# weathernext | Google DeepMind | Knowledge Base | Instagit

GitHub Stars: 7.3k

Repository: https://github.com/google-deepmind/weathernext

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## Articles

### [WeatherNext Performance Benchmarks: RMSE, CRPS, and Hardware Comparisons Explained](/google-deepmind/weathernext/what-are-the-performance-benchmarks-of-weathernext)

Discover WeatherNext performance benchmarks including RMSE and CRPS. See hardware comparisons and learn how WeatherNext achieves state-of-the-art weather forecasting. Get unbiased results.

- Tags: performance
- Published: 2026-08-16

### [Is WeatherNext Suitable for Real‑Time Forecasting? Architecture Constraints and Practical Limits](/google-deepmind/weathernext/is-weathernext-suitable-for-real-time-forecasting)

Discover if WeatherNext supports real-time forecasting. Explore its architecture and practical limits for operational weather predictions. Learn about its update cycles.

- Tags: architecture
- Published: 2026-08-16

### [How to Submit Bug Reports for WeatherNext: A Complete Guide](/google-deepmind/weathernext/how-to-submit-bug-reports-for-weathernext)

Learn how to submit bug reports for WeatherNext effectively. Follow our guide for clear instructions on using GitHub Issues and email for detailed feedback and issue resolution.

- Tags: how-to-guide
- Published: 2026-08-16

### [WeatherNext Use Cases: 5 Real-World Applications for AI Weather Forecasting](/google-deepmind/weathernext/what-are-the-typical-use-cases-for-weathernext)

Explore 5 real-world use cases for WeatherNext AI weather forecasting. Discover applications in medium-range forecasting, tropical cyclone tracking, research, and more.

- Tags: use-cases
- Published: 2026-08-16

### [How to Access WeatherNext Datasets: 4 Methods for Forecasts, Weights, and Training Data](/google-deepmind/weathernext/how-to-access-weathernext-datasets)

Access WeatherNext datasets for forecasts, weights, and training data using Google Cloud Storage, OpenMeteo API, or WeatherLab. No authentication needed for public buckets.

- Tags: how-to-guide
- Published: 2026-08-16

### [What Are the Limitations of WeatherNext? A Deep Dive into Google's Global Weather Model Constraints](/google-deepmind/weathernext/what-are-the-limitations-of-weathernext)

Explore WeatherNext limitations including resolution constraints, hardware requirements, and research-grade status. Understand its global weather model challenges for informed use.

- Tags: deep-dive
- Published: 2026-08-16

### [How to Reproduce WeatherNext Results: A Complete Step-by-Step Guide](/google-deepmind/weathernext/how-to-reproduce-weathernext-results)

Reproduce WeatherNext results with this step-by-step guide. Download weights, install the package, prepare data, and run the autoregressive rollout function for accurate weather forecasting.

- Tags: how-to-guide
- Published: 2026-08-16

### [WeatherNext Computational Cost: TPU & GPU Pricing Breakdown for Google DeepMind's GenCast Model](/google-deepmind/weathernext/what-is-the-computational-cost-of-running-weathernext)

Discover the computational cost of Google DeepMind's WeatherNext model. Get a TPU and GPU pricing breakdown for GenCast and understand the cost of running forecasts.

- Tags: performance
- Published: 2026-08-16

### [How WeatherNext Handles Different Geographical Regions: Geodesic-Aware Cyclone Tracking Across the Globe](/google-deepmind/weathernext/how-does-weathernext-handle-different-geographical-regions)

Discover how WeatherNext achieves geodesic-aware cyclone tracking globally. Learn about its methods for handling different geographical regions and ensuring consistent performance worldwide.

- Tags: deep-dive
- Published: 2026-08-16

### [WeatherNext Pre-Trained Models: Complete Guide to GraphCast and GenCast Checkpoints](/google-deepmind/weathernext/what-are-the-pre-trained-models-available-for-weathernext)

Explore WeatherNext's pre-trained GraphCast and GenCast models. Discover their capabilities, resolutions, and training data to enhance your weather forecasting.

