Potential impacts of land-use on climate variability and extremes

This study aims at exploring potential impacts of land-use vegetation change (LUC) on regional climate variability and extremes. Results from a pair of Australian Bureau of Meteorology Research Centre (BMRC) climate model 54-yr (1949-2002) integrations have been analysed. In the model experiments, two vegetation datasets are used, with one representing current vegetation coverage in China and the other approximating its potential coverage without human intervention. The model results show potential impacts ...     

Spatial variability of rainfall: Variations within a single radar pixel

As a part of a Local Area Weather Radar (LAWR) calibration exercise 15 km south of Århus, Denmark, the variability in accumulated rainfall within a single radar pixel (500 by 500 m) was measured using nine high-resolution rain gauges. The measured values indicate up to a 100% variation between neighbouring rain gauges within the pixel over a 4-day period.     

Influence of spatial and temporal scales on statistical analyses of rainfall variability in the River Nile basin

In this study, empirical orthogonal function was applied to analyze rainfall variability in the Nile basin based on various spatio-temporal scales. The co-occurrence of rainfall variability and the variation in selected climate indices was analyzed based on various spatio-temporal scales. From the highest to the lowest, the cumulative amount of variance explained by the first two principal components (PCs) for any selected size of the spatial domain was obtained for the annual, seasonal, and monthly rainfall series respectively. The variability in the annual rainfall of 1° × 1° spatial coverage explained by only the first PC was about 55% on average. However, this percentage reduced to about 40% on average across the study area when the size of the spatial domain was increased from 1° × 1° to 10° × 10°. The variation in climate indices was shown to explain rainfall variability more suitably at a regional than location-specific spatial scale. The magnitudes and sometimes signs of the correlation between rainfall variability and the variation in climate indices tended to vary from one time scale to another. These findings are vital in the selection of spatial and temporal scales for more considered attribution of rainfall variability across the study area.     

Politics eclipses climate extremes for climate change perceptions

Whether or not actual shifts in climate influence public perceptions of climate change remains an open question, one with important implications for societal response to climate change. We use the most comprehensive public opinion survey data on climate change available for the US to examine effects of annual and seasonal climate variation. Our results show that political orientation has the most important effect in shaping public perceptions about the timing and seriousness of climate change. Objective climatic conditions do not influence Americans’ perceptions of the timing of climate change and only have a negligible effect on perceptions about the seriousness of climate change. These results suggest that further changes in climatic conditions are unlikely to produce noticeable shifts in Americans’ climate change perceptions.     

Satellite estimates and subpixel variability of rainfall in a semi-arid grassland

卫星估雨精度的不确定性受到当地降雨类型和像元内降雨非均匀性影响,而结合这两个关键因素开展半干旱草原卫星估雨的研究有限.2009年夏,我们在中国锡林郭勒半干旱草原用多部微雨雷达和雨量计构建了9 km卫星像元降雨观测网,观测了像元内降雨非均匀性(空间变异系数CV),并评估了卫星估雨精度.结果表明:(1)CV值受像元内平均降雨量,降雨类型,降雨云面积及移向等影响,如高Cv值的降雨过程大多为平均降雨量小,对流性降雨过程,降雨云边缘像元CV值较高;(2)TRMM 3B42V7卫星估雨产品适用性较好,CMORPH和PERSIANN次之,但TRMM 3B42V7易在半干旱草原湖泊处高估降雨.     

Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model

We analyse properties of a simple discrete multiplicative random cascade model for rainfall disaggregation in urban hydrology. Two types of cascade models (canonical and microcanonical) are applied to the stochastic fine graining of rainfall observations into high resolution data. In particular, we analyse the disaggregation of 1280-min into 10-min data for a 20-year record period (Zurich raingauge, 1979–1998). Differences between the models and parameter estimation techniques are explored on simulated data with a special focus on three important properties of observed rainfall: distribution, intermittency, and extremes. The canonical models are overall better at preserving the distribution of rainfall at the 10-min scale. It is demonstrated that the growth of intermittency across scales is preserved well with all studied models. The ability of the models to reproduce rainfall extremes is a fundamental requirement in disaggregation. The studied models preserved annual rainfall maxima satisfactorily for short durations; however, the performance deteriorated for longer durations. The canonical models performed substantially better in capturing the variability in rainfall. The results are encouraging considering the parsimonious nature of the models and simple parameter estimation.     

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.     

Analysis of rainfall variability over Tanzania in late austral summer

利用站点观测资料和再分析资料,采用相关分析,Morlet小波功率谱分析和复合分析等方法,研究了 1961-2011年南半球夏季后期(1-3月)坦桑尼亚降水的年际变化特征,并探讨了相关的大气环流和海温异常情况,以及坦桑尼亚干,湿年发生的机制.研究结果表明:坦桑尼亚1-3月降水变化存在显著的2-8年的年际变化周期和8-12...     

