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Abstract

Despite being important contributor to polar motion (PM) variation especially at seasonal time scales, hydrological angular momentum (HAM) is a main source of uncertainties in the estimation of PM excitation.With the growing scientific interest in climate change in recent years, works have intensified on the development of new climate models that simulate changes in the properties of the atmosphere, oceans and hydrosphere. One of the effects of these activities is latest implementation of the CMIP (Coupled Model Intercomparison Project) – CMIP6.In this study, we use various CMIP6 historical simulations to determine HAM series. We focus on the analysis of HAM calculated from clustered models determined on the basis of the mean of several models or on their combination with use of refined statistical algorithms. The obtained HAM series are analysed in different spectral bands and evaluated taking the hydrological signal in geodetically observed PM excitation as a reference. The results are also compared with those received for data from Gravity Recovery and Climate Experiment (GRACE) mission. Our research shows that despite the large differences between the HAM series obtained from single CMIP6 simulations, it is possible to choose the groups or combinations of models that allow for quite reliable determination of HAM, especially in seasonal spectral band. In terms of phase, the chosen models perform better than GRACE for annual prograde and semiannual retrograde term. In terms of amplitudes, the chosen models perform better than GRACE for annual prograde and annual retrograde term.