大气季节内振荡对东亚夏季风活动的影响研究

利用ERA40逐日再分析资料、NCEP/NCAR2逐日再分析资料、中国740个测站日降水资料、上海台风研究所提供的西太平洋热带气旋资料、Kaplan等重建的月平均SSTA资料、NOAA逐日长波辐射（OLR）等资料，应用离散功率谱分析、带通滤波、EOF分析等统计方法，研究了东亚夏季风(EASM）的移动特征、东亚地区季节内振荡(ISO)的基本特征、季节内振荡对东亚夏季风活动的影响、季节内振荡对东亚夏季风异常活动的影响机理。主要结论如下： （1）综合动力和热力因素定义了可动态描述东亚夏季风移动和强度的指数，并利用该指数研究了东亚夏季风的爆发和移动的季节内变化及其年际和年代际变化特征。研究发现，气候平均东亚夏季风前沿分别在28候、33候、36候、38候、40候、44候出现了明显的跳跃。东亚夏季风活动具有显著的年际变率，主要由于季风前沿在某些区域异常停滞和突然跨越北跳或南撤引起，造成中国东部旱涝灾害频繁发生。东亚夏季风的活动具有明显的年代际变化，在1965年、1980年、1994年发生了突变，造成中国东部降水由“南旱北涝”向“南涝北旱”的转变。 （2）东亚季风区季节内变化具有10~25d和30~60d两个波段的季节内振荡周期，以30-60d为主。存在三个主要低频模态，第一模态主要表征了EASM在长江中下游和华北地区活动期间的低频形势；第二模态印度洋-菲律宾由低频气旋式环流控制，主要表现了ISO在EASM爆发期间的低频形势；第三模态主要出现在EASM在华南和淮河活动期间的低频形势。第一模态和第三模态是代表东亚夏季风活动异常的主要低频形势。 （3）热带和副热带地区ISO总是沿垂直切变风的垂直方向传播。因此，在南海-菲律宾东北风垂直切变和副热带西太平洋北风垂直切变下，大气热源激发菲律宾附近交替出现的低频气旋和低频反气旋不断向西北传播，副热带西太平洋ISO以向西传播为主。中高纬度地区，乌拉尔山附近ISO以向东、向南移动或局地振荡为主；北太平洋中部ISO在某些情况下向南、向西传播。 （4）季风爆发期，伴随着热带东印度洋到菲律宾一系列低频气旋和低频反气旋， 冷空气向南输送，10~25天和30~60天季节内振荡低频气旋同时传入南海加快了南海夏季风的爆发。在气候态下，ISO活动表现的欧亚- 太平洋（EAP）以及太平洋-北美（PNA）低频波列分布特征(本文提出的EAP和PNA低频波列与传统意义上的二维定点相关得到的波列不同)。这种低频分布形式使得欧亚和太平洋中高纬度的槽、脊及太平洋副热带高压稳定、加强，东亚地区的低频波列则成为热带和中高纬度ISO相互作用影响东亚夏季风活动的纽带。不同的阶段表现不同的低频模态，30~60d低频模态的转变加快了EASM推进过程中跳跃性；30-60d低频模态的维持使得EASM前沿相对停滞。 （5）30-60d滤波场，菲律宾海域交替出现的低频气旋和低频反气旋不断向西北传播到南海-西太平洋一带。当南海-西太平洋地区低频气旋活跃时，季风槽加强、东伸，季风槽内热带气旋（TC）频数增加；当南海-西太平洋低频反气旋活跃时，季风槽减弱、西退，TC处于间歇期，生成位置不集中。 （6）在El Nino态下，大气季节内振荡偏弱，北传特征不明显，但ISO由中高纬度北太平洋中部向南和副热带西太平洋向西的传播特征显著，东亚地区ISO活动以第三模态为主，EASM集中停滞在华南和淮河流域，常伴随着持续性区域暴雨的出现，易造成华南和江淮流域洪涝灾害，长江和华北持续干旱。在La Nina态下，大气季节内振荡活跃，且具有明显的向北传播特征，PNA低频波列显著，东亚地区ISO活动以第一模态单峰为主；EASM主要停滞在长江中下游和华北地区，这些地区出现异常持续强降水，华南和淮河流域多干旱；在El Nino态向La Nina态转换期，ISO活动以第一模态双峰为主，长江中下游常常出现二度梅。

