甘肃东部旱作小麦水分生产力研究

甘肃东部旱作区小麦产量变幅大，不分生产力变化极不稳定，但潜力很大。冬小麦降水和土壤水分生产力平均为０．９２ｋｇ／ｍｍ和０．８５ｇ／ｍｍ和０．７５ｋｇ／ｍｍ。土壤贮水量是旱作区小麦生产力的最重要因素。秋季土壤贮水量是翌年小麦产量的基础，有收无收的关键，对产量的贡献最大；小麦产量对春季土壤贮水量的利用率最高，对小麦高产优质至关重要。     

桂平市江河沿岸低水位农田早稻避洪的探讨

桂平市位于广西东南部,北回归线横贯中部,属南亚热带季风气候,雨量充沛,年平均雨量为１７１４．０ｍｍ,最多年可达２４８５．０ｍｍ,最少年１０２６．５ｍｍ,４～９月为汛期,平均总雨量为１２７９．３ｍｍ,占年雨量的７４．６％,汛期多大雨、暴雨和大暴雨,易发...     

近40年广东省的旱涝特征

利用广东省８６个测站近４０年（建站起至１９９４年）的降水资料,分析和讨论了平均年雨量分布的特征,并以５级旱标准确定了全省和各分区的逐年旱涝级别,初步讨论了若干旱涝特征。结果表明,全省平均年雨量为１７４８ｍｍ;四个主要雨量大值（年雨量２０００ｍｍ以上）中心分别位于恩平、清远、海丰和龙门;全省平均而言,１９５９、１９６１、１９７３、１９７５和１９８３年为涝年,１９５６、１９６３、１９７７和１９９１年为     

旱作带田-膜两用的水热效应及增产效益研究

西北黄土高原，光照丰富，雨热同期。实施旱作带田一膜两用技术，可增温２—５℃，节水３０—４０ｍｍ以上，调水７０％左右。热量利用率高达０．９８７，降水利用效率１５．１５ｋｇ／（ｍｍ·ｈｍ２），气候生产力利用指数０．４９。增产效益明显，变作物一年一作为一年两作，总产可达８２５０—９０００ｋｇ／ｈｍ２，比单作增产４５％以上。     

用极值分布计算黔南最大一日降水量的重现期

该文应用极值分布计算黔南各县市最大日降水量的重现期，结果表明：都匀市最大降水量５０年一遇为１８８．１ｍｍ，１００年一遇为２０７．６ｍｍ，２００年一遇为２２７．０ｍｍ，罗甸２００年一遇为３０８．２ｍｍ，为全州最大，龙里２００年一遇为１３８．９ｍｍ为全州最小，此外，还计算了罗甸１９７６年５月２４日出现的全省最大一日降水量３３６．７ｍｍ的重现期约为４００年一遇。     

蒙古五十年来旱涝变化和降水趋势的研究

本文利用蒙古２５个台站的５２年逐月降水量资料，研究了蒙古旱变化和降水趋势。结果表明：蒙古平均年降水量为２１６．１ｍｍ，分布由南向北增加，东西部少，中部多，南部和西部为干旱区，中部和东部为半干旱区，与我国干旱半干旱区是一个整体，降水主要集中在夏季；年降水量变率为１５．６％－３８．０％。蒙古旱涝都很频繁，旱的频率高于涝的频率，而大涝的频率是大旱的两倍。年降水量服从正态分布，并有准３年和１１－１４年周期     

内江市近34年来降水变化分析

利用１９６０－１９９３年内江市各测站的逐月降水量资料，分析了内江市近３４年来降水的变化特征，发现区域平均年降水量以－２３．８６ｍｍ／１０年的倾向率减少，减少最快在我市西部，东部略有增加，并且指出，近３０多年来，内江市的区域平均降水量冬，春两季正在增加，而夏，秋两季却在减少，冬半年与夏半年具有反位相变化的特点。     

