基于集合预报极端天气预测指数的浙江分类强对流预报模型

利用2016—2021年ECWMF集合预报资料、浙江自动站实况资料等,计算浙江短时强降水、雷暴大风和冰雹等强对流天气相关物理量的极端天气预报指数（EFI：Extreme Forecast Index）,分析EFI分布特征,并构建了分类强对流预报模型。结果表明：强对流天气与物理量的EFI有密切联系,发生短时强降水时,对流有效位能、整层可降水量、850 hPa与500 hPa温差和位温差的EFI较大,而垂直风切变的EFI为负值,因而较小的垂直风切变更有利于出现极端降水;发生雷暴大风和冰雹时,对流有效位能、850 hPa与500 hPa温差和位温差以及850 hPa温度露点差的EFI较大,700 hPa露点温度的EFI为负值,与上层干冷下层暖湿的有利层结条件有关。利用支持向量机多分类方法,将强对流天气相关物理量的EFI作为特征值开展训练,构建的预报模型对于非局地强对流天气有较好的预报效果,其中短时强降水的误判率明显低于雷暴大风。     

A comparison of the main methods for estimating probabilities of extreme still water levels

Sea-level return periods are estimated at 18 sites around the English Channel using: (i) the annual maxima method; (ii) the r-largest method; (iii) the joint probability method; and (iv) the revised joint probability method. Tests are undertaken to determine how sensitive these four methods are to three factors which may significantly influence the results; (a) the treatment of the long-term trends in extreme sea level; (b) the relative magnitudes of the tidal and non-tidal components of sea level; and (c) the frequency, length and completeness of the available data. Results show that unless sea-level records with lengths of at least 50 years are used, the way in which the long-term trends is handled in the different methods can lead to significant differences in the estimated return levels. The direct methods (i.e. methods i and ii) underestimate the long (> 20 years) period return levels when the astronomical tidal variations of sea level (relative to a mean of zero) are about twice that of the non-tidal variations. The performance of each of the four methods is assessed using prediction errors (the difference between the return periods of the observed maximum level at each site and the corresponding data range). Finally, return periods, estimated using the four methods, are compared with estimates from the spatial revised joint probability method along the UK south coast and are found to be significantly larger at most sites along this coast, due to the comparatively short records originally used to calibrate the model in this area. The revised joint probability method is found to have the lowest prediction errors at most sites analysed and this method is recommended for application wherever possible. However, no method can compensate for poor data.     

临汾地震安全性评价的极值理论方法

本文根据极值理论建立了烈度超越给定值Ｉｊ的平均重现期公式，根据最大熵原理建立了未来Ｔ年烈度超越给定值Ｉｊ的概率和烈度超越给定值Ｉｊ的平均重现期之间的关系式。利用１０２２─１９９３年的地震资料，计算了临汾（３６．１０°Ｎ，１１１．５０°Ｅ）周围４级以上地震在临汾造成的烈度，绘制了未来１００年临汾的烈度超越概率曲线（地震危险性曲线）。结果表明，计算场地烈度的极值理论方法可作为地震危险性分析的综合概率法的补充和验证。     

On the Bayesian analysis of the earthquake hazard in the North-East Indian peninsula

The Bayesian extreme-value distribution of earthquake occurrences has been used to estimate the seismic hazard in 12 seismogenic zones of the North-East Indian peninsula. The Bayesian approach has been used very efficiently to combine the prior information on seismicity obtained from geological data with historical observations in many seismogenic zones of the world. The basic parameters to obtain the prior estimate of seismicity are the seismic moment, slip rate, earthquake recurrence rate and magnitude. These estimates are then updated in terms of Bayes’ theorem and historical evaluations of seismicity associated with each zone. From the Bayesian analysis of extreme earthquake occurrences for North-East Indian peninsula, it is found that for T = 5 years, the probability of occurrences of magnitude (M _w = 5.0–5.5) is greater than 0.9 for all zones. For M _w = 6.0, four zones namely Z1 (Central Himalayas), Z5 (Indo-Burma border), Z7 (Burmese arc) and Z8 (Burma region) exhibit high probabilities. Lower probability is shown by some zones namely␣Z4, Z12, and rest of the zones Z2, Z3, Z6, Z9, Z10 and Z11 show moderate probabilities.     

An extreme value analysis of the flow of Burbage Brook

An extreme value analysis of the flow of Burbage Brook is carried out by modelling peaks over a high threshold. The aims are to illustrate recently developed statistical techniques and to report on interesting features of the flow of the brook over a 58-year period. Peak flows are found to show marked seasonal variation and a downward trend. Then-year return level is estimated for various values ofn, and the reliability of the estimates is assessed.     

Climate change and North Sea storm surge extremes: an ensemble study of storm surge extremes expected in a changed climate projected by four different regional climate models

The coastal zones are facing the prospect of changing storm surge statistics due to anthropogenic climate change. In the present study, we examine these prospects for the North Sea based on numerical modelling. The main tool is the barotropic tide-surge model TRIMGEO (Tidal Residual and Intertidal Mudflat Model) to derive storm surge climate and extremes from atmospheric conditions. The analysis is carried out by using an ensemble of four 30-year atmospheric regional simulations under present-day and possible future-enhanced greenhouse gas conditions. The atmospheric regional simulations were prepared within the EU project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). The research strategy of PRUDENCE is to compare simulations of different regional models driven by the same global control and climate change simulations. These global conditions, representative for 1961–1990 and 2071–2100 were prepared by the Hadley Center based on the IPCC A2 SRES scenario. The results suggest that under future climatic conditions, storm surge extremes may increase along the North Sea coast towards the end of this century. Based on a comparison between the results of the different ensemble members as well as on the variability estimated from a high-resolution storm surge reconstruction of the recent decades it is found that this increase is significantly different from zero at the 95% confidence level for most of the North Sea coast. An exception represents the East coast of the UK which is not affected by this increase of storm surge extremes.     

