Vol.23, NO.1, 2012

Display Method:
Comparing Vertical Structure of Precipitation Cloud and Non-precipitation Cloud Using Cloudsat
Shang Bo, Zhou Yuquan, Liu Jianzhao, Huang Yimei
2012, 23(1): 1-9.
Precipitation cloud is the main target of artificial rain enhancement operation. Understanding the vertical structure of precipitation cloud is essential to choose seeding conditions. Based on the data of Cloudsat, the vertical structure of precipitation cloud and non-precipitation cloud in North China and Jianghuai Area from March 2008 to February 2009 are analyzed.First of all, the approach of judging precipitation cloud with Cloudsat is validated effectively by lots of examples. Then precipitation cloud and non-precipitation cloud are analyzed by a statistical analysis to get the vertical structure characteristics. Results show that precipitation cloud and non-precipitation cloud vertical structures are different. The cloud base height of single-layer and multi-layer precipitation cloud is less than 2 km. The cloud base height of non-precipitation single-layer cloud is mainly above 2 km in both two areas, the annual mean frequencies are 55% in North China and 51% in Jianghuai Area. Cloud thickness of single-layer precipitation cloud is mainly lager than 6 km in these two areas, and the annual mean frequencies are 67% in North China and 73% in Jianghuai Area.Cloud thickness of precipitation multi-layer cloud is mainly between 2 km and 4 km, and the frequency is 36% in the two areas. Cloud thickness of non-precipitation cloud is mainly below 2 km. The frequency is all more than 50% for single or multi-layer cloud. The precipitation cloud thickness of multilayer cloud except interlayer is mainly between 1 km and 2 km, the annual mean frequencies are 33% in North China and 34% in Jianghuai Area. The non-precipitation cloud thickness of multilayer cloud except interlayer is mainly above 4 km, the annual mean frequencies are 41% in North China and 44% in Jianghuai Area. The annual mean height of cloud top and cloud base in precipitation cloud are different from non-precipitation cloud, the annual mean height of cloud top and cloud base in precipitation cloud are 8.7 km and 0.7 km in North China, 9.85 km and 0.7 km in Jianghuai Area. On the other hand, the annual mean height of cloud top and cloud base in non-precipitation cloud are 7.45 km and 2.8 km in North China, 7.8 km and 2.75 km in Jianghuai Area, respectively.
Regional Emissions of Gaseous Pollutants Based on Observations
Li Yang, Xu Xiaobin, Lin Weili, Zhao Huarong
2012, 23(1): 10-19.
Measurements of ambient CO, NOx and SO2 made at Gucheng Station, Hebei Province, China from September 2006 to August 2007 are analyzed and applied to the validation of emission inventory data. It shows that the concentrations of these gases are significantly correlated among each other, suggesting that the gases have common sources. The concentration ratios of CO to NOx, CO to SO2 and SO2 to NOx for the entire day, daytime and nighttime in different seasons are obtained based on the slopes of the respective correlation lines. The results show that the seasonal variations of the ratios are not very high and the correlations of CO and NOx, CO and SO2, SO2 and NOx in winter are more significant than those in other seasons. There is large difference between the daytime and nighttime in the ratio of CO to NOx, particularly in the warmer seasons, indicating strong photochemical impact on the ratio of CO to NOx. There are certain dependences of the gas concentrations and the concentration ratios on wind directions, reflecting the different impacts of sources from different wind sectors. The prevailing surface wind directions at the Gucheng Station are northeast and southwest, facilitating the transport of plumes from Beijing and Baoding, respectively. When winds come from the north sector (Beijing), surface concentrations of CO and NOx are significantly higher than those from other directions, and when the winds come from south sector (Baoding, Shijiazhuang), surface concentration of SO2 is significantly higher than that from other directions. The characteristics of pollutants in different wind directions may reflect the characteristics of pollution sources in different directions. The concentration ratios from the observations are compared with emission ratios derived from the emission inventories (INTEX-B, TRACE-P, REAS, HB). To avoid the influences from inadequate vertical mixing and strong photochemistry, only afternoon data in seasons other than summer are considered. Under this condition, the observed concentration ratios are 43.7 and 31.6 for CO to SO2 and for CO to NOx, respectively, which are 2—12 times higher than the respective emission ratios derived from the emission inventories. This result suggests that CO emission may be underestimated by more than two times in the emission inventories. Further studies show that CO emission from biomass combustion, especially the large-scale straw combustion in harvest seasons would be the important but greatly underestimated source. The analysis of the observation data indicates that the average CO level in open straw burning periods is (90%±30%) higher than that in the other periods under similar meteorological conditions. So far, biofuels are still used for cooking and heating by rural families in many Chinese regions and open burning of agricultural residues is often not effectively controlled. In the future, the impacts of emissions from agricultural straw burning on the emission strengths should be given more attention in the process of making and using the emission inventories.