沿海滩涂盐场保卤时机的确定及其预报

本文通过分析确定了黄海地部盐雨日必须进行保卤的临界降水量，春，秋季ＲＳ＝３．０ｍｍ，ＲＳ＝５．０ｍｍ，冬季＝１．０ｍｍ，若预报Ｒ≥ＲＳ，则需保卤。并利用本站资料及有关预报产品建立了补充预报方程，取得了显著的社会效益和经济效益。     

1994．8．6暴雨分析

１９９４．８．６暴雨分析孙田文，李社宏（铜川市气象局铜川·７２７０００）１降水概况１９９４年８月５日晚至６日凌晨．渭北及陕北市部地区出现了大范围的突发性强对流暴雨。降水主要集中在０时至４时，铜川地区各站日最大雨量为７３．０ｍｍ，１ｈ最大雨量４７．０ｍ...     

“93.8.4”暴雨过程分析

“９３．８．４”暴雨过程分析王正旺，庞转棠（长治市气象局０４６０００）１引　言１９９３年８月４日长治市所属１２个县区降了大一暴雨和大暴雨。雨量为２８．８～１２７。０ｍｍ，其中５个县区（襄垣、沁县、黎城、潞城、长治市城区）雨量在１００ｍｍ以上，暴雨中心...     

Assessing the spatial impact of climate on wheat productivity and the potential value of climate forecasts at a regional level

Quantification of the spatial impact of climate on crop productivity and the potential value of seasonal climate forecasts can effectively assist the strategic planning of crop layout and help to understand to what extent climate risk can be managed through responsive management strategies at a regional level. A simulation study was carried out to assess the climate impact on the performance of a dryland wheat-fallow system and the potential value of seasonal climate forecasts in nitrogen management in the Murray-Darling Basin (MDB) of Australia. Daily climate data (1889–2002) from 57 stations were used with the agricultural systems simulator (APSIM) to simulate wheat productivity and nitrogen requirement as affected by climate. On a good soil, simulated grain yield ranged from <2 t/ha in west inland to >7 t/ha in the east border regions. Optimal nitrogen rates ranged from <60 kgN/ha/yr to >200 kgN/ha/yr. Simulated gross margin was in the range of –$20/ha to $700/ha, increasing eastwards. Wheat yield was closely related to rainfall in the growing season and the stored soil moisture at sowing time. The impact of stored soil moisture increased from southwest to northeast. Simulated annual deep drainage ranged from zero in western inland to >200 mm in the east. Nitrogen management, optimised based on ‘perfect’ knowledge of daily weather in the coming season, could add value of $26～$79/ha compared to management optimised based on historical climate, with the maximum occurring in central to western part of MDB. It would also reduce the nitrogen application by 5～25 kgN/ha in the main cropping areas. Comparison of simulation results with the current land use mapping in MDB revealed that the western boundary of the current cropping zone approximated the isolines of 160 mm of growing season rainfall, 2.5t/ha of wheat grain yield, and $150/ha of gross margin in QLD and NSW. In VIC and SA, the 160-mm isohyets corresponded relatively lower simulated yield due to less stored soil water. Impacts of other factors like soil types were also discussed.     

Has climate change opened new opportunities for wheat cropping in Argentina?

As a result of climate change, and in particular rainfall changes, agricultural production is likely to change across the globe. Until now most research has focused on areas which will become unsustainable for agricultural production. However, there are also regions where climate change might actually improve conditions for growth. In the western Pampas region of Argentina, average annual rainfall has increased by 100–200 mm over the last 70 years, mainly during summer. Wheat is grown during winter, primarily on stored soil water and the main factor limiting plant production in this area is rainfall. Using the well tested simulation model APSIM-NWheat, we studied whether recent climate change has potentially opened new opportunities for wheat cropping in Argentina. Simulation results indicated that the additional rainfall in the Pampas of Argentina has increased the achievable yield (defined as the yield limited by solar radiation, temperature, water and nitrogen supply) of wheat in the currently cropped region, but less than expected based on the large amount of additional rainfall. The higher achievable yield from additional rainfall could potentially allow an expansion of profitable wheat cropping into currently non-cropped areas, where the achievable wheat yield increased in average from 1 t/ha to currently 2 t/ha. However, the poor water-holding capacity of the sandy soils which dominate the region outside the current cropping area limits the systems ability to use most of the increased summer rainfall. Nevertheless, the current higher achievable yield indicates a suitability of the region for cropping, which will slightly decline or remain unchanged depending on summer rainfall storage, with current and future climate change, including projected changes in rainfall, temperature and atmospheric CO₂ concentration. Factors other than just the achievable yield will eventually influence any future development of this region for cropping, including the high sensitivity of the sandy soils to erosion and nutrient leaching, current relatively high land prices, restrictions on clearing for cropping, the distance to the nearest port and current unsuitable cultivars withstanding the high frost risk.     

