A review on statistical models for identifying climate contributions to crop yields

Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies, and have provided a common alternative to process-based models, which require extensive input data on cultivar, management, and soil conditions. However, very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields. This paper introduces three main statistical methods, i.e., time-series model, cross-section model and panel model, which have been used to identify such issues in the field of agrometeorology. Generally, research spatial scale could be categorized into two types using statistical models, including site scale and regional scale (e.g. global scale, national scale, provincial scale and county scale). Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models. The issues include the extent of spatial and temporal scale, non-climatic trend removal, colinearity existing in climate variables and non-consideration of adaptations. Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.     

用多变量灰色预测模型模拟预测参考作物蒸散量的研究

当观测资料的数据量少而又存在多个相互影响或关联的变量时,常用的灰色预测模型GM（1,1）不能全面考虑多个变量。为此,采用自适应MGM（1,n）模型—多变量灰色预测模型,较好地解决了这一问题。针对一些地区气象数据较少甚至缺失的情况,以内蒙古正蓝旗的气象资料用Penman-Monteith计算的参考作物蒸散量（ET0）为研究对象,运用灰色系统理论建立MGM（1,3）模型,模拟预测参考作物蒸散量变化规律,并与GM（1,1）模型和BP神经网络模型比较,结果表明MGM（1,3）模型有较好的预测效果。     

气候变化及其对农作物生产潜力的影响

利用国家气象中心整编的1951—1990年全国160站年、月平均气温和总降水量,的资料序列,计算和分析了我国近40年的气候变化,讨论了我国气候变化的区域性和季节性差异;计算了各站的年作物光温生产潜力,探讨了气象变化对农业生产的影响。     

农作物长势遥感监测业务化应用与研究进展

农作物长势监测可为田间管理提供及时的决策支持信息和早期估产提供依据。为了更好地研究作物生长过程中不同遥感监测作物长势方法的适用性,从多光谱遥感数据、高光谱遥感数据和微波遥感数据的应用及遥感监测指标与模型模拟方面综述了国内外农作物长势遥感监测研究及业务化应用的最新进展,指出了未来拟重点加强的研究任务,包括高时空分辨率和高光谱分辨率遥感数据的业务化技术、多遥感反演参数协同监测作物长势技术研发、基于遥感信息与作物过程模型的集合预报技术研究、全球尺度作物长势监测业务运行系统研发。     

2014年秋季长株潭城市群一次典型霾污染天气过程的气象特征及成因分析

利用长株潭地区地面空气质量监测资料、常规地面气象资料及NCEP再分析资料和MODIS火点监测资料,结合HYSPLIT4后向轨迹模式,对2014年10月1718日长株潭地区一次严重霾天气过程的空气污染特征和成因进行综合分析。研究表明,长株潭地区此次严重霾天气污染事件的主要污染物为PM2.5,安徽南部和江西西北部地区秸秆焚烧产生的颗粒物,经高空偏东北气流引导输送到长株潭地区,是这次大范围烟霾天气的主要来源。长株潭地区西部高空槽区宽广,槽前西南气流较为强盛,地面受均压场控制,水平风速弱,为严重霾污染天气的维持提供了有利的环流条件。中低层逆温和大气底层湿度的增加,使污染物粒子不断累积;近地面连续静（小）风和风向的频繁转变,不利于污染物粒子的水平扩散;中下层弱的下沉气流、较低的混合层高度有利于污染物的垂直累积,为此次重度霾污染天气的发展、加强提供了有利的气象条件。     

国家级现代农业气象业务技术进展

农业气象业务技术是开展农业气象服务的基础和前提,因此,农业气象业务技术的研发一直是国家级农业气象业务服务的核心工作。近年来,国家级农业气象业务技术已逐步迈向精细化、定量化,涵盖了农业气象监测评价、作物产量预报、农业气象灾害监测评估与影响预报、农用天气预报、农林病虫害发生发展气象等级预报等诸多领域。随着农业气象业务技术的发展,支撑农业气象服务的客观产品更加丰富和多样化,既有站点产品,又有格点产品,涵盖了日、周、月、季、年等不同时间尺度。以农业气象指标、数理统计模型、作物生长模拟、卫星遥感、地理信息系统、大数据等技术为核心的国家级农业气象业务平台（CAgMSS）已成为全国农业气象业务系统的重要品牌。面向现代农业发展对气象服务日益增长的需求,精细化、精准化的农业气象灾害监测与风险评估技术、作物长势评估与产量预报综合集成技术、农业应对气候变化技术以及农业气象大数据挖掘与人工智能技术将是未来国家级农业气象业务技术发展的重点。     

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS), which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China: one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.     

利用GVG线采样技术提取农作物种植面积及其精度分析

GVG(GIS&Video&GPS)线采样系统提出以线状样区代替以往成数抽样中的点样区与面积样区概念,通过统计线状样区内作物种植面积成数来反映区域总体农作物种植面积成数。通过 GVG实地采样,将其结果与解译遥感影像提取的作物种植面积成数结果进行了对比分析,结果显示采用GVG线采样方式精确度较高,其采样系统具有实用性和推广价值。     

影响我国主要粮食作物产量的气象因子研究

通过收集前人主要粮食作物气象产量预报的研究成果，将所得到的资料按作物进行分类，并进行归一化处理，使用系统聚类分析方法，以预报方程中的影响因子为指标，分区找出各区主要粮食作物产量的主、次要影响因子和影响时期，为大范围作物产量预报提供了科学依据。     

农作物产量对夏季累积高温的气候响应——以南京市为例

利用南京站1949—2008年逐日气温、逐月降水距平百分率资料及南京市统计年鉴数据,分析农作物产量对夏季累积高温的气候响应特征。结果表明：1949年以来南京市夏季累积高温呈波动上升趋势;最近60年（1949—2008年）和最近30年（1979—2008年）夏季累积高温的线性增长率分别为0.35℃/a和2.88℃/a;夏季累积高温与夏、秋粮产量均存在显著的负相关,相关系数分别为-0.66和-0.62,油料作物对夏季累积高温的变化也有一定的响应,但不如前两者显著,棉花产量对夏季累积高温变化不敏感。