Simulation of Return Signal Spectrum of Wind Profile Radar
Wang Sha, Ruan Zheng, Ge Runsheng
2012, 23(1): 20-29.
Wind profile radar uses coherent accumulation technology to improve sounding sensitivity, which can obtain high resolution spectral data and entire spectrum information of return signal compared to the Doppler weather radar, so it is applied in precipitation, cloud body structure detection and research aspects widely. The concrete implementing schemes of noise signal processing and spectrum parameters extraction leads to the differences in ability of extraction the useful signal from atmosphere return signal and estimation accuracy, so the method of signal processing and information extraction is the key technologies of signal process.The simulation of radar return signal is an important method to evaluate ability of extracted information. Based on the clear sky atmospheric detection data of different types of wind profile radars which are placed at Yanqing of Beijing and Dongguan of Guangdong, both the power spectral density distribution of atmospheric return signals and the statistical characteristics of radar system noise amplitude are analyzed. The distribution of atmospheric return signal is Gaussian distribution. Radar system noise is white noise, the noise amplitude statistical characteristics presents Gaussian distribution. Based on this, radar output signal is simulated by Gaussian random function generating method. Comparison is conducted between the detected and simulated signal spectrum parameters 1000 times, showing good accordance, the average relative error of the average signal power for CFL-08 wind profile radar is 2%, the error of average Doppler velocity is 3%, the average relative error of spectral width is 1%; the average relative error of the average signal power is 3% for CFL-03 wind profile radar, the error of average Doppler velocity of which is 2%, and the average relative error of spectral width of which is 2%. Furthermore, preliminary test and analysis for wind profile radar information processing method and its processing precision are carried out by using the simulation data.
Correlation Analysis on Estimating Rainfall Using Radar-rain Gauge Calibration
Dong Gaohong, Liu Liping
2012, 23(1): 30-39.