Effects of Climate Change on Rice Production in the Tropical Humid Climate of Kerala, India

The CERES-Rice v3. crop simulation model, calibrated and validated for its suitability to simulate rice production in the tropical humid climate Kerala State of India, is used for analysing the effect of climate change on rice productivity in the state. The plausible climate change scenario for the Indian subcontinent as expected by the middle of the next century, taking into account the projected emissions of greenhouse gases and sulphate aerosols, in a coupled atmosphere-ocean model experiment performed at Deutsches Klimarechenzentrum, Germany, is adopted for the study. The adopted scenario represented an increase in monsoon seasonal mean surface temperature of the order of about 1.5°C, and an increase in rainfall of the order of 2 mm per day, over the state of Kerala in the decade 2040–2049 with respect to the 1980s. The IPCC Business-as-usual scenario projection of plant usable concentration of CO₂ about 460 PPM by the middle of the next century are also used in the crop model simulation. On an average over the state with the climate change scenario studied, the rice maturity period is projected to shorten by 8% and yield increase by 12%. When temperature elevations only are taken into consideration, the crop simulations show a decrease of 8% in crop maturity period and 6% in yield. This shows that the increase in yield due to fertilisation effect of elevated CO₂ and increased rainfall over the state as projected in the climate change scenario nearly makes up for the negative impact on rice yield due to temperature rise. The sensitivity experiments of the rice model to CO₂ concentration changes indicated that over the state, an increase in CO₂ concentration leads to yield increase due to its fertilisation effect and also enhance the water use efficiency of the paddy. The temperature sensitivity experiments have shown that for a positive change in temperature up to 5°C, there is a continuous decline in the yield. For every one degree increment the decline in yield is about 6%. Also, in another experiment it is observed that the physiological effect of ambient CO₂ at 425 ppm concentration compensated for the yield losses due to increase in temperature up to 2°C. Rainfall sensitivity experiments have shown that increase in rice yield due to increase in rainfall above the observed values is near exponential. But decrease in rainfall results in yield loss at a constant rate of about 8% per 2 mm/day, up to about 16 mm/day.     

江西省早稻雨洗花灾害指标构建与灾损评估

构建早稻雨洗花灾害指标及适于早稻产量估算的灾损评估模型,对开展早稻雨洗花灾害监测、损失评估、灾害保险等具有重要意义。该文以江西省早稻为研究对象,利用1981-2015年14个水稻气象观测站逐日气象资料和农业气象观测资料,筛选出基于早稻抽穗扬花期间过程降水量、最大降水量、降水日数及实际产量的雨洗花灾害样本78个,在此基础上,利用相关分析、正态分布以及主成分回归法,建立了雨洗花灾害指标和灾损评估模型,并对其进行验证。结果表明:抽穗扬花期降水对雨洗花灾害形成有显著影响,其主要影响时段为抽穗扬花普遍期前后5 d内,关键时段为抽穗扬花普遍期前后3 d内。日降水量40 mm可作为早稻抽穗扬花期雨洗花灾害临界指标。以该指标为基础,统计日降水量不低于40 mm的降水日数及其对应的累积降水量,当累积降水量为40~170 mm时,为轻度雨洗花灾害,早稻一般减产小于15%,平均减产10%;当累积降水量不小于170 mm时,为重度雨洗花灾害,早稻一般减产不低于15%,平均减产22%。指标验证结果与历史实际灾害发生情况有较好的一致性。雨洗花灾损评估模型检验结果表明:雨洗花年模拟产量与实际产量吻合度较高,平均相对模拟误差为4.3%,78.0%的资料相对误差在5%以内,可利用该模型对雨洗花年的早稻减产率进行模拟和预测。     

