Hsu, Huang-Hsiung許晃雄

CEO & Distinguished Research Fellow

Research Interests

HHH’s research interest includes climate variation and change, monsoon, and atmosphere-ocean teleconnection. He published journal papers in a) atmosphere-ocean teleconnection, b) multiscale interaction in the Western North Pacific, c) compound effects causing the weather and climate extremes, d) simulation, projection, mechanism, and ecological impacts of the Madden-Julian Oscillation/Intraseasonal Oscillation (MJO/ISO), and e) diagnostics and projection of Asian monsoon and Taiwan climate.

 His recent research focuses on the linkage between natural climate variability, e.g., detecting the emerging anthropogenic effect on climate and projecting how the known climatic processes might change in the warming future. He leads the Taiwan Earth System Model team in RCEC’s climate model development effort and the participation in the Coupled Model Intercomparison Project Phase 6 to contribute locally-produced climate change data for the preparation of IPCC AR6. He also organizes the effort in developing seamless model system for the simulation and projection of global–urban climate and weather with the focus on extreme events.

Representative Publications

  1. Hsu, P.-C., H.-H. Hsu*, H.-J. Hong, Y.-T. Chen, Y.-L. Chen, and W.-L. Tseng, 2022: 2021 Texas Cold Snap: Manifestation of Natural Variability and Recent Warming Trend. Weather and Climate Extremes, 37, 100476, https://doi.org/10.1016/j.wace.2022.100476.
  2. Tseng, W.-L., H.-H. Hsu*, Y.-Y. Lan, C.-Y. Tu, P.-H. Kuo, B.-J. Tsuang, H.-C. Liang, 2022: Improving Madden–Julian Oscillation Simulation in Atmospheric General Circulation Models by Coupling with Snow–Ice–Thermocline One-dimensional Ocean Model. Geosci. Model Dev., 15, 5529–5546, https://doi.org/10.5194/gmd-15-5529-2022.
  3. Wang, Y. C., H.-H. Hsu*, C.-A. Chen, W.-L. Tseng, P.-C. Hsu, C.-W. Lin, Y.-L. Chen, L.-C. Jiang, Y.-C. Lee, H.-C. Liang, and W.-M. Chang, W.-L. and Lee, C.-J. Shiu, 2021: Performance of the Taiwan Earth System Model in Simulating Climate Variability Compared With Observations and CMIP6 Model Simulations. J. Advances in Modeling Earth Systems, 13, 7, 1-28, https://doi.org/10.1029/2020MS002353.
  4. Arakane, S., and H.-H. Hsu#, 2021: Tropical Cyclone Footprints in Long-Term Mean State and Multiscale Climate Variability in the Western North Pacific as Seen in the JRA-55 Reanalysis. J. Climate, 34, 18, 7443-7460, https://doi.org/10.1175/JCLI-D-20-0887.1.
  5. Hong, C.-C., W.-L. Tseng, H.-H. Hsu*, M.-Y. Lee, and C.-C. Chang, 2021: Relative Contribution of Trend and Interannually Varying SST Anomalies to the 2018 Heat Waves in the Extratropical Northern Hemisphere. J. Climate, 34,15, 6319–6333, http://dx.doi.org/10.1175/jcli-d-20-0556.1.
  6. Hsu, H.-H.*, and Y.-T. Chen, 2020: Simulation and Projection of Circulations Associated with Atmospheric Rivers along the North American Northeast Coast. J. Climate, 33, 13, 5673–5695, http://dx.doi.org/10.1175/jcli-d-19-0104.1.
  7. Chang, C. J., H.-H. Hsu*, W. Cheah, W.-L. Tseng, and L.-C. Jiang, 2019: Madden–Julian Oscillation Enhances Phytoplankton Biomass in the Maritime Continent. Sci. Rep., 9, 5421, https://doi:10.1038/s41598-019-41889-5.
  8. Chen, C.-A., H.-H. Hsu*, C.-C. Hong, P.-G. Chiu, C.-Y. Tu and S.-J. Lin, 2019: Seasonal precipitation change in the Western North Pacific and East Asia under global warming in two high-resolution AGCMs. Climate Dynamics, 53, 5583–5605, https://doi.org/10.1007/s00382-019-04883-1.
  9. Arakane, S., and H.-H. Hsu*, 2019: Remote effect of a tropical cyclone in the Bay of Bengal on a heavy-rainfall event in subtropical East Asia. npj Climate and Atmospheric Science, 2, 25, https://doi:10.1038/s41612-019-0082-8.
  10. Hong, C.-C., M.-Y. Lee, H.-H. Hsu*, and W.-L. Tseng, 2018: Distinct Influences of the ENSO-Like and PMM-Like SST Anomalies on the Mean TC Genesis Location in the Western North Pacific: The 2015 Summer as an Extreme Example. J. Climate, 31, 8, 3049-3059, https://doi:10.1175/JCLI-D-17-0504.1.


