长江流域极端降水过程事件的年内分布特征

基于1960-2016年乌江流域41个气象站的逐日降水观测资料,利用线性倾向估计、滑动平均、累积距平等方法计算趋势系数和气候趋势,分析了研究时段内乌江流域年暴雨等级面雨量、年平均最大日降水量、年平均极端持续强降水次数和对应降水量的时空分布特征,分析表明：（1）乌江流域年暴雨等级面雨量和日数呈显著增加趋势（均通过α=0.05显著性水平检验）,而暴雨强度呈不显著性增加趋势;5-10月各旬暴雨等级面雨量及日数变化基本一致,5月中旬至8月上旬呈单峰型分布,暴雨强度呈波动增减分布。（2）近57 a乌江流域年平均最大日降水量年代际变化比较明显。（3）乌江流域发生极端持续强降水年平均次数呈不显著的减少趋势,但极端持续强降水量呈不显著的增加趋势。采用耿贝尔极值Ⅰ型分布法计算了乌江流域5个代表站不同重现期日最大降水量值,发现不同站点日极端最大降水量重现期水平差异明显,重现期时间尺度存在临界点,约为50 a。

     

中国近50 a极端降水事件变化特征的季节性差异

强降水极易造成暴雨灾害,尤其是突发性强的短时强降水,动态监测、影响评估和风险预估是灾害防御的重要手段。但目前气象服务业务中,强降水的定量评估和风险预估还是以天为单位,现代气象服务精细化的需求迫切要将时间分辨率提升至小时尺度。本文利用1951-2018年国家气象观测站小时降水观测资料,从小时尺度界定站点、大区域、小区域降水过程的辨识方法。基于改进的降水过程综合强度评估方法,在概率密度分布的基础上,重新划分了极端、特强、强、较强、中等五个等级的降水过程综合强度指数。检验论证显示,基于小时分辨率降水过程的自动提取和评估方法合理,具有可操作性,能够对过程性降水、短时降水过程动态评估和预评估,可实时支撑气象服务业务,提升气象防灾减灾能力,也为后续开展短时强降水影响评估和风险预估建立基础。

     

Vegetation response to climate and climatic extremes in northwest Bangladesh: a quantile regression approach

Theoretical and Applied Climatology - The present study assessed the vegetation response to climate in the water-stressed northwest Bangladesh (NWB). The quantile regression analysis was employed...     

Soil temperature response in Korea to a changing climate using a land surface model

The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme — the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change.     

North-Atlantic SST amplified recent wintertime European land temperature extremes and trends

Europe has been warming over the past 30?years. In particular all seasonal temperature records have been broken since 2003, which altered socio-economic and environmental systems. Since we expect this trend in both mean and extreme temperatures to continue along the twenty first century under enhanced radiative forcing, it is crucial to understand the underlying mechanisms of such climate variations to help in considering adaptation or mitigation strategies to reduce the impacts of a warmer climate. From a statistical analysis we show that the inter-annual variability of European seasonal temperatures can be reconstructed from North-Atlantic atmospheric circulation only, but not their recent trends and extreme seasons. Adding North-Atlantic sea-surface temperature (SST) as a predictor helps improving the reconstruction, especially in autumn and winter. Sensitivity experiments with the MM5 regional model over 2003?C2007 suggest that the anomalous SST enhance European land temperatures through the upper-air advection of heat and water vapor, interacting with radiative fluxes over the continent. This mechanism is pronounced in autumn and winter, where estimates of SST influence as obtained from MM5 are in agreement with those obtained from statistical regressions. We find a lesser SST influence in spring and summer, where local surface and radiative feedbacks are the main amplifiers of recent extremes.     

1951-1990年中国极端气温变化分析

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

     

Statistics of extremes in climate change

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

Regionally optimized forest management under changing climate

The purpose of this study was to optimize forest management for a forest region (the total area of forest and scrub land 1.54 mill. ha) under changing climate by using the large-scale forestry scenario model MELA and sample plot data from the geo-referenced National Forest Inventory (NFI). The MELA model is based on integrated simulation and optimisation; in the simulation it utilises empirical tree-level models into which the impacts of climate change were introduced by transfer variables derived by using the physiological model FinnFor. Six scenarios with differences in climate and forest management were defined. In simulations, the accelerating tree growth caused by climate change resulted in an increase in maximum sustainable removal of trees at regional level. Changes in regionally optimized forest management were also detected during the analysis period of 30 years; the proportion of thinnings increased because the stands fulfilled the thinning requirements earlier than in the current climate. This study was the first attempt to solve endogenously maximum sustainable timber production and corresponding forest management at the regional level under different climate scenarios. When implemented in the MELA system, which is widely used in Finnish forestry, the transfer variables offer means of disseminating the results from physiological studies to planning of adjustment and mitigation measures under changing climate.     

