Spatiotemporal forecasting in earth system science: Methods, uncertainties, predictability and future directions

Learning earth system models from observations: machine learning or data assimilation?

(2021) A. J. Geer   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Improving global monthly and daily precipitation estimation by fusing gauge observations, remote sensing and reanalysis datasets

(2020) Lei Xu et al.   WATER RESOURCES RESEARCH

Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms

(2020) Manali Pal et al.   Scientific Reports

Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model

(2020) David John Gagne et al.   Journal of Advances in Modeling Earth Systems

Short-Term Traffic Flow Forecasting Based on Data-Driven Model

(2020) Su-qi Zhang et al.   Mathematics

Estimating daily ground-level PM2.5 in China with random-forest-based spatiotemporal kriging

(2020) Yanchuan Shao et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions

(2020) Janni Yuval et al.   Nature Communications

Purely satellite data–driven deep learning forecast of complicated tropical instability waves

(2020) Gang Zheng et al.   Science Advances

A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China

(2020) Rong-Hua Zhang et al.   Journal of Oceanology and Limnology

Continental drought monitoring using satellite soil moisture, data assimilation and an integrated drought index

(2020) Lei Xu et al.   REMOTE SENSING OF ENVIRONMENT

In-situ and triple-collocation based evaluations of eight global root zone soil moisture products

(2020) Lei Xu et al.   REMOTE SENSING OF ENVIRONMENT

Improving the North American multi-model ensemble (NMME) precipitation forecasts at local areas using wavelet and machine learning

(2019) Lei Xu et al.   CLIMATE DYNAMICS

Applications of Deep Learning to Ocean Data Inference and Sub-Grid Parameterisation

(2019) Thomas Bolton et al.   Journal of Advances in Modeling Earth Systems

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

Deep learning and its application in geochemical mapping

(2019) Renguang Zuo et al.   EARTH-SCIENCE REVIEWS

Development and Evaluation of Hybrid Artificial Neural Network Architectures for Modeling Spatio-Temporal Groundwater Fluctuations in a Complex Aquifer System

(2019) Thendiyath Roshni et al.   WATER RESOURCES MANAGEMENT

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

(2019) Tao Lingjiang et al.   WEATHER AND FORECASTING

Making the black box more transparent: Understanding the physical implications of machine learning

(2019) Amy McGovern et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

Deep learning for multi-year ENSO forecasts

(2019) Yoo-Geun Ham et al.   NATURE

A comprehensive comparison of four input variable selection methods for artificial neural network flow forecasting models

(2019) E. Snieder et al.   JOURNAL OF HYDROLOGY

The Pacific Decadal Oscillation less predictable under greenhouse warming

(2019) Shujun Li et al.   Nature Climate Change

Changes in ENSO amplitude under climate warming and cooling

(2018) Yingying Wang et al.   CLIMATE DYNAMICS

A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon-Ocean Feedback in Typhoon Forecast Models

(2018) Guo-Qing Jiang et al.   GEOPHYSICAL RESEARCH LETTERS

Could Machine Learning Break the Convection Parameterization Deadlock?

(2018) P. Gentine et al.   GEOPHYSICAL RESEARCH LETTERS

Evaluation of four hydrological models for operational flood forecasting in a Canadian Prairie watershed

(2018) Fisaha Unduche et al.   HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES

A comparison of large-scale climate signals and the North American Multi-Model Ensemble (NMME) for drought prediction in China

(2018) Lei Xu et al.   JOURNAL OF HYDROLOGY

Deep learning for smart manufacturing: Methods and applications

(2018) Jinjiang Wang et al.   JOURNAL OF MANUFACTURING SYSTEMS

Statistical and Machine Learning forecasting methods: Concerns and ways forward

(2018) Spyros Makridakis et al.   PLoS One

Forecasting daily global solar irradiance generation using machine learning

(2018) Amandeep Sharma et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Novel short term solar irradiance forecasting models

(2018) Emre Akarslan et al.   RENEWABLE ENERGY

A Deep CNN-LSTM Model for Particulate Matter (PM2.5) Forecasting in Smart Cities

(2018) Chiou-Jye Huang et al.   SENSORS

An evaluation of statistical, NMME and hybrid models for drought prediction in China