Quantifying the value of historical climate knowledge and climate forecasts using agricultural systems modelling

A well tested agricultural systems model was used together with 114 years of historical climate data to study the performance of a dryland wheat–fallow system as impacted by climate variations and nitrogen input levels in southeast Australia, and to investigate the value of: (1) historical climate knowledge, (2) a perfect climate forecast, and (3) various forecasts of targeted variables. The potential value of historical climate records increases exponentially with the number of years of data. In order to confidently quantify the long term optimal nitrogen application rate at the study site at least 30 years of climate data are required. For nitrogen management only, the potential value of a perfect climate forecast is about $54/ha/year with a reduction of excess nitrogen application of 20 kg N/ha/year. The value of an ENSO based forecast system is $2/ha/year. Perfect forecasting of three or six categories of growing season rainfall would have a value of $10–12/ha/year. Perfect forecasts of three or six categories of simulated crop yield would bring about $33–34/ha/year. Choosing integrated variables as a forecasting target, for example crop yield derived from agricultural modelling, has the potential to significantly increase the value of forecasts.     

北上台风强降水形成机制及微物理特征

利用NCEP FNL分析资料、青岛降水现象仪和双偏振雷达观测资料,对北上台风利奇马(1909)和巴威(2008)引发的局地对流性强降水微物理特征进行分析,结果表明:在台风外围的东南暖湿气流内,受地形或边界层锋区触发形成的强对流单体后向传播或原地合并加强造成了局地强降水;雨滴的质量加权平均直径(Dm)和对数归一化浓度(l...     

Quantitative evaluation of climatic variability and risks for wheat yield in India

This study comprises (1) an analysis of recent climate trends at two sites in north-west India (Ludhiana in Punjab and Delhi) and (2) an impact and risk assessment for wheat yields associated with climatic variability. North-west Indian agriculture is dominated by rice-wheat rotation in which the wheat season (‘rabi’, November to March) is characterized by predominantly dry conditions—superimposed by very high inter-annual variability of rainfall (17 to 260 mm in Ludhiana and <1 to 155 mm in Delhi). While rainfall remained without discernable trend over the last three decades, minimum and average temperatures showed increasing trends of 0.06 and 0.03°C year^???1, respectively, at Ludhiana. The site in (metropolitan) Delhi was apparently influenced by city-effects, which was noticeable from the decrease in solar radiation of 0.09 MJ m^???2 day^???1 year^???1. The CERES-wheat model was used to calculate yields of rainfed wheat that were at both locations highly correlated with seasonal rainfall. An assessment framework was developed to quantify yield impacts due to rainfall variability in three steps: (1) data from different years were aggregated into four classes, i.e., years with scarce, low, moderate, and high rainfall, (2) yield records of each rainfall class were ranked according to yield to facilitate (3) a comparison of yields with identical rank, i.e. among the best yield of each class, the second-best, etc. The class with moderate rainfall was taken as baseline yield to compute yield impacts of other rainfall scenarios. Years with scarce rainfall resulted in only 34% (Ludhiana) and 35% (Delhi) of the baseline yield. The yields in years with low rainfall accounted for 61% (Delhi) and 49% (Ludhiana) of the baseline yields. In Ludhiana, high rainfall years resulted in 200% yield as compared to the baseline yield, whereas they reached only 105% in Delhi. Low-intensity (1× and 3×) irrigation decreased the relative yield losses, but entailed a higher vulnerability in terms of absolute yield losses. Only high-intensity (4×) irrigation buffered wheat yields against adverse rainfall years. Early sowing was beneficial for wheat yields under all rainfall scenarios. The framework could be a valuable decision-support tool at the farm level where seasonal rainfall variability is high.     

