%0 conference lecture
%@ 
%A Georgievski, G., Hagemann, S., Sein, D., Drozdov, D., Gravis, A., Romanovsky, V., Nicolsky, D., Onaca, A., Ardelean, F., Chetan, M., Dornik, A.

%D 2020
%J EGU General Assembly 2020

 
%R doi:10.5194/egusphere-egu2020-16115
%T Climate extremes relevant for permafrost degradation
%U https://doi.org/10.5194/egusphere-egu2020-16115
 
%X Several key types of events have been classified based on various combinations of temperature, precipitation and snow depth statistics. Then, the respective events have been identified in ERA-Interim reanalysis and evaluated against in situ observations in West Siberia region. The evaluation proved that the developed algorithm could successfully detect relevant extreme climate conditions in meteorological re-analysis dataset. It also indicated possibilities to improve the algorithm by refining definitions of extreme events. Refinement of algorithm is currently work in progress as well as the evaluation against satellite observations and a hierarchy of numerical models. Nevertheless, the method is applicable for all kinds of gridded climatological datasets that contain air temperature, precipitation and snow depth.