Interdisciplinary Workshop on 'Arctic Climate And Weather Extremes: Detection, Attribution, And Future Projection'

Aspen Global Change Institute(AGCI)将在2020年春季举办一个为期一周的跨学科科学研讨会，题为“北极气候和极端天气：探测、归因和未来预测”。与会者的任务是：a)改进对极端事件涉及的每个气候系统组成部分的基本过程的洞察；b)综合结果以提高对气候系统组成部分反馈过程的理解；c)确定现有的关键问题和知识差距；d)提出改进我们预测和模拟北极极端事件的能力的前进方向。为实现这些目标，PIS将采用AGCI建立的研讨会模式，召集来自大气、海洋和海冰社区的30名数据分析师、动态学家和模型师。参与者将包括早期职业科学家，以及来自不同和代表性不足背景的个人。北极气候系统变化的轨迹表现出高度的非线性行为，表现为极端事件发生的频率增加，叠加向平均状态变暖的长期趋势。最近最引人注目的极端事件包括2007年、2012年和2016年夏季出现创纪录的海冰面积最小值，以及2015/2016和2017/2018年冬季出现创纪录的地表气温最高值。然而，北极气候变化的研究主要集中在使用月、季或年平均数据的长期变化或趋势上。但极端事件通常会间歇性地发生，时间从几天到几个月不等，是长期趋势的异常值。即使对于发生在较长时间段的极端事件，月度或季节平均数据也可能无法解决支持其快速发展的潜在物理因素。因此，目前仍不清楚这些极端事件为什么会发生，它们的多尺度驱动机制是什么，以及它们的可预测性的来源在哪里。本次研讨会旨在解决这些关键的知识差距。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Aspen Global Change Institute (AGCI) will host a week-long interdisciplinary scientific workshop in Spring 2020 entitled "Arctic Climate and Weather Extremes: Detection, Attribution, and Future Projection". Participants will be tasked with the scientific objectives of a) providing improved insight into the fundamental processes of each climate system component involved in extreme events, b) synthesizing results to improve understanding of feedback processes across the climate system components, c) identifying existing key questions and knowledge gaps, and d) suggesting a way forward to improve our ability to predict and model extremes in the Arctic. To achieve these objectives, The PIs will employ AGCI's established workshop model to convene thirty data analysts, dynamicists, and modelers from the atmosphere, ocean, and sea ice communities. Participants will include early career scientists, and individuals from diverse and underrepresented backgrounds. The trajectory of Arctic climate system change has exhibited highly nonlinear behavior, as manifested by the increased frequency of occurrence of extreme events superimposed on a long-term trend towards a warmer mean state. The most recent, striking extreme events include occurrences of record minima of sea ice extent in the summers of 2007, 2012, and 2016, and record maxima of surface air temperatures in the winters of 2015/2016 and 2017/2018. However, Arctic climate change studies have predominantly focused on the long-term changes or trends using monthly, seasonal, or annual mean data. But extreme events generally occur intermittently for periods from days to several months as outliers of the long-term trends. Even for the extreme events that occur across longer time periods, monthly or seasonal mean data may not be able to resolve the underlying physics supporting their rapid development. It therefore still remains unclear why these extreme events occur, what their multi-scale driving mechanisms are, and where the source of their predictability exists. This workshop seeks to address these critical knowledge gaps.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.