Key papers

• Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition (2025)
  Zeinab Hassani et al.
  5.04
• Disentangling Forced and Internal Climate Variability in Single Realizations using Dynamic Mode Decomposition with Control (2026)
  Nathan Mankovich et al.
  5.01
• Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning (2024)
  Ayoub Jadouli et al.
  4.85
• FireCastNet: Earth-as-a-Graph for Seasonal Fire Prediction (2025)
  Dimitrios Michail et al.
  3.59
• When Simpler Wins: Facebooks Prophet vs LSTM for Air Pollution Forecasting in Data-Constrained Northern Nigeria (2025)
  Habeeb Balogun and Yahaya Zakari
  2.99
• SF$^2$Bench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida (2025)
  Xu Zheng and Chaohao Lin and Sipeng Chen and Zhuomin Chen and Jimeng Shi and Wei Cheng and Jayantha Obeysekera and Jason Liu and Dongsheng Luo
  2.87
• Urban Water Consumption Forecasting Using Deep Learning and Correlated District Metered Areas (2025)
  Kleanthis Malialis et al.
  2.60
• The Merit of River Network Topology for Neural Flood Forecasting (2024)
  Nikolas Kirschstein et al.
  2.21
• Water Level Forecasting in the Gamcheon River, Korea, Using TimeGPT (2026)
  Jon-Lark Kim et al.
  1.94
• Skillful Global Ocean Emulation and the Role of Correlation-Aware Loss (2026)
  Niraj Agarwal et al.
  1.83
• Attention-based Multi-modal Deep Learning Model of Spatio-temporal Crop Yield Prediction with Satellite, Soil and Climate Data (2026)
  Gopal Krishna Shyam et al.
  1.83
• Interpretable PM2.5 Forecasting for Urban Air Quality: A Comparative Study of Operational Time-Series Models (2026)
  Moazzam Umer Gondal et al.
  1.78
• Advanced Global Wildfire Activity Modeling with Hierarchical Graph ODE (2026)
  Fan Xu et al.
  1.67
• Eddy-Resolving Global Ocean Forecasting with Multi-Scale Graph Neural Networks (2026)
  Yuta Hirabayashi et al.
  1.67
• A Graph Neural Network Approach for Localized and High-Resolution Temperature Forecasting (2025)
  Joud El-Shawa et al.
  1.61
• A Novel Deep Neural Network Architecture for Real-Time Water Demand Forecasting (2025)
  Tony Salloom et al.
  1.61
• CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting (2025)
  Shu Wan et al.
  1.61
• Applying Time Series Deep Learning Models to Forecast the Growth of Perennial Ryegrass in Ireland (2025)
  Oluwadurotimi Onibonoje et al.
  1.56
• Long-Term PM2.5 Forecasting Using a DTW-Enhanced CNN-GRU Model (2025)
  Amirali Ataee Naeini et al.
  1.50
• A Deep Learning Approach for Spatio-Temporal Forecasting of InSAR Ground Deformation in Eastern Ireland (2025)
  Wendong Yao et al.
  1.44
• A Causality-Aware Spatiotemporal Model for Multi-Region and Multi-Pollutant Air Quality Forecasting (2025)
  Junxin Lu et al.
  1.44
• Marine Chlorophyll Prediction and Driver Analysis based on LSTM-RF Hybrid Models (2025)
  Zhouyao Qian et al.
  1.39
• XFMNet: Decoding Cross-Site and Nonstationary Water Patterns via Stepwise Multimodal Fusion for Long-Term Water Quality Forecasting (2025)
  Ziqi Wang et al.
  1.39
• MVAR: MultiVariate AutoRegressive Air Pollutants Forecasting Model (2025)
  Xu Fan et al.
  1.33
• Sugar-Beet Stress Detection using Satellite Image Time Series (2025)
  Bhumika Laxman Sadbhave et al.
  1.33
• A Data-Driven Approach to Estimate LEO Orbit Capacity Models (2025)
  Braden Stock et al.
  1.33
• Multi-Hazard Early Warning Systems for Agriculture with Featural-Temporal Explanations (2025)
  Boyuan Zheng and Victor W. Chu
  1.33
• Next-Generation Conflict Forecasting: Unleashing Predictive Patterns through Spatiotemporal Learning (2025)
  Simon P. von der Maase
  1.28
• LanTu: Dynamics-Enhanced Deep Learning for Eddy-Resolving Ocean Forecasting (2025)
  Qingyu Zheng et al.
  1.22
• STFM: A Spatio-Temporal Information Fusion Model Based on Phase Space Reconstruction for Sea Surface Temperature Prediction (2025)
  Yin Wang et al.
