苹果套袋气象适用技术

1　套袋前的准备工作套袋前首先要选择质量可靠,性能良好的优质袋,因天、因地、因树、因品种制宜。其次,喷施农药,营造不利于病虫害生长发育的环境,是消灭袋内病虫害发生的主要方法。苹果谢花后,要适时喷施富力钙、优质甲级托布津、万灵粉、灭脲3号等药剂,喷施农药与天气的变化十分密切,在5月上、中旬,就要及时收听天气预报,及时向气象部门了解旬、月、侯的天气变化情况,喷施农药前,要看后期是否有雨,如果后期预报有降水,就不能喷药,否则,会降低农药浓度,影响喷防效果。套袋前如果天气干旱,可对果园适当浇水灌溉,然后套袋,可以避免日灼。2　…     

海东市平安区气象服务与精准扶贫工作的思考

通过对精准扶贫工作基本情况的调研,认为精准扶贫工作需要气象部门积极主动的参与,提供针对性强、精细化、无缝隙的气象服务产品。找准气象服务与精准扶贫工作的结合点,加强气象为精准扶贫工作服务的能力建设,完善气象信息发布渠道,提高气象服务的效益。     

发展十堰气象产业的实践与探讨

地处鄂西北贫困山区的十堰市气象部门,近年来经过一系列以气象产业为主题的改革,极大地促进了气象事业的发展。连续四年“综合优秀达标”,连续两届被授予省级文明单位或省级最佳文明单位。对此成绩,十堰市委有关领导尤为关注,并强调指出,十堰市局发展气象产业,服务于整个社会,更充分地展示了气象产业的社会价值,值得研究和借鉴;同时十堰市气象部门的这一发展态势又被中国气象局领导誉为“有湖北特色的西北现象”。     

发挥气象科技优势为扶贫攻坚做出贡献

发挥气象科技优势为扶贫攻坚做出贡献樊春生（山西省气象局０３０００２）我省处于季风气候区边缘，境内地形复杂，植被差，气候的年际变化大，极易发生各种气象灾害。气象灾害在所有自然灾害中出现频次最多。据初步统计，１９９０年到１９９５年由于气象灾害造成的损失占...     

充分发挥气象科技优势为科技扶贫兴农作贡献

气象部门是一个以为国民经济各行各业服务，以为农业服务为重点的基础性、先导性、公益性事业部门。在中国气象局和省委。省政府的领导下，我省气象部门响应党中央、国务院的号召，积极行动起来，充分发挥气象科技优势，主动参与扶贫开发，科技兴农工作，为我省农业丰收。扶贫攻坚作出了积极的贡献。气象科技是我省科技扶贫兴农，实现贫困地区脱贫致富可持续发展的一支重要科技力量。1气象科技扶贫兴农的主要成绩我省是一个农业省，而气象灾害频繁，对农业丰收影响较大，尤其是贫困地区抗御气象灾害的能力差，素有“大灾大减产，小灾小减产…     

三门峡苹果气象灾害气象服务效益评估一

选择三门峡苹果种植有代表性的低海拔的塬区、海拔较高的浅山区和海拔最高的高山区,以德尔菲法作为评估方法,通过问卷调查及专家评估的形式,依据气象服务效益贡献率评估模型,对苹果主要气象灾害的气象服务效益进行分析和评估.结果表明：苹果主要气象灾害的气象服务效益贡献率总体为6.5％,冰雹气象灾害的气象服务效益贡献率最高,其次是低温冻害气象服务效益贡献率,高温和连阴雨气象服务效益贡献率处于中间,干旱的气象服务效益贡献率最低.     

搞好气象产业档案浅议

在社会主义市场经济蓬勃发展的新形势下 ,大力发展产业是气象事业“可持续”发展的重要条件。 1 998年 ,省局适时制定了《甘肃省气象事业结构战略性调整实施方案(1 998～ 2 0 0 0年 )》推动了全省气象事业结构战略性调整工作全面展开 ,并取得突破性进展 ,科技服务和综合经营工作积极开拓 ,取得了可喜成绩。知识经济时代即将到来 ,现代气象科技发展日新月异。中国气象局副局长马鹤年最近指出 ,气象产业可望成为知识经济重要成员。展望未来 ,气象科学技术正在酝酿着一些重大高新科技的突破 ,预示着即将开发出一些新的气象智力资源 ,为知识经济…     

气象服务主动融入精准扶贫的思考

为更好地将气象服务主动融入精准扶贫工作中,促进宁夏贫困地区早日脱贫,文章通过分析气象防灾减灾与精准脱贫的融合度、农村抵御气象灾害能力不足的主要原因、气象扶贫等方面问题,为气象工作提出建议。建议气象服务应从开展贫困群众气象服务需求调研、完善气象信息发布渠道、提高气象服务效益、提高贫困人群防灾减灾能力等4个方面开展,以将气象服务主动融入精准扶贫的工作中。     

Strengthening conceptual foundations: Analysing frameworks for ecosystem services and poverty alleviation research

A research agenda is currently developing around the linkages between ecosystem services and poverty alleviation. It is therefore timely to consider which conceptual frameworks can best support research at this nexus. Our review of frameworks synthesises existing research on poverty/environment linkages that should not be overlooked with the adoption of the topical language of ecosystem services. A total of nine conceptual frameworks were selected on the basis of relevance. These were reviewed and compared to assess their ability to illuminate the provision of ecosystem services, the condition, determinants and dynamics of poverty, and political economy factors that mediate the relationship between poverty and ecosystem services. The paper synthesises the key contributions of each of these frameworks, and the gaps they expose in one another, drawing out lessons that can inform emerging research. Research on poverty alleviation must recognize social differentiation, and be able to distinguish between constraints of access and constraints of aggregate availability of ecosystem services. Different frameworks also highlight important differences between categories of services, their pathways of production, and their contribution to poverty alleviation. Furthermore, we highlight that it is important to acknowledge the limits of ecosystem services for poverty alleviation, given evidence that ecosystem services tend to be more associated with poverty prevention than reduction. We conclude by reflecting on the relative merits of dynamic Social–Ecological Systems frameworks versus more static checklists, and suggest that research on ecosystem services and poverty alleviation would be well served by a new framework distilling insights from the frameworks we review.     

