Probabilistic Verification of spatially explicit monthly snow water equivalent forecasts in Switzerland

Timely knowledge on the availability of snow resources is important for recreation and economy in Switzerland. Forecasting snow water equivalent (SWE) with numerical models is advancing more and more into the focus of research.

Background

Timely knowledge on the availability of snow resources is important for recreation and economy in Switzerland. Forecasting snow water equivalent (SWE) with numerical models is advancing more and more into the focus of research. We consider monthly ensemble water resources forecast and corresponding simulation of spatially explicit SWE to assess their potential in giving guidance to potential users. The study is performed for the Alpine Rhine River Basin at 200 m resolution and for entire Switzerland at 600 m resolution. having its source in the Swiss Alps. The ECMWF VarEPS 5 members reforecast covering 18 years (weekly issued forecasts) is used as forcing for the hydrological model PREVAH. A thoroughly performed verification with respect to runoff and SWE has to be completed. Observed runoff is provided by the Swiss Federal Office for Environment, while a spatially explicit data set of SWE based on observations of snow depth and snow density is available through previous work in a research program funded by the Swiss National Research Foundation.

Tasks

Goal of this master thesis is the development of spatially explicit probabilistic verification environment for the obtained set of monthly forecast. It is expected that different verification metrics are implemented to obtain insight on model skill in different months, lead-time (from one day to one month) sub-areas and elevation bands. The Thesis should be written in the style of a scientific paper.

Literature

http://www.hydrol-earth-syst-sci-discuss.net/9/6857/2012/hessd-9-6857-2012.html

Profile of the candidate

The candidate has to be motivated in completing a successful Master Thesis. He/she should be able to work independently. He/she brings sound knowledge on climatology and catchment hydrology. Basic knowledge in Statistics (e.g. R) is welcome. Candidates with knowledge of a programming language (C, FORTRAN, Tcl, and IDL) or the motivation to learning a scripting language are particularly adequate.

The Research Group

http://www.wsl.ch/fe/gebirgshydrologie/HEX/index_EN

Contact

Massimiliano Zappa
Swiss Federal Institute for Forest, Snow and Landscape Research WLS
Zürcherstrasse 111, CH-8903 Birmensdorf
Phone +41 44 739 24 33

Email: zappa@wsl.ch