砂砾岩储层流动单元四维模型研究

This article is an important part of "95" technological subject of SINOPEC. It has a large number of difficulties and workloads, and has significant theoretical meanings and practical value. The study area is composed of sandstone & conglomerate reservoir of alluvial fan & fan delta, which belong to Sha3 lower member and Sha4 upper member of lower tertiary of Yong'an Town Oilfield in Dongying Depression. The target stataum develops in the hanging wall of the synsedimentary fault in the scarp zone of Dongying Depression. The frequently intense movements result in the variation of sandstone and conglomerate reservoir and the evolution of the time and space of Sha3 lower member and Sha4 upper member in Yong'an Town Oilfield. As a result, it is difficult for the individual reservoir correlation at the root of fan, which bring about a tackle problem for the exploitation of oilfield. In this background, the research of fluid units will be more difficult. In this article, the new concepts, the new methods, and the new techniques of sedimentology, petroleum geology, reservoir geology, physics of crystal surface, dynamic & static state reservoir description and well logging geology are synthetically applied, and the computer technology are made full uses of, and the identifying, dividing and appraising of the two-formation-type sandstone & conglomerate reservoir fluid units of Sha3 lower member and Sha4 upper member systemically analyzed in Yong'an Town Oilfield, Dongying Depression. For the first time, the single-well model, the section model, the plane model, the nuclear magnetism log model, the microcosmic network model, the 4-D geology model and the simulation model of the two-formation-type reservoir fluid units of the of sandstone & conglomerate reservoir of Sha3 lower member and Sha4 upper member are established, and the formative mechanism and distributing & enrichment laws of oil-gas of the two type of sandstone and conglomerate reservoir fluid units are revealed. This article established the optimizing, identifying, classifying and appraising standard of the two-formation-type reservoir fluid units of the of sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member, which settles the substantial foundations for static state model of the fluid units, reveals the macroscopic & microcosmic various laws of geometrical static state of the fluid units, and instructs the oil exploitation. This article established static state model of the two-formation-type sandstone and conglomerate reservoir fluid units by using the multi-subject theories, information and techniques, and reveals the geometrical configuration, special distribution and the oil-gas enrichment laws of the sandstone and conglomerate reservoir fluid units. For the first time, we established the nuclear magnetism log model of the two-formation-type sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member, which reveals not only the character and distributing laws of the porosity and permeability, bat also the formation and distribution of the movable fluid. It established six type of microcosmic net model of the two-formation-type sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member in the working area by using the advanced theories, such as rock thin section, SEM, image analysis, intrusive mercury, mold, rock C.T. measure & test image etc., which reveals the microcosmic characteristic of porosity & throat, filterate mode and microcosmic oil-gas enrichment laws of the sandstone and conglomerate reservoir. For the first time, it sets up the 4-D model and mathematic model of the sandstone and conglomerate reservoir, which reveals the distributing and evolving laws of macroscopic & microcosmic parameters of the two-formation-type sandstone and conglomerate reservoir and oil-gas in 4-D space. At the same time, it also forecasts the oil-gas distribution and instructs the oilfield exploitation. It established reservoir simulation model, which reveals the filterate character and distributing laws of oil-gas in different porosity & throat net models. This article established the assistant theories and techniques for researching, describing, indicating and forecasting the sandstone and conglomerate reservoir fluid units, and develops the theories and techniques of the land faces faulted basin exploitation geology. In instructing oilfield exploitation, it had won the notable economic & social benefits.

