应用气象学报

Multi-scale Satellite Data Sensitivity Study on Cloud Analysis of Strong Typhoon

Liu Jian, Jiang Jianying

2014, 25(1): 1-10.

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Abstract:
The traditional obervation interval of Fengyun geostationary meteorological series satellite is 1 hour for a single satellite. During flooding season, the obervation frequency is imporived to half an hour. Double satellite observation mode can provide remote sensing data every 15 minutes. Due to the difference of observation angles and calibration error between different satellites, remote sensing data sometimes appear consistency and uniformity deviation. So improving observation frequency for a single satellite is the best way to get high quality remote sensing data. Rapid scan mode of geostationary meteorological satellites is an important method to monitor all kinds of weather processes.National Satellite Meteorological Center uses retired FY-2C satellite to carry out high frequency rapid regional scan observation trials and get continuous data with an average of 10-minute interval. Based on high frequency observations, Hovmöller diagram and coefficient of variation are used to analyze the sensitivity of multi-scale satellite data on monitoring the structure of a strong typhoon Muifa (2011).The research results show that the high frequency observations can clearly demonstrate the evolution of a strong typhoon cloud structure. Each channel with different spatial and temporal resolution has different sensitiveness in monitoring the structure feature of cloud. Reflectivity at visible channel with 1.25-kilometer spatial resolution and 10-minute temporal resoution can well show features of typhoon cloud. Under the same observation temporal resolution condition, lowering spatial resolution has great impact on monitoring the structure of cloud. If the spatial resolution keeps the same, reduced observation temporal resolution has less effect on extracting the characteristics of clouds. Using Hovmöller diagram to compare cloud brightness temperature characteristics through infrared window channel under different temporal resolution, it can be seen that there is no great difference between 10-minute and 30-minute observation modes. The cloud features are greatly reduced after the observation interval being changed to 60 minutes. The results also show that the cloud characteristics change greatly during 60 minutes based on brightness temperature coefficient of variation difference. Because the brightness temperature coefficient of variation at water vapor channel is smaller than infrared channel, the evolution of cloud characters observed by infrared window channel is more sensitive than that by water vapor channel. So improved observation temporal resolution can get more cloud information through infrared window channel.

The East Asian Winter Monsoon Background on the Variation of Winter Air Temperature in Northeast China

Liu Shi, Sui Bo, Tu Gang, Feng Xiyuan

2014, 25(1): 11-21.

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Abstract:
Using monthly mean temperature data from 72 meteorological stations in Northeast China of temperature dataset established by National Meteorological Information Center of CMA and NCEP/NCAR reanalysis data from 1961 to 2011, two sequences of the East Asian winter monsoon intensity index and winter air temperature in Northeast China are processed, removing the linear trend. The contrastive analysis is made on the variation characteristics between the winter monsoon intensity index and the winter air temperature in Northeast China.The result shows that two sequences change synchronously and the correlation coefficient after removal of linear trend is-0.69, which is greater than that between two original sequences. Under the background of global warming, the increasing trend of winter air temperature in Northeast China makes this relationship become weaker. When Northeast China enters the cold phase in 2004, the East Asian winter monsoon intensity index also enhancs at the same time. The warming trend of winter air temperature plays an important role in the warming climate abrupt change in 1986.Correlation coefficient between the inter-decadal signals of the East Asian winter monsoon intensity index and the winter air temperature in Northeast China is-0.86, which is also more obvious compared with the original sequences. A quasi-period of about 21.5 years is found for the inter-decadal variation, the winter air temperature in Northeast China is in the low stage, and the East Asian winter monsoon is in strong phase of this period at present. A 4-year quasi-period is found for the inter-annual variability.The inter-annual and inter-decadal anomalies of the winter air temperature in Northeast China are related with the abnormal background of some systems such as the East Asia westerly jet stream at 200 hPa, the East Asia trough and the high in Ural at 500 hPa, wind at 850 hPa, and the Siberian high on the ground associated with the East Asian winter monsoon. During the inter-decadal low temperature stage, the westerly jet moves further south at 200 hPa, the Siberia high and the East Asia trough is stronger at 500 hPa, the Siberia anticyclone is abnormally stronger, and there is the cyclonic circulation anomaly in western continental Europe at 850 hPa and significant northerly wind anomaly in the north region of the Okhotsk Sea. All of these anomalies reflect the inter-decadal stronger characteristic of the East Asian winter monsoon, and vice versa. The possible physical contact between the East Asian winter monsoon intensity and the winter air temperature in Northeast China may be consistent associated with inter-decadal on the inter-annual timescale.

