Winters in Norway are under pressure from climate change, with an increasing frequency in extreme weather events such as rain-on-snow, false springs and frost droughts. Field surveys have shown that such extreme shifts in temperature and snow cover can be highly damaging for vegetation, but it remains unclear how widespread the damage from these events is across Norway, in particular for frost droughts.
Frost droughts occur when temperatures are below zero, but snow cover is absent. Combined with strong winds and sunshine, such extreme weather can severely damage evergreen shrubs and trees (e.g. heather and crowberry shrubs, and pine and spruce trees). Last winter, for example, a frost drought occurred along the west coast of Norway that was so severe that it led to a number of mid-winter wildfires. The drought also led to wider damage to vegetation all along the coast from Rogaland to Trøndelag.
In this MSc project, you will combine gridded climate datasets (i.e. SeNorge/Era5) and remote sensing imagery (i.e. MODIS) to identify the historical occurrence of frost droughts across Norway. By applying an indicator based on temperature and snow cover, you will identify areas where frost droughts may have occurred since the start of the century. The impact of these events will then be verified by quantifying the reduction in the Normalized Difference Vegetation Index (NDVI) in the following summer. The goal is to improve detection methods for frost droughts, that may be extended across the whole Arctic-boreal region.
For this MSc project, it is preferable if you are already familiar with Python, and having experience with remote sensing and other gridded data is helpful. This project is suitable regardless of how familiar you are with its ecological aspects.
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