiment is designed between PredRNN and COTREC, including an independent verification over months of each radar and two severe convective cases analysis. The test is carried out by point by point in three different reflectivity thresholds:20 dBZ, 30 dBZ and 50 dBZ. Indexes of verification are CSI, POD and FAR. The time range of the test is 0-1 h by 6 min. Results show that PredRNN has better forecast performance in all the verification items especially in 20 dBZ and 30 dBZ, when the CSI can be raised by 0.15-0.30, POD can be raised by 0.15-0.25, and FAR can be reduced by 0.15-0.20. This effect of improvement enhances with time. Although forecast performances of both PredRNN and COTREC fall with time, the performance of PredRNN method descends more slowly. The forecast performances of both PredRNN and COTREC fall with the increase of the combined reflectivity factor strength, which shows the insufficient of prediction ability for the region with intensity over 50 dBZ. Two cases show that the PredRNN method has predictive ability for the change of reflectivity factor intensity. In summary, PredRNN is suitable for nowcasting, and its forecast performance is much better than COTREC.
Effects of a Modified Sub-grid-scale Terrain Parameterization Scheme on the Simulation of Low-layer Wind over Complex Terrain
Liu Yujue, Miao Shiguang, Liu Lei, Hu Fei
2019, 30(1): 70-81. DOI: 10.11898/1001-7313.20190107
Due to the limited representation of observation over complex terrain, high resolution model becomes a favorable tool. Fine numerical simulation of wind field is quite important for micro-siting wind farms and wind energy resources assessment, especially in the complex terrain area. The accuracy of low-layer wind simulation over mountain area is one of the difficulties and key points in the field of wind energy research. The state-of-the-art WRF (Weather Research and Forecasting) model is one of the most widely used mesoscale numerical weather models for wind energy assessment in recent years. However, effects of sub-grid-scale topographic shape on surface wind field are not considered. With the new WRF version 3.4.1, a sub-grid-scale terrain parameterization scheme named Jiménez scheme is added into the YSU (Yonsei University) planet boundary layer parameterization scheme. The Jiménez scheme is designed aiming to reduce the systematic error of wind speed overestimation over valleys or plains and underestimation over hills conversely. However, correction effects of original WRF simulated 10 m wind speed by Jiménez scheme show great differences under different horizontal resolutions, particularly when over high hills. A series of sensitive numerical experiments are carried out under windy days for the Taihang Mountains in the west of Beijing-Tianjin-Hebei area. The main purpose of these experiments is to address some of issues regarding Jiménez scheme and try to solve the existing problems by establishing a relationship between the key topographic parameter Ct and the model grid spacing(dx/dy) to fit different numerical simulation for high resolution based on secondly SRTM topographic dataset. The simulated 10 m wind speed results of WRF without Jiménez scheme, with original Jiménez scheme and modified Jiménez scheme version are compared with observations of 3 automatic weather stations during the MOUNTAOM (MOUNtain Terrain Atmospheric Observations and Modeling) campaign which is prepared for 2022 winter Olympic Games. Results show that the modified Jiménez scheme can partially correct the error of the original Jiménez scheme at lower and higher resolutions. The simulated 10 m wind speed near the ground by modified version is closer to the actual condition. The correction method for Jiménez sub-grid-scale terrain scheme can provide reference for high resolution wind simulations over complex terrain and help users to obtain more detailed information on the surface wind field for wind energy related researches and applications.
