Tropical Cyclone Climatology in a 10-km Global Atmospheric GCM: Toward Weather-Resolving Climate Modeling

Abstract

Northern Hemisphere tropical cyclone (TC) activity is investigated in multiyear global climate simulations with the ECMWF Integrated Forecast System (IFS) at 10-km resolution forced by the observed records of sea surface temperature and sea ice. The results are compared to analogous simulations with the 16-, 39-, and 125-km versions of the model as well as observations. In the North Atlantic, mean TC frequency in the 10-km model is comparable to the observed frequency, whereas it is too low in the other versions. While spatial distributions of the genesis and track densities improve systematically with increasing resolution, the 10-km model displays qualitatively more realistic simulation of the track density in the western subtropical North Atlantic. In the North Pacific, the TC count tends to be too high in the west and too low in the east for all resolutions. These model errors appear to be associated with the errors in the large-scale environmental conditions that are fairly similar in this region for all model versions. The largest benefits of the 10-km simulation are the dramatically more accurate representation of the TC intensity distribution and the structure of the most intense storms. The model can generate a supertyphoon with a maximum surface wind speed of 68.4 m s−1. The life cycle of an intense TC comprises intensity fluctuations that occur in apparent connection with the variations of the eyewall/rainband structure. These findings suggest that a hydrostatic model with cumulus parameterization and of high enough resolution could be efficiently used to simulate the TC intensity response (and the associated structural changes) to future climate change.

The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale

“…There is mounting evidence from many modeling studies that atmosphere resolutions at 50 km or finer skillfully represent the interannual variability of tropical cyclones (Zhao et al 2009;Manganello et al 2012;Roberts et al 2015;Kodama et al 2015). In the Atlantic, much of this improvement can be attributed to better global teleconnections (from El Niño; e.g., Bell et al 2014) providing a constraint on the environment and improved dynamical precursor features such as African easterly waves (AEWs).…”

“…More recently the grid spacing in state-of-the-art global models has become sufficiently fine (of order 10-30 km) to realistically represent TCs, even in terms of intensity (Manganello et al 2012;Wehner et al 2014Wehner et al , 2015Murakami et al 2015;Walsh et al 2015;Scoccimarro 2016;Scoccimarro et al 2017), up to the maximum category 5. Our current understanding of future changes to frequency and intensity (Walsh et al 2015) is based on these relatively few capable models, hence indicating a more systematic and multimodel study is required to increase our confidence in such interpretations.…”

The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

“…Error statistics based on this measure is shown to be consistent with more traditional verification metrics [see Hodges and Emerton, 2015]. In addition, 10 m wind speed and minimum sea level pressure (SLP) were compared against the IBTrACS (Figure 9) because these quantities are underestimated in the CFSR data due to the model's resolution [e.g., Manganello et al, 2012]. …”

“…Recent advancements in high performance computing represent an exciting opportunity for global climate model development, pushing the limits of representing clouds and convection in a global atmospheric model [Chen and Lin, 2011;Dirmeyer et al, 2012;Manganello et al, 2012;Murakami et al, 2012;Bacmeister et al, 2014;Wehner et al, 2014]. As a consequence, atmospheric moist convection can now be represented in sophisticated schemes such as global cloud-resolving models and super parameterization schemes [Grabowski, 2001;Khairoutdinov and Randall, 2001;Randall et al, 2003;Tomita and Satoh, 2004;Satoh et al, 2008Satoh et al, , 2014Stan et al, 2010].…”

The influence of model resolution on the simulated sensitivity of North Atlantic tropical cyclone maximum intensity to sea surface temperature

“…Importantly, the MRI-AGCM, GFDL-HiRAM, and FSU-COAPS Strazzo et al [2015] suggest that model errors in larger scale features are partially to blame. Manganello et al [2012] attribute the inability of the ECMWF integrated forecast system to capture the observed spatial distribution of TC activity to model errors in the large-scale environmental conditions. Furthermore, they show that these errors tend to be fairly consistent regardless of the resolution used for the model run.…”