6.25 km高分辨率降尺度数据对雄安新区及整个京津冀地区未来极端气候事件的预估

基于RCP4.5情景下6.25 km高分辨率统计降尺度数据,使用国际上通用的极端气候事件指数,分析雄安新区及整个京津冀地区未来极端气候事件的可能变化。首先对当代模拟结果进行评估,结果表明,集合平均模拟可以较好地再现大部分极端气候事件指数的分布,且对与气温有关的极端气候事件指数模拟效果较好。但也存在一定偏差,特别是对连续干旱日数(CDD)的模拟效果相对较差。集合平均的预估结果表明,未来在全球变暖背景下,雄安新区及整个京津冀地区均表现为极端暖事件增多,极端冷事件减少,连续干旱日数减少,极端强降水事件增多。具体来看,到21世纪末期,日最高气温最高值(TXx)和日最低气温最低值(TNn)在整个区域上都是增加的,大部分地区增加值分别超过2.4℃和3.2℃;夏季日数(SU)和热带夜数(TR)也都表现为增加,但两者的变化分布基本相反,其中SU在山区增加幅度较大,平原地区增加幅度较小,而TR在平原地区的增加值较山区更显著,两个指数未来增加值分别为20~40 d和5~40 d;霜冻日数(FD)和冰冻日数(ID)都表现为减少,减少值分别超过10 d和5 d;与降水有关的极端气候事件指数,CDD、降雨日数(R_1mm)和中雨日数(R_10mm)的变化均以减少为主,但数值较小,一般都在?10%~0之间;最大5 d降水量(R_X5day)、降水强度(SDII)和大雨日数(R_20mm)主要表现为增加,增加值一般在0~25%之间。从区域平均的变化来看,与气温有关的极端气候事件指数的变化趋势较为显著,与降水有关的极端气候事件指数变化趋势较小。两个区域对比来看,雄安新区模式间的不确定性更大,反映出模式对较小区域模拟的不足。     

Misspecification of extreme rainfall population statistics and frequency inference due to measurement bias and variability

Statistical analysis of rainfall extremes is mostly based on the assumption of error-free data, despite common knowledge about the widespread incidence of precipitation measurement bias and variability. The objective of this study is primarily to investigate the impact of measurement bias and variability in statistical classification and quantile estimates of rainfall extremes. A theoretical framework is presented for the analysis of moment coefficients and probability distributions for rainfall extremes corrupted by measurement bias and variability. Furthermore, methods are outlined for practical statistical analysis of error-corrupted rainfall extremes, based on maximum likelihood. Frequency inference and testing for the presence of measurement variability are the main topics. Modelling of data series is undertaken in order to exemplify the statistical assessment and the real-life impact of measurement error.It is shown that: (a) unaccounted measurement error may potentially cause a considerable degree of misspecification about the conventional moment and L-moment coefficients of variation, and the conventional moments of skewness and kurtosis; (b) the presence of measurement variability alone can cause significant and nonlinear quantile bias which further strongly increases with the additional presence of measurement bias; and (c) maximum likelihood estimation provides a general and efficient tool for assessing measurement error in extreme rainfall frequency analysis.     

IPCC AR6报告解读：极端天气气候事件变化

与IPCC第五次评估报告（AR5）相比,在第六次评估报告（AR6）评估中,观测的极端天气气候事件变化证据,特别是归因于人为影响的证据加强。人类活动造成的气候变化已影响到全球每个区域的许多极端天气气候事件。随着未来全球变暖进一步加剧,预估极端热事件、强降水、农业生态干旱的强度和频次以及强台风（飓风）比例等将增加,越罕见的极端天气气候事件,其发生频率的增长百分比越大。这些结论再次凸显了应对气候变化和极端天气气候事件的必要性和紧迫性。     

Maize seed choice and perceptions of climate variability among smallholder farmers

Despite decades of research and interventions, crop yields for smallholder farmers across sub-Saharan Africa are dramatically lower than in developed countries. Attempts to address low yields of staple crops in Africa since the Green Revolution through policies and investments in advanced seed cultivars have had mixed results. Numerous countries have heartily embraced and promoted hybrid cultivars through government subsidy programs and investments in research and seed multiplication. One possible explanation for why these programs have not resulted in more significant yield improvements is the challenge faced by farmers to select cultivars that are suited to their local environmental conditions. The question of what seeds farmers choose is exceptionally complex as it is often affected by local seed availability, the availability of information on seed performance, and the transfer of that information to farmers. At the foundation of this choice are farmers’ perceptions of different seed varieties coupled with their perceptions of climate variability. We examine seed choice in Zambia, a country with decades of hybrid maize seed development and supporting policies. We demonstrate how input subsidy programs and seed market liberalization have led to choice overload and a discontinuity in information exchange between farmers and seed companies. The decision making environment is further complicated by the heterogeneity in growing conditions and its variable impact on seed performance, which complicates characterization of seed duration at the farm level. Perceptions and biases related to climate variability effect seed choice, and potentially lead farmers to make risk averse decisions, which ultimately depress maize yields.     

