Ping Huang

Prof. Ping Huang


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 April 2013 in Nature Geoscience
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Journal Article
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PHPing Huang
Ping Huang
SXShang-Ping Xie
Shang-Ping Xie
KHKaiming Hu
Kaiming Hu
Gang HuangGang Huang
Gang Huang
RHRonghui Huang
Ronghui Huang

26 October 2015 in Nature Geoscience
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Journal Article
Closed access
PHPing Huang
Ping Huang
SXShang-Ping Xie
Shang-Ping Xie

15 April 2021 in Nature Geoscience
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Journal Article
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KHKaiming Hu
Kaiming Hu
Gang HuangGang Huang
Gang Huang
PHPing Huang
Ping Huang
YKYu Kosaka
Yu Kosaka
SXShang-Ping Xie
Shang-Ping Xie

18 May 2015 in Nature Communications
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Journal Article
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PHPing Huang
Ping Huang
ILI. -I Lin
I. -I Lin
CCChia Chou
Chia Chou
RHRong-Hui Huang
Rong-Hui Huang
Tropical cyclones (TCs) are hazardous natural disasters. Because TC intensification is significantly controlled by atmosphere and ocean environments, changes in these environments may cause changes in TC intensity. Changes in surface and subsurface ocean conditions can both influence a TC’s intensification. Regarding global warming, minimal exploration of the subsurface ocean has been undertaken. Here we investigate future subsurface ocean environment changes projected by 22 state-of-the-art climate models and suggest a suppressive effect of subsurface oceans on the intensification of future TCs. Under global warming, the subsurface vertical temperature profile can be sharpened in important TC regions, which may contribute to a stronger ocean coupling (cooling) effect during the intensification of future TCs. Regarding a TC, future subsurface ocean environments may be more suppressive than the existing subsurface ocean environments. This suppressive effect is not spatially uniform and may be weak in certain local areas.

2 April 2021 in The Innovation
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Open access
XYXianke Yang
Xianke Yang
PHPing Huang
Ping Huang
El Niño–Southern Oscillation (ENSO) was identified as the dominant predictor for the Indian summer monsoon rainfall (ISMR) in the early 1900s. An apparent weakening of the ENSO–ISMR relationship has been observed since the 1970s. Here, we found a clear restoration of the ENSO–ISMR relationship since 1999/2000. This restoring relationship is closely linked to the interdecadal transition of ENSO evolution and the associated sea surface temperature anomalies (SSTAs) over the tropical Atlantic. During 1979–1997, summer ENSO events mainly continued from the previous winter, which can drive apparent Atlantic Niña SSTAs to offset ENSO's impact on ISMR and weaken the ENSO–ISMR relationship. In contrast, when ENSO events newly emerge from late spring, as they have done more recently during 2000–2018, the associated tropical Atlantic SSTAs are weak and shift to the tropical North Atlantic, which can offset the contribution of Atlantic Niña and reinforce the ENSO–ISMR relationship. We identified that the diversity of ENSO's evolution, continuing from the previous winter or emerging from late spring, is the dominant factor perturbing the ENSO–ISMR relationship in recent epochs, with tropical Atlantic SSTAs as the crucial bridge. This finding should be considered in our efforts to improve ISMR prediction.

1 April 2021 in Journal of Climate
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WJWenping Jiang
Wenping Jiang
PHPing Huang
Ping Huang
GHGang Huang
Gang Huang
JYJun Ying
Jun Ying
An excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSO SST variability among the models. The ENSO SST bias lowers the models’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension of ENSO SST in 25 CMIP5 and 25 CMIP6 models. Based on the intermodel spread of ENSO SST variability simulated in the 50 models, we reveal that this ENSO SST bias among the models largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue from CMIP5 to CMIP6, the excessive westward extension bias of ENSO SST in CMIP6 models is also reduced relative to those in CMIP5 models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which improves ENSO simulation.