Evolution of the Parisian urban climate under a global changing climate

The evolution of the Parisian urban climate under a changing climate is analyzed from long-term offline numerical integrations including a specific urban parameterization. This system is forced by meteorological conditions based on present-climate reanalyses (1970–2007), and climate projections (2071–2099) provided by global climate model simulations following two emission scenarios (A1B and A2). This study aims at quantifying the impact of climate change on air temperature within the city and in the surroundings. A systematic increase of 2-meter air temperature is found. In average according to the two scenarios, it reaches +?2.0/2.4°C in winter and +?3.5/5.0°C in summer for the minimum and maximum daily temperatures, respectively. During summer, the warming trend is more pronounced in the surrounding countryside than in Paris and suburbs due to the soil dryness. As a result, a substantial decrease of the strong urban heat islands is noted at nighttime, and numerous events with negative urban heat islands appear at daytime. Finally, a 30% decrease of the heating degree days is quantified in winter between present and future climates. Inversely, the summertime cooling degree days significantly increase in future climate whereas they are negligible in present climate. However, in terms of accumulated degree days, the increase of the demand in cooling remains smaller than the decrease of the demand in heating.     

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.     

Changing trends of thermal extremes in Pakistan

Extreme events have gained considerable scientific attention recently due to their potentially catastrophic impacts. Heat waves are thought to be more pronounced now in most parts of the world, and especially in South Asia, but doubts remain. The aim of this study is to calculate the frequency and intensity of heat waves in South Asia, focusing on Pakistan and identifying the regions within Pakistan that are most vulnerable to heat waves. Analyses have been performed both at provincial and country levels from 1961 to 2009. The provincial level analysis shows positive trends for heat waves of magnitudes ≥40°C and ≥45°C for 5 and 7 consecutive days. Events of magnitude ≥40°C and ≥45°C for 10 consecutive days also increased in frequency in Punjab, Sindh, and Balochistan. These regions are therefore considered to be the regions most vulnerable to heat wave events in Pakistan. The Balochistan region shows a consistently increasing trend throughout the study period, which may lead to more frequent drought in the future. The country level analysis indicates an increase in the frequency of 5 and 7 consecutive days heat waves at all defined temperature thresholds. The 10-days heat waves spells show a slight increase at ≥40°C and no significant change at ≥45°C. The Gilgit Baltistan and Azad Jammu & Kashmir areas reported no events at ≥45°C for 5, 7 and 10 continuous days. It is anticipated that with a long term rise in temperatures around the globe, heat waves will become more frequent and intense in all parts of the world, including Pakistan.     

Spatial distribution of temperature trends and extremes over Maharashtra and Karnataka States of India

Earth surface temperatures are changing worldwide together with the changes in the extreme temperatures. The present study investigates trends and variations of monthly maximum and minimum temperatures and their effects on seasonal fluctuations at different climatological stations of Maharashtra and Karnataka states of India. Trend analysis was performed on annual and seasonal mean maximum temperature (TMAX) and mean minimum temperature (TMIN) for the period 1969 to 2006. During the last 38 years, an increase in annual TMAX and TMIN has occurred. At most of the locations, the increase in TMAX was faster than the TMIN, resulting in an increase in diurnal temperature range. At the same time, annual mean temperature (TM) showed a significant increase over the study area. Percentiles were used to identify extreme temperature indices. An increase in occurrence of warm extremes was observed at southern locations, and cold extremes increased over the central and northeastern part of the study area. Occurrences of cold wave conditions have decreased rapidly compared to heat wave conditions.     

Recent trends in observed temperature and precipitation extremes in the Yangtze River basin,China

Summary The present study is an analysis of the observed extreme temperature and precipitation trends over Yangtze from 1960 to 2002 on the basis of the daily data from 108 meteorological stations. The intention is to identify whether or not the frequency or intensity of extreme events has increased with climate warming over Yangtze River basin in the last 40 years. Both the Mann-Kendall (MK) trend test and simple linear regression were utilized to detect monotonic trends in annual and seasonal extremes. Trend tests reveal that the annual and seasonal mean maximum and minimum temperature trend is characterized by a positive trend and that the strongest trend is found in the winter mean minimum in the Yangtze. However, the observed significant trend on the upper Yangtze reaches is less than that found on the middle and lower Yangtze reaches and for the mean maximum is much less than that of the mean minimum. From the basin-wide point of view, significant increasing trends are observed in 1-day extreme temperature in summer and winter minimum, but there is no significant trend for 1-day maximum temperature. Moreover, the number of cold days ≤0 °C and ≤10 °C shows significant decrease, while the number of hot days (daily value ≥35 °C) shows only a minor decrease. The upward trends found in the winter minimum temperature in both the mean and the extreme value provide evidence of the warming-up of winter and of the weakening of temperature extremes in the Yangtze in last few decades. The monsoon climate implies that precipitation amount peaks in summer as does the occurrence of heavy rainfall events. While the trend test has revealed a significant trend in summer rainfall, no statistically significant change was observed in heavy rain intensity. The 1-day, 3-day and 7-day extremes show only a minor increase from a basin-wide point of view. However, a significant positive trend was found for the number of rainstorm days (daily rainfall ≥50 mm). The increase of rainstorm frequency, rather than intensity, on the middle and lower reaches contributes most to the positive trend in summer precipitation in the Yangtze.     