CDM: Is it a ‘win–win’ strategy for rural poverty alleviation in India?

India is perceived to be one of the most attractive Non-Annex I countries for CDM project development. There are more than 350 projects in the CDM pipeline, largely in the areas of renewable energy, energy efficiency in industries and fossil fuel switching. This paper examines the socio-economic component of sustainable development commitments of the CDM projects to see if they can make any impact on rural poverty in India, since the goal of poverty alleviation lies at the core of the country’s development priorities. The study concludes that CDM is not contributing to rural poverty alleviation to any notable extent. Nearly all the projects have a business orientation and are not directed to the development of rural poor. Even the renewable energy projects will have limited role in up-liftment of the masses below poverty line due to their weak resource base. For CDM to emerge as a “win–win” strategy for poverty alleviation projects should be aimed at the rural communities and designed to accelerate agricultural growth in the rainfed regions of the country.     

加强全行业气象工作为龙江经济发展做出新贡献--在全省气象工作会议上的讲话

很高兴参加这次会议。首先代表省政府向常年工作在气象战线的全省气象干部职工表示亲切的问候。对辽宁、吉林省气象局领导到会指导表示欢迎。     

Least squares support vector machine for short-term prediction of meteorological time series

The prediction of meteorological time series plays very important role in several fields. In this paper, an application of least squares support vector machine (LS-SVM) for short-term prediction of meteorological time series (e.g. solar irradiation, air temperature, relative humidity, wind speed, wind direction and pressure) is presented. In order to check the generalization capability of the LS-SVM approach, a K-fold cross-validation and Kolmogorov–Smirnov test have been carried out. A comparison between LS-SVM and different artificial neural network (ANN) architectures (recurrent neural network, multi-layered perceptron, radial basis function and probabilistic neural network) is presented and discussed. The comparison showed that the LS-SVM produced significantly better results than ANN architectures. It also indicates that LS-SVM provides promising results for short-term prediction of meteorological data.     

Bridging organizations in agricultural carbon markets and poverty alleviation: An analysis of pro-Poor carbon market projects in East Africa

International agricultural carbon market projects face significant challenges in delivering greenhouse gas mitigation objectives whilst also seeking to provide additional benefits for poverty alleviation. The carbon credit producer (the smallholder farmer) and carbon credit buyer in the carbon market transaction typically operate at different spatial and temporal scales. Buyers operate at a global scale, responding to opportunities for financial speculation and both private and public climate action plans. Farmers operate within households, farms, and immediate agricultural landscapes, pursuing livelihood and food security needs. These different scales often result in mismatches of timing, payment, and knowledge in market transactions and can be partially rectified by project developers who serve to broker the relationship between the farmers and the buyers. We examined eight East African agricultural carbon market projects to determine how project developers function as bridging organizations and minimize the mismatches between these actors. Results show that projects better bridged the timing and payment gap between buyers and producers when project developers provided non-monetary benefits or direct monetary assistance to farmers. However, knowledge gaps remained a significant barrier for farmers wishing to participate in the market. We discuss how project developers brokered relationships in ways that reflected their interests and highlight the limitations, trade-offs, and challenges that must be overcome if win-win outcomes of poverty alleviation and climate change mitigation are to be realized.     

Development of forecasting technologies for meteorological support of the Sochi-2014 Winter Olympic Games

In February–March 2014 the Winter Olympic Games will be held in Sochi. Sharp weather contrasts and high spatiotemporal variability are typical of the region of the Sochi-2014 Games. The complex mountain terrain and the intricate mixture of marine subtropical and Alpine conditions make the weather forecasting in this region extremely challenging. Although all lead times of the forecast are important for the Games, primary needs for these sport events are associated with the nowcasting and the short-range weather forecasting. The complexity of the Sochi region stimulates the development of high-resolution mesoscale modeling as a backbone of the Olympic meteorological services. Presented are the main branches of the current research in this area carried out in Roshydromet.     

Evaluation of support vector machine for estimation of solar radiation from measured meteorological variables

Solar radiation is an essential and important variable to many models. However, it is measured at a very limited number of meteorological stations in the world. Developing method for accurate estimation of solar radiation from measured meteorological variables has been a focus and challenging task. This paper presents the method of solar radiation estimation using support vector machine (SVM). The main objective of this work is to examine the feasibility of SVM and explore its potential in solar radiation estimation. A total of 20 SVM models using different combinations of sunshine ratio, maximum and minimum air temperature, relative humidity, and atmospheric water vapor pressure as input attributes are explored using meteorological data at 15 stations in China. These models significantly outperform the empirical models with an average 14 % higher accuracy. When sunshine duration data are available, model SVM2 using sunshine ratio and air temperature range is proposed. It significantly outperforms the empirical models with an average 26 % higher accuracy. When sunshine duration data are not available, model SVM19 using maximum temperature, minimum temperature and atmospheric water vapor pressure is proposed. It significantly outperforms the temperature-based empirical models with an average of 18 % higher accuracy. The remarkable improvement indicates that the SVM method would be a promising alternative over traditional approaches for estimation of solar radiation at any locations.