HDR Institute: HARP- Harnessing Data and Model Revolution in the Polar Regions

气候变化引起的极地冰盖损失影响到许多生命，并通过海平面上升和影响海洋环流增加沿海洪灾。然而，准确预测冰盖将以多快的速度继续萎缩仍然很困难。特别是，我们仍然受到对决定冰盖变化的跨学科过程的有限理解的挑战，例如冰下地形和冰-大气-海洋相互作用的作用。及时投资于机器学习和数据密集型研究可以彻底改变科学家目前回答冰动力学相关问题的方式。HDR研究所作为一个研究中心，汇集了来自学术界、政府和私营部门的数据科学、北极和南极科学以及网络基础设施方面的专家，共同开发变革性和综合性的数据科学解决方案，以减少预测未来海平面上升和气候变化的不确定性。i-HARP研究人员研究了新型物理感知数据科学和机器学习方法的潜力，以解决在新北极导航、气候变化和海平面上升方面的国家优先事项和挑战。HDR研究所旨在利用空间和时间上的大量异构、噪声和不连续数据，并将数据与数值和物理模型相结合。i-HARP的研究人员正在研究新的数据科学技术，包括深度生成对抗网络、图神经网络、元学习、混合网络、物理信息机器学习、因果人工智能、数据同化、时空深度学习和可扩展算法。由于i-HARP解决的数据科学问题的基本性质，解决方案可以转化为其他学科，如遥感、医学和自动驾驶。此外，融合团队支持多个研究整合教育计划集群，特别注重促进跨学科合作，培训下一代多学科研究人员，并让公众参与与气候变化和数据科学相关的科学探究。在与相关社区的合作伙伴关系中，i-HARP设计课程，并提供动手社区讲习班，讲座系列，会议教程和培训。i-HARP通过利用几个现有的少数群体组织来吸引来自少数群体的学生。该项目是美国国家科学基金会“利用数据革命”（HDR）大创意活动的一部分。该奖项由先进网络基础设施办公室颁发，由美国国家科学基金会极地项目办公室的南极科学部和北极科学部联合支持。该奖项反映了美国国家科学基金会的法定使命，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。

Climate-change induced loss of polar ice sheets impacts many lives and increases coastal flooding by rising sea level and affecting ocean circulation. However, it remains difficult to accurately predict how quickly the ice sheets will continue to shrink. In particular, we are still challenged by a limited understanding of transdisciplinary processes that determine ice sheet change, such as the role of subglacial topography and ice-atmosphere-ocean interactions. Timely investment in machine learning and data intensive research can revolutionize the way that scientists currently answer questions related to ice dynamics. This HDR Institute serves as a research hub where experts in data science, Arctic and Antarctic science, and cyberinfrastructure in academia, government, and private sectors come together to develop transformative and integrative data science solutions to reduce uncertainties in projecting future sea-level rise and climate change. i-HARP researchers investigate the potential of novel physics-aware data science and machine learning approaches to address national priorities and challenges on Navigating the New Arctic, climate change, and sea-level rise.The HDR Institute aims to harness massive heterogeneous, noisy, and discontinuous data in space and time and integrate data with numerical and physical models. Researchers at i-HARP are investigating novel data science techniques including deep generative adversarial networks, graph neural networks, meta learning, hybrid networks, physics-informed machine learning, causal artificial intelligence, data assimilation, spatiotemporal deep learning, and scalable algorithms. Due to the fundamental nature of data science problems that i-HARP addresses, the solutions can be translated to other disciplines such as remote sensing, medicine, and autonomous driving. Moreover, the convergence team champions multiple clusters of research-integrated educational initiatives, with a specific focus on facilitating cross-disciplinary collaborations, training next-generation multi-disciplinary researchers and engaging the public in scientific inquiry as related to climate change and data science. In partnership with related communities, i-HARP designs curricula, and offers hands-on community workshops, lecture series, conference tutorials, and training. i-HARP engages students from underrepresented minority groups by leveraging several existing organizations for underrepresented minorities.This project is part of the National Science Foundation's Big Idea activities in Harnessing the Data Revolution (HDR). This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Section for Antarctic Sciences and the Section for Arctic Sciences within the NSF Office of Polar Programs.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.