Vol.22, NO.5, 2011

Display Method:
Spatial and Temporal Distributions of Probability Classification of Precipitation and Temperature Anomalies over China
Yang Xiaobo, Chen Lijuan, Liu Yunyun
2011, 22(5): 513-524.
Based on the standard of the probability classification definition and scoring method in short term climate prediction operation, analysis is conducted on six-level probability classification of monthly precipitation and temperature anomalies in January and July. Spatial and temporal distributions are obtained through the monthly precipitation and temperature data at 160 stations in China, which are operationally used by National Climate Center of CMA. The six levels are defined as much more than normal (L1), moderately more than normal (L2), slightly more than normal (L3), slightly less than normal (L4), moderately less than normal (L5), much less than normal (L6).The results indicate that the issued six-level probability classification is suitable for symmetrical distribution cases for positive and negative anomalies but neglecting spatial inhomogeneous distributions and inter-decadal variations of monthly temperature and precipitation. During the period of 1980—2009, the probability of L1 and L6 for precipitation in North China is high in January whereas that of L6 and L5 is elevated in South China in July. The six-level probability for precipitation in January and July is generally similar in South China. The probability of L4, L3, and L2 temperature is high whereas that of L6, L5, and L1 is low for temperature in China in both January and July. Compared to those in the period of 1951—1979, the station numbers of L1 and L2 in January and L5 for precipitation in July have significantly increased but those of L6 precipitation in January and L6 and L4 for precipitation in July have remarkably decreased in the period of 1980—2009. Meanwhile, the station numbers of L4, L5, L6 for temperature in January have substantially decreased but those of L1, L2, L3 for temperature in January increases significantly and the six-level temperature probability in July shows no variability since 1980.The above results could provide an important reference for climate forecasters to fully consider inter-decadal, inter-annual and inter-seasonal variability. The standard of the scoring method for the climate prediction focuses on the accurate rate of classification prediction, and especially emphasizes the abnormal level of precipitation and temperature. Therefore, the scoring method will help promote climate prediction services. The six-level scoring method for precipitation is more reasonable, while for temperature the method needs appropriate improvements.
The Mesoscale Characteristics and Causes of a Severe Hail Event in Tianjin
Min Jingjing, Liu Huanzhu, Cao Xiaozhong, Wang Shigong
2011, 22(5): 525-536.
A severe hail process occurs in Tianjin on 25 June 2008, based on the data of intensive AWS observation, Doppler weather radar, FY-2C geostationary satellite and NCEP/NCAR reanalysis data, analysis and diagnosis studies are carried out to seek the characteristic of this rare storm system and its evolution. The results show that with the cold vortex over North China, the upper-layer cold and lower-layer warm potential instability stratification is formed. In the left front of the core of upper-level jet, non-geostrophic effect enhances the development of the storm system. Three meso-β convective clusters merge into a quasi-circular structure meso-α scale convective system and maintain for about 4 hours in Tianjin. The CAPE increases rapidly before thunderstorm while the CIN decreases gradually, thus the lower atmosphere becomes slightly unstable from stable. As the storm approaches, the trend of θsewind profile is arcuate, and the convective instability atmosphere in the middle-low levels remain.Water vapour transported through southwesterly flow from the southern part of Hebei forms a high humidity area, and Tianjin region is located in the area of wet tongue. Wind speed difference between 700 hPa level and near-surface reaches 20 m/s at 14:00, SHR (0—3 km) increases significantly, reaching moderate intensity (6.5 m · s-1· km-1). Super cell storms merged by a number of multi-cells have direct effects on the hail during the development of its mature stage. With the aid of Doppler radar, bow echo, weak echo region are found in the lower level, strong hanging echo in the middle-upper level and three-body scattering spike (TBSS) are observed. VIL jumps significantly from the lowest value to 65 kg· m-2before the hail occurs in Tanggu, and the top height of the storm remains 14 km, when VIL density increases to 4.6 g· m-3, exceeding the threshold of heavy hail. Analysis indicate that the dry intrusion of upper troposphere and cold air from the middle troposphere near the ground may also be the triggering factor in this process, besides the northwest-southeast convergence line located in Tanggu and the northeast of Hebei Province.
