基于GIS的闪电数据可视化监测与统计分析系统

基于ArcEngine开发平台,结合大型网络数据库sqlServer2005,设计并实现了基于GIS的闪电数据可视化监测与统计分析系统.有效地将闪电数据与GIS平台进行无缝对接,实现其相关数据管理、查询以及时空统计分析等功能,为气象部门进行有效的雷电灾害监测,更好地掌握雷电发生的规律提供有利的可视化平台,同时也为GIS与气象专业领域的结合进行了有益的探索.     

A statistical analysis of sea temperature data

The paper analyzes sea temperature series measured at two geographical locations along the coast of Norway. We address the question whether the series are stable over the sample period 1936–2012 and whether we can measure any signal of climate change in the regional data. We use nonstandard supF, OLS-based CUSUM, RE, and Chow tests in combination with the Bai-Perron’s structural break test to identify potential changes in the temperature. The augmented Dickey-Fuller, the KPSS, and the nonparametric Phillips-Perron tests are in addition applied in the evaluation of the stochastic properties of the series. The analysis indicates that both series undergo similar structural instabilities in the form of small shifts in the temperature level. The temperature at Lista (58° 06′ N, 06° 38′ E) shifts downward about 1962 while the Skrova series (68° 12′ N, 14° 10′ E) shifts to a lower level about 1977. Both series shift upward about 1987, and after a period of increasing temperature, both series start leveling off about the turn of the millennium. The series have no significant stochastic or deterministic trend. The analysis indicates that the mean temperature has moved upward in decadal, small steps since the 1980s. The result is in accordance with recent analyses of sea temperatures in the North Atlantic. The findings are also related to the so-called hiatus phenomenon where natural variation in climate can mask global warming processes. The paper contributes to the discussion of applying objective methods in measuring climate change.     

Ice phenomena terms on the water bodies of Northwestern Russia

The dependence of ice phenomena (the dates of ice freeze-up and break-up) on the air temperature and geographic factors (geographic latitude, height above sea level, and average depth and area of lakes) is investigated on the basis of the data of long-term observations on the water bodies of Northwestern Russia. The regression models with rather high accuracy level are proposed not requiring a large number of input parameters unlike the deterministic models.     

The Influence of Vegetation Cover on Summer Precipitation in China： a Statistical Analysis of NDVI and Climate Data

This study provides new evidence for the feedback effects of vegetation cover on summer precipitation in different regions of China by calculating immediate (same season), and one-and two-season lagged correlations between the normalized difference vegetation index (NDVI) and summer precipitation. The results show that the correlation coefficients between NDVI in spring and the previous winter and precipitation in summer are positive in most regions of China, and they show significant difference between regions. The stronger one-and two-season lagged correlations occur in the eastern arid/semi-arid region, Central China,and Southwest China out of the eight climatic regions of China, and this implies that vegetation cover change has more sensitive feedback effects on summer precipitation in the three regions. The three regions are defined as sensitive regions. Spatial analyses of correlations between spring NDVI averaged over each sensitive region and summer precipitation of 160 stations suggest that the vegetation cover strongly affects summer precipitation not only over the sensitive region itself but also over other regions, especially the downstream region.     

A statistical analysis of air pollution data in terms of meteorological conditions

The air pollution in the planetary boundary layer (PBL) at a height of about 1 km is considered. Assuming stationarity and horizontal homogeneity of the underlying surface, the turbulent state in the PBL is completely determined by the following external parameters: the Rossby number, one parameter for thermal stratification and two for baroclinicity. The turbulent state in the PBL under the same conditions is also determined completely by the following internal parameters: one for thermal stratification and two for baroclinicity. If the internal or external parameters completely determine the PBL turbulent state, then they should completely determine the diffusion processes in it. That is why for the analysis of pollution data, it is recommended that these representative meteorological parameters should be used rather than selected ones. The external parameters which may be obtained from synoptic data have a definite advantage for statistical processing of air pollution data. This is clearly of importance for forecasting. On the other hand, the connection between pollution and the internal parameters is comparatively well-studied theoretically. That is why for the prediction of pollution, it is necessary to know the dependence between the internal and external parameters, as given by the resistance law. An example of statistical processing of air pollution data in the PBL is treated in terms of the external parameters. In addition, an example is given of a theoretical prediction of pollution using synoptic data.     

