Collaborative Research: EaSM-3: Regional decadal predictions of coupled climate-human systems

像新泽西这样的沿海地区及其周边地区不仅极易受到大气风暴的直接风雨影响，而且还容易受到风暴潮等相关海洋反应的影响。此外，该地区的大城市地区特别容易受到与大气阻塞有关的夏季热浪的影响。最极端的风暴类型包括飓风、大气“炸弹”（中心气压在24小时内迅速下降的风暴）、东北风和过渡到热带外风暴的热带风暴。非常强的风暴降水，部分是由邻近的海洋造成的，可能导致内陆洪水，再加上海平面异常，造成毁灭性的沿海淹没，最近的热带风暴艾琳和超级风暴桑迪都证明了这一点。典型的气候模型分辨率约为一度，但由于过于粗糙，无法很好地捕捉到热浪、强风暴和飓风造成的高降水和破坏性近地面风。该项目的总体目标是在区域和年代际尺度上预测极端天气事件对经济和其他人类系统的影响，同时考虑到一些自然气候变率、人为影响。成功纳入一公里陆地表面模式的多尺度气候模式，将扩展到能够表示气旋和大气阻塞的多尺度大气模式，以及能够产生风暴潮的沿海海洋模式。目标区域的环境和气候结果将与现有的区域经济模型和当前和未来气候条件的当前经济评估方法相结合。该项目将地方（市和县）决策者与学术气候和社会经济科学家聚集在一起，以解决社会面临的一些最紧迫的挑战：我们的社会和经济系统将如何应对不断变化的气候？该项目还为两名研究生提供了在一个高度跨学科的气候和人类系统科学家团队中进行培训的机会，并在两个领先的机构之间为未来的挑战做准备。这个项目的预期遗产是一个可以在世界许多地区使用的模型框架、下一代科学家的培训、科学家与脆弱地区的当地决策者之间的交流以及向一般人群的推广。该项目旨在预测气候变化、气候变率和新泽西州及其周边地区城市化沿海环境变化对人类和经济的影响。它建立在一个多尺度气候模式的基础上，该模式成功地将社区地球系统模式（CESM）框架内的1公里陆地表面模式纳入其中，将天气事件的尺度降至社会经济模式的尺度。后者包括电力需求、土地使用、决策以及宏观和微观经济活动的模型。驱动假说认为，主要的社会经济影响将是对热浪和风暴等极端事件的反应。因此，该项目将通过采用现有的高分辨率大气和区域海洋模型来推进缩小尺度，这些模型已证明有能力产生气候状态的函数，包括相关的海平面上升。因此，该项目将更有信心地模拟气候/社会经济系统对这些事件作出反应的共同演变，并将对社会经济反应作出十年预测。而不是用完全耦合的气候和社会经济模式进行集合模拟，将对未来状态（2050年）进行时间片计算。将进行气候和社会模型之间的异步耦合，以开发社会经济模型的不确定性措施。时间片方法可以被视为建模框架的概念证明，然后可以在未来的工作中使用它来研究基于给定场景的系统的完整演变。

Coastal regions like New Jersey and its environs are highly susceptible not only to the direct wind and rain effects of atmospheric storms, but also to related oceanic responses like storm surges. Moreover, the area's large metropolitan areas are particularly vulnerable to summer heat waves associated with atmospheric blocking. The most extreme storm types include hurricanes, atmospheric "bombs" (storms whose central pressure falls rapidly over a 24-hour period), nor'easters and tropical storms that transition to extra-tropical storms. Very heavy storm precipitation, fed in part by the neighboring ocean can lead to inland flooding, which can combine with high sea level anomalies to produce devastating coastal inundation, as evidenced recently by both Tropical Storm Irene and Superstorm Sandy. Typical climate models with a resolution of around one degree are too coarse to capture well heat waves or the high precipitation and destructive near-surface winds generated by severe storms and hurricanes. The overarching goal of this project is to predict economic and other human system impacts of extreme weather events at regional and decadal scales, while accounting for some natural climate variability, anthropogenic influences. A multi-scale climate model in which a one-kilometer land surface model was successfully incorporated will be extended to include a multi-scale atmosphere model capable of representing cyclones and atmospheric blocking, a coastal ocean model that can produce storm surge. The environmental and climate outcomes for the target region will be integrated with existing regional economic models and current economic valuation methodologies for present and future climate conditions. This project brings together local (municipal and county) decision makers with the academic climate and socio-economic scientists to tackle some of the most urgent challenges facing society: How will our social and economic systems respond to a changing climate? The project also offers the opportunity for two graduate students to train in a highly interdisciplinary team of climate and human systems scientist and between two leading institutions preparing for challenges of the future. The expected legacy of this project is a model framework that can be used in many regions of the world, the training of next generation scientists, communication between scientists and local decision makers in vulnerable areas and outreach to the general population. This project aims to predict some aspects of the human and economic impacts of climate change, climate variability and changing urbanized coastal environments of New Jersey and environs. It builds on a multi-scale climate model that successfully incorporated a 1 km land surface model within the framework of the Community Earth System Model (CESM) to downscale weather events to the scales of socio-economic models. The latter include models for electricity demand, land-use, decision making and macro- and micro-economic activity. The driving hypothesis is that the dominant socio-economic impacts will be responses to extreme events such as heat waves and storms. Therefore, the project will advance the downscaling by employing existing higher resolution models of the atmosphere and a regional ocean with a demonstrated capability of producing such events as a function of climate state, including related surges in sea level. Thus, with a greater degree of confidence, the project will simulate the co-evolution of the coupled climate/socio-economic systems in response to these events and will make decadal predictions of the socio-economic responses. Rather than performing ensemble simulations with the full coupled climate and socio-economic models time-slice computations for future states (2050) will be performed. Asynchronous coupling between the climate and social models will be carried out to develop uncertainty measures for the socio-economic models. The time-slice approach can be regarded as a proof of concept for the modeling framework, which can then be used in future work to study the full evolution of the system based on a given scenario.