Winter Wheat Drought Disaster Insurance Risk Assessment and Regionalization in Henan Province
Ren Yifang, Zhao Yanxia, Wang Chunyi
2011, 22(5): 537-548.
Through quantifying the hazards and distribution of meteorological disasters which impact on crop growth and final yield, taking the drought of winter wheat in Henan Province as an example, a system methodology of the insurance risk assessment and regionalization of agrometeorological disasters is proposed.Based on the calculation of relative humility index in different growth stages, taking the moisture content coercion sensitive coefficient given by Jensen multiplication model as the weighting factor, winter wheat drought index of entire period is established, while considering the first three months before emergence as the period before sowing, using the precipitation anomalous percentage combined with the contribution factors, the winter wheat drought index of entire period is revised and meanwhile the suitable winter wheat drought index for Henan is established.After that, from the aspects of climatic factors, crop yield and social-economic, and after considering the characteristics of agricultural insurances and their requirements for elaboration, specialization, four indicators are used, including drought risk level, vulnerability index, yield risk index and anti-disaster ability, to evaluate the disastrous factors, vulnerability of crops, hazards of disaster events and ability of disaster prevention and reduction. Among these indexes, considering the social economy level and individual management scale, the vulnerability index is constructed by the winter wheat production efficiency index, production specialized index, and exposed index, which manifests the characteristics of agricultural insurance risk regionalization different from the general insurance risk regionalization.Finally, using these four indexes and cluster analysis method, weather index insurance risk regionalization and policy-related insurance risk regionalization are carried out in winter wheat drought at county level in Henan Province. The risk regionalization results of weather index insurance show that most counties located in the west of Henan belong to high risk areas, the south part of Henan belongs to low risk area, while majority of the other counties belong to medium risk areas. The risk regionalization results of policy-related insurance show that most counties located in the west of Henan belong to high risk areas, counties located in south, middle and north of Henan belong to medium risk areas, while most countries located in the southwest and individual counties located in the middle belong to low risk areas. There are remarkable differences between these two regionalization results, for better regional agricultural insurance and implement differential premium rate, different regionalization indexes and methods are required according to their characteristics and demands.Some quantitative analysis conclusions could be combined with elevation, soil types, knowledge level of peasant, GDP level, the agricultural insurance popularization situation as well as space and time rules of the agrometeorological disasters, further consummating the results of crop insurance risk assessment and regionalization, in order to instruct the peasant to choose the types of insurance more properly and the insurance company to arrange the premium rate more reasonably.
Estimation for Weather Yield of Winter Wheat Under A2 and B2 Scenarios in Hebei, Shandong and Henan Provinces
Wang Peijuan, Zhang Jiahua, Xie Donghui, Zhao Junfang, Bai Yueming, Mao Fei
2011, 22(5): 549-557.
Winter wheat is one of the main crops in China. Hebei, Shandong and Henan provinces are the main planting areas for winter wheat in China. It is important for China to recognize the change of weather yield for winter wheat in the next several decades.Trend yield models of winter wheat are built based on statistical yield from 1978 to 2008 using nonlinear simulation method for Hebei, Shandong and Henan provinces. Multiple correlation coefficients of trend yield models are greater than 0.90 for each province. Then, weather yields of winter wheat are got by subtracting the trend yield from statistical yields for each province. Historical meteorological data from 1978 to 2008 are disposed to get the average data (or maximum or minimum or sum) of every ten days for three provinces. Disposed meteorological data and weather yields of winter wheat are used to establish the models, whose significance reaches 0.05 level.In order to predict the weather yields of winter wheat, meteorological data coming from regional climate model (PRECIS) are used. The average data (or maximum or minimum or sum) of every ten days for each province for the reference period of 1978—1990 are achieved, as well as the data for future climate change under A2 and B2 scenarios of 2011—2050. Weather yields of winter wheat for the reference period are computed by using disposed meteorological data with weather yield models for Hebei, Shandong and Henan provinces. Meanwhile, trend yields of winter wheat are calculated using trend yield models by province. The total yields of each province from 1979 to 1990 are summed by weather yields and trend yields, which are compared with statistical yields. The results show that the correlation coefficients are 0.928, 0.792 and 0.837 for Hebei, Shandong and Henan. The significance reaches 0.001 level for Hebei and Henan, 0.002 level for Shandong.Weather yields of winter wheat are simulated based on weather yield models under A2 and B2 scenarios from 2012 to 2050 with disposed regional climate model (PRECIS) data for Hebei, Shandong and Henan provinces. The results show that in both A2 and B2 scenarios, the weather yields of winter wheat deduce for Hebei and Henan, with increase for Shandong for most years of 2012—2050.
