A SEASONAL INFLUENZA THEORY AND MATHEMATICAL MODEL INCORPORATING METEOROLOGICAL AND SOCIO- BEHAVIORAL FACTORS

On the basis of a comprehensive literature review and data analysis of global influenza surveillance, a transmission theory based numerical model is developed to understand the causative factors of influenza seasonality and the biodynamical mechanisms of seasonal flu. The model is applied to simulate the seasonality and weekly activity of influenza in different areas across all continents and climate zones around the world. Model solution and the good matches between model output and actual influenza indexes affirm that influenza activity is highly auto-correlative and relies on determinants of a broad spectrum. Internal dynamic resonance; variations of meteorological elements (solar radiation, precipitation and dewpoint); socio-behavioral influences and herd immunity to circulating strains prove to be the critical explanatory factors of the seasonality and weekly activity of influenza. In all climate regions, influenza activity is proportional to the exponential of the number of days with precipitation and to the negative exponential of quarter power of sunny hours. Influenza activity is a negative exponential function of dewpoint in temperate and arctic regions and an exponential function of the absolute deviation of dewpoint from its annual mean in the tropics. Epidemics of seasonal influenza could be deemed as the consequence of the dynamic resonance and interactions of determinants. Early interventions (such as opportune vaccination, prompt social distancing, and maintaining incidence well below a baseline) are key to the control and prevention of seasonal influenza. Moderate amount of sunlight exposure or Vitamin D supplementation during rainy and short-day photoperiod seasons, more outdoor activities, and appropriate indoor dewpoint deserve great attention in influenza prevention. To a considerable degree, the study reveals the mechanism of influenza seasonality, demonstrating a potential for influenza activity projection. The concept and algorithm can be explored for further applications.     

定量评估极端天气影响农业总产值的方法

选取对极端天气敏感性和脆弱性较高的农业领域为研究对象,将极端天气因子和农业生产因子引入Cobb-Douglas生产函数,构建气候经济模型,定量分析了极端天气事件对浙江省农业总产值的影响。结果表明：极端天气因子与浙江省农业总产值存在长期均衡关系,对农业总产值有显著的负面影响。高温日数、低温日数、强降水日数每增加1%,浙江农业总产值分别减少0.072%、0.046%、0.076%;高温日数和强降水日数的短期波动对农业总产值也有显著的负面影响;不同区域的农业总产值受极端天气影响程度存在差异,浙江西北地区和西南地区相对东部沿海地区受极端天气影响更为严重。     

海南岛海风雷暴结构的数值模拟

本文利用高分辨率WRF模式对2012年7月20日发生在海南地区的一次海风雷暴过程进行模拟,探讨了海南岛复杂地形下海风雷暴的结构、发展演变过程及其触发机制.结果表明,海南岛北部向内陆传播的海风与南部受地形阻挡的海风相遇后会形成海风辐合带,辐合带能影响当地的散度和涡旋特征,为雷暴的发生发展提供有利的动力和热力学条件.海南岛受热带海洋的影响较大,当地的水汽条件和对流潜势长期保持着有利于对流发展的状态,自由对流高度始终处于较低的位置,一旦海风辐合带来的抬升运动克服对流抑制到达自由对流高度后,对流就能自主地发展起来,所以单纯的海风辐合也常常能触发当地的强雷暴.雷暴发生发展过程中对流参数存在明显的变化,其演变曲线的突变位置对雷暴的发生有一定的指示作用.海南岛的海风雷暴过程与当地的复杂地形密切相关,地形的动力阻挡作用影响着低层海风的辐合以及对流的发展.     

近地空间环境的GNSS无线电掩星探测技术

从GPS/MET计划开始,基于GNSS的无线电掩星技术已成为一种强大的近地空间环境探测手段.截至到目前,已经有20多颗发射的低轨道卫星带GPS掩星接收机,其中COSMIC是首个专门用于掩星探测的卫星星座.这些掩星数据被广泛应用于气象预报、气候与全球变化研究、及空间天气监测和电离层研究.由于COSMIC的成功,相关合作单位目前正积极推动COSMIC-2计划,该计划将总共有12颗卫星,于2016年与2019年各发射6颗.COSMIC-2将携带一个高级的GNSS掩星接收机,它将接受GPS与GLONASS信号,并具备接受其他可获得信号源的能力(如中国北斗定位信号),其每日观测的掩星数量将是COSMIC的4~6倍.同时COSMIC-2还将携带两个空间天气载荷,加强空间天气的监测能力.本文以COSMIC与COSMIC-2计划为主线,对掩星的发展历史、技术要点进行了简单介绍,并简要综述了COSMIC取得的部分科学成果,同时对未来包括技术发展和众多的掩星观测进行了展望.     

