区域气候变化监测与检测学术研讨会在哈尔滨召开

2011年8月18—20日,由中国气象学会气候变化专业委员会、中国气象局气候研究开放实验室、南京信息工程大学和黑龙江省气象局联合举办的"区域气候变化监测与检测学术研讨会"在黑龙江省哈尔滨市隆重召开。来自北京大学、北京师范大学、南京信息工程大学、中国海洋大学、中国科学院大气物理研究所、国家气候中心、中     

与时俱进 成就斐然——丁裕国教授

丁裕国教授,江办人,1941年出生于江苏省镇江市。1964年南京大学毕业后分配到南京气象学院（后更名为南京信息工程大学）任教,长期从事气候学研究与教学。曾任气象系气候教研室主任多年;先后讲授《气候统计学》、《气候变化》、《气象时间序列谱分析》、《气候诊断与预测》等课程,指导和培养硕士生30多人。曾任中国气象学会统计气象专业委员会暨江苏省气象学会统计气象专业委员会及出版委员会委员等职。     

抓住机遇加快陕西省气象培训现代化建设

1气候概率分布理论及其应用新进展 《气象科技》2009年第3期 丁裕国 南京信息工程大学大气科学学院210044 摘要：随着全球变暖加剧,气候变化的研究不断深入,有关气候概率分布理论及其应用研究不但增加了许多新的内涵,而且有了长足的发展。对于给定时段来说,概率分布可以全面描述某一气候变量观测取值的频率特征,而一旦概率分布发生变动,则必然可从中检测出气候变化的信号。文章从观测资料的分布拟合,气候概率分布的形成机制,     

短期气候预测:南京信息工程大学60年回顾与展望

本文从科学发展角度回顾了国内外短期气候预测的发展历程;在此基础上,回顾了南京信息工程大学建校60 a来短期气候预测领域的团队建设及其在教学、科研和预测方面的实践,并展望其未来工作。     

国家气候中心暨气候研究开放实验室2008年度学术年会在京召开

2009年2月12—13日,中国气象局国家气候中心暨气候研究开放实验室2008年度学术年会在京召开。来自北京大学、南京大学、南京信息工程大学、成都信息工程学院等高校,中国科学院大气物理研究所、地理科学与资源研究所、南京地理与湖泊研究所、青藏高原研究所以及中国农业科学研究院农业环境与可持续发展研究所等科研院所,中国气象局国家气候中心、国家卫星气象中心、国家气象中心、国家信息中心、培训中心、中国气象科学研究院,以及有关省（区）市气象局的专家及研究生,共计40余个单位100多位代表参加了学术年会。     

中国气象局国家气候中心暨气候研究开放实验室2007年度学术年会召开

2008年2月25—26日,“中国气象局国家气候中心暨气候研究开放实验室2007年度学术年会”在北京召开。来自北京大学、南京大学、南京信息工程大学,北京师范大学等高校,中国科学院大气物理研究所、寒区旱区环境与工程研究所,地理科学与资源研究所等科研院所,中国气象局国家气候中心、国家气象中心、国家气象信息中心,以及中国气象局有关省、市、     

NUIST地球系统模式模拟ENSO对西北太平洋热带气旋活动的影响

地球系统模式已经逐步成为研究热带气旋(TC)活动气候变化的重要工具之一,之前的研究发现南京信息工程大学地球系统模式(NESM)高分辨率版本可以较好地模拟全球海温分布及TC活动的气候特征.本研究进一步分析了NESM地球系统模式模拟西北太平洋TC活动的年际变化,并与1967～2016年观测的TC活动进行对比.NESM模式高...     

长江三角洲近百年来气候跃变的诊断分析

本文利用1905—1990年南京,上海两站的温度和降水资料分析了长江三角洲近百年来的气候变化情况,提出了用方差分析方法来讨论近百年来的气候跃变,并得到与Yamamoto所用“信噪比”方法研究气候跃变相一致的结论,为探讨区域性气候变异作了初步的尝试。     

全国各省市气象科技期刊文章摘要(35)

