Contribution of mean climate to hot temperature extremes for present and future climates
Contribution of mean climate to hot temperature extremes for present and future climates
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DOI：
10.1016/j.wace.2020.100255
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发表时间：
2020-06-01
影响因子：
8
通讯作者：
Argueso, Daniel
中科院分区：
文献类型：
--
作者：
Di Luca, Alejandro;de Elia, Ramon;Argueso, Daniel
极端高温的发生往往与对人类健康、自然生态系统和经济(如能源、供水和农业)的负面影响有关。研究总是表明，未来极端高温的强度和频率将会增加，从而增加与之相关的风险。虽然在量化和理解极端高温及其未来变化方面已经取得了很大进展，但仍然存在一些悬而未决的问题。本文采用一种简单而明确的方法，将日热极值描述为四个众所周知的物理术语的叠加，包括年平均温度、年周期幅度、日较差和极值当天的局地温度异常的信息，重点讨论了热极值的来源及其变化。该方法被应用于来自6个基于观测的数据集和来自耦合模式相互比较项目第五阶段(CMIP5)的31个大气-海洋全球气候模式的30年每日温度记录。观测到的和模拟的热极端之间的比较显示了一幅非常一致的图景，其中大多数CMIP5模式高估了描述全球大多数地区局部温度极端异常的项，而不考虑所考虑的观测数据集。同时，CMIP5模式在年平均气温和日较差方面显示出系统性的冷偏差，导致在一些地区进行了实质性的误差补偿。这促使我们将新的误差估计器定义为单个项的误差总和，与传统的偏差估计器相比，它在表征模型性能方面似乎要有效得多。对未来极端高温变化的评估表明，变化主要是由年平均气温的变化主导的，其他项的贡献也不同，这与所考虑的特定区域密切相关。西欧似乎是极端温度变化的热点(到本世纪末上升(类似)8摄氏度)，这是由于包括夏季平均异常、昼夜温度范围和每日极端异常在内的所有分解项的显著贡献。热带南美洲也似乎是极端温度变化的热点(上升(类似)7摄氏度)，这主要是由于每日极端异常项的增加(约占总变化的30%)，使该地区成为世界上最敏感的极端温度地区之一。分析表明，根据描述均值、变异性和尾部的术语对未来变化的分离对均值分量的具体定义方式非常敏感，包括关于平稳性的假设。
The occurrence of very high temperatures (hot extremes) is often linked with negative impacts in human health, natural ecosystems and the economy (e.g., energy, water supply and agriculture). Studies have invariably shown that the intensity and frequency of hot extremes will increase in the future thus increasing their associated risks. While much progress has been made in quantifying and understanding hot temperature extremes and their future changes, there are still open questions. This paper focusses on the sources of hot extremes and their changes by applying a simple and unambiguous methodology that describes daily hot extremes as the superposition of four well known physical terms that include information on the annual mean temperature, the amplitude of the annual cycle, the diurnal temperature range and the local temperature anomaly on the day of the extreme. The methodology was applied to 30-year daily temperature records from 6 observation-based datasets and 31 atmosphere-ocean global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The comparison between observed and simulated hot extremes shows a remarkably consistent picture where most CMIP5 models overestimate the term describing the local temperature extreme anomaly over most regions of the globe regardless of the observed dataset considered. Simultaneously, CMIP5 models show a systematic cold bias in the annual mean temperature and in the diurnal temperature range terms leading to substantial error compensation over some regions. This prompted us to define a new error estimator as the sum of errors in individual terms that appears to be much more effective at characterising model's performance compared to the traditional bias estimator. The assessment of future changes in hot extremes shows that changes are dominated by changes in annual mean temperatures with varying contributions from the other terms that strongly depend on the specific region being considered. Western Europe appears as a hot spot for extreme temperature changes (increases of (similar to)8 degrees C by the end of the century) due to significant contributions from all decomposition terms including the summer mean anomaly, the diurnal temperature range and the daily extreme anomaly. Tropical South America also appears as a hot spot for extreme temperature changes (increases of (similar to)7 degrees C) largely due to an increase in the daily extreme anomaly term (explaining about 30% of the full change) making this region one of the most sensitive regions in the world in terms of hot extremes. The analysis reveals that the separation of future changes according to terms describing mean, variability and tails is very sensitive to the specific way the mean component is defined including assumptions about stationarity.