Vol.30, NO.2, 2019

Display Method:
Review on Disaster of Hot Dry Wind for Wheat in China
Huo Zhiguo, Shang Ying, Wu Dingrong, Wu Li, Fan Yuxian, Wang Peijuan, Yang Jianying, Wang Chunzhi
2019, 30(2): 129-141. DOI: 10.11898/1001-7313.20190201

Hot dry wind (HDW) is one of the major agro-meteorological disasters which impact wheat production in North China. From the aspect of its definition, classification and research methods, recent progress are reviewed on its influencing mechanism, meteorological environmental causes, disaster index, spatial-temporal distribution, monitoring and forecasting measures, defensive and mitigation ways, and the future research direction is discussed. In China, HDW can be classified as three major kinds, including high temperature with low humidity, green-dry after rain, and dry wind. HDW can intensify transpiration, damage flag leaf, weaken root activity, shorten growth duration, and decrease accumulated dry matter, chlorophyll content and photosynthetic rate. Meteorological environment of HDW is mainly determined by dry hot-air weather system, influenced by climate warming and soil moisture. Disaster index of HDW can be divided into three kinds:Morphological, synoptic, and comprehensive index. The damage of HDW to wheat is heavy in both east and west parts while light in the central part of China. HDW mainly occurs in three areas, including the Huang-Huai-Hai Plain, Hexi Corridor and Xinjiang. The damage decreases with elevation of altitude, and generally it has no impact in areas higher than 1700-1800 meters. One month before harvest is the main occurrence period of HDW. It starts from early May in China, and postpones to mid-late July from south to north and from southeast to northwest. For winter wheat, the disaster date is earlier than spring wheat. Presently, major monitoring and forecasting methods include ground meteorological monitoring, remote sensing monitoring, classification and forecast based on weather prediction, statistic forecast, and numerical prediction products. Temporal and spatial pattern of HDW in China is obviously affected by the change of wheat plantation layout, climate, irrigation and field management. Under historical climate warming condition, HDW days in most regions have a sudden change in the 1980s and 1990s. During the recent 30 years, HDW days and the degree of influence have increased obviously. Improvement of irrigation conditions obviously relieves its occurrence and influence. Future research directions include incorporating soil moisture into the existing HDW hazard grade index, researching and developing process-based disaster monitor and assessments, prediction and early warning methods, model simulations and business application technologies, investigating the change of spatial and temporal distribution of HDW and the formation of its meteorological environment under future climate change and wheat planting layout change.

Review on Forecast Methods of Rainfall-induced Geo-hazards
Chen Yueli, Zhao Linna, Wang Ying, Wang Chengxin
2019, 30(2): 142-153. DOI: 10.11898/1001-7313.20190202
The classification of geological hazards is very complicated for there being different methods according to different standards. Factors triggering geological hazards are divided into two categories:Internal and external. Internal factors mainly include geological and geomorphological factors, and external factors include precipitation, earthquake, volcanic eruption and human activities. The majority of the geological hazards are triggered by precipitation, especially heavy rainfall.Geological hazards including the debris flow, landslide and collapse triggered by rainfall are discussed. Geological hazard forecast plays a major role in the disaster risk reduction paradigm as cost-effective method to mitigate disaster damage. The geo-hazard forecasting mainly refers to the temporal and spatial warning in specific areas. Based on reviewing literatures related to rainfall-induced geological hazard prediction, related concepts are formulated, and previous researches are sorted and summarized. Afterwards, characteristics and application of the rainfall-induced geo-hazard prediction models are summarized, including the implicit statistics model, the explicit statistics model and the dynamic models. At present, the first-generation implicit statistic models considering precipitation characteristics are further developed into a second-generation explicit statistic models which consider rainfall factor, geology and geomorphology factors. Statistic models are widely used in the operational forecasting for their conciseness and convenience. However, the accuracy of the spatial and temporal simulating is limited because models can't simulate the physical mechanism of geological hazards. Geo-hazard early warning systems based on dynamic model can provide a better forecasting product with higher spatial and temporal resolution. The dynamic model is gradually developed from a slope stability model based on the theory of vertical infiltration to a coupled hydrological-geotechnical model.The geo-hazard forecasting model is the key of the early warning system. Lots of rainfall-induced geo-hazard early warning systems based on the statistic model have been set up in China. Meteorological models are used to forecast the rainfall in order to issue a warning with a given lead time. A complete geological hazards forecasting chain include the rainfall predicting, the disaster model, model results displaying, and the early warning releasing. The research foci of geological hazard forecasting have gradually expanded from the prediction model to the input of multi-source precipitation data, the display and release of early warning. Based on previous literature reviews and analysis, the coupled hydrological-geotechnical framework combined with multi-source forecasting precipitation data as an important direction for future development can be considered a useful geo-hazard risk mitigation measure to employ over widespread areas.