A statistical power analysis of woody carbon flux from forest inventory data

At a national scale, the carbon (C) balance of numerous forest ecosystem C pools can be monitored using a stock change approach based on national forest inventory data. Given the potential influence of disturbance events and/or climate change processes, the statistical detection of changes in forest C stocks is paramount to maintaining the net sequestration status of these stocks. To inform the monitoring of forest C balances across large areas, a power analysis of a forest inventory of live/dead standing trees and downed dead wood C stocks (and components thereof) was performed in states of the Great Lakes region, U.S. Using data from the Forest Inventory and Analysis (FIA) program of the U.S. Forest Service, it was found that a decrease in downed wood C stocks (?1.87 Mg/ha) was nearly offset by an increase in standing C stocks (1.77 Mg/ha) across the study region over a 5-year period. Carbon stock change estimates for downed dead wood and standing pools were statistically different from zero (α?=?0.10), while the net change in total woody C (?0.10 Mg/ha) was not statistically different from zero. To obtain a statistical power to detect change of 0.80 (α?=?0.10), standing live C stocks must change by at least 0.7 %. Similarly, standing dead C stocks would need to change by 3.8 %; while downed dead C stocks require a change of 6.9 %. While the U.S.’s current forest inventory design and sample intensity may not be able to statistically detect slight changes (<1 %) in forest woody C stocks at sub-national scales, large disturbance events (>3 % stock change) would almost surely be detected. Understanding these relationships among change detection thresholds, sampling effort, and Type I (α) error rates allows analysts to evaluate the efficacy of forest inventory data for C pool change detection at various spatial scales and levels of risk for drawing erroneous conclusions.     

Reconstruction of hydrometeorological time series and its uncertainties for the Kaidu River Basin using multiple data sources

This paper tried to reconstruct the time series (TS) of monthly average temperature (MAT), monthly accumulated precipitation (MAP), and monthly accumulated runoff (MAR) during 1901–1960 in the Kaidu River Basin using the Delta method and the three-layered feed forward neural network with backpropagation algorithm (TLBP-FFNN) model. Uncertainties in the reconstruction of hydrometeorological parameters were also discussed. Available monthly observed hydrometeorological data covering the period 1961–2000 from the Kaidu River Basin, the monthly observed meteorological data from three stations in Central Asia, monthly grid climatic data from the Climatic Research Unit (CRU), and Coupled Model Intercomparison Project Phase 3 (CMIP3) dataset covering the period 1901–2000 were used for the reconstruction. It was found that the Delta method performed very well for calibrated and verified MAT in the Kaidu River Basin based on the monthly observed meteorological data from Central Asia, the monthly grid climatic data from CRU, and the CMIP3 dataset from 1961 to 2000. Although calibration and verification of MAP did not perform as well as MAT, MAP at Bayinbuluke station, an alpine meteorological station, showed a satisfactory result based on the data from CRU and CMIP3, indicating that the Delta method can be applied to reconstruct MAT in the Kaidu River Basin on the basis of the selected three data sources and MAP in the mountain area based on CRU and CMIP3. MAR at Dashankou station, a hydrological gauge station on the verge of the Tianshan Mountains, from 1961 to 2000 was well calibrated and verified using the TLBP-FFNN model with structure (8,1,1) by taking MAT and MAP of four meteorological stations from observation; CRU and CMIP3 data, respectively, as inputs; and the model was expanded to reconstruct TS during 1901–1960. While the characteristics of annual periodicity were depicted well by the TS of MAT, MAP, and MAR reconstructed over the target stations during the period 1901–1960, different high frequency signals were captured also. The annual average temperature (AAT) show a significant increasing trend during the 20th century, but annual accumulated precipitation (AAP) and annual accumulated runoff (AAR) do not. Although some uncertainties exist in the hydrometeorological reconstruction, this work should provide a viable reference for studying long-term change of climate and water resources as well as risk assessment of flood and drought in the Kaidu River Basin, a region of fast economic development.     

Statistical analysis of hydrometeorological characteristics in extreme winters in the northeastern part of the Black Sea

Analyzed are the similarities and differences in the processes of intraseasonal variability of wind conditions in extremely cold and extremely warm real winter seasons 1953/54 and 1965/66. Revealed is the significance of the contribution of calm pauses to the formation mechanism of seasonal characteristics on the whole and, to much greater degree, to the determination of the properties of weather windows. Emphasized is a role of calm pauses as the indicators of weather windows. Studies is the possibility of estimating the severity of winter conditions using a set o characteristics of initial ten-day periods of winter season within the arbitrary annual cycle.     

