| description abstract | A baroclinic model for the atmospheric jet at middle latitudes is used as a stochastic generator of nonstationary time series of the total energy of the system. A linear time trend is imposed on the parameter TE, descriptive of the forced equator-to-pole temperature gradient and responsible for setting the average baroclinicity in the model. The focus lies on establishing a theoretically sound framework for the detection and assessment of trend at extreme values of the generated time series. This problem is dealt with by fitting time-dependent generalized extreme value (GEV) models to sequences of yearly maxima of the total energy. A family of GEV models is used in which the location ? and scale parameters σ depend quadratically and linearly on time, respectively, while the shape parameter ? is kept constant. From this family, a GEV model is selected with Akaike?s information criterion, complemented by the likelihood ratio test and by assessment through standard graphical diagnostics. The inferred location and scale parameters are found to depend in a rather smooth way on time and, therefore, on TE. In particular, power-law dependences of ? and σ on TE are obtained, in analogy with the results of a previous work where the same baroclinic model was run with fixed values of TE spanning the same range as in this case. It is emphasized under which conditions the adopted approach is valid. | |
