Weather Forecasting

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

5 leaderboard tables shown for this task, 5 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

16 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 188 papers with code (420 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
  13 Jun 2015 23 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 2 pointer-only (licence)
  The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time.
• GraphCast: Learning skillful medium-range global weather forecasting
  24 Dec 2022 11 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  Global medium-range weather forecasting is critical to decision-making across many social and economic domains.
• Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks
  16 Feb 2021 6 repositories listed
  Recurrent graph convolutional neural networks are highly effective machine learning techniques for spatiotemporal signal processing.
• WeatherBench: A benchmark dataset for data-driven weather forecasting
  2 Feb 2020 6 repositories listed
  Data-driven approaches, most prominently deep learning, have become powerful tools for prediction in many domains.
• FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
  22 Feb 2022 5 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  FourCastNet accurately forecasts high-resolution, fast-timescale variables such as the surface wind speed, precipitation, and atmospheric water vapor.
• Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
  7 Jun 2024 4 repositories listed Syntology ran 8 of 15 samples · 7 unverified
  While most current machine learning models focus on deterministic forecasts, accurately capturing the uncertainty in the chaotic weather system calls for probabilistic modeling.
• Graph-based Neural Weather Prediction for Limited Area Modeling
  29 Sep 2023 4 repositories listed
  The rise of accurate machine learning methods for weather forecasting is creating radical new possibilities for modeling the atmosphere.
• NGBoost: Natural Gradient Boosting for Probabilistic Prediction
  8 Oct 2019 4 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  NGBoost generalizes gradient boosting to probabilistic regression by treating the parameters of the conditional distribution as targets for a multiparameter boosting algorithm.
• Verified Uncertainty Calibration
  23 Sep 2019 4 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  In these experiments, we also estimate the calibration error and ECE more accurately than the commonly used plugin estimators.
• GenCast: Diffusion-based ensemble forecasting for medium-range weather
  25 Dec 2023 3 repositories listed Syntology ran 9 of 9 samples · 0 unverified
  Weather forecasts are fundamentally uncertain, so predicting the range of probable weather scenarios is crucial for important decisions, from warning the public about hazardous weather, to planning renewable energy use.
• Neural General Circulation Models for Weather and Climate
  13 Nov 2023 3 repositories listed Syntology ran 1 of 10 samples · 9 unverified
  Here we present the first GCM that combines a differentiable solver for atmospheric dynamics with ML components, and show that it can generate forecasts of deterministic weather, ensemble weather and climate on par with…
• TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
  5 Oct 2022 3 repositories listed
  TimesBlock can discover the multi-periodicity adaptively and extract the complex temporal variations from transformed 2D tensors by a parameter-efficient inception block.
• Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
  15 Jul 2021 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  However, many tasks of practical interest have different modalities, such as tabular data, audio, text, or sensor data, which offer significant challenges involving regression and discrete or continuous structured…
• PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
  17 Mar 2021 3 repositories listed
  This paper models these structures by presenting PredRNN, a new recurrent network, in which a pair of memory cells are explicitly decoupled, operate in nearly independent transition manners, and finally form unified…
• Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
  6 Jul 2020 3 repositories listed Syntology ran 5 of 7 samples · 2 unverified · 1 pointer-only (licence)
  We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.
• Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction
  3 Mar 2020 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  Leveraging physical knowledge described by partial differential equations (PDEs) is an appealing way to improve unsupervised video prediction methods.
• Eidetic 3D LSTM: A Model for Video Prediction and Beyond
  1 May 2019 3 repositories listed
  We first evaluate the E3D-LSTM network on widely-used future video prediction datasets and achieve the state-of-the-art performance.
• Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
  22 Dec 2018 3 repositories listed
  We cast the weather forecasting problem as an end-to-end deep learning problem and solve it by proposing a novel negative log-likelihood error (NLE) loss function.
• Dynamical errors in machine learning forecasts
  15 Apr 2025 2 repositories listed
  In this work, we investigate the relationship between standard forecasting error metrics, such as MAE and MSE, and the dynamical properties of the underlying system.
• WeatherMesh-3: Fast and accurate operational global weather forecasting
  28 Mar 2025 2 repositories listed
  We present WeatherMesh-3 (WM-3), an operational transformer-based global weather forecasting system that improves the state of the art in both accuracy and computational efficiency.
• DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
  14 Dec 2024 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  First, we design a Temporal Clustering Module (TCM) that clusters time series into fine-grained distributions to handle heterogeneous temporal patterns.
• Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators
  6 Aug 2024 2 repositories listed Syntology ran 5 of 6 samples · 1 unverified · 4 pointer-only (licence)
  Using the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) as a baseline, we develop an evaluation pipeline composed of mean, spectral, and extreme diagnostics.
• Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators
  2 Aug 2024 2 repositories listed
  HENS has two primary applications: (1) as a large dataset with which to study the statistics and drivers of extreme weather and (2) as a weather forecasting system.
• TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning
  21 Jun 2024 2 repositories listed Syntology ran 21 of 22 samples · 1 unverified
  To fill this gap, we propose TorchSpatial, a learning framework and benchmark for location (point) encoding, which is one of the most fundamental data types of spatial representation learning.
• TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
  23 May 2024 2 repositories listed
  Going beyond the mainstream paradigms of plain decomposition and multiperiodicity analysis, we analyze temporal variations in a novel view of multiscale-mixing, which is based on an intuitive but important observation…
• SST: Multi-Scale Hybrid Mamba-Transformer Experts for Long-Short Range Time Series Forecasting
  23 Apr 2024 2 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  To meet the objectives, we propose a multi-scale hybrid Mamba-Transformer experts model State Space Transformer (SST).
• FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting
  28 Jan 2024 2 repositories listed
  Therefore, building a kilometer-scale global forecast model is a persistent pursuit in the meteorology domain.
• FuXi: A cascade machine learning forecasting system for 15-day global weather forecast
  22 Jun 2023 2 repositories listed Syntology ran 3 of 6 samples · 3 unverified · 1 pointer-only (licence)
  Over the past few years, due to the rapid development of machine learning (ML) models for weather forecasting, state-of-the-art ML models have shown superior performance compared to the European Centre for Medium-Range…
• OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
  20 Jun 2023 2 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  Spatio-temporal predictive learning is a learning paradigm that enables models to learn spatial and temporal patterns by predicting future frames from given past frames in an unsupervised manner.
• Federated Prompt Learning for Weather Foundation Models on Devices
  23 May 2023 2 repositories listed
  On-device intelligence for weather forecasting uses local deep learning models to analyze weather patterns without centralized cloud computing, holds significance for supporting human activates.

Syntology lines on 17 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.