- Tags: getting-started
- Published: 2026-08-16

### [Where to Find WeatherNext Documentation: Complete Guide to Google's AI Weather Models](/google-deepmind/weathernext/where-to-find-weathernext-documentation)

Find WeatherNext documentation within the google-deepmind/weathernext GitHub repo. Explore the README, Colab notebooks, and code comments for a complete guide to Google's AI weather models.

- Tags: getting-started
- Published: 2026-08-16

### [How to Contribute to WeatherNext: A Complete Guide to Open-Source Contributions](/google-deepmind/weathernext/how-to-contribute-to-weathernext)

Learn how to contribute to WeatherNext with this guide. Sign the CLA, fork the repo, follow coding standards, run tests, and submit your pull request to the google-deepmind/weathernext project.

- Tags: how-to-guide
- Published: 2026-08-16

### [What License Does WeatherNext Use? Apache 2.0 Explained](/google-deepmind/weathernext/what-is-the-license-for-weathernext)

Discover the Apache 2.0 license for WeatherNext. Understand its open-source terms for using, modifying, and distributing the code freely.

- Tags: getting-started
- Published: 2026-08-16

### [Can WeatherNext Be Integrated With Other Libraries? Integration Guide for Scientific Python Workflows](/google-deepmind/weathernext/can-weathernext-be-integrated-with-other-libraries)

Integrate WeatherNext with xarray JAX pandas and scientific Python. Learn how WeatherNexts native data structures enable seamless integration for your workflows.

- Tags: integration-guide
- Published: 2026-08-16

### [WeatherNext Input Requirements: Complete Guide to Data Format, Resolution, and Variables](/google-deepmind/weathernext/what-are-the-input-requirements-for-weathernext)

Understand WeatherNext input requirements. Learn about Zarr datasets, ERA5/HRES fields, resolution, and variables needed for optimal model performance.

- Tags: tutorial
- Published: 2026-08-16

### [How to Use WeatherNext for Forecasting: A Complete Guide to DeepMind's Weather AI](/google-deepmind/weathernext/how-to-use-weathernext-for-forecasting)

Learn to use WeatherNext for forecasting with this guide. Discover how DeepMind's AI generates multi-day global weather predictions. Install, load data, and run forecasts easily.

- Tags: how-to-guide
- Published: 2026-08-16

### [WeatherNext Evaluation Metrics: CRPS, MAE, and MAD Explained](/google-deepmind/weathernext/what-are-the-evaluation-metrics-for-weathernext)

Understand WeatherNext evaluation metrics like CRPS, MAE, and MAD. Learn how these metrics assess probabilistic forecast quality for improved weather predictions.

- Tags: deep-dive
- Published: 2026-08-16

### [How to Fine-Tune WeatherNext Models: A Complete Guide for Custom Weather Forecasting](/google-deepmind/weathernext/how-to-fine-tune-weathernext)

Learn how to fine-tune WeatherNext models with this guide. Load checkpoints, prepare data, and perform gradient updates using JAX and Optax for custom weather forecasting.

- Tags: how-to-guide
- Published: 2026-08-16

### [How to Train a WeatherNext Model: A Complete Guide to Data-Driven Weather Forecasting](/google-deepmind/weathernext/how-to-train-a-weathernext-model)

Learn to train a WeatherNext model with our complete guide. Prepare data, build architecture, and run a JAX training loop for advanced weather forecasting.

- Tags: how-to-guide
- Published: 2026-08-16

### [WeatherNext Data Format Explained: A Guide to the Structured Array Containers](/google-deepmind/weathernext/what-is-the-weathernext-data-format)

Explore the WeatherNext data format a typed tree-structured collection of arrays that unifies grids point clouds and meshes for JAX compatibility.

- Tags: deep-dive
- Published: 2026-08-16

### [How to Run WeatherNext Locally: A Complete Setup and Inference Guide](/google-deepmind/weathernext/how-to-run-weathernext-locally)

Run WeatherNext locally with this complete setup and inference guide. Discover the JAX/Flax framework for powerful weather forecasting via a simple command.

