Shineng Hu

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Articles

Weather-Changing El Niño Oscillation Is at Least 250 Million Years Old

Oct 21, 2024 | today.duke.edu | Shineng Hu

Published October 21, 2024 The El Niño event, a huge blob of warm ocean water in the tropical Pacific Ocean that can change rainfall patterns around the globe, isn't just a modern phenomenon. A new modeling study from a pair of Duke University researchers and their colleagues shows that the oscillation between El Niño and its cold counterpart, La Niña, was present at least 250 million years in the past, and was often of greater magnitude than the oscillations we see today.
The role of sea surface salinity in ENSO forecasting in the 21st century - npj Climate and Atmospheric Science

Sep 4, 2024 | nature.com | Shineng Hu

AbstractSignificant strides have been made in understanding El Niño-Southern Oscillation (ENSO) dynamics, yet its long-lead prediction remains challenging, especially for the El Niño events after 2000. Sea surface salinity (SSS) is known to affect ENSO development and intensity by influencing ocean stratification and heat redistribution and therefore, when combined with sea surface temperature (SST) data, can potentially enhance ENSO forecast skill.
Elevation-dependent warming: observations, models, and energetic mechanisms

Jan 5, 2024 | wcd.copernicus.org | Michael Byrne |William R. Boos |Shineng Hu

Bliss, A., Hock, R., and Radić, V.: Global response of glacier runoff to twenty-first century climate change, J. Geophys. Res.-Earth, 119, 717–730, https://doi.org/10.1002/2013JF002931, 2014. a Byrne, M. P. and O'Gorman, P. A.: Land–ocean warming contrast over a wide range of climates: Convective quasi-equilibrium theory and idealized simulations, J. Climate, 26, 4000–4016, 2013.
Historical Changes in Wind‐Driven Ocean Circulation Can Accelerate Global Warming

Feb 22, 2023 | agupubs.onlinelibrary.wiley.com | Sarah Larson |Shineng Hu |Ryan Kramer |Kay McMonigal

2.5 Significance Testing To determine the regions and time periods where trends are significantly different, we consider the spread of the ensemble members as a normal distribution. To test if the distributions are significantly different, we calculate the Z statistic and use 95% significance (Z ≥ 1.96) as a threshold, where: is the ensemble mean from each simulation. 𝝈 is the standard deviation of each ensemble member divided by the square root of the number of ensemble members.