Numerical Simulation and Flight Observation of Stratiform Precipitation Clouds in Spring of Shanxi Province

Li Junxia, Li Peiren, Tao Yue, Shi Yueqin, Jin Lijun

2014, 25(1): 22-32.

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Abstract:
The CAMS meso-scale cloud model is introduced and operationally applied since 2009 in Shanxi Province. The macro and micro structure of stratiform precipitation clouds, especially the vertical micro-physical structure are simulated and analyzed for a spring stratiform precipitation process in Shanxi Province on 20 April 2010 using the model. Two cloud physical detection flights are carried out by using weather modification plane with equipments of droplet measurement technologies (DMT) in the same place during the same period of the day. The data and images from flight detection and results of numerical simulation are compared and studied. Simulation results show that the precipitation process mainly comes from cold stratiform cloud. The cloud contains a lot of supercooled water, and the thickness of the rich supercooled water layer is about 4000 meters. The temperature of the supercooled layer is about 0 to-40℃, and the ratio content of the supercooled cloud water is about 0.1—0.7 g·kg^-1 with some ice crystals distributed unevenly. The structures of stratus precipitation cloud can be roughly divided into three layers. The first layer (upper layer) is mainly composed of ice crystals; snow, sleet and supercooled cloud water are mixed in the second layer (middle layer); and the third layer (lower layer) is mainly of liquid raindrops. The vertical distribution and the transformation of different hydrometers in different stages of the precipitation are analyzed. The precipitation mainly comes from the melting of the ice phase particles such as ice crystals, snow, sleet and the transformation of liquid cloud droplets. Comparison of the numerical simulation results and the plane observation shows that the temperature and altitude relationship are in good agreement. The simulated vertical structure of the different cloud particles phase and the vertical distribution of the cloud liquid water ratio content are nearly the same as the vertical distribution of different cloud particles images and the cloud liquid water content of the flight detection. The difference is that the simulated height where various hydrometeors appears is higher than the actual flight detection.

Relationship Between Lightning and Precipitation Based on Classification of Atmospheric Stratification and Development of Thunderstorm

Wang Tingbo, Zheng Dong, Zhang Yijun, Yao Wen, Zhang Wenjuan

2014, 25(1): 33-41.

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Abstract:
A total of 28 thunderstorms occurring in and around Beijing area from 2006 to 2008 are picked to investigate the relationship between total lightning (observed by SAFIR3000) and convective precipitation (by radar inversion). These cases are classified according to parameters of the atmospheric stratification where they are generated and the reflectivity of radar. The quantitative results can provide a reference for the applications of lightning data on severe weather warning and precipitation estimation. The lightning forecast can also be improved by assimilating the relationship between the hydrometeors and the lightning activities to the numerical prediction models. The analysis can extend the application field of the lightning data.The results show that the average convective rain yields per flash is 1.92×10⁷ kg·fl^-1 on the whole, while the linear correlation coefficient between the total lightning frequency and convective precipitation is 0.584. Total lightning frequency (expressed by F with the time space being 6 min) can be used to calculate the amount of convective precipitation with the equation R=(2.813×10⁸)+(4.570×10⁶)F. A total of 28 thunderstorms are classified according to the convective available potential energy (E_CAP) and lifting index I_L of the atmospheric stratification where they are generated. It is explored that strong instability of atmospheric stratification tends to be associated with smaller precipitation and more pronounced correlation between total lightning and precipitation. Of which, the classification of E_CAP no less than 1600 J·kg^-1 has the correlation coefficient of 0.837, the total lightning frequency can be used to calculate the amount of convective precipitation with the equation of R=(1.620×10⁸)+(5.478×10⁶)F. While the classification of I_L no less than 4 K has the correlation coefficient of 0.853, the total lightning frequency can be used to calculate the area of the amount of convective precipitation with the equation of R=(1.530×10⁸)+(6.276×10⁶)F. Another three parameters calculated from radar reflectivity, i.e., maximum height of 20 dBZ reflectivity, maximum reflectivity at 12 km level, and volume ratio of the reflectivity larger than 30 dBZ above 0℃ to the reflectivity larger than 40 dBZ above 0℃, in terms of their radar volume scans. The most pronounced relationships between lightning and precipitation occur in the classification of H_{20 dBZ} < 11.5 km, 25 dBZ ≤f_{12 km} < 35 dBZ, and V_40/30 < 0.39, when the correlation coefficients are 0.804, 0.609 and 0.750, respectively. The linear correlation between lightning and precipitation show obvious differences in different classifications. The fitting equations in different classifications are revealed, which will provide references for the application of relationships between lightning and precipitation according to the characteristics of thunderstorm processes.