- Tags: how-to-guide
- Published: 2026-08-16

### [WeatherNext Dependencies: Complete Installation Guide for Google's AI Weather Model](/google-deepmind/weathernext/what-are-the-dependencies-for-weathernext)

Install Google's WeatherNext AI model. Learn about essential dependencies like JAX, Haiku, Xarray, and Dask. Get your complete installation guide now.

- Tags: how-to-guide
- Published: 2026-08-16

### [How to Install WeatherNext: Complete Setup Guide for DeepMind's Weather Prediction Model](/google-deepmind/weathernext/how-to-install-weathernext)

Install WeatherNext, DeepMinds powerful weather prediction model, easily via pip or local clone. Get started with this complete setup guide.

- Tags: getting-started
- Published: 2026-08-16

### [How to Run Ensemble Predictions with Multiple Model Checkpoints in WeatherNext](/google-deepmind/weathernext/how-to-run-ensemble-predictions-multiple-model-checkpoints)

Learn to run ensemble predictions with multiple model checkpoints in WeatherNext. Load checkpoints, stack models, broadcast data, and aggregate forecasts for enhanced accuracy.

- Tags: how-to-guide
- Published: 2026-08-12

### [WeatherNext GenCast Performance: H100 GPU vs TPU v5p Benchmarks and Throughput Analysis](/google-deepmind/weathernext/performance-benchmarks-throughput-h100-vs-tpu-v5p)

Analyze H100 vs TPU v5p performance for WeatherNext GenCast. Discover TPU v5p delivers 3x higher inference throughput than H100 GPUs with minimal forecast skill degradation.

- Tags: performance
- Published: 2026-08-12

### [How `extra_dims_to_split` in `xarray_dense` Controls Weight Sharding in WeatherNeXt](/google-deepmind/weathernext/what-does-extra-dims-to-split-xarray-dense-mean-weight-sharding)

Understand how extra_dims_to_split in xarray_dense controls weight sharding in WeatherNeXt. Learn to shard parameters across dimensions like time and pressure levels for efficient model training.

- Tags: deep-dive
- Published: 2026-08-12

### [How to Configure Per-Variable Activation Functions in WeatherNext's Output Layer](/google-deepmind/weathernext/how-to-configure-per-variable-activation-functions-output-layer)

Learn how to configure per-variable activation functions in WeatherNext's output layer. Apply distinct functions to individual forecast variables using the per_var_activation_fns dictionary.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Fine-Tune WeatherNext on Custom Datasets with Different Variables](/google-deepmind/weathernext/how-to-fine-tune-weathernext-custom-datasets-different-variables)

Learn how to fine-tune WeatherNext on custom datasets. Extend variables, define new tasks, and train using JAX and Optax for advanced weather forecasting.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Visualize xarray Outputs with Temperature, Wind, and Geopotential Fields in WeatherNext](/google-deepmind/weathernext/how-to-visualize-xarray-outputs-temperature-wind-geopotential)

Learn to visualize xarray outputs for temperature wind and geopotential fields using WeatherNext and Matplotlib. Explore atmospheric forecasts effectively.

- Tags: tutorial
- Published: 2026-08-12

### [How to Use `remat` Options for Memory Optimization in WeatherNext: A Complete Guide](/google-deepmind/weathernext/how-to-use-remat-options-memory-optimization)

Optimize WeatherNext memory with remat options. Learn to set remat_grid_to_mesh_gnn, remat_mesh_gnn, and remat_mesh_to_grid_gnn to True for efficient training.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Use the Checkpoint Module for Saving and Loading Models in WeatherNext](/google-deepmind/weathernext/how-to-use-checkpoint-module-saving-loading-models)

Learn to save and load WeatherNext models using the checkpoint module. Easily serialize with dump() and restore with load() for efficient model management.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Implement Custom Loss Functions in the WeatherNext Training Pipeline](/google-deepmind/weathernext/how-to-implement-custom-loss-functions-training-pipeline)