Response of the mean global vegetation distribution to interannual climate variability

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941     

基于格点降水场的中国东部冬季降水变化特征

采用1958-2007年国家级2419地面台站0.5°×0.5°格点降水场和NCEP/NCAR月平均再分析资料,对中国东部冬季降水量变化及对应的大气环流变化特征进行研究。结果表明：冬季近50 a降水量时间序列表现出明显的长期气候变化趋势。20世纪90年代降水较多,大气水汽充足, 60、70年代相反,这种特征反映出水汽在东亚地区输送的强弱及从海洋输入中国大陆水汽的多寡。降水量强弱年差值合成的异常降水量可达40 mm以上。降水量与水汽收支时间序列的相关系数为0.605。水汽收支与降水场的回归系数揭示了长江流域以南地区为异常大值区。降水量强年,冬季风偏弱,对流层低层和高层为异常气旋式环流,低层盛行异常偏南风,孟加拉湾、南海异常暖湿水汽输送到中国东部地区,中国东部近海海温偏高,配合加强的异常垂直上升运动,有利于水汽的增加,造成降水量增加。     

20世纪60~90年代辽东地区气候年代际变化特征分析

利用1961～2000年辽东地区13个观测台站的逐月降水和气温资料,分析了辽东地区降水和气温的年代际变化。并利用高桥公式计算出辽东地区的蒸发量,得出了该地区蒸发量和降水蒸发差的年代际变化特征;同时利用干燥度指标研究了辽东地区气候干旱对气候变暖的响应。结果表明:近40 a来辽东地区气候变化呈暖干变化趋势,即气温升高、降水减少,尤其以20世纪90年代变化最为明显。     

Firm relocation as adaptive response to climate change and weather extremes

Growing scientific evidence suggests that human-induced climate change will bring about large-scale environmental changes such as sea-level rise and coastal flooding, extreme weather events and agricultural disruptions. The speed and extent of these changes and the expected impacts on social and corresponding economic and industrial systems are now moving to the forefront of debates. In this paper, we argue that climate change will lead to significant disruptions to firms which might ultimately create the necessity of a geographical shift of firm and industrial activities away from regions highly affected by climate change. Such a shift might become necessary due to (1) direct disruptions through climate change impacts on firm operations, for instance through droughts, floods, or sea level rise, and due to (2) disruptions in a firm's supplier, buyer or resource base that lead to flow-on effects and adverse consequences for a firm. We propose a framework for integrating firm relocation decisions into firm adaptive responses to climate change. The framework consists of three assessment steps: the level of risk from climate change impacts at a firm's location, the feasibility of relocation, and associated costs and benefits. We apply the framework to two case examples. The first case of electricity distribution firms in Victoria/Australia illustrates how the relocation (undergrounding) of cables could decrease the vulnerability of distribution networks to bushfires and the risk of electricity-caused fires, but would require significant investments. The second case of firms in the Australian pastoral industry points to geographic diversification of pastoral land holdings as possible adaptation option, but also to constraints in form of availability of suitable properties, ties to local communities, and adverse impacts on biodiversity. Implications for adaptation research and practice are outlined.     

Divergent adaptation to climate variability: A case study of pastoral and agricultural societies in Niger

Adaptation is a complex, dynamic, and sometimes unequal process. Stemming from social ecological systems theories of climate change adaptation and adaptive capacity, this case study introduces the concept of ‘divergent’ adaptation. Adaptation is divergent when one user or group's adaptation causes a subsequent reduction in another user or group's adaptive capacity in the same ecosystem. Using the example of pastoral and agricultural groups in northern and southern rainfall zones of Niger, this study illustrates the concept of divergent adaptation by identifying changes to the adaptive capacity of users who are currently engaged in conflicts over access to natural resources. Similar to other studies, we find that expansion of farmland and the consequent loss of pastoral space are restricting pastoral adaptation. Divergent adaptations favoring agricultural livelihoods include cultivating near or around pastoral wells or within pastoral corridors, both of which limit the mobility and entitlements of pastoralists. Institutions rarely secure pastoral routes and access to water points, a problem that is compounded by conflicting modes of governance, low accountability, and corruption. The case study illustrates the need to enhance the adaptive capacity of multiple user groups to reduce conflict, enhance human security, and promote overall resilience.     

