应用气象学报

2017, 28(6)

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Abstract:

Review on Agricultural Flood Disaster in China

Huo Zhiguo, Fan Yuxian, Yang Jianying, Shang Ying

2017, 28(6): 641-653. DOI: 10.11898/1001-7313.20170601

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Abstract:
Agricultural flood disaster is generally accepted as an important branch of disaster science. Based on reviewing literatures related to agricultural flood, related concepts are formulated and previous research and existing facts are sorted and summarized. Afterwards, directions for future research are discussed integrating impacts of climate warming.According to affected crops and occurrence times, agricultural flood disaster in China can be divided into spring waterlogging, summer waterlogging and grown or harvested in the summer and autumn waterlogging, which have impacts on the overwintering crop, sowing crop and autumn harvest, respectively. The formation of agricultural flood and its intensity are induced by comprehensive effects of weather, crop flooding tolerance, topography, soil structure and human activities. In the context of climate warming, an increasing tendency is detected in the hazard rate and stricken area of China's agricultural flood, however, the regional disparity is significant. Agricultural flood disaster decreases in north China, while it increases in the south part. Two fundamental aspects must be linked to explain the spatiotemporal characteristic of agricultural flood. The first one is the disaster weather itself, i.e., the frequency and intensity change of extreme precipitation. The second one is the characteristic of the crop affected, such as crop growth and development speed, the crop boundary, crop strains, cropping system and planting area, which indirectly influence the formation and development of agricultural flood disaster. The occurrence mechanism of flood on crop yield are the comprehensive result of many processes, including the physical damage caused by the flood struck, physiological damage of watered out and ecological hazard because of environment change. Field survey, modeling experiment and numerical simulation are currently the dominant tools available to investigate agricultural flood disaster. Agricultural flood level indexes such as the morphology index, waterlogging degree index, meteorological index and agriculturalmeteorological index are used to systematize effects of flood on agriculture. Impacts of agricultural flood is multidisciplinary, including affecting the agricultural production environment, affecting the ecophysiological processes of crop, crop growth and development and inducing diseases and pests. It suggests that three broad areas be addressed to improve the simulating ability, and attentions should be paid to future impacts of flood on crop yields. First, multidisciplinary agricultural flood index is required under the background of climate change. Second, a comprehensive risk assessment of the disaster needs to be conducted considering knowledge of the disaster process. Finally and the most importantly, data representative of actual disaster is needed to evaluate the influence of climate warming on the agricultural flood.

Assessment on Main Kinds of Satellite Cloud Climate Datasets

Liu Jian, Wang Xijin

2017, 28(6): 654-665. DOI: 10.11898/1001-7313.20170602

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Abstract:
Cloud is not only a key parameter that affects the radiation balance between earth and atmosphere system, but also is an important index to research atmosphere cycle and climate change. Cloud information can be achieved by surface observation, but it is limited by the spatial and temporal distribution of stations. Only satellite observations can provide a continuous synoptic survey of the state of the atmosphere over the entire globe, and satellite remote sensing also has advantages in observation area and time frequency. The operational weather satellite sensors can supply data records as long as more than 40 years, provide major support for cloud climate research. Whereas polar-orbiting cross-track scanning sensors generally only provide daily global coverage at particular local times, geostationary satellites are placed at particular longitudes along the equator and permit higher-frequency temporal sampling.Building the cloud climate dataset is related with some factors, such as recalibration, stable retrieval algorithm and validation. Based on long term satellite data, several cloud climate datasets, such as ISCCP, Patmos-x, CLARA, MODIS-ST, HIRS and so on are built selecting different instruments and different retrieval algorithm. Spatial and temporal resolutions of these cloud climate datasets are also different. Focusing on different properties of these cloud climate datasets including instruments and retrieval algorithm, references are cited to show the accuracy of these cloud climate datasets. Applications of these cloud climate data in weather and climate analysis are also introduced. As an example, the Tibetan Plateau is selected to analyze the difference between Patmos-x and CLARA-A2 that has the same satellite data source and high similar cloud detection algorithm. In long term, the changing trend is similar. The difference between these two cloud datasets is the spatial resolution:For Patmos-x, it's 0.1°, while for CLARA-A2, it's 0.25°. Compared with CLARA-A2, the Patmos-x has smaller cloud amount at day-time and has larger cloud amount at night-time. Based on NOAA-18 and Aqua data, Patmos-x, CLARA-A2 and Aqua/MODIS cloud amount during 2005 and 2015 are compared. Results show that the difference between three kinds of cloud amount is smaller in day-time, especially in summer. The difference increases in night-time, especially in winter and spring. The main cause may come from different observation ability, retrieval algorithm and observation time of different satellites.