A case for a reassessment of the risks of extreme hydrological hazards in the Caribbean

There is an urgent need for the development and implementation of modern statistical methodology for long-term risk assessment of extreme hydrological hazards in the Caribbean. Notwithstanding the inevitable scarcity of data relating to extreme events, recent results and approaches call into question standard methods of estimation of the risks of environmental catastrophes that are currently adopted. Estimation of extreme hazards is often based on the Gumbel model and on crude methods for estimating predictive probabilities. In both cases the result is often a remarkable underestimation of the predicted probabilities for disasters of large magnitude. Simplifications do not stop here: assumptions of data homogeneity and temporal independence are usually made regardless of potential inconsistencies with genuine process behaviour and the fact that results may be sensitive to such mis-specifications. These issues are of particular relevance for the Caribbean, given its exposure to diverse meteorological climate conditions.In this article we present an examination of predictive methodologies for the assessment of long-term risks of hydrological hazards, with particular focus on applications to rainfall and flooding, motivated by three data sets from the Caribbean region. Consideration is given to classical and Bayesian methods of inference for annual maxima and daily peaks-over-threshold models. We also examine situations where data non-homogeneity is compromised by an unknown seasonal structure, and the situation in which the process under examination has a physical upper limit. We highlight the fact that standard Gumbel analyses routinely assign near-zero probability to subsequently observed disasters, and that for San Juan, Puerto Rico, standard 100-year predicted rainfall estimates may be routinely underestimated by a factor of two.     

Mistreatment of the economic impacts of extreme events in the Stern Review Report on the Economics of Climate Change

The Stern Review on the Economics of Climate Change has focused debate on the costs and benefits of alternative courses of action on climate change. This refocusing has helped to move debate away from science of the climate system and on to issues of policy. However, a careful examination of the Stern Review's treatment of the economics of extreme events in developed countries, such as floods and tropical cyclones, shows that the report is selective in its presentation of relevant impact studies and repeats a common error in impacts studies by confusing sensitivity analyses with projections of future impacts. The Stern Review's treatment of extreme events is misleading because it overestimates the future costs of extreme weather events in developed countries by an order of magnitude. Because the Stern Report extends these findings globally, the overestimate propagates through the report's estimate of future global losses. When extreme events are viewed more comprehensively the resulting perspective can be used to expand the scope of choice available to decision makers seeking to grapple with future disasters in the context of climate change. In particular, a more comprehensive analysis underscores the importance of adaptation in any comprehensive portfolio of responses to climate change.     

21世纪初极端天气气候事件研究进展

由于极端天气气候事件的严重影响，越来越多的研究开始关注其变化情况。从观测分析到模拟研究，几乎都发现极端气温、降水事件发生了显著变化，而且在全球变暖的大背景下，未来有些极端事件可能会发生频数更高或强度更强。当然，研究结论也存在一定程度的不确定性，从模式模拟来看，目前模拟结果仍存在不确定性，不同模式的结果间常常存在较大的差异；而从观测分析来看，研究主要局限于20世纪后半叶，如果对更长时间作分析，结论或许会有所不同。文章从最基本的极端天气气候事件的定义出发，结合观测事实和模拟研究两个主要方面来介绍近几年来极端事件研究取得的主要进展，最后简单地总结了这些进展，并提出了进一步研究的思路。      

Soil erosion and sediment interception by check dams in a watershed for an extreme rainstorm on the Loess Plateau,China

The magnitude of soil erosion and sediment load reduction efficiency of check dams under extreme rainstorms is a long-standing concern. The current paper aims to use check dams to deduce the amount of soil erosion under extreme rainstorms in a watershed and to identify the difference in sediment interception efficiency of different types of check dams. Based on the sediment deposition at 12 check dams with 100% sediment interception efficiency and sub-catchment clustering by taking 12 dam-controlled catchments as clustering criteria, the amount of soil erosion resulting from an extreme rainstorm event on July 26, 2017 (named “7·26” extreme rainstorm) was estimated in the Chabagou watershed in the hill and gully region of the Loess Plateau. The differences in the sediment interception efficiency among the check dams in the watershed were analyzed according to field observations at 17 check dams. The results show that the average erosion intensity under the “7–26” extreme rainstorm was approximately 2.03 × 10⁴ t/km², which was 5 times that in the second largest erosive rainfall in 2017 (4.15 × 10³ t/km²) and 11–384 times that for storms in 2018 (0.53 × 10² t/km² - 1.81 × 10³ t/km²). Under the “7–26” extreme rainstorm, the amount of soil erosion in the Chabagou watershed above the Caoping hydrological station was 4.20 × 10⁶ t. The sediment interception efficiency of the check dams with drainage canals (including the destroyed check dams) and with drainage culverts was 6.48 and 39.49%, respectively. The total actual sediment amount trapped by the check dams was 1.11 × 10⁶ t, accounting for 26.36% of the total amount of soil erosion. In contrast, 3.09 × 10⁶ t of sediment were input to the downstream channel, and the sediment deposition in the channel was 2.23 × 10⁶ t, accounting for 53.15% of the total amount of soil erosion. The amount of sediment transport at the hydrological station was 8.60 × 10⁵ t. The Sediment Delivery Ratio (SDR) under the “7·26” extreme rainstorm was 0.21. The results indicated that the amount of soil erosion was huge, and the sediment interception efficiency of the check dams was greatly reduced under extreme rainstorms. It is necessary to strengthen the management and construction technology standards of check dams to improve the sediment interception efficiency and flood safety in the watershed.