Melt probabilities and surface temperature trends on the Greenland ice sheet using a Gaussian mixture model
The Greenland ice sheet has experienced significant melt over the past six decades, with extreme melt events covering large areas of the ice sheet. Melt events are typically analysed using summary statistics, but the nature and characteristics of the events themselves are less frequently analysed. O...
| Main Authors: | , , |
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| Format: | Text |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/tc-2021-259 https://tc.copernicus.org/preprints/tc-2021-259/ |
| Summary: | The Greenland ice sheet has experienced significant melt over the past six decades, with extreme melt events covering large areas of the ice sheet. Melt events are typically analysed using summary statistics, but the nature and characteristics of the events themselves are less frequently analysed. Our work examines melt events from a statistical perspective by modelling 19 years of Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature data using a Gaussian mixture model. We use a mixture model with separate model components for ice and meltwater temperatures at 1139 locations spaced across the ice sheet. By considering the uncertainty of the ice surface temperature measurements, we use the two categories of model components to define a probability of melt for a given observation rather than using a fixed melt threshold. This probability can then be used to estimate the expected number of melt events at a given location. Furthermore, the model can be used to estimate temperature quantiles at a given location, and analyse temperature and melt trends over time by fitting the model to subsets of time. Fitting the model to data from 2001–2009 and 2010–2019 shows increases in melt probability for significant portions of the ice sheet, as well as the yearly expected maximum temperatures. |
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