The Vertical Transport of the Ozone and Carbon Monoxide by Severe Convective Weather
Li Dongchen, Lin Cizhe, Yin Yan
2019, 30(1): 82-92. DOI: 10.11898/1001-7313.20190108
Clouds have significant impacts on the quality of the atmosphere in the troposphere, the redistribution of chemical gases and climate change. In general, environmental and climatic effects of atmospheric pollutants are to a large extent determined by their vertical distribution in the atmosphere. Deep convective clouds, as the main carrier of vertical conveying of atmospheric mass, can transport air from the boundary layer to the upper troposphere in a very short time. So various chemical gaseous components can be transported from lower layers to the upper troposphere or even the lower stratosphere in a relative short time and this process can also increase the chemical gas residence time in the atmosphere.Using ozone and carbon monoxide data obtained from aircraft observations for altitude from 1 to 15 km near Darwin(12.41°S, 130.9°E) in northern Australia, in the Aerosol and Chemical Transport in Tropical Convection (ACTIVE) campaign from November 2005 to February 2006, a squall line process on 20 January 2006 and a non-convective weather day on 27 January 2006 are compared. Differences between the distribution of ozone and carbon monoxide in severe convective and non-convective conditions are analyzed. According to results of contrastive analysis, there is a very close relationship between the peak concentration of ozone and carbon monoxide in upper troposphere and the appearance of strong convective systems. Severe vertical ascending motion inside the deep convective cloud carries ozone, carbon monoxide and other chemical gases to the top of the troposphere, and then these chemical gases accumulate in the upper troposphere, leading to a peak concentration. Results show that in convection, the concentration of cloud particles and chemical gas such as ozone, carbon monoxide rise and their variability is large too. At the same time, peak concentrations of ozone and carbon monoxide appear in the upper troposphere. But outside convective clouds, concentrations of cloud particles, ozone and carbon monoxide all drop. On the contrary, under non-convective condition, concentration of ozone is stable, and no peak value is observed.Results show that deep-convective cloud have obvious vertical conveying effects on ozone and carbon monoxide. The distribution of ozone and carbon monoxide closely rely on vertical conveying of strong convection, as well as distribution of meteorological factors and synoptic dynamic transportation process.
Effects of Low-frequency Oscillation on the Persistent Extreme Precipitation in Sichuan Basin
Huang Yao, Xiao Tiangui, Jin Ronghua
2019, 30(1): 93-104. DOI: 10.11898/1001-7313.20190109
Based on precipitation data of surface meteorological stations and NCEP/NCAR reanalysis data during 1981-2016, the persistent extreme precipitation is defined for Sichuan Basin, and 15-30-day low-frequency oscillation characteristics of precipitation and atmosphere are analyzed in detail by means of wavelet analysis, synthetic analysis and Butterworth filtering, which provide theoretical basis and reference for extended period forecast.Results show that persistent extreme precipitations in Sichuan Basin are concentrated from June to September, which generally last for 3 days. The precipitation has low-frequency oscillation characteristics of 15-30 days and 30-60 days, and mainly 15-30-day oscillation. During the precipitation, the South Asia high and upper jet form a high-level divergence field, the subtropical high is strong and extends westward, the low pressure in the Lake Baikal and the Sea of Okhotsk extends southward, and the airflow in South China Sea and the airflow in the west side of subtropical high converge and pass northward. During the precipitation, low-frequency systems in each height layer and each latitude cooperate with each other in three-dimension space to form a low-frequency circulation which is favorable for precipitation. The vertical baroclinicity of the low-frequency system is conducive to the accumulation of unstable energy and provides energy conditions for precipitation.In the low-frequency flow field, during the precipitation period, the low-level and middle-level north-south airflows merge into the basin to form a convergence area, and the upper layer appears as a northerly wind. The low-latitude cyclone in the lower layer is generated in the western Pacific Ocean and gradually moves northwestward to the South China Sea to bring warm and humid airflow. The southeast side of the mid-high-latitude Lake Baikal generates a cyclone which then moves eastward to the vicinity of the Okhotsk Sea to enhance the northerly wind transport. The mid-high-latitude Eurasia low-pressure center in the middle layer corresponds to the transverse trough in the polar region of the original field. With the transverse trough turning vertical, the center of the low-pressure moves to the southeast, arriving at Mongolia in precipitation, and splits the small trough to the downstream, strengthening in the Sea of Japan, followed by the high-pressure center to the Ural Mountains. During the precipitation period, the divergence of Sichuan Basin at high-level is positive, which is favorable for the continuous convergence and upward movement at lower and middle layers.
