气候变化对延伸期预报的影响

10～30 d时效的延伸期预报,作为无缝隙预报预测体系中至关重要的一环,连接着天气预报和短期气候预测。受不断加剧的气候变化的影响,延伸期预报将面临更为重大的挑战。首先概述国内外延伸期预报现状,然后分析了全球气候变化对极端天气气候事件分布特征、关键环流系统可预报性等方面的影响,发现气候变化将导致延伸期预报难度加大、需求更加旺盛,同时也更加突显延伸期预报在防灾减灾方面的作用。进一步展望延伸期预报将面临的新挑战以及未来业务发展的新动向,提出了适应气候变化的应对措施和建议,如大力发展数值预报模式、深入开展延伸期预报机理研究、大力发展动力—统计相结合的预报方法以及尝试多学科交叉协作等。     

极端天气气候事件指标体系研讨会暨项目进展会召开

2009年4月10-11日,"极端天气气候事件指标体系研讨会"暨科技部"十一五"支撑重点项目"我国主要极端天气气候事件及重大气象灾害的监测、检测和预测关键技术研究"项目进展会在江苏扬州市召开.     

把脉极端天气气候事件,构建预测方法

<正>极端天气气候事件是造成我国重大自然灾害的主要根源,并且在近年来有加重的趋势。暴雨、台风、持续性强降温、暴雪、高温热浪、重霾污染等都是全社会高度关注的,科学家们需要剖析形成这些极端天气气候事件的原因和科学过程、机理,并研究构建有效的科学预测方法,以达到防灾减灾的目的。     

克拉玛依特强大风的气候特征及天气分析与预报

分析1971—2006年克拉玛依11级以上特强大风天气的气候特征,总结了年代际变化及月、季分布特点。研究显示,在全球气候变暖造成极端天气事件明显增多的大气候背景下,克拉玛依特强大风天气呈明显减少趋势。在这种气候背景下,利用NCEP资料,分析了克拉玛依发生特强大风的主要天气形势特征,提出预报思路,给出预报经验指标,提高对特强大风的防范意识和预报能力     

关于复合型极端事件的新认识和启示

近年来,极端天气气候事件频繁发生,且常常表现为多种事件交织形成的复合型极端事件。为了更好地认识复合型极端事件,IPCC AR6基于现有的新证据评估了复合型极端事件的最新研究成果,并取得一些新认识：扩展了有关复合型极端事件的定义,重点围绕高温干旱复合型极端事件、复合洪水和野火,评估了复合型极端事件的变化特征,探讨了复合型极端事件多因子之间的依赖性,对人类活动的影响进行了归因分析并给出了未来可能的变化。这些评估结果丰富了对复合型极端事件的基本认识。但根据现有的评估可以发现,目前在复合型极端事件发生发展机理认识方面还存在不足;同时,未来仍需进一步完善跨学科跨部门跨区域研究,加强对复合型极端事件形成机理、预估及其对生态系统,经济社会影响风险的评估,提高对区域气候变化的适应能力。     

气候变暖背景下降水持续性与相态变化的研究综述

持续性降水和固态降水（或近地面气温为0℃左右的降水）都能导致洪涝和低温雨雪冰冻等灾害性的极端事件,对人民群众生命和财产安全以及社会经济发展也会造成严重危害。目前中外围绕降水量、极端降水事件变化等已开展了大量研究,但在降水持续性和相态变化的特征及其影响机理方面的研究仍显不足。因此,围绕降水持续性和相态变化的相关研究,对近20余年来取得的一些重要研究进展进行回顾。研究指出,在气候变暖背景下降水持续性和相态变化的特征在全球范围内表现出了区域上的不一致性。有关降水持续性变化方面,中国南方地区持续性降水过程及其产生的降水量呈现增多趋势,但北方地区呈现减少的趋势,而西南地区长持续性降水呈下降趋势。至于降水相态变化方面,中国南方地区持续性雨雪冰冻事件在气候变暖背景下总体呈减少趋势。这些变化除了与气候变暖有关外,可能还与大气遥相关模态、低频振荡及ENSO事件等引起的大气环流异常有关。今后应该更多开展气候变暖背景下降水持续性和相态变化的特征、可能机理以及其与气候变暖的可能联系方面的研究,以期通过相关研究深入理解中国降水持续性与相态变化的规律、成因及其与旱涝、低温雨雪灾害等的联系,进一步加深对气候变暖背景下中国天气、气候的影响及其机理的认识。      