TRMM卫星对青藏高原东坡一次大暴雨强降水结构的研究

利用热带测雨卫星（TRMM）探测资料,NCEP、ERA-Interim再分析资料,结合C波段多普勒雷达和其他地面观测资料,研究了2013年7月21日发生在青藏高原东坡的一次大暴雨强降水结构。结果表明,高能、高湿的不稳定大气在700 hPa切变线及地面辐合线的触发下产生了此次大暴雨,降水具有明显的强对流性质。从水平结构来看,降水系统由成片的层云雨团中分散分布的多个对流性雨团组成,对流样本数远少于层云,但平均雨强是层云的4.7倍,对总降水的贡献达到25.6%;以超过10 mm/h雨强为强度标准,3个20-50 km、回波强度在45-50 dBz的β中尺度对流雨团零散地分布在主雨带中,对应 < 210 K的微波辐射亮温区和≥ 32 mm/h的地面强降水;对流降水的雨强谱集中在1-50 mm/h,其中20-30 mm/h的雨强对总雨强的贡献最大,这与中国东部降水有着显著区别,而90%的层云降水的雨强均小于10 mm/h。从垂直结构来看,对流降水云呈柱状自地面伸展,平均雨顶高度随地面雨强的增强而不断升高（5-12 km）,强降水中心区域的质心在2-6 km;降水廓线反映出强降水系统中降水主要集中在6 km以下高度范围,且降水强度在垂直方向分布不均匀,对流降水和层云降水的强度随高度升高的总趋势是趋于减弱,但在一定高度范围内,对流降水强度随高度升高而增大,并且在多个地表雨强廓线中都有体现。此外,地基雷达的探测结果也表明了强降水的低质心特点及显著的逆风区演变特征,这是对TRMM PR探测的验证和补充。      

我国地面降水的分级回归统计降尺度预报研究

利用TIGGE资料中欧洲中期天气预报中心(ECMWF,the European Centre for Medium-Range Weather Forecasts)、日本气象厅(JMA,the Japan Meteorological Agency)、美国国家环境预报中心(NCEP,the National Centers for Environmental Prediction)以及英国气象局(UKMO,the UK Met Office)4个中心1~7 d预报的日降水量集合预报资料,并以中国降水融合产品作为"观测值",对我国地面降水量预报进行统计降尺度处理。采用空间滑动窗口增加中雨和大雨雨量样本,建立分级雨量的回归方程,并与未分级雨量的统计降尺度预报进行对比。结果表明,对于不同模式、不同预报时效以及不同降水量级,统计降尺度的预报技巧改进程度不尽相同。统计降尺度的预报技巧依赖于模式本身的预报效果。相比雨量未分级回归,雨量分级回归的统计降尺度预报与观测值的距平相关系数更高,均方根误差更小,不同量级降水的ETS评分明显提高。对雨量分级回归统计降尺度预报结果进行二次订正,可大大减少小雨的空报。     

Impact assessment of climate change,carbon dioxide fertilization and constant growing season on rice yields in China

Rice is the staple food in China, and the country’s enlarging population puts increasing pressure on its rice production as well as on that of the world. In this study, we estimate the impact of climate change, CO₂ fertilization, crop adaptation and the interactions of these three factors on the rice yields of China using model simulation with four hypothetical scenarios. According to the results of the model simulation, the rice yields without CO₂ fertilization are predicted to decrease by 3.3 % in the 2040s. Considering a constant rice-growing season (GS), the rice yields are predicted to increase by 3.2 %. When the effect of CO₂ fertilization is integrated into the Agro-C model, the expected rice yields increase by 20.9 %. When constant GS and CO₂ fertilization are both integrated into the model, the predicted rice yield increases by 28.6 %. In summary, the rice yields in China are predicted to decrease in the 2040s by 0.22 t/ha due to climate change, to increase by 0.44 t/ha due to a constant GS and to increase by 1.65 t/ha due to CO₂ fertilization. The benefits of crop adaptation would completely offset the negative impact of climate change. In the future, the most of the positive effects of climate change are expected to occur in northeastern and northwestern China, and the expansion of rice cultivation in northeastern China should further enhance the stability of rice production in China.