中国粮食生产的区域演进研究

Grain is one of the primary material conditions of the human survival and the grain production concerns the stability and development of the society directly. The regional patterns influence greatly on the grain production and the rational production distribution the regional comparative advantages and promotes grain production. This thesis starts with summarizing of the characteristics of changes and the overall trend of regional pattern of grain production of our country since 1949. Then it carries on network analyses to the factors, which influences the evolvement of regional grain production patterns of our country. And finally it gives some proposals to the grain production distribution in the future. The main content includes: Firstly, Reviewing the regional evolvement of grain production in our country, and analyzing the changes of the regional pattern of grain production of our country on the provincial scale and county scale separately, since 1949, especially since the reform and opening up policy. The main grain production areas are acting an important position in ensuring the national grain security, so this thesis analyses the main matter of the main grain production areas, forecasts the grain production situation in the future, and selects the Northeastern main grain production areas as the typical area to carry on the positive research. Secondly, this thesis analyzes the origin causes from two respects of natural and social economy of the regional evolvement pattern of grain production in China. Thirdly, based on the summarizing to the status of the regional pattern of the grain production, this thesis proposes the precept of the grain production distribution in the future in our country. Therefore, the areas of three major cereal crops, rice, wheat and corn, are confirmed on the basis of the comparative advantages. Finally, this thesis puts forward the security system of guaranteeing the grain production progressing steady in China. According to the above analysis, some conclusions have been achieved as follows: (1) The grain gross production gets on extricating itself from awkward position frequently while fluctuating greatly annually since 1949 in China. (2) Since the reform, its traditional regional pattern of grain production, the most of which was concentrated in the south area, has changed rapidly. China's center of gravity of grain production has shifted from the south to the north, and on the belts of latitude, the grain production has represented a trend of focusing to the middle area in China. (3) The main grain production areas play a very important role in ensuring China's food security. With their relative severe situation of the problems of agriculture, rural area and peasant, China has carried out a series of measures, which aim at improving the food-producing conditions of the main grain production areas, and enhancing the grain yields there. Under this condition, a forecast of the producing amount of the main grain production areas under the nation's self-supplying rate of over 95% shows that the increasing provision production in these areas can meet the demand of the country. (4) The natural and social economic factors influence together on the changes of the grain production regional pattern. Along with the state system transition and progress of agricultural science and technology, the regional pattern of grain production is affected heavier by the agricultural policy and technological elements. (5) The grain production will be concentrated to the middle province in the future, which economic development level being medium-sized; According to crop allocation, although the rice superiority production area located in the South, its comparative advantage index is little in some degree. Meanwhile, the wheat and corn superiority production areas are in the North mainly and its scale superiority and production level advantage are all comparatively obviously.

Uncertainty in wind energy forecasting

Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.

Changes to the North Atlantic subtropical high and its role in the intensification of summer rainfall variability in the southeastern United States

This study investigates the changes of the North Atlantic subtropical high (NASH) and its impact on summer precipitation over the southeastern (SE) United States using the 850-hPa geopotential height field in the National Centers forEnvironmental Prediction (NCEP) reanalysis, the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), long-term rainfall data, and Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) model simulations during the past six decades (1948-2007). The results show that the NASH in the last 30 yr has become more intense, and its western ridge has displaced westward with an enhanced meridional movement compared to the previous 30 yr. When the NASH moved closer to the continental United States in the three most recent decades, the effect of the NASH on the interannual variation of SE U.S. precipitation is enhanced through the ridge's north-south movement. The study's attribution analysis suggested that the changes of the NASH are mainly due to anthropogenic warming. In the twenty-first century with an increase of the atmospheric CO2 concentration, the center of the NASH would be intensified and the western ridge of the NASH would shift farther westward. These changes would increase the likelihood of both strong anomalously wet and dry summers over the SEUnited States in the future, as suggested by the IPCC AR4 models. © 2011 American Meteorological Society.

