冬小麦遥感冠层温度监测土壤含水量的试验研究

在冬小麦主要生育期(2002年4月初到5月底),对不灌溉的冬小麦测定了冠层温度、地温、气温以及土壤含水量,计算了冠气温差且分析了冠层温度和冠气温差与不同土层厚度的土壤含水量相关关系。结果表明:14:00的冠层温度能较好地反映20cm土层的土壤含水量变化,但与其它各土层相关性有较大的波动性;14:00的冠气温差能较好地反映40cm以上土层的土壤含水量变化,二者的相关性很高,在20cm、40cm土层,两者相关系数R2分别为0.98866、0.99389,这为用区域遥感数据反演主要生育期冬小麦的冠气温差进而监测区域40cm土壤含水量提供了实验性的依据;拔节期和灌浆期,用14:00冠气温差来拟合各土壤层的土壤含水量有较高的精度,从而为用区域遥感数据监测区域土壤含水量提供了经验性的模型。     

Damage Evaluation of Agro-meteorological Hazards in the Maize-Growing Region of Songliao Plain,China: Case Study of Lishu County of Jilin Province

Agro-meteorological hazards such as drought, waterlogging and cool summer occur with very high frequency and affect maize production and social-economic development in the maize-growing region of Songliao Plain, China. Moreover, both the frequency of these hazards and loss from them are considered to be increasing with global warming. The purpose of this paper is to quantitatively analyze the relationships between the fluctuation of maize yield and drought, waterlogging and cool summer, and to evaluate the consequences of these hazards in the maize-growing area of Songliao Plain, taking Lishu county as a case study area based on GIS (Geographic Information System). Crop yield-climate analysis and regression analysis were employed to analyze and quantify relationships between the fluctuation of maize yield and drought, waterlogging and cool summer, and to evaluate the consequences of these hazards. The parameters and model of damage evaluation were presented using weighted comprehensive analysis, and the degree of damage of drought, waterlogging and cool summer to maize production was comprehensively evaluated and regionalized. It is shown that from 1949 to 1990, the negative value years of the fluctuation of maize yield due to meteorological hazards accounted for 55% of seasons, of which 14% was caused by drought, 30% by waterlogging, 4% by cool summer and drought, 9% by cool summer and waterlogging, 13% by drought and waterlogging, 30% by drought, waterlogging and cool summer. Studies on the instability and spatial variation of the fluctuations in maize yield in Lishu county showed that the middle plains are stable areas to climatic influence, while southeastern hills and low mountains, the low lands of the plains along the East Liao River and the western plain are unstable areas in terms of areas in maize yield. The synthetic index of the degree of damage to maize of drought, waterlogging and cool summer showed a strong positive correlation with the ratio of the amount damaged to the normal yield of maize. This suggests that this index can be used to evaluate such damage. The degree of damage of drought, waterlogging and cool summer to maize in Lishu county shows the regional characteristics, which increase gradually from the center to the west and east, this being almost identical with the spatial distribution of the fluctuation of maize yield due to these hazards. This study can be expected to provide the basis for developing strategies to mitigate agro-meteorological hazards and reducing the losses from them, and adjust the medium and long-term distribution of agricultural activities so as to adapt to environmental changes.     

Meteorological Office, Pune-411 005

Natural disasters like floods, tornadoes, tropicalcyclones, heat and cold wavewreak havoc and cause tremendous loss ofproperty all over the world. Most ofthe natural disasters are either dueto weather or are triggered due toweather related processes.Extreme weather events claimed thousands oflives and caused damage on vastscale. Recent super cyclone which affectedOrissa in 1999, Bangladesh cyclone of1970 and Hurricane Andrew in 1992 areexamples of some of the more damagingtropical cyclones which affected developingas well as the developed world. Heatand cold waves are also extreme events,which cause enormous losses in terms oflives lost and human discomfort and ailmentsarising out of them. The heat waveof 1995 and 1998 are still fresh in the mindof the Indian public. The estimated lossof human lives due to heat wave in 1998 was morethan 15,000. Economic losses asa result of these disasters and in particular inassociation with tropical cyclones haveincreased enormously over the last three decades.During 1961–1991, total loss oflives from drought alone was 1,333,728 overthe whole world. In terms of economiclosses, there is 8–10 fold increase from thebase figure of 1960. The socio-economicimpact of natural disaster is complex dependingupon the vulnerability of the placeand mitigation strategies that are put in place.Meteorology plays a crucial role in forewarningpeople about the severe/extremeweather systems and a constant endeavour by themeteorological services worldover has gone a long way towards minimizing thelosses caused by natural disasters.The paper summarises the natural disasterstatistics over south Asia and the possibleprediction strategies for combating theirsocio-economic impacts.     