In order to give full play to the advantages of radar-gauge calibration algorithms, the correlation of radar data and rain gauge data is studied before and after quality control by analyzing the quality of radar data and rain gauge data. Based on 11 major precipitation processes during 2008—2009, impacts of 14 types of rain gauge densities on radar rainfall estimation are analyzed by using three radar-gauge calibration algorithms, which are variational calibration method, optimal interpolation method and Kalman filter method. The results show that the quality of rain gauge precipitation data of Tianjin is reliable, only 0.5% of the rain gauge precipitation data has larger error, and equipment failure or external factors is the main cause of its larger error. A reflectivity quality control (QC) procedure has been developed by Chinese Academy of Meteorological Sciences for identifying and removing non-precipitation echoes (such as ground clutter or anomalously propagated ground returns) from the radar base reflectivity fields, and quality control of radar data is implemented using the QC procedure. These non-meteorological echoes can be effectively removed, while retaining precipitation echoes, and thus the rainfall overestimation phenomenon of radar can be significantly improved. The correlation of radar reflectivity data and rain gauge data is analyzed before and after controlling their qualities by selecting different types of precipitation process, results show that quality control of the radar and rain gauge data is necessary to significantly increase the correlation between them and to improve the capacity of radar rainfall estimation. Using some radar-gauge calibration algorithms, impacts of different rain gauge densities on radar rainfall estimation are analyzed. The conclusion is that the capacity of radar rainfall estimation on rain gauge calibration can be improved significantly. The precision of radar rainfall estimation is continuously improved and then become stable with the density of rain gauge increased. The impacts of radar rainfall estimation and the calibration gauge density are related to the types of rainfall. To achieve equal calibration results, convective precipitation caused by cumulus needs the rain gauge density of about a gauge per 182 km2, mixed cloud precipitation needs about a gauge per 211 km2, and for stratiform precipitation a gauge per 405 km2 is enough. The impacts of different radar-gauge calibration algorithms are different. It shows that Kalman filter method is suitable for the calibration of stratiform precipitation or for the low rain gauge density area, and variational method and optimal interpolation method are suitable for the calibration of convective precipitation or for the high rain gauge density area.
Application of USCRN Station Density Strategy to China Climate Reference Network
Hu Ting, Zhou Jiangxing, Dai Kan
2012, 23(1): 40-46.
The US Climate Reference Network (USCRN) consists of 114 stations developed, deployed, managed, and maintained by the National Oceanic and Atmospheric Administration (NOAA) in the continental United States for the express purpose of detecting the national signal of climate change, focusing solely on precipitation and temperature. The vision of the USCRN program is to reduce uncertainty and error range envelopes in producing the most precise in situ precipitation and temperature records possible, and to do it with the fewest possible stations located in areas of minimal human disturbance and with the least likelihood of human development over the coming 50—100 years. And the key goal of USCRN is to reduce climate uncertainty at the national level to a statistically insignificant level. That is, for precipitation climate uncertainty should be reduced by 95% and for temperature climate uncertainty at the national level should be reduced by 98%.China is in great need of a sustainable high-quality and long-term climate observation network, especially for areas without observations or with little information. Given the complexity of the network development, the overall structure of the climate network should be analyzed first. Therefore, the minimum number of sites and locations which are able to represent national climate characteristics of China are proposed, on the basis of the equilateral triangular mesh employed by the USCRN, in order to provide preliminary advice for adjustment and optimization of China Climate Reference Network. For the purpose of assessing the performance of the network in addressing this goal, the coefficient of determination (r2) is used as the performance measure (PM). This PM is an assessment of how closely the current and past configuration of the network captures the true national temperature and precipitation signal as defined by an area-averaged time series of annual temperature and precipitation derived from 2416 China observing stations scattered across the continental China. The result is an explained variance that measures how closely the network's time series follows the true time series.Employing the USCRN standard that coefficient of determination exceeds 98% for precipitation and exceeds 95% for temperature, the 2416 stations in the conterminous China are investigated over the period of 1966—1995. Results indicate that China Climate Observing System should consist of at least 103 quasi-uniformly distributed stations on a 3.0° equilateral triangular grid in order to reproduce inter-annual variability in temperature and precipitation all over China. And on this structure, the new network will be established after surveys, approval or disapproval assessment, test and evaluation periods for each site at each geographic location. On the other hand, China Climate Reference Network may be adjusted and improved on the basis of the existing observing systems. The optimized network consists of 229 quasi-uniformly distributed stations on a 2.0° triangular grid, founded by the existing 199 stations and 30 new-established stations. The expected new-established stations are mainly located in the southwestern part of the Qinghai-Tibet Plateau, where will be the key areas in the network establishment. Based on the actual history of USCRN establishment, the final climate observing network of China may be formed by less than 103 or 229 stations.
Characteristics of Precipitable Water Vapor of Summer Rainstorm Based on Beijing GPS-MET Network
Ding Haiyan, Li Qingchun, Zheng Zuofang, Chu Yanli, Chen Xiaolei
2012, 23(1): 47-58.