Retrieval of Atmospheric Aerosol Optical Depth over Land from AVHRR

Gao Ling, Zhang Liyang, Li Jun, Chen Lin, Sun Ling, Li Xiaojing

2014, 25(1): 42-51.

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Abstract:
The moderate-resolution imaging spectroradiometer (MODIS) onboard NASA EOS Terra and Aqua satellites, advanced very high resolution radiometer (AVHRR) onboard NOAA series provide important aerosol measurements. MODIS provides atmosphere aerosol optical depth (AOD) product since 2000, and AVHRR also provides AOD product since 1981 but only over ocean. Developing AOD retrieval algorithm which can also obtain AOD from AVHRR over land is very important for establishing a long term AOD data record for climate studies. As 2.1 μm band is absent, an algorithm which is different from MODIS is introduced to retrieve AOD over land from AVHRR. With this method, the surface target is assumed to remain radiometrically invariant over a certain time period and some of observations are made under clear-sky background aerosol conditions. When background aerosol conditions are given, surface reflectance can be estimated by extracting the second minimum reflectance during the previous 22 days and the future 22 days. The second darkest reflectance is chosen to reduce cloud shadow contamination. After surface reflectance is selected, AOD is retrieved from a look up table (LUT) generated with the second simulation of the satellite signal in the solar spectrum (6S) radiative transfer model. The AOD over part of China (15°—45°N, 75°—135°E) from AVHRR in 2009 is obtained based on this algorithm. The distribution pattern of AOD from this work is consistent with that of MYDO04 from MODIS in North China and East China, but has some difference in Northwest China. The daily regional mean AOD from AVHRR in the Yangtze Delta (28°—36°N, 112°—122°E) agrees well with MODIS AOD with all correlation coefficients larger than 0.5 for four seasons, even up to 0.8 in winter. The correlation coefficients are 0.70 in Beijing, 0.63 in Xianghe and 0.61 in Taihu when AOD from AERONET are used to validate the AVHRR AOD retrievals. To compare temporally varying AERONET data with spatially varying AVHRR, the time match window is limited within 30 minutes and the spatial distance is limited within 0.10. The monthly variation of AOD from AVHRR in the Yangtze River Delta is consistent with that from MODIS, but the former is larger. Error sources about this retrieving algorithm are also discussed, including different satellite zenith angles in the selected period, surface reflectance, aerosol types, background AOD, calibration and sensor noise and so on. According to these results, this algorithm has the potential for deriving long-term AOD climate data record over land from AVHRR although some uncertainties still exist. Quality control and error characterization will be further investigated in the future.

An Objective TC Intensity Estimation Method Based on Satellite Data

Lu Xiaoqin, Lei Xiaotu, Yu Hui, Zhao Bingke

2014, 25(1): 52-58.