The Regional Objective Precipitation Forecast in North China and Adjacent Areas in Summer
Zhao Cuiguang, Zhao Shengrong
2011, 22(5): 558-566.
North China is one of three major summer rainfall areas in eastern China. Precipitation over North China shows the characteristics of obvious emergency and locality. According to the statistics, 80%—90% precipitation occurs in June—August. Sometimes daily precipitation of a rainstorm can account for 50% precipitation amount of that month. Therefore, effective forecast is crucial especially for larger magnitude precipitation. Objective precipitation forecast is a difficult problem in NWP products interpretation at present. Objective precipitation forecast models are always established station by station, but larger magnitude precipitation is rare event for individual station. It is difficult to establish an effective forecast equation for an individual station. Precipitation intensity, spatial and temporal distribution over North China has its own particularity. Due to the regional characteristic, it is difficult to summarize in one model. Objective partitioning can be used in establishment of precipitation forecast model. Similar samples in the weather region are combined together. Regional forecast model is more stable than single-station forecast model, as the number of large-class precipitation samples increases.Seven weather divisions for summer precipitation over North China and adjacent areas are developed through Rotated Empirical Orthogonal Function (REOF) method, defined by the large contours of the seven REOF models. Objective precipitation forecast is based on probability regression precipitation categorical forecast. First, original precipitation is converted to 0 and 1 corresponding categories, and then forecast equations of different categories are developed to calculate each criterions. In real forecasting, the categorical precipitation will be determined through the criterion and the probability forecast of that category. Based on the daily precipitation data of station and T213 NWP products during the summer of 2006—2008, precipitation forecast model over North China and adjacent is established, which covers the domain (32°—42°N, 110°—124°E), including a total of 703 weather stations. Precipitation experiment is carried out for the summer of 2009 and 2010, and analysis of the forecast result indicates that regional method is better than single station method, especially for heavy precipitation. Regional model handles more factors than the single station model, so regional model makes a better prediction. Comparing to model direct forecast, regional forecast result is better, which reduces empty report obviously.
Comparisons of Boundary Mixing Layer Depths Determined by the Empirical Calculation and Radiosonde Profiles
Ma Jin, Zheng Xiangdong
2011, 22(5): 567-576.
Mixing layer is one typical type of atmosphere boundary layer, and it is named after strong vertical mixing which leads to the nearly constant variables, such as potential temperature and water vapor in this layer. The depth of mixing layer is an important parameter to identify features of thermodynamics and atmospheric dynamics in the boundary layer, and also a key to monitor the air quality. Mixing layer has very distinct daily variation as different meteorological conditions and synoptic processes largely influence the structure of boundary layer. Mixing layer becomes thicker under clear sky conditions, while remains physically stable and almost invariant during a single day under cloudy or raining weather conditions. Therefore, measurements and calculation of mixing layer depth are worth studying.The depths of mixing layer at 14:00 of Beijing, Longfengshan, Lin'an, Aletai, Sanya, Xining and Tengchong are compared using two kinds of datasets: The Nozaki empirical method and the radiosonde observational data reduced by vertical profiles of potential temperature and refractivity. It shows that the two observational depths are in good agreement, and the radiosonde measurements of mixing layer can be seen as criteria in the comparison with the Nozaki empirical method. Few bad linear correlation points of mixing layer depth from potential temperature profiles and refractivity profiles indicate that depth of mixing layer determined by refractivity profiles sometimes cannot find out the actual mixing layer, possibly due to dramatic variation of refractivity profiles under stable atmosphere vertical structure conditions.The comparisons illustrate that the Nozaki method may reflect the daily variations of mixing layer as those shown in observational dataset. However, the Nozaki method underestimates mixing layer depth when the mixing layer is above 2000 m. On the contrary, it overestimates mixing layer depth when the mixing layer is lower than 1000 m. Nozaki method also overestimates mixing layer depth at the sites (Beijing, Longfengshan, Aleitai, Xining) located at higher latitudes, but underestimates mixing layer depth in the sites (Sanya, Lin'an, Tengchong) at lower latitudes. Errors of Nozaki method are smaller under cloudy (total cloud amount is about 3—7) weather conditions, while larger in clear days. The lack of considering terrain effect and the simplifying of physical process maybe sources of comparative error of Nozaki method. These results suggest that the empirical determination of mixing layer depth need more subtle consideration before extensive use.