A COMPARISON OF MARKET CLEARING TOOLS IN ELECTRICITY SYSTEMS

To maintain a strict balance between demand and supply in the US power systems, the Independent System Operators (ISOs) schedule power plants and determine electricity prices using a market clearing model. This model determines for each time period and power plant, the times of startup, shutdown, the amount of power production, and the provisioning of spinning and non-spinning power generation reserves, etc. Such a deterministic optimization model takes as input the characteristics of all the generating units such as their power generation installed capacity, ramp rates, minimum up and down time requirements, and marginal costs for production, as well as the forecast of intermittent energy such as wind and solar, along with the minimum reserve requirement of the whole system. This reserve requirement is determined based on the likelihood of outages on the supply side and on the levels of error forecasts in demand and intermittent generation. With increased installed capacity of intermittent renewable energy, determining the appropriate level of reserve requirements has become harder. Stochastic market clearing models have been proposed as an alternative to deterministic market clearing models. Rather than using a fixed reserve targets as an input, stochastic market clearing models take different scenarios of wind power into consideration and determine reserves schedule as output. Using a scaled version of the power generation system of PJM, a regional transmission organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia, and wind scenarios generated from BPA (Bonneville Power Administration) data, this paper explores a comparison of the performance between a stochastic and deterministic model in market clearing. The two models are compared in their ability to contribute to the affordability, reliability and sustainability of the electricity system, measured in terms of total operational costs, load shedding and air emissions. The process of building the models and running for tests indicate that a fair comparison is difficult to obtain due to the multi-dimensional performance metrics considered here, and the difficulty in setting up the parameters of the models in a way that does not advantage or disadvantage one modeling framework. Along these lines, this study explores the effect that model assumptions such as reserve requirements, value of lost load (VOLL) and wind spillage costs have on the comparison of the performance of stochastic vs deterministic market clearing models.

Future requirements for and supply of ophthalmologists for an aging population in Singapore.

BACKGROUND: Singapore's population, as that of many other countries, is aging; this is likely to lead to an increase in eye diseases and the demand for eye care. Since ophthalmologist training is long and expensive, early planning is essential. This paper forecasts workforce and training requirements for Singapore up to the year 2040 under several plausible future scenarios. METHODS: The Singapore Eye Care Workforce Model was created as a continuous time compartment model with explicit workforce stocks using system dynamics. The model has three modules: prevalence of eye disease, demand, and workforce requirements. The model is used to simulate the prevalence of eye diseases, patient visits, and workforce requirements for the public sector under different scenarios in order to determine training requirements. RESULTS: Four scenarios were constructed. Under the baseline business-as-usual scenario, the required number of ophthalmologists is projected to increase by 117% from 2015 to 2040. Under the current policy scenario (assuming an increase of service uptake due to increased awareness, availability, and accessibility of eye care services), the increase will be 175%, while under the new model of care scenario (considering the additional effect of providing some services by non-ophthalmologists) the increase will only be 150%. The moderated workload scenario (assuming in addition a reduction of the clinical workload) projects an increase in the required number of ophthalmologists of 192% by 2040. Considering the uncertainties in the projected demand for eye care services, under the business-as-usual scenario, a residency intake of 8-22 residents per year is required, 17-21 under the current policy scenario, 14-18 under the new model of care scenario, and, under the moderated workload scenario, an intake of 18-23 residents per year is required. CONCLUSIONS: The results show that under all scenarios considered, Singapore's aging and growing population will result in an almost doubling of the number of Singaporeans with eye conditions, a significant increase in public sector eye care demand and, consequently, a greater requirement for ophthalmologists.

Recruitment in a changing environment: the 2000s North Sea herring recruitment failure

Environmentally induced change appears to be impacting the recruitment of North Sea herring (Clupea harengus). Despite simultaneously having a large adult population, historically low exploitation, and Marine Stewardship Council accreditation (implying sustainability), there have been an unprecedented 6 sequential years of poor juvenile production (recruitment). Analysis suggests that the poor recruitment arises during the larval overwintering phase, with recent survival rates greatly reduced. Contemporary warming of the North Sea has caused significant changes in the plankton community, and a recently identified regime shift around 2000 shows close temporal agreement with the reduced larval survival. It is, therefore, possible that we are observing the first consequences of this planktonic change for higher trophic levels. There is no indication of a recovery in recruitment in the short term. Fishing mortality is currently outside the agreed management plan, and forecasts show a high risk of the stock moving outside safe biological limits soon, potentially precipitating another collapse of the stock. However, bringing the realized fishing mortality back in line with the management plan would likely alleviate the problem. This illustrates again that recruitment is influenced by more than just spawning-stock biomass, and that changes in other factors can be of equal, or even greater, importance. In such dynamically changing environments, recent management success does not necessarily guarantee future sustainability.