Further results of the analysis of central England temperature data

Summary Central England temperature data for 1659–1986 are analysed using a new procedure for separating the trend from monthly mean temperatures. The method has been developed without any important assumption relating to the trend function. The monthly trends are illustrated. It is suggested that a general warming tendency underlies various cooling and warming periods. Several autoregressive-moving average (ARMA) processes have been fitted to the stationarized time series of which an ARMA (2, 1) process proved to be the most appropriate model. Calculations on the data after adjustment to remove non-linear trends show much lower autocorrelations of yearly and individual monthly mean temperatures than estimated before.

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Zusammenfassung In vorliegender Studie werden Temperaturdaten von Mittelengland des Zeitraums 1659 bis 1986 unter Zuhilfenahme eines neuen Verfahrens zur Trennung von Trend und Monatsmittel analysiert. Die Methode wurde ohne besondere Annahme für die Temperaturtrendfunktion entwickelt. Die Monatstrends werden illustriert. Daraus ergibt sich eine allgemeine Tendenz der Erwärmung, der Perioden der Abkühlung und der Erwärmung überlagert sind. Verschiedene Verfahren mit autoregressiven gleitenden Mitteln (ARMA) wurden an die stationären Zeitserien angepaßt, wobei sich ein bestimmter ARMA-Prozeß (2, 1) als besonders geeignet erwies. Nach einer Anpassung durch Entfernung der nichtlinearen Trends ergaben die Berechnungen weit niedrigere Autokorrelationen der jährlichen und monatlichen Temperaturmittelwerte als bislang angenommen.

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With 6 Figures     

Estimation and medium-term forecasting of anthropogenic carbon dioxide and methane emission in Russia with statistical methods

A statistical method of estimation and medium-term forecasting of greenhouse gas emission is under consideration. It is shown that availability of significant enough and stable statistical relationships between greenhouse gas emission and a number of indicators of the economy development allows operational estimating and forecasting of greenhouse gas emission in the Russian economy with a lead-time out to several years. It is possible to estimate and forecast both the total emission of all greenhouse gasses in terms of CO₂-equivalent and emission of particular greenhouse gases in different sectors of economy. Both miacroeconomic and industrial indicators of the economy development can be used as predictors for building regression forecasting models.     

探空资料云检测及其统计研究

基于已知的云垂直结构判断的方法,将相对湿度阈值法与温度露点法相结合,并加以改进,得到更加科学有效的云垂直结构判断方法。利用南京地区探空站的探空资料数据,分析得到了该地区的云垂直结构参数,并对全年云垂直结构特征进行了统计分析。经过统计分析发现:这种改进的相对湿度阈值法是科学有效的;南京地区夏秋季节有云的概率大,多层云的状况较多;春冬季节有云的概率相对较小,单层云的状况较多;云层厚度呈现出"夏厚冬薄"、中低云厚而高云薄的规律。     

Environmental research and provision of hydrometeorological safety in high-latitude and polar regions

The information is presented on the activity of Roshydromet in high-latitude and polar regions for providing the hydrometeorological safety of population and economy in the Arctic and presence in Antarctica as well as on its development and modernization since the 2000s and on the contribution of Roshydromet to Russian studi es and works in the framework of the International Polar Year 2007–2008.     

Complex studies of hydrometeorological and ice conditions on the northwestern shelf of the Caspian Sea based on satellite and expedition observational data and model calculations

In accordance with the contract of the LUKOIL Oil Company, a cooperation of the Roshydromet organizations (Planeta Research Center for Space Hydrometeorology, a main contractor, Hydrometeorological Research Center of the Russian Federation, Arctic and Antarctic Research Institute, and State Oceanographic Institute) carried out in 2008 complex studies of the hydrometeorological and ice conditions for the Filanovskii oil- and gas-field facility construction on the northwestern shelf of the Caspian Sea. Three expeditions were organized and conducted within that project: a helicopter ice research expedition (specialists from the Arctic and Antarctic Research Institute carried out a huge volume of measurements of physicomechanic properties of level, rafted and hummocked ice, and morphometric characteristics of ice piling, hummocks, and stamukhas); specialists from the State Oceanographic Institute organized a ship expedition on studying sea ground exaration formed due to impacts of ice formations (hummocks and stamukhas) using hydro-radar and echo-sounder surveys as well as a complex hydrometeorological and hydrochemical expedition with five autonomous buoy stations mounted in two months. From the moment of ice formation to the end of the expedition activity, an operational space monitoring of the northwestern Caspian Sea was carried out at the Planeta Research Center for Space Hydrometeorology. Based on the NOAA, TERRA, and AQUA satellite data, corrected and geographically fixed satellite images of the area of activity were issued with a periodicity of 6 times per day; index maps on the ice situation (twice a week) and ice situation forecasts (lead-time of 1–7 days). Besides, long-term series of satellite data on the northwestern Caspian Sea are collected and processed: their results are used for estimating seasonal and interannual variability of the drift ice and fast ice. Specialists of the Hydrometeorological Research Center of the Russian Federation completed the work on processing and analysis of library materials, research/technical reports, handbooks, expedition observational data, and on hydrodynamic and probability modeling of long-term series of hydrological, meteorological, and partly ice data. In particular, basic characteristics of the hydrological regime (sea level, currents, and waving) are calculated for the place of the oil platform location and along the pipeline routing. Tentative local specifications on the hydrometeorological regime in the Filanovskii field are worked out based on the results of the work performed.     