上海梅汛期强降水的低频特征及延伸期预报

利用2007-2013年NCEP/NCAR的700 hPa经、纬向风场及水汽场逐日再分析资料和上海市11站逐日降水资料。进行周期分析,提取低频信息,并利用向量场的经验正交函数方法进行分型。结果表明：上海地区梅汛期降水存在30-50 d的显著周期。强降水发生期,低频系统存在4个主要聚集区。贝加尔湖以西至河套地区存在并维持低频反气旋、鄂霍次克海附近多为低频气旋,这两地是中高纬冷空气的主要活动区域;孟加拉湾附近的低频反气旋及热带洋面的低频气旋是水汽的两大源地。这些区域的显著低频系统的生消是延伸预报的主要依据。上海入梅首场强降水发生前,多为偏北气流控制。南北低频气流辐合区向北移动至30°N附近,上海地区梅汛期强降水发生。低频风场及水汽场的北传与梅雨带的移动有较好的对应,当低纬低频水汽稳定北传至30°N附近时,江南北部入梅,随后偏南水汽或继续北进或滞留,对应梅雨带的持续北抬或间歇性停滞。低频经向风及水汽输送的特征是梅汛期延伸期强降水的前兆信号。跟踪监测低频偏南气流的北传进程有助于预报入梅强降水过程。     

我国空间物理研究进展

经过多年的建设与努力,我国日地空间物理与空间天气领域的研究呈现蓬勃的发展态势.《地球物理学报》以空间物理为专辑,集中在2014年11期刊发38篇文章,涵盖了基于"子午工程"观测数据分析在内的空间物理和空间天气方面的一批最新研究成果.这些工作涉及电离层、中高层大气、地磁与磁层、太阳及太阳风等学科方向,还有两篇工作涉及行星空间环境.本文将从这五个学科方向简要地介绍收入专辑的这些工作.     

Dependence of radar quantitative precipitation estimation error on the rain intensity in the Cévennes region,France

Abstract

Radar quantitative precipitation estimates (QPEs) were assessed using reference values established by means of a geostatistical approach. The reference values were estimated from raingauge data using the block kriging technique, and the reference meshes were selected on the basis of the kriging estimation variance. Agreement between radar QPEs and reference rain amounts was shown to increase slightly with the space–time scales. The statistical distributions of the errors were modelled conditionally with respect to several factors using the GAMLSS approach. The conditional bias of the errors presents a complex structure that depends on the space–time scales and the considered geographical sub-domains, while the standard deviation of the errors has a more homogeneous behaviour. The estimation standard deviation of the reference rainfall and the standard deviation of the errors between radar and reference rainfall were found to have the same magnitude, indicating the limitations of the available network in terms of providing accurate reference values for the spatial scales considered (5–100 km²).

Editor D. Koutsoyiannis; Guest editor R.J. Moore

Citation Delrieu, G., Bonnifait, L., Kirstetter, P.-E., and Boudevillain, B., 2013. Dependence of radar quantitative precipitation estimation error on the rain intensity in the Cévennes region, France. Hydrological Sciences Journal, 59 (7), 1300–1311. http://dx.doi.org/10.1080/02626667.2013.827337     

Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area

Abstract

Due to the relatively small spatial scale, as well as rapid response, of urban drainage systems, the use of quantitative rainfall forecasts for providing quantitative flow and depth predictions is a challenging task. Such predictions are important when consideration is given to urban pluvial flooding and receiving water quality, and it is worthwhile to investigate the potential for improved forecasting. In this study, three quantitative precipitation forecast methods of increasing complexity were compared and used to create quantitative forecasts of sewer flows 0–3 h ahead in the centre of a small town in the north of England. The HyRaTrac radar nowcast model was employed, as well as two different versions of the more complex STEPS model. The STEPS model was used as a deterministic nowcasting system, and was also blended with the Numerical Weather Prediction (NWP) model MM5 to investigate the potential of increasing forecast lead-times (LTs) using high-resolution NWP. Predictive LTs between 15 and 90 min gave acceptable results, but were a function of the event type. It was concluded that higher resolution rainfall estimation as well as nowcasts are needed for prediction of both local pluvial flooding and combined sewer overflow spill events.

Editor D. Koutsoyiannis; Guest editor R.J. Moore     

江苏省汛期强降水过程的延伸期预报试验

针对汛期延伸期降水预报问题,根据大气低频振荡特性,运用低频天气图预报方法,通过分析关键区低频天气系统(低频气旋和低频反气旋)的活动特征,建立低频系统与强降水过程间的对应关系,通过低频系统的活动特征来预报降水过程。在2011年7—9月江苏省延伸期强降水过程预报试验中,低频天气图预报方法的预报效果较好,且预报时效为10~30 d,可以在延伸期业务预报中加以应用。此外,还运用模式统计降尺度方法预报降水落区,为强降水过程的发生提供背景依据和参考信息,具有一定的实用意义。     

基于CAN总线的地面自动气象观测集成系统

随着气象业务领域进一步深入拓展,嘉兴市气象局从2006年起,增加了紫外线、下垫面温度等特种要素观测,并与江苏省无线电科学研究所合作研发了地面自动气象观测集成系统。该系统基于CAN总线,由中心站计算机,综合观测系统业务软件及各种分采集器组成,具备积木式扩充特点,能根据需求扩充气象要素,系统采用Microsoft VB 60作为开发工具,后台数据支持MS SQL Server2000专业版,采用C/S架构,适合多点多要素方式监测。该自动气象观测集成系统集数据查询、统计计算、报警监控等一体,具有可扩性好、稳定性高、信号衰减小、功能完备、运行稳定、界面友好等特点,能满足气象业务日益拓展的需要,适合在全国气象业务部门推广使用。