LAUSR

ABSTRACT The climate variability in global land precipitation is important for the global hydrological cycle. Based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) historical experiments and the Global Monsoons Model Intercomparison Project (GMMIP) Tier-1 experiments, the spatial-temporal characteristics of global and regional land precipitation long-term climate changes in CAS FGOALS-f3-L are evaluated in this study. By comparing these two kinds of experiments, the precipitation biases related to the SSTs are also discussed. The results show that the two experiments could capture the precipitation trend and amplitude to a certain degree compared with observations. The GMMIP simulations show a higher skill than the historical runs verified by correlation coefficients partly because the observed monthly mean SST was prescribed. For the Northern Hemisphere, GMMIP can reproduce the trend and variability in global precipitation, while historical simulations cannot reproduce the trend and variability. However, both experiments fail to simulate the amplitude of the southern hemisphere summer precipitation anomalies. Ensemble empirical mode decomposition (EEMD) was applied to compare the simulated precipitation on different time scales. The sea surface temperature anomaly (SSTA) bias, especially the La Niña-type SSTA, is the dominant source of the model bias for simulating interannual precipitation anomalies. The authors also emphasize that the response of precipitation anomalies to the ENSO effect varies regionally. This study highlights the importance of the multiannual variability in SSTAs in global and hemispheric precipitation simulations. The ways to improve the simulation of global precipitation for CAS FGOALS-f3-L are also discussed. Graphical abstract