Vol.21, NO.5, 2010

Display Method:
Development of Mesoscale Ensemble Prediction System at National Meteorological Center
Deng Guo, Gong Jiandong, Deng Liantang, Chen Jing, Cui Yingjie, Hu Jiangkai, Wang Xiaocong, Li Yinglin, Li Li
2010, 21(5): 513-523.
Abstract:
To improve short-range weather forecast predictability of high impact weather process, a set of national-level mesoscale ensemble prediction system (MEPS) is developed at National Meteorological Center (NMC). The theory to set up an ensemble prediction system lies in the following facts: There are no perfect forecast models, and atmosphere is a chaotic dynamical system, so any small error in the initial condition will lead to growing errors in the forecast, eventually leading to a total loss of any predictive information. The MEPS at NMC takes advantage of achievements at high resolution deterministic mesoscale prediction model, data assimilation system as well as experience from development of global ensemble prediction system. The error growth features for mesoscale model forecast within China area is explored and it is found that most of the convective-scale weather system develops in weak baroclinic environment and the quick growth errors resulted from baroclinic instability. Considering characteristics of the circulation regime, season and geographical domain, the initial perturbation technique of breeding method is adopted to perturb the initial fields. Furthermore, to reflect uncertainties within physical process as well as systematic errors within mesoscale model, many options of microphysics, convective cumulus parameterization, boundary layer schemes, land surface process schemes and combinations in the model are tested for a certain period to evaluate the performance of different schemes. The experiment indicates that physical process perturbation has equal or even greater impacts on spread of ensemble prediction comparing with initial condition perturbation. Therefore, assembling of different microphysics schemes, cumulus parameterization, and planetary boundary layer processes is applied to build a multi-initial condition, multi physics ensemble system. The initial conditions and lateral boundary conditions are obtained from global ensemble system at NMC and trickily rescaled during model integration process. To reduce systematic bias in ensemble forecasts, an adaptive Kalman Filtering algorithm is applied as bias correction method and the results is inspiring. Ensemble forecast products include ensemble averages, spread and probability of multiple elements (wind, temperature, humidity, geopotential height, rainfall, etc.) in multiple layers are produced and performance of the ensemble system is evaluated. To evaluate the performance of NMC's regional mesoscale ensemble prediction system, different ensemble verification methods is used to estimate and compare 6 mesoscale ensemble prediction systems within a common forecasting configuration during the WMO/WWRP Beijing 2008 Olympics Mesoscale Ensemble Research and Development Project. Results indicate that the overall predictability of mesoscale ensemble prediction system at NMC is overall comparable to the international participants. The MEPS is still not good enough for fixed site and time-specific forecasts, but it demonstrates good ability to capture the high impact weather event and will play a role in everyday forecast.
Verification of GRAPES_Meso V3.0 Model Forecast Results
Wang Yu, Li Li.
2010, 21(5): 524-534.
Abstract:
The rainfall, temperature, height and wind forecast products of GRAPES_Meso model (V3.0), which is mesoscale model of the new generation multiple time scale numerical weather prediction system, are verified by operational statistical verification methods from March 2008 to February 2009. Dichotomous and continuous forecast verification methods for deterministic forecast model recommended by World Meteorological Organization or Chinese Meteorological Administration are employed. The verification results show the rainfall forecast of V3.0 model is better than V2.5 model. The annual mean TS of rainfall forecast is improved for all five grades and is higher than that of V2.5 model clearly for four seasons mean, all months mean of a year, except for 48-hour moderate rain and storm rain of autumn and winter. The forecasted rainfall of V3.0 model is mainly greater than observed rainfall, especially for moderate to heavy rain. The simulated distribution of the season mean raining rate is much more similar to the observed patterns. For the 24-hour forecast of eastern China in autumn and winter, rainfall is almost no longer underestimated. The forecast performance of location and intensity of strong rainfall center for spring and summer has also been improved, but the amount of 48-hour rainfall is obviously overestimated comparing to observation, shown clearly through the figures of daily mean rain rate time series. Meanwhile, the developing trend and intensity forecast of strong rainfall processes is better than that of V2.5 model for most time of the year. The height, temperature and wind forecasts of the upper prognostic forecast have made remarkable progresses especially for 500 hPa height forecast, 500 hPa wind forecast, and 48 hour 850 hPa wind forecast. However, the forecast of 24-hour low level temperature and height in summer are hardly improved, so the model still need more progresses especially in rainy season. For other seasons, the forecast of temperature and wind in low level atmosphere is fairly good.