Beyond long-term averages: making biological sense of a rapidly changing world

Biological responses to climate change are typically communicated in generalized terms such as poleward and altitudinal range shifts, but adaptation efforts relevant to management decisions often require forecasts that incorporate the interaction of multiple climatic and nonclimatic stressors at far smaller spatiotemporal scales. We argue that the desire for generalizations has, ironically, contributed to the frequent conflation of weather with climate, even within the scientific community. As a result, current predictions of ecological responses to climate change, and the design of experiments to understand underlying mechanisms, are too often based on broad-scale trends and averages that at a proximate level may have very little to do with the vulnerability of organisms and ecosystems. The creation of biologically relevant metrics of environmental change that incorporate the physical mechanisms by which climate trains patterns of weather, coupled with knowledge of how organisms and ecosystems respond to these changes, can offer insight into which aspects of climate change may be most important to monitor and predict. This approach also has the potential to enhance our ability to communicate impacts of climate change to nonscientists and especially to stakeholders attempting to enact climate change adaptation policies.

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

Myopic Rationality in a Mania

The rationality of investors during asset price bubbles has been the subject of considerable debate. An analysis of the British Railway Mania, which occurred in the 1840s, suggests that investors may have been myopic, as their expectations were only accurate in the short-term, but they remained rational, as they acted in a utility maximising manner given their expectations. Investors successfully incorporated forecasts of short-term dividend changes into their valuations, but were unable to predict longer-term changes. When short-term growth is controlled for, it appears that the railways were priced consistently with the non-railways throughout the entire episode.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.

Individual and Public-Program Adaptation: Coping with Heat Waves in Five Cities in Canada

Heat Alert and Response Systems (HARS) are currently undergoing testing and implementation in Canada. These programs seek to reduce the adverse health effects of heat waves on human health by issuing weather forecasts and warnings, informing individuals about possible protections from excessive heat, and providing such protections to vulnerable subpopulations and individuals at risk. For these programs to be designed effectively, it is important to know how individuals perceive the heat, what their experience with heat-related illness is, how they protect themselves from excessive heat, and how they acquire information about such protections. In September 2010, we conducted a survey of households in 5 cities in Canada to study these issues. At the time of the survey, these cities had not implemented heat outreach and response systems. The study results indicate that individuals' recollections of recent heat wave events were generally accurate. About 21% of the sample reported feeling unwell during the most recent heat spell, but these illnesses were generally minor. Only in 25 cases out of 243, these illnesses were confirmed or diagnosed by a health care professional. The rate at which our respondents reported heat-related illnesses was higher among those with cardiovascular and respiratory illnesses, was higher among younger respondents and bore no relationship with the availability of air conditioning at home. Most of the respondents indicated that they would not dismiss themselves as

A Dynamic Factor Approach to Mortality Modelling

Longevity risk has become one of the major risks facing the insurance and pensions markets globally. The trade in longevity risk is underpinned by accurate forecasting of mortality rates. Using techniques from macroeconomic forecasting, we propose a dynamic factor model of mortality that fits and forecasts mortality rates parsimoniously.We compare the forecasting quality of this model and of existing models and find that the dynamic factor model generally provides superior forecasts when applied to international mortality data. We also show that existing multifactorial models have superior fit but their forecasting performance worsens as more factors are added. The dynamic factor approach used here can potentially be further improved upon by applying an appropriate stopping rule for the number of static and dynamic factors.