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.     

Tropospheric Wet Refractivity Tomography Based on the BeiDou Satellite System简

This paper presents a novel approach for assessing the precision of the wet refractivity field using BDS （BeiDou navigation satellite system） simulations only,GPS,and BDS＋GPS for the Shenzhen and Hongkong GNSS network.The simulations are carried out by adding artificial noise to a real observation dataset.Instead of using the δ and σ parameters computed from slant wet delay,as in previous studies,we employ the Bias and RMS parameters,computed from the tomography results of total voxels,in order to obtain a more direct and comprehensive evaluation of the precision of the refractivity field determination.The results show that：（1） the precision of tropospheric wet refractivity estimated using BDS alone （only 9 satellites used） is basically comparable to that of GPS; （2） BDS＋GPS （as of current operation） may not be able to significantly improve the data＇s spatial density for the application of refractivity tomography; and （3） any slight increase in the precision of refractivity tomography,particularly in the lower atmosphere,bears great significance for any applications dependent on the Chinese operational meteorological service.     

An Overview of BCC Climate System Model Development and Application for Climate Change Studies

This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model(BCC-CSM) and its four component models(atmosphere,land surface,ocean,and sea ice).Two recent versions are described:BCC-CSM1.1 with coarse resolution(approximately 2.8125°×2.8125°) and BCC-CSM1.1(m) with moderate resolution(approximately 1.125°×1.125°).Both versions are fully coupled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation.Both models well simulate the concentration and temporal evolution of atmospheric CO_2 during the 20th century with anthropogenic CO2 emissions prescribed.Simulations using these two versions of the BCC-CSM model have been contributed to the Coupled Model Intercomparison Project phase five(CMIP5) in support of the Intergovernmental Panel on Climate Change(IPCC) Fifth Assessment Report(AR5).These simulations are available for use by both national and international communities for investigating global climate change and for future climate projections.Simulations of the 20th century climate using BCC-CSMl.l and BCC-CSMl.l(m) are presented and validated,with particular focus on the spatial pattern and seasonal evolution of precipitation and surface air temperature on global and continental scales.Simulations of climate during the last millennium and projections of climate change during the next century are also presented and discussed.Both BCC-CSMl.l and BCC-CSMl.l(m) perform well when compared with other CMIP5 models.Preliminary analyses indicate that the higher resolution in BCC-CSM1.1(m) improves the simulation of mean climate relative to BCC-CSMl.l,particularly on regional scales.     

北京气候中心气候系统模式研发进展——在气候变化研究中的应用

较全面地介绍了北京气候中心气候系统模式(BCC_CSM)研发所取得的一些进展及其在气候变化研究中的应用,重点介绍了全球近280 km较低分辨率的全球海-陆-气-冰-生物多圈层耦合的气候系统模式BCC_CSM1.1和110 km中等大气分辨率的BCC_CSM1.1(m),以及大气、陆面、海洋、海冰各分量模式的发展。BCC_CSM1.1和BCC_CSM1.1(m)气候系统模式均包含了全球碳循环和动态植被过程。当给定全球人类活动导致的碳源排放后,就可以模拟和预估人类活动对气候变化的影响。BCC_CSM1.1和BCC_CSM1.1(m)已应用于IPCC AR5模式比较,为中外开展气候变化机理分析和未来气候变化预估提供了大量的试验数据。还介绍了BCC_CSM1.1和BCC_CSM1.1(m)参与国际耦合模式比较计划(CMIP5)的大量试验分析评估结果,BCC_CSM能够较好地模拟20世纪气温和降水等气候平均态和季节变化特征,以及近1000年的历史气候变化,所预估的未来100年气候变化与国际上其他模式的CMIP5试验预估结果相当。初步的分析表明,分辨率相对高的BCC_CSM1.1(m)在区域气候平均态的模拟上优于分辨率较低的BCC_CSM1.1。     

Preface to Special Issue on Climate Science for Service Partnership China

正This special issue of Advances in Atmospheric Sciences provides a selection of research highlights from the Climate Science for Service Partnership China(CSSP China).This pioneering partnership between China and UK based researchers has broken new ground in the development of climate science for services.By accelerating and enhancing collaborative science,CSSP China has built a strong foundation for services to support climate and weather resilient economic development     

2016年汛期中国降水极端特征及与1998年对比

本文利用国家气象信息中心提供的1961—2016年全国2341个气象观测站日和小时降水量资料,分析了2016年中国汛期降水的极端特征,并与1998年进行比较。主要结论如下：2016年汛期全国平均降水量为1961年以来历史同期最多,共有140站汛期降水量突破1961年以来历史同期极大值,有112站出现历史次极大值,比1998年分别偏多54和47站。1998年降水极值主要出现在东北和长江中上游地区,2016年主要出现在华东地区,而且范围更加集中。共出现6972站次暴雨,其中大暴雨1251站次,为1961年以来最多。44次大范围暴雨过程持续时间达90 d,总体呈现“中间强、前后弱”的特征。有417站出现日降水量极端事件,其中88站突破历史纪录,创1961年以来新高;最大小时降水量共有113站突破历史极值,比1998年偏多29站。从空间分布来看,日降水量极端事件2016年主要位于华东和华北地区,1998年集中在中部地区;破纪录小时降水2016年主要在西部地区,而1998年东部地区更为突出。     

