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Exploring Western North Pacific Tropical Cyclone Activity in the High-Resolution Community Atmosphere Model
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  • Xiaoning Wu,
  • Kevin A. Reed,
  • Patrick Callaghan,
  • Julio T. Bacmeister
Xiaoning Wu
Stony Brook University

Corresponding Author:[email protected]

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Kevin A. Reed
Stony Brook University
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Patrick Callaghan
National Center for Atmospheric Research
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Julio T. Bacmeister
National Center for Atmospheric Research (UCAR)
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High-resolution climate models (~28 km grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus enabling their investigation in relation to the climate system. On the global scale, previous works have demonstrated that the Community Atmosphere Model (CAM) version 5 presents a reasonable TC climatology under prescribed present-day (1980-2005) forcing. However, for the Western North Pacific (WNP) region, known biases in simulated TC genesis frequency and location under-represent the basin’s dominant share in observation. This study addresses these model biases in WNP by evaluating WNP TCs in a decadal simulation, and exploring potential improvements through nudging experiments. Among the major environmental controls of TC genesis, the lack of mid-level moisture is identified as the leading cause of the deficit in simulated WNP TC genesis over the Pacific Warm Pool. Subsequent seasonal experiments explore the effect of constraining the large-scale environment on TC development by nudging WNP temperature field towards reanalysis at various strengths. Temperature nudging elicits significant response in TC genesis and intensity development, as well as in moisture and convection over the Warm Pool. These responses are sensitive to the choice of nudging timescale. Overall, the nudging experiments demonstrate that improvements in the large-scale environment can lead to improvements in simulated TCs. The verification of the environmental controls for simulated TC genesis suggests future model developments in relation to model physics. The potential improvements will contribute to the understanding of how the mean state of current or future climates may give rise to extremes such as TCs.
Jan 2022Published in Earth and Space Science volume 9 issue 1. 10.1029/2021EA001862