  1.17
• Frequency-Aware Attention-LSTM for PM$_{2.5}$ Time Series Forecasting (2025)
  Jiahui Lu et al.
  1.11
• A Study on Monthly Marine Heatwave Forecasts in New Zealand: An Investigation of Imbalanced Regression Loss Functions with Neural Network Models (2025)
  Ding Ning et al.
  1.06
• Multi-Year-to-Decadal Temperature Prediction using a Machine Learning Model-Analog Framework (2025)
  M. A. Fernandez and Elizabeth A. Barnes
  1.06
• CoNOAir: A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities (2025)
  Sanchit Bedi (1) et al.
  1.00
• Accelerating Flood Warnings by 10 Hours: The Power of River Network Topology in AI-enhanced Flood Forecasting (2024)
  Hongjun Wang et al.
  0.89
• Data-driven rainfall prediction at a regional scale: a case study with Ghana (2024)
  Indrajit Kalita et al.
  0.89
• Reconstructing East Asian Temperatures from 1368 to 1911 Using Historical Documents, Climate Models, and Data Assimilation (2024)
  Eric Sun et al.
  0.89
• Time Distributed Deep Learning Models for Purely Exogenous Forecasting: Application to Water Table Depth Prediction using Weather Image Time Series (2024)
  Matteo Salis et al.
  0.83
• Hierarchically Disentangled Recurrent Network for Factorizing System Dynamics of Multi-scale Systems: An application on Hydrological Systems (2024)
  Rahul Ghosh et al.
  0.72
• WaveCastNet: Rapid Wavefield Forecasting for Earthquake Early Warning via Deep Sequence to Sequence Learning (2024)
  Dongwei Lyu et al.
  0.61
• Prolongation of SMAP to Spatio-temporally Seamless Coverage of Continental US Using a Deep Learning Neural Network (2017)
  Kuai Fang et al.
  —
• A History Matching Approach for Calibrating Hydrological Models (2017)
  Natalia V. Bhattacharjee and Pritam Ranjan and Abhyuday Mandal and Ernest W. Tollner
  —
• Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for Day and Night Air Pollution in Silesia Region: A Critical Overview (2017)
  Daniel Kosiorowski et al.
  —
• Forecasting Crime with Deep Learning (2018)
  Alexander Stec and Diego Klabjan
  —
• Using Deep Learning to Extend the Range of Air-Pollution Monitoring and Forecasting (2018)
  Philipp Haehnel et al.
  —
• Ionospheric activity prediction using convolutional recurrent neural networks (2018)
  Alexandre Boulch and No\"elie Cherrier and Thibaut Castaings
  —
• DeepCSO: Forecasting of Combined Sewer Overflow at a Citywide Level using Multi-task Deep Learning (2018)
  Duo Zhang et al.
  —
• Deep Air Quality Forecasting Using Hybrid Deep Learning Framework (2018)
  Shengdong Du et al.
  —
• Global Fire Season Severity Analysis and Forecasting (2019)
  Leonardo N. Ferreira and Didier A. Vega-Oliveros and Liang Zhao and Manoel F. Cardoso and Elbert E. N. Macau
  —
• Forecasting Drought Using Multilayer Perceptron Artificial Neural Network Model (2019)
  Zulifqar Ali et al.
  —
• A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting (2019)
  Pei Du et al.
  —
• Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms (2019)
  Hristos Tyralis et al.
  —
• Comparison of Deep learning models on time series forecasting : a case study of Dissolved Oxygen Prediction (2019)
  Hongqian Qin
  —
• Forecasting vegetation condition for drought early warning systems in pastoral communities in Kenya (2019)
  Adam B. Barrett et al.
  —
• Hydrological time series forecasting using simple combinations: Big data testing and investigations on one-year ahead river flow predictability (2020)
  Georgia Papacharalampous et al.
  —
• Stream-Flow Forecasting of Small Rivers Based on LSTM (2020)
  Youchuan Hu et al.
  —
• Forecasting Corn Yield with Machine Learning Ensembles (2020)
  Mohsen Shahhosseini et al.
  —
• Prediction of short and long-term droughts using artificial neural networks and hydro-meteorological variables (2020)
  Yousef Hassanzadeh et al.
  —
• PlumeNet: Large-Scale Air Quality Forecasting Using A Convolutional LSTM Network (2020)
  Antoine All\'eon et al.
  —
• Computational Model for Urban Growth Using Socioeconomic Latent Parameters (2020)
  Piyush Yadav et al.
  —