Applying Scale Decomposition Method to Verification of Quantitative Precipitation Nowcasts
Kong Rong, Wang Jianjie, Liang Feng, Zhao Wenfang
2010, 21(5): 535-544.
Abstract:
Verification of quantitative precipitation forecast has always been a challenge due to the high discontinuity of rainfall in spatial and temporal scales. Conventional methods (TS and MSE score, etc.) cannot meet the need for verification of high resolution (1—2 km) forecasts. In recent years, several new spatial verification approaches which can give more information about the complex spatial structure of forecast field have been developed, such as the intensity-scale verification method, the feather based (or object-oriented) verification method, neighborhood (or fuzzy) verification method and field deformation approaches etc. The attempt to use the intensity scale technique is introduced by Casati et al. to assess radar based 1 hour quantitative precipitation forecasts for 4 different nowcasting systems (BJANC, GRAPES SWIFT, STEPS, and CARDS) which attended the World Weather Research Program for the Beijing 2008 Olympic Games (WWRP B08FDP). The intensity-scale verification approach accounts for the spatial structure of the forecast field and allows the skill score to be diagnosed as a function of the spatial scale of the forecast error and intensity of the precipitation events. Different precipitation types (convective, stratiform and mixed type) during B08FDP demo period are selected to get representative results, it shows that these nowcasting systems exhibit forecasting skills only when the precipitation system is above 32 km spatial scale and last longer than 1 hour despite the using of most advanced systems in the world with the high resolution of 1 to 2 km. For spatial scale lower than that, the forecasting ability is very limited, which indicates that product performance characterized at different spatial scale should be considered in the applying of nowcasting products. When analyzing the forecasting errors with different spatial and temporal scales, it's found that more than 60% and more than 85% of the forecasting error come from spatial scales smaller than 8 km and time scales smaller than 1 hour respectively. Improvements in smaller scales precipitation forecasts are important. Most nowcasting systems explore the linear extrapolation technique to make 0 to 2 hours nowcasts, yet the valid extrapolation time is very limited, especially for smaller scale (less than 1 hour) convective systems, which is mainly caused by the nonlinear development of the convections. Therefore, more information about the circulation which has close relation to the movement and development of the storm should be considered. So far, the most popular way is to blend the radar based extrapolation with the dense observations and numerical model based potential forecast.
Comparison of Propagating Boreal Summer Intraseasonal Oscillation over Tropics Represented by Wind and Convection Fields
Lin Ailan, Li Tim, Li Chunhui
2010, 21(5): 545-557.
