A hybrid approach for El Niño prediction based on Empirical Mode Decomposition and convolutional LSTM Encoder-Decoder

Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach

(2020) Lingjiang Tao et al.   CLIMATE DYNAMICS

Prediction of ENSO Beyond Spring Predictability Barrier Using Deep Convolutional LSTM Networks

(2020) Mayuna Gupta et al.   IEEE Geoscience and Remote Sensing Letters

Using a nonlinear forcing singular vector approach to reduce model error effects in ENSO forecasting

(2019) Tao Lingjiang et al.   WEATHER AND FORECASTING

The Application of Machine Learning Techniques to Improve El Niño Prediction Skill

(2019) Henk A. Dijkstra et al.   Frontiers in Physics

ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas: A Target Observation Perspective

(2018) Ling-Jiang Tao et al.   ADVANCES IN ATMOSPHERIC SCIENCES

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

(2018) Wansuo Duan et al.   CLIMATE DYNAMICS

Improved ENSO Forecasting Using Bayesian Updating and the North American Multimodel Ensemble (NMME)

(2017) Wei Zhang et al.   JOURNAL OF CLIMATE

Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons

(2017) Boyin Huang et al.   JOURNAL OF CLIMATE

Understanding ENSO Diversity

(2015) Antonietta Capotondi et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

The initial errors that induce a significant “spring predictability barrier” for El Niño events and their implications for target observation: results from an earth system model

(2015) Wansuo Duan et al.   CLIMATE DYNAMICS

The quiet revolution of numerical weather prediction

(2015) Peter Bauer et al.   NATURE

Development of the analogue-dynamical method for error correction of numerical forecasts

(2014) Haipeng Yu et al.   Journal of Meteorological Research

Prediction of sea surface temperature in the tropical Atlantic by support vector machines

(2012) Isis Didier Lins et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

The ‘spring predictability barrier’ for ENSO predictions and its possible mechanism: results from a fully coupled model

(2012) Wansuo Duan et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

Skill of Real-Time Seasonal ENSO Model Predictions during 2002–11: Is Our Capability Increasing?

(2011) Anthony G. Barnston et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

ECMWF seasonal forecast system 3 and its prediction of sea surface temperature

(2011) Timothy N. Stockdale et al.   CLIMATE DYNAMICS

Daily streamflow forecasting by machine learning methods with weather and climate inputs

(2011) Kabir Rasouli et al.   JOURNAL OF HYDROLOGY

An artificial neural network (p,d,q) model for timeseries forecasting

(2009) Mehdi Khashei et al.   EXPERT SYSTEMS WITH APPLICATIONS

Forecasting Pacific SSTs: Linear Inverse Model Predictions of the PDO

(2008) Michael A. Alexander et al.   JOURNAL OF CLIMATE