中国华北雾霾天气与超强El Ni?o事件的相关性研究

2015年11—12月,全国接连发生七次大范围、持续性雾霾天气过程,其中,11月27日—12月1日的雾霾天气过程持续时间长达五天,成为2015年最强的一次重污染天气过程;12月19-25日重度雾霾再次发展,影响面积一度达到35.2万km~2.本文利用多种数据资料通过个例对比和历史统计详细分析了超强El Ni?o背景下雾霾天气频发的天气气候条件.其结果清楚表明:2015年11—12月欧亚中高纬度以纬向环流为主,东亚冬季风偏弱,使得影响我国的冷空气活动偏少,我国中东部大部地区对流层低层盛行异常偏南风,大气相对湿度明显偏大,并且大气层结稳定,对流层底层存在明显逆温.上述大气环流条件使得污染物的水平和垂直扩散条件差,因此在有一定污染排放的情况下,造成了重度雾霾天气过程的频发.由此,超强El Ni?o事件所导致的大尺度大气环流异常是我国中东部,尤其华北地区冬季雾霾天气频发的重要原因之一.     

A simple assessment approach for winter wheat loss risk impacted by water stress

In this study, an empirical assessment approach for the risk of crop loss due to water stress was developed and used to evaluate the risk of winter wheat loss in China, the United States, Germany, France and the United Kingdom. We combined statistical and remote sensing data on crop yields with climate data and cropland distribution to model the effect of water stress from 1982 to 2011. The average value of winter wheat loss due to water stress for the three European countries was about ?931 kg/ha, which was higher than that in China (?570 kg/ha) and the United States (?367 kg/ha). Our study has important implications for the operational assessment of crop loss risk at a country or regional scale. Future studies should focus on using higher spatial resolution remote sensing data, combining actual evapotranspiration to estimate water stress, improving the method for downscaling of statistical crop yield data and establishing more sophisticated zoning methods.     

A study on trade-offs between spatial resolution and temporal sampling density for wheat yield estimation using both thermal and calendar time

Within-season forecasting of crop yields is of great economic, geo-strategic and humanitarian interest. Satellite Earth Observation now constitutes a valuable and innovative way to provide spatio-temporal information to assist such yield forecasts. This study explores different configurations of remote sensing time series to estimate of winter wheat yield using either spatially finer but temporally sparser time series (5daily at 100 m spatial resolution) or spatially coarser but denser (300 m and 1 km at daily frequency) time series. Furthermore, we hypothesised that better yield estimations could be made using thermal time, which is closer to the crop physiological development. Time series of NDVI from the PROBA-V instrument, which has delivered images at a spatial resolution of 100 m, 300 m and 1 km since 2013, were extracted for 39 fields for field and 56 fields for regional level analysis across Northern France during the growing season 2014-2015. An asymmetric double sigmoid model was fitted on the NDVI series of the central pixel of the field. The fitted model was subsequently integrated either over thermal time or over calendar time, using different baseline NDVI thresholds to mark the start and end of the cropping season. These integrated values were used as a predictor for yield using a simple linear regression and yield observations at field level. The dependency of this relationship on the spatial pixel purity was analysed for the 100 m, 300 m and 1 km spatial resolution. At field level, depending on the spatial resolution and the NDVI threshold, the adjusted R² ranged from 0.20 to 0.74; jackknifed – leave-one-field-out cross validation – RMSE ranged from 0.6 to 1.07 t/ha and MAE ranged between 0.46 and 0.90 t/ha for thermal time analysis. The best results for yield estimation (adjusted R² = 0.74, RMSE =0.6 t/ha and MAE =0.46 t/ha) were obtained from the integration over thermal time of 100 m pixel resolution using a baseline NDVI threshold of 0.2 and without any selection based on pixel purity. The field scale yield estimation was aggregated to the regional scale using 56 fields. At the regional level, there was a difference of 0.0012 t/ha between thermal and calendar time for average yield estimations. The standard error of mean results showed that the error was larger for a higher spatial resolution with no pixel purity and smaller when purity increased. These results suggest that, for winter wheat, a finer spatial resolution rather than a higher revisit frequency and an increasing pixel purity enable more accurate yield estimations when integrated over thermal time at the field scale and at the regional scale only if higher pixel purity levels are considered. This method can be extended to larger regions, other crops, and other regions in the world, although site and crop-specific adjustments will have to include other threshold temperatures to reflect the boundaries of phenological activity. In general, however, this methodological approach should be applicable to yield estimation at the parcel and regional scales across the world.     

