Climate model trend errors are evident in seasonal forecasts at short leads

Abstract

Abstract Climate models exhibit errors in their simulation of historical trends of variables including sea surface temperature, winds, and precipitation, with important implications for regional and global climate projections. Here, we show that the same trend errors are also present in a suite of initialised seasonal re-forecasts for the years 1993–2016. These re-forecasts are produced by operational models that are similar to Coupled Model Intercomparison Project (CMIP)-class models and share their historical external forcings (e.g. CO2/aerosols). The trend errors, which are often well-developed at very short lead times, represent a roughly linear change in the model mean biases over the 1993–2016 re-forecast record. The similarity of trend errors in both the re-forecasts and historical simulations suggests that climate model trend errors likewise result from evolving mean biases, responding to changing external radiative forcings, instead of being an erroneous long-term response to external forcing. Therefore, these trend errors may be investigated by examining their short-lead development in initialised seasonal forecasts/re-forecasts, which we suggest should also be made by all CMIP models.