Abstract:
Finite-domain wavenumber-frequency analysis and components analysis are applied to analyze the spectrum climatology and inter annual anomaly of diversified propagating boreal summer intra-seasonal oscillation (BSISO) over tropics denoted by tropospheric wind field and convection field, based on the daily outgoing longwave radiation (OLR) data and the second set reanalysis data of NCEP/DOE (daily mean is obtained from 4 times observation). It shows that differences of BSISO climatology and inter-annual anomaly characteristics exist among different elements. Low level wind (850 hPa zonal wind or meridional wind) is more consistent with convection generally. Zonal (Meridional) propagating BSISO climatology characteristics denoted by 850 hPa meridional (zonal) wind is the most similar to those of convection. During the ENSO developing year, the enhanced tendency of eastward propagating mode at the equator reflected by 850 hPa meridional wind is more consistent with convection; the changing tendency of northward propagating mode reflected by both of 850 hPa meridional wind and zonal wind is similar to convection. The weakened tendency of northward propagating mode over eastern Indian Ocean reflected by 850 hPa zonal wind is more significant. During the ENSO decaying year, the weakened tendency of eastward (westward) propagating mode at the equator (off the equator) reflected by 850 hPa zonal (meridional) wind is more consistent with convection; 4 elements (convection, 850 hPa meridional wind, 200 hPa zonal wind and 200 hPa meridional wind) can exhibit the characteristic that the northward propagation over South China Sea and its border is suppressed, i.e., this characteristic is resulted from the combination of atmospheric anomaly between upper and low troposphere. The relationship between eastward propagation of BSISO at the equator and BWA mode of Indian Ocean is only presented by convection, and the other 4 elements of wind filed cannot reflect it. Both of convection and 850 hPa zonal wind can reflect the relationship between northward propagation and the Indian Ocean dipole mode. The northward propagation of BSISO over middle and eastern Indian Ocean and South China Sea weakened (enhanced) under positive (negative) dipole mode. The conclusions above indicate that different results would be obtained from different meteorological elements. This is one of the possible causes that the results are not consistent in the past. For different conditions, proper element should be selected for analyzing tropical BSISO. For example, from the view of the forecasting of regional weather and climate, element which indicates the forecasting area well can be chosen based on diagnoses of the remote relationship between weather in forecasting region and the activity of tropical BSISO.
The Assimilation Results of Ocean Temperature and Salinity Data from GTS in BCC_GODAS 2.0
Liu Xiangwen, Li Weijing, Wu Tongwen, Xiao Xianjun
2010, 21(5): 558-569.
Abstract:
Ocean temperature and salinity observations data from GTS (Global Telecommunication System) are assimilated in second generation global ocean data assimilation system of Beijing Climate Center (BCC_GODAS 2.0) and the results are analyzed. First, the comparison with SODA (Simple Ocean Data Assimilation) reveals the vertical distribution features of root mean square error (RMSE) of global temperature and salinity in model and assimilation system. The analysis shows that, for the RMSE of temperature with assimilation, compared with the results without assimilation, it has a slight decline with a range of 0—0.3 ℃ in the sea surface layer, and an obvious descent with a range of 0.1—0.7 ℃ in depth from about 100 m to deep layer, but has no obvious variation in depth from the middle and lower mixed layer to about 100 m. For the RMSE of salinity after assimilation, it has a descent with a range of 0—0.2 psu in depth from ocean surface to deep layer. Second, further comparison is made for some vertical cross sections, including the zonal cross section along equator, the meridional cross section along 165°E in Pacific Ocean, the meridional cross section along 30°W in Atlantic Ocean, the longitudinal cross section along 90°E in Indian Ocean. The results show that, generally speaking, the GTS data assimilation improves the temperature and salinity simulation in many aspects including the extension and central intensity of warm sector in mixed layer, the depth of temperature ridge and trough in thermocline, the temperature gradient near thermocline, the extension and central intensity of high and low salinity sector, and so on. Moreover, the further comparison with some ARGO (Array for Real time Geostrophic Oceanography) observation indicates that, in most cases, the RMSE of temperature and salinity profiles has an obvious descent after assimilation, leading to more accurate vertical distribution features of temperature and salinity simulations. For selected single point profiles in different ocean areas in January, after assimilation, the RMSE of temperature and salinity decrease by 0.49 ℃ and 0.19 psu, respectively; for selected profiles in July, the descent of RMSE of temperature and salinity is 0.87 ℃ and 0.18 psu, respectively. The comparison with TAO (Tropical Atmosphere Ocean) data also shows that the assimilation can improve the temperature and salinity features to a certain extent. The BCC_GODAS 2.0 has superiority in some degree in ocean data assimilation, however, there is still some deficiency, and the assimilation effect is not very good in some areas or periods, which may be induced by lack of observations, uncertainties of the data, the imperfection of assimilation system, as well as the simulation capability of model, and so on.
Characteristics of Environment Flow Related to Intensity Change of Landing Tropical Cyclones Towards the Yellow Sea and the Bohai Sea
Guo Lixia, Chen Lianshou, Li Ying
2010, 21(5): 570-579.
