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。     

1951-1990年中国极端气温变化分析

利用1975-2014年安徽省77个观测站的日最高温度、最低温度和平均气温资料,对近40 a极端温度事件的时空分布特征进行分析。结果表明：安徽省冬季极端低温事件的发生频次分布,总体呈北多南少,地区差异较大,极端低温事件发生次数最多的是宿州萧县。近40 a间冬季的极端低温事件发生减少趋势显著,与冬季平均温度的显著上升相对应。年极端最低温度年际变化趋势不明显,且极端低温的发生频次与强度并不对应。夏季极端高温事件发生频次较多区域为江南。1975-2014年,夏季极端高温事件发生呈整体增多趋势,但趋势不显著。年极端最高温度的时间序列,与极端高温事件发生频次的时间序列是相对应的,呈现明显的正相关。从MK突变上看,年极端低温和高温事件发生均存在突变。分析合成环流场发现,冬季极端冷事件发生时,亚洲中高纬度环流的经向度明显增强;夏季极端暖事件的发生与副高的明显西伸增强维持有关。

     

Assessing organizational resilience to climate and weather extremes: complexities and methodological pathways

This paper offers insights for assessing organizational resilience to the effects of climate change, specifically to climate and weather extremes. The assessment of organizational resilience to climate and weather extremes brings about several challenges due to (1) uncertainties about future climate change outcomes across temporal and spatial scales and (2) a lack of insight into what lead to organizational resilience, or which variables should be measured in a given study. We suggest methodological pathways for organizational managers to identify properties of future climate and weather extremes and to include them in resilience assessments. We also suggest approaches to identify factors that promote organizational resilience to selected climate and weather extremes. Findings are intended to help managers to understand how organizational resilience to climate and weather extremes can be enhanced.     

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.     

Changes in climate extremes, variability and signature on sub-Antarctic Marion Island

The ecological consequences of climate change are determined by many climate parameters, not just by the commonly investigated changes in mean temperature and rainfall. More comprehensive studies, including analyses of climate variability, extremes and aggregate changes in the climate system, can improve the understanding of the nature, and therefore possible consequences, of recent changes in climate. Here climate trends on the sub-Antarctic Marion Island are documented (between 1949 and 2003) in more detail than previously. Significant trends in biologically-relevant, and previously unexplored, parameters were observed, and the potential ecological consequences of these changes discussed. For example, the decline in precipitation experienced on the island comprises a trend for longer dry spells punctuated by fewer and smaller precipitation events. This more detailed understanding of the island’s drying trends enables more accurate predictions about its impacts, including, for example, particularly severe effects on plant species growing in soils with poor water-holding capacity. Therefore, in addition to changes in average conditions, more inclusive climate analyses should also examine trends in climatic variability and extremes, for individual climate parameters as well as for the climate system as a whole.     

Changes in daily climate extremes in the arid area of northwestern China

There has been a paucity of information on trends in daily climate and climate extremes, especially for the arid region. We analyzed the changes in the indices of climate extremes, on the basis of daily maximum and minimum air temperature and precipitation at 59 meteorological stations in the arid region of northwest China over the period 1960–2003. Twelve indices of extreme temperature and six indices of extreme precipitation are examined. Temperature extremes show a warming trend with a large proportion of stations having statistically significant trends for all temperature indices. The regional occurrence of extreme cool days and nights has decreased by ?0.93 and ?2.36 days/decade, respectively. Over the same period, the occurrence of extreme warm days and nights has increased by 1.25 and 2.10 days/decade, respectively. The number of frost days and ice days shows a statistically significant decrease at the rate of ?3.24 and ?2.75 days/decade, respectively. The extreme temperature indices also show the increasing trend, with larger values for the index describing variations in the lowest minimum temperature. The trends of Min Tmin (Tmax) and Max Tmin (Tmax) are 0.85 (0.61) and 0.32 (0.17)?°C/decade. Most precipitation indices exhibit increasing trends across the region. On average, regional maximum 1-day precipitation, annual total wet-day precipitation, and number of heavy precipitation days and very wet days show insignificant increases. Insignificant decreasing trends are also found for consecutive dry days. The rank-sum statistic value of most temperature indices exhibits consistent or statistically significant trends across the region. The regional medians after 1986 of Min Tmin (Tmax), Max Tmin (Tmax), warm days (nights), and warm spell duration indicator show statistically more larger than medians before 1986, but the frost days, ice days, cool days (nights), and diurnal temperature range reversed. The medians of precipitation indices show insignificant change except for consecutive dry days before and after 1986.     

Statistics of extremes in climate change

This editorial essay concerns the use (or lack thereof) of the statistics of extremes in climate change research. So far, the statistical theory of extreme values has been primarily applied to climate under the assumption of stationarity. How this theory can be applied in the context of climate change, including implications for the analysis of the economic impacts of extremes, is described. Future research challenges include the statistical modeling of complex extreme events, such as heat waves, and taking into account spatial dependence in the statistical modeling of extremes for fields of climate observations or of numerical model output. Addressing these challenges will require increased collaboration between climate scientists and statisticians.     

