Pun Iam-Fei

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Pun
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Iam-Fei
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  • Article
    Rapid intensification of Typhoon Hato (2017) over shallow water
    (MDPI, 2019-07-06) Pun, Iam-Fei ; Chan, Johnny C. L. ; Lin, I.-I. ; Chan, Kelvin T. F. ; Price, James F. ; Ko, Dong S. ; Lien, Chun-Chi ; Wu, Yu-Lun ; Huang, Hsiao-Ching
    On 23 August, 2017, Typhoon Hato rapidly intensified by 10 kt within 3 h just prior to landfall in the city of Macau along the South China coast. Hato’s surface winds in excess of 50 m s−1 devastated the city, causing unprecedented damage and social impact. This study reveals that anomalously warm ocean conditions in the nearshore shallow water (depth < 30 m) likely played a key role in Hato’s fast intensification. In particular, cooling of the sea surface temperature (SST) generated by Hato at the critical landfall point was estimated to be only 0.1–0.5 °C. The results from both a simple ocean mixing scheme and full dynamical ocean model indicate that SST cooling was minimized in the shallow coastal waters due to a lack of cool water at depth. Given the nearly invariant SST in the coastal waters, we estimate a large amount of heat flux, i.e., 1.9k W m−2, during the landfall period. Experiments indicate that in the absence of shallow bathymetry, and thus, if nominal cool water had been available for vertical mixing, the SST cooling would have been enhanced from 0.1 °C to 1.4 °C, and sea to air heat flux reduced by about a quarter. Numerical simulations with an atmospheric model suggest that the intensity of Hato was very sensitive to air-sea heat flux in the coastal region, indicating the critical importance of coastal ocean hydrography.
  • Article
    Satellite-derived ocean thermal structure for the North Atlantic hurricane season
    (American Meteorological Society, 2015-12-08) Pun, Iam-Fei ; Price, James F. ; Jayne, Steven R.
    This paper describes a new model (method) called Satellite-derived North Atlantic Profiles (SNAP) that seeks to provide a high-resolution, near-real-time ocean thermal field to aid tropical cyclone (TC) forecasting. Using about 139 000 observed temperature profiles, a spatially dependent regression model is developed for the North Atlantic Ocean during hurricane season. A new step introduced in this work is that the daily mixed layer depth is derived from the output of a one-dimensional Price–Weller–Pinkel ocean mixed layer model with time-dependent surface forcing. The accuracy of SNAP is assessed by comparison to 19 076 independent Argo profiles from the hurricane seasons of 2011 and 2013. The rms differences of the SNAP-estimated isotherm depths are found to be 10–25 m for upper thermocline isotherms (29°–19°C), 35–55 m for middle isotherms (18°–7°C), and 60–100 m for lower isotherms (6°–4°C). The primary error sources include uncertainty of sea surface height anomaly (SSHA), high-frequency fluctuations of isotherm depths, salinity effects, and the barotropic component of SSHA. These account for roughly 29%, 25%, 19%, and 10% of the estimation error, respectively. The rms differences of TC-related ocean parameters, upper-ocean heat content, and averaged temperature of the upper 100 m, are ~10 kJ cm−2 and ~0.8°C, respectively, over the North Atlantic basin. These errors are typical also of the open ocean underlying the majority of TC tracks. Errors are somewhat larger over regions of greatest mesoscale variability (i.e., the Gulf Stream and the Loop Current within the Gulf of Mexico).