Based on the inversion data of perceptible water vapor (PWV) from ground-based GPS network in Beijing, the ichnography distribution characteristics of PWV before precipitation are analyzed. Using ground and upper air meteorological data from the routine AWS and IAWS, the specific humidity of different heights are calculated, which are associated with temperature and wind, the large scale vapor transportation and the local mesoscale convergence. The changes of PWV, occurrence time of precipitation, rainfall and hourly rain intensity are analyzed.According to the precipitation and the curve of PWV in July 2009, the rainfall are not correspond with the PWV value, but it is nearly associated with the vapor transportation and vapor convergence evoked by all kind scales weather systems.The value of PWV increases continuously before precipitation, sometimes there is a sudden increase an hour before precipitation. The ichnography distributions of high PWV value are accord with precipitation area.Curve change of PWV is nearly related with vapor transportation and convergence, and the PWV is related with vapor resource in 3 ways. There is large scale vapor transportation and local mesoscale convergence, the PWV is stably increasing, 4 hours before precipitation, the PWV rises sharply, the local precipitation will occur 2—3 hours after the value of PWV reaches above 50 mm. There is large scale vapor transportation, but there is not precipitation mechanism, the PWV has exceeded 50 mm, the vapor will increase continuously and maintain. The rain will not occur until the precipitation mechanism appears. There is no apparent resource of outer vapor, and the overall level of the PWV is not high. Effects of local apparent wind converge and shear, 2 hours before precipitation, the PWV value increases sharply. The PWV value will exceed 50 mm an hour before precipitation, and the precipitation area is relative convergence. Above all, it shows that if vapor conditions and precipitation mechanisms are suitable, the precipitation will occur 2—3 hours after PWV reaches 50 mm. Otherwise it will not rain even if the PWV value is greater than 50 mm until precipitation mechanism occurs. From the curve of PWV and timely change of precipitation, 4 hours before precipitation, the curve of PWV shows abrupt increase by larger than 1.1 mm per hour. The maximum of hourly rain intensity occurs 1—2 hours after the peak of PWV.
Total Column Water Vapor over Chinese Mainland Based on Different Datasets
Peng Yanqiu, Wang Weiguo, Liu Yu, Li Weiliang
2012, 23(1): 59-68.
The spatial distribution characteristics and linear trends of total column water vapor (TCWV) are compared between radiosonde data, NCEP/NCAR reanalysis data and ERA-40 reanalysis data over Chinese Mainland from 1971 to 2001. The TCWV is also used to investigate how water vapor changes under the context of climate change. The radiosonde data are used to calculate TCWV, which is integrated vertically from surface to 300 hPa, TCWV of NCEP/NCAR and ERA-40 reanalysis data also restricts from surface to 300 hPa. Considering the missing rate and integrity, 78 stations are selected and the analyzed. The result shows that the climatological annual mean and seasonal mean spatial distribution features of TCWV between those data are consistent. TCWV decreases gradually from southeast to northwest, but the decreasing rate derived from the two reanalysis data are smaller than that of radiosonde data. Seasonal variations of TCWV is distinct, the largest TCWV occurs in summer and the smallest in winter. For linear trend of annual mean, TCWV is increasing in northeast of China, the coastal regions of Southern China, northern regions of Southwest China and northern Xinjiang region in all three data. The most evident differences in three data are in southern Xinjiang region and parts of north and east China. In southern Xinjiang region, TCWV of NCEP/NCAR reanalysis data shows decreasing trend, it is increasing according to the other two datasets. In parts of north and east China, TCWV of the two reanalysis datasets both show decreasing trend, but according to the radiosonde data, TCWV may increase slightly rather than decrease. The linear trend of TCWV by all three datasets is not significant at 95% confidence level in this region. Radiosonde data also shows that the largest relative trends are in higher latitudes. Six stations are selected to compare time series of anomaly TCWV between the three datasets, indicating that anomaly TCWV of three datasets have similar variation tendency at the same station, though not equal. The variation tendency of TCWV is different from station to station, which illustrates water vapor responds differently to climate change in different regions.
