Monitoring Antarctic Ice Sheet Melting from Space

格陵兰岛和南极冰盖的融化造成了全球海平面上升的约三分之一。虽然格陵兰冰盖的表面融化是有据可查的，但对南极洲过去和现在的表面融化知之甚少，特别是每年在冰表面形成的湖泊和河流的瞬时网络。这些难以捉摸的特征对于理解冰盖的演变非常重要，并且与最近几个外围冰架的解体有关。该博士学位将对南极融化的时空演变以及由此产生的地表水文网络形成新的认识。使用传统方法和新的数据科学技术，将探讨几个关键问题，（1）南极洲的表面融水会发生什么-它会在哪里重新冻结，它会流入冰盖，还是直接流入海洋，（2）有多少水储存在地表湖泊中，以及多长时间，以及（3）水文系统将如何在未来气候情景下演变？为了回答这些问题，您将利用卫星数据的快速，最近的扩展，使用光学和合成孔径雷达卫星图像系统地绘制南极洲融化特征的分布。除了传统方法外，还将有机会探索最先进的机器学习，贝叶斯优化和信号处理技术，以提供对地表水文系统的新见解。然后，您将使用先进的时间序列分析技术，如极值理论和变点检测，以探索跨空间和时间的趋势和变化。最后，您将利用区域气候模型对未来融化的估计，结合高分辨率卫星地形数据，预测南极冰盖水文网络的未来演变。该项目由欧洲航天局（ESA）根据其4D南极合同提供部分资金，并由EPSRC CASE奖提供部分资金。因此，成功的学生将有机会与欧空局以及其他行业和空间机构合作伙伴密切合作，包括德国航空航天中心（DLR），环境地球观测IT GmbH（EnvEO），利兹大学和爱丁堡大学。此外，学生还将加入新的兰开斯特大学CEH环境数据科学卓越中心和英国NERC极地观测与建模中心（https：//cpom.org.uk/）。

Melting of the Greenland and Antarctic ice sheets contributes approximately one-third of global sea level rise. Whilst surface melting of the Greenland Ice Sheet is well documented, less is known about the past and present surface melting of Antarctica, and specifically, the transient network of lakes and rivers that form on the surface of the ice each year. These elusive features are important for understanding the evolution of the ice sheet, and have been implicated in the recent disintegration of several peripheral ice shelves.This PhD will develop new understanding of the spatial and temporal evolution of Antarctic melting, and the resulting surface hydrological network. Using both traditional methods and novel data science techniques, several key questions will be explored, (1) What happens to Antarctica's surface meltwater - where does it refreeze, does it drain into the ice sheet, or does it run off directly into the ocean, (2) How much water is stored in surface lakes, and for how long, and (3) How will the hydrological system evolve under future climate scenarios? To answer these questions, you will exploit the rapid, recent expansion in satellite data, to systematically map the distribution of melt features across Antarctica using both optical and Synthetic Aperture Radar satellite imagery. In addition to traditional methods, there will be opportunities to explore state-of-the-art Machine Learning, Bayesian optimisation and signal processing techniques to deliver new insight into the surface hydrological system. You will then use advanced time series analysis techniques, such as extreme value theory and changepoint detection, to explore trends and variability in melt across space and time. Finally, you will utilise regional climate model estimates of future melting, together with high resolution satellite topography data, to predict the future evolution of the Antarctic ice sheet hydrological network.The project is part-funded by the European Space Agency (ESA), under their 4DAntarctica contract, and part-funded by an EPSRC CASE award. The successful student will therefore have the opportunity to work closely with ESA, and with other industry and space agency partners including the German Aerospace Center (DLR), Environmental Earth Observation IT GmbH (EnvEO), the University of Leeds and the University of Edinburgh. Additionally, the student will also join the new Lancaster University-CEH Centre of Excellence in Environmental Data Science, and the UK NERC Centre for Polar Observation & Modelling (https://cpom.org.uk/).