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Abstract:
Researches prove that TC (tropical cyclone) intensity is mainly determined by the top cloud convection strength, distribution and size. Then how to extract this information from TC cloud image is very important for TC intensity estimation. In 1988, Adler put forward a method named CST (convective-stratiform technique) to extract tropical convective cores from TC cloud image. Using MTSAT (multi-functional transport satellite) IR1 black body temperature data, the TC cloud top strong convection is extracted. Based on the convective cores number, convective core distance to TC center and convective core black body temperature extreme value, which are closely related to TC intensity, a TC intensity (expressed by V_max, the maximum sustained wind speed near surface TC center) estimation model is put forward using stepwise regress method. The experiment result shows that there is a linear correlation between their estimation error and their intensity for V_max >40 m·s^-1 and V_max < 18 m·s^-1 samples. So according to the estimation error distribution a linear revision is carried out.Statistical tests show this model is equivalent to Dvorak method and AMSU in TC intensity estimation accuracy. It's also reliable based on the relationship between the convective cores, convective cores distribution, brightness temperature and TC intensity. It could be used in all TC life span automatically and objectively, so it could be applied in the operation.Comparing with the advanced objective dvorak technique (AODT) and objective Dvorak technique (ODT), this algorithm gives accurate results in the Western North Pacific, but it's simpler with no complicated pattern types identifying process or other rules. A fixed radius of 135 km area is used as TC convective cores searching effective area in the model, but actually the maximum wind speed radius of the TC is variable, the TC size and the strongest convective area size are different for different TC in different stage. So using the fixed searching area may affect TC intensity estimation accuracy. The research on how to get the dynamical maximum wind speed radius would be carried out in the future.

Numerical Simulation of the Lake Breeze Impact on Thunderstorm over the Taihu Area

Yang Wei, Miao Junfeng, Tan Zhemin

2014, 25(1): 59-70.

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Abstract:
During the afternoon hours of 18 August 2010, thunderstorms struck the Taihu area and cause extensive damage in the vicinity. To investigate the impact of lake land use changes on the evolution of the severe thunderstorms, a coupled Weather Research and Forecasting (WRF) model with the NOAH land surface model is used. The control run and two sensitivity experiments are designed. The control run (CNTL) is carried out with the original surface characteristics; the first sensitivity experiment EXP1 is designed to replace the Taihu with cropland; and in the second sensitivity experiment EXP2 the underlying surface is considered as water. Three experiments employ four nested fixed grid which are set as a two-way run with spacing of 27, 9, 3, 1 km, respectively. The initial and boundary conditions are provided by the NCEP FNL analysis. To verify the simulation, the control run results from 1 km domain are compared with observation.Results show that the control run simulates well both lake-land breeze circulation and remarkable lake-land breeze evolution on 18 August 2010. It is found that the wind speed and depth of the lake breeze are horizontal asymmetries on the east and west coast of the Taihu are affected by southeasterly gradient flows and valley breeze. At the leading edge of lake breeze circulation called lake breeze front, convergence lines spread along the lake shore, and then the ascending motion, moisture air and low-level vertical wind shear triggers the development of thunderstorm at 1200 BT. Characteristics of the diurnal evolution of the thunderstorm are reproduced by WRF model, representing the initiation of convection along the lake breeze front and the formation of thunderstorm, and then the collision between outflow from thunderstorm and lake breeze triggers a new thunderstorm.The convective cloud doesn't develop in EXP1, and the whole area shows cloudless in EXP2. The comparison experiments show that the lake breeze front triggers and strengthens the severe convective weather. In the course of thunderstorm development, the exchange of sensible heat fluxes can change the structure of the boundary layer, and make the atmosphere more unstable. On the other hand, the surface fluxes moisten the boundary layer atmosphere and enhance horizontal convergence and divergence which can accelerate the development of cloud and precipitation.

Observational Analysis of Cloud Characteristics of the Bohai Sea-effect Snowstorms

Zheng Yi, Gao Shanhong, Wu Zengmao

2014, 25(1): 71-82.

