A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

Coverage probability of bootstrap confidence intervals in heavy-tailed frequency models, with application to precipitation data

Bootstrap, a technique for determining the accuracy of statistics, is a tool widely used in climatological and hydrological applications. The paper compares coverage probabilities of confidence intervals of high quantiles (5- to 200-year return values) constructed by the nonparametric and parametric bootstrap in frequency analysis of heavy-tailed data, typical for maxima of precipitation amounts. The simulation experiments are based on a wide range of models used for precipitation extremes (generalized extreme value, generalized Pareto, generalized logistic, and mixed distributions). The coverage probability of the confidence intervals is quantified for several sample sizes (n?=?20, 40, 60, and 100) and tail behaviors. We show that both bootstrap methods underestimate the width of the confidence intervals but that the parametric bootstrap is clearly superior to the nonparametric one. Even a misspecification of the parametric model—often unavoidable in practice—does not prevent the parametric bootstrap from performing better in most cases. A tendency to narrower confidence intervals from the nonparametric than parametric bootstrap is demonstrated in the application to high quantiles of distributions of observed maxima of 1- and 5-day precipitation amounts; the differences increase with the return level. The results show that estimation of uncertainty based on nonparametric bootstrap is highly unreliable, especially for small and moderate sample sizes and for very heavy-tailed data.     

Processes governing the predictability of the Atlantic meridional overturning circulation in a coupled GCM

The processes that govern the predictability of decadal variations in the North Atlantic meridional overturning circulation (MOC) are investigated in a long control simulation of the ECHO-G coupled atmosphere?Cocean model. We elucidate the roles of local stochastic forcing by the atmosphere, and other potential ocean processes, and use our results to build a predictive regression model. The primary influence on MOC variability is found to come from air?Csea heat fluxes over the Eastern Labrador Sea. The maximum correlation between such anomalies and the variations in the MOC occurs at a lead time of 2?years, but we demonstrate that the MOC integrates the heat flux variations over a period of 10?years. The corresponding univariate regression model accounts for 74.5% of the interannual variability in the MOC (after the Ekman component has been removed). Dense anomalies to the south of the Greenland-Scotland ridge are also shown to precede the overturning variations by 4?C6?years, and provide a second predictor. With the inclusion of this second predictor the resulting regression model explains 82.8% of the total variance of the MOC. This final bivariate model is also tested during large rapid decadal overturning events. The sign of the rapid change is always well represented by the bivariate model, but the magnitude is usually underestimated, suggesting that other processes are also important for these large rapid decadal changes in the MOC.     

单块积云降水参数的直接估算

介绍了单块积云的雷达回波参数与降雨参数的一元、二元回归分析分析结果表明，单块积云的降雨量、雨强和持续时间与雷达皮的顶高、面积的相关性较好。     

Probabilistic assessment of flood risks using trivariate copulas

In this paper, a copula-based methodology is presented for probabilistic assessment of flood risks and investigated the performance of trivariate copulas in modeling dependence structure of flood properties. The flood is a multi-attribute natural hazard and is characterized by mutually correlated flood properties peak flow, volume, and duration of flood hydrograph. For assessing flood risk, many studies have used bivariate analysis, but a more effective assessment can be possible considering all three mutually correlated flood properties simultaneously. This study adopts trivariate copulas for multivariate analysis of flood risks, and applied to a case study of flood flows of Delaware River basin at Port Jervis, NY, USA. On evaluation of various probability distributions for representation of flood variables, it is found that the flood peak flow and volumes can be best represented by Fréchet distribution, whereas flood duration by log-normal distribution. The joint distribution is modeled using four trivariate copulas, namely, three fully nested form of Archimedean copulas: Clayton, Gumbel–Hougaard, Frank copulas; and one elliptical copula: Student’s t copula. Based on distance-based performance measures, graphical tests, and tail-dependence measures, it is found that the Student’s t copula best representing the trivariate dependence structure of flood properties as compared to the other copulas. Similar results are found for bivariate copula modeling of flood variables pairs, where Student’s t copula performed better than the other copulas. The obtained copula-based joint distributions are used for multivariate analysis of flood risks, in terms of primary and secondary return periods. The resultant trivariate return periods are compared with univariate and bivariate return periods, and addressed the necessity of multivariate flood risk analysis. The study concludes that the trivariate copula-based methodology is a viable choice for effective risk assessment of floods.     