吉林省大暴雨的统计分析

通过资料的统计分析,证明吉林省大范围大暴雨和局地大暴雨之间存在着明显的差异.大范围大暴雨不仅暴雨区面积大、水汽充沛、整层湿润、含有较大的内能,而且几乎都是由台风造成的——至少影响吉林省面积最大的九次大暴雨都如此.大范围大暴雨与环境场密切相关,而局地大暴雨与东亚环流关系不大.经过计算得到大范围大暴雨所需水汽,仅靠影响系统是不够的,它需要有大量源源不断水汽的补充,而局地大暴雨则所需水汽依靠影响系统已足足有余.     

雷雨大风与河北电网灾害特征分析

根据灾情观测资料、重要天气报告资料,从多角度对京津冀地区雷暴大风进行了统计分析,结合MICAPS资料、NCEP资料、自动站资料以及多普勒天气雷达资料,讨论了雷暴大风形成的天气条件、类型和风暴特征,结果表明：雷暴大风主要分布在北京西北部山区、沿海地区以及西北部高原,平原相对较少,近30 a演变趋势为振荡减少。雷暴大风最早始于3月中旬,最晚终于11月上旬,6月下旬达到顶峰,6、7月份为最多月份,14—20时为日高峰期。雷暴大风的旬、月分布与冷空气活动、南支急流的位置有关;雷暴大风的形成,5、9月份需要更高的热力条件和动力条件,6、7、8月份需要更高的不稳定条件和能量条件;西北气流型和低涡型是产生雷暴大风日数最多的天气类型。各类型天气系统的月分布与冷空气活动、副热带高压位置以及南支急流的强度、位置有关;雷暴大风的范围与影响系统的尺度和强度有关,冷锋和低涡出现区域性雷暴大风天气的几率最高,且级别越高,冷锋的优势越明显;雷暴大风过程多单体风暴最多,飑线次之。雷暴大风的范围与风暴的强弱有关,飑线、超级单体风暴是出现区域性雷暴大风几率最高的对流风暴,且级别越高,飑线的优势越明显。

     

The Effects of Climate on Welfare and Well-Being in Russia

This paper measures the concepts of welfare and well-being in Russia on the basis of two large Russian household surveys, carried out in 1993 and 1994. Welfare refers to satisfaction with income and well-being refers to satisfaction with life as a whole. This paper investigates how climate conditions in various parts of Russia affect the cost of living and well-being. Climate equivalence scales have been constructed for both welfare and well-being.     

金城江暴雨洪涝统计特征分析及防御措施

统计分析金城江暴雨洪涝分布特征,提出防御措施。     

Medium-range forecast of air temperature and of some dangerous phenomena using the technique of the hydrometcenter of Russia

The improved forecasting technique is presented of weather element computation developed at the Hydrometcenter of Russia for the medium-range forecasting on the basis of statistical interpretation of the results of integration of hydrodynamic atmospheric models. The methodology of numerical forecasting algorithms is described. The methods of forecasting the air temperature for ten-day periods and the extreme air temperature detailed for every day for the territory of Russia are realized on the basis of the weather element computation technique. According to the resolution of the Central Methodical Committee for Hydrometeorological and Heliogeophysical Forecasts, these methods are introduced into the operational practice as the basic ones. The examples of forecasts and the data on their accuracy are given. The approach is developed to the solution of the problem of the dangerous phenomena forecast (of anomalously cold and anomalously hot weather) with the earliness of 48–96 h within the frameworks of this technique.