Record occurrence and record values in daily and monthly temperatures

We analyze the occurrence and the values of record-breaking temperatures in daily and monthly temperature observations. Our aim is to better understand and quantify the statistics of temperature records in the context of global warming. Similar to earlier work we employ a simple mathematical model of independent and identically distributed random variables with a linearly growing expectation value. This model proved to be useful in predicting the increase (decrease) in upper (lower) temperature records in a warming climate. Using both station and re-analysis data from Europe and the United States we further investigate the statistics of temperature records and the validity of this model. The most important new contribution in this article is an analysis of the statistics of record values for our simple model and European reanalysis data. We estimate how much the mean values and the distributions of record temperatures are affected by the large scale warming trend. In this context we consider both the values of records that occur at a certain time and the values of records that have a certain record number in the series of record events. We compare the observational data both to simple analytical computations and numerical simulations. We find that it is more difficult to describe the values of record breaking temperatures within the framework of our linear drift model. Observations from the summer months fit well into the model with Gaussian random variables under the observed linear warming, in the sense that record breaking temperatures are more extreme in the summer. In winter however a significant asymmetry of the daily temperature distribution hides the effect of the slow warming trends. Therefore very extreme cold records are still possible in winter. This effect is even more pronounced if one considers only data from subpolar regions.     

Projected Heat Wave Characteristics over the Korean Peninsula During the Twenty-First Century

Climate change is expected to increase temperatures globally, and consequently more frequent, longer, and hotter heat waves are likely to occur. Ambiguity in defining heat waves appropriately makes it difficult to compare changes in heat wave events over time. This study provides a quantitative definition of a heat wave and makes probabilistic heat wave projections for the Korean Peninsula under two global warming scenarios. Changes to heat waves under global warming are investigated using the representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) experiments from 30 coupled models participating in phase five of the Coupled Model Inter-comparison Project. Probabilistic climate projections from multi-model ensembles have been constructed using both simple and weighted averaging. Results from both methods are similar and show that heat waves will be more intense, frequent, and longer lasting. These trends are more apparent under the RCP8.5 scenario as compared to the RCP4.5 scenario. Under the RCP8.5 scenario, typical heat waves are projected to become stronger than any heat wave experienced in the recent measurement record. Furthermore, under this scenario, it cannot be ruled out that Korea will experience heat wave conditions spanning almost an entire summer before the end of the 21st century.     

Temperature variability and early clustering of record-breaking events

As the number of climatological studies using record-breaking statistics is growing rapidly, understanding the sensitivity of the chosen time period becomes essential. To that end, here we examine the evolving variability of monthly mean temperatures and its dependence on beginning and final year. Specifically, we use an index, α, based on record-breaking statistics and employing reversibility such that 〈α〉=0 indicates no trend in variability. Generally, 〈α〉 has decreased between 1900 and 2013, indicating decreasing variability relative to early decades for stations from the contiguous USA (United States Historical Climatology Network, version 2.5). We find, somewhat surprisingly, that the observed decrease is due to an early excess of records beginning in 1917 (record low value) and 1921 (record high value). While detailed results depend on whether the data is gridded, detrended, etc., the general finding appears remarkably robust and holds globally as well.     

Changes in European temperature extremes can be predicted from changes in PDF central statistics

Although uncertainties are still large, many potentially dangerous effects have already been identified concerning the impacts of global warming on human societies. For example, the record-breaking 2003 summer heat wave in Europe has given a glimpse of possible future European climate conditions. Here we use an ensemble of regional climate simulations for the end of the twentieth and twenty-first centuries over Europe to show that frequency, length and intensity changes in warm and cold temperature extremes can be derived to a close approximation from the knowledge of changes in three central statistics, the mean, standard deviation and skewness of the Probability Distribution Function, for which current climate models are better suited. In particular, the effect of the skewness parameter appears to be crucial, especially in the case of cold extremes, since it mostly explains the relative warming of these events compared to the whole distribution. An application of this finding is that the future impacts of extreme heat waves and cold spells on non-climatological variables (e.g., mortality) can be estimated to a first-order approximation from observed time series of daily temperature transformed in order to account for simulated changes in these three statistics.     