A Spatial Verification Method for Integrating Wind Speed and Direction
Zhang Bo, Zhao Bin
2019, 30(2): 154-163. DOI: 10.11898/1001-7313.20190203
In traditional statistical analyses, the vector wind field is always verified by wind speed and wind direction separately. However, assessment results of wind speed are often contrary to those of wind direction, which then makes it difficult to obtain a uniform conclusion. To solve this problem, a novel selection scheme of wind speed thresholds is defined based on the probability distribution of wind speed, which is not affected by geographical and seasonal factors and it can keep universality in different complex environments. A vector wind classification is established based on integrating wind speed classes and wind directions. Using the spatial verification technique of fraction skill score (FSS), a vector wind verification method is developed by integrating wind speed and wind direction together. Based on hourly forecast products with different resolution (10 km and 3 km) simulated by GRAPES_Meso model from 1 April 2018 to 30 April 2018, assessment results show that the randomness of the wind direction forecast will decrease with the increasing of wind speed, which indicates it's difficult to predict the wind direction of weak wind speed successfully. By the comprehensive analysis of the vector wind field, it is found that the high-resolution (GRAPES_3 km) forecasting performance has a maximum score advantage of 0.24 on the 170 km spatial scale than the lower one (GRAPES_10 km). Scores in adjacent region are highly consistent, and it does not change the evolution of the score with the time series. And therefore, a comprehensive score can be calculated and used to assess the modelling performance by averaging skill scores in each spatial scale. In this way, deficiencies of artificial definitions of spatial scale can be avoided, which guarantee the spatial verification score of vector wind better practical application value. Simultaneously, different vector wind field classification methods have an impact on evaluation results. By sensitivity analysis, the higher wind classification method can make the score more stable with moderate wind classification one, and the magnitude of comprehensive scores are basically equivalent. The lower wind classification method has a relatively low overall score due to its single classification score weight, and it leads to the weak consistency with results of higher classification method. Therefore, under conditions of computing ability, choosing an encrypted wind direction classification to obtain a vector wind classification method will help to obtain a more stable verification result and improve the convergence and stability of the comprehensive evaluation.
Evaluation on SO2 Emission Inventory Optimizing Applied to RMAPS_Chem V1.0 System
Xu Jing, Chen Dan, Zhao Xiujuan, Chen Min, Cui Yingjie, Zhang Fangjian
2019, 30(2): 164-176. DOI: 10.11898/1001-7313.20190204
Air pollution emission inventory is an important input data of air quality model. The uncertainty of emission inventory is a primary source of error in air quality forecasts and it also affects the regulation of air pollution sources. RMAPS_Chem V1.0 is an operational forecasting system for haze and atmospheric pollution in North China. It is established based on an online coupled regional chemical transport model WRF_Chem. In order to reduce the large deviation of forecasted SO2 concentration, through the test of model accuracy on weather condition, a conclusion is drawn that the simulated error of SO2 concentration mainly comes from the deviation of emission. An optimized SO2 emission inventory is established, first inversed by ensemble square root Kalman filter (EnKF) approach, and then revised by using statistical error correction method. Comparison indicates that the optimized emission has obvious advantages to improve the prediction accuracy of ground SO2 concentration. Distribution of surface SO2 concentration over North China in October 2017 is simulated using initial emission inventory (MEIC_2012) and the optimized emission inventory. Simulated results are compared with observations at 616 stations from China National Environmental Monitoring Center (CNEMC), and the difference between simulated results using two emission inventories is analyzed. Results show that the above emission inventory optimizing method is applicable for the correcting of regional deviation in SO2 emission, which is very effective on improving SO2 forecast accuracy in main regions and urban areas. Simulated results using optimized emissions are closer to the observed value in focus areas of RMAPS_Chem V1.0 system. The largest forecast deviation areas concentrate in south region of Hebei, west region of Shandong and Beijing, which is consistent with the distribution of SO2 emissions deviation. Optimizing of the emission inventory brought significant reduction in forecast deviation in these regions, with root mean square error and normalized mean absolute error reduced obviously. The simulation error show normal distribution characteristics. The probability of error distribution range, the maximum range are significantly narrowed, and the biggest error probability value rises significantly, indicating errors are reduced.