川西亚高山三个森林群落的湿林冠蒸发速率

于3个假说和林冠上方2m处的气象变量，采用Penman-Monteith组合模型估算了一个生长季节内川西亚高山林区分别以云杉(SF)、冷杉(FF)和白桦(BF)为优势树种的3个林分的湿林冠蒸发速率(Er)。研究结果表明，SF、FF和BF的湿林冠蒸发量(E)分别为44．51mm、88．51mm和57．8mm，分别占总降雨量的9．2％、16．6％和10．2％。与SF和BF相比，FF具有最高的月平均Er和蒸发比例。SF、FF和BF的平均Er分别为0．097mm／h(变化范围：0．028-0．487mm／h)、0．242mm／h(变化范围：0．068～0．711mm／h)和0．149mm／h(0．060～0．576mm／h)。最高和最低的月平均Er分别在6月(SF、FF和BF分别为0．120mm／h、0．317mm／h和0．169mm／h)和10月(SF、FF和BF分别为0．083mm／h、0．187mm／h和0．101mm／h)。8：00至16：00期间的平均点Er显著高于0：00至8：00以及16：00至0：00期间的平均Er。Er显著的日变化和月变化主要归因于林冠上方的太阳辐射、空气温度和相对湿度的变化。     

沙尘天气等对西安市空气污染影响的研究

通过对西安市1981—2000年TSP、SO2和NOx年平均浓度资料,1998—2000年周报和日报环境监测资料以及相应的地面、高空常规气象观测资料的统计分析,研究了该市空气污染的时间变化特点以及沙尘天气等几种气象条件对其浓度变化的影响。结果表明:(1)颗粒污染物(TSP和PM10)是西安市的首要污染物,其次是SO2。1981—2000年期间,TSP年平均浓度降低了75%,SO2年平均浓度降低了77%,NOx年平均浓度总体上变化不大;这三种污染物月平均浓度的年变化都呈单周期型,冬季1月份最高,夏季最低(TSP是7月份最低,SO2和NOx是8月份最低)。(2)2001年春季3～4月份沙尘天气的频繁发生,使西安市空气污染日出现全年的第二个多发期(23d·月-1),这有别于正常年份仅在冬季1月份出现一个浓度峰值的特点;强沙尘暴天气过程会使西安市PM10浓度在非常短的时间内提高3倍左右,造成严重的颗粒物污染。(3)西安市冬半年出现轻度污染以上级别的几率明显大于夏半年。影响西安市的地面天气系统可归纳为12类,当受不同天气系统控制时,其污染状况会有较大差异。(4)西安市一年四季都有逆温存在,100m平均逆温强度为0.90℃;全年以低层逆温出现日数最多,但冬季贴地逆温出现日数最多,厚度最厚,强度最大,是造成西安市冬季空气污染严重的最重要气象因素之一。(5)西安     

侯马市酸雨概况及其气象条件分析

通过对侯马近14a酸雨观测资料分析,发现侯马出现酸雨的概率较大,强度较强,时间变化特征明显,与气象条件关系密切。     

闽东干旱概况及夏季人工增雨作业天气形势分析

对闽东干旱的成因和干旱的环流形势进行了探讨,着重分析了夏旱期间人工增雨作业的天气形势以及不同形势、不同云型下的降水情况。结果表明:闽东干旱的形成与大型环流形势、地理因素、土壤植被等有关,平均而言,沿海干旱明显多于内陆山区;夏季发生干旱的机率最大而且强度级别高,西太平洋副热带高压是致旱的主要天气系统;在夏季,台风型(T)、弱流场型(R)是进行人工增雨作业的优势天气型,Cb、Cu、Sc云是开展人工增雨作业比较适合的作业云。这些结果为夏旱期间开展人工增雨作业提供了理论依据。     

棉花生育期关键气象因子及单产丰歉评估指标

根据河南省棉花播种面积权重,选出安阳、新乡、商丘、周口和南阳5个代表站,利用棉花产量与棉花生育期间5个代表站旬平均光照、温度、降水的相关系数,确定7个关键气象因子,建立了其与产量的回归方程,提出了考虑7个关键气象因子综合影响的棉花单产丰歉评估指标。应用该评估指标对1980~2004年棉花单产的丰歉进行检验,与实况一致的达84%,产量与评估指标相关系数达0.71以上,相关极显著。     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

京津唐地区HFMD时空变异分析与影响因子探测

手足口病（HFMD）是一种多发于儿童的常见传染病。近年来,中国HFMD发病人数逐年上升,疾病疫情也日益受到社会广泛关注。虽已有不少相关研究,但对于探测其时空异质性及量化潜在影响因子解释力的研究仍然较少。本文采用地理探测器及贝叶斯时空层次模型,对2009-2013年京津唐地区HFMD发病率的时空异质性进行分析,并量化各影响因子及其两两交互作用对HFMD发病率的解释力。结果表明：① HFMD的相对风险存在时间异质性,其发病风险在春夏季（5-7月）达到峰值,而冬季（12-次年2月）发病风险最低;② HFMD的相对风险存在空间异质性,在经济发达的地区HFMD发病率较高;③ 影响HFMD发病率时间异质性的主要气象因子为平均温度、累积降水、相对湿度,解释力分别为0.38,0.27,0.13,且交互作用都大于独自影响的作用,如平均温度和相对湿度、平均温度和降水,平均温度和风速两两交互的解释力分别为0.43, 0.40, 0.42。通过研究京津唐地区HFMD发病率的时空异质性以及影响因子的量化状况,为本地区HFMD的预防和控制提供理论依据。