Operational climate prediction in the era of big data in China: Reviews and prospects

Big data has emerged as the next technological revolution in IT industry after cloud computing and the Internet of Things. With the development of climate observing systems, particularly satellite meteorological observation and high-resolution climate models, and the rapid growth in the volume of climate data, climate prediction is now entering the era of big data. The application of big data will provide new ideas and methods for the continuous development of climate prediction. The rapid integration, cloud storage, cloud computing, and full-sample analysis of massive climate data makes it possible to understand climate states and their evolution more objectively, thus predicting the future climate more accurately. This paper describes the application status of big data in operational climate prediction in China; it analyzes the key big data technologies, discusses the future development of climate prediction operations from the perspective of big data, speculates on the prospects for applying climatic big data in cloud computing and data assimilation, and puts forward the notion of big data-based super-ensemble climate prediction methods and computerbased deep learning climate prediction methods.     

MJO Simulations by GAMIL1.0 and GAMIL2.0

GAMIL2.0 is the newly released version of the Grid-point Atmospheric Model of IAP LASG(GAMIL),in which the major modifications from GAMIL1.0 include an updated deep convection scheme and the incorporation of a two-moment bulk stratiform cloud microphysics scheme.This study evaluates the performances of both versions on Madden Julian Oscillation(MJO) simulations.The results show that GAMIL2.0 obtains an enhanced MJO eastward and northward propagation,which is weak in GAMIL1.0,and it reproduces a more reasonable MJO major structure coupling upper level wind,lower level wind,and outgoing long wave radiation.The contributions of each scheme and factor to the improvement of GAMIL2.0 simulations need further study.     

ANALYSIS OF THE CHARACTERISTICS OF RAINFALL AND LINEAR TREND IN MENGLUN, XISHUANGBANNA, SOUTHWEST CHINA

1 INTRODUCTIONAs one of the main factors affecting input and useof precipitation by forests, rainfall also makes adifference on partitioning of gross precipitation overthe canopy, equilibrium of water amount in river basinsand water cycling processes[1-4]…     

Changes in Water Use Efficiency Caused by Climate Change,CO2 Fertilization,and Land Use Changes on the Tibetan Plateau

Terrestrial ecosystem water use efficiency(WUE) is an important indicator for coupling plant photosynthesis and transpiration, and is also a key factor linking the carbon and water cycles between the land and atmosphere. However,under the combination of climate change and human intervention, the change in WUE is still unclear, especially on the Tibetan Plateau(TP). Therefore, satellite remote sensing data and process-based terrestrial biosphere models(TBMs) are used in this study to investigate ...     

甘肃中部雨养农业区土壤水分预测模式的研究

采用联合国粮农组织（ＦＡＯ）最新推荐的计算农田蒸散量的彭曼－蒙蒂斯公式（ＦＡＯ－ＰＭ）,选取甘肃中部雨养农业区定西１９８０～１９９５年的常规气象资料和１９９０～１９９５年固定地段０～１００ｃｍ的土壤湿度资料,对水平衡和Ｙ．Ｍ安格斯坦土壤水分预测模式进行对比分析,认为后者适宜于本地区的土壤水分预测,并分析了误差原因     

内蒙古乡镇精细化预报模型及业务试验

文章利用县级台站天气实况插值生成乡镇天气实况资料库进而建立乡镇MOS预报方程的处理方法,建立了内蒙古1242个乡镇及一般风景点24小时天气要素精细化客观预报模型,并建成了业务化系统进行了业务试验运行。预报效果检验表明,这一方法是一种可行的精细化预报研制技术,其预报效果明显好于中央台精细预报指导产品,个别要素甚至略好于人工订正产品,完全可以应用于业务工作中。     

呼和浩特市秋季一次大到暴雨天气过程分析

利用天气预报业务中的多种预报产品资料,对2008年9月21日呼和浩特地区秋季一次降水过程进行了分析,结果表明:(1)太平洋副高西伸,地面西南倒槽是本次降水形成的主要影响系统。(2)700hPa西南低空急流的形成与地面倒槽东移北上共同为降水提供了暖湿能量,对降水的形成发展起了重要作用。(3)在降水过程中,大气的高层辐散、低层辐合以及较强的垂直上升运动使降水加强。     

太阳活动变化的小波分析

结合太阳活动变化分析,介绍了Morlet小波变换方法在气象时间序列周期分析和突变分析中的应用,对太阳黑子活动得出了一些有意义的结果。分析发现,太阳活动存在14.5 a和106 a的变化周期,其中14.5 a周期最为显著。太阳活动强弱变化存在一定的阶段性,在近258 a发生过6次突变。     

呼和浩特市夏季降水与影响因子的相关分析

利用呼和浩特市南郊1961-2008年夏季降水资料与海温、亚洲季风、西太平洋副热带高压和东亚阻塞高压等因子进行相关分析,结果表明：这些因子的异常变化,可以作为呼和浩特市南郊夏季降水的预测信号。     

气象卫星及其产品在天气气候分析和环境灾害监测中的应用概述

随着气象卫星技术的发展,卫星观测能力不断提升,全球气象卫星观测体系逐步形成。美国、欧洲和中国都建立了极轨和静止气象卫星观测系统,日本、韩国等国家也拥有各自的气象卫星。与卫星发展初期相比,现在的气象卫星在空间分辨率、时间分辨率、光谱分辨率以及波段覆盖范围等方面都有了极大的提高。与之相伴,气象卫星遥感资料应用也取得了长足的进步。卫星应用领域不断拓展,新的资料处理方法不断涌现,数据使用也完成了从定性向定量的跨越。本文将在总结目前气象卫星遥感载荷观测能力的基础上,着重介绍卫星资料在天气分析、环境灾害监测以及气候变化研究方面的应用。