1 气候概率分布理论及其应用新进展 <气象科技>2009年第3期 丁裕国 南京信息工程大学大气科学学院 210044     

气候系统预测:基础创新和集成应用

随着全球变暖,极端天气气候事件增强,天气气候灾害造成的损失也愈发严重。当前气候预测的准确性远远不能满足社会需要,气候系统预测理论和方法面临着众多挑战性问题。为提档气候预测科学水平和准确率,由南京信息工程大学和中山大学承担的“气候系统预测研究中心”获得国家自然科学基金基础科学中心项目支持(2021年1月—2025年12月)。在该项目执行的前三年,项目团队开展了大量深入系统的研究,并取得了若干重要进展:1)揭示了气候系统的若干关键变化、驱动力和机制;2)剖析了海-陆-冰-气相互作用对我国重大极端气候事件的影响;3)在气候系统数值模式研发和预测系统集成方面取得重要进展;4)发展了延伸期-S2S-年代际的气候系统预测理论和方法。本文对这些进展作了扼要介绍,并针对气候与环境变化归因、古今气候环境研究融合、跨时空气候系统变异和极端气候、人工智能与气候科学、年代际预测和风险应对体系等关键科学问题做了展望。     

气候学与中国古代的辩证思想

该文强调科学指导思想的重要性，讨论了中国古代气候知识中的辩证思想，并指出现代气候问题中的辩证性质，最后，根据西文学者对中国古代科学思想的高度评价，论述气候学面临的新机遇。     

西北太平洋热带气旋气候变化的若干研究进展

热带气旋气候变化研究不仅是当前国际热带气旋气候界的热点科学问题,而且也是具有现实意义的社会问题,各国气象学者和科学家们对此进行了广泛的研究。虽然热带气旋活动与气候变化之间的关系及其相应的内在物理机制至今还处在探究之中,但是近20多年来热带气旋气候学的研究还是取得了显著的进展。本文主要针对濒临中国的西北太平洋海域,回顾了热带气旋活动季节内、年际、年代际变化及其全球变暖背景下的变化趋势的气候学研究。此外,文中也对西北太平洋热带气旋气候学的研究进行了展望,并提出了该领域中一些亟待解决的科学问题。     

广东省气象部门应对气候变化工作的进展、问题与对策

介绍广东气象部门应对气候变化工作在组织管理、观测系统和业务体系建设,决策和公众服务,科研和技术开发,科普宣传和合作交流等方面取得了一定进展。但也存在着诸如人才匮乏、经费不足、基础气候资料质量不高、业务体系建设不完善、影响评估和适应措施研究薄弱等问题。认为加强应对气候变化工作,应采取大力发展气候变化研究和业务、加强应对气候变化决策服务、成立专门业务机构、拓宽科研经费筹措渠道、加强气候变化科普宣传等对策与措施。     

Representativeness of Four Precipitation Observational Networks of China

Four precipitation observational networks with varied station densities are maintained in China. They are: the Global Climate Observation System (GCOS) Surface Network (GSN), the national Reference Climate Network (RCN), the national Basic Meteorological Network (BMN), and the national Ordinary Meteorological Network (OMN). The GSN, RCN, BMN, and the merged network of RCN and BMN (R&B) have been widely used in climatology and climate change studies. In this paper, the impact of the usage of different networks on the precipitation climatology of China is evaluated by using the merged dataset of All Station Network (ASN) as a benchmark. The results show that all networks can capture the main features of the country average precipitation and its changing trends. The differences of average annual precipitation of the various networks from that of the ASN are less than 50 mm ( 10%). All networks can successfully detect the rising trend of the average annual precipitation during 1961-2009, with the R&B exhibiting the best representativeness (only 2.90% relative difference) and the GSN the poorest (39.77%). As to the change trends of country average monthly precipitation, the networks can be ranked in descending order as R&B (1.27%), RCN (2.35%), BMN (4.17%), and GSN (7.46%), and larger relative differences appear from August to November. The networks produce quite consistent spatial patterns of annual precipitation change trends, and all show an increasing trend of precipitation in Northwest and Southeast China, and a decreasing trend in North China, Northeast China, and parts of central China. However, the representativeness of the BMN and R&B are better in annual and seasonal precipitation trends, in spite of the fact that they are still far from satisfactory. The relative differences of trends in some months and regions even reach more than 50%. The results also show that the representativeness of the RCN for country average precipitation is higher than that of the BMN because the RCN has a more homogeneous distribution of stations.     