Mooring system reliability in tropical cyclone and North Sea winter storm environments

The characteristics of waves, winds and currents in a tropical cyclone environment differ significantly from those in a winter storm environment, like the North Sea. This can have a significant effect on the reliability of a mooring system that is designed to satisfy 100 yr conditions with specified Factors of Safety in accordance with ISO19901-7 or API RP 2SK. This paper presents reliability analysis of the mooring system of a permanently connected Floating LNG vessel, placed at two locations: (a) a tropical cyclone environment of the North West Shelf of Australia and (b) a winter storm environment of the North Sea. It is demonstrated that as a result of differences in the long term distribution of environmental parameters (waves, winds) between a North Sea environment and a tropical cyclone environment, the long term distribution of the mooring line response differs significantly in these two locations.This paper shows that a mooring system which is designed in accordance with ISO (or API), in these two environments, will achieve very different reliability levels because of the significant differences in environmental characteristics. In order to achieve the same reliability for the mooring system at these two geographical locations, Factors of Safety for use with 100 yr environmental conditions (Ultimate Limit State) were derived to achieve the same target probability of failure of 10⁻⁴/annum. It was found that for the North Sea environment, a factor of 1.5 is required for both the mooring chain and the pile, while for the tropical cyclone environment the required Factor of Safety has to be increased to 2.1. These differences are very significant and design standards need to be revised to reflect these findings.     

长江口外海域冬、春季水温变化规律研究

收集了1963—1996年长江口外海域水温的观测数据,分析了该海域冬、春季表层、10m层、20m层和30m层不同层次水温的季节和年际变化规律,以及其间水温垂向结构的变化。季节变化上,表层多年平均水温在8月最高,3月最低,底层多年平均水温9月最高,3月最低。年际变化上,冬季在1979年存在一个由冷到暖的跃迁;4月水温的年际变化较冬季复杂,表层、10m层、20m层和30m层水温分别在1979、1973、1973和1975年发生从冷到暖的跃迁。水平分布上,冬季除东南角小范围表层水温降低外,沿岸及北部海区表层水温均升高,春季北部和南部中间海域水温升高,升温幅度由表层至30m层逐渐变小。垂向结构上,冬季表底混合均匀,表层与20m层的年际变化相关系数高达0.97,春季表层与20m层的水温差存在10年左右的变化周期。本文将一些可能影响春季水温年际变化的因素与海温进行了比较并发现,在冷期,春季表层海温与长江口外海域气温相关较暖期好,相关指数为0.79;而暖期的春季表层与20m层的水温差与净热通量相关系数较高,为0.65。     

利用遥感信息研究区域冬小麦气孔导度的时空分布

气孔导度是影响作物蒸散和作物的光合速率进而影响作物产量的重要因子。文中通过利用NOAA－AVHRR数据首次对华北平原典型区冬小麦气孔导度分布进行了研究,给出了华北平原典型区冬小麦不同生长季节的气孔导度空间分布状况,为进一步研究田间水分和作物蒸散对产量影响以及建立遥感作物水分胁迫生物量模型和监测不同生育期的农田缺水等提供依据。     