Learn to implement custom loss functions in WeatherNext. Create a callable or subclass a predictor to easily integrate your custom loss for improved model training.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Customize PointsMeshUpdateConstructor for Different Data Modalities in WeatherNext](/google-deepmind/weathernext/how-to-customize-pointsmeshupdateconstructor-different-data-modalities)

Customize PointsMeshUpdateConstructor for diverse data modalities in WeatherNext. Inherit SpatialData, configure connectivity, and tune hyperparameters for optimal results.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Configure Mesh Padding for Spatial Axis Operations in WeatherNext](/google-deepmind/weathernext/how-to-configure-mesh-padding-spatial-axis-operations)

Learn to configure mesh padding for spatial axis operations in WeatherNext. Utilize padding utilities for efficient graph edge management and balanced execution.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Initialize WeatherNext Models from HRES Operational Data vs ERA5 Reanalysis](/google-deepmind/weathernext/how-to-initialize-models-hres-operational-data-vs-era5-reanalysis)

Learn to initialize WeatherNext models using HRES operational data or ERA5 reanalysis. Understand the differences in data loading, normalization, and checkpoints for optimal model setup.

- Tags: how-to-guide
- Published: 2026-08-12

### [GraphCast vs GenCast: Deterministic and Probabilistic Weather Forecasting Architectures in DeepMind's WeatherNext](/google-deepmind/weathernext/differences-deterministic-graphcast-probabilistic-gencast)

Explore GraphCast's deterministic weather forecasts and GenCast's probabilistic ensembles. Understand the architectural differences of these deep learning models from Google DeepMind's WeatherNext.

- Tags: deep-dive
- Published: 2026-08-12

### [Direct Cyclone Tracker Implementation and Track Extraction in WeatherNext](/google-deepmind/weathernext/how-direct-cyclone-tracker-implemented-track-extracted)

Learn how to implement the Direct Tracker in WeatherNext to extract cyclone tracks. Explore momentum-based prediction and probability-weighted refinement for accurate results.

- Tags: implementation
- Published: 2026-08-12

### [WeatherNext Memory Requirements and VRAM Usage: Full vs. Mini Models Compared](/google-deepmind/weathernext/memory-requirements-vram-usage-full-vs-mini-models)

Discover WeatherNext memory requirements for full vs Mini models. Learn VRAM needs for H100 and P100 GPUs, plus system RAM usage to optimize your setup.

- Tags: performance
- Published: 2026-08-12

### [How Norm Conditioning Features Improve Weather Forecast Accuracy in WeatherNext](/google-deepmind/weathernext/how-norm-conditioning-features-improve-forecast-accuracy)

Discover how norm conditioning features boost weather forecast accuracy in WeatherNext. Learn how normalized scalar context enhances climate regime adaptation for more precise predictions.

- Tags: deep-dive
- Published: 2026-08-12

### [How to Configure Sharding for Multi-TPU Training with JAX Device Meshes in WeatherNext](/google-deepmind/weathernext/how-to-configure-sharding-multi-tpu-training-jax-device-meshes)

Learn to configure JAX device meshes for multi-TPU training in WeatherNext. Discover how to declaratively partition tensors across TPU cores using PartitionSpec for efficient distributed computation.

- Tags: how-to-guide
- Published: 2026-08-12

### [Supported Input and Output Variables in WeatherNext's Data Modalities](/google-deepmind/weathernext/supported-input-output-variables-data-modalities)

Explore WeatherNext's supported input and output variables in data_modalities. Standardize data with five input and seven output properties across all spatial and non-spatial types.

- Tags: api-reference
- Published: 2026-08-12

### [How the Icosahedral Mesh GNN Processes Atmospheric Data in WeatherNext](/google-deepmind/weathernext/how-icosahedral-mesh-gnn-processes-atmospheric-data)

Learn how the icosahedral mesh GNN in WeatherNext processes atmospheric data using a triangular mesh graph and a typed message-passing neural network for accurate weather pattern learning.

