Visit to NCAR for Statistical-based Compression of Climate Model Output

这笔旅行赠款旨在纽卡斯尔大学数学与统计学院新任命的讲师首席研究员与位于美国博尔德的国家大气研究中心(NCAR)(美国和世界上最顶尖的气候研究中心之一)在使用统计模型压缩气候数据的项目上建立合作。专门针对气候输出的压缩算法的开发对科学界来说是新的，目前，NCAR是唯一从事这一创新研究领域的机构。开发基于统计的压缩算法以及评估压缩质量的方法，将使气候科学家能够产生更多的数据，改善他们对地球系统的科学了解，并提供更可靠的未来气候预测。PI已经开发了一种基于统计的气候集合压缩算法，该算法已经发表在一本顶级统计期刊上，并打算将该方法扩展到多个变量，这是NCAR科学家高度感兴趣的研究。作为这一合作的一部分，纽卡斯尔大学EPSRC大数据云计算博士培训中心的联合博士提案将被概念化并起草。此次访问定于2015年6月至8月，将有助于启动与国际和平研究所和纽卡斯尔大学在气候建模方面的世界领先机构的国际合作，这将导致在顶级统计和地球科学研究期刊上发表高调文章。

This travel grant aims at establishing a collaboration between the Principal Investigator, a newly appointed Lecturer in the School of Mathematics & Statistics at Newcastle University, and the National Center for Atmospheric Research (NCAR) in Boulder, USA (one of the top research centers in climate in the United States and in the world) on a project in climate data compression using statistical models. The development of compression algorithms specifically aimed at climate output is new to the scientific community, and NCAR is, at present, the only institution pursuing this innovative research area. The development of statistically-based compression algorithms, as well as methodologies to assess the quality of the compression, will allow climate scientists to generate a larger quantity of data, to improve their scientific understanding of the Earth's system and to deliver more reliable future climate projections. The PI has developed a statistical based compression algorithm for climate ensemble that has already been published in a top statistical journal, and intends to extend the methodology to multiple variables, an investigation of high interest to NCAR scientists. As part of this collaboration, a joint PhD proposal for the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data at Newcastle University will be conceptualized and drafted. The visit, which will be scheduled between June and August 2015, will contribute to initiate an international collaboration with a world leading institution in climate modelling with the PI and Newcastle University that will lead to high profile publications in top Statistics and Geosciences research journals.