On the role of domain size and resolution in the simulations with the HIRHAM region climate model

We investigate the simulated temperature and precipitation of the HIRHAM regional climate model using systematic variations in domain size, resolution and detailed location in a total of eight simulations. HIRHAM was forced by ERA-Interim boundary data and the simulations focused on higher resolutions in the range of 5.5–12 km. HIRHAM outputs of seasonal precipitation and temperature were assessed by calculating distributed model errors against a higher resolution data set covering Denmark and a 0.25° resolution data set covering Europe. Furthermore the simulations were statistically tested against the Danish data set using bootstrap statistics. The results from the distributed validation of precipitation showed lower errors for the winter (DJF) season compared to the spring (MAM), fall (SON) and, in particular, summer (JJA) seasons for both validation data sets. For temperature, the pattern was in the opposite direction, with the lowest errors occurring for the JJA season. These seasonal patterns between precipitation and temperature are seen in the bootstrap analysis. It also showed that using a 4,000 × 2,800 km simulation with an 11 km resolution produced the highest significance levels. Also, the temperature errors were more highly significant than precipitation. In similarly sized domains, 12 of 16 combinations of variables, observation validation data and seasons showed better results for the highest resolution domain, but generally the most significant improvements were seen when varying the domain size.     

A Comparison of Higher-Order Vertical Velocity Moments in the Convective Boundary Layer from Lidar with In Situ Measurements and Large-Eddy Simulation

We have analyzed measurements of vertical velocity w statistics with the NOAA high resolution Doppler lidar (HRDL) from about 390 m above the surface to the top of the convective boundary layer (CBL) over a relatively flat and uniform agricultural surface during the Lidars-in-Flat-Terrain (LIFT) experiment in 1996. The temporal resolution of the zenith-pointing lidar was about 1 s, and the range-gate resolution about 30 m. Vertical cross-sections of w were used to calculate second- to fourth-moment statistics of w as a function of height throughout most of the CBL. We compare the results with large-eddy simulations (LES) of the CBL and with in situ aircraft measurements. A major cause of the observed case-to-case variability in the vertical profiles of the higher moments is differences in stability. For example, for the most convective cases, the skewness from both LES and observations changes more with height than for cases with more shear, with the observations changing more with stability than the LES. We also found a decrease in skewness, particularly in the upper part of the CBL, with an increase in LES grid resolution.     

Temporal and spatial patterns of modern climatic warming: case study of Northern Eurasia

Century-scale near-surface air temperature data from 744 weather stations in Russia and neighboring countries indicate that the temperature variations have distinct temporal patterns. Two periods, near the beginning and at the end of the 20th century, experienced the largest warming rates. Temperature changes in both periods were not uniform in time or space. We used statistical criteria and applied them to data at the weather stations to define a “tipping point” corresponding to the beginning of the modern climatic period. Results indicate that the position of this point depends on location, and in most cases falls into the interval from the early 1970s through the late 1980s. By means of spatial correlation analysis we delineated regions with coherent air temperature changes and calculated the region-specific rates and magnitudes of changes. We compared the distribution of regional tipping points in time and over space with large-scale atmospheric circulation patterns over northern Eurasia. We analyzed the 20th—early 21st century changes in the relative frequencies of the three circulation forms defined by Vangengheim-Girs classification, and found their qualitative correspondence with the spatial temperature patterns and spread of the tipping points in time. These results improve our knowledge about the regional structure and drivers of modern climate change in northern Eurasia, which is likely to hold the fingerprint of the anthropogenic signal. Findings of this study can be used to obtain insight into regional climatic changes in northern Eurasia over the next few decades.     

Squeezing information from regional climate change projections - results from a synthesis of CMIP5 results for south-east Queensland, Australia

We present a synthesis of CMIP5 model results for projected rainfall changes for a single region (south-east Queensland, Australia) and note that, as was evident in CMIP3 results, the multi-model mean projected changes for the late 21st century are not statistically significant for any season nor annually. Taking account of the number of statistically significant changes to mean rainfall, we find some evidence favouring a decrease in both spring and annual rainfall, but this is not compelling. In almost all cases the most frequent result is for no significant change. However, if we consider the number of results where there is a statistically significant change in the distributions of rainfall amounts, there appears to be slightly more information available for risk assessment studies. These numbers suggest an increase in the frequency of both wet and dry events during summer and spring, and a shift towards more frequent dry events during winter. There is no evidence for any significant changes to the distributions for either autumn or annually. The findings suggest that, in one respect, multi-model rainfall projections may contain more information than is evident from syntheses which focus on changes to the means and that, for some regions where changes in the frequency of wet and dry seasons/years have known impacts, the model projections may be more valuable than previously thought.     