The Wind Turbulence of the Near-surface Layer of Jiangsu Coastal Area and Its Response to Typhoon
Chen Yan, Zhang Ning
2019, 30(2): 177-190. DOI: 10.11898/1001-7313.20190205
In order to study the influence of wind turbulence characteristics on the rational and safe development and utilization of wind energy resources, long-term wind gradient observations are carried out in Jiangsu with five wind towers along the beach. Based on the wind speed and wind direction observations for 42 consecutive months from June 2009 to November 2012, temporal and spatial variation characteristics of the surface layer wind gust factor and turbulence intensity are analyzed. Variation characteristics of gust factor and turbulence intensity with wind speed, the influence of land and sea distribution on gust factor and turbulence intensity are then discussed. Seven typhoons that have great impacts on Jiangsu are selected, including the rare typhoon Damrey in 2012 that landed in Jiangsu, and the typhoon's influence on the wind is discussed. Results show that the gust factor and turbulence intensity are strong at the height of 10 meters, in the coastal areas of Jiangsu. The annual average gust factor of 10 m and 70 m heights in the coastal areas of Jiangsu are 1.50 and 1.24; the turbulence intensities are 0.20 and 0.11, respectively. The frequency distribution of gust factor and turbulence intensity is unimodal. At lower observation heights, the frequency distribution is wider, the peak is lower, and the peak is biased toward the high value area. The influence of sea and land distribution is obvious. The turbulence intensity of offshore wind is significantly greater than that of onshore wind. The wind speed has a significant impact on gust factor and turbulence intensity, which decrease with the increase of wind speed. When a wind greater than strong breeze happens, the gust factor and turbulence intensity are basically stable and less variable. Near the typhoon center, the wind speed has a bimodal change of increasing-subtracting-increasing, and the wind direction changes rapidly in a short time. The turbulence intensity at 10 m and 70 m heights are 0.25 and 0.14, the gust factor at 10 m and 70 m heights are 1.65 and 1.33, much larger than the value around typhoon and without typhoon. During the passage of the typhoon center, the turbulence intensity and gust factor do not decrease with height and they increase between 30 m and 50 m. When the wind speed increases, the turbulence intensity and gust factor decrease overall, but local peaks may occur when the wind is strong breeze to moderate gale while the typhoon center passes, threatening the safety of the turbine.