Effects of Channel-induced Charge on Discharge Activity Characteristics
Yu Mengying, Tan Yongbo, Shi Zheng, Liu Jun, Wang Mengyi, Zheng Tianxue
2019, 30(1): 105-116. DOI: 10.11898/1001-7313.20190110
In order to explore effects of different polarity charge implantation method on the discharge of thunderstorm clouds in the charge-replacement scheme after lightning discharge, a batch of sensitive experiments are implemented by changing the channel-induced charge to simulate a typical thunderstorm case in Nanjing, based on existing three-dimensional (3-D) thunderstorm cloud electrification and discharge patterns. Eeffects of thunderstorm cloud discharge are discussed from the perspective of space charge structure after discharge, lightning channel length, lightning frequency and type. Simulations show that the amount of induced charge by the lightning channel has a significant effect on the spatial charge structure distribution and the length of the intra-cloud flash channel. As the amount of induced charge in the channel increases, the number of lattice points where the polarity of the space charge is reversed before and after discharge increases, and the space charge structure becomes more complex, which in turn increases the intra-cloud flash with a shorter length of the lightning channel. The space charge structure is disordered, and it becomes more difficult for a wide range of identical-polar charge stacks to form during the development process. Meanwhile, it is also difficult for the lightning channel to pass through charge stack with the same polarity during the propagation process, and therefore the intra-cloud flash channel is limited to a pair of smaller heteropolar charge stacks. Eventually, the frequency of intra-cloud flashes that leads to shorter lightning channel lengths increases. The total amount of channel induced charge accumulation under different induction control multiples can be considered approximately the same within the error tolerance. The frequency of intra-cloud flashes is negatively correlated with the average cumulative amount of channel charges in different lightning channel induced charges:When the average cumulative amount of channel induced charges increases, the frequency of intra-cloud flashes will decrease. The change of the induced charge amount in the channel makes the charge distribution of the space charge region unbalanced. The frequency and type of the cloud-to-ground flash are affected by many factors, and the changing pattern is not obvious. Therefore, the channel-induced charge amount has little correlation with the frequency and type of cloud-to-ground flashes.
Grade Evaluation of Detection Environment of Meteorological Stations in Beijing
Wang Chenggang, Wei Xialu, Yan Jiade, Jin Lianji
2019, 30(1): 117-128. DOI: 10.11898/1001-7313.20190111
With the rapid development of urbanization, meteorological station detection environment is constantly changing. A large number of research results show that the impact of detecting environmental changes on meteorological elements is very obvious, and the spatial representativeness of observations has strong diversity characteristics. Therefore, it is necessary to establish a scientific and reasonable assessment method for the spatial representativeness of observation sites.Using Landsat satellite remote sensing data of 6 selected summers of 1990, 1994, 2000, 2005, 2011, 2013 and digital elevation data in 2009, the landscape indicator parameters around national surface weather observatories in Beijing are calculated and statistical analysis are carried out with observations of national surface meteorological stations. Results show that parameters, such as land use types, landscape indexes around station, building height and sky view factor, etc., can digitally denote the configuration information of the meteorological detection environment.The correlation between landscape indicator parameters and meteorological elements is analyzed. In the study of landscape indicator parameters affecting temperature changes, three high-altitude stations (Foyeding Station, Xiayunling Station and Shangdianzi Station) are used as climate background stations to select advantages and disadvantages of existing indicators. The study shows that main factors which affect the difference of temperature are urban area, water area, largest patch index, largest patch of urban area, contagion index, mean fractal dimension and sky view factor. In the study of response of the landscape indicator parameters to the absolute humidity, the correlation between the absolute humidity and the observed landscape indicator parameters which pass the significance test shows that, among the landscape indicator parameters, urban area, water area, largest patch index, largest patch of urban area, contagion index, mean fractal dimension and sky view factor have good relationship with humidity. But only three landscape indicator parameters have good response correlation with small wind frequency, which are water area, largest patch index and largest patch of urban area. Based on statistical results, a set of preliminary methods for evaluating the detection environment are obtained according to the response intensity of landscape indicator parameters to each element. By classifying different stations and obtaining the effective influence range of site data, the landscape indicator assessment which can detect the environmental impact degree may streamline the assessment.This method is used to evaluate 15 national surface meteorological stations in Beijing. The impact of the surrounding environment is lowest in Huairou Station, followed by Fangshan Station, Changping Station, Miyun Station, Pinggu Station and Yanqing Station. There are two stations with the greatest environmental impacts, namely Fengtai Station and Chaoyang Station.