江淮流域持续性极端降水及预报方法研究进展

持续性极端降水过程会引发严重的洪涝灾害,是我国主要的灾害性天气之一,其形成机理和预报理论与方法研究受到广泛关注。近年来,针对持续性极端降水的形成机理和预报方法研究取得了一系列进展,主要包括:开展了我国区域性持续性极端降水事件的自动识别方法研究,研制建立了江淮流域持续性极端降水的大尺度环流概念模型,并提取了1~2周的前兆信号;从东亚—太平洋遥相关型 (EAP) 角度探究其对持续性极端降水的影响机理,并探讨利用EAP对江淮流域持续性极端降水进行预报的可行性。此外,在上述研究的基础上发展了基于关键影响系统的持续性极端降水的物理统计预报方法。     

时空投影模型(STPM)的次季节至季节(S2S)预测应用进展

随着数值天气预报技术和季节动力预报系统的发展,短期天气预报及长期气候预测的能力持续提高,然而介于两者之间的次季节至季节(S2S,两周至三个月)预测技巧偏低,成为当今气象学界和业务服务的难题。南京信息工程大学国家特聘专家李天明教授团队于2012年研发了基于时空投影技术的统计预报模型(STPM),成功地对中国大陆降水和气温距平,以及区域极端降水、夏季高温、冬季低温和西太平洋台风群发事件等高影响天气进行提前10~30 d的预报,并在国家气候中心及多个省份开展了业务应用。STPM也成功应用于台湾春雨预报、南海季风爆发和ENSO预测等季节至年际变化的预测。本文对S2S预测的理论基础、STPM的发展和应用进行了完整的介绍,并讨论了S2S预测业务中所面临的挑战和未来展望。     

天气和气候极端事件的变化及其与全球变暖的联系——纪念2002年世界气象日“减低对天气和气候极端事件的脆弱性”

2002年3月23日世界气象日的主题是“减低天气和气候极端事件的脆弱性”。针对这个主题,作者对以下四方面问题作了阐述：（1）天气与气候极端事件以及脆弱性的定义;（2）近百年来全球天气与气候极端事件的变化及其与全球气候变化的关系;（3）未来天气与气候极端事件及其影响的预测;（4）天气与气候极端事件的适应与减缓对策。由于篇幅有限,未介绍中国在这方面的研究。     

区域气候模拟研究及其应用进展

区域气候模拟研究在过去十几年里取得了显著的进步。经过广泛的发展和不断的检验,区域气候模式现在已经成为气候研究和业务预报的重要工具。目前已经发表了很多令人鼓舞的结果,其中包括过去极端气候事件的模拟,当前气候发展演变和未来气候变化的预测,特别是对月和季节尺度气候的模拟与预测。通过对高分辨率和动力连续的区域气候模式结果的分析,人们对于周-季节时间尺度的各种物理过程,包括陆面和水文过程、边界层、云和降水、云-辐射相互作用的认识也在不断的深入。然而,区域气候是多尺度扰动(如中尺度、天气尺度、行星尺度扰动)和多圈层系统(如大气圈、生物圈、水圈、冰雪圈、陆面)相互作用的结果,同时物理过程本身具有不确定性,人们对一些复杂的物理过程,特别是土壤湿度作用以及云-气候反馈过程也缺乏深刻的理解,因此该领域的研究还面临着很多挑战。作者重点总结并评述了区域气候模式对现在和未来区域气候模拟、极端天气和气候事件模拟、物理过程研究、短期气候预测几方面应用的研究进展,最后讨论了区域气候模式发展在上述各方面,特别是周-次季节时间尺度区域天气和气候的模拟与预测所面临的挑战和应用前景。     

全球变暖与城市效应共同作用下的极端天气气候事件变化的最新认知

近年来,城市气候变化问题引起高度关注.综合IPCC第一工作组第六次评估报告(IPCC AR6)关于气候变暖背景下城市对极端天气气候事件影响的评估,本文得到以下科学认识:城市化加剧了局部气候变暖,全球许多城市都面临更多更强的高温热浪事件;城市化使得诸多城市区域及其下风向极端降水增加,地表径流加强;沿海城市受到日益加剧的与...     