- Tags: internals
- Published: 2026-08-12

### [WeatherNext2 vs WeatherNext Cyclones: Key Differences in Model Checkpoints Explained](/google-deepmind/weathernext/differences-weathernext2-vs-weathernext-cyclones-model-checkpoints)

Explore WeatherNext2 vs WeatherNext Cyclones model checkpoints. Discover key differences in their transformer backbones and cyclone-specific forecasting capabilities for tropical weather.

- Tags: deep-dive
- Published: 2026-08-12

### [How to Load Pre-Trained Model Weights from a Google Cloud Storage Bucket in WeatherNext](/google-deepmind/weathernext/how-to-load-pre-trained-model-weights-google-cloud-bucket)

Learn how to load pre-trained WeatherNext model weights from a Google Cloud Storage bucket using tfio gfile.Reconstruct your model parameters efficiently and speed up your development.

- Tags: how-to-guide
- Published: 2026-08-12

### [Understanding the Autoregressive Rollout Process and PredictorFn Protocol in WeatherNext](/google-deepmind/weathernext/what-is-autoregressive-rollout-process-predictorfn-protocol)

Explore the autoregressive rollout process in WeatherNext for multi-step forecasts. Learn how PredictorFn protocol and the Predictor wrapper enable iterative predictions using past outputs as new inputs.

- Tags: deep-dive
- Published: 2026-08-12

### [How to Switch Between TPU and GPU Attention in WeatherNext 2](/google-deepmind/weathernext/how-to-switch-between-tpu-and-gpu-attention-implementations)

Learn how to switch between TPU and GPU attention in WeatherNext 2 by setting the attention_type field to splash_mha mha or triblockdiag_mha for optimized performance.

- Tags: how-to-guide
- Published: 2026-08-12

### [How to Configure FGN Architecture with `mesh_num_splits` in WeatherNext: A Complete Guide](/google-deepmind/weathernext/how-to-configure-fgn-architecture-with-mesh-num-splits)

Configure FGN architecture with mesh_num_splits in WeatherNext. Learn how this parameter controls mesh subdivision and FGN spatial resolution in our complete guide.

- Tags: how-to-guide
- Published: 2026-08-12

### [WeatherNext API Documentation: A Complete Guide to Public Endpoints and Python Interfaces](/google-deepmind/weathernext/where-to-find-weathernext-api-documentation)

Access comprehensive WeatherNext API documentation for public endpoints and Python interfaces. Explore the OpenMeteo WeatherNext API and Google Developers Guide for detailed insights.

- Tags: api-reference
- Published: 2026-08-10

### [How WeatherNext Compares to Other Weather Prediction Models: Architecture and Performance Analysis](/google-deepmind/weathernext/how-weathernext-compares-to-other-weather-prediction-models)

Discover how WeatherNext models outperform traditional NWP systems in speed and accuracy. Explore graph neural networks and diffusion ensembles for superior weather prediction.

- Tags: architecture
- Published: 2026-08-10

### [How to Integrate WeatherNext into Your Own Applications: A Developer's Guide](/google-deepmind/weathernext/how-to-integrate-weathernext-into-own-applications)

Learn how to integrate WeatherNext into your applications using the unified Predictor API. This guide simplifies JAX model complexity and supports GraphCast and GenCast models.

- Tags: how-to-guide
- Published: 2026-08-10

### [WeatherNext Future Development Plans: Roadmap for AI Weather Forecasting](/google-deepmind/weathernext/what-are-future-development-plans-for-weathernext)

Explore WeatherNext future development plans including AI weather forecasting, higher-resolution models, unified APIs, and enhanced cyclone tracking. See the roadmap.

- Tags: architecture
- Published: 2026-08-10

### [How WeatherNext Handles Different Geographical Regions: Technical Deep Dive](/google-deepmind/weathernext/how-weathernext-handles-geographical-regions)

Discover how WeatherNext dynamically adapts to diverse geographical regions. Learn about its innovative sub-grid selection and geodesic bounding boxes for accurate global weather forecasting.

