Seasonal Extremes and Rates of Change in Past Warm Climates: Insights from Advanced Statistical Estimations on High-Resolution Coral Proxy Records (SEARCH)

自2013年IPCC发布第五次评估报告以来，越来越多的证据表明，全球变暖对社会和生态的影响实际上更依赖于季节性极端事件(例如夏季峰值温度)，而不是年平均趋势。对于热带地区来说尤其如此，那里的极端气候已经成为生态系统的最大威胁。然而，目前或未来，人们对平均值和极端值的变化率知之甚少。缺乏过去温暖气候的高分辨率数据(作为类比)，以及缺乏先进的数据分析方法，可以解释这种知识赤字。为了克服这一点，我们建议(1)利用高分辨率珊瑚代理记录的数据库，(2)应用统计科学的先进模拟技术。我们寻求以下问题的量化答案。(A)海表面温度(SST)的变化率是多少？(B)季节性海温周期的幅度是多少？(C)季节性海温极端事件发生的变化率是多少？这导致了对关于长期气候变暖与季节性极端事件发生之间的关系的最终问题(D)的更好的评估。Search从(A)人类世、(B)中世纪气候异常-中世纪暖期、(C)全新世最高温度、(D)末次间冰期和(E)中上新世暖期的现有和新的(双月)解析记录建立了一个数据库。搜索得到了来自SPP 2299内八个合作伙伴的新数据和建模专业知识的支持。搜索将影响学术气候研究、气候建模、应用气候风险评估--以及五名学生未来的科学生涯。

Since the release of the Fifth Assessment Report by the IPCC in 2013, evidence is mounting that the impacts of global warming on society and ecology actually depend stronger on seasonal extremes (e.g., summer peak temperature) than on trends in annual mean. This is true especially for tropical regions, where extremes have become the greatest threat to ecosystems. However, little is known about the rates of change in mean and extremes, currently or in future. Lack of high-resolution data from past warm climates (which serve as analogues) and lack of advanced data-analytical methods explain this knowledge deficit. To overcome it, we propose here to (1) utilize a database from high-resolution coral proxy records and (2) apply advanced simulation techniques from statistical science. We seek quantitative answers to the following questions. (A) What is the rate of change in sea surface temperature (SST)? (B) What is the amplitude of the seasonal SST cycle? (C) What is the rate of change in occurrence of seasonal SST extremes? This leads to a better assessment of the ultimate question (D) about the relation between long-term climate warming and the occurrence of seasonal extremes. SEARCH builds a database from existing and new (bi-)monthly resolved records during the (a) Anthropocene, (b) Medieval Climate Anomaly-Medieval Warm Period, (c) Holocene Thermal Maximum, (d) Last Interglacial and (e) Mid-Pliocene Warm Period. SEARCH is supported by new data and modeling expertise from eight cooperation partners within SPP 2299. SEARCH will impact academic climate research, climate modeling, applied climate risk assessments – and the future scientific careers of five students.