Characteristics of Black Carbon at Wuqing Observed by Single Particle Soot Photometer
An Linchang, Sun Junying, Zhang Yangmei, Shen Xiaojing, Wang Tingting, Liang Wende, Chen Lili
2011, 22(5): 577-583.
Black carbon (BC) plays a significant role in climate change, which has attracts increasing research interest. Single Particle Soot Photometer (SP2) is used at Wuqing Meteorological Station in Tianjin. SP2 utilizes the high optical power available intra-cavity from a Nd:YAG laser as the analytical technique. Light absorbing particles, mainly BC in atmosphere, absorb sufficient energy and are heated to the point of incandescence. The energy emitted in this incandescence is measured, and quantitatively determine the mass of the particle. SP2 operates in a single particle mode, measuring the light scattering and incandescence of each particle. Through the time delay between the two signals, the mixing state of BC particles can be obtained. SP2 is different from the traditional filter-based method which could provide more accurate information on single BC particle properties. First, SP2 could count the BC particles individually, so BC number concentration could be given; second, SP2 measures the mass of each BC particle, which could be converted to particle size; finally, SP2 could give the information on BC mixing state, which is important for estimating the aerosol effect on climate change.The observation taken at Wuqing in December 2009 shows that the average number concentration of BC is 1504 cm-3, with the maximum 5050 cm-3and the minimum 46.8 cm-3. The number of BC particles occupies 57.2% of the aerosol particles measured by SP2. The average number concentration of non-absorbing aerosol is 1124 cm-3, with the maximum 3311 cm-3and the minimum 70.7 cm-3. The average mass concentration of BC is 8.15 μg/m3. 51.5% of BC particles are thickly coated. On a clear windy day, the daily average number concentration is 215 cm-3, the mass concentration is 1.17 μg/m3, and 40.2% of them are mixed. However in the seriously polluted case, the daily average number concentration is 3169 cm-3, the mass concentration reaches 17.2 μg/m3, and the ratio of mixed BC also increases to 78.7%.
Improvement on the Nelder-Mead Simplex Algorithm and Its Application to Meteorology
Zhang Zhengqiu
2011, 22(5): 584-589.