Historical and future changes in maximum and minimum temperature records over Europe

Recent studies examining changes in temperature record frequency over the continental United States have reported that the number of Tmax records has been increasing over the past 50 years and occurring at twice the frequency of Tmin records. In a stationary climate, the number of records should decrease with time as 1/n, where n is the number of years of record-keeping. Here we seek to understand how European temperature records have changed during the late 20th century and how they are expected to change as greenhouse gases increase during the 21st century, using a new ensemble method to filter out the effect of the starting year in the calculation of the records. We find that until 1980, the ratio of Tmax to Tmin records remains close to one, indicating that the climate was relatively stationary. After 1980, there is a distinct positive trend where the observed ratio averages around four during the early part of the 21st century, indicative of a warming trend. We note considerable spatial variability in the observations. Further, the ratio of Tmax to Tmin records set by the year 2100 as simulated by five RCM simulations reaches values of up to several hundred by the end of the 21st century. However, the changes in record frequency vary spatially over Europe. The models project the highest numbers of Tmax records over the Mediterranean during summer, and Scandinavia during the spring and fall. Tmin records decrease most substantially over eastern Europe and western Russia, and the Mediterranean. Our analysis confirms the value of the use of maximum and minimum temperature records in regional climate change studies.     

西安市气候变暖与城市热岛效应问题研究

选取1961—2003年西安站和周围4站月平均气温资料, 利用西安站与周围4站气温距平滑动平均变化趋势的差异, 发现该站平均气温有两个明显的上升期, 热岛效应使西安站平均升温1.07 ℃, 并建立了西安市城市热岛效应模型。在此基础上分离了气候变暖过程中由于城市热岛效应引起的增温作用。     

Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models

Simulation and projection of the characteristics of heat waves over China were investigated using 12 CMIP5 global climate models and the CN05.1 observational gridded dataset. Four heat wave indices (heat wave frequency, longest heat wave duration, heat wave days, and high temperature days) were adopted in the analysis. Evaluations of the 12 CMIP5 models and their ensemble indicated that the multi-model ensemble could capture the spatiotemporal characteristics of heat wave variation over China. The inter-decadal variations of heat waves during 1961–2005 can be well simulated by multi-model ensemble. Based on model projections, the features of heat waves over China for eight different global warming targets (1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0 °C) were explored. The results showed that the frequency and intensity of heat waves would increase more dramatically as the global mean temperature rise attained higher warming targets. Under the RCP8.5 scenario, the four China-averaged heat wave indices would increase from about 1.0 times/year, 2.5, 5.4, and 13.8 days/year to about 3.2 times/year, 14.0, 32.0, and 31.9 days/year for 1.5 and 5.0 °C warming targets, respectively. Those regions that suffer severe heat waves in the base climate would experience the heat waves with greater frequency and severity following global temperature rise. It is also noteworthy that the areas in which a greater number of severe heat waves occur displayed considerable expansion. Moreover, the model uncertainties exhibit a gradual enhancement with projected time extending from 2006 to 2099.     

TEMPERATURE VARIATIONS DURING THE LAST CENTURY AT HIGH ELEVATION SITES

Differential temperature changes with altitude can shed light on the relative importance of natural versus anthropogenic climatic change. There has been heightened interest in this subject recently due to the finding that high-elevation tropical glaciers have been retreating and that significant melting from even the highest alpine regions has occurred in some areas during the past 20 years or so, as recorded in ice core records, which do not reveal any similar period during previous centuries to millennia. In this paper we find evidence for appreciable differences in mean temperature changes with elevation during the last several decades of instrumental records. The signal appears to be more closely related to increases in daily minimum temperature than changes in the daily maximum. The changes in surface temperature vary spatially, with Europe (particularly western Europe), and parts of Asia displaying the strongest high altitude warming during the period of record. High-elevation climate records of long standing taken at a number of mountain tops throughout the world, but primarily in Europe, are available from a number of countries. In some cases, meteorological observations at these unique mountain sites have been discontinued for a variety of reasons, usually budgetary. It is hoped that the papers published in this special issue of Climatic Change can contribute to a reassessment of the value of continuing climate measurements at these mountain observatories by the appropriate entities, so that we may continue to have access to climate information from the tops of the world.     