Radar Analysis and Numerical Simulation of Strong Convective Weather for "Oriental Star" Depression

Duan Yapeng, Wang Donghai, Liu Ying

2017, 28(6): 666-677. DOI: 10.11898/1001-7313.20170603

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Abstract:
At about 2132 BT 1 June 2015, "Oriental Star" cruise from Nanjing for Chongqing suffers severe stormy weather when sailing in the Yangtze River near Jianli County, resulting in 442 people killed. The investigation team finds that the occurrence of the catastrophic accident is caused by a sudden downburst of squall line weather. Using ARPS (the Advanced Regional Prediction System) model and assimilation of conventional data and four-radar data in the surrounding area, the severe weather process is simulated. Combined with the high-resolution radar observation, the structure and strength of the squall line are analyzed synthetically.The atmosphere of dry ambient at low level and humid ambient at middle level is favorable for the occurrence of convective weather phenomena. Radar observations show that the squall line convective system is northeast-southwest direction, and moves fast to southeast, the life duration is about 6 hours, and the squall line transit lasts about an hour. During the evolution of the squall line, convections developed to their strongest at the intensifying stage, when the strong convection region reached its maximum. At its mature stage, gust front appears in front of ground thunderstorms, and the horizontal scale of the squall line system reaches the upper limit. The instability of the stratification and the flat terrain of the Jianghan Plain are important causes for the strong convective activity and the downburst phenomenon.The numerical simulation shows that the high-speed wind area above the ground, the position of instantaneous maximum speed of horizontal and vertical wind, cumulative rainfall maximum center, the composite reflectivity high value area of 200 m resolution show a zonal distribution to uniform, which coordinates with the time and spatial distribution of the accident. Influenced by the direct impact of the down burst, intensity of thunderstorm near the accident point increases rapidly, and a narrow gust wind appears near the ground where wind shear increased significantly. Ship wreck is affected by above 10 m·s^-1 downdraft and above 18 m·s^-1 strong westerly wind from 2132 BT to 2134 BT. The precipitation intensity begins to increase at 2131 BT, and the center of heavy precipitation is located just above the accident spot from 2131 BT to 2135 BT, with a maximum precipitation of more than 10 mm per minute. A gust wind makes great contribution to the transportation of momentum from the middle and low levels to the land surface, accompanied by raindrops of drag and the sinking air flow, enhancing the speed of the wind further.

Improvement and Comparison of the Accumulated Temperature Model of Northeast Spring Maize