Comprehensive Consistency Method of Data Quality Controlling with Its Application to Daily Temperature
Wang Haijun, Liu Ying
2012, 23(1): 69-76.
Due to the historical daily temperature data playing an important role in climate analysis and climate change research, the data quality is attached more importance. At present the daily temperature data are checked for quality control using the traditional methods in China, lacking a systematic and comprehensive method to pick up the outliers data hidden in the historical temperature data. These error data in the daily temperature affect data application, therefore, it's necessary to carry out the research of new quality control method.Using linear regression model and historical daily temperature (average temperature, maximum temperature and minimum temperature) data of the neighbouring stations in the same period, a quality check algorithm based on linear regression estimation method is designed, which includes both time consistency check and spatial consistency check in quality control of meteorological observational data. To further enhance the detection performance of data quality check, a comprehensive consistency check method is developed based on this algorithm, which adds internal consistency check that refers the variation of related meteorological elements such as daily temperature (average temperature, maximum temperature and minimum temperature), precipitation and sunshine duration to check data quality.Using the data seeded errors check test and compared with spatial regression test, the method of linear regression data quality control algorithm has higher error data check performance. The algorithm can detect suspicious data that is about 3℃ difference from the correct value on the temperature.Through data quality control practices and analysis on historical data, the comprehensive consistency check method has the following advantages: The flagged rates of Type Ⅰ errors are lower, thus reducing false detection rate of that the correct data flagged as error data; the logical relationship are kept with time consistency, internal consistency, and spatial consistency in data quality control process, and these three methods of checking the consistency of data quality are as a whole at the same time; the weather factors are referred, thus reducing the impact on data quality of small-scale weather phenomena which can flag data incorrectly. Therefore, the method of comprehensive consistency data quality control, which compared to the traditional data quality control method, has higher error detection performance.The algorithm achieves good progress on the applications of daily temperature data from 251 weather stations from 1961 to 2009 in Hubei, Hunan and Henan provinces. Detection of outliers in the average temperature is 0.001%, that in the maximum temperature is 0.05%, and that in the minimum temperature is 0.04%.
Numerical Simulation of Atmospheric Duct in Typhoon Subsidence Area
Liu Guiyan, Gao Shanhong, Wang Yongming, Chen Xueen
2012, 23(1): 77-88.
The atmospheric duct is a kind of anomalous refraction phenomena in the troposphere atmosphere. It can change the normal propagation characteristic of the electromagnetic wave, and has a significant influence on radar detections and radio communications. The emergence of duct strongly depends on the weather conditions and it often occurs in the subsidence area west to a typhoon.With the rapid development and extensive application of atmospheric numerical models, high-resolution numerical modeling has become an important tool to get insight of duct.Using the WRF model, the atmospheric duct process occurred on 31 August 2002 over Nanjing region in a subsidence area west to Typhoon Rusa is studied in details. The WRF numerical simulation reproduces well the evolution of the duct, which starts to form in the evening of 31 August, reaches the strongest level the next early morning, weakened and disappeared rapidly after sunrise. Based on numerical simulation output with high spatial-temporal resolution, results show that humidity gradient is a key factor to the formation of this duct, and the humidity invertion enhances its strength. The outside low-level flow in the typhoon early stage brings plenty of moisture from the sea to Nanjing region in the near surface layer. The typhoon moves northeastward and dry air mass is transported from the north by the outside high-level flow in the typhoon late stage, and sink down due to high pressure, so an intense gradient of humidity which is prerequisite for the formation of duct appears in the near surface layer. The subsidence itself is not strong enough to directly cause the inversion, but the clear-sky weather caused by it is favorable for long-wave radiation cooling during night time, which is the primary cause for the inversion formation. The inversion formation hinders the upward transport of water vapor, so that the humidity gradient develops further. Besides, the simulation results also reflect the marine atmospheric duct.These results also show that the high-resolution atmospheric meso-scale numerical simulation can be used as an effective means of studying and forecasting duct.
