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

像新泽西州及其周边地区这样的沿海地区不仅非常容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)、东北风和转变为热带外风暴的热带风暴。部分由邻近海洋提供的非常强的风暴降水可能会导致内陆洪水，这可能与高海平面异常结合在一起，产生毁灭性的沿海洪水，最近热带风暴艾琳和超级风暴桑迪都证明了这一点。分辨率在1度左右的典型气候模型太粗糙，无法很好地捕捉到热浪或由严重风暴和飓风产生的高降水和破坏性近地表风。该项目的首要目标是预测区域和十年尺度的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化、人为影响。一个成功地纳入一公里陆面模式的多尺度气候模式将被扩展，以包括一个能够代表气旋和大气阻塞的多尺度大气模式，一个可以产生风暴潮的沿海海洋模式。目标区域的环境和气候成果将与目前和未来气候条件的现有区域经济模型和现行经济评估方法相结合。该项目将地方(市和县)决策者与学术氛围和社会经济科学家聚集在一起，以应对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气候和人类系统科学家高度跨学科的团队中进行培训的机会，并在两个领先机构之间为未来的挑战做准备。这一项目的预期遗产是一个可在世界许多地区使用的模式框架、培训下一代科学家、科学家与脆弱地区的地方决策者之间的交流以及与普通民众的接触。该项目旨在预测新泽西州及其周边地区气候变化、气候多变性和城市化沿海环境变化对人类和经济的某些影响。它建立在一个多尺度气候模型的基础上，该模型成功地将1公里陆面模型纳入共同体地球系统模型的框架内，以将天气事件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。驱动假设是，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，该项目将通过采用现有的更高分辨率的大气和区域海洋模式来推进缩小尺度，这些模式已证明有能力根据气候状态产生这种事件，包括海平面的相关波动。因此，该项目将更有信心地模拟气候/社会经济耦合系统对这些事件的共同演变，并将对社会经济反应进行十年预测。而不是使用完全耦合的气候和社会经济模型进行整体模拟，而是对未来国家(2050年)进行时间切片计算。将在气候模型和社会模型之间进行非同步耦合，以制定社会经济模型的不确定性措施。时间切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，以研究基于给定场景的系统的完整演化。

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.