Li Rui, Guo Jianping

2017, 28(6): 678-689. DOI: 10.11898/1001-7313.20170604

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Abstract:
Spring maize in Northeast China plays a more and more important role in the national maize production. The gradually increase in acreage, the per unit area yield and total yield of spring maize have markedly improved since 1980s. Accumulated temperature is one of indexes which are commonly used in agricultural meteorological research and operation service. It's also used in crop model and regional thermal resource analysis which can reflect differences in demand of heat resources between different crops and varieties. And it can also be used to evaluate the suitability of heat conditions in a certain area for crop growth and development to avoid blindness of crops introduction. But in fact, the stability of accumulated temperature is relative, and it fluctuates with differences of crop varieties, locations, years and growth periods. It results in the limited application of the accumulated temperature index. Besides environmental conditions, the instability of accumulated temperature is also affected by different calculation methods. In general, accumulated temperature models are divided into two categories, including linear model and nonlinear model. Therefore, how to choose and revise the existing model for stabilizing the calculation value of accumulated temperature and making it fit well with the actual situation is of great significance for agricultural production and meteorological service.Based on observations of spring maize and meteorological data in Northeast China, the spring maize Sidan19 is taken as an example. The nonlinear accumulated temperature model proposed by Shen Guoquan with good stability is adopted to fit, and the influence of parameter selection on the stability of accumulated temperature is analyzed. The quadratic function of mean temperature to the liner model is revised and analyzed, and the nonlinear model is compared. Results show that the stability of accumulated temperature is related to the parameter P, more stable with smaller P. However, accumulated temperature calculated by the nonlinear model shows inter-annual and inter-regional differences. The main cause for the instability is different temperature strength and its less correlated with other meteorological factors. For each growth period, fitted curves between accumulated temperature and mean temperature are quadratic. The fitting effect of the accumulated temperature calculated by the revised linear model is better than that of Shen Guoquan nonlinear model. Moreover, the stability doesn't appear to be much different between two methods. Thus, the revision of linear model considering the mean temperature for spring maize in Northeast China is feasible, which can help revising agro-meteorological indexes and improving agriculture service capacity.

Estimation of Crop Evapotranspiration Under Standard Conditions for Winter Wheat in the Huang-Huai-Hai Plain

Wu Xia, Wang Peijuan, Chen Pengshi, Wu Dingrong, Huo Zhiguo

2017, 28(6): 690-699. DOI: 10.11898/1001-7313.20170605

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Abstract:
Crop evapotranspiration under standard conditions (E_c) is defined as the evapotranspiration from disease-free, well-fertilized crops grown in large fields, under optimum soil water conditions, and achieving full production under the given climatic conditions. The calculation of E_c considers crop and local surface conditions. E_c is the theoretical upper limit of actual evapotranspiration for actual local surface coverage, ensuring objective analysis on crop water requirements and agricultural drought. To summarize the spatial and temporal distribution characteristics and their causes of E_c, daily E_c is calculated based on Penman-Monteith method using meteorological data and satellite remote sensing data from 2000 to 2015. The meteorological data are provided by 27 meteorological stations in the winter wheat growing area of the Huang-Huai-Hai Plain. The satellite remote sensing data are extracted from NASA MODIS products (LAI (MOD15A2) and Albedo (MCD43C3)) at the corresponding location of 27 meteorological stations. E_k is calculated based on single crop coefficient approach recommended by FAO. Results show that daily dynamic changes of E_c and E_k are consistent in the regional tie scale. However, compared with E_k, E_c has a spatial distribution corresponding to the objective reality. The growth period of winter wheat is divided into five stages:Before wintering stage, wintering stage, returning green-jointing stage, heading stage and milky maturity-maturity stage. With the spatial distribution characteristic of higher in the south and lower in the north, the average daily E_c in the whole winter wheat season, wintering stage and returning green-jointing stage is 1.95 mm, 0.46 mm and 2.74 mm, respectively. The average value of E_c is 1.23 mm before wintering stage, and the whole fluctuation of E_c in the Huang-Huai-Hai Plan is small. There is no significant fluctuation in E_c in heading stage and milky maturity-maturity stage except for the middle part of the Huang-Huai-Hai Plain. The average value of E_c is 4.71 mm and 3.72 mm in these two growth stages, respectively. In terms of spatial distribution, extremely significant positive correlation is shown between LAI and E_c in all growth periods. In wintering stage, returning green-jointing stage and milky maturity-maturity stage, E_c also shows a higher significant negative correlation with albedo. During the whole growth period of winter wheat, E_c has a higher partial correlation coefficient with LAI and water vapor pressure. These results can provide basic data for drought monitoring and wet or dry climate zoning in China, and also provide a new idea for the actual evapotranspiration estimation.