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Abstract:
Sea-effect snowstorm is a kind of typical local disastrous weather phenomena in winter of Shandong Province. The pioneering researches on snowstorm clouds usually focus on the period of snowfalls, but studies on their formation and development stages are rare. The clouds over the northern Shandong Peninsula usually are the southern edge of the sea-effect snowstorm clouds, and its evolution is closely relative to the main clouds over the Bohai Sea. 12 sea-effect snowstorm events during 2001—2010 over the Bohai Sea are investigated.First, stationary satellites (GMS-5, GOES-9, MTSAT) infrared data is used to investigate the evolution characteristics of snowstorm clouds, and combined with NECP FNL data, forming locations and moving features of different processes are classified. In addition, routine observation is used to analyze the corresponding relationship between snow and snowstorm clouds and the influence of the diabatic heating effect over the Bohai Sea. Finally, cloud profiling radar data of CloudSat are used to analyze the vertical structure and compositions of snowstorm clouds.The snowstorm clouds with different origins usually grow rapidly over the Bohai Sea, and among the clouds there are dense clouds with horizontal scale of 100—300 km in form of strips or a bulk, which is closely relative to the snowfall areas.The snowstorm clouds during their initial stages can be classified into three main categories according to their forming locations, near the Bohai Bay and the Laizhou Bay, the central part of the Bohai Sea, and near the Liaodong Bay. The movements of snowstorm clouds depend on winds at 850 hPa, and its dominant directions of movements can be classified into three types, by reference to the Bohai Strait move from west to east, from northwest to southeast, and from north to south, and finally the clouds reach the upper air of the northern Shandong Peninsula, which leads to its snowfalls.As cold winds move across long expanses of warmer water, the heat and moisture transport from the Bohai Sea warm surface upwards to its above cold air, defined as the Bohai sea-effect, results in the unstable conditions over the Bohai Sea. And meanwhile, the unstable conditions improve the shallow convection to intense, which results in the snowstorm clouds.The height of mature sea-effect snowstorm clouds can reach 4 km or so, and its ice-water mixture content has an average value of about 303 mg·m^-3, its maximum is about 600 mg·m^-3 and mainly distributes at 2 km height, and additionally the maximum and average values of ice effective radius is about 120 μm and 91 μm, respectively.

Direct Effects of Tropospheric Aerosols on Stratospheric Climate

Song Liuming, Liu Yu, Zhu Bin, Li Weiliang

2014, 25(1): 83-94.

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Abstract:
The comparison between satellite data and WACCM-3 model simulated results shows that simulated results are well consistent with satellite data in central Africa, the Arabian Peninsula, Indian subcontinent, and most parts of China, but in south central Africa, Caribbean and Europe, the model results are lower. In short, model results can well reproduce the global distribution of aerosols, but numerical difference exists in some areas.Simulation indicates that changes of stratospheric temperature are neither caused by changes of stratospheric short-wave radiation nor decided by the changes of long-wave radiation. The changes of stratospheric temperature are not caused by the tropospheric aerosol effect but the results of dynamic process, and the changes of longwave radiative heating rate are in response to temperature changes and mitigate the change. The process of stratospheric chemical, dynamic and radiation process are tightly coupled together. By comparison, the experiment group A including stratospheric chemical process and experiment group B not including stratospheric chemical process, it shows that the changes of temperature and wind are different in the tropospheric aerosols direct effect on stratosphere. The stratospheric chemical process is of vital importance on the tropospheric aerosols effects on stratospheric climate. Stratospheric chemical process has different effects in different seasons and in different regions, polar and high-altitude regions are considered to be mostly affected, in addition, stratospheric chemical process also has great influence on the upper stratosphere. The temperature variation can reach 6 K at the most, and zonal wind variation can also reach 12 m/s. The tropospheric aerosols influence the tropospheric radiative balance, tropospheric temperature, atmospheric circulation and EP flux, and changes in EP flux indicate the planetary wave propagation changes.Planetary wave propagation changes make the stratospheric climate change: Stratospheric temperature, and wind field change, stratospheric ozone and radiation and dynamic processes are closely linked and influenced by each other, the temperature and wind changes will influence the concentration of ozone. Polar and high-latitude regions are considered to be mostly affected, and the impact on southern high latitudes is greater than that on northern high latitudes. The temperature variation can reach 10 K at the most, zonal wind variation can also reach 12 m/s and ozone mixing ratio can decline for 0.8×10^-6 at the most at 20 hPa in the lower Antarctic stratosphere, while in most other areas the temperature change does not exceed 1 K.