- Tags: deep-dive
- Published: 2026-08-10

### [What Are the Limitations of WeatherNext Predictions? A Technical Deep Dive](/google-deepmind/weathernext/what-are-weathernext-prediction-limitations)

Explore the limitations of WeatherNext predictions including their 10-day range 0.25° resolution and hardware needs. Understand the constraints of this advanced weather forecasting model.

- Tags: deep-dive
- Published: 2026-08-10

### [How to Get Support for WeatherNext: Official Channels and Best Practices](/google-deepmind/weathernext/how-to-get-support-for-weathernext)

Get help for WeatherNext by emailing weathernext@google.com, opening a GitHub issue, or exploring the Colab demo and README. Find fast support for your WeatherNext project.

- Tags: getting-started
- Published: 2026-08-10

### [What License Does WeatherNext Use? Understanding Google DeepMind's Weather Forecasting License](/google-deepmind/weathernext/what-is-weathernext-license)

Discover the Apache License 2.0 for Google DeepMind's WeatherNext. Learn about its permissive terms for commercial use, modification, and distribution.

- Tags: licensing
- Published: 2026-08-10

### [How to Fine-Tune the WeatherNext Model: A Complete Guide for GraphCast and GenCast](/google-deepmind/weathernext/how-to-fine-tune-weathernext-model)

Learn how to fine-tune WeatherNext models like GraphCast and GenCast. Adapt the data pipeline and resume training on your custom dataset for improved weather forecasting.

- Tags: how-to-guide
- Published: 2026-08-10

### [WeatherNext Example Notebooks: Complete Guide to Running the Official Demos](/google-deepmind/weathernext/are-there-example-notebooks-for-weathernext)

Explore WeatherNext example notebooks to run official demos of GraphCast, GenCast, and cyclone tracking. Get started with these end-to-end workflow guides.

- Tags: getting-started
- Published: 2026-08-10

### [What Programming Languages Are Used in WeatherNext? A Deep Dive into the Google DeepMind Codebase](/google-deepmind/weathernext/what-programming-languages-are-used-in-weathernext)

Discover the programming languages powering Google DeepMind's WeatherNext. Explore Python, JAX, JSON, and Markdown's roles in this advanced weather forecasting system.

- Tags: deep-dive
- Published: 2026-08-10

### [How to Visualize WeatherNext Predictions: A Complete Guide with Code Examples](/google-deepmind/weathernext/how-to-visualize-weathernext-predictions)

Visualize WeatherNext predictions using xarray.plot, matplotlib, or Cartopy. This guide provides code examples for clear weather data visualization.

- Tags: how-to-guide
- Published: 2026-08-10

### [What Data Does WeatherNext Use for Training? ERA5, HRES, and IBTrACS Explained](/google-deepmind/weathernext/what-data-does-weathernext-use-for-training)

Discover the diverse datasets powering WeatherNext. Learn how ERA5, HRES, and IBTrACS data train advanced weather prediction models for superior accuracy.

- Tags: deep-dive
- Published: 2026-08-10

### [Core Components of the WeatherNext Project: Architecture and Implementation](/google-deepmind/weathernext/what-are-weathernext-core-components)

Discover the core components of the WeatherNext project, including GraphCast, GenCast, and WN2. Explore its architecture, implementation, and modular utilities.

- Tags: architecture
- Published: 2026-08-10

### [How to Set Up the WeatherNext Environment for Development: Complete Setup Guide](/google-deepmind/weathernext/how-to-setup-weathernext-development-environment)

Set up the WeatherNext development environment efficiently. Follow our complete guide to clone the repo install dependencies and verify your setup for Google DeepMind's weather forecasting model.

- Tags: getting-started
- Published: 2026-08-10

### [What Is the google-deepmind/weathernext Repository? A Deep Dive into AI Weather Forecasting](/google-deepmind/weathernext/what-is-google-deepmind-weathernext-repository)

Explore the google-deepmind/weathernext repository, an open-source platform for advanced AI weather forecasting. Access WeatherNext 2, GraphCast, GenCast models, checkpoints, and inference tools for reproducible research.

- Tags: deep-dive
- Published: 2026-08-10