Madden-Julian Oscillation:  The oscillation is the most important tropical climatic phenomenon only second to the El Niño, and yet is still a big challenge for climate models to properly simulate. HHH and collaborators made a breakthrough in early 2010s by demonstrating that coupling a high-resolution one-column ocean mixed-layer model (named SIT) to the atmospheric general circulation model AGCM dramatically improves the simulation of the MJO to have realistic strength, period, and propagation speed. Better resolving the fine structure of upper ocean temperature, especially the warm layer, produces more vigorous atmosphere-ocean interaction and strengthens intraseasonal variations in both SST and atmospheric circulation. HHH was one of the first few researchers to systematically investigate the orographic effect of the Maritime Continent on the MJO, which is an important mechanism having been largely neglected in the MJO research and recently receiving more attention because of the Year of Maritime Continent field campaign.

Multiscale Interaction in the Western North Pacific:  HHH and collaborators explored the multiscale interaction between tropical cyclone (TC), submonthly perturbation, and intraseasonal oscillation in the western North Pacific (WNP) during the boreal summer. They found that the existence of TCs significantly enhanced the monsoon trough and weakened the subtropical high in the WNP, and amplified the intraseasonal–interannual climate variability by 40–60 percent. This finding suggests that TC is a part of climate system and should be considered as an integral component to understand climate variability and climate change.

Weather and climate extremes:  HHH and collaborators conducted a series of studies on record-breaking extreme events and proposed that the compound effect of various influencing factors caused the weather and climate extremes. Each seemingly random event might be caused by different combination of various factors. This randomness is seemingly the reason for the low predictability of the extremes and why statistical study such as composite or correlation analysis often failed to explain the extremes. Global warming would result in an increase in the probability of synchronization of various influencing factors and increase the occurrence probability of weather and climate extremes.

Climate model development:  HHH organized an effort at climate model development in 2011 under the support of the MOST to nurture local talents in climate modeling and develop/implement climate models for the use in Taiwan. Since 2011, a climate model team has been established with the ability in modifying the existing climate models and implementing new modules developed locally. This effort has led to the implementation of Taiwan Earth System Model (TaiESM) developed locally, the High-resolution Atmospheric Model (GFDL, 25 and 50 km) developed by the GFDL and the extremely high-resolution (13 km) fvGFS-tw with a nested domain (3 km) over Taiwan.

Climate change projection under RCP emission scenarios:  Using the high-resolution projection data from the HiRAM and MRI-AGCM (including d4PDF data) and also coarser-resolution CMIP5/6 models (including TaiESM) to conduct a series of climate change studies with the focus on East Asian monsoon and climate systems (e.g., front, drought, atmospheric river) that affect Taiwan.

  • Distinguished Research Fellow, Research Fellow
    Research Center for Environmental Changes
    Academia Sinica (2017~present, 2011~2017)
  • Professor, Associate professor, Chairman
    Department of Atmospheric Sciences
    National Taiwan University (1992~2011, 1989~1992, 2002~2005)
  • Post-doctoral Research Fellow
    Department of Meteorology
    University of Reading, UK (1989)
  • Ph.D.
    Atmospheric Sciences
    University of Washington, Seattle, USA (1986)