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。     

Mediterranean climate extremes in synoptic downscaling assessments

The behaviour of precipitation and maximum temperature extremes in the Mediterranean area under climate change conditions is analysed in the present study. In this context, the ability of synoptic downscaling techniques in combination with extreme value statistics for dealing with extremes is investigated. Analyses are based upon a set of long-term station time series in the whole Mediterranean area. At first, a station-specific ensemble approach for model validation was developed which includes (1) the downscaling of daily precipitation and maximum temperature values from the large-scale atmospheric circulation via analogue method and (2) the fitting of extremes by generalized Pareto distribution (GPD). Model uncertainties are quantified as confidence intervals derived from the ensemble distributions of GPD-related return values and described by a new metric called “ratio of overlapping”. Model performance for extreme precipitation is highest in winter, whereas the best models for maximum temperature extremes are set up in autumn. Valid models are applied to a 30-year period at the end of the twenty-first century (2070–2099) by means of ECHAM5/MPI-OM general circulation model data for IPCC SRES B1 scenario. The most distinctive future changes are observed in autumn in terms of a strong reduction of precipitation extremes in Northwest Iberia and the Northern Central Mediterranean area as well as a simultaneous distinct increase of maximum temperature extremes in Southwestern Iberia and the Central and Southeastern Mediterranean regions. These signals are checked for changes in the underlying dynamical processes using extreme-related circulation classifications. The most important finding connected to future changes of precipitation extremes in the Northwestern Mediterranean area is a reduction of southerly displaced deep North Atlantic cyclones in 2070–2099 as associated with a strengthened North Atlantic Oscillation. Thus, the here estimated future changes of extreme precipitation are in line with the discourse about the influence of North Atlantic circulation variability on the changing climate in Europe.     

South Australian rainfall variability and climate extremes

Rainfall extremes over South Australia are connected with broad-scale atmospheric rearrangements associated with strong meridional sea surface temperature (SST) gradients in the eastern Indian Ocean. Thirty-seven years of winter radiosonde data is used to calculate a time series of precipitable water (PW) and convective available potential energy (CAPE) in the atmosphere. Principle component analysis on the parameters of CAPE and PW identify key modes of variability that are spatially and seasonally consistent with tropospheric processes over Australia. The correlation of the leading principle component of winter PW to winter rainfall anomalies reveal the spatial structure of the northwest cloudband and fronts that cross the southern half of the continent during winter. Similarly the second and third principle components, respectively, reveal the structures of the less frequent northern and continental cloudbands with remarkable consistency. 850 hPa-level wind analysis shows that during dry seasons, anomalous offshore flow over the northwest of Australia inhibits advection of moisture into the northwest, while enhanced subsidence from stronger anticyclonic circulation over the southern half of the continent reduces CAPE. This coincides with a southward shift of the subtropical ridge resulting in frontal systems passing well to the south of the continent, thus producing less frequent interaction with moist air advected from the tropics. Wet winters are the reverse, where a weaker meridional pressure gradient to the south of the continent allows rain-bearing fronts to reach lower latitudes. The analysis of SSTs in the Indian Ocean indicate that anomalous warm (cool) waters in the southeast Indian Ocean coincide with a southward (northward) shift in the subtropical ridge during dry (wet) seasons.     

Assessment of climate extremes in the Eastern Mediterranean

Summary Several seasonal and annual climate extreme indices have been calculated and their trends (over 1958 to 2000) analysed to identify possible changes in temperature- and precipitation-related climate extremes over the eastern Mediterranean region. The most significant temperature trends were revealed for summer, where both minimum and maximum temperature extremes show statistically significant warming trends. Increasing trends were also identified for an index of heatwave duration. Negative trends were found for the frequency of cold nights in winter and especially in summer. Precipitation indices highlighted more regional contrasts. The western part of the study region, which comprises the central Mediterranean and is represented by Italian stations, shows significant positive trends towards intense rainfall events and greater amounts of precipitation. In contrast, the eastern half showed negative trends in all precipitation indices indicating drier conditions in recent times. Significant positive trends were revealed for the index of maximum number of consecutive dry days, especially for stations in southern regions, particularly on the islands.Current affiliation: National Observatory of Athens, Athens, Greece.     