冬小麦土壤深松保墒增产效应试验研究

采用土壤深松 45cm、30 cm处理打破犁底层 ,1 996～ 1 998年连续进行 2个年度的冬小麦保墒、增产效应田间试验 .试验结果表明 :土壤深松处理后可减少冬小麦全生育期 0～ 1 0 0 cm的作物耗水量 ,促进根系对 1 0 0～ 2 0 0 cm土层土壤水分的利用 ,提高冬小麦的产量耗水比 .土壤深松处理能明显增加 0～ 30 cm土层的土壤湿度和含水量 ,降低 0～ 50 cm土层的土壤容重 .有利于冬小麦根系、茎、叶的生长发育和总生物量的累积 .土壤深松 45cm处理 2年平均冬小麦增产 7.0 % ,土壤深松 30 cm处理第一年增产 7.7% .冬小麦土壤深松保墒增产效应的适宜深松深度为 30 cm.     

南海海流对冬季风风应力的响应特征

本文用美国普林斯顿大学海洋模式（ＰＯＭ）的南海版本（ＳＣＳ－ＰＯＭ） 模拟了持续冬季风风应力作用下,南海海流的响应特征。结果表明,从静止的海洋 出发,定常冬季风风应力驱动下的南海海流有明显的时间变化,垂直积分后的海流 （全流）约需１２０天左右的时间,方能达到准稳定态,表层、次表层和深层海流的时 间演变也有类似特征。模拟结果还表明,ＳＣＳ－ＰＯＭ有能力模拟出南海边界流、沿 岸流和海流的涡旋状结构。     

WINTER RUNOFF AND EROSION ON NORTHWESTERN USA CROPLAND

h200l.llNTRODUCTI0NTheNorthwesternWheatandRangeRegi0n(NWax)(Austin,l98l),whichincludesportionsofIdaho,Oregon,andWashington,isoneofthem0stuniqueagriculturalregionsoftheUSA.Winterandspringsmallgrainsand0thercropsareproukcedonl0esss0ilsdepositedoverbasalt.TheloessvariesinboththicknessandtopograPhicfeatures.Someareashavesteepanddune-likeslopes,while0thershavel0ng,gentlesl0pes.Theregion,br0kenfromnativeprairielessthanl20yearsag0(Kaise,l96l)hassufferedseriousdegradationofthesoilresourcebyw…     

与厄尔尼诺和拉尼娜相联系的中国南方冬季降水的年代际异常特征

利用NCEP/NCAR再分析大气环流资料、哈得来中心海温资料、中国700多站降水资料以及全球格点降水资料,详细分析了中国南方冬季降水异常的特征,并揭示了其所对应的欧亚大气环流和东亚冬季风异常与ENSO事件的联系,以及ENSO暖/冷位相对其影响的非对称性。研究进一步证明了厄尔尼诺是导致中国南方冬季降水偏多的重要外强迫因子,并指出拉尼娜对中国南方冬季降水的影响表现出明显的年代际变化特征。1980年之前的拉尼娜年冬季,东亚冬季风显著偏强,东亚大槽偏深,西北太平洋副热带高压偏弱偏东,中国南方受一致偏北风影响,气温偏低,降水偏少,多表现为冷干的气候特征。但1980年之后的拉尼娜年冬季,东亚大槽偏弱,印缅槽偏强,同时在菲律宾以西激发出异常气旋性环流,使得异常偏东风控制中国南方,有利于热带水汽输送增强,因此降水偏多。同时,1980年之后的拉尼娜事件还使得东亚副热带西风急流偏强偏北,中国南方处于急流入口区的右侧,通过二级环流使得中国南方上空的上升运动偏强,有利于降水偏多。因此,1980年之后的拉尼娜年冬季,中国南方易表现出冷湿的气候特征,有时也容易发生低温雨雪冰冻灾害。进一步分析表明,1980年以后拉尼娜成熟期海温异常空间分布型的变化,以及北半球大气环流的年代际变化可能是导致拉尼娜对东亚大气环流的影响在1980年之后发生变化的重要原因。