Bias Correction for FY-3A Microwave Sounding Data with Its Application to Typhoon Track Forecast
Du Mingbin, Yang Yinming, Yang Yuhua, Zhang Jie, Zhu Xuesong
2012, 23(1): 89-95.
The quality of numerical weather prediction depends closely on accuracies of initial condition provided by observation system. Satellite observations are very important source for data assimilating models, which is of good overcast, high resolution and stable, improving prediction compared to conventional data in many cases. A new generation polar-orbiting meteorological satellite of China, FY-3A is successfully launched on 27 May 2008, and FY-3B is also successfully launched on 5 November 2010. The two kinds of microwave vertical sounding sensors aboard are very similar in capability to ATOVS (the Advanced TIROS Operational Vertical Sounder) of NOAA series satellite. One of them is microwave temperature sounder (MWTS), and the other one is microwave humidity sounder (MWHS). They are used to sound the vertical distribution of the atmospheric temperature and humidity respectively. They provide very important observations for application in regional and global data assimilation system.Because of the observation instrument accuracy, observation operator approximation, assimilation model limitations, to the assimilating bias needs correction. The significant characteristics of bias effect are to cause systematic increment field, and the increment field could be obtained by OMB (observed minus background) statistic. This bias correction experiment of FY-3A satellite microwave data is developed on the basis of Harris and Kelley's bias correction experience method for TOVS radiation data, and with combination of improved WRF-3DVAR system. By analyzing the algorithmic method of radiative transfer in the spectral of microwave coverage, mapping function of model variables and brightness temperature of satellite microwave channel is established, making the fast radiative transfer model to be of quasi-linear expression, with considerable accuracy. Under the fast radiative transfer model and its corresponding tangent linear and adjoint model, a direct variational data assimilation system is established in the original assimilation framework using FY-3A microwave temperature sounder and microwave humidity sounder as input. In consideration of the spatial variations and the air mass dependence of satellite radiation data, the microwave data are processed with scan bias correction and air mass bias correction. And the microwave data of each channel basically has a fitting line along the leading diagonal after bias correction. Distribution of most the satellite observation and the brightness temperature derived by observation operator using background tends to be reasonable, and the bias is reduced a lot.With bias correction, FY-3A microwave data is directly assimilated in numerical weather prediction. The assessment of the forecast experiments for 4 typhoons shows that after assimilation the track forecasting ability is significantly improved, especially after 36 hours. And assimilation of FY-3A microwave data has reduced track forecast error by an average of 20%, while the assimilation of conventional data can reduce it by only 4%.
Monitoring of Low Temperature in Fujian Based on the Distance to the Coastline and GIS Technology
Wang Jiayi, Chen Hui, Xia Lihua, Pan Weihua, Cai Wenhua
2012, 23(1): 96-104.