The climatic impact of a Sonoran vegetation discontinuity

The international fence separating Mexico and the United States is marked by a sharp vegetation discontinuity in the Sonoran Desert. Due to overgrazing, the Mexican side of the border has shorter grasses, more bare soil, and a higher albedo compared to the adjacent lands in the United States. In this investigation, long-term climate records are analyzed to determine the magnitude of any climatic differences associated with the spatial variation in the vegetation regime. The results suggest that summertime maximum temperatures recorded at the Mexican stations are significantly higher (by nearly 2.5 °C) than the Arizona stations when latitude and elevation are held constant. When only elevation is held constant, the difference in the maximum temperature jumps to approximately 4 dgC. No discernible changes in monthly and/or summer season precipitation could be identified in the records. These findings add support to other site-specific field measurements suggesting warming in desert areas where vegetation cover is decreasing and albedo is increasing.     

Climate Change Estimates of Summer Temperature and Precipitation in the Alpine Region

Summary Climatic changes of summer temperature and precipitation in the greater Alpine region are assessed by using statistical-dynamical downscaling. The downscaling procedure is applied to two 30-year periods (1971–2000 and 2071–2100, summer months only) taken from the results of a transient coupled ocean/atmosphere climate scenario simulation with increasing greenhouse gas concentrations. The downscaling results for the present-day climate are compared with observations. The estimated regional climate change during the next 100 years shows a general warming. The mean summer temperatures increase by 3 to 5 Kelvin. The most intense climatic warming is predicted in the western parts of the Alps. The amount of summer precipitation decreases in most parts of central Europe by more than 20 percent. Increasing precipitation is simulated only over the Adriatic area and parts of eastern central Europe. The results are compared with observed climate trends for the last decades and results of other regional climate change estimations. The observed trends and the majority of the simulated trends (including ours) have a number of common features. However, there are also climate change estimates of other groups which completely contradict our results. Received April 8, 1999 Revised November 16, 1999     

The Urban Heat Island Effect at Fairbanks, Alaska

Summary  Using climatic data from Fairbanks and rurally situated Eielson Air Force Base in Interior Alaska, the growth of the Fairbanks heat island was studied for the time period 1949 – 1997. The climate records were examined to distinguish between a general warming trend and the changes due to an increasing heat island effect. Over the 49-year period, the population of Fairbanks grew by more than 500%, while the population of Eielson remained relatively constant. The mean annual heat island observed at the Fairbanks International Airport grew by 0.4 °C, with the winter months experiencing a more significant increase of 1.0 °C. Primary focus was directed toward long-term heat island characterization based on season, wind speed, cloud cover, and time of day. In all cases, the minima temperatures were affected more than maxima and periods of calm or low wind speeds, clear winter sky conditions, and nighttime exhibited the largest heat island effects. Received August 17, 1998 Revised March 26, 1999     

城市化对长沙市两气象站气温记录的影响

为深入认识城市对其附近气象站气温的影响,采用位于长沙市区东部和西部两个气象观测站的2007-2009年的逐日气温、风向和风速资料,结合地表覆盖特征数据,对比分析了两站气象记录差异,并通过改进的城市影响指数模型估算了气温资料中的城市影响偏差。分析显示：（1）2007-2009年东、西气象站逐月平均气温（T_mean）、最高气温（T_max）和最低气温（T_min）差异很大,最大差异分别可达0.90℃、0.83℃和1.34℃;（2）受城市及风向的影响,两气象站的逐月城市影响指数（K）差异较大,东、西站平均K值分别为2.01和1.50,年内同一台站的K值存在季节变化规律;（3）两站逐月△K与△T之间存在极显著正相关关系;（4）东、西两站2007年T_mean中的城市增温最大,分别达0.63℃和0.45℃。城市附近气象站气温记录受城市规模、风向和风速等因素影响明显,在分析长历时气候变化特征和利用站点记录数据进行空间分析时,有必要对气温数据进行订正。     

Pairwise comparisons to reconstruct mean temperature in the Arctic Atlantic Region over the last 2,000 years