Abstract:
To study the intensity changing patterns and the large scale environmental flow characteristics of landing tropical cyclones moving out to Yellow Sea and Bohai Sea (ab. YBTC), based on 1949—2006 typhoon data and NCEP object reanalysis data every 6 hours, the intensity change of YBTCs is statistically analyzed. The annual YBTC number is 0.9, and the reinforced ratio is 49% when moving into the sea. The maximum value and the largest variation of reinforcement occur in September. The reinforcement ratio of YBTC which land at Fujian Province is higher. The number of reinforced YBTC in 1970s and in 1990s is smaller, and then it increases. The reinforcement is stronger than the attenuation according to Vmax, and the reinforcement is equivalent to the attenuation according to Pmin, but they are not synchronous. The reinforcement maintains till it enters sea or 6 hours later at most, but Vmax doesn't weaken much. 5 cases of reinforced YBTCs and another 5 cases of weakened YBTCs are analyzed and compared using large scale circulation composed diagnostic method. It's found that middle latitude trough occurs in both type of cases, but the intensity and collocation are different. The trough of reinforced YBTC cases is stronger and coupled with YBTC when entering the sea. Strong high level trough brings strong vortices advection and warm advection, and then YBTC gets baraclinic energy thereby develops. In the other type of cases, trough is from west to YBTC with no coupled frontal zone, and north to YBTC is weak ridge. The subtropical high of the former type is massive with the guide flow mainly from southerly wind, facilitating interaction with middle latitude trough. While for the later type, subtropical high is strong and extend westward, blocking the interaction with middle latitude trough. YBTC of the former type moves rapidly to right side of high level jet when entering the sea. But for weakened YBTCs the high level jet is weaker. On low levels, there are southwest yet, but for the reinforced YBTCs, there is also stronger northerly flow which accelerates baraclinic developing in the west of TC. In the first type of cases, there is much stronger moist baraclinity and steep θse, which are favorable for vortices to develop. The impairing function to the intensity of YBTC of the strong speed vertical sheer is not remarkable, but the speed vertical sheer of the former type is stronger than the latter type of YBTCs.
Simulating Future Climate Changes over North China with a High Resolution Regional Climate Model
Shi Ying, Gao Xuejie, Wu Jia, Giorgi F
2010, 21(5): 580-589.
Abstract:
Multi decadal climate change simulations have been performed over China using 20 km horizontal resolution regional climate model (RegCM3) one way nested within a global model (FvGCM/CCM3, here in after called FvGCM) from NCAR/NASA. Two experiments are conducted, one for the period of 1961—1990, the other is for the future climate of 2071—2100 under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 emission scenario. The analysis focuses on the warm half of the year, from April to September. First, simulations of present climate conditions over North China by FvGCM and RegCM3 are compared with observations to assess the model performance. Results show that both models can reproduce the observed spatial patterns of surface air temperature and precipitation. Compared with FvGCM, RegCM3 shows a better performance especially in providing more spatial details of the surface variables. The changes (differences between future and present) of mean temperature and precipitation are analyzed and compared between the two models simulations. Significant warming in the end of 21st century is predicted by both models however their results are different both in spatial distribution and amount. Compared with FvGCM, a greater warming is simulated by RegCM3 in some areas of the northern part while in the southeast and the east of the region RegCM3 indicates the warming is slighter. General increase in mean precipitation is found in FvGCM simulation, in a range of less than 10% to exceeding 30%. While for RegCM3, the simulated precipitation increases in the north of Henan as well as Shandong, but changes little or even decreases in the northern part of the region is simulated. Future changes in extreme heat events simulated by RegCM3 are statistically analyzed using the days with daily maximum temperature no less than 35 ℃(DT35) and the days with a heat index which includes the humidity factor also no less than 35 ℃(DHI35). Results show a substantial increase of DT35 over the whole region and increase of DHI35over the plain areas. Increase in the maximum number of consecutive dry days (CDD) is also simulated by the model over the region, especially in the north of Hebei Province. According to the classification of UNEP drought index (AU), there will be significant less humid area and a corresponding increase of dry sub humid and semi arid, indicating the future increase of drought extent in the future over the region.
