Representation of atmospheric blocking in the new global non-hydrostatic weather prediction model ICON

The correct depiction of atmospheric blocking still poses a key challenge for current numerical weather prediction (NWP) and climate models. This study evaluates the representation of blocking in the new global ICOsahedral Non-hydrostatic NWP and climate model ICON and links model mean state biases to observed blocking deviations. Blocking is identif ed using both an anomaly and a f ow reversal approach in an eight member ensemble of 15-year AMIP-type ICON simulations and verifie against ERA Interim reanalyses. Either approach demonstrates a good representation of annual blocking frequencies in ICON. Deviations emerge when considering individual seasons. In the anomaly framework, enhanced blocking occurrence in the mid-latitude Pacif c domain during winter and spring and a marked underestimation of blocking in the Euro-Atlantic region are found during summer. Moreover, this approach indicates a general underestimation of blocking at higher latitudes. The f ow reversal index reveals the often reported underestimation of blocking in the Euro-Atlantic region during winter. Furthermore, increased blocking activity in the Pacifi and Greenland region during spring and decreased blocking occurrence at high latitudes in summer are found. Focusing on the anomaly approach, we assess how the model mean state inf uences blocking identif cation. A systematically higher tropopause, forced by a cold bias in the lower stratosphere, reduces diagnosed blocking frequencies at higher latitudes especially during summer. This goes along with a reduction in blocking size, duration, and intensity. While conf rming an overall good representation of blocking in ICON, this study demonstrates how mean state biases can crucially affect the identificati n of blocking and that blocking deviations have to be interpreted with caution as they are highly dependent on the exact diagnostic used.