Mid-Holocene and last glacial maximum climate simulations with the IPSL model: part II: model-data comparisons

The climates of the mid-Holocene (MH, 6,000 years ago) and the Last Glacial Maximum (LGM, 21,000 years ago) have been extensively documented and as such, have become targets for the evaluation of climate models for climate contexts very different from the present. In Part 1 of the present work, we have studied the MH and LGM simulations performed with the last two versions of the IPSL model: IPSL_CM4, run for the PMIP2/CMIP3 (Coupled Model Intercomparion Project) projects and IPSL_CM5A, run for the most recent PMIP3/CMIP5 projets. We have shown that not only are these models different in their simulations of the PI climate, but also in their simulations of the climatic anomalies for the MH and LGM. In the Part 2 of this paper, we first examine whether palaeo-data can help discriminate between the model performances. This is indeed the case for the African monsoon for the MH or for North America south of the Laurentide ice sheet, the South Atlantic or the southern Indian ocean for the LGM. For the LGM, off-line vegetation modelling appears to offer good opportunities to distinguish climate model results because glacial vegetation proves to be very sensitive to even small differences in LGM climate. For other cases such as the LGM North Atlantic or the LGM equatorial Pacific, the large uncertainty on the SST reconstructions, prevents model discrimination. We have examined the use of other proxy-data for model evaluation, which has become possible with the inclusion of the biogeochemistry morel PISCES in the IPSL_CM5A model. We show a broad agreement of the LGM–PI export production changes with reconstructions. These changes are related to the mixed layer depth in most regions and to sea-ice variations in the high latitudes. We have also modelled foraminifer abundances with the FORAMCLIM model and shown that the changes in foraminifer abundance in the equatorial Pacific are mainly forced by changes in SSTs, hence confirming the SST-foraminifer abundance relationship. Yet, this is not the case in all regions in the North Atlantic, where food availability can have a strong impact of foraminifer abundances. Further work will be needed to exhaustively examine the role of factors other than climate in piloting changes in palaeo-indicators.     

Trends in extremes of temperature, dew point, and precipitation from long instrumental series from central Europe

For the analysis of trends in weather extremes, we introduce a diagnostic index variable, the exceedance product, which combines intensity and frequency of extremes. We separate trends in higher moments from trends in mean or standard deviation and use bootstrap resampling to evaluate statistical significances. The application of the concept of the exceedance product to daily meteorological time series from Potsdam (1893 to 2005) and Prague–Klementinum (1775 to 2004) reveals that extremely cold winters occurred only until the mid-20th century, whereas warm winters show upward trends. These changes were significant in higher moments of the temperature distribution. In contrast, trends in summer temperature extremes (e.g., the 2003 European heatwave) can be explained by linear changes in mean or standard deviation. While precipitation at Potsdam does not show pronounced trends, dew point does exhibit a change from maximum extremes during the 1960s to minimum extremes during the 1970s.     

Variability of the Atlantic thermohaline circulation described by three-dimensional empirical orthogonal functions

We describe the use of bivariate three-dimensional empirical orthogonal functions (EOFs) in characterising low frequency variability of the Atlantic thermohaline circulation (THC) in the Hadley Centre global climate model, HadCM3. We find that the leading two modes are well correlated with an index of the meridional overturning circulation (MOC) on decadal timescales, with the leading mode alone accounting for 54% of the decadal variance. Episodes of coherent oscillations in the sub-space of the leading EOFs are identified; these episodes are of great interest for the predictability of the THC, and could indicate the existence of different regimes of natural variability. The mechanism identified for the multi-decadal variability is an internal ocean mode, dominated by changes in convection in the Nordic Seas, which lead the changes in the MOC by a few years. Variations in salinity transports from the Arctic and from the North Atlantic are the main feedbacks which control the oscillation. This mode has a weak feedback onto the atmosphere and hence a surface climatic influence. Interestingly, some of these climate impacts lead the changes in the overturning. There are also similarities to observed multi-decadal climate variability.     

Radiative and Evaporative Cooling in the Entrainment Zone of Stratocumulus – the Role of Longwave Radiative Cooling Above Cloud Top

A mixing fraction determines the relative amount of above-cloud-top air that has been mixed into a cloudy air parcel. A method, based on the use of mixing fractions, to calculate the cooling effects due to mixing, longwave radiation and phase changes at cloud top is derived and discussed. We compute cooling effects for the whole range of mixing fraction for two observed cases of the stratocumulus-topped marine boundary layer. In both cases the total radiative cooling effect is found to be the most dominant contributor to the negative buoyancy excess found at cloud top. The largest radiative cooling rates are found for clear-air parcels immediately adjacent to cloud top rather than inside the cloud. With the help of a simple longwave radiation model, we show this to be caused by clear-air radiative cooling due to the temperature inversion at cloud top. Further we show that flux profiles in the entrainment zone can be computed from data obtained from a horizontal level run that is half the time in cloud and half the time out of cloud.     

