Re-Imagining Computation and Storage Resources in Climate- and Weather-dedicated Cyberinfrastructures

气候模型的使用对于了解我们星球的未来以及气候变化对当地的影响至关重要。然而，这些模型相当昂贵，因为它们需要数周甚至数月的运行时间和大量的存储空间。该研究项目开发了新的软件，能够使用应用数学，统计学和机器学习的最新进展以及最先进的计算资源节省大量的计算时间和空间。该软件应用于风的行为，以更好地了解野火蔓延的风险。气候和天气模型是了解地球大气层未来状态的基本工具，这将影响我们星球所有尺度（城市到全球）的人类可居住性。基于模型的环境科学受到其不断增加的计算和存储成本的阻碍，即使是拥有最先进网络基础设施的研究机构也只能进行有限数量的模拟，从而导致不确定性量化不足和不准确。该提案的主要研究目标是提出关键的方法发展，以帮助先进的气候和天气专用网络基础设施中的计算（使用随机偏微分方程）和存储（使用深层水库计算）。该项目由美国国家科学基金会（National Science Foundation）的“国家发现云气候倡议”（National Discovery Cloud for Climate initiative）通过高级网络基础设施办公室（Office of Advanced Cyberinfrastructure）资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The use of climate models is extremely important to understand the future of our planet and the local impacts of a changing climate. These models are however considerably expensive, as they require weeks or even months to run and a large amount of storage space. This research project develops new software that is able to save a considerable amount of computational time and space using the latest advances in applied mathematics, statistics and machine learning as well as the most advanced computational resources available. The software is applied to wind behavior to better understand the risk of wildfire spread. Climate and weather models are fundamental tools to understand the future state of the Earth's atmosphere, which will affect the human habitability of our planet at all scales (urban to global). Model-based environmental science is hampered by its ever-increasing computational and storage cost, and even research institutions with the most advanced cyberinfrastructure are able to perform only a limited number of simulations, thus leading to an inadequate and inaccurate uncertainty quantification. The main research goal of this proposal is to propose key methodological developments in order to aid computation (with Stochastic Partial Differential Equations) and storage (with deep reservoir computing) in advanced climate- and weather-dedicated cyberinfrastructures. These methods will be then implemented on a cyberinfrastructure for modeling atmospheric flows in complex terrain.This project is funded by the National Science Foundation's National Discovery Cloud for Climate initiative through the Office of Advanced Cyberinfrastructure.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.