A Review of Climate Change Attribution Studies

This paper reviews recent progress in climate change attribution studies. The focus is on the attribution of observed long-term changes in surface temperature, precipitation, circulation, and extremes, as well as that of specific extreme weather and climate events. Based on new methods and better models and observations, the latest studies further verify the conclusions on climate change attribution in the IPCC AR5, and enrich the evidence for anthropogenic influences on weather and climate variables and extremes. The uncertainty of global temperature change attributable to anthropogenic forcings lies in the considerable uncertainty of estimated total radiative forcing due to aerosols, while the uncertainty of precipitation change attribution arises from the limitations of observation and model simulations along with influences from large internal variability. In terms of extreme weather and climate events, it is clear that attribution studies have provided important new insights into the changes in the intensity or frequency of some of these events caused by anthropogenic climate change. The framing of the research question, the methods selected, and the model and statistical methods used all have influences on the results and conclusions drawn in an event attribution study. Overall, attribution studies in China remain inadequate because of limited research focus and the complexity of the monsoon climate in East Asia. Attribution research in China has focused mainly on changes or events related to temperature, such as the attribution of changes in mean and extreme temperature and individual heat wave events. Some progress has also been made regarding the pattern of changes in precipitation and individual extreme rainfall events in China. Nonetheless, gaps remain with respect to the attribution of changes in extreme precipitation, circulation, and drought, as well as to the event attribution such as those related to drought and tropical cyclones. It can be expected that, with the continual development of climate models, ongoing improvements to data, and the introduction of new methods in the future, climate change attribution research will develop accordingly. Additionally, further improvement in climate change attribution will facilitate the development of operational attribution systems for extreme events, as well as attribution studies of climate change impacts.     

极端天气气候事件监测与预测研究进展及其应用综述

极端天气气候事件(简称"极端事件")分为单站极端事件和区域性极端事件。本文回顾了极端事件的研究进展,首先回顾了单站极端温度、极端降水和干旱事件的观测研究及相关指数,进而对近年来不断增多的区域性极端事件研究做了简要回顾,最后还回顾了极端事件气候预测研究进展。同时,对国内外在极端事件气候监测和预测业务现状进行了初步总结,并指出:在极端事件气候监测方面中国的业务产品较丰富,并率先开展了针对区域性极端事件的监测业务,但在产品表现形式上缺乏统一组织,特别是英文产品表现力严重不足;在极端事件气候预测方面,国家气候中心发展了两种方法:一个是基于物理统计的BP-CCA和OSR的干旱预测方法,另一个基于国家气候中心月动力延伸预报模式(DERF)的高温预测方法。最后,对极端事件监测和预测业务发展及相关科学问题给出展望,指出应根据极端事件的业务需求继续加强相关研究和业务能力建设。     

Identification Standard for ENSO Events and Its Application to Climate Monitoring and Prediction in China

The El Niño–Southern Oscillation (ENSO) reflects anomalous variations in the sea surface temperature (SST) and atmospheric circulation over the tropical central–eastern Pacific. It remarkably impacts on weather and climate worldwide, so monitoring and prediction of ENSO draw intensive research. However, there is not yet a unique standard internationally for identifying the timing, intensity, and type of ENSO events. The National Climate Center of China Meteorological Administration (NCC/CMA) has led the effort to establish a national identification standard of ENSO events, which was officially endorsed by the National Standardization Administration of China and implemented operationally in NCC/CMA in 2017. In this paper, two key aspects of this standard are introduced. First, the Niño3.4 SST anomaly index, which is well-recognized in the international ENSO research community and used operationally in the US, has replaced the previous Niño Z index and been used to identify the start, end, and peak times, and intensity of ENSO events. Second, two new indices—the eastern Pacific ENSO (EP) index and the central Pacific ENSO (CP) index, based on the SST conditions in Niño3 and Niño4 region respectively, are calculated to first determine the ENSO type before monitoring and assessing the impacts of ENSO on China’s climate. With this standard, all historical ENSO events since 1950 are consistently re-identified; their distinct properties are diagnosed and presented; and the impacts of ENSO events under different types on China’s climate are re-assessed. This standard is also employed to validate the intensity, grade, and type of the ENSO events predicted by the NCC/CMA operational ENSO prediction system. The new standard and the thus derived unified set of re-analyzed historical ENSO events and associated information provide a good reference for better monitoring and prediction of future ENSO events.     

