Yishuai Jin

Code for Transient Mechanisms of the Interhemispheric Thermal Contrast in an Earth System Model

Feiyu Huang, Chengfei He, Yishuai Jin

Major scripts for paper Transient Mechanisms of the Interhemispheric Thermal Contrast in an Earth System Model.

mx, cn (code pays fourni par la source)

Code for Transient Mechanisms of the Interhemispheric Thermal Contrast in an Earth System Model

Feiyu Huang, Chengfei He, Yishuai Jin

Major scripts for paper Transient Mechanisms of the Interhemispheric Thermal Contrast in an Earth System Model.

mx, cn (code pays fourni par la source)

Atmospheric Noise Forcing Increases Multiyear El Niño Events

Keqing Bai, Yishuai Jin, Wei Zhang, Xiaopei Lin et autres

Abstract Despite their pronounced climate impacts, the physical processes that control the frequency of multiyear El Niño events remain incompletely understood. Using an Interactive Ensemble (IE) coupling strategy, we find that atmospheric noise forcing plays an important role in modulating the frequency …

cn, us (code pays fourni par la source)

Non‐Gaussian Assimilation of Atmospheric and Oceanic Data in Latent Space for Paleoclimate Reconstruction

Zikuan Lin, Shaoqing Zhang, Zhengyu Liu, Yishuai Jin et autres

Abstract Two of the challenges for paleoclimate data assimilation (PDA) are the extreme sparsity of proxy observations and the non‐Gaussian nature of background errors in the climate system. In this study, we develop a latent‐space variational data assimilation framework based on variational …

cn, us (code pays fourni par la source)

Deep learning reveals enhanced ENSO predictability under historical anthropogenic forcing

Zikuan Lin, Yishuai Jin, Chengfei He, Shaoqing Zhang et autres

Understanding how ENSO predictability responds to climate change is essential for improving future climate projections. In this study, we apply a deep learning model-convolutional neural network with a leave-one-out model strategy to Coupled Model Intercomparison Project Phase 6 (CMIP6) historical and preindustrial …

cn, us (code pays fourni par la source)

A Winter Predictability Barrier in the Far-Eastern Pacific

饶正祥, Yishuai Jin

Abstract The far-eastern Pacific (FEP) sea surface temperature anomaly (SSTA) has sparked renewed interest among scientists after coastal Niño had a huge impact on Peru in 2017. However, its predictability and the way to improve its prediction remain unknown. Our research indicates …

cn (code pays fourni par la source)

The mechanism of the ENSO diversity predictability paradox

Sheng Wu, 饶正祥, Yishuai Jin, Yonggang Liu

The predictability of the El Niño–Southern Oscillation (ENSO) has attracted increasing attention, as it has important impacts on both global ecosystems and the global climate system. However, current ENSO prediction capabilities remain limited. Previous studies have revealed an ENSO diversity predictability paradox: …

cn, us (code pays fourni par la source)

South China Sea “神针(Trident)”: Solution for ocean forecast foundation models

Wei Zhao, Xiaopei Lin, Yishuai Jin, Weinan Huang et autres

cn (code pays fourni par la source)

Impact of high-frequency atmospheric noise on ENSO predictability

Guangyu Chi, Ao Li, Yishuai Jin, Xiaopei Lin

cn (code pays fourni par la source)

Reduced ENSO Amplitude via Diurnal Air–Sea Interaction: A Modeling Study in CESM

Yiqun Pang, Yishuai Jin, K. Wang, Lv Lu et autres

Abstract Previous studies have shown that incorporating diurnal surface air–sea interactions—described by the integrated subdiurnal parameterization (ISDP)—enhances the overall performance of model simulations, but the impact of this parameterization on El Niño–Southern Oscillation (ENSO) events and its underlying physical mechanism is still …

cn (code pays fourni par la source)

Improving ENSO Prediction at Longer Lead Times: Role of Off‐Equatorial South Pacific Heat Content

Gui Qing YANG, Yishuai Jin, Yingying Zhao, Emanuele Di Lorenzo et autres

Abstract Previous studies have demonstrated that signals originating from the South Pacific can improve the El Niño‐Southern Oscillation (ENSO) prediction at various lead times. In this study, it is found that sea surface height anomalies in the off‐equatorial South Pacific (SP SSH), …

cn, us (code pays fourni par la source)

The Hidden Predictor of Multi‐Year ENSO Predictions Revealed by Deep Learning

Xianyao Chen, Yishuai Jin, Yingying Zhao, Junyu Dong et autres

Abstract Data‐driven deep learning models (DLMs) can predict the El Niño‐Southern Oscillation (ENSO) up to a year in advance, a capability that traditional physical and statistical models struggle to achieve due to the Spring Predictability Barrier (SPB). However, the specific knowledge that …

cn (code pays fourni par la source)