Journal Article

Impact of Model Resolution on Tropical Cyclone Simulation Using the HighResMIP–PRIMAVERA Multimodel Ensemble

Ullrich, Paul, Senan, Retish, Mecking, Jenny, Scoccimarro, Enrico, Valcke, Sophie, Moine, Marie-Pierre, Zarzycki, Colin, Seddon, Jon, Hodges, Kevin, Vidale, Pier Luigi, Putrasahan, Dian, Caron, Louis-Philippe, Haarsma, Rein, Roberts, Christopher, Bellucci, Alessio, Roberts, Malcolm John, Camp, Joanne, Vanniere, Benoit, Terray, Laurent, Chauvin, Fabrice

2020

Overview

A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ∼0.5 to ∼0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.

• Publisher: American Meteorological Society
• Subject: Algorithms / Atmosphere / Climate / Climate models / Climate variability / Climatology / Computer simulation / Cyclones / Datasets / Design / Earth Sciences / Energy / ENVIRONMENTAL SCIENCES / Extreme events / Hurricanes / Interannual variability / Meteorology & Atmospheric Sciences / Model evaluation/performance / Oceans / Optical properties / Resolution / Sciences of the Universe / Simulation / Spatial distribution / SPECIAL U.S. CLIVAR Hurricanes COLLECTION / Storm structure / Storms / Tracking / Tropical climate / Tropical climates / Tropical cyclones / Variability / Weather