Existing multi-proxy climate reconstruction methods assume the suitably transformed proxy time series are linearly related to the target climate variable, which is likely a simplifying assumption for many proxy records. Furthermore, with a single exception, these methods face problems with varying temporal resolutions of the proxy data. Here we introduce a new reconstruction method that uses the ordering of all pairs of proxy observations within each record to arrive at a consensus time series that best agrees with all proxy records. The resulting unitless composite time series is subsequently calibrated to the instrumental record to provide an estimate of past climate. By considering only pairwise comparisons, this method, which we call PaiCo, facilitates the inclusion of records with differing temporal resolutions, and relaxes the assumption of linearity to the more general assumption of a monotonically increasing relationship between each proxy series and the target climate variable. We apply PaiCo to a newly assembled collection of high-quality proxy data to reconstruct the mean temperature of the Northernmost Atlantic region, which we call Arctic Atlantic, over the last 2,000 years. The Arctic Atlantic is a dynamically important region known to feature substantial temperature variability over recent millennia, and PaiCo allows for a more thorough investigation of the Arctic Atlantic regional climate as we include a diverse array of terrestrial and marine proxies with annual to multidecadal temporal resolutions. Comparisons of the PaiCo reconstruction to recent reconstructions covering larger areas indicate greater climatic variability in the Arctic Atlantic than for the Arctic as a whole. The Arctic Atlantic reconstruction features temperatures during the Roman Warm Period and Medieval Climate Anomaly that are comparable or even warmer than those of the twentieth century, and coldest temperatures in the middle of the nineteenth century, just prior to the onset of the recent warming trend.     

Northward migration of permafrost along the Mackenzie highway and climatic warming

Based on two field surveys of permafrost distribution, conducted 26 years apart, along the Mackenzie Highway south of Great Slave Lake, Canada, the southern limit of the sporadic discontinuous permafrost zone in the region has migrated northward by about 120 km. To substantiate that the disappearance of perennial frozen ground is largely caused by climatic warming, a detailed trend analysis of monthly air temperature records from nine weather stations was performed using the non-parametric Kendall's test. The results show that the region experienced a general warming trend for the period 1949–1989 and warming is more prominent in the minimum than the maximum temperature series. From estimates of the magnitude of warming trends on a monthly basis, the resultant increase in mean annual air temperature could readily lead to the observed northward migration of permafrost.     

Changes of atmospheric circulation in central Europe and their influence on climatic trends in the Czech Republic

This work deals with the influence of changes of atmospheric circulation on observed trends of 11 climatic elements at 21 stations in the Czech Republic in the period 1961–1998. Atmospheric circulation in central Europe is described by the German (Hess-Brezowsky) and Czech-Slovak (Brádka’s) subjective catalogues of synoptic types. In the study period there is a strong downward trend in the occurrence of anticyclonic types in Brádka’s catalogue in all seasons, this trend being most prominent in autumn. Westerly and northwesterly types become more frequent in autumn and winter, less frequent in spring and summer under both classifications. In the Hess-Brezowsky catalogue, the occurrence of anticyclonic types increases in winter, spring, and summer. To assess the effect of circulation changes on observed climate trends we have used the method of “hypothetical” seasonal trends that are calculated from a daily series, constructed by assigning the long-term monthly average of the given climatic element under a specific circulation type to each day classified with this type. The ratio of these circulation-conditioned trends and observed seasonal trends shows that changes in atmospheric circulation are the primary cause of massive winter warming and autumn cooling, which is connected with increasing precipitation and humidity. Summer climate trends are unrelated to changes in atmospheric circulation. Simultaneous use of more circulation classifications for the detection of climatic changes is highly recommended, as the long-term circulation trends depend on the catalogue applied.     

Interannual variability and expected regional climate change over North America

This study aims to analyse the interannual variability simulated by several regional climate models (RCMs), and its potential for disguising the effect of seasonal temperature increases due to greenhouse gases. In order to accomplish this, we used an ensemble of regional climate change projections over North America belonging to the North American Regional Climate Change Program, with an additional pair of 140-year continuous runs from the Canadian RCM. We find that RCM-simulated interannual variability shows important departures from observed one in some cases, and also from the driving models’ variability, while the expected climate change signal coincides with estimations presented in previous studies. The continuous runs from the Canadian RCM were used to illustrate the effect of interannual variability in trend estimation for horizons of a decade or more. As expected, it can contribute to the existence of transitory cooling trends over a few decades, embedded within the expected long-term warming trends. A new index related to signal-to-noise ratio was developed to evaluate the expected number of years it takes for the warming trend to emerge from interannual variability. Our results suggest that detection of the climate change signal is expected to occur earlier in summer than in winter almost everywhere, despite the fact that winter temperature generally has a much stronger climate change signal. In particular, we find that the province of Quebec and northwestern Mexico may possibly feel climate change in winter earlier than elsewhere in North America. Finally, we show that the spatial and temporal scales of interest are fundamental for our capacity of discriminating climate change from interannual variability.     