Based on the 1:250000 Digital Elevation Model (DEM) data and statistical data of the air temperature of 67 weather stations, considering the distance to coastline in Fujian Province considering the feedback effect of ocean to continent, the geographic mathematical model is established depending on the connections between factors such as the lowest temperature, latitude, longitude, altitude, and is used to simulate the fine distribution of lowest temperature in cold air processes of winter from 2008 to 2010.On the basis of the ascertainment of coastline and proven distributions, the appropriating calculation formula of the distance to coastline is ensured and the three monitoring models of low temperature processes are founded based on the choice of different distance to coastline or no distance to coastline. Moreover, the models are analyzed comparably and the best model is applied to simulate the low temperature. Contemporarily, the method of selecting appropriate the distance to coastline is approved by regression models and integrative residual sum of squares, and the transacting process of simulated errors in the joint of inter and outer coastline is introduced.The results show that the lowest temperature is well simulated by introducing the appropriate distance to coastline to the low temperature monitoring model during the cold air processes. With the increase of average cooling range of cold air, the efficiency of distance to the coastline factor to the value of the minimum temperature simulation decreases. Moreover, the distances to the coastline are changed with the different cold air processes and are not more than 50 kilometers. Furthermore, the method of how to select appropriate distance to the coastline is confirmed based on the value of different square sum. Although there is adjusting effect of ocean temperature to land temperature, with the increase of distance to coastline, the feedback effect on temperature of ocean to land decreases, and the mathematical model made up of factors such as longitude, latitude, altitude and the distance to coastline is suitable for low temperature monitoring simulation in regions where the distance to the coastline are more than 50 kilometers. Similarly, the mathematical model made up of factors as longitude, latitude, altitude and the distance to coastline is suitable for low temperature monitoring simulation in regions of the distance less more than 50 kilometers, which could increase the precision of low temperature monitoring simulation and embody the adjustment function of sea to land temperature. Finally, 9 destined samples (each sample is selected optionally from one city of Fujian) are verified in the model and the simulated results of low temperature are proved to match with actual situation substantially.
Function and Designing of Automatic Observing System for Agro-meteorology
Zhang Xuefen, Xue Hongxi, Sun Han, Cao Zhiguo, Li Cuina, Jin Hongwei, Yu Zhenghong
2012, 23(1): 105-112.
Based on the proposed technique thought and designing principles, the hardware component parts and software function is designed for automatic observing system of agro-meteorology (named AOSA), which is visual and real time and can be controlled remotely according to the requirement of modern agro-meteorological operation. The AOSA is made of the automatic observing system of crop growing and meteorological observing as well as environment monitoring in the field. It includes temperature and humidity sensors for different heights, and solar radiation, photosynthetically active radiation, infrared temperature, rain, wind sensors above crop, and soil humidity and soil temperature sensors for different depths in soil. It can realize automatic observation of crop growing phases, crop height, crop cover, and main agro-meteorological disasters by means of crop meteorological observing and soil moisture data. There are many observing elements in agro-meteorology observation task, but the urgently needed elements and crop types in operational observation are solved in AOSA.The automatic observing techniques are introduced systematically. The technological specification of crop growing sensor is the foundation of AOSA research and development, which (resolutions of CCD sensors and installing height) have influences on accuracy of the crop automatic distinguishing. The results show that CCD sensor height and focus for short stalked plant is not below 3 m and 16 mm respectively and CCD sensor height and focus for tall stalked plant is not below 5 m and 21 mm respectively to observe an area of 5 m2 properly. The automatic distinguishing technique of crop development phases is realized by means of picture differentiating technique, considering crop growing and meteorological index. Crop observation is complicated, so different development phases have different algorithms of automatic observing. Observing method of crop height is developed by photography and dynamic tracking technique. The method of plant cover calculating is given out per hour, and automatic observing of crop density and leaf area will be solved through researching out the relationship between them. The AOSA will preliminarily realize visual, real time and automatic observing of main agro-meteorology observation through image processing and photogrammetry techniques.
Design of CMA's Broadcast System for Meteorological Data—CMACast
Wang Chunfang, Li Xiang, Chen Yongtao, Jiang Kejian
2012, 23(1): 113-120.