Spatiotemporal variability of extreme precipitation in Shaanxi province under climate change

Extreme climate index is one of the useful tools to monitor and detect climate change. The primary objective of this study is to provide a more comprehensively the changes in extreme precipitation between the periods of 1954–1983 and 1984–2013 in Shaanxi province under climate change, which will hopefully provide a scientific understanding of the precipitation-related natural hazards such as flood and drought. Daily precipitation from 34 surface meteorological stations were used to calculated 13 extreme precipitation indices (EPIs) generated by the joint World Meteorological Organization Commission for Climatology (CCI)/World Climate Research Programme (WCRP) project on Climate Variability and Predictability (CLIVAR) expect Team on climate change Detection, Monitoring and Indices (ETCCDMI). Two periods including 1954–1983 and 1984–2013 were selected and five types of precipitation days (R10mm-R100mm) were defined, to provide more evidences of climate change impacts on the extreme precipitation events, and specially, to investigate the changes in different types of precipitation days. The EPIs were generated using RClimRex software, and the trends were analyzed using Mann-Kendall nonparametric test and Sen’s slope estimator. The relationships between the EPIs and the impacts of climate anomalies on typical EPIs were investigated using correlation and composite analysis. The mainly results include: 1) Thirteen EPIs, except consecutive dry day (CDD), were positive trends dominated for the period of 1984–2013, but the trends were not obvious for the period of 1954–1983. Most of the trends were not statistically significant at 5 % significance level. 2) The spatial distributions of stations that exhibited positive and negative trends were scattered. However, the stations that had negative trends mainly distributed in the north of Shaanxi province, and the stations that had positive trends mainly located in the south. 3) The percentage of stations that had positive trends had increased from the period of 1954–1983 to 1984–2013 for all the 13 EPIs except CDD, indicating the possible climate change impacts on extreme precipitation events. 4) The correlations between annual total wet-day precipitation (PRCPTOT) and other 12 EPIs varied for different indices and stations. The composite analysis found that El Niño Southern Oscillation (ENSO) exerted greater impacts on PRCPTOT than other EPIs and greater in the Guanzhong Plain (GZP) than Qinling-Dabashan Mountains (QDM) and Shanbei Plateau (SBP) of Shaanxi province.     

Spatiotemporal variations in climate moisture indices in Georgia under global warming

Using observational data from 50 weather stations in Georgia for the period of 1936-2013, the following climate indices of moisture regime are studied: maximum 1-day precipitation, maximum 5-day precipitation, the simple daily intensity index, the number of days with precipitation equal to not less than 10, 20, and 50 mm, number of consecutive wet and dry days. Geoinformation maps of the spatial structure are plotted, and the dynamics of these indices is studied for the period of global warming. Expected changes in the moisture regime in different physiographic regions in Georgia are assessed.     

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.     

Transforming local natural resource conflicts to cooperation in a changing climate: Bangladesh and Nepal lessons

ABSTRACT

Since the 1990s, climate change impact discourse has highlighted potential for large scale violent conflicts. However, the role of climate stresses on local conflicts over natural resources, the role of policies and adaptation in these conflicts, and opportunities to enhance cooperation have been neglected. These gaps are addressed in this paper using evidence from participatory action research on 79 cases of local collective action over natural resources that experience conflicts in Bangladesh and Nepal. Climate trends and stresses contributed to just under half of these conflict cases. Nine factors that enable greater cooperation and transformation of conflict are identified. Participatory dialogue and negotiation processes, while not sufficient, changed understanding, attitudes and positions of actors. Many of the communities innovated physical measures to overcome natural resource constraints, underlying conflict, and/or institutional reforms. These changes were informed by improving understanding of resource limitations and indigenous knowledge. Learning networks among community organizations encouraged collective action by sharing successes and creating peer pressure. Incentives for cooperation were important. For example, when community organizations formally permitted excluded traditional resource users to access resources, those actors complied with rules and paid towards management costs. However, elites were able to use policy gaps to capture resources with changed characteristics due to climate change. In most of the cases where conflict persisted, power, policy and institutional barriers prevented community-based organizations from taking up potential adaptations and innovations. Policy frameworks recognizing collective action and supporting flexible innovation in governance and adaptation would enable wider transformation of natural resource conflicts into cooperation.

Key policy insights

• Climate stresses, policy gaps and interventions can all worsen local natural resource conflicts.

• Sectoral knowledge and technical approaches to adaptation are open to elite capture and can foster conflicts.

• Many local natural resource conflicts can be resolved but this requires an enabling environment for participatory dialogue, external facilitation, flexible responses to context, and recognition of disadvantaged stakeholder interests.

• Transforming conflict to greater cooperation mostly involves social and institutional changes, so adaptation policies should focus less on physical works and more on enabling factors such as negotiation, local institutions, knowledge, and incentives.