We developed objective performance metrics that measure precipitation variability amplitude across timescales from sub-daily to interannual and found many CMIP 5 and 6 models overestimate the forced variability amplitude (e.g., diurnal cycle and annual cycle) while they underestimate the internal variability amplitude, especially for higher frequency variability. The internal variability is overall improved in CMIP6 from CMIP5 but remains underestimated, and there is little evidence of improvement in forced variability.
Biases in simulated precipitation variability have been objectively quantified on a wide range of time scales, including sub-daily internal variability, the diurnal cycle, synoptic variability, sub-seasonal variability, the seasonal cycle, and interannual variability. The current study proposes a framework to assess large-scale forced and internal variability of simulated precipitation across time scales. This framework provides high-level summary statistics that would be useful for routine evaluation of simulated precipitation in Earth system models.
In this study, we describe the development and application of a framework to assess large-scale forced and internal variability of simulated precipitation across time scales in CMIP 5 and 6 models. Many models tend to overestimate the forced variability over the tropics and underestimate the internal variability more broadly and across time scales. The underestimation of internal variability is overall improved in many CMIP6 models when compared to their CMIP5 counterparts, but there is little or no improvement in forced variability.