Assessing damage from extreme winter events in remote sensing datasets
The Arctic is warming rapidly, especially in winter. Disruptive winter events such as rain-on-snow and frost droughts have become more common, particularly in the Nordic Arctic region. These extreme events can lead to extensive vegetation damage, which in turn is detectable with satellites. However, few of these events have been adequately analyzed or even identified.
In this project, the aim is to characterize extreme winter events in historical weather data and identify, with the help of remote sensing, whether these events led to extensive vegetation damage. The student may focus on known extreme winters, such as in Norway in 2014 and 2018, but he or she is also encouraged to identify other extreme events that occurred elsewhere in the Arctic and subarctic, but which may have been underreported or not yet detected.
For this MSc project, we seek a highly motivated student with strong analytical skills. Previous experience handling large datasets and programming in languages such as Python, R or Matlab is recommended. For more information, please do not hesitate to ask.