Due to broad coverage, low-cost user equipment and easy installation, data broadcast system based on commercial communication satellite has been considered to be the most effective way for data dissemination worldwide. CMA has implemented three satellite broadcast systems, PCVSAT, DVB-S and FENGYUNCast since 1998. PCVSAT and DVB-S, which are Ku band systems covering China and surrounding area, are primarily used to distribute land and air based observation data and products. FENGYUNCast, which is a C-band system covering Asia and part of the south-western Pacific area, is primarily used to distribute space-based observation data and derived products from Fengyun series satellites of China. FENGYUNCast becomes part of GEONETCast Centre of GENONETCast Network in Asia-Pacific region in 2008. Currently PCVSAT, DVB-S and FENGYUNCast have 2400, 700 and 200 users respectively.The coexistence of three broadcast system causes inefficiency and inconvenience to both CMA and users. In 2008, CMA started to build a new system, CMACast, to consolidate the services and users of the three systems together. CMACast is a multimedia dissemination system based on the second-generation Digital Video Broadcast (DVB-S2) technology with both file and multimedia transmission capability, employing a whole 36 MHz C-band transponder of AsiaSat-4 and the transmission capacity can reach up to 70 Mbps. Besides high data rate, CMACast is expected to enhance user management and data exchange cooperation with other regional GEONETCast Network Centres (GNC), including EUMETCast and GEONETCast Americas.CMACast is not only the main component of CMA national and international communication system, but also the main component of WMO IGDDS and GEONETCast. The infrastructural, main function and key technology of CMACast and its comparison between PCVSAT, DVB-S, FENGYUNCast, EUMETCast and GEONETCast Americas are introduced. Infrastructural introduction includes system architecture, coverage and capacity. Main function includes file broadcast, multimedia broadcast, data exchange, user management and data reception. Key technology includes DVB-S2 standard, bandwidth sharing mechanism and dynamic data encryption mechanism. The comparison result indicates that CMACast is a leading satellite data broadcast system in the world with broad coverage, advanced technology and multiple functions.CMACast is on trail operation in the middle of 2011 and will operate simultaneously together with PCVSAT, FENGYUNCast and DVB-S from June to October in 2011, when all the users of the current three systems will transit to CMACast. After that, the current three systems will be closed and CMACast will be the only operating data broadcast system of CMA.
Application of the WAN Acceleration Technologies to FY-3 Satellite Data Transmission
Wei Lan, Lin Manyun, Zhao Xiangang, Zhang Zhanyun
2012, 23(1): 121-128.
FY-3 series is a new generation of polar-orbiting meteorological satellite which is much more powerful than FY-1 series. As the first research and development satellite of FY-3 series, FY-3A meteorological satellite carries 11 kinds of instruments with more than 90 observation and probing channels, and it has the capabilities of global sounding, global imaging of the earth's surfaces and natural color imagery with a higher spatial resolution of 250 m. The size of the raw data files for one pass of FY-3 meteorological satellite is almost 100 times as FY-1. There are 4 domestic ground stations set up in China, and they are located in Beijing, Guangzhou, Urumqi and Jiamusi respectively. These 4 ground stations are responsible for receiving the FY-3 satellite observation data and transferring them to the data processing center which is located inside the building of National Satellite Meteorological Center in Beijing. It is really a big challenge for the data transmission system of the FY-3 satellite to transfer the massive meteorological satellite observation data efficiently and timely from the ground stations to the data processing center.The WAN acceleration technique is studied to solve the problems such as high delay in transmission of massive satellite observation data and little bandwidth utilization during WAN link. To deal with the data transfer characteristics of FY-3 properly, massive observation data and high-timeliness requirement for instance, the transmission optimization effects of three different acceleration techniques, including data compression, cache and TCP protocol optimization on meteorological satellite data are analyzed respectively. According to the analysis results, a WAN data transmission acceleration architecture which is suitable to FY-3 satellite observation data transmission is illustrated and presented to break the bottleneck of data transmission through WAN. This architecture combines TCP proxy module, segment index module and HS-TCP transfer module by integrating three different acceleration techniques to realize the key functions such as data compression, cache and protocol optimization. Experimental and operational practices show that this WAN data transmission acceleration architecture results in impressive acceleration, and FY-3 satellite data transmission rate through the WAN is accelerated up to 50%—243%.