Variation Characteristics and Causes of the Flood and Drought in the Three Gorges Area in Summer
Liu Xiaoran, Cheng Bingyan, Li Guoping
2010, 21(5): 590-597.
Abstract:
The Three Gorges area is located in the East Asian monsoon region. Under the influence of the monsoon activity, the precipitation of the Three Gorges area mainly concentrates on the period from June to August with relatively high variability, which is prone to the occurrence of the flood and drought disaster. The flood and drought of the Three Gorges area not only has a great impact on the lives of local residents and social activities, but also directly determines the operation and power generation efficiency of the Three Gorges Hydropower complex Project. As a result, the study of the variation characteristics and the formation of the flood and drought of the Three Gorges area is of great significance, providing a scientific decision base to prevent the disaster of flood and drought.
The temporal evolution of the drought and flood of the Three Gorges area in summer and its circulation patterns in the anomalous years are analyzed, obtaining a consistent result. The droughts occur frequently in the Three Gorges area in summer from 1951 to 1978. Following, there is a decadal abrupt change from the droughts to the floods in 1979. Then the floods are popular in the Three Gorges area from 1979 to 2000. Severe droughts take place frequently in the Three Gorges area after 2001. The circulation patterns are obviously different between in severe flood years and in severe drought years of the Three Gorges area. As for the severe flood years of the Three Gorges area, the South Asia High strengthens in 100 hPa, and there is a "-+-" wave train from the west to the east of the Eurasia high latitude area in 500 hPa height anomaly, which reflects that there are continuing block highs in the Okhotsk and Ural regions. Furthermore, the weaker convections over the Western Pacific Warm Pool make the West Pacific Subtropical High to shift southward. In addition, there is strengthening southwest water vapor transport from the Three Gorges area to the Indo China peninsula, which enhances the water vapor convergence in the Three Gorges area. These circulation patterns are advantageous to the genesis of the floods in the Three Gorges area.
Calibration Method of Echo Intensity of Wind Profile Radar
Zhong Liujun, Ruan Zheng, Ge Runsheng, Chen Zhongrong, Ren Jingwei, Shen Xianglin, Zhang Zhe, Wei Yanqiang
2010, 21(5): 598-605.
Abstract:
A lot of researches about wind profile radar are based on analysis of echo power. So the estimation accuracy of echo power has direct effects on the use and expansion of wind profile radar data. At present, return signal power of wind profile radar is estimated by signal to noise ratio (SNR) and radar system noise power. Environmental noise may cause errors when estimating SNR in power spectrum of wind profile radar, affecting calibration accuracy. Another viable option is quantitatively testing the receiver and signal processor respectively using the same signal source, and then the calibration curve of radar systems can be determined according to the measured signal processor linear curve. Using this method, the calibration curve of CFL 03 wind profile radar is determined, and probe data of the radar in July and August, weather radar data and surface rain gauge data are compared. The results show that the weak signal of wind profile radar can be calibrated effectively, on the basis of measurement of the coherent accumulation and pulse compression accumulation using intermediate frequency source. The method proves feasible through the actual test. And through field experiments it can be seen that calibrated echo intensity of wind profile radar and SA weather radar echo intensity are basically the same with an average error less than 2 dB, within the scope of weather radar calibration error. The errors between calibrated echo intensity of wind profile radar and ground rain gauge data is less than 2 dB, indicating that the calibration results are credible.
The Application of Clear air Echo to Early Warning of Severe Convective Weather
Wang Lirong, Bian Tao, Su Yuntao, Sun Yun, Zhang Yufeng
2010, 21(5): 606-613.
Abstract:
Using Doppler weather radar data, two methods are implemented to estimate the divergence of environmental wind field. The first method is radial velocity image qualitative identification, through which the wind divergence is qualitatively judged by calculating the difference between positive and negative radial velocity area, and the wind speed given by comparing the value of positive and negative radial velocity in the same range rings. The other is EVAD (Extended Velocity Azimuth Display) quantitative analysis, which estimates the divergence of each level in 10—50 km around radar. They are applied in the analysis of two strong convective weather processes occurred in August 2009. The relationships between clear air echo characteristics, divergence in different levels and the time of convection appearance are statistically investigated by analyzing 50 processes from May to September during 2005 to 2008. It's found that clear air echo appears within 50 km from radar center, the reflectivity are 10—20 dBZ, and the radial velocity is about±5 m/s. There are always convergences in low levels before convective weather, so it can be used as indicator of convergent environment field when consecutive five convergences appear on low level. As the altitude lowers, convergence happens ahead of convective weather much more, and on the level of 0.5 km, the forecast time of simple rainstorm can bring forward longer than that of simultaneous multiform convective weather.