Predicting thermal vulnerability of stream and river ecosystems to climate change

We use a predictive model of mean summer stream temperature to assess the vulnerability of USA streams to thermal alteration associated with climate change. The model uses air temperature and watershed features (e.g., watershed area and slope) from 569 US Geological Survey sites in the conterminous USA to predict stream temperatures. We assess the model for predicting climate-related variation in stream temperature by comparing observed and predicted historical stream temperature changes. Analysis of covariance confirms that observed and predicted changes in stream temperatures respond similarly to historical changes in air temperature. When applied to spatially-downscaled future air temperature projections (A2 emission scenario), the model predicts mean warming of 2.2 °C for the conterminous USA by 2100. Stream temperatures are most responsive to climate changes in the Cascade and Appalachian Mountains and least responsive in the southeastern USA. We then use random forests to conduct an empirical sensitivity analysis to identify those stream features most strongly associated with both observed historical and predicted future changes in summer stream temperatures. Larger changes in stream temperature are associated with warmer future air temperatures, greater air temperature changes, and larger watershed areas. Smaller changes in stream temperature are predicted for streams with high initial rates of heat loss associated with longwave radiation and evaporation, and greater base-flow index values. These models provide important insight into the potential extent of stream temperature warming at a near-continental scale and why some streams will likely be more vulnerable to climate change than others.     

秦皇岛市气温及其变化对居民死亡风险的影响研究

气温及其变化是影响人群健康特别是死亡的重要环境危险因素。为了揭示气温对秦皇岛市居民死亡人数的影响,基于2014—2020年该市各区、县逐日气象资料和居民死亡资料,采用广义相加模型（GAM）和分布滞后非线性模型（DLNM）研究了气温、气温日较差和24 h变温对非意外死亡、循环系统疾病死亡、呼吸系统疾病死亡人数的影响。按性别、年龄分层建模,使用相对危险度（Relative Risk,RR）量化了暴露在特定气温变化状态下的死亡风险。采用非参数双变量响应模型分析了气温与变温的协同影响效应。结果显示:（1）秦皇岛市居民非意外死亡、循环系统疾病死亡、呼吸系统疾病死亡人数全年峰值均出现在最冷的1月,气温对3类死亡人数的影响以冷效应为主且具有滞后效应,而高温具有即时效应。（2）气温日较差与非意外死亡、循环系统疾病死亡的总体暴露反应曲线呈“U”型分布,较大的气温日较差与上述两类死亡存在显著的风险效应,其中循环系统疾病死亡受影响最大,大的气温日较差（19℃）累积3 d相对危险度为1.27,其95%的置信区间（95%CI）为1.15—1.4,而其对呼吸系统疾病死亡的风险效应未通过显著性检验。（3）24 h变温对非意外死亡、循环系统疾病死亡总体影响效应的暴露曲线呈非线性递增趋势,其中正变温呈现显著的风险效应。（4）性别、年龄分组结果显示,女性对气温变化更敏感,男性对气温变化存在一定的滞后效应,老年人群更容易受到气温变化的影响。（5）低温与变温的协同作用加剧了死亡风险。总体上,冬季低温背景与大幅度气温变化相叠加对当地老年居民死亡影响风险最大,应予适时重点预防。      

Response of evapotranspiration and water availability to the changing climate in Northern Eurasia

We introduce a probabilistic framework for vulnerability analysis and use it to quantify current and future vulnerability of the US water supply system. We also determine the contributions of hydro-climatic and socio-economic drivers to the changes in projected vulnerability. For all scenarios and global climate models examined, the US Southwest including California and the southern Great Plains was consistently found to be the most vulnerable. For most of the US, the largest contributions to changes in vulnerability come from changes in supply. However, for some areas of the West changes in vulnerability are caused mainly by changes in demand. These changes in supply and demand result mainly from changes in evapotranspiration rather than from changes in precipitation. Importantly, changes in vulnerability from projected changes in the standard deviations of precipitation and evapotranspiration are of about the same magnitude or larger than those from changes in the corresponding means over most of the US, except in large areas of the Great Plains, in central California and southern and central Texas.     

