Improved seasonal prediction of the hot summer of 2003 over Europe through better representation of uncertainty in the land surface

Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.

Sensitivity and variability redux in hot-Jupiter flow simulations

We revisit the issue of sensitivity to initial flow and intrinsic variability in hot-Jupiter atmospheric flow simulations, originally investigated by Cho et al. (2008) and Thrastarson & Cho (2010). The flow in the lower region (~1 to 20 MPa) `dragged' to immobility and uniform temperature on a very short timescale, as in Liu & Showman (2013), leads to effectively a complete cessation of variability as well as sensitivity in three-dimensional (3D) simulations with traditional primitive equations. Such momentum (Rayleigh) and thermal (Newtonian) drags are, however, ad hoc for 3D giant planet simulations. For 3D hot-Jupiter simulations, which typically already employ strong Newtonian drag in the upper region, sensitivity is not quenched if only the Newtonian drag is applied in the lower region, without the strong Rayleigh drag: in general, both sensitivity and variability persist if the two drags are not applied concurrently in the lower region. However, even when the drags are applied concurrently, vertically-propagating planetary waves give rise to significant variability in the ~0.05 to 0.5 MPa region, if the vertical resolution of the lower region is increased (e.g. here with 1000 layers for the entire domain). New observations on the effects of the physical setup and model convergence in ‘deep’ atmosphere simulations are also presented.

The 2014 hot, dry summer in Northeast Asia

Northeast Asia experienced a severe drought in summer 2014. Sea surface temperature forcing may have increased the risk of low precipitation, but model biases preclude reliable attribution to anthropogenic forcing.