Based on the results, a severe convective weather automatic warning system (SWEAWAR) is established and run on trial from June to August of 2009 except for 5 days without radar records. Among the 57 warnings, the hit ratio is 88.9% and false warnings ratio is 29.8%, the critical success index for the early warning is 64.5% and the convergence occurs 7.1 hours ahead of the convective weather on average. The SWEAWAR system seldom misses but generate quite a few false warnings too. Overall, it can help to reduce the missing report rate and improve forecast of severe convective weather.
Downscaling Methods and Application System Based on Monthly scale Dynamical Model Outputs and Forecast Skill Analysis
Qin Zhinian, Chen Lijuan, Tang Hongyu, Huang Ying
2010, 21(5): 614-620.
Abstract:
In order to solve the practical problems in short range climate prediction, an operational system has been developed for monthly scale climate prediction based on Dynamical Extended Range Forecast (DERF) model output, statistical prediction methods and downscaling techniques. The system has the following features. It provides two subjunctive methods including Perfect Prediction (PP) and Model Output Statistics (MOS) methods. The former supposes that the prediction of model is perfect enough and needn't to be modified. The downscaling model can be built on the historical observed data. The latter supposes that the prediction of model has certain bias and the downscaling model is developed using the hindcast data of model output. Predictants can be determined in two ways. One is called the single station method and predictants are determined at each station within the studied area based on the reasonable physical mechanism. The other is called the regional average method and predictants are determined based on the relationship of regional average features and predictants. Three types of high correlation centers, i.e., positive correlation centers, negative correlation centers and local correlation centers are used to determine key circulation regions which could be taken as predictants. Six downscaling methods are used to obtain predictants from key circulation regions, and seven combinations of correlation coefficients within key circulation regions are used to find optimal prediction result. The stepwise regression, optimal sub tree regression, analogous regression and minimum distance resemblance are used to develop statistic prediction models. Predicted results can be assessed after the data is updated. The output of the prediction methods provided by the system is compared with observed precipitation data at 88 stations of Guangxi in June, 2005—2008. The results of the independent samples show that the skill of the MOS method is much better than the PP method in the downscaling techniques. The best forecast method is based on the predictors which are selected from the key circulation region near the station. The Empirical Orthogonal Functions (EOF) and combined dynamical statistical prediction method are more accurate and stable than the other downscaling methods. In determining key areas which affected predictants, the regions where model output and predictants, reanalysis data and predictants are well correlated are selected. The prediction skill of the downscaling techniques is generally above 70%, which is higher than that of the conventional physical-statistical prediction.
An Integrated Bio meteorological Forecasting Method for the Occurrence Level of Locust Around the Bohai Sea of China
Yao Shuran, Guan Fulai, Li Chunqiang
2010, 21(5): 621-626.
Abstract:
Locust is an important loss causing pest around the Bohai Sea of China, and its occurrence degree is close related with weather and climate conditions. In order to study the relationship objectively, four typical locust areas around the Bohai Sea are chosen as experimental areas, which are coast, reservoir, depression shallow lake and water logging areas, respectively. Based on the observed climate and locust data from 1980 to 2008, Spearman order correlation method is used to analyze the meteorological factors affecting the occurrence degree of locust. The results show that meteorological factors have accumulated effects on locust. The temperature in July and August has a significant effect on summer locust of the next year in four locust areas, and higher temperature is more favorable for locust growth and reproduction. October is the key time for the egg life of autumn locust in three areas (reservoir, depression shallow lake and water logging areas), and sufficient rainfall is favorable for the development of locust egg, increasing the occurrence degree of summer locust in the next year. In addition, air temperature in winter and spring and rainfall affect the extent of summer locust in four areas before locust eggs hatch and come out of soil. The historical modeled accuracy are 81%—93% and 78%—89% by the Euclidean distance model modified with the weights of meteorological factors and biological model based on locust bio characteristics for predicting the locust extent, respectively. The extended forecast result of last two years is fairly accurate, i.e., one level difference for one area of the former model and one level difference for two areas of the latter model, and correct in all other areas. Then a comprehensive model is established by integrating the meteorological and biological models to forecast the locust occurrence extent and its historical modeled accuracy are 85%—96%. There is only one level difference in one area for the two years extended forecast, showing that the accuracy of integrated model is better than the single models.