基于Copula函数的北京强降水频率及危险性分析

客观分析强降水事件的发生频率及其致灾因子危险性,能为局地洪涝灾害的防灾、减灾规划及灾害预警提供科学依据。探讨了基于二元Copula函数的强降水致灾变量联合分布及其在强降水危险性分析中的应用。利用北京地区2005-2014年逐时降水资料提取强降水事件案例,通过建立能反映两个主要致灾因素--降水持续时间和过程降水量依存关系的二元联合分布模型,计算了北京地区强降水事件条件重现期,并以此为基础开展危险性分析。研究表明,北京地区强降水事件的持续时间多小于24 h,且主要服从广义极值和对数正态分布,而过程降水量则更适用于广义极值分布;通过Gumbel Copula函数能较好刻画过程降水量与持续时间的相互依存关系。北京地区短时强降水重现期受持续时间影响明显,仅基于降水量的重现期估算会低估其致灾危险性,利用基于Copula函数的条件重现期能更合理描述不同强降水情景致灾因子的危险性特征及其空间差异性特征。北京地区持续时间小于12 h、过程降水量在50 mm以上的强降水事件多呈东北-西南走向,而持续时间在6 h以内的50 mm以上强降水则在北京城区及东北部地区更加频繁。     

The use of bootstrap confidence intervals for the correlation coefficient in climatology

Summary The importance of defining confidence intervals for sample statistics that are used to estimate characteristics of the parent population(s) is emphasised. Not all sample statistics are unbiased estimators or have normally distributed sampling distributions and so it is not always easy to reflect the reliability of the estimator. In such cases, Efron's bias corrected percentile method, which uses bootstrap samples to estimate the bias and makes no assumptions about the distribution of the sample statistic can be used to define confidence limits for the population parameter. The method is explained and the procedure for calculating the confidence limits is outlined.As an example, bootstrap confidence limits calculated for the maximum correlation between the Southern Oscillation Index and rainfall at South African stations over the period 1935–1983 suggest that the sample correlation is an unreliable measure of the true association. One possible reason for this is that the association is thought to have broken down during the 1940s. However, the reliability of the estimator does not seem to improve when confidence limits are calculated for the 30-year period 1954–1983. It is possible that the width of the confidence interval is an indication of more than one distinct statistical population.     

Regional hydrologic consequences of increases in atmospheric CO2 and other trace gases

Concern over changes in global climate caused by growing atmospheric concentrations of carbon dioxide and other trace gases has increased in recent years as our understanding of atmospheric dynamics and global climate systems has improved. Yet despite a growing understanding of climatic processes, many of the effects of human-induced climatic changes are still poorly understood. Major alterations in regional hydrologic cycles and subsequent changes in regional water availability may be the most important effects of such climatic changes. Unfortunately, these are among the least well-understood impact. Water-balance modeling techniques - modified for assessing climatic impacts - were developed and tested for a major watershed in northern California using climate-change scenarios from both state-of-the-art general circulation models and from a series of hypothetical scenarios. Results of this research suggest strongly that plausible changes in temperature and precipitation caused by increases in atmospheric trace-gas concentrations could have major impacts on both the timing and magnitude of runoff and soil moisture in important agricultural areas. Of particular importance are predicted patterns of summer soil-moisture drying that are consistent across the entire range of tested scenarios. The decreases in summer soil moisture range from 8 to 44%. In addition, consistent changes were observed in the timing of runoff-specifically dramatic increases in winter runoff and decreases in summer runoff. These hydrologic results raise the possibility of major environmental and socioeconomic difficulties and they will have significant implications for future water-resource planning and management.     

Variability of extreme events in the Colombian Pacific and Caribbean catchment basins

This paper analyses the behavior of extreme events of surface precipitation and temperature inside the Pacific and Caribbean Catchment Basins in Colombia using several datasets such as observations, reconstructed data, NCEP-NCAR and ERA-40 reanalyses and data from the regional model REMO. We use an extreme value method that selects the time series excesses over a nonstationary threshold and adjusts them to a generalized Pareto distribution. The goodness of fit is evaluated through a test that includes the Cramer–von Mises, Kolmogorov–Smirnov and Anderson–Darling statistics and the p values generated by parametric bootstrap resampling. The test not only evaluates the goodness of fit but also the threshold choice. The parameters are presented in maps that allow recognition of the features of the extreme behaviour inside the catchment basins, and differences and similarities between them. Maps of return periods for the maximum extreme events are also presented. A strong influence of the El Niño–Southern oscillation on the extreme events of both temperature and precipitation is found in the two catchment basins.