4.7 Article

Real World and Tropical Cyclone World. Part I: High-Resolution Climate Model Verification

Journal

JOURNAL OF CLIMATE
Volume 33, Issue 4, Pages 1455-1472

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-19-0078.1

Keywords

Tropical cyclones; Climate variability; Climate models

Funding

  1. Australian Research Council [DP15012272]
  2. Northern Australia Climate Program (NACP) project at the University of Southern Queensland/Bureau of Meteorology, Australia
  3. ARC Centre of Excellence for Climate System Science
  4. Australian Government

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Recent global climate models with sufficient resolution and physics offer a promising approach for simulating real-world tropical cyclone (TC) statistics and their changing relationship with climate. In the first part of this study, we examine the performance of a high-resolution (40-km horizontal grid) global climate model, the atmospheric component of the Australian Community Climate and Earth System Simulator (ACCESS) based on the Met Office Unified Model (UM8.5) Global Atmosphere (GA6.0). The atmospheric model is forced with observed sea surface temperature, and 20 years of integrations (1990-2009) are analyzed for evaluating the simulated TC statistics compared with observations. The model reproduces the observed climatology, geographical distribution, and interhemispheric asymmetry of global TC formation rates reasonably well. The annual cycle of regional TC formation rates over most basins is also well captured. However, there are some regional biases in the geographical distribution of TC formation rates. To identify the sources of these biases, a suite of model-simulated large-scale climate conditions that critically modulate TC formation rates are further evaluated, including the assessment of a multivariate genesis potential index. Results indicate that the model TC genesis biases correspond well to the inherent biases in the simulated large-scale climatic states, although the relative effects on TC genesis of some variables differs between basins. This highlights the model's mean-state dependency in simulating accurate TC formation rates.

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