Simulation and Projection of Temperature in China with BCC_CSM1.1 Model

Zhou Xin, Li Qingquan, Sun Xiubo, Wei Min

2014, 25(1): 95-106.

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Abstract:
Inter-annual and inter-decadal variability are two kinds of different timescale variability existing at the same time in climate system found in previous studies. Affected by the global warming, the inter-decadal signal of climate change becomes more and more significant. The next 10 to 30 years of climate change, namely inter-decadal time scales climate change and their impacts on the global environment, society and economic development, draw more and more attention. Climate change features of inter-decadal scale become one of the most important content of the IPCC AR5. The 10 to 30 years' timescale of inter-decadal forecast experiment which is listed as one of the main experiment content has joined the 5th Coupled Model Inter-comparison Project (CMIP5). More in-depth research will be carried out on predictability of inter-decadal timescale.The air temperature data of 541 stations in China from 1960 to 2010 as well as the CMIP5 historical and decadal experiment results of Beijing Climate Center Climate System Model (BCC_CSM1.1) are utilized to evaluate the simulation ability of the model. The model results are interpolated to the corresponding latitude and longitude of 541 stations use bilinear interpolation method. Whether the pattern of regional prediction ability could improve by the decadal experiment of BCC_CSM1.1 which initialed the SST (sea surface temperature) is discussed. Bias corrections to the decadal experiment results are done and the preliminary projection of the changes of the air temperature of China for the next 10—20 years is presented. Results show that both historical and decadal experiments can capture the warming trend in accordance with the observations, but the warming tendency of the experiments are less significant than those of observations. Results of historical experiments are slightly better than those of decadal experiments of the model. On the inter-decadal timescales, simulations in the eastern part of China are better than those in the western part of China. On the inter-annual timescales, the high prediction skills are located in the southwestern and eastern parts of northwest region, and southwest of China. Distributions of temperature in China are well simulated in both of historical and decadal experiments, such as the spatial correlation coefficients of 0.9 or above. After bias correction, results of decadal experiments are much better. By the corrected result of decadal experiments, the result of temperature spatial distribution simulation is better. The model projects that the rising rate of the mean temperature of China will be 0.48℃/10 a during 2011—2030, which is more significant than the warming rate of 0.27℃/10 a during 1960—2010 on the basis of observations. And the forecast results of the model show that the air temperature of China during 2001—2010 grows more slowly and fluctuate less compared with the period of 2011—2030.

Application of Stratospheric NAM Signal to Wintertime Climate Prediction

Jia Zhe, Wen Xinyu, Hu Yongyun, Guo Yanjun

2014, 25(1): 107-111.

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Abstract:
Stratospheric circulations are of planetary scales and long periods. It is considered that signals of stratospheric circulation anomalies could be used to predict tropospheric weather and climate systems in wintertime, but few practice is reported so far. To evaluate whether stratospheric signals can be used in long-term weather prediction or short-term climate prediction in wintertime, four intra-seasonal climate prediction experiments are carried out in winters of 2011 and 2012, using the index of stratospheric northern annular mode (NAM). Among the four predictions, the second and the third predictions successfully captured the polarity of NAM and surface temperature tendency in North China, which are well verified by observations in following weeks. The second prediction is particularly successful. The results suggest that stratospheric NAM signals are indeed useful for improving prediction skills for long-range weather or short-term climate variability in winter.

Hydrometeorology Forecast System of the Danjiangkou Basins in Hanjiang

Peng Tao, Wei Chengzhi, Ye Jintao, Wang Junchao, Yin Zhiyuan, Shen Tieyuan

2014, 25(1): 112-119.

