A Model Passes the Test for Tropical Cyclones
Manganello, J.V., Hodges, K.I., Kinter III, J.L., Cash, B.A., Marx, L., Jung, T., Achuthavarier, D., Adams, J.M., Altshuller, E.L., Huang, B., Jin, E.K., Stan, C., Towers, P. and Wedi, N. 2012. Tropical Cyclone Climatology in a 10-km Global Atmospheric GCM: Toward Weather-Resolving Climate Modeling. Journal of Climate 25: 3867-3892.
Early Atmospheric General Circulation Models (AGCMs) had horizontal resolutions that were the equivalent of approximately 450 km. In such a model, resolving individual storm events was impossible, and these could only be inferred from the aggregate statistical properties of quantities such as momentum or temperature flux.
Manganello et al. (2012) employ the European Centre for Medium-Range Weather Forecasts (ECMWF) IFS model to examine the climatology of TCs by identifying individual events. This model is the recent version of the ECMWF GCM, and it included the latest physical packages for cloud formation (i.e., prognostic equations for cloud water), land surface processes and hydrology, and improved convective adjustment schemes. The latter provides for a better representation of tropical weather and year-to-year variations in tropical climate.
The model was run for "Project Athena" (Jung et al. 2012) with resolutions at 125 km, 39 km, 16 km (the current resolution of a weather forecast model), and 10 km, and for all of these there were 91 levels in the vertical. The model was also run each year from 1960 to 2008 for the larger resolutions, but from 1989-2008 for the 10 km run. To keep the data storage manageable, the authors used data for May through November in the Northern Hemisphere (NH) from 1990-2008. The authors also controlled the data to make sure storms identified were indeed TCs, such as requiring that a TC be warm core, or that the center is warmer than the surrounding environment.
In doing so, Manganello et al. found that over the entire NH, the 39 km run produced the most realistic count for TCs, while the higher resolution model produced too many TCs. Within each basin (e.g., Atlantic) or sub-basin (Northwest Pacific), however, the higher resolutions occasionally produced the best results. One problem for models is tropical cyclogenesis tends to be too weak, and it was still an issue here in spite of better resolution. In a related issue, the model still produces TCs that are weaker than observed in terms of wind speed, but comparable in terms of central pressure (Fig 1). Finally, the higher model resolution runs did better in capturing ENSO variability of TCs. ENSO is well-known to have a large influence on the interannual variation of TC occurrence and intensity.
Figure 1. Adapted from Fig. 9, Manganello et al. (2012), life cycle composite of the (a) maximum 10-m wind speed and (b) minimum SLP for the 25 most intense typhoons, in terms of the maximum 10-m wind speed, over the northwest Pacific for observed data (black), the 10-km (purple), the 16-km (red), and 39-km (green) runs during MJJASON of 1990-2008. The time step is in 6-h increments.
As stated by Manganello et al. (2012), "as computing power continues to grow, it is becoming increasingly possible to model the global climate at horizontal resolutions presently used in short-term weather prediction." However, as shown by the authors, even hindcasts with improved resolution and physics were still having problems representing observations to a high degree. However, the models are able to reasonably reproduce the number of events, and even produced structures that look like observed TCs (Fig. 2), thus, passing the test. These kinds of advances represent progress and should make future computer scenarios for climate more reasonable and useful.
Jung, T., Miller, M.J., Palmer, T.N., Towers, P., Wedi, N., Achuthavarier, D., Adams, J.M., Altshuler, E.L., Cash, B.A., Kinter III, J.L., Marx, L., Stan, C. and Hodges, K.I. 2012. High-resolution global climate simulations with the ECMWF model in Project Athena: Experimental design, model climate, and seasonal forecast skill. Journal of Climate 25: 3155-3172.