Spatio-temporal Scale and Optical Radiance of Flashes over East Asia and Western Pacific Areas
You Jin, Zheng Dong, Yao Wen, Meng Qing
2019, 30(2): 191-202. DOI: 10.11898/1001-7313.20190206
Distributions and correlations of flash properties including duration, length, footprint and radiance are investigated in the east Asia and western Pacific areas of 18°-36°N, 70°-160°E and six specially chosen regions (Region 1-6) within it, by analyzing data of lightning imaging sensor (LIS) aboard Tropical Rainfall Measuring Mission (TRMM) satellite from 2002 to 2014. While the flash density over land is generally greatest, followed by offshore waters and deep ocean, the spatial scale and radiance of flash over the deep ocean is the greatest, followed by offshore waters and land, and the duration of flash over offshore waters is the longest, followed by the deep ocean and land. Regions with the largest flash density, duration, spatial extent and radiance are the southern Himalayan front, offshore waters near the east coast of China, deep Pacific Ocean in the southern part of study area and ocean to the east of Japan, respectively. Meanwhile, the flash duration, spatial extent and radiance always have the smallest values over the Tibet Plateau and the southern Himalayan front. In most regions, based on samples during periods of 0900-1400 LT and 1800-0600 LT, the monthly variation of the flash spatial size and radiance is roughly unanimous, except for the ocean to the east of Japan. Inverse correlations of flash activity with flash spatial scale and radiance in the monthly variation is relatively obvious over land. In addition, it is found that some flash properties over some regions in monthly variation are different between periods of 0900-1400 LT and 1800-0600 LT. The flash spatial-temporal scale and the radiance follow lognormal distributions. Relative to the flash over ocean, properties of flash over land tend to concentrate toward smaller values. During 1800-0600 LT when the LIS is of relatively better performance, the median range of flash properties in 6 chosen regions are:Flash duration from 0.18 to 0.29 s, length from 12 to 21 km, and radiance from 0.11 to 0.52 J·m-2·sr-1·μm-1. Correlation analysis between different properties of flash show that relationships between flash properties during 1800-0600 LT are better than those during 0900-1400 LT, and the best correlation is between length and footprint, because they both represent the spatial scale of flash. Relationships between flash spatial scale and radiance are also strong, but the flash duration has weak correlations with flash spatial scale or radiance.
Characteristics of Downward Cloud-to-ground Lightning Flashes Around Canton Tower Based on Optical Observations
Wu Shanshan, Lü Weitao, Qi Qi, Wu Bin, Chen Lüwen, Su Zhiguo, Jiang Ruijiao, Zhang Changxiu
2019, 30(2): 203-210. DOI: 10.11898/1001-7313.20190207

With the progress on the research of lightning hitting high buildings, influences of high buildings on characteristics of cloud-to-ground lightning flashes in the nearby area still need further research. At present, this kind of research are mainly based on data obtained by lightning location system, while optical observations are more visible and should be better considered. Results of optical observations can deepen our understanding of high-building impacts on characteristics of downward cloud-to-ground lightning flashes activity in nearby areas and provide basic data for lightning protection design of high buildings and nearby areas.Based on optical data of Tall-Object Lightning Observatory in Guangzhou (TOLOG) from 2009 to 2014, combined with the lightning acoustics and electromagnetic field variation waveform data, distribution characteristics of 119 downward cloud-to-ground lightning flashes in the northwest of Canton Tower within 3 km in 60° sector region are analyzed statistically. Results show that 43.7% (52/119) of downward cloud-to-ground lightning flashes occurs on four tallest buildings in the area. Lightnings hit Canton Tower, Canton West Tower, Canton East Tower and Guangsheng Building for 20, 12, 10 and 10 times, respectively. Besides 20 (16.8%) flashes directly hit Canton Tower, no downward lightning is observed within 1 km distance from Canton Tower (11.1% of total area). The closest stroke point to Canton Tower is about 1.2 km away. 35 (29.4%) lightning flashes are observed in the area of 1-2 km away from Canton Tower (33.3% of total area). Building lower than 300 m is hit no more than once in the area each. 64 (53.8%) lightning flashes are observed in 2-3 km away from Canton Tower (55.6% of total area). Some buildings with a height below 300 m are hit more than once, up to 5 times. The attraction of Canton Tower to downward cloud-to-ground lightning flashes makes no downward cloud-to-ground flashes observed in the vicinity of 1 km or so. The relative density of the flash (excluding flashes hitting buildings with a height of more than 300 m) increases gradually with the increase of distance. Results indicate that the attraction of high buildings to the downward cloud-to-ground lightning flashes gradually weakens with the increase of distance.