The Space-time Propagation Patterns of the Stratospheric Volcanic Aerosols and the Preliminary Analysis of Their Climate Effect
Qu Weizheng, Liu Yingchen, Huang Fei, Cao Yong, Qin Ting, Bai Yan
2010, 21(5): 627-631.
Abstract:
Based on the research of the propagation patterns of the stratospheric volcanic aerosols, the space time distribution function of Volcanic Explosivity Index (VEI) with the exponential decay is constructed which can reflect the volcano eruption intensity, the relative concentration, the propagation rate of the stratospheric volcanic aerosols and the volcano eruption location. Furthermore, time series of the volcanic activity indexes (1945—2008) every 3 months at middle and high latitudes of the Northern Hemisphere, the low latitudes of the Northern and Southern Hemisphere and the middle and high latitudes of the Southern Hemisphere are built up. Based on the time series of volcanic activity indexes, the influences of the volcano activity on the surface temperature at middle and high latitudes of the Northern Hemisphere, at low latitudes of the Northern and Southern Hemisphere and at middle and high latitudes of the Southern Hemisphere, are analyzed separately. The results indicate that either at the Northern and Southern hemisphere or at the tropical zone the ground layer air temperature decreases when the volcanic activity is strong, while it increases when the volcanic activity is weak. At the same time, the variations of the ground layer air temperature lag behind those of the volcanic activity.
Design and Establishment of a Nationwide Meteorological Computational Grid
Wang Bin, Zong Xiang, Tian Hao
2010, 21(5): 632-640.
Abstract:
Weather forecast is one major application area of high performance computing technology. The running of meteorological numerical models demands strong high performance computing resource support to ensure the timeliness of numerical weather prediction systems. However, high performance computing resources and supporting capabilities are characterized by geographically contagious distribution in CMA. Local meteorological bureaus are well behind national institutions, whether in the possession of HPC resources or application development capabilities. High performance computing in meteorological field has some typical features in accordance with the requirements for grid computing, such as computational intensiveness, distributed and cooperative mass data access. Regarding the requirements of resource integration, sharing and management by local and national institutions in CMA, a design scheme of nationwide meteorological computational Grid is proposed. Grid technology is used to form abstract virtual resources on heterogeneous computing resources in meteorological department, so as to shield the heterogeneity of the underlying physical systems. Through orderly management and collaborative computing, the service platform implements effective aggregation and comprehensive utilization of resources. The design scheme employs a 3 level layout of national, regional and provincial nodes, constituting a distributed, tightly coupled network computing sharing system. The nodes are interconnected by WAN based meteorological broadband network. Upon the resource aggregation platform, function modules are intercalated for resource management, application services and user interfaces. With key technologies like UNICORE, function modules are developed and implemented. 6 geographically distributed nodes are established. UNICORE gateway services are deployed onto the meteorological broadband network, interacting with one another via grid communication protocols. 9 heterogeneous high performance computers in different places have been integrated and make up a meteorological computing resource pool. Two types of sharing services are provided, grid middleware and customized operations, on the nationwide meteorological computational Grid. By means of customized operations, three model application systems are set up. Since establishment and operational running, the meteorological computational Grid disseminates numerical weather prediction products to users in remote or resource poor areas, and thus provides strong support for disastrous weather prediction services and important events meteorological assurance, which plays an important role in local disaster prevention and mitigation efforts.