Quantifying Changes in Extreme Weather Events in Response to Warmer Global Temperature

Global warming is expected to affect both the frequency and severity of extreme weather events, though projections of the response of these events to climate warming remain highly uncertain. The range of changes reported in the climate modelling literature is very large, sometimes leading to contradictory results for a given extreme weather event. Much of this uncertainty stems from the incomplete understanding of the physics of extreme weather processes, the lack of representation of mesoscale processes in coarse-resolution climate models, and the effect of natural climate variability at multi-decadal time scales. However, some of the spread in results originates simply from the variety of scenarios for future climate change used to drive climate model simulations, which hampers the ability to make generalizations about predicted changes in extreme weather events. In this study, we present a meta-analysis of the literature on projected future extreme weather events in order to quantify expected changes in weather extremes as a function of a common metric of global mean temperature increases. We find that many extreme weather events are likely to be significantly affected by global warming. In particular, our analysis indicates that the overall frequency of global tropical cyclones could decrease with global warming but that the intensity of these storms, as well as the frequency of the most intense cyclones could increase, particularly in the northwestern Pacific basin. We also found increases in the intensity of South Asian monsoonal rainfall, the frequency of global heavy precipitation events, the number of North American severe thunderstorm days, North American drought conditions, and European heatwaves, with rising global mean temperatures. In addition, the periodicity of the El Niño–Southern Oscillation may decrease, which could, in itself, influence extreme weather frequency in many areas of the climate system.     

Progress in the Study of Nonlinear Atmospheric Dynamics and Predictability of Weather and Climate in China (2007--2011)

Recent progress in the study of nonlinear atmospheric dynamics and related predictability of weather and climate in China (2007-2011) are briefly introduced in this article. Major achievements in the study of nonlinear atmospheric dynamics have been classified into two types:(1) progress based on the analysis of solutions of simplified control equations, such as the dynamics of NAO, the optimal precursors for blocking onset, and the behavior of nonlinear waves, and (2) progress based on data analyses, such as the nonlinear analyses of fluctuations and recording-breaking temperature events, the long-range correlation of extreme events, and new methods of detecting abrupt dynamical change. Major achievements in the study of predictability include the following:(1) the application of nonlinear local Lyapunov exponents (NLLE) to weather and climate predictability; (2) the application of condition nonlinear optimal perturbation (CNOP) to the studies of El Nin o-Southern Oscillation (ENSO) predictions, ensemble forecasting, targeted observation, and sensitivity analysis of the ecosystem; and (3) new strategies proposed for predictability studies. The results of these studies have provided greater understanding of the dynamics and nonlinear mechanisms of atmospheric motion, and they represent new ideas for developing numerical models and improving the forecast skill of weather and climate events.     

不同气候背景下我国冬夏两季极端气温特征分析

利用全国175个测站1960—1999年间的日平均气温资料,分别选取1960—1989年(气候态A)、1970—1999年(气候态B)作为气候背景,采用蒙特卡洛显著性检验法检验了这两个气候态背景下我国冬夏两季季节平均气温的差异显著性。并在此基础上利用气候百分位法分别分析了在这两个气候态背景下2000—2010年间我国冬夏两季的极端气温特征。分析结果表明,相对于夏季,冬季气候态A、B背景下季节平均气温的差异更为显著。冬夏两季,我国大部分地区极端低温事件的发生频率相对较低,而极端高温事件的发生频率相对较高。由于气候态B包含了全球变暖特征最为显著的20a,故在气候态B背景下,冬夏两季极端低(高)温事件的发生频率要高(低)于气候态A,这与全球变暖的趋势相吻合。     

新、旧气候态差异及对中国地区气候和极端事件评估业务的影响

利用1961—2020年中国区域2089个地面观测站资料,分析了1991—2020年和1981—2010年新、旧气候态下,平均气温、最高气温、最低气温和降水量等变量的空间变化特征,探讨对气候距平值、极端事件等评估结果的影响。结果表明：新气候态下,全国三类气温年和季节平均均一致升高,年降水增加,空间上气温偏高（低）、降水偏多（少）的特征将弱（强）化;华北东部、华东中部和北部以及青海西南部的年平均风速和日照时数距平增加;极端高温年减少,低温年增多,其中平均气温和最低气温受到的影响较最高气温更大;夏季南北方两条雨带极端强降水年的发生概率降低,冬季东北中部和南部、华北、华东北部、西北东部极端弱降水年概率显著增加;全国超过一半的站点极端日高温、低温和强降水事件的历史频次发生改变;新气候态还减弱了极端日高温事件的增速,加快了极端日低温事件的降速。     

近50年中国气温、降水极值分区的时空变化特征

在全球增暖背景下,当前极端天气气候事件频发,由此引发的气象灾害及其所带来的社会经济损失日益增加.深入了解与社会生活密切相关的气温和降水极值的特征,对开展防灾减灾工作有指导意义.文中用百分位阈值求算变量极值的概率密度值,从极值概率角度用系统聚类分析法合并站点,根据方差稳定性特征和变量最概然值的均值确定划分区域个数和对区域...