Numerical Simulation of Hygroscopic Seeding Effects on Warm Convective Clouds and Rainfall Reduction
Liu Pei, Yin Yan, Chen Qian, Lou Xiaofeng
2019, 30(2): 211-222. DOI: 10.11898/1001-7313.20190208
With the rapid development of social economy, the frequency of various large-scale and important events is also getting higher and higher. In order to host events more smoothly, the need of society for artificial precipitation suppression technologies during major events is also urgent. Hygroscopic seeding is an important way to suppress precipitation artificially. Although previous research on artificial precipitation suppression basically confirms that the hygroscopic nuclei of smaller than 1 μm can inhibit the convective cloud precipitation, how to use it more effectively to achieve the best effect is still a difficult problem in precipitation research. In order to provide some useful theoretical references for artificial precipitation suppression operations, a two-dimensional slab-symmetric detailed spectral bin microphysical model of Tel Aviv University in Israel is used to simulate the warm shallow convective cloud and precipitation in East China at about 1600 BT on 4 September 2016. The height of the strong radar reflectivity center and the range of high radar reflectivity are basically consistent with observations. The cloud seeding experiments with hygroscopic nuclei smaller than 1 μm are conducted in order to examine sensitivities of seeding effects to seeding time, seeding height and seeding amounts of particles, respectively. Results show that the early seeding in the cloud development stage can lead to more significant effect on rainfall suppression. The earlier the seeding time is, the stronger the inhibition of the growth of large particles. As the seeding time goes backwards, the particle size segment with the most significant inhibition shifts to smaller particle size; the effect of rainfall suppression is more obvious when seeding is carried out just below the area with large supersaturation in the center of cloud. Since a large number of hygroscopic nuclei seeded here enter the supersaturation zone, they are activated to be small cloud droplets, and the cloud water conversion and collision process are suppressed. The reduction rate of ground accumulated precipitation reaches 23.3% when the seeding concentration is 350 cm-3. In addition, with the increase of seeding amounts of hygroscopic nuclei, the precipitation suppression effect is more significant, and the rain is even eliminated. Therefore, seeding hygroscopic nuclei smaller than 1 μm properly in warm shallow convective clouds can achieve expected results of reducing or eliminating rain.
Bias Correction of Summer Extreme Precipitation Simulated by CWRF Model over China
Dong Xiaoyun, Yu Jinhua, Liang Xinzhong, Ma Yuan
2019, 30(2): 223-232. DOI: 10.11898/1001-7313.20190209
Accurate forecast of extreme precipitation plays an important role in guiding the national economy and people's livelihood. The newly developed Climate-Weather Research and Forecasting model (CWRF) is applied to the operational forecasting experiment of China National Climate Center. It provides valuable scientific basis for improving the operational prediction for extreme precipitation.CWRF integrates a comprehensive ensemble of alternate parameterization schemes for each of key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation. This facilitates the use of an optimized physics ensemble approach to improve weather and climate prediction.Daily precipitation data simulated by CWRF from June to August during 1980-2015 and the observation by China Meteorological Administration are used to evaluate the performance of various parameterization schemes, and cumulative distribution function transform (CDFt) correction method is introduced. Based on the CDFt, the probability bias correction model XCDFt is proposed for extreme rainfall by introducing generalized Pareto distribution (GPD) and results are assessed. It shows that Morrison-aerosol parameterization scheme of CWRF model can simulate the spatial distribution of extreme precipitation better as well as correct daily precipitation by CDFt.Simulated results of Morrison-aerosol for daily precipitation threshold and super-threshold samples in summer in North China, Central China and East China are similar to those observed in this scheme. In Changsha, Jinan, Nanjing, and Nanning, GPD characterizes the distribution of each extreme precipitation well. It shows that XCDFt can preserve the CDF form of the observed calibrated precipitation and acquire the small change from the calibration to validations. XCDFt can improve the consistency between model simulation and observation in regional extreme precipitation recurrence levels. In North China, Central China and South China, after model simulation correction by XCDFt, the 20-year recurrence interval of extreme precipitation are closer to the observation, which shows that the revised data are more reliable.Error correction can only be used as a supplementary means to improve extreme precipitation prediction, though. The precision description of model physical process and the improvement of model resolution are the key to improve extreme precipitation prediction level.