Owing to computers providing great advantage in iterative calculation, the non-derivative algorithms have great potential applications to scientific research. Nelder-Mead Simplex (NMS) algorithm is a technique for minimizing an objective function in a multiple-dimensional space without differentiation, proposed by Nelder and Mead (1965). As a simple non-derivative technique, NMS algorithm is widely introduced in many computational books and used in numerical computations, and Matlab implements this algorithm for instance. Unfortunately, the method has some disadvantages such as slow converging and low precision, which need to be improved.Meteorological problems, usually nonlinear, are very complicated to solve, which require nonlinear fittings, solving the relationships between different meteorological variables, determining parameters in empirical formulas, solving the system of nonlinear equations and so forth. Conventionally, nonlinear problems are usually transformed into linear ones to solve, but this is not always practical. Fortunately the non-derivative algorithm could do this work, and an introduction to the application of the NMS algorithm to meteorological computations could be beneficial for meteorological community.An improvement on the NMS algorithm is proposed. To avoid the problems existing in the original NM simplex algorithm, a constraint is introduced to obtain next iterative point rather than finding the points of reflection, expansion, contraction and shrink, similar to that in the Powell's Method or in the Steepest Gradient algorithm. However, the searching direction is still along the downhill direction, i.e., the direction along the segment line between the vertex with the greatest functional value and the gravity center point. By introduction of the constraint, the multi-variable function will be transformed into a function with one variable, i.e., the constraint, which can be solved by the algorithms to calculate the minimum of a function with one variable, such as the Golden Section Search, Fibonacci Search and so forth. This approach will still keep the calculation without differentiation. After the improvement, the computation is greatly simplified, and its convergence will be accelerated.Some possible applications of the NMS algorithm to meteorology are also introduced, and it's also described how to implement the algorithm in fitting parameters in empirical formulas and solving the system of nonlinear equations.To testify this improvement, fitting experiments to some parameters in land surface process are made using the modified algorithm. Relationships between zero plane displacement and leaf area index (ILA) and between aerodynamic resistance and ILA at ground surface are calculated using the Least Square Method and the NMS algorithm to determine parameters. Experimental results show that the proposed algorithm have very high precision when fitting nonlinear formulas, therefore it can be used in computations for solving nonlinear issues or the system of nonlinear equations.
Airborne Field Campaign Results of Ka-band Precipitation Measuring Radar in China
Shang Jian, Guo Yang, Wu Qiong, Yang Hu, Yin Honggang
2011, 22(5): 590-596.

Spaceborne precipitation measuring radar can measure precipitation quantitatively, observe the vertical distribution and provide three dimensional precipitation structures. Spaceborne precipitation measuring radar is an important instrument on FY-3 meteorological satellite constellation. As a possible future member of the Global Precipitation Measurement (GPM), this satellite will carry dual-frequency precipitation radar operating at Ku and Ka bands to provide scientific data for dual-frequency retrieval algorithm. Its two prototype devices, Ku-band and Ka-band radars have already been developed under the support of National Defense Science and Industry Bureau. Field campaign of Ku/Ka-band airborne precipitation measuring radar is carried out by National Satellite Meteorological Center of China Meteorological Administration combining several groups from June to October in 2010 in Tianjin and Jiangsu, called BH-RM 2010 and JS-RM 2010, respectively. This is the first time that China carries out airborne precipitation measuring radar field campaign. The purposes of this field campaign are to validate the correctness of internal and external calibration scheme under airborne conditions, observe simultaneously with ground-based radar and microwave radiometer and compare satellite-airplane-ground observation data, validate the functionality and performance of precipitation measuring radar, and explore data processing and retrieval algorithms of precipitation measuring radar. Numerous data are obtained from various instruments in the field campaign, including airborne precipitation measuring radar, ground-based weather radar, ground-based multi-channel microwave radiometer, GPS radiosonde, 10 GHz and 37 GHz radiometer, portable wind measuring device, and temperature measuring device. Initial analysis is accomplished with observation data obtained from BH-RM 2010. Observation results of Ka-band precipitation measuring radar working in pulse compression mode and short pulse mode are presented, which show clearly the vertical and horizontal structure of rainfall. Due to the radar different scan modes, resolutions, frequencies, and dynamic range, it's difficult to compare airborne radar data and ground-based radar data accurately, and the unstable attitude of the airplane makes the comparison more difficult. Spatial matching of Ka-band airborne radar data and Tianjin S-band ground-based Doppler radar data is carried out and detailed procedures are introduced. Quantitative indexes are further computed to indicate the observation consistency statistically. In rain retrieval algorithms, attenuation correction is a critical step. Using GPS radiosonde data, ground-based multi-channel microwave radiometer data and microwave radiative transfer model, the integrated attenuation of Ka-band radar is computed and attenuation correction is accomplished. The result is reasonable, which lays a basis for future rain retrieval. Data obtained by various instruments in the field campaign will be analyzed thoroughly, propelling development and rain rate retrieval of our spaceborne precipitation measuring radar.

Numerical Simulations of Lee Wave's Nonlinear Characteristics and Vapor Sensitivity
Xu Liangtao, Lin Wenshi, Zhang Yijun
2011, 22(5): 597-603.