英国CRU高分辨率格点资料揭示的20世纪中国气候变化

中国覆盖比较完整的台站观测始于1951年,1951年之前虽然有一些观测记录,但是残缺不全.所以要建立更长的气候序列就要吸收代用资料,但是代用资料可能与气候要素仅有一定程度的相关,不可能一一对应,因此应用代用资料重建的气候序列有一定的不确定性.英国East Anglia大学的Climatic Research Unit(简称CRU)通过整合已有的若干个知名数据库,重建了一套覆盖完整、高分辨率、且无缺测的月平均地表气候要素数据集,时间范围覆盖1901～2003年,空间为0.5°×0.5°经纬网格覆盖所有陆地.这套资料和中国已有的气候数据相比具有如下优点: 第一,中国西部20世纪前半期非常缺少观测,CRU资料尽管包含插值带来的误差,经比较仍可作为有一定信度的参考; 第二,中国现有的百年温度序列只是年或季分辨率,而CRU资料达到月分辨率; 第三,建立这个序列仅使用观测结果,做统计内插,不包括代用资料所带来的不确定性.因此,CRU的序列与用代用资料补充得到的序列在资料方面有较大不同,比较这两个序列,不仅可以进一步确认中国气候变化的特征,也可以彼此校正.结果表明:(1)CRU资料反映的全国年平均温度年际变化和考虑代用资料重建的序列吻合得很好,相关系数达到0.84;(2)区域尺度上,两者在10个典型分区的气温变率也相当一致,相关整体保持在0.8左右,仅新疆西南部和西藏西北部两者差异较大;(3)CRU资料揭示的中国年总降水量在1951～2000年的变化与160站观测吻合,相关系数达到0.93;(4)CRU资料的中国东部四季降水量和重建资料十分一致,秋季一致性最好,相关0.93;(5)CRU资料和重建的序列比较一致地表现出中国温度和降水年代际变化的主要特征,其给出的20世纪20年代中国大旱和20世纪40年代中国高温的空间分布与作者过去的结论相一致.这表明,作者过去重建的中国气候序列有比较大的可靠性,而CRU资料也提供了新的信息,特别是在20世纪前半期和中国西部.     

Local climatic drivers of changes in phenology at a boreal-temperate ecotone in eastern North America

Ecosystems in biogeographical transition zones, or ecotones, tend to be highly sensitive to climate and can provide early indications of future change. To evaluate recent climatic changes and their impacts in a boreal-temperate ecotone in eastern North America, we analyzed ice phenology records (1975?C2007) for five lakes in the Adirondack Mountains of northern New York State. We observed rapidly decreasing trends of up to 21?days less ice cover, mostly due to later freeze-up and partially due to earlier break-up. To evaluate the local drivers of these lake ice changes, we modeled ice phenology based on local climate data, derived climatic predictors from the models, and evaluated trends in those predictors to determine which were responsible for observed changes in lake ice. November and December temperature and snow depth consistently predicted ice-in, and recent trends of warming and decreasing snow during these months were consistent with later ice formation. March and April temperature and snow depth consistently predicted ice-out, but the absence of trends in snow depth during these months, despite concurrent warming, resulted in much weaker trends for ice-out. Recent rates of warming in the Adirondacks are among the highest regionally, although with a different seasonality of changes (early winter > late winter) that is consistent with other lake ice records in the surrounding area. Projected future declines in snow cover could create positive feedbacks and accelerate current rates of ice loss due to warming. Climate sensitivity was greatest for the larger lakes in our study, including Wolf Lake, considered one of the most ecologically intact ??wilderness lakes?? in eastern North America. Our study provides further evidence of climate sensitivity of the boreal-temperate ecotone of eastern North America and points to emergent conservation challenges posed by climate change in legally protected yet vulnerable landscapes like the Adirondack Park.     

气候序列的层次结构

一个气候时间序列含有多个时间尺度 ,形成不同尺度的气候层次。气候是冷还是暖是随着尺度而变化的。文中用北半球地表月平均气温气候资料的子波变换分析表明 :气候突变点既随尺度有规律的变化 ,也具有随尺度变化而不变的性质 ,即标度不变性。不论什么尺度 ,气候总是有冷暖之分 ,这种自相似性可以帮助笔者从气候资料的子波变换中建立一个一维映射动力系统 ,它反映出气候突变时间的演变规律和气候的层次结构。