1961—2012年中国冬半年霾日数的变化特征及气候成因分析

利用全国664站1961—2012年逐日霾观测资料、降水量、平均风速和最大风速资料,分析中国霾日数变化特征及其气候成因。结果表明：我国年霾日数分布呈明显东多西少特征,中东部大部地区年霾日数在5～30 d,部分地区超过30 d,西部地区基本在5 d以下。霾日数主要集中在冬半年,冬季最多,秋季和春季次之,夏季最少,12月是霾日数最多的月份,约占全年霾日数的2成。我国中东部地区冬半年平均霾日数呈显著的增加趋势（1.7 d/10a）,霾日数显著增加时段主要在1960年代、1970年代和21世纪初,在1970年代初和21世纪初发生了明显均值突变。从区域分布来看,华南、长江中下游、华北等地霾日数呈增加趋势,而东北、西北东部、西南东部霾日数呈减少趋势。持续性霾过程增加,持续时间越长的霾过程比持续时间短的霾过程增加更为明显。不利的气候条件加剧了霾的出现。霾日数与降水日数在中东部地区基本以负相关为主,中东部冬半年降水日数呈减少趋势（-4 d/10a）,表明降水日数的减少导致大气对污染物的沉降能力减弱。另一方面,霾日数与平均风速和大风日数以负相关为主,而与静风日数则以正相关为主,冬半年平均风速和大风日数减小,静风日数增加,表明风速减小导致空气中污染物不易扩散,从而更易形成霾天气。     

Analysis of extreme low-temperature events during the warm season in Northeast China

The trends of global warming are increasingly significant, especially in the middle and high latitude regions of the northern hemisphere, where the impact of climate change on extreme events is becoming more noticeable. Northeast China is located in a high latitude region and is sensitive to climate change. Extreme minimum temperatures causing cold damage during the warm season is a major type of agro-meteorological disaster in Northeast China, which causes serious reductions in crop yield. In this paper, we analyzed the temporal and spatial trends in the frequency of extreme minimum temperatures during the warm season (from May to September) during 1956–2005 in Northeast China. Abrupt climatic changes were identified using the Mann–Kendall test. The results show that the frequency of extreme minimum temperature days during the warm season in Northeast China decreases significantly from 1956 to 2005 with a background of climate warming. The highest number of extreme minimum temperature days occurred in the 1970s and 1980s, and there was an abrupt climatic change in 1993. The spatial analysis identified that the north and southeast of the region experienced a larger decrease in the number of extreme low temperature days than the west and south of the region. Rice, sorghum, corn, and soybeans are most vulnerable to cold damage. In severe low temperature years, the average crop yield was reduced by 15.2% in Northeast China.     

Construction and Application of a Climate Risk Index for China

In the context of global warming, China is facing with increasing climate risks. It is imperative to develop quantitative indices to reflect the climate risks caused by extreme weather/climate events and adverse climatic conditions in association with different industries. Based on the observations at 2288 meteorological stations in China and the meteorological disasters data, a set of indices are developed to measure climate risks due to water-logging, drought, high temperature, cryogenic freezing, and typhoon. A statistical method is then used to construct an overall climate risk index (CRI) for China from these individual indices. There is a good correspondence between these indices and historical climatic conditions. The CRI, the index of water-logging by rain, and the high temperature index increase at a rate of 0.28, 0.37, and 0.65 per decade, respectively, from 1961 to 2016. The cryogenic freezing index is closely related to changes in the consumer price index for food. The high temperature index is correlated with the consumption of energy and electricity. The correlation between the yearly growth in claims on household property insurance and the sum of the water-logging index and the typhoon index in the same year is as high as 0.70. Both the growth rate of claims on agricultural insurance and the annual growth rate of hospital inpatients are positively correlated with the CRI. The year-on-year growth in the number of domestic tourists is significantly negatively correlated with the CRI in the same year. More efforts are needed to develop regional CRIs.     

1998年长江流域特大洪水的降水分析

利用长江流域 (102°E以东) 125个站的实测降水资料, 分析了1998年夏季长江流域降水的时空分布和气候统计特征, 并与历史同期进行了比较, 特别是和1931、1954年等特大洪水年份进行了较全面的对比.结果表明, 1998年夏季长江流域的强降水主要分为4个时段; 总降水量的分布成不对称的鞍型场; 上、中、下游地区异常频繁的、特别集中的强降水是造成长江持续高水位和特大洪涝灾害的最主要原因.