Based on the Scorer's theory of the lee wave, the trapped lee wave of small amplitude is successfully simulated using the Weather Research and Forecasting (WRF) model, considering the dry atmosphere with three even layers. Results show that in the linear theory, the trapped lee wave of the flow over terrain can be simulated well. The wave appears primarily from 2 km to 5 km in the vertical direction and the wavelength is on the order of 8 km. These results are in accordance with previous observation and numerical simulations.The analysis shows that the energy wave packet drifts downstream in the forming process of stationary lee wave and the oscillation intensity of each location periodically amplifies and weakens. At the same time, before the stable trapped lee wave forms, small disturbances have been generated, which would have significant impacts on vertical velocity of the wave.The process of introducing vapor is deemed to be creditable according to the original relative humidity vertical profile by WRF model output data. Small disturbances mentioned make vapor oscillate and easily initiate cumulus convection. Further, with vapor content increasing, cumulus convection appears earlier in the simulation. When vapor is introduced in the model, the lee wave would interact with cumulus convection, which has not been discussed in detail.Sensitivity experiments are conducted by changing the relative humidity of air, and the simulated results about the vapor's effect to the lee wave show that as the vapor increases, the wavelength becomes longer. In the simulation, the wavelength increases from 8 km to 9 km when relative humidity increases from 0 to 60%. In essence, it is buoyancy oscillation in the vertical direction of lee wave. The increase of the turbulent friction is attributed to the air density changes because of the variation of humidity, and then the damp of the oscillation increases. As a result, the oscillation frequency in the moist air is smaller than that in the dry air, accordingly the lee wave shifts to longer wavelength.Besides, when vapor is introduced in the model, the maximum of vertical velocity in the process of wave propagation has a decreasing tendency. For one thing, the strength of the lee wave can be weakened by the growth of turbulent friction. On the other hand, the vertical velocity will decrease with the air density increasing for the same wave energy.

Risk Assessment of Flood Disaster in the Mid-lower Reaches of the Yangtze
Bian Jie, Li Shuanglin, He Jinhai
2011, 22(5): 604-611.
Flood disasters caused by heavy rain events occur frequently in the mid-lower reaches of the Yangtze in monsoonal rainy season. The risk of heavy rain events is an important topic in meteorological research in China. Therefore, risk rank of flood disaster in six provinces in the mid-lower reaches of the Yangtze (Hubei, Hunan, Anhui, Jiangxi, Jiangsu and Zhejiang) are assessed based on most recently updated meteorological disaster losses dataset collected by the Ministry of Civil Affairs, National Disaster Reduction Centre of China from 2000 to 2008.First, losses due to flood disasters are classified and quantified by using the method of grey association analysis. The results show that the grey association method is reasonable in disaster situation grading and loss ranking, and the results are basically in agreement with the actual situation. Then an integrated index series in the recent 9 years is established. In addition, the model is very practical and flexible because the numbers of the grade indexes are not limited. Second, since there are not enough integrated historical disaster indexes, an information diffusion based fuzzy method is introduced to optimize the historical disaster data and then the risk in each province is assessed individually. The risk rank results show substantial difference in these provinces. Although medium risk is universal in all the provinces with the occurrence probability of once in one to two years, high risk is relatively more frequent in three provinces, Anhui, Hubei and Hunan, which approximately tallies with the practical situation. This also suggests an efficiency of the present risk-assessment model in processing inadequately long records and deserves extensive use.
The Hail Risk Zoning in Beijing Integrated with the Result of Its Loss Assessment
Hu Haibo, Dong Pengjie, Pan Jinjun
2011, 22(5): 612-620.
