Expires on: 04/30/2024
Northern areas are subject to accelerated warming due to global climate change, with Arctic areas experiencing temperature increases up to four times compared to equatorial regions. Warming temperatures have resulted in changes to the duration and distribution of seasonal snow cover through earlier spring melt but also changing precipitation patterns in winter. Satellite data records indicate that the trends of the total mass of seasonal snow may vary greatly on different regions of the Northern Hemisphere, and the overall impact on surface water availability from seasonal snow is highly uncertain.
We are looking for a talented and motivated candidate to advance the use of remotely sensed properties of seasonal snow, in particular of Snow Water Equivalent, in hydrological models and forecasts. The PhD project aims at understanding ongoing changes in snow mass over northern areas, and how these impact freshwater availability in the future. The main objective of the project is to investigate and improve the uptake of present and upcoming snow mass estimates from satellite remote sensing in hydrology, including operational runoff forecasts, focusing on the following research questions: 1) investigation of the validity and limitations of present approaches based on passive microwave remote sensing from a hydrology viewpoint, making use of in situ observations, snow process models and other reference data sources 2) coupling existing remote sensing snow products and conducting OSSE-type experiments on anticipated snow products from future satellite sensors with hydrological models at basin scale investigating potential benefits and limitations in operational hydrology forecasts; 3) assessing the impact of anticipated changes in seasonal snow on availability of freshwater and hydropower capacity in the future, focusing on selected research basins.
The PhD project may also encompass a selection of the above research questions, based on interests and the background of the applicant. The work is conducted in the context of the Digital Waters (DIWA) flagship program. Work is done in close collaboration with larger research teams at FMI and University of Oulu.