Interannual spring Wyrtki jet variability and its regional impacts

The role of spring Wyrtki jets in modulating the equatorial Indian Ocean and the regional climate is an unexplored problem. The source of interannual variability in the spring Wyrtki jets is explored in this study. The relationship between intraseasonal and interannual variability from 1958 to 2008 and its relation with Indian Summer Monsoon is further addressed. Analysis reveals that the interannual variability in spring Wyrtki jets is controlled significantly by their intraseasonal variations. These are mostly defined by a single intraseasonal event of duration 20 days or more which either strengthens or weakens the seasonal mean jet depending on its phase. The strong spring jets are driven by such intraseasonal westerly wind bursts lasting for 20-days or more, whereas the weak jets are driven by weaker intraseasonal westerlies. During the years of strong jets, the conventional westward phase propagation of Wyrtki jets is absent and instead there is an eastward phase propagation indicating the possible role of Madden Julian Oscillation (MJO) in strengthening the spring Wyrtki jets. These strong intraseasonal westerly wind bursts with eastward phase propagation during strong years are observed mainly in late spring and have implications on June precipitation over the Indian and adjoining land mass. Anomalously strong eastward jets accumulate warm water in the eastern equatorial Indian Ocean (EIO), leading to anomalous positive upper ocean heat content and supporting more local convection in the east. This induces subsidence over the Indian landmass and alters monsoon rainfall by modulating monsoon Hadley circulation. In case of weak current years such warm anomalies are absent over the eastern EIO. Variations in the jet strength are found to have strong impact on sea level anomalies, heat content, salinity and sea surface temperature over the equatorial and north Indian Ocean making it a potentially important player in the north Indian Ocean climate variability.     

青藏高原三江源地区近60 a气候与极端气候变化特征分析

青藏高原三江源地区正在面临着以"变暖变湿"为主的气候变化,是气候变化的显著区与敏感区。基于中国气象局位于三江源地区20个地面台站的气温、降水数据以及HadCRUT4（Climatic Research Unit land-surface air temperature-4 dataset and the Hadley Centre sea-surface temperature dataset,Hadley Centre,UK）气温、PREC（Precipitation Reconstruction,National Oceanic and Atmospheric Administration,USA）降水资料,从气候要素空间格局、极端气候指标以及区域-全球平均多年变化对比等3个方面系统总结了三江源地区1961-2019年气候和极端气候变化的特征。结果显示,三江源区域在过去近60 a里平均增暖速率为0.37℃/（10 a）,是全球平均水平（0.16℃/（10 a））的2倍以上,同时大幅高于全球同纬度（0.19℃/（10 a））及中国区域（0.28℃/（10 a））。在全球变暖背景下,三江源地区大部分极端气候指标上升,其中以夜间最低气温的上升（0.55℃/（10 a））最为显著,且极端高温事件的出现频率上升,区域日温差减小、气温变化极端性增强。三江源近60 a温湿气候态的空间格局为沿西北-东南方向的正温湿梯度,其变化趋势存在自西向东速率上升的暖湿化空间分异特征。本文的研究结论进一步揭示了三江源地区近60 a气候变化与极端气候的时空格局,为三江源地区气候系统和生态系统的脆弱性研究以及未来气候变化预估提供了科学依据,同时也为气候变化敏感的高寒地区对全球变暖的响应研究提供了对比案例。     

华南地区汛期极端降水的概率分布特征

利用1960-2005年华南地区71个测站的逐日降水量资料和NCEP/NCAR南半球月平均海平面气压场再分析资料,采用Le Page榆验、广义极值分布等统计诊断方法,研究了华南地区近46 a前汛期(4-6月)和后汛期(7-9月)极端降水的时空变化及概率分布特征.并讨论了南半球澳大利亚高压和马斯克林高压强度指数与华南汛期暴雨日数间年代际变化的关系.结果表明:(1)1992年华南地区降水发生了由减少趋势到增多趋势的突变,降水趋势发生突变后前汛期极端降水量和日极端降水强度有所下降,而后汛期则是显著增强.(2)华南汛期年平均日最大降水量、50 a一遇日最大降水量极值和暴雨日数的空间分布特征相似,即前汛期的空间分布自南向北呈现"低-高-低"的分布趋势,后汛期呈现由沿海到内陆的"高-低"的分布趋势.(3)1992年发生突变后,前、后汛期年平均日最大降水量和年平均暴雨日数显著增加和减少的空间分布基本一致.(4)就年代际变化而言,南半球澳大利亚高压和马斯克林高压的强度变化是华南汛期降水异常的重要气候背景,即当两高压处在同时增强时期时,华南前汛期极端降水处于偏少阶段,后汛期则处于偏多阶段.