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Abstract:
The modern meteorological service technology development, especially quantitative precipitation estimation and forecast technology, makes it possible to improve the hydrological meteorological forecast service. Based on real-time hydrological and meteorological monitoring, quantitative precipitation estimation (QPE), quantitative precipitation forecasting (QPF), real-time flood forecast technique, hydrometeorology forecast system of the Danjiangkou Basins in Hanjiang applies high spatial and temporal resolution rainfall data in hydrological model to carry out the real-time hydrometeorology forecast. Adopting the browser/client/server (B/C/S) three-layer structure, the rainfall monitoring, radar quantitative precipitation estimation, numerical forecast precipitation, flood forecast, hydrology and other product information are processed on client/server (C/S) system, and then the products can be displayed on the browser side. GIS technology is used to define the basin boundary and extract the river system based on the DEM data, and then to define the place and water in basin, to complete the digital work of basin basic information. Second, precipitation information, basin actual observation, radar estimation, model forecast precipitation products are processed with some clipping algorithm and basin geography information, and input into the hydrological model. Third, to construct basin hydrological forecast model based on basin geography climate characteristics, the Xinanjiang Hydrological Model is adopted to make the real time flood forecast, and the data files are stored in specified directory for database calling. Finally, the Asp.Net (C#) 4.0 is adopted to develop system display platform, including the display for basin overview, graphics products of basin actual monitoring, radar QPE, model QPF, hydrological forecast and monitor products. The completed system platform can achieve the hydrological meteorological information monitoring and forecasting. During the two flood processes in July of 2010 and September of 2011, the precipitation observed and forecasted is given and displayed timely and accurately, the flood process curve is also forecasted accurately. Nowadays, the system has been successfully transplanted to the Three Gorges, Qingjiang Shuibuya Reservoir, Huaihe Wangjiaba, the Zhanghe Basins, and has carried out flood tests and services, achieving good effects.

Model and Generation of Weather Forecast Analytic Data

Tan Xiaoguang, Luo Bing

2014, 25(1): 120-128.

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Abstract:
To solve the problem of "information exploration" in operational weather forecast, building a data warehouse to help forecaster's analysis is necessary. The key and most valuable idea is to change raw data to analytic data, include extracting useful data, making data clean, and aggregating data to rough granularity data. Usually the meteorological data got in operational weather forecast is processed, clean and canonical. So the main process is "aggregation" to concentrate the weather information to fewer data which have clear physical meaning.A conceptual model of weather analytic data is suggested with a pentagon tuple considering the spatial, transitional, physical and multi-scale natures of meteorological data. The pentagon tuple refers to ID (identification), SA (spatial attributes), EA (entity attributes), TA (time attributes) and PA (physical attributes), including several detailed attributes set each. Although meteorological data is field data, forecasters usually use spatial object data to analyze the weather systems. So the main work of changing raw data to analytic data is identifying spatial objects from field data.Four aggregations arithmetics to change raw data to analytic data are suggested: Statistics for fixed region, statistics for given spatial or temporal partitions, identification of basic weather systems and identification of weather conceptual models. The former two are relatively simple statistics, while the latter two are complex for mutative spatial object and they are discussed in detail.Basic weather systems include region of high/low, center of high/low and trough/ridge in a data field. A filtering-dividing-measuring arithmetic is suggested. Filtered with a Mexican-hat function, the trough/ridge become high/low region and easier to identify, and then the high/low region are divided from the filtered field, with some arithmetics adopted to tread with multi-scale problems of meteorological field. At last the divided regions are measured to get area, extreme value, length, width, aspect ratio (width/length), geometry center, extreme data location, points of central line, including all attributes of SA, EA, TA and PA. If the aspect ratio is smaller than a threshold, the region will be identified as a trough or ridge, and the central line is the trough or ridge line.A knowledge base system with spatial fuzzy production rule is suggested for identifying weather conceptual models (e.g., cold front), and the rational process of this rule is described. 4 topological relations, several order relations, measure relations and their subjection functions are suggested. The conclusion of the rules is expanded to spatial objects with a result-spatial-object.

Vol.25, NO.1, 2014