Abstract ID: 228
Impacts of increased horizontal resolution on the seasonal predictability of Tropical Pacific variability
Lead Author: Aude Carreric
Keywords: ENSO, Seasonal forecast, High resolution, Tropical Pacific, Teleconnections
Abstract: Seasonal to Decadal climate prediction (S2D) skill can arise from two major sources. The first is related to the representation of the externally forced signals (such as from volcanic eruptions, solar activity or anthropogenic greenhouse gases), which have caused important climate trends in recent decades. And the second is the internal low-frequency variability, usually associated with oceanic processes operating from monthly to multi-decadal timescales. The premise of multi-year prediction is that such internal variability processes, when adequately modelled and initialised, can be used to improve our predictive capacity not only on the oceans but also over the surrounding land areas, such as in the North Atlantic region.
However, one major limitation common to current S2D prediction systems is the little skill that they present over the continents, which appears to be connected with an incorrect representation of the teleconnection mechanisms that, mediated via the atmosphere, connect the ocean with the neighbouring continents. There are several indications that the current generation of global climate models at standard resolutions (typically with ~100 km grid spacings) misrepresents those key teleconnections, and that higher resolution versions able to partially resolve the contributions of mesoscale ocean eddies can improve their realism, leading to reduced mean-state biases and improved skill to predict certain regions at seasonal scales, e.g. in Tropical sea surface temperature.
In this study, we explore how the forecast skill of two different seasonal prediction systems based on the climate models EC-Earth3 and CNRM-CM6.1, can be improved by increasing the spatial resolution of the model from ~100 to ~40 km in the atmosphere and ~100 to ~25 km in the ocean. We focus in particular on the Tropical Pacific region where prominent improvements are found in both systems related to improved predictive skill for ENSO and its associated climate teleconnections. A comparison of the results from both prediction systems allows us to assess how the development of model-specific biases impacts the regional predictive skill.
Pablo Ortega (BSC-CNS)
Francisco Doblas-Reyes (BSC-CNS)
Lauriane Batte (CNRM-Meteo France)
Damien Specq (CNRM-Meteo France)