In order to recognize the meteorological disaster risk and assess it, the task of risk zoning is started exploring the possibility and severity influenced by the disaster, and the distribution of risk area zone is determined. The study is very important for the disaster avoidance or prevention, and is widely utilized in disaster emergency and meteorological service of supporting decision regulation. Normally the risk zoning depends upon the probability of extreme weather or climate events, such as the occurrence or probability of extreme meteorological elements. However, the risk of disaster focuses on the intensity or loss of the disaster besides the probability. Moreover, the index of hail risk zoning in Beijing is carried out based on the formula that risk equals probability multiplied by loss, and it can avoid the solely doing statistics on the probability of extreme weather and climate events. The loss assessment is firstly fulfilled by the Gray-correlation Model with the data of disaster occurred in Beijing during recent 30 years. Meanwhile, the BG algorithm is introduced here for the time-series analysis on the disaster data, and it is found that the year of 1997 in the time-series is an inconsistent standpoint, which means that the data should be separated into two series for its inconsistence. Based on this judgment, the expectations of the bias from 1997 are considered to be the variation modulus. On the other hand, with the result of loss assessment, the hail occurring frequency is calculated out by 10 groups divided by average intervals form 0 to 1 of the loss index value. It can be utilized in deducing normalized hail risk index of Beijing, with which the risk zoning standards can be determined. Eventually the risk index is calculated with the risk function, and the indexes are also summed up by groups. Furthermore, the risk zonings are symbolized upon the index with its zoning standards. From the result of risk zoning, it can be concluded that the relatively higher hail risk zone mainly locate in urban area of Beijing, such as the centers of Miyun and Pinggu, while the risks of the mountain area and its piedmont, are relatively lower.
Mesoscale Weather Analysis and Forecasting Display Platform
Gao Mei, Ni Yunqi, Zhang Wenhua, Li Feng, Jie Lianshu, Li Hongli
2011, 22(5): 621-630.
The Meso-scale Weather Analysis and Forecasting System (MWAFS) is reviewed, introducing its components and technical features, describing the technical architecture, system function, products of MWAFS general analysis and display platform in details. The differences between MWAFS and MICAPS are also discussed.MWAFS is established for monitoring, analyzing and predicting meso-scale disaster weather based on network, GIS, database as well as the meteorological professional analysis. It is the integration of several major national research projects results in meso-scale disaster weather research as well as the key operational products of the meteorological industry. It can be used for tracking and obtaining the meso-scale weather information quickly and effectively. MWAFS consists of data acquisition, data processing and data display subsystems. The data display subsystem is developed on the technologic platform of Geobeans and realizes seamless integration between GIS and meteorology spatial analysis models by the embedded form. The techniques such as spatial database, spatial (online analytical processing) and spatial data displaying can be put together effectively, which can offer the abilities of management, inquiry, analysis and display of spatial information. MWAFS is based on multitier architecture, and supports B/S and C/S structure.
The Application of Software Design Patterns in Agrometeorology Software Systems Development
Zhuang Liwei, Wei Jianguo, Mao Liuxi
2011, 22(5): 631-640.
Software design pattern is the use of object-oriented technology to solve certain problems under a particular condition, which is the software design process for problems of a specific environment. It can share the successful experience and solutions, reduce the complexity of problem solving and improve the design of the modular. At the same time, meteorological software construction has entered a rapid developing stage, requiring higher system reliability and reusability, thus it's particularly important to analyze systems and the design of pattern. If the past development practices are considered reasonably and professional software development model is applied properly in agrometeorology software development process, the program can be more logical with reasonable structure and high code reusability.The analysis on the development and changes in agrometeorology service needs imply that the existing agro-meteorological service systems are non-unified and non-standard in architecture, data management and product production. A model based, factory method supplemented design pattern is proposed in order to meet the needs. However, there are more than one system design patterns, so similar applications may also have a variety of useful patterns. Choosing what kind of design patterns depends on the development of the information technology, the change of business needs and the result of application. On the primary technologies with this pattern are discussed, such as the overall framework of the mode model, data control model, data service model, data encapsulation component model, plug-in module reuse management model and professional development. Two samples, one evaluation system based on ArcMap platform and the other based on Oracle database are analyzed to illustrate the dynamic library data component plug-in technology, packaging technology, and their application.With the support of standard database, framework development technology and the development of GIS component, the plug-in professional module technology has been basically achieved and proved effective in operation. In the project which is called National Agrometeorological Disasters Service and Security System, this technology is fully applied. But more complex and professional module design requires further research to meet the changing operation requiements.