(2018) Lei Xu et al.   JOURNAL OF HYDROLOGY

Deep learning of aftershock patterns following large earthquakes

(2018) Phoebe M. R. DeVries et al.   NATURE

Deep learning to represent subgrid processes in climate models

(2018) Stephan Rasp et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables

(2018) Tomislav Hengl et al.   PeerJ

A stochastic data‐driven ensemble forecasting framework for water resources: A case study using ensemble members derived from a database of deterministic wavelet‐based models

(2018) John Quilty et al.   WATER RESOURCES RESEARCH

Comparison of Artificial Intelligence and Physical Models for Forecasting Photosynthetically-Active Radiation

(2018) Lan Feng et al.   Remote Sensing

Progress in ENSO prediction and predictability study

(2018) Youmin Tang et al.   National Science Review

Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

(2018) Ata Akbari Asanjan et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Adaptive Neuro-Fuzzy Inference System integrated with solar zenith angle for forecasting sub-tropical Photosynthetically Active Radiation

(2018) Ravinesh C. Deo et al.   Food and Energy Security

Variational Inference: A Review for Statisticians

(2017) David M. Blei et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Bayesian maximum entropy approach and its applications: a review

(2017) Junyu He et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Deep learning for short-term traffic flow prediction

(2017) Nicholas G. Polson et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Improved ensemble-mean forecasting of ENSO events by a zero-mean stochastic error model of an intermediate coupled model

(2016) Fei Zheng et al.   CLIMATE DYNAMICS

PM2.5forecasting with hybrid LSE model-based approach

(2016) Yunliang Chen et al.   SOFTWARE-PRACTICE & EXPERIENCE

The quiet revolution of numerical weather prediction

(2015) Peter Bauer et al.   NATURE

Probabilistic machine learning and artificial intelligence

(2015) Zoubin Ghahramani   NATURE

Deep learning

(2015) Yann LeCun et al.   NATURE

A Short-term Traffic Flow Forecasting Method Based on the Hybrid PSO-SVR

(2015) Wenbin Hu et al.   NEURAL PROCESSING LETTERS

Machine learning: Trends, perspectives, and prospects

(2015) M. I. Jordan et al.   SCIENCE

A framework for propagation of uncertainty contributed by parameterization, input data, model structure, and calibration/validation data in watershed modeling

(2014) Haw Yen et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target

(2014) Kaighin A. McColl et al.   GEOPHYSICAL RESEARCH LETTERS

The North American Multimodel Ensemble: Phase-1 Seasonal-to-Interannual Prediction; Phase-2 toward Developing Intraseasonal Prediction

(2013) Ben P. Kirtman et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting

(2013) M. Rezaeianzadeh et al.   International Journal of Environmental Science and Technology

M5 model tree application in daily river flow forecasting in Sohu Stream, Turkey

(2013) M. Taghi Sattari et al.   Water Resources

Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products

(2012) Wade T. Crow et al.   REVIEWS OF GEOPHYSICS

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

An Overview of CMIP5 and the Experiment Design

(2011) Karl E. Taylor et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

Using the WRF Model in an Operational Streamflow Forecast System for the Jordan River

(2011) Amir Givati et al.   Journal of Applied Meteorology and Climatology

An adaptive model for predicting of global, direct and diffuse hourly solar irradiance

(2009) A. Mellit et al.   ENERGY CONVERSION AND MANAGEMENT

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Multi-model decadal potential predictability of precipitation and temperature

(2008) G. J. Boer et al.   GEOPHYSICAL RESEARCH LETTERS

An ANN-based model for spatiotemporal groundwater level forecasting

(2008) Vahid Nourani et al.   HYDROLOGICAL PROCESSES

Validation of high‐resolution satellite rainfall products over complex terrain

(2008) T. Dinku et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

Average Predictability Time. Part I: Theory

(2008) Timothy DelSole et al.   JOURNAL OF THE ATMOSPHERIC SCIENCES

Ensemble forecasting

(2007) M. Leutbecher et al.   JOURNAL OF COMPUTATIONAL PHYSICS