Changes in climate variability and seasonal rainfall extremes: a case study from San Fernando (Spain), 1821–2000

Summary ?Small changes in the mean and standard deviation values can produce relatively large changes in the probability of extreme events. The seasonal precipitation record in San Fernando (SW Spain) for 1821–2000 is used to investigate how much the relative frequency of dry and wet seasons changes with changes in mean value and standard deviation. The percentiles P10, P25, P75 and P90 of the reference period 1961–1990 are used to define dry and wet seasons. The probability of extreme seasons as function of mean and standard deviation is analysed. The main conclusion is a non-linear relationship between changes in mean and standard deviation values and extreme seasons probability. With these threshold values, the main influence corresponds to changes in mean value. Results are discussed bearing in mind projections of General Circulation Models on future climate in southern Iberian Peninsula. Received June 11, 2001; Revised March 3, 2002     

Scale dependency of regional climate modeling of current and future climate extremes in Germany

A 26-year simulation (1980–2005) was performed with the Weather Research and Forecast (WRF) model over the Volta Basin in West Africa. This was to investigate the ability of a climate version of WRF to reproduce present day temperature and precipitation over the Volta Basin. The ERA-Interim reanalysis and one realization of the ECHAM6 global circulation model (GCM) data were dynamically downscaled using two nested domains within the WRF model. The outer domain had a horizontal resolution of 50 km and covered the whole of West Africa while the inner domain had a horizontal resolution of 10 km. It was observed that biases in the respective forcing data were carried over to the RCM, but also the RCM itself contributed to the mean bias of the model. Also, the biases in the 50-km domain were transferred unchanged, especially in the case of temperature, to the 10-km domain, but, for precipitation, the higher-resolution simulations increased the mean bias in some cases. While in general, WRF underestimated temperature in both the outer (mean biases of ?1.6 and ?2.3 K for ERA-Interim and ECHAM6, respectively) and the inner (mean biases of ?0.9 K for the reanalysis and ?1.8 K for the GCM) domains, WRF slightly underestimated precipitation in the coarser domain but overestimated precipitation in the finer domain over the Volta Basin. The performance of the GCM, in general, is good, particularly for temperature with mean bias of ?0.7 K over the outer domain. However, for precipitation, the added value of the RCM cannot be overlooked, especially over the whole West African region on the annual time scale (mean biases of ?3% for WRF and ?8% for ECHAM6). Over the whole Volta Basin and the Soudano-Sahel for the month of April and spring (MAM) rainfall, respectively, mean bias close to 0% was simulated. Biases in the interannual variability in both temperature and precipitation over the basin were smaller in the WRF than the ECHAM6. High spatial pattern correlations between 0.7 and 0.8 were achieved for the autumn precipitation and low spatial correlation in the range of 0.0 and 0.2 for the winter season precipitation over the whole basin and all the three belts over the basin.     

A new daily weather generator to preserve extremes and low-frequency variability

This paper addresses deficiencies of stochastic Weather Generators (WGs) in terms of reproduction of low-frequency variability and extremes, as well as the unanticipated effects of changes to precipitation occurrence under climate change scenarios on secondary variables. A new weather generator (named IWG) is developed in order to resolve such deficiencies and improve WGs performance. The proposed WG is composed of three major components, including a stochastic rainfall model able to reproduce realistic rainfall series containing extremes and inter-annual monthly variability, a multivariate daily temperature model conditioned to the rainfall occurrence, and a suitable multi-variate monthly generator to fit the low-frequency variability of daily maximum and minimum temperature series. The performance of IWG was tested by comparing statistical characteristics of the simulated and observed weather data, and by comparing statistical characteristics of the simulated runoff outputs by a daily rainfall-runoff model fed by the generated and observed weather data. Furthermore, IWG outputs are compared with those of the well-known LARS-WG weather generator. The tested characteristics are a variety of different daily statistics, low-frequency variability, and distribution of extremes. It is concluded that the performance of the IWG is acceptable, better than LARS-WG in the majority of tests, especially in reproduction of extremes and low-frequency variability of weather and runoff series.     

The predictability of weather and climate

The last thirty years have seen the development of comprehensive numerical models of the large-scale circulation of the atmosphere, based on physical principles. Such models are quite skillful at describing the evolving weather up to a few days ahead, despite imperfect theory and inadequate observational data. Yet even a hypothetical perfect model, which exactly represented the dynamics of the real atmosphere, and which used data from the best conceivable observing system, could not produce an accurate forecast of indefinitely long range. Any forecast must eventually lose skill because of the intrinsic instability of the atmosphere itself.This limitation on the predictability of the detailed evolution of the atmosphere (weather) does not preclude the possibility of seasonal and longer-range forecasts of means and other statistical properties (climate). However, we are only beginning to learn what aspects of climate may be predictable, and what theoretical tools and observational data will be required to predict them.     

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 ...     

应用NASA MERRA再分析资料对一次高原切变线的诊断分析

高原切变线是影响青藏高原及其下游地区重要的降水天气系统,也是高原气象学研究的重点和热点。本文回顾了近10 a高原切变线的研究进展,包括高原切变线的时空分布及其与暴雨的关系、高原切变线的结构特征及演变机制、高原切变线与高原低涡的相互作用等。在此基础上,对未来高原切变线研究的主要方面进行了展望,以期加深对高原切变线的认识,为青藏高原及其下游地区灾害性天气研究和预报预警提供参考依据。

     

Modelling daily temperature extremes: recent climate and future changes over Europe

Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries.