Changes in weather and climate extremes: phenomenology and empirical approaches

The terms “weather extremes” and “climate extremes” are widely used in meteorology, often in relation to climate change. This paper reviews the empirical investigations into parallel changes in extreme events and climate change published in recent years and looks at their relevance for the global energy system. Empirical investigation into the correlation of extremes with global warming covers five groups: changes in temperature, precipitation, wind (storm) extremes, tropical and extra-tropical circulation phenomena. For temperature extremes, extensive analyses demonstrate that extreme hot days and nights will likely become more frequent, and extreme cold days and nights less frequent. Intense precipitation events will likely become more frequent in most continental regions. Scientific confidence in the trends of the frequency, duration, and intensity of tropical cyclones, is still low. A poleward shift is observed for extratropical cyclones, whereas no convincing tendencies of many smaller-scale phenomena, for example, tornados, or hail, can yet be detected. All these extremes have serious implications for the energy sector.     

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.     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

Observed Changes in One-in-20 Year Extremes of Canadian Surface Air Temperatures

Weather and climate extremes are often associated with substantial adverse impacts on society and the environment. Assessment of changes in extremes is of great and broad interest. This study first homogenizes daily minimum and maximum surface air temperatures recorded at 146 stations in Canada. In order to assess changes in one-in-20 year extremes (i.e., extremes with a 20-year return period) in temperature, annual maxima and minima of both daily minimum temperatures and daily maximum temperatures are derived from the homogenized daily temperature series and analyzed with a recently developed extreme value analysis approach based on a tree of generalized extreme value distributions (including stationary and non-stationary cases). The procedure is applied to estimate the changes over the period 1911 to 2010 at 115 stations, located mainly in southern Canada, and over the period 1961 to 2010 at 146 stations across Canada (including 37 stations in the North). The results show that warming is strongest for extreme low temperature and weakest for extreme high temperature and is much stronger in the Canadian Arctic than in southern Canada. Warming is stronger in winter than in summer and stronger during nighttime than daytime of the same season.     

Scenarios of extreme temperature events

Based on the principles of the probability theory a statistical model has been developed assessing the likelihood of occurrence of extreme temperature events from the knowledge of the statistical characteristics of the daily temperature extremes. It is demonstrated that the probability of such events is more sensitive to changes in the variability of climate than to changes in its average. Further, this sensitivity increases at a nonlinear rate the more extreme the event. The applicability of the model has been verified by comparing the simulated frequencies of a large spectrum of temperature events with the observed numbers derived from a long time series of daily temperature extremes at Potsdam. Accordingly, the relative simulation errors increase significantly as the events become more extreme. A correction is possible, because most of these errors are systematic rather than random. Moreover, in accordance with the climate observations the simulations reveal statistically significant linear trends in the number of extreme events since the end of the last century. Local scenarios of extreme temperature events have been derived for the city of Berlin by considering both hypothetical new climate states and climate changes simulated by a General Circulation Model (GCM). As a consequence of an increase in the atmospheric concentration of greenhouse gases up to the end of the next century according to the IPCC Scenario A the repetition rate of extreme events in summer (e.g., hot days) is expected to rise considerably relative to the current climate. Moreover, in the winter season cold days will become extremely rare.     

近40年我国极端温度变化趋势和季节特征

利用1961—2000年我国194个测站逐日最高温度和最低温度器测资料,结合具有实际意义的季节极端温度指数,分析了我国近40年极端温度事件的年变化趋势和季节特征。对年极端气候指数的研究表明:绝对阈值定义的冷暖指数由于无法考虑南北气候差异,其结果不理想。百分比阈值所得的冷暖指数中,冷日指数和暖日指数具有不对称性,冷夜指数和暖夜指数具有较强的对称性。对季节极端温度指数研究表明:冬季极端冷指数变化趋势最为明显,夏季极端暖指数的变化趋势次之,春、秋两季极端冷指数的变化趋势不明显;年和季节尺度的极端冷暖指数均反映出增暖趋势。     

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。     

Temperature Extremes from Canadian Regional Climate Model (CRCM) Climate Change Projections

Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.

The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.

The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes.     

Simulation of regional climate change under the IPCC A2 scenario in southeast China

A variable-grid atmospheric general circulation model, LMDZ, with a local zoom over southeast China is used to investigate regional climate changes in terms of both means and extremes. Two time slices of 30?years are chosen to represent, respectively, the end of the 20th century and the middle of the 21st century. The lower-boundary conditions (sea-surface temperature and sea-ice extension) are taken from the outputs of three global coupled climate models: Institut Pierre-Simon Laplace (IPSL), Centre National de Recherches Météorologiques (CNRM) and Geophysical Fluid Dynamics Laboratory (GFDL). Results from a two-way nesting system between LMDZ-global and LMDZ-regional are also presented. The evaluation of simulated temperature and precipitation for the current climate shows that LMDZ reproduces generally well the spatial distribution of mean climate and extreme climate events in southeast China, but the model has systematic cold biases in temperature and tends to overestimate the extreme precipitation. The two-way nesting model can reduce the ??cold bias?? to some extent compared to the one-way nesting model. Results with greenhouse gas forcing from the SRES-A2 emission scenario show that there is a significant increase for mean, daily-maximum and minimum temperature in the entire region, associated with a decrease in the number of frost days and an increase in the heat wave duration. The annual frost days are projected to significantly decrease by 12?C19?days while the heat wave duration to increase by about 7?days. A warming environment gives rise to changes in extreme precipitation events. Except two simulations (LMDZ/GFDL and LMDZ/IPSL2) that project a decrease in maximum 5-day precipitation (R5d) for winter, other precipitation extremes are projected to increase over most of southeast China in all seasons, and among the three global scenarios. The domain-averaged values for annual simple daily intensity index (SDII), R5d and fraction of total rainfall from extreme events (R95t) are projected to increase by 6?C7, 10?C13 and 11?C14%, respectively, relative to their present-day values. However, it is clear that more research will be needed to assess the uncertainties on the projection in future of climate extremes at local scale.     

Cold Temperature Extremes in Russia and Risks of Critical Temperature Impacts on Infrastructure Facilities

The features of changes and variability for cold temperature extremes over Russia are analyzed using observational data for the period from the middle of the 20th century. The impact is assessed that observed changes in thermal regime make on the characteristics of rare extremes which are used as standard parameters for designing infrastructure facilities. The results are interpreted in terms of the power system operation reliability. The risk assessment for critical temperature impacts indicates the important regional features of climate change effect on extreme energy loads and requirements for power capacities during the cold season.     

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.     

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.     

An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century: part 2: historical trends

We analyze historical simulations of variability in temperature and rainfall extremes in the twentieth century, as derived from various global models run informing the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4). On the basis of three indices of climate extremes, we compare observed and modeled trends in time and space, including the direction and significance of the changes at the scale of South America south of 10° S. The climate extremes described warm nights, heavy rainfall amounts and dry spells. The reliability of the GCM simulations is suggested by similarity between observations and simulations in the case of warm nights and extreme rainfall in some regions. For any specific extreme temperature index, minor differences appear in the spatial distribution of the changes across models in some regions, while substantial differences appear in regions in the interior of tropical and subtropical South America. The differences are in the relative magnitude of the trends. Consensus and significance are less strong when regional patterns are considered, with the exception of the La Plata Basin, where observed and simulated trends in warm nights and extreme rainfall are evident.     

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。     

Trends and periodicity of daily temperature and precipitation extremes during 1960–2013 in Hunan Province,central south China

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960–2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960–1986 and 1987–2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970–1980 and after 1992.     

Assessment of indices of temperature extremes simulated by multiple CMIP5 models over China

Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity (absolute indices and threshold indices), duration (duration indices), and frequency (percentile indices) of extreme temperature. The overall performance of each model is summarized by a "portrait" diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.     

Critical analysis of simulated daily temperature data from the ARPEGE-climate model: application to climate change in the Champagne wine-producing region

As global warming is scientifically and widely accepted, its impacts at regional scales are raising many questions for wine producers. In particular, climate parameters, especially temperature, play a decisive role in vine growth and grape ripening. An overview of expected climate change in terms of bioclimatic indexes (Winkler and Huglin) and thermal extremes in the wine-producing region of Champagne is presented. A variable-grid atmospheric general circulation model, ARPEGE-Climate, with a local zoom at 50 km over the area of interest, is used to investigate potential future changes in thermal extremes and bioclimatic indexes. Changes in daily maximum and minimum temperatures at key stages are discussed for three emission scenarios (B1, A1B, A2) that are currently used in studies of impacts of climate change. Model outputs are analyzed and critically assessed for a control period (1971–2000) and for changes in extreme events in relation to future scenarios, such as a decrease in extreme low temperatures in spring (April) during bud break and an increase in extreme high temperatures in summer, associated with more frequent heat waves during ripening.     

Changes in Mean and Extreme Temperature and Precipitation over the Arid Region of Northwestern China:Observation and Projection

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally,the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21 st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing.     

Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model

The results are analyzed of the ensemble forecast of temperature and precipitation extremes on the territory of Siberia by the middle of the 21st century based on the regional climate model of the Main Geophysical Observatory (MGO) with the resolution of 25 km. The results of computation of oceanic components of CMIP3 coupled models are used as the boundary conditions on the sea surface. It is demonstrated that the high resolution of the regional model enables to simulate the observed climate variability in a more realistic way as compared to the low-resolution models. The analysis of the signal-to-noise ratio for future climate changes made it possible to determine to which degree its internal variability for various time scales (from interannual to interdecennial one) bounds the potential of the ensemble to compute the statistically significant anthropogenic changes of extremes. A comparative analysis of variations of extreme and average seasonal characteristics of the Siberian climate is carried out.