Quantitative Assessment of Regional Heavy Rainfall Process in Guangdong and Its Climatological Characteristics
Wu Hongyu, Zou Yan, Liu Wei
2019, 30(2): 233-244. DOI: 10.11898/1001-7313.20190210
Using daily precipitation data of 86 meteorological stations in Guangdong from 1961 to 2017, the standard of regional heavy rainfall process is defined. Assessment methods on composite intensity of regional heavy rainfall process in Guangdong are constructed, which take duration, range, maximum daily precipitation and maximum accumulated precipitation during the process into consideration. Characteristics and changes of the frequency, intensity and rain-waterlogging years of regional heavy rainfall process in Guangdong in recent 57 years are studied. 1211 regional heavy rainfall processes are captured, and the annual average frequency is 21.2 times. There are obvious interannual and interdecadal variations, the highest frequency occurs in 2016 (30 times), and the lowest occurs in 1963 (13 times). The annual frequency of regional heavy rainfall process in Guangdong increases at a rate of 0.08/(10 a) in recent 57 years, though not quite significant. The regional heavy rainfall process in Guangdong mainly occurs from April to September, accounting for 81.9% in the year, among which 45.4% processes occur in the first flood season (April-June), and 36.5% processes occur in the second flood season (July-September). The average duration of single regional heavy rainfall process in Guangdong is 2.3 d, and the longest is 17 d (9-25 June 1968). The average range of a single process covers 20.3 stations, and the process occurring on 28 January 2016 is observed by the most stations (83). The regional heavy rainfall process with the maximum composite intensity index occurs during 12-24 June 2005, reaching 1385.1 mm (Longmen), and this coincides "05.6" torrential rains and floods in Guangdong. The frequency and strength of the regional heavy rainfall process in Guangdong have intermonth, interannual and inter-decade variations, the frequency in May is the highest, and the strength in June is the highest. The annual harvest index of the rain waterlogging in Guangdong increases obviously at a rate of 0.17/(10 a) in recent 57 years. Regional heavy rainfall processes of relatively strong and strong class increase significantly, while those of relatively weak class decrease obviously in recent 57 years. Evaluation results show that there are five heavy rain waterlogging years, i.e., 2008, 2001, 1973, 1994, 1993.
Development and Application of National Verification System in CMA
Wei Qing, Li Wei, Peng Song, Xue Feng, Zhao Shengrong, Zhang Jinyan, Qi Dan
2019, 30(2): 245-256. DOI: 10.11898/1001-7313.20190211
National Verification System in CMA provides a unified verification data environment to realize unified management and service of the observation, forecast and verification data. A standardized and efficient verification operational process is established, which is compatible with multiple data including MICAPS data, GRIB2 data, NWFD data, automatic weather station data and other meteorological data. It works with dozens of verification operation such as national and provincial intelligent grid forecasting, urban weather forecast, quantitative precipitation forecast, and the air quality forecast in big cities. The verification products are displayed in spatial distribution map, histogram and data table.Verification results can provide management departments with assessment and evaluation of forecasters from different departments, and support optimizing the management and allocation of resources. On the other hand, forecasters can also examine the verification results to improve future forecasting. Moreover, these results can also indicate forecasting capacity of different models for model developers. Regular annual and monthly verification reports issued by official departments, temporary verification reports required for the assessment and evaluation of forecasters are provided by the inspection system.National Verification System is overall standardized and systematic. The construction of the system emphasizes unification of norms and interfaces, so as to standardize basic functions, operational processes, data models and data coding information standards of the system construction and enhance the expansibility of the system. The system is deployed on three Linux servers, namely Web server, database server and data processing server. By updating and upgrading the system, the efficiency of statistical query results is improved, the interactive response of the inspection system is faster, and the operational process is complete and more standardized.The system consists of 4 functional modules:Forecast verification, analysis of verification documents, query and analysis of verification data and management of verification platform. The system organizes and manages all kinds of data effectively, dispatches the verification algorithm uniformly, and is compatible with new verification methods in the future. Key technologies include standardized data management, open algorithm module management and scheduling, and visual analysis of verification data.In order to provide references for provincial development of relevant verification systems, the specific verification methods of each module and the detailed processing in real-time operation are also described in particular. At the same time, the system provides comparison between results of urban weather forecasting and ten-day, monthly and annual intelligent grid forecasting. And therefore, it strongly supports the operational research and development of intelligent grid forecasting products and operational tests.