The 3D Spatial and Temporal Evolution of K Process in Intra-cloud Flash

Liu Hengyi, Dong Wansheng, Zhang Yijun

2017, 28(6): 700-713. DOI: 10.11898/1001-7313.20170606

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Abstract:
K process is a kind of discharge event in lightning. The study on evolution features of this event helps to increase understanding on the mechanism of lightning initiation and developing. 3D lightning imaging data of 3 intra-cloud flashes are used to describe and analyze spatial and temporal characteristics of K events and corresponding electric field's changing waveforms. These 3D location data are recorded by 2 VHF broadband interferometers at Conghua, Guangdong Province, in the summer of 2010, providing the developing image of lightning discharges with a temporal resolution of 5 μs and a spatial resolution better than 500 m. The VHF radiation of lightning is recorded by a high-speed oscilloscope with a sample rate of 1 GS·s^-1. Both fast and slow filed change antennas are employed in two broadband interferometer systems. Their decade time constants are 1 ms and 8 s, respectively. Changing waveforms of the electric field are record by an A/D card working synchronously with the oscilloscope used to record the VHF signal of lightning.Results show that K process is a kind of fast negative breakdown discharge and can be divided into 3 stages according to the distribution of VHF radiation sources located by broadband interferometers. In the first stage, negative recoil leaders occur under the initiation position of intra-cloud lightning, progress along the path of pre-existing positive leader, heading to the initiation region of lightning. In the second stage, some negative recoil leader can progress fast in the channel established by the previous negative leader of lighting initiation stage and induce a relatively large variation of electric field on the ground. In the last stage, the negative recoil leader reactivates the channel of negative leader in lighting initiation stage and facilitates the negative breakdown at the end of existing path. Speeds of the new air breakdown processes happen at the end of existing path are generally reduced to an order of 10⁴~10⁵ m·s^-1. The evolution speeds of 8 recoil leaders in the 3 intra-cloud lighting records are also calculated. The maximum, minimum and average value of the developing speeds of 8 recoil leaders are 3.1×10⁷, 3.1×10⁶ m·s^-1 and 1.6×10⁷ m·s^-1, respectively. The range of K process speeds is similar with that of dart leader but slower than return stroke.

Application of Himawari-8 Data to Enteromorpha Prolifera Dynamically Monitoring in the Yellow Sea

Wang Meng, Zheng Wei, Li Feng

2017, 28(6): 714-723. DOI: 10.11898/1001-7313.20170607

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Abstract:
As a new generation geostationary meteorological satellite, Himawari-8 can provide measurements dynamically monitoring of Enteromorpha prolifera, with its high temporal-spatial resolution. According to the normalized differential vegetation index NDVI, by studying reflection characteristics of enteromorpha, a method using Himawari-8 data is proposed for enteromorpha information detection, drift speed and intensity estimation. Using the above methods, the outbreak processes of enteromorpha prolifera in the Yellow Sea from May to July in 2016 are monitored including the appearing time, location, areas, intensity, range of influence, drift path and drift speed. Results show that the enteromorpha are detected firstly on 19 May 2016 in the Yellow Sea and areas are relatively small. It outbreaks in mid and late June with its continuous growth, and areas, range of influence and intensity all reach the maximum in this period. The enteromorpha enters recession period in early July near the coast of Shandong Province, the Yellow Sea, such as Qingdao, Yantai, Weihai and so on.The calculation shows that enteromorpha intensity changes with time, and multi-temporal enteromorpha intensity are accumulated into enteromorpha intensity synthetic product. The multi-temporal enteromorpha intensity synthetic product shows that enteromorpha intensity covers more in the central Yellow Sea and the east of Yantai waters, and less in initial position. The moving path of enteromorpha from appearance to disappearance shows that the drift path of enteromorpha is from the southeast open sea to the northwest offshore, and the average daily drift speed changes constantly.Dynamic changes of enteromorpha are closely related to the environmental hydro meteorological conditions, such as temperature, wind speed and direction. The suitable temperature is the basis for enteromorpha's growth and development. In late May, enteromorpha growth are detected near the northern coast of Jiangsu Province firstly, where the temperature is stably 20℃. And then in early June, enteromorpha area increases rapidly with the increasing temperature, and then outbreaks in mid-June when the temperature reaches 20℃ in east of Shandong Peninsula sea. In early July, the average temperature of the Yellow Sea is above 25℃, making the enteromorpha decay and disappear gradually. It shows that dominant wind direction is the main driving force of enteromorpha drift, the calculation shows that enteromorpha drifts northward with large and steady south wind from May to July in 2016, and finally arrive in Weihai coast, and the moving direction is in line with the wind.

Ice Cloud Distribution and Seasonal Migration over Land Area of China Based on MODIS Data

Li Te, Zheng Youfei, Wang Liwen, Lin Tong

2017, 28(6): 724-736. DOI: 10.11898/1001-7313.20170608

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Abstract:
Ice clouds have an important impact on the global climate, and ice cloud features vary with convection and weather system. Mid-latitude ice clouds originate from the convective cloud system and the atmospheric circulation in the atmosphere, but the understanding on the formation of ice crystals in clouds is still lacking. Non-spherical ice crystal particles have also posed a great challenge to the accurate calculation of the ice cloud in the climate model. Due to limitations of aircraft observation and remote sensing, the observation of ice clouds depends mainly on satellite remote sensing. Based on moderate resolution imaging spectrometer (MODIS) cloud product level-3 data (MOD08_M3), the probability distribution of ice cloud, ice cloud optical thickness, ice cloud effective radius and ice water path over China from November 2011 to October 2016 are analyzed, and the distribution and seasonal migration are discussed. The horizontal distribution and trend of ice cloud attributes in different seasons are studied emphatically. Main conclusions are as follows. The occurrence probability of ice clouds is higher in the northeastern part of the Qinghai-Tibet Plateau during winter, spring and autumn, mainly due to the warm and humid air raised by the northeast slope of the Qinghai-Tibet Plateau. The occurrence probability of ice clouds in low latitudes in summer is related to monsoon and the intertropical convergence zone. The overall occurrence probability of ice clouds is on the rise, especially in the summer of 2016. The horizontal distribution of effective radius of ice cloud is increasing from southwest to northeast, mainly due to the difference of temperature distribution. Through the year, the effective low radius of the ice particles appears in the southwest region, and the high value appears in the northeastern region during the winter, spring and autumn, and appears in Xinjiang area during summer. The ice cloud effective particle radius is larger in high latitudes than in low latitudes, and the overall seasonal variation is not obvious. The horizontal distribution and seasonal changes of ice cloud thickness and ice water path are roughly the same, showing the downward trend from southeast to northwest. The large value of ice cloud optical thickness and ice water path are mainly in the southern region. The minimum value appears in the northern part of Xinjiang, which is mainly related to the air vapor content and the East Asian Monsoon. The ice cloud optical thickness and ice water path are larger in monsoon area than in non-monsoon zone. There is little difference in the distribution of ice thickness between ice age and ice water, and large value areas are in the southern region. Seasonal changes in northwest, northern and the Qinghai-Tibet Plateau regions are relatively significant.

Assessment of Ground Temperature Simulation in China by Different Land Surface Models Based on Station Observations

