Status: this discussion paper is a preprint. It has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). The manuscript was not accepted for further review after discussion.
Does the AO index have predictive power regarding extreme cold temperatures in Europe?
Tamás Bódai1,2and Torben Schmith3Tamás Bódai and Torben SchmithTamás Bódai1,2and Torben Schmith3
Abstract. With a view to seasonal forecasting of extreme value statistics, we apply the method of Nonstationary extreme value statistics to determine the predictive power of large scale quantities. Regarding winter cold extremes over Europe, we find that the monthly mean daily minimum local temperature – which we call a native co-variate in the present context – has a much larger predictive power than the nonlocal monthly mean Arctic Oscillation index. Our results also prompt that the exploitation of both co-variates is not possible from 70 years-long data sets.
How to cite. Bódai, T. and Schmith, T.: Does the AO index have predictive power regarding extreme cold temperatures in Europe?, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2020-117, 2020.
A lot of people work outdoors year-round and their work safety is of basic concern. For example, in shipping route planning, it is very important to be able to know well in advance how long time crew can stay on deck to carry out their task, which depends on the temperature. We examine one element of a forecast system with respect to the choice of the quantity that it relies on. The forecast of cold extremes can be much more precise when relying on a local quantity rather than a nonlocal one.
A lot of people work outdoors year-round and their work safety is of basic concern. For example,...