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非常容易受到大气风暴的直接风雨影响，而且也非常容易受到风暴潮等相关海洋反应的影响。此外，该地区的大都市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小时内迅速福尔斯的风暴）、东北风暴和过渡为热带风暴的热带风暴。特大风暴降水，部分由邻近海洋提供，可能导致内陆洪水，这可能与高海平面异常联合收割机结合，产生毁灭性的沿海洪水，最近的热带风暴艾琳和超级风暴桑迪就是明证。分辨率约为一度的典型气候模型过于粗糙，无法很好地捕捉热浪或强风暴和飓风产生的高降水和破坏性近地表风。该项目的总体目标是预测区域和十年尺度上极端天气事件对经济和其他人类系统的影响，同时考虑一些自然气候变异和人为影响。一个多尺度气候模型成功地纳入了一公里陆面模型，该模型将扩大到包括一个能够代表气旋和大气阻塞的多尺度大气模型，一个能够产生风暴潮的沿海海洋模型。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气候变化？该项目还为两名研究生提供了机会，在气候和人类系统科学家的高度跨学科团队中进行培训，并在两个领先的机构之间为未来的挑战做准备。这一项目的预期成果是一个可在世界许多地区使用的示范框架、下一代科学家的培训、脆弱地区科学家与当地决策者之间的交流以及对广大民众的宣传。该项目旨在预测气候变化、气候变异性和新泽西及其周边地区不断变化的城市化沿海环境对人类和经济的影响。它建立在一个多尺度气候模型的基础上，该模型成功地将一个1公里的陆面模型纳入了社区地球系统模型的框架，将天气事件的尺度缩小到社会经济模型的尺度。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。主导假设是，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，该项目将利用现有的分辨率更高的大气和区域海洋模型来推进缩小尺度的工作，这些模型已被证明有能力根据气候状况产生这种事件，包括相关的海平面上升。因此，该项目将以更高的置信度模拟气候/社会经济耦合系统对这些事件作出反应的共同演变，并对社会经济反应作出十年期预测。将不使用完全耦合的气候和社会经济模型进行集合模拟，而是对未来状态（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，以制定社会经济模型的不确定性措施。时间片的方法可以被看作是一个概念的建模框架，然后可以在未来的工作中使用，以研究系统的全面发展的基础上，一个给定的场景证明。

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.