非线性时间序列分析在气候中的应用研究进展

非线性时间序列分析方法在气候领域中的应用主要包括如下三个方面:观测数据处理、气候突变和气候预测.综述众多文献的结果表明,有许多学者为非线性时间序列分析方法在气候领域中的应用做了大量的工作,大部分文章用到了非线性时间序列分析方面较新的方法,几乎每种方法都能在某个方面取得一定的成功.但这些大多是个例的研究,得出的结论有待更多的验证和理论上更系统的阐述;可用于业务预测且可提高预报技巧的方法仍需探求.非线性时间序列分析在气候中的应用还是任重而道远.     

乌鲁木齐南山中山带气候特征分析

对乌鲁木齐南山中山带的气候资料进行了分析，总结出主要气候特征。     

Evaluation of the CORDEX regional climate models performance in simulating climate conditions of two catchments in Upper Blue Nile Basin

This study was targeted at evaluating the performance of six Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX). The evaluation is on the bases of how well the RCMs simulate the seasonal mean climatology, interannual variability and annual cycles of rainfall, maximum and minimum temperature over two catchments in western Ethiopia during the period 1990–2008. Observed data obtained from the Ethiopian National Meteorological Agency was used for performance evaluation of the RCMs outputs. All Regional Climate Models (RCMs) have simulated seasonal mean annual cycles of precipitation with a significant bias shown on individual models; however, the ensemble mean exhibited better the magnitude and seasonal rainfall. Despite the highest biases of RCMs in the wet season, the annual cycle showed the prominent features of precipitation in the two catchments. In many aspects, CRCM5 and RACMO22 T simulate rainfall over most stations better than the other models. The highest biases are associated with the highest error in simulating maximum and minimum temperature with the highest biases in high elevation areas. The rainfall interannual variability is less evident in Finchaa with short rainy season experiencing a larger degree of interannual variability. The differences in performance of the Regional Climate Models in the two catchments show that all the available models are not equally good for particular locations and topographies. In this regard, the right regional climate models have to be used for any climate change impact study for local-scale climate projections.     

The use of a climate-type classification for assessing climate change effects in Europe from an ensemble of nine regional climate models

Making use of the Köppen–Trewartha (K–T) climate classification, we have found that a set of nine high-resolution regional climate models (RCM) are fairly capable of reproducing the current climate in Europe. The percentage of grid-point to grid-point coincidences between climate subtypes based on the control simulations and those of the Climate Research Unit (CRU) climatology varied between 73 and 82%. The best agreement with the CRU climatology corresponds to the RCM “ensemble mean”. The K–T classification was then used to elucidate scenarios of climate change for 2071–2100 under the SRES A2 emission scenario. The percentage of land grid-points with unchanged K–T subtypes ranged from 41 to 49%, while those with a shift from the current climate subtypes towards warmer or drier ones ranged from 51 to 59%. As a first approximation, one may assume that in regions with a shift of two or more climate subtypes, ecosystems might be at risk. Excluding northern Scandinavia, such regions were projected to cover about 12% of the European land area.     

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

A coupled earth system model(ESM) has been developed at the Nanjing University of Information Science and Technology(NUIST) by using version 5.3 of the European Centre Hamburg Model(ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean(NEMO), and version 4.1 of the Los Alamos sea ice model(CICE). The model is referred to as NUIST ESM1(NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific(CP)-ENSO and eastern Pacific(EP)-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation(MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version(T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.     

自然气候变异与人为气候变化对径流影响研究进展

 在回顾IPCC于1990-2007年4次关于气候变化对径流影响的评估报告进展的基础上,将第一次与第二次评估报告归纳为第一代--以气候均值变化对径流影响及其适应为主要特征;第三次与第四次评估报告为第二代--突出人为气候变化与自然气候变异对径流影响及其适应问题,分析了常规的气候变化对水文水资源影响评估方法的发展过程及存在的问题。研究结果反映了年代际时间尺度的自然气候变异的影响,而未能考虑与极端事件发生频次和强度变化密切相联的日、季和年际尺度的气候变异的影响,从而低估了气候变暖对洪水、干旱以及农业灌溉需水的负面作用。在介绍国内外研究的基础上,为第五次IPCC评估报告提出了加强交叉学科综合研究的建议。