Sun Shuai, Shi Chunxiang, Liang Xiao, Han Shuai, Jiang Zhiwei, Zhang Tao

2017, 28(6): 737-749. DOI: 10.11898/1001-7313.20170609

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Abstract:
As an important physical quantity in the land surface process, the ground temperature plays an important role in climate change research, agricultural production and ecological environment. A set of simulation experiments are carried out, in which ground temperature are simulated by Community Land Model 3.5 (CLM3.5) land surface model and Noah-Multi Parameterization Land Surface Model (Noah-MP) of three different parameterization schemes, forced by China Meteorological Administration Land Data Assimilation System (CLDAS) atmosphere forcing data containing high-quality temperature, pressure, humidity, wind speed, precipitation and solar shortwave radiation. The different model-simulated ground temperature is verified by 2000 national ground temperature observation stations of China Meteorological Administration from 2009 to 2013. Results show that errors of different model-simulated ground temperature compared with observations behave seasonal fluctuations from the error analysis of time series. And the ground temperature simulated by CLM3.5 land surface model and Noah-MP land surface model can better represent the spatial distribution of ground temperature of China in seasonal climate state. The ground temperature is underestimated in general, and the underestimation in spring and autumn is smaller than that in summer and winter. On the spatial distribution, the error of the model-simulated ground temperature in the eastern China is smaller than that in the western China, and in the northeastern China and northern Xinjiang the error is even greater. Three different parameterization schemes of Noah-MP land surface model are selected to compare the simulation result. Results show that when the non-dynamic vegetation scheme remain unchanged, considering different radiation transferring schemes, the two-stream approximation radiative transferring scheme considering vegetation coverage of Noah-MP land surface model performs better than the radiative transferring scheme considering the solar altitude angle and vegetation 3D structures of Noah-MP surface land model. When the default two-stream approximation radiative transferring scheme in Noah-MP land model doesn't change, considering the dynamic vegetation scheme of Noah-MP land surface model, the result shows that the ground temperature choosing the dynamic vegetation scheme of Noah-MP land surface model is better than the non-dynamic vegetation scheme named of Noah-MP land model. Above all, the ground temperature simulated by the dynamic vegetation scheme of Noah-MP land surface model is better than the other two parameterization schemes of Noah-MP land model and the CLM3.5 land surface model.

Technical Characteristics of the Architecture Design of China Integrated Meteorological Information Sharing System

Zhao Fang, Xiong Anyuan, Zhang Xiaoying, Deng Li, Wang Ying, Ma Qiang, Yang Xin, Tan Xiaohua, Gao Feng

2017, 28(6): 750-758. DOI: 10.11898/1001-7313.20170610

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Abstract:
The enterprise architecture (EA) reflects its business components and process, application system, data composition, technical composition and organization setting, so it's an important tool to realize the strategic goal of the enterprise. EA includes frameworks and reference models, consisting of business architecture and IT architecture.China Integrated Meteorological Information Sharing System (CIMISS) is the unified data environment which is distributed in national service center and 31 provincial services centers. Main functions of CIMISS include data collection and dissemination, quality control and product generation, data management, data services and operational monitoring, which achieves the initial unity of data standards and the standardized management of meteorological data. CIMISS provides direct data services to meteorological applications, and is put into operation at the end of 2016. CIMISS obtains good efficiency of overall data process and service, the collection and storage time of core data is less than 3 minutes, the data access performance is enhanced by 2-5 times compared to the national meteorological archival and retrieval system (MDSS).The architecture design is an important stage of the construction of CIMISS which gives strong foundational support to the detailed design and development of the application software system. The architecture design of CIMISS and its core components are introduced and illustrated, combined with the case analysis of the application practice.Applying EA methodology, in the form of top-down and layer-by-layer decomposition, the business architecture, the data architecture, the application architecture, the technique architecture and the standardization framework are established. By adopting a series of optimized architecture design, the effective management and synchronization of metadata and data quality control are realized, the scalability of unified monitoring of new business and the rapid online service of new meteorological data are provided, the universal data service model of heterogeneous database systems is established, the good performance of data services is achieved and is easy for the upgrade of the database technology. Through the hierarchical design and the application of cluster technology, requirements of maintainability, scalability and high reliability of CIMISS are satisfied.Based on CIMISS, the meteorological data service platform under design can be upgraded to be compatible with new technologies such as cloud computing and big data. The intensive infrastructure service platform would be built, and distributed data curation technology would be implemented comprehensively in data management to achieve high performance. Through application programming interfaces (API), operational applications wouldn't be affected by the update.

Vol.28, NO.6, 2017