How Do Model Biases Affect Large-Scale Teleconnections That Control Southwest US Precipitation?

Using hindcasts from subseasonal and seasonal forecast models, we examine large-scale atmospheric model biases that may affect the prediction of Southwest United States (SWUS) precipitation (between October and March). The focus is on the atmospheric mean state and large-scale teleconnections responsible for SWUS precipitation variability. In both subseasonal and seasonal hindcasts, we identify key model biases that degrade the models’ capability to predict SWUS precipitation. In particular, westerly biases in the subtropical jet cause a westward retraction of the waveguide in the midlatitude Eastern North Pacific, which divert wavetrains southward. These results are confirmed using linear, barotropic ray tracing analysis. At the subseasonal time scale, tropical convection anomalies associated with the Madden-Julian Oscillation (MJO) are too weak and incoherent at lead times greater than two weeks, when compared to reanalysis. At seasonal time scales, we find that the models are too dependent on tropical, El Niño-like, wave train anomalies for producing high seasonal SWUS precipitation, when in observations there is a larger influence of zonal Rossby wave trains in the North Pacific. This underestimation of the influence of zonal wave patterns is also found in the subseasonal hindcasts, suggesting this is a recurrent model bias. A case study of the 2016/17 winter illustrates the great challenge behind skillful seasonal prediction of SWUS precipitation. The almost record-breaking precipitation observed that year in the absence of ENSO is not predicted in the seasonal hindcasts, and model perturbation experiments suggest that even a perfect prediction of tropical sea